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  • 1.
    Agullo, Luis
    et al.
    Univ Vic Cent Univ Catalonia UVIC UCC, Dept Syst Biol, U Sci Tech, Sagrada Familia 7, Vic 08500, Spain..
    Buch, Ignasi
    Hosp Del Mar Med Res Inst IMIM, Computat Biophys Lab, Barcelona 08003, Spain..
    Gutierrez-de-Teran, Hugo
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Garcia-Dorado, David
    Vall DHebron Res Inst VHIR, Cardiocirculatory Pathol Grp, Barcelona 08035, Spain..
    Villa-Freixa, Jordi
    Univ Vic Cent Univ Catalonia UVIC UCC, Dept Syst Biol, U Sci Tech, Sagrada Familia 7, Vic 08500, Spain..
    Computational exploration of the binding mode of heme-dependent stimulators into the active catalytic domain of soluble guanylate cyclase2016In: Proteins: Structure, Function, and Bioinformatics, ISSN 0887-3585, E-ISSN 1097-0134, Vol. 84, no 10, p. 1534-1548Article in journal (Refereed)
    Abstract [en]

    Soluble guanylate cyclase (sGC), the main target of nitric oxide (NO), has been proven to have a significant role in coronary artery disease, pulmonary hypertension, erectile dysfunction, and myocardial infarction. One of its agonists, BAY 41-2272 (Riociguat), has been recently approved for treatment of pulmonary arterial hypertension (PHA), while some others are in clinical phases of development. However, the location of the binding sites for the two known types of agonists, heme-dependent stimulators and heme-independent activators, is a matter of debate, particularly for the first group where both a location on the regulatory (H-NOX) and on the catalytic domain have been suggested by different authors. Here, we address its potential location on the catalytic domain, the unique well characterized at the structural level, by an in silico approach. Homology models of the catalytic domain of sGC in inactive or active conformations were constructed using the structure of previously described crystals of the catalytic domains of inactive sGCs (2WZ1, 3ET6) and of active adenylate cyclase (1CJU). Each model was submitted to six independent molecular dynamics simulations of about 1 s. Docking of YC-1, a classic heme-dependent stimulator, to all frames of representative trajectories of inactive and active conformations, followed by calculation of absolute binding free energies with the linear interaction energy (LIE) method, revealed a potential high-affinity binding site on the active structure. The site, located between the pseudo-symmetric and the catalytic site just over the loop (2)-(3), does not overlap with the forskolin binding site on adenylate cyclases.

  • 2.
    Aken, Bronwen L.
    et al.
    European Bioinformat Inst Wellcome Genome Campus, European Mol Biol Lab, Cambridge CB10 1SD, England.;Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England..
    Ayling, Sarah
    Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England.;Genome Anal Ctr, Norwich Res Pk, Norwich NR4 7UH, Norfolk, England..
    Barrell, Daniel
    European Bioinformat Inst Wellcome Genome Campus, European Mol Biol Lab, Cambridge CB10 1SD, England.;Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England.;Eagle Genom Ltd, Babraham Res Campus, Cambridge CB22 3AT, England..
    Clarke, Laura
    Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England.;European Bioinformat Inst, European Mol Biol Lab, Wellcome Genome Campus, Cambridge CB10 1SD, England..
    Curwen, Valery
    Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England..
    Fairley, Susan
    Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England.;European Bioinformat Inst, European Mol Biol Lab, Wellcome Genome Campus, Cambridge CB10 1SD, England..
    Banet, Julio Fernandez
    Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England.;Pfizer Inc, 10646 Sci Ctr Dr, San Diego, CA 92121 USA..
    Billis, Konstantinos
    European Bioinformat Inst Wellcome Genome Campus, European Mol Biol Lab, Cambridge CB10 1SD, England.;Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England..
    Giron, Carlos Garcia
    European Bioinformat Inst Wellcome Genome Campus, European Mol Biol Lab, Cambridge CB10 1SD, England.;Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England..
    Hourlier, Thibaut
    European Bioinformat Inst Wellcome Genome Campus, European Mol Biol Lab, Cambridge CB10 1SD, England.;Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England..
    Howe, Kevin
    Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England.;European Bioinformat Inst, European Mol Biol Lab, Wellcome Genome Campus, Cambridge CB10 1SD, England..
    Kähäri, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England.
    Kokocinski, Felix
    Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England..
    Martin, Fergal J.
    European Bioinformat Inst Wellcome Genome Campus, European Mol Biol Lab, Cambridge CB10 1SD, England.;Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England..
    Murphy, Daniel N.
    European Bioinformat Inst Wellcome Genome Campus, European Mol Biol Lab, Cambridge CB10 1SD, England.;Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England..
    Nag, Rishi
    European Bioinformat Inst Wellcome Genome Campus, European Mol Biol Lab, Cambridge CB10 1SD, England.;Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England..
    Ruffier, Magali
    Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England.;European Bioinformat Inst, European Mol Biol Lab, Wellcome Genome Campus, Cambridge CB10 1SD, England..
    Schuster, Michael
    European Bioinformat Inst Wellcome Genome Campus, European Mol Biol Lab, Cambridge CB10 1SD, England.;Austrian Acad Sci, CeMM Res Ctr Mol Med, A-1090 Vienna, Austria..
    Tang, Y. Amy
    Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England.;European Bioinformat Inst, European Mol Biol Lab, Wellcome Genome Campus, Cambridge CB10 1SD, England..
    Vogel, Jan-Hinnerk
    Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England.;Genentech Inc, 1 DNAWay, San Francisco, CA 94080 USA..
    White, Simon
    Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England.;Baylor Coll Med, Human Genome Sequencing Ctr, Houston, TX 77030 USA..
    Zadissa, Amonida
    Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England.;European Bioinformat Inst, European Mol Biol Lab, Wellcome Genome Campus, Cambridge CB10 1SD, England..
    Flicek, Paul
    European Bioinformat Inst Wellcome Genome Campus, European Mol Biol Lab, Cambridge CB10 1SD, England.;Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England..
    Searle, Stephen M. J.
    Wellcome Trust Sanger Inst Wellcome Genome Campus, Cambridge CB10 1SA, England..
    The Ensembl gene annotation system2016In: Database: The Journal of Biological Databases and Curation, ISSN 1758-0463, E-ISSN 1758-0463, article id baw093Article in journal (Refereed)
    Abstract [en]

    The Ensembl gene annotation system has been used to annotate over 70 different vertebrate species across a wide range of genome projects. Furthermore, it generates the automatic alignment-based annotation for the human and mouse GENCODE gene sets. The system is based on the alignment of biological sequences, including cDNAs, proteins and RNA-seq reads, to the target genome in order to construct candidate transcript models. Careful assessment and filtering of these candidate transcripts ultimately leads to the final gene set, which is made available on the Ensembl website. Here, we describe the annotation process in detail.

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  • 3.
    Ameur, Adam
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Natl Genom Infrastruct, Sci Life Lab, Stockholm, Sweden..
    Dahlberg, Johan
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Natl Genom Infrastruct, Sci Life Lab, Stockholm, Sweden.
    Olason, Pall
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology. Natl Bioinformat Infrastruct, Sci Life Lab, Stockholm, Sweden..
    Vezzi, Francesco
    Natl Genom Infrastruct, Sci Life Lab, Stockholm, Sweden.;Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Stockholm, Sweden..
    Karlsson, Robert
    Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden..
    Martin, Marcel
    Natl Bioinformat Infrastruct, Sci Life Lab, Stockholm, Sweden.;Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Stockholm, Sweden..
    Viklund, Johan
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Natl Bioinformat Infrastruct, Sci Life Lab, Stockholm, Sweden..
    Kähäri, Andreas
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Natl Bioinformat Infrastruct, Sci Life Lab, Stockholm, Sweden..
    Lundin, Par
    Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Stockholm, Sweden..
    Che, Huiwen
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    Thutkawkorapin, Jessada
    Karolinska Inst, Dept Mol Med & Surg, Stockholm, Sweden..
    Eisfeldt, Jesper
    Karolinska Inst, Dept Mol Med & Surg, Stockholm, Sweden..
    Lampa, Samuel
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Natl Bioinformat Infrastruct, Sci Life Lab, Stockholm, Sweden.
    Dahlberg, Mats
    Natl Bioinformat Infrastruct, Sci Life Lab, Stockholm, Sweden.;Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Stockholm, Sweden..
    Hagberg, Jonas
    Natl Bioinformat Infrastruct, Sci Life Lab, Stockholm, Sweden.;Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Stockholm, Sweden..
    Jareborg, Niclas
    Natl Bioinformat Infrastruct, Sci Life Lab, Stockholm, Sweden.;Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Stockholm, Sweden..
    Liljedahl, Ulrika
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Natl Genom Infrastruct, Sci Life Lab, Stockholm, Sweden.
    Jonasson, Inger
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Natl Genom Infrastruct, Sci Life Lab, Stockholm, Sweden..
    Johansson, Åsa
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.
    Feuk, Lars
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.
    Lundeberg, Joakim
    Natl Genom Infrastruct, Sci Life Lab, Stockholm, Sweden.;Royal Inst Technol, Div Gene Technol, Sch Biotechnol, Sci Life Lab, Stockholm, Sweden..
    Syvänen, Ann-Christine
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular Medicine. Natl Genom Infrastruct, Sci Life Lab, Stockholm, Sweden.
    Lundin, Sverker
    Royal Inst Technol, Div Gene Technol, Sch Biotechnol, Sci Life Lab, Stockholm, Sweden..
    Nilsson, Daniel
    Karolinska Inst, Dept Mol Med & Surg, Stockholm, Sweden..
    Nystedt, Björn
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Evolution. Natl Bioinformat Infrastruct, Sci Life Lab, Stockholm, Sweden..
    Magnusson, Patrik K. E.
    Natl Genom Infrastruct, Sci Life Lab, Stockholm, Sweden.;Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden..
    Gyllensten, Ulf B.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.
    SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population2017In: European Journal of Human Genetics, ISSN 1018-4813, E-ISSN 1476-5438, Vol. 25, no 11, p. 1253-1260Article in journal (Refereed)
    Abstract [en]

    Here we describe the SweGen data set, a comprehensive map of genetic variation in the Swedish population. These data represent a basic resource for clinical genetics laboratories as well as for sequencing-based association studies by providing information on genetic variant frequencies in a cohort that is well matched to national patient cohorts. To select samples for this study, we first examined the genetic structure of the Swedish population using high-density SNP-array data from a nation-wide cohort of over 10 000 Swedish-born individuals included in the Swedish Twin Registry. A total of 1000 individuals, reflecting a cross-section of the population and capturing the main genetic structure, were selected for whole-genome sequencing. Analysis pipelines were developed for automated alignment, variant calling and quality control of the sequencing data. This resulted in a genome-wide collection of aggregated variant frequencies in the Swedish population that we have made available to the scientific community through the website https://swefreq.nbis.se. A total of 29.2 million single-nucleotide variants and 3.8 million indels were detected in the 1000 samples, with 9.9 million of these variants not present in current databases. Each sample contributed with an average of 7199 individual-specific variants. In addition, an average of 8645 larger structural variants (SVs) were detected per individual, and we demonstrate that the population frequencies of these SVs can be used for efficient filtering analyses. Finally, our results show that the genetic diversity within Sweden is substantial compared with the diversity among continental European populations, underscoring the relevance of establishing a local reference data set.

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  • 4.
    Asp, Michaela
    et al.
    KTH Royal Inst Technol, Div Gene Technol, Sci Life Lab, Stockholm, Sweden..
    Salmen, Fredrik
    KTH Royal Inst Technol, Div Gene Technol, Sci Life Lab, Stockholm, Sweden..
    Ståhl, Patrik L.
    Karolinska Inst, Dept Cell & Mol Biol, Stockholm, Sweden..
    Vickovic, Sanja
    KTH Royal Inst Technol, Div Gene Technol, Sci Life Lab, Stockholm, Sweden..
    Felldin, Ulrika
    Karolinska Inst, Dept Mol Med & Surg, Stockholm, Sweden..
    Löfling, Marie
    Karolinska Inst, Dept Mol Med & Surg, Stockholm, Sweden..
    Navarro, Jose Fernandez
    Karolinska Inst, Dept Cell & Mol Biol, Stockholm, Sweden..
    Maaskola, Jonas
    KTH Royal Inst Technol, Div Gene Technol, Sci Life Lab, Stockholm, Sweden..
    Eriksson, Maria J.
    Karolinska Inst, Dept Mol Med & Surg, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Clin Physiol, Stockholm, Sweden..
    Persson, Bengt
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Karolinska Inst, Dept Med Biochem & Biophys, Sci Life Lab, Stockholm, Sweden..
    Corbascio, Matthias
    Karolinska Univ Hosp, Dept Cardiothorac Surg & Anesthesiol, Solna, Sweden..
    Persson, Hans
    Danderyd Hosp, Dept Cardiol, Stockholm, Sweden.;Karolinska Inst, Danderyd Hosp, Dept Clin Sci, Stockholm, Sweden..
    Linde, Cecilia
    Karolinska Inst, Dept Med, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Cardiol, Stockholm, Sweden..
    Lundeberg, Joakim
    KTH Royal Inst Technol, Div Gene Technol, Sci Life Lab, Stockholm, Sweden..
    Spatial detection of fetal marker genes expressed at low level in adult human heart tissue2017In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, article id 12941Article in journal (Refereed)
    Abstract [en]

    Heart failure is a major health problem linked to poor quality of life and high mortality rates. Hence, novel biomarkers, such as fetal marker genes with low expression levels, could potentially differentiate disease states in order to improve therapy. In many studies on heart failure, cardiac biopsies have been analyzed as uniform pieces of tissue with bulk techniques, but this homogenization approach can mask medically relevant phenotypes occurring only in isolated parts of the tissue. This study examines such spatial variations within and between regions of cardiac biopsies. In contrast to standard RNA sequencing, this approach provides a spatially resolved transcriptome- and tissue-wide perspective of the adult human heart, and enables detection of fetal marker genes expressed by minor subpopulations of cells within the tissue. Analysis of patients with heart failure, with preserved ejection fraction, demonstrated spatially divergent expression of fetal genes in cardiac biopsies.

    Download full text (pdf)
    fulltext
  • 5.
    Azuaje, Jhonny
    et al.
    Univ Santiago de Compostela, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain.;Univ Santiago de Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain..
    Jespers, Willem
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Yaziji, Vicente
    Univ Santiago de Compostela, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain.;Univ Santiago de Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain..
    Mallo, Ana
    Univ Santiago de Compostela, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain.;Univ Santiago de Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain..
    Majellaro, Maria
    Univ Santiago de Compostela, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain.;Univ Santiago de Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain..
    Caamano, Olga
    Univ Santiago de Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain..
    Loza, Maria I.
    Univ Santiago de Compostela, Ctr Singular Invest Med Mol & Enfermedades Cronic, Santiago De Compostela 15782, Spain..
    Cadavid, Maria I.
    Univ Santiago de Compostela, Ctr Singular Invest Med Mol & Enfermedades Cronic, Santiago De Compostela 15782, Spain..
    Brea, Jose
    Univ Santiago de Compostela, Ctr Singular Invest Med Mol & Enfermedades Cronic, Santiago De Compostela 15782, Spain..
    Åqvist, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Sotelo, Eddy
    Univ Santiago de Compostela, Ctr Singular Invest Quim Biol & Mat Mol CIQUS, Santiago De Compostela 15782, Spain.;Univ Santiago de Compostela, Fac Farm, Dept Quim Organ, Santiago De Compostela 15782, Spain..
    Gutiérrez-de-Terán, Hugo
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Effect of Nitrogen Atom Substitution in A(3) Adenosine Receptor Binding: N-(4,6-Diarylpyridin-2-yl)acetamides as Potent and Selective Antagonists2017In: Journal of Medicinal Chemistry, ISSN 0022-2623, E-ISSN 1520-4804, Vol. 60, no 17, p. 7502-7511Article in journal (Refereed)
    Abstract [en]

    We report the first family of 2-acetamidopyridines as potent and selective A, adenosine receptor (AR) antagonists. The computer -assisted design was focused on the bioisosteric replacement of the N1 atom by a CH group in a previous series of diarylpyrimidines. Some of the generated 2-acetamidopyridines elicit an antagonistic effect with excellent affinity (K-j < 10 nM) and outstanding selectivity profiles, providing an alternative and simpler chemical scaffold to the parent series of diarylpyrimidines. In addition, using molecular dynamics and free energy perturbation simulations, we elucidate the effect of the second nitrogen of the parent diarylpyrimidines, which is revealed as a stabilizer of a water network in the binding site. The discovery of 2,6-diaryl-2-acetamidopyridines represents a step forward in the search of chemically simple, potent, and selective antagonists for the hA(3)AR, and exemplifies the benefits of a joint theoretical- experimental approach to identify novel hA(3)AR antagonists through succinct and efficient synthetic methodologies.

  • 6.
    Ballante, Flavio
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Rudling, Axel
    Stockholm Univ, Dept Biochem & Biophys, SE-10691 Stockholm, Sweden.
    Zeifman, Alexey
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Uppsala University, Science for Life Laboratory, SciLifeLab. Stockholm Univ, Dept Biochem & Biophys, SE-10691 Stockholm, Sweden.
    Luttens, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Vo, Duc Duy
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Irwin, John J.
    Univ Calif San Francisco, Dept Pharmaceut Chem, Byers Hall,1700 4th St, San Francisco, CA 94158 USA.
    Kihlberg, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - BMC, Organic Chemistry.
    Brea, Jose
    Univ Santiago de Compostela, Ctr Res Mol Med & Chron Dis, Innopharma Screening Platform BioFarma Res Grp, Santiago De Compostela 15706, Spain.
    Isabel Loza, Maria
    Univ Santiago de Compostela, Ctr Res Mol Med & Chron Dis, Innopharma Screening Platform BioFarma Res Grp, Santiago De Compostela 15706, Spain.
    Carlsson, Jens
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Docking Finds GPCR Ligands in Dark Chemical Matter2020In: Journal of Medicinal Chemistry, ISSN 0022-2623, E-ISSN 1520-4804, Vol. 63, no 2, p. 613-620Article in journal (Refereed)
    Abstract [en]

    High-throughput screening has revealed dark chemical matter, a set of drug-like compounds that has never shown bioactivity despite being extensively assayed. If dark molecules are found active at a therapeutic target, their extraordinary selectivity profiles make excellent starting points for drug development. We explored if ligands of therapeutically relevant G-protein-coupled receptors could be discovered by structure-based virtual screening of the dark chemical matter. Molecular docking screens against crystal structures of the A(2A) adenosine and the D-4 dopamine receptors were carried out, and 53 top-ranked molecules were evaluated experimentally. Two ligands of each receptor were discovered, and the most potent had sub-micromolar affinities. Analysis of bioactivity data showed that the ligands lacked activity at hundreds of off-targets, including several that are associated with adverse effects. Our results demonstrate that virtual screening provides an efficient means to mine the dark chemical space, which could contribute to development of drugs with improved safety profiles.

  • 7.
    Baltzer, Nicholas
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Predictive Healthcare: Cervical Cancer Screening Risk Stratification and Genetic Disease Markers2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The use of Machine Learning is rapidly expanding into previously uncharted waters. In the medicine fields there are vast troves of data available from hospitals, biobanks and registries that now are being explored due to the tremendous advancement in computer science and its related hardware. The progress in genomic extraction and analysis has made it possible for any individual to know their own genetic code. Genetic testing has become affordable and can be used as a tool in treatment, discovery, and prognosis of individuals in a wide variety of healthcare settings. This thesis addresses three different approaches to-wards predictive healthcare and disease exploration; first, the exploita-tion of diagnostic data in Nordic screening programmes for the purpose of identifying individuals at high risk of developing cervical cancer so that their screening schedules can be intensified in search of new dis-ease developments. Second, the search for genomic markers that can be used either as additions to diagnostic data for risk predictions or as can-didates for further functional analysis. Third, the development of a Ma-chine Learning pipeline called ||-ROSETTA that can effectively process large datasets in the search for common patterns. Together, this provides a functional approach to predictive healthcare that allows intervention at early stages of disease development resulting in treatments with reduced health consequences at a lower financial burden

    List of papers
    1. Risk stratification in cervical cancer screening by complete screening history: Applying bioinformatics to a general screening population
    Open this publication in new window or tab >>Risk stratification in cervical cancer screening by complete screening history: Applying bioinformatics to a general screening population
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    2017 (English)In: International Journal of Cancer, ISSN 0020-7136, E-ISSN 1097-0215, Vol. 141, no 1, p. 200-209Article in journal (Refereed) Published
    Abstract [en]

    Women screened for cervical cancer in Sweden are currently treated under a one-size-fits-all programme, which has been successful in reducing the incidence of cervical cancer but does not use all of the participants' available medical information. This study aimed to use women's complete cervical screening histories to identify diagnostic patterns that may indicate an increased risk of developing cervical cancer. A nationwide case-control study was performed where cervical cancer screening data from 125,476 women with a maximum follow-up of 10 years were evaluated for patterns of SNOMED diagnoses. The cancer development risk was estimated for a number of different screening history patterns and expressed as Odds Ratios (OR), with a history of 4 benign cervical tests as reference, using logistic regression. The overall performance of the model was moderate (64% accuracy, 71% area under curve) with 61-62% of the study population showing no specific patterns associated with risk. However, predictions for high-risk groups as defined by screening history patterns were highly discriminatory with ORs ranging from 8 to 36. The model for computing risk performed consistently across different screening history lengths, and several patterns predicted cancer outcomes. The results show the presence of risk-increasing and risk-decreasing factors in the screening history. Thus it is feasible to identify subgroups based on their complete screening histories. Several high-risk subgroups identified might benefit from an increased screening density. Some low-risk subgroups identified could likely have a moderately reduced screening density without additional risk.

    Keywords
    bioinformatics, cervical cancer, screening, personalized medicine, machine learning
    National Category
    Cancer and Oncology Bioinformatics (Computational Biology)
    Identifiers
    urn:nbn:se:uu:diva-323754 (URN)10.1002/ijc.30725 (DOI)000400766500021 ()28383102 (PubMedID)
    Available from: 2017-06-12 Created: 2017-06-12 Last updated: 2019-10-07Bibliographically approved
    2. Allele specific chromatin signals, 3D interactions, and motif predictions for immune and B cell related diseases
    Open this publication in new window or tab >>Allele specific chromatin signals, 3D interactions, and motif predictions for immune and B cell related diseases
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    2019 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 9, article id 2695Article in journal (Refereed) Published
    Abstract [en]

    Several Genome Wide Association Studies (GWAS) have reported variants associated to immune diseases. However, the identified variants are rarely the drivers of the associations and the molecular mechanisms behind the genetic contributions remain poorly understood. ChIP-seq data for TFs and histone modifications provide snapshots of protein-DNA interactions allowing the identification of heterozygous SNPs showing significant allele specific signals (AS-SNPs). AS-SNPs can change a TF binding site resulting in altered gene regulation and are primary candidates to explain associations observed in GWAS and expression studies. We identified 17,293 unique AS-SNPs across 7 lymphoblastoid cell lines. In this set of cell lines we interrogated 85% of common genetic variants in the population for potential regulatory effect and we identified 237 AS-SNPs associated to immune GWAS traits and 714 to gene expression in B cells. To elucidate possible regulatory mechanisms we integrated long-range 3D interactions data to identify putative target genes and motif predictions to identify TFs whose binding may be affected by AS-SNPs yielding a collection of 173 AS-SNPs associated to gene expression and 60 to B cell related traits. We present a systems strategy to find functional gene regulatory variants, the TFs that bind differentially between alleles and novel strategies to detect the regulated genes.

    Place, publisher, year, edition, pages
    NATURE PUBLISHING GROUP, 2019
    National Category
    Medical Genetics
    Identifiers
    urn:nbn:se:uu:diva-379258 (URN)10.1038/s41598-019-39633-0 (DOI)000459571100059 ()30804403 (PubMedID)
    Funder
    Swedish Research Council, 78081Swedish National Infrastructure for Computing (SNIC)EXODIAB - Excellence of Diabetes Research in SwedenSwedish Diabetes AssociationErnfors FoundationSwedish Cancer Society, 160518German Research Foundation (DFG), GR-3526/1German Research Foundation (DFG), GR-3526/2
    Available from: 2019-03-15 Created: 2019-03-15 Last updated: 2019-10-07Bibliographically approved
    3. Risk Stratification in Cervical Cancer Screening – Validation and Generalization of a Data-driven  Screening Recall Model
    Open this publication in new window or tab >>Risk Stratification in Cervical Cancer Screening – Validation and Generalization of a Data-driven  Screening Recall Model
    Show others...
    (English)Manuscript (preprint) (Other academic)
    Keywords
    Cervical Cancer, Screening, Classification, Bioinformatics, Rough Sets
    National Category
    Bioinformatics and Systems Biology
    Research subject
    Bioinformatics; Bioinformatics
    Identifiers
    urn:nbn:se:uu:diva-394291 (URN)
    Available from: 2019-10-07 Created: 2019-10-07 Last updated: 2019-10-07
    4. Studies of liver tissue identify functional gene regulatory elements associated to gene expression, type 2 diabetes, and other metabolic diseases
    Open this publication in new window or tab >>Studies of liver tissue identify functional gene regulatory elements associated to gene expression, type 2 diabetes, and other metabolic diseases
    Show others...
    2019 (English)In: HUMAN GENOMICS, ISSN 1473-9542, Vol. 13, article id 20Article in journal (Refereed) Published
    Abstract [en]

    Background:

    Genome-wide association studies (GWAS) of diseases and traits have found associations to gene regions but not the functional SNP or the gene mediating the effect. Difference in gene regulatory signals can be detected using chromatin immunoprecipitation and next-gen sequencing (ChIP-seq) of transcription factors or histone modifications by aligning reads to known polymorphisms in individual genomes. The aim was to identify such regulatory elements in the human liver to understand the genetics behind type 2 diabetes and metabolic diseases.

    Methods:

    The genome of liver tissue was sequenced using 10X Genomics technology to call polymorphic positions. Using ChIP-seq for two histone modifications, H3K4me3 and H3K27ac, and the transcription factor CTCF, and our established bioinformatics pipeline, we detected sites with significant difference in signal between the alleles.

    Results:

    We detected 2329 allele-specific SNPs (AS-SNPs) including 25 associated to GWAS SNPs linked to liver biology, e.g., 4 AS-SNPs at two type 2 diabetes loci. Two hundred ninety-two AS-SNPs were associated to liver gene expression in GTEx, and 134 AS-SNPs were located on 166 candidate functional motifs and most of them in EGR1-binding sites.

    Conclusions:

    This study provides a valuable collection of candidate liver regulatory elements for further experimental validation.

    Keywords
    ChIP-seq, T2D, Regulatory SNPs
    National Category
    Medical Genetics Bioinformatics and Systems Biology
    Identifiers
    urn:nbn:se:uu:diva-383513 (URN)10.1186/s40246-019-0204-8 (DOI)000466335200001 ()31036066 (PubMedID)
    Available from: 2019-05-16 Created: 2019-05-16 Last updated: 2019-10-07Bibliographically approved
    5. ||-ROSETTA
    Open this publication in new window or tab >>||-ROSETTA
    (English)Manuscript (preprint) (Other academic)
    Keywords
    bioinformatics, Rough Sets
    National Category
    Computer Sciences Bioinformatics (Computational Biology)
    Research subject
    Bioinformatics; Computer Science
    Identifiers
    urn:nbn:se:uu:diva-393477 (URN)
    Available from: 2019-10-07 Created: 2019-10-07 Last updated: 2019-10-07
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  • 8.
    Baltzer, Nicholas
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Komorowski, Jan
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    ||-ROSETTAManuscript (preprint) (Other academic)
  • 9.
    Baltzer, Nicholas
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Komorowski, Jan
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Sundström, Karin
    Nygård, Jan
    Nygård, Mari
    Dillner, Joakim
    Risk Stratification in Cervical Cancer Screening – Validation and Generalization of a Data-driven  Screening Recall ModelManuscript (preprint) (Other academic)
  • 10.
    Baltzer, Nicholas
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Stockholm County, Sweden.
    Sundström, Karin
    Karolinska Inst, Dept Lab Med, Stockholm, Stockholm Count, Sweden..
    Nygård, Jan F.
    Canc Registry Norway, Dept Registry Informat, Oslo, Oslo County, Norway..
    Dillner, Joakim
    Karolinska Inst, Dept Lab Med, Stockholm, Stockholm Count, Sweden..
    Komorowski, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Polish Acad Sci, Inst Comp Sci, Warsaw, Warsaw County, Poland..
    Risk stratification in cervical cancer screening by complete screening history: Applying bioinformatics to a general screening population2017In: International Journal of Cancer, ISSN 0020-7136, E-ISSN 1097-0215, Vol. 141, no 1, p. 200-209Article in journal (Refereed)
    Abstract [en]

    Women screened for cervical cancer in Sweden are currently treated under a one-size-fits-all programme, which has been successful in reducing the incidence of cervical cancer but does not use all of the participants' available medical information. This study aimed to use women's complete cervical screening histories to identify diagnostic patterns that may indicate an increased risk of developing cervical cancer. A nationwide case-control study was performed where cervical cancer screening data from 125,476 women with a maximum follow-up of 10 years were evaluated for patterns of SNOMED diagnoses. The cancer development risk was estimated for a number of different screening history patterns and expressed as Odds Ratios (OR), with a history of 4 benign cervical tests as reference, using logistic regression. The overall performance of the model was moderate (64% accuracy, 71% area under curve) with 61-62% of the study population showing no specific patterns associated with risk. However, predictions for high-risk groups as defined by screening history patterns were highly discriminatory with ORs ranging from 8 to 36. The model for computing risk performed consistently across different screening history lengths, and several patterns predicted cancer outcomes. The results show the presence of risk-increasing and risk-decreasing factors in the screening history. Thus it is feasible to identify subgroups based on their complete screening histories. Several high-risk subgroups identified might benefit from an increased screening density. Some low-risk subgroups identified could likely have a moderately reduced screening density without additional risk.

  • 11.
    Baltzer, Nicholas
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Sundström, Karin
    Karolinska Inst, Dept Lab Med, Stockholm, Sweden.
    Nygård, Jan
    Canc Registry Norway, Dept Registry Informat, Oslo, Norway.
    Nygård, Mari
    Canc Registry Norway, Dept Registry Informat, Oslo, Norway.
    Dillner, Joakim
    Karolinska Inst, Dept Lab Med, Stockholm, Sweden.
    Komorowski, Jan
    Uppsala Univ, Dept Cell & Mol Biol, Uppsala, Sweden;Polish Acad Sci, Warsaw, Poland.
    Stratifying Cervical Cancer Risk With Registry Data2018In: 2018 IEEE 14th International Conference on e-Science (e-Science 2018), IEEE, 2018, p. 288-289Conference paper (Refereed)
    Abstract [en]

    The cervical cancer screening programmes in Sweden and Norway have successfully reduced the frequency of cervical cancer incidence but have not implemented any form of evaluation for screening needs. This means that the screening frequency for individuals can he suboptimal, increasing either the cost of the programme or the risk of missing an early stage cancer development. We developed a framework for assessing an individual's risk of cervical cancer based on their available screening history and computing a primary risk factor called CRS from a data-driven separation model together with multiple derived attributes. The results show that this approach is highly practical, validates against multiple established trends, and can he effective in personalizing the screening needs for individuals.

  • 12.
    Barrenäs, Fredrik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Univ Washington, Dept Microbiol, Seattle, WA 98195 USA.
    Raehtz, Kevin
    Univ Pittsburgh, Dept Med, Div Infect Dis, Pittsburgh, PA USA;Univ Pittsburgh, Sch Med, Dept Microbiol & Mol Genet, Pittsburgh, PA USA.
    Xu, Cuiling
    Univ Pittsburgh, Sch Med, Dept Pathol, Pittsburgh, PA USA.
    Law, Lynn
    Univ Washington, Dept Immunol, Seattle, WA 98195 USA;Univ Washington, Ctr Innate Immun & Immune Dis, Seattle, WA 98195 USA.
    Green, Richard R.
    Univ Washington, Dept Immunol, Seattle, WA 98195 USA;Univ Washington, Ctr Innate Immun & Immune Dis, Seattle, WA 98195 USA.
    Silvestri, Guido
    Emory Univ, Dept Pathol & Lab Med, Atlanta, GA 30322 USA;Emory Univ, Yerkes Natl Primate Res Ctr, Div Microbiol & Immunol, Atlanta, GA 30322 USA.
    Bosinger, Steven E.
    Emory Univ, Dept Pathol & Lab Med, Atlanta, GA 30322 USA;Emory Univ, Yerkes Natl Primate Res Ctr, Div Microbiol & Immunol, Atlanta, GA 30322 USA.
    Nishida, Andrew
    Univ Washington, Dept Microbiol, Seattle, WA 98195 USA.
    Li, Qingsheng
    Univ Nebraska, Sch Biol Sci, Nebraska Ctr Virol, Lincoln, NE USA.
    Lu, Wuxun
    Univ Nebraska, Sch Biol Sci, Nebraska Ctr Virol, Lincoln, NE USA.
    Zhang, Jianshui
    Univ Nebraska, Sch Biol Sci, Nebraska Ctr Virol, Lincoln, NE USA.
    Thomas, Matthew J.
    Univ Washington, Dept Immunol, Seattle, WA 98195 USA;Univ Washington, Washington Natl Primate Res Ctr, Seattle, WA 98195 USA.
    Chang, Jean
    Univ Washington, Dept Immunol, Seattle, WA 98195 USA;Univ Washington, Ctr Innate Immun & Immune Dis, Seattle, WA 98195 USA.
    Smith, Elise
    Univ Washington, Dept Immunol, Seattle, WA 98195 USA;Univ Washington, Ctr Innate Immun & Immune Dis, Seattle, WA 98195 USA.
    Weiss, Jeffrey M.
    Univ Washington, Dept Microbiol, Seattle, WA 98195 USA.
    Dawoud, Reem A.
    Emory Univ, Dept Pathol & Lab Med, Atlanta, GA 30322 USA.
    Richter, George H.
    Univ Pittsburgh, Sch Med, Dept Pathol, Pittsburgh, PA USA.
    Trichel, Anita
    Univ Pittsburgh, Div Lab Anim Resources, Pittsburgh, PA USA.
    Ma, Dongzhu
    Univ Pittsburgh, Dept Orthoped Surg, Pittsburgh, PA USA.
    Peng, Xinxia
    North Carolina State Univ, Dept Mol Biomed Sci, Raleigh, NC 27695 USA.
    Komorowski, Jan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Apetrei, Cristian
    Univ Pittsburgh, Dept Med, Div Infect Dis, Pittsburgh, PA USA;Univ Pittsburgh, Sch Med, Dept Microbiol & Mol Genet, Pittsburgh, PA USA.
    Pandrea, Ivona
    Univ Pittsburgh, Sch Med, Dept Microbiol & Mol Genet, Pittsburgh, PA USA;Univ Pittsburgh, Sch Med, Dept Pathol, Pittsburgh, PA USA.
    Gale, Michael, Jr.
    Univ Washington, Dept Immunol, Seattle, WA 98195 USA;Univ Washington, Ctr Innate Immun & Immune Dis, Seattle, WA 98195 USA;Univ Washington, Washington Natl Primate Res Ctr, Seattle, WA 98195 USA.
    Macrophage-associated wound healing contributes to African green monkey SIV pathogenesis control2019In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 10, article id 5101Article in journal (Refereed)
    Abstract [en]

    Natural hosts of simian immunodeficiency virus (SIV) avoid AIDS despite lifelong infection. Here, we examined how this outcome is achieved by comparing a natural SIV host, African green monkey (AGM) to an AIDS susceptible species, rhesus macaque (RM). To asses gene expression profiles from acutely SIV infected AGMs and RMs, we developed a systems biology approach termed Conserved Gene Signature Analysis (CGSA), which compared RNA sequencing data from rectal AGM and RM tissues to various other species. We found that AGMs rapidly activate, and then maintain, evolutionarily conserved regenerative wound healing mechanisms in mucosal tissue. The wound healing protein fibronectin shows distinct tissue distribution and abundance kinetics in AGMs. Furthermore, AGM monocytes exhibit an embryonic development and repair/regeneration signature featuring TGF-beta and concomitant reduced expression of inflammatory genes compared to RMs. This regenerative wound healing process likely preserves mucosal integrity and prevents inflammatory insults that underlie immune exhaustion in RMs.

    Download full text (pdf)
    FULLTEXT01
  • 13.
    Barrozo, Alexandre
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Liao, Qinghua
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structural Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Esguerra, Mauricio
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Marloie, Gael
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Florian, Jan
    Loyola Univ Chicago, Dept Chem & Biochem, Chicago, IL 60660 USA..
    Williams, Nicholas H.
    Univ Sheffield, Dept Chem, Sheffield S3 7HF, S Yorkshire, England..
    Kamerlin, Shina C. Lynn
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Computer simulations of the catalytic mechanism of wild-type and mutant beta-phosphoglucomutase2018In: Organic and biomolecular chemistry, ISSN 1477-0520, E-ISSN 1477-0539, Vol. 16, no 12, p. 2060-2073Article in journal (Refereed)
    Abstract [en]

    beta-Phosphoglucomutase (beta-PGM) has served as an important model system for understanding biological phosphoryl transfer. This enzyme catalyzes the isomerization of beta-glucose-1-phosphate to -glucose-6-phosphate in a two-step process proceeding via a bisphosphate intermediate. The conventionally accepted mechanism is that both steps are concerted processes involving acid-base catalysis from a nearby aspartate (D10) side chain. This argument is supported by the observation that mutation of D10 leaves the enzyme with no detectable activity. However, computational studies have suggested that a substrate-assisted mechanism is viable for many phosphotransferases. Therefore, we carried out empirical valence bond (EVB) simulations to address the plausibility of this mechanistic alternative, including its role in the abolished catalytic activity of the D10S, D10C and D10N point mutants of beta-PGM. In addition, we considered both of these mechanisms when performing EVB calculations of the catalysis of the wild type (WT), H20A, H20Q, T16P, K76A, D170A and E169A/D170A protein variants. Our calculated activation free energies confirm that D10 is likely to serve as the general base/acid for the reaction catalyzed by the WT enzyme and all its variants, in which D10 is not chemically altered. Our calculations also suggest that D10 plays a dual role in structural organization and maintaining electrostatic balance in the active site. The correct positioning of this residue in a catalytically competent conformation is provided by a functionally important conformational change in this enzyme and by the extensive network of H-bonding interactions that appear to be exquisitely preorganized for the transition state stabilization.

    Download full text (pdf)
    fulltext
  • 14.
    Bashardanesh, Zahedeh
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Effect of Macromolecular Crowding on Diffusive Processes2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Macromolecular crowding are innate to cellular environment. Understanding their effect on cellular components and processes is essential. This is often neglected in dilute experimental setup both in vitro and in silico.

    In this thesis I have dealt with challenges in biomolecular simulations at two levels of modeling, Brownian Dynamics (BD) and Molecular Dynamics (MD).

    Conventional BD simulations become inefficient since most of the computational time is spent propagating the particles towards each other before any reaction takes place. Event-driven algorithms have proven to be several orders of magnitude faster than conventional BD algorithms. However, the presence of diffusion-limited reactions in biochemical networks lead to multiple rebindings in case of a reversible reaction which deteriorates the efficiency of these types of algorithms. In this thesis, I modeled a reversible reaction coupled with diffusion in order to incorporate multiple rebindings. I implemented a Green's Function Reaction Dynamics (GFRD) algorithm by using the analytical solution of the reversible reaction diffusion equation. I show that the algorithm performance is independent of the number of rebindings.

    Nevertheless, the gain in computational power still deteriorates when it comes to the simulation of crowded systems. However, given the effects of macromolecular crowding on diffusion coefficient and kinetic parameters are known, one can implicitly incorporate the effect of crowding into coarse-grain algorithms by choosing right parameters. Therefore, understanding the effect of crowding at atomistic resolution would be beneficial.

    I studied the effect of high concentration of macromolecules on diffusive properties at atomistic level with MD simulations. The findings emphasize the effect of chemical interactions at atomistic level on mobility of macromolecules.

    Simulating macromolecules in high concentration raised challenges for atomistic physical models. Current force fields lead to aggregation of proteins at high concentration. I probed scenarios based on weakening and strengthening protein-protein and protein-water interactions, respectively. Furthermore, I built a cytoplasmic model at atomistic level based on the data available on Escherichia coli cytoplasm. This model was simulated in time and space by MD simulation package, GROMACS. Through this model, it is possible to study structural and dynamical properties under cellular like environment at physiological concentration.

    List of papers
    1. Efficient Green's function reaction dynamics (GFRD) simulations for diffusion-limited, reversible reactions
    Open this publication in new window or tab >>Efficient Green's function reaction dynamics (GFRD) simulations for diffusion-limited, reversible reactions
    2018 (English)In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 357, p. 78-99Article in journal (Refereed) Published
    National Category
    Computational Mathematics Bioinformatics (Computational Biology)
    Identifiers
    urn:nbn:se:uu:diva-338758 (URN)10.1016/j.jcp.2017.12.025 (DOI)000427393800004 ()
    Available from: 2017-12-21 Created: 2018-01-12 Last updated: 2019-10-14Bibliographically approved
    2. Impact of Dispersion Coefficient on Simulations of Proteins and Organic Liquids
    Open this publication in new window or tab >>Impact of Dispersion Coefficient on Simulations of Proteins and Organic Liquids
    2018 (English)In: Journal of Physical Chemistry B, ISSN 1520-6106, E-ISSN 1520-5207, Vol. 122, no 33, p. 8018-8027Article in journal (Refereed) Published
    Abstract [en]

    In the context of studies of proteins under crowding conditions, it was found that there is a tendency of simulated proteins to coagulate in a seemingly unphysical manner. This points to an imbalance in the protein-protein or protein-water interactions. One way to resolve this is to strengthen the protein-water Lennard-Jones interactions. However, it has also been suggested that dispersion interactions may have been systematically overestimated in force fields due to parameterization with a short cutoff. Here, we test this proposition by performing simulations of liquids and of proteins in solution with systematically reduced C-6 (dispersion constant in a 12-6 Lennard-Jones potential) and evaluate the properties. We find that simulations of liquids with either a dispersion correction or explicit long-range Lennard-Jones interactions need little or no correction to the dispersion constant to reproduce the experimental density. For simulations of proteins, a significant reduction in the dispersion constant is needed to reduce the coagulation, however. Because the protein- and liquid force fields share atom types, at least to some extent, another solution for the coagulation problem may be needed, either through including explicit polarization or through strengthening protein-water interactions.

    National Category
    Physical Chemistry Biophysics
    Identifiers
    urn:nbn:se:uu:diva-364048 (URN)10.1021/acs.jpcb.8b05770 (DOI)000442959900008 ()30084244 (PubMedID)
    Available from: 2018-12-10 Created: 2018-12-10 Last updated: 2019-10-14Bibliographically approved
    3. Rotational and Translational Diffusion of Proteins as a Function of Concentration
    Open this publication in new window or tab >>Rotational and Translational Diffusion of Proteins as a Function of Concentration
    2019 (English)In: ACS OMEGA, E-ISSN 2470-1343, Vol. 4, no 24, p. 20654-20664Article in journal (Refereed) Published
    Abstract [en]

    Atomistic simulations of three different proteins at different concentrations are performed to obtain insight into protein mobility as a function of protein concentration. We report on simulations of proteins from diluted to the physiological water concentration (about 70% of the mass). First, the viscosity was computed and found to increase by a factor of 7-9 going from pure water to the highest protein concentration, in excellent agreement with in vivo nuclear magnetic resonance results. At a physiological concentration of proteins, the translational diffusion is found to be slowed down to about 30% of the in vitro values. The slow-down of diffusion found here using atomistic models is slightly more than that of a hard sphere model that neglects the electrostatic interactions. Interestingly, rotational diffusion of proteins is slowed down somewhat more (by about 80-95% compared to in vitro values) than translational diffusion, in line with experimental findings and consistent with the increased viscosity. The finding that rotation is retarded more than translation is attributed to solvent-separated clustering. No direct interactions between the proteins are found, and the clustering can likely be attributed to dispersion interactions that are stronger between proteins than between protein and water. Based on these simulations, we can also conclude that the internal dynamics of the proteins in our study are affected only marginally under crowding conditions, and the proteins become somewhat more stable at higher concentrations. Simulations were performed using a force field that was tuned for dealing with crowding conditions by strengthening the protein-water interactions. This force field seems to lead to a reproducible partial unfolding of an alpha-helix in one of the proteins, an effect that was not observed in the unmodified force field.

    National Category
    Biophysics
    Identifiers
    urn:nbn:se:uu:diva-395115 (URN)10.1021/acsomega.9b02835 (DOI)000502130800028 ()31858051 (PubMedID)
    Funder
    Swedish Research Council, 2013-5947Swedish National Infrastructure for Computing (SNIC), SNIC2017-12-41
    Available from: 2019-10-12 Created: 2019-10-12 Last updated: 2020-01-23Bibliographically approved
    4. Making Soup: Preparing and Validating Molecular Simulations of the Bacterial Cytoplasm
    Open this publication in new window or tab >>Making Soup: Preparing and Validating Molecular Simulations of the Bacterial Cytoplasm
    (English)Manuscript (preprint) (Other academic)
    National Category
    Natural Sciences
    Identifiers
    urn:nbn:se:uu:diva-395118 (URN)
    Available from: 2019-10-12 Created: 2019-10-12 Last updated: 2019-10-14
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    presentationsbild
  • 15.
    Bashardanesh, Zahedeh
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Zhang, Haiyang
    University of Science and Technology Beijing, Peoples R China.
    Van der Spoel, David
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Rotational and Translational Diffusion of Proteins as a Function of Concentration2019In: ACS OMEGA, E-ISSN 2470-1343, Vol. 4, no 24, p. 20654-20664Article in journal (Refereed)
    Abstract [en]

    Atomistic simulations of three different proteins at different concentrations are performed to obtain insight into protein mobility as a function of protein concentration. We report on simulations of proteins from diluted to the physiological water concentration (about 70% of the mass). First, the viscosity was computed and found to increase by a factor of 7-9 going from pure water to the highest protein concentration, in excellent agreement with in vivo nuclear magnetic resonance results. At a physiological concentration of proteins, the translational diffusion is found to be slowed down to about 30% of the in vitro values. The slow-down of diffusion found here using atomistic models is slightly more than that of a hard sphere model that neglects the electrostatic interactions. Interestingly, rotational diffusion of proteins is slowed down somewhat more (by about 80-95% compared to in vitro values) than translational diffusion, in line with experimental findings and consistent with the increased viscosity. The finding that rotation is retarded more than translation is attributed to solvent-separated clustering. No direct interactions between the proteins are found, and the clustering can likely be attributed to dispersion interactions that are stronger between proteins than between protein and water. Based on these simulations, we can also conclude that the internal dynamics of the proteins in our study are affected only marginally under crowding conditions, and the proteins become somewhat more stable at higher concentrations. Simulations were performed using a force field that was tuned for dealing with crowding conditions by strengthening the protein-water interactions. This force field seems to lead to a reproducible partial unfolding of an alpha-helix in one of the proteins, an effect that was not observed in the unmodified force field.

    Download full text (pdf)
    fulltext
  • 16.
    Bashardanesh, Zahedeh
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Lötstedt, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Efficient Green's function reaction dynamics (GFRD) simulations for diffusion-limited, reversible reactions2018In: Journal of Computational Physics, ISSN 0021-9991, E-ISSN 1090-2716, Vol. 357, p. 78-99Article in journal (Refereed)
  • 17.
    Bashardanesh, Zahedeh
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    van der Spoel, David
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Impact of Dispersion Coefficient on Simulations of Proteins and Organic Liquids2018In: Journal of Physical Chemistry B, ISSN 1520-6106, E-ISSN 1520-5207, Vol. 122, no 33, p. 8018-8027Article in journal (Refereed)
    Abstract [en]

    In the context of studies of proteins under crowding conditions, it was found that there is a tendency of simulated proteins to coagulate in a seemingly unphysical manner. This points to an imbalance in the protein-protein or protein-water interactions. One way to resolve this is to strengthen the protein-water Lennard-Jones interactions. However, it has also been suggested that dispersion interactions may have been systematically overestimated in force fields due to parameterization with a short cutoff. Here, we test this proposition by performing simulations of liquids and of proteins in solution with systematically reduced C-6 (dispersion constant in a 12-6 Lennard-Jones potential) and evaluate the properties. We find that simulations of liquids with either a dispersion correction or explicit long-range Lennard-Jones interactions need little or no correction to the dispersion constant to reproduce the experimental density. For simulations of proteins, a significant reduction in the dispersion constant is needed to reduce the coagulation, however. Because the protein- and liquid force fields share atom types, at least to some extent, another solution for the coagulation problem may be needed, either through including explicit polarization or through strengthening protein-water interactions.

  • 18.
    Bauer, Paul
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Barrozo, Alexandre
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structure and Molecular Biology.
    Amrein, Beat Anton
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structure and Molecular Biology.
    Purg, Miha
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structure and Molecular Biology.
    Esguerra, Mauricio
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Wilson, Philippe
    De Montfort University Leicester, School of Pharmacy .
    Åqvist, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Major, Dan Thomas
    Department of Chemistry, The Lise Meitner-Minerva Center of Computational Quantum Chemistry, Bar-Ilan University, Ramat-Gan 52900, Israel.
    Kamerlin, Shina Caroline Lynn
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structure and Molecular Biology.
    Q Version 6, a comprehensive toolkit for empirical valence bond and related free energy calculations.Manuscript (preprint) (Other academic)
  • 19.
    Bauer, Paul
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Barrozo, Alexandre
    Department of Chemistry, University of Southern California, SGM 418, 3620 McClintock Ave., Los Angeles, CA 90089-1062, United StatesDepartment of Chemistry, University of Southern California, SGM 418, 3620 McClintock Ave., Los Angeles, CA 90089-1062, United States.
    Purg, Miha
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Amrein, Beat Anton
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Esguerra, Mauricio
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Wilson, Philippe Barrie
    Leicester School of Pharmacy, De Montfort University, The Gateway, Leicester LE1 9BH, UK.
    Major, Dan Thomas
    Department of Chemistry, Bar-Ilan University, Ramat-Gan 52900, Israel.
    Åqvist, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Kamerlin, Shina C. Lynn
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structural Biology.
    Q6: A comprehensive toolkit for empirical valence bond and related free energy calculations2018In: SoftwareX, ISSN 2352-7110, p. 388-395Article in journal (Refereed)
    Abstract [en]

    Atomistic simulations have become one of the main approaches to study the chemistry and dynamicsof biomolecular systems in solution. Chemical modelling is a powerful way to understand biochemistry,with a number of different programs available to perform specialized calculations. We present here Q6, anew version of the Q software package, which is a generalized package for empirical valence bond, linearinteraction energy, and other free energy calculations. In addition to general technical improvements, Q6extends the reach of the EVB implementation to fast approximations of quantum effects, extended solventdescriptions and quick estimation of the contributions of individual residues to changes in the activationfree energy of reactions.

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  • 20.
    Behzadi, Hadi
    et al.
    Department of Physical Chemistry, Faculty of Chemistry, Kharazmi University, 15719-14911, Tehran, Iran.
    Manzetti, Sergio
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Fjordforsk AS, N-6894 Midtun, Vangsnes, Norway.
    Darghai, Mayram
    Department of Chemistry, Faculty of Science, Imam Khomeini International University, Qazvin, Iran.
    Roonasi, Payman
    Department of Physical Chemistry, Faculty of Chemistry, Kharazmi University, 15719-14911, Tehran, Iran.
    Khalilnia, Zahra
    Department of Physical Chemistry, Faculty of Chemistry, Kharazmi University, 15719-14911, Tehran, Iran.
    Application of calculated NMR parameters, aromaticity indices and wavefunction properties for evaluation of corrosion inhibition efficiency of pyrazine inhibitors2018In: Journal of Molecular Structure: THEOCHEM, ISSN 0166-1280, Vol. 1151, p. 34-40Article in journal (Refereed)
  • 21.
    Behzadi, Hadi
    et al.
    Kharazmi Univ, Fac Chem, Dept Phys Chem, Tehran, Iran.
    Roonasi, Payman
    Kharazmi Univ, Fac Chem, Dept Phys Chem, Tehran, Iran.
    Taghipour, Khatoon Assle
    Kharazmi Univ, Fac Chem, Dept Phys Chem, Tehran, Iran.
    van der Spoel, David
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Manzetti, Sergio
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Fjordforsk AS Inst Sci & Technol, N-6894 Midtun, Vangsnes, Norway.
    Relationship between electronic properties and drug activity of seven quinoxaline compounds: A DFT study2015In: Journal of Molecular Structure, ISSN 0022-2860, E-ISSN 1872-8014, Vol. 1091, p. 196-202Article in journal (Refereed)
    Abstract [en]

    The quantum chemical calculations at the DFT/B3LYP level of theory were carried out on seven quinoxaline compounds, which have been synthesized as anti-Mycobacterium tuberculosis agents. Three conformers were optimized for each compound and the lowest energy structure was found and used in further calculations. The electronic properties including E-HOMO, E-LUMO and related parameters as well as electron density around oxygen and nitrogen atoms were calculated for each compound. The relationship between the calculated electronic parameters and biological activity of the studied compounds were investigated. Six similar quinoxaline derivatives with possible more drug activity were suggested based on the calculated electronic descriptors. A mechanism was proposed and discussed based on the calculated electronic parameters and bond dissociation energies.

  • 22.
    Bellissent-Funel, Marie-Claire
    et al.
    CEA Saclay, CNRS, Lab Leon Brillouin, F-91191 Gif Sur Yvette, France..
    Hassanali, Ali
    Abdus Salaam Int Ctr Theoret Phys, Condensed Matter & Stat Phys, I-34151 Trieste, Italy..
    Havenith, Martina
    Ruhr Univ Bochum, Fac Chem & Biochem, Univ Str 150 Bldg NC 7-72, D-44780 Bochum, Germany..
    Henchman, Richard
    Univ Manchester, Manchester Inst Biotechnol, 131 Princess St, Manchester M1 7DN, Lancs, England..
    Pohl, Peter
    Johannes Kepler Univ Linz, Gruberstr 40, A-4020 Linz, Austria..
    Sterpone, Fabio
    Inst Biol Physicochim, Lab Biochim Theor, 13 Rue Pierre & Marie Curie, F-75005 Paris, France..
    van der Spoel, David
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Xu, Yao
    Ruhr Univ Bochum, Fac Chem & Biochem, Univ Str 150 Bldg NC 7-72, D-44780 Bochum, Germany..
    Garcia, Angel E.
    Los Alamos Natl Lab, Ctr Non Linear Studies, Los Alamos, NM 87545 USA..
    Water Determines the Structure and Dynamics of Proteins2016In: Chemical Reviews, ISSN 0009-2665, E-ISSN 1520-6890, Vol. 116, no 13, p. 7673-7697Article, review/survey (Refereed)
    Abstract [en]

    Water is an essential participant in the stability, structure, dynamics, and function of proteins and other biomolecules. Thermodynamically, changes in the aqueous environment affect the stability of biomolecules. Structurally, water participates chemically in the catalytic function of proteins and nucleic acids and physically in the collapse of the protein chain during folding through hydrophobic collapse and mediates binding through the hydrogen bond in complex formation. Water is a partner that slaves the dynamics of proteins, and water interaction with proteins affect their dynamics. Here we provide a review of the experimental and computational advances over the past decade in understanding the role of water in the dynamics, structure, and function of proteins. We focus on the combination of X-ray and neutron crystallography, NMR, terahertz spectroscopy, mass spectroscopy, thermodynamics, and computer simulations to reveal how water assist proteins in their function. The recent advances in computer simulations and the enhanced sensitivity of experimental tools promise major advances in the understanding of protein dynamics, and water surely will be a protagonist.

  • 23.
    Bharate, Sandip B.
    et al.
    CSIR Indian Inst Integrat Med, Div Med Chem, Canal Rd, Jammu 180001, Jammu & Kashmir, India.;CSIR Indian Inst Integrat Med, Acad Sci & Innovat Res AcSIR, Canal Rd, Jammu 180001, Jammu & Kashmir, India..
    Singh, Baljinder
    CSIR Indian Inst Integrat Med, Nat Prod Chem Div, Canal Rd, Jammu 180001, Jammu & Kashmir, India..
    Kachler, Sonja
    Univ Wurzburg, Inst Pharmakol & Toxikol, Versbacher Str 9, D-97078 Wurzburg, Germany..
    Oliveira, Ana
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Kumar, Vikas
    CSIR Indian Inst Integrat Med, Acad Sci & Innovat Res AcSIR, Canal Rd, Jammu 180001, Jammu & Kashmir, India.;CSIR Indian Inst Integrat Med, Preformulat Lab, Canal Rd, Jammu 180001, Jammu & Kashmir, India..
    Bharate, Sonali S.
    CSIR Indian Inst Integrat Med, Preformulat Lab, Canal Rd, Jammu 180001, Jammu & Kashmir, India..
    Vishwakarma, Ram A.
    CSIR Indian Inst Integrat Med, Div Med Chem, Canal Rd, Jammu 180001, Jammu & Kashmir, India.;CSIR Indian Inst Integrat Med, Acad Sci & Innovat Res AcSIR, Canal Rd, Jammu 180001, Jammu & Kashmir, India..
    Klotz, Karl-Norbert
    Univ Wurzburg, Inst Pharmakol & Toxikol, Versbacher Str 9, D-97078 Wurzburg, Germany..
    de Teran, Hugo Gutierrez
    Uppsala Univ, Dept Cell & Mol Biol, Box 596, SE-75124 Uppsala, Sweden..
    Discovery of 7-(Prolinol-N-yl)-2-phenylamino-thiazolo[5,4-d]pyrimidines as Novel Non-Nucleoside Partial Agonists for the A(2A) Adenosine Receptor: Prediction from Molecular Modeling2016In: Journal of Medicinal Chemistry, ISSN 0022-2623, E-ISSN 1520-4804, Vol. 59, no 12, p. 5922-5928Article in journal (Refereed)
    Abstract [en]

    We describe the identification of 7-(prolinol-N-yl)-2-phenylamino-thiazolo[5,4-d]pyrimidines as a novel chemotype of non-nucleoside partial agonists for the A(2A) adenosine receptor (A(2A)AR). Molecular-modeling indicated that the (S)-2-hydroxymethylene-pyrrolidine could mimic the interactions of agonists' ribose, suggesting that this class of compounds could have agonistic properties. This was confirmed by functional assays on the A(2A)AR, where their efficacy could be associated with the presence of the 2-hydroxymethylene moiety. Additionally, the best compound displays promising affinity, selectivity profile, and physicochemical properties.

  • 24.
    Björneholm, Olle
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Molecular and condensed matter physics.
    Hansen, Martin H.
    Tech Univ Denmark, DK-2800 Lyngby, Denmark.;Univ Copenhagen, Dept Chem, Univ Pk 5, DK-2100 Copenhagen, Denmark..
    Hodgson, Andrew
    Univ Liverpool, Dept Chem, Liverpool L69 7ZD, Merseyside, England..
    Liu, Li-Min
    UCL, London Ctr Nanotechnol, Thomas Young Ctr, Dept Phys & Astron, London WC1E 6BT, England.;UCL, Dept Chem, London WC1E 6BT, England.;Beijing Computat Sci Res Ctr, Beijing 100193, Peoples R China..
    Limmer, David T.
    Princeton Univ, Princeton Ctr Theoret Sci, Princeton, NJ 08544 USA..
    Michaelides, Angelos
    UCL, London Ctr Nanotechnol, Thomas Young Ctr, Dept Phys & Astron, London WC1E 6BT, England.;UCL, Dept Chem, London WC1E 6BT, England..
    Pedevilla, Philipp
    UCL, London Ctr Nanotechnol, Thomas Young Ctr, Dept Phys & Astron, London WC1E 6BT, England.;UCL, Dept Chem, London WC1E 6BT, England..
    Rossmeisl, Jan
    Univ Copenhagen, Dept Chem, Univ Pk 5, DK-2100 Copenhagen, Denmark..
    Shen, Huaze
    Peking Univ, Int Ctr Quantum Mat, Beijing 100871, Peoples R China.;Peking Univ, Sch Phys, Beijing 100871, Peoples R China..
    Tocci, Gabriele
    UCL, London Ctr Nanotechnol, Thomas Young Ctr, Dept Phys & Astron, London WC1E 6BT, England.;UCL, Dept Chem, London WC1E 6BT, England.;Ecole Polytech Fed Lausanne, Sch Engn, Inst Bioengn & Mat Sci & Engn, Lab Fundamental BioPhoton,Lab Computat Sci & Mode, CH-1015 Lausanne, Switzerland.;Ecole Polytech Fed Lausanne, Lausanne Ctr Ultrafast Sci, CH-1015 Lausanne, Switzerland..
    Tyrode, Eric
    KTH Royal Inst Technol, Dept Chem, S-10044 Stockholm, Sweden..
    Walz, Marie-Madeleine
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Molecular and condensed matter physics. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Werner, Josephina
    Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Molecular and condensed matter physics. Swedish Univ Agr Sci, Dept Chem & Biotechnol, Box 7015, S-75007 Uppsala, Sweden..
    Bluhm, Hendrik
    Lawrence Berkeley Natl Lab, Div Chem Sci, Berkeley, CA 94720 USA..
    Water at Interfaces2016In: Chemical Reviews, ISSN 0009-2665, E-ISSN 1520-6890, Vol. 116, no 13, p. 7698-7726Article, review/survey (Refereed)
    Abstract [en]

    The interfaces of neat water and aqueous solutions play a prominent role in many technological processes and in the environment. Examples of aqueous interfaces are ultrathin water films that cover most hydrophilic surfaces under ambient relative humidities, the liquid/solid interface which drives many electrochemical reactions, and the liquid/vapor interface, which governs the uptake and release of trace gases by the oceans and cloud droplets. In this article we review some of the recent experimental and theoretical advances in our knowledge of the properties of aqueous interfaces and discuss open questions and gaps in our understanding.

  • 25.
    Borroto-Escuela, Dasiel O.
    et al.
    Karolinska Inst, Dept Neurosci, Retzius Vag 8, S-17177 Stockholm, Sweden;Univ Urbino Carlo Bo, Dept Biomol Sci, I-61029 Urbino, Italy;Observ Cubano Neurociencias, Grp Bohio Estudio, Zaya 50, Yaguajay 62100, Cuba.
    Narvaez, Manuel
    Univ Malaga, Inst Invest Biomed Malaga, Fac Med, E-29071 Malaga, Spain.
    Ambrogini, Patrizia
    Univ Urbino Carlo Bo, Dept Biomol Sci, I-61029 Urbino, Italy.
    Ferraro, Luca
    Univ Ferrara, SVEB, Dept Life Sci & Biotechnol, I-44121 Ferrara, Italy.
    Brito, Ismel
    Karolinska Inst, Dept Neurosci, Retzius Vag 8, S-17177 Stockholm, Sweden;Observ Cubano Neurociencias, Grp Bohio Estudio, Zaya 50, Yaguajay 62100, Cuba.
    Romero Fernandez, Wilber
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Andrade-Talavera, Yuniesky
    Karolinska Inst, Dept Neurobiol Care Sci & Soc, Ctr Alzheimer Res, Neuronal Oscillat Lab, S-17177 Stockholm, Sweden.
    Flores-Burgess, Antonio
    Univ Malaga, Inst Invest Biomed Malaga, Fac Med, E-29071 Malaga, Spain.
    Millon, Carmelo
    Univ Malaga, Inst Invest Biomed Malaga, Fac Med, E-29071 Malaga, Spain.
    Gago, Belen
    Univ Malaga, Inst Invest Biomed Malaga, Fac Med, E-29071 Malaga, Spain.
    Angel Narvaez, Jose
    Univ Malaga, Inst Invest Biomed Malaga, Fac Med, E-29071 Malaga, Spain.
    Odagaki, Yuji
    Saitama Med Univ, Dept Psychiat, Saitama 3388570, Japan.
    Palkovits, Miklos
    Semmelweis Univ, Fac Med, Dept Anat Histol & Embryol, H-1094 Budapest, Hungary.
    Diaz-Cabiale, Zaida
    Univ Malaga, Inst Invest Biomed Malaga, Fac Med, E-29071 Malaga, Spain.
    Fuxe, Kjell
    Karolinska Inst, Dept Neurosci, Retzius Vag 8, S-17177 Stockholm, Sweden.
    Receptor-Receptor Interactions in Multiple 5-HT1A Heteroreceptor Complexes in Raphe-Hippocampal 5-HT Transmission and Their Relevance for Depression and Its Treatment2018In: Molecules, ISSN 1420-3049, E-ISSN 1420-3049, Vol. 23, no 6, article id 1341Article, review/survey (Refereed)
    Abstract [en]

    Due to the binding to a number of proteins to the receptor protomers in receptor heteromers in the brain, the term "heteroreceptor complexes" was introduced. A number of serotonin 5-HT1A heteroreceptor complexes were recently found to be linked to the ascending 5-HT pathways known to have a significant role in depression. The 5-HT1A-FGFR1 heteroreceptor complexes were involved in synergistically enhancing neuroplasticity in the hippocampus and in the dorsal raphe 5-HT nerve cells. The 5-HT1A protomer significantly increased FGFR1 protomer signaling in wild-type rats. Disturbances in the 5-HT1A-FGFR1 heteroreceptor complexes in the raphe-hippocampal 5-HT system were found in a genetic rat model of depression (Flinders sensitive line (FSL) rats). Deficits in FSL rats were observed in the ability of combined FGFR1 and 5-HT1A agonist cotreatment to produce antidepressant-like effects. It may in part reflect a failure of FGFR1 treatment to uncouple the 5-HT1A postjunctional receptors and autoreceptors from the hippocampal and dorsal raphe GIRK channels, respectively. This may result in maintained inhibition of hippocampal pyramidal nerve cell and dorsal raphe 5-HT nerve cell firing. Also, 5-HT1A-5-HT2A isoreceptor complexes were recently demonstrated to exist in the hippocampus and limbic cortex. They may play a role in depression through an ability of 5-HT2A protomer signaling to inhibit the 5-HT1A protomer recognition and signaling. Finally, galanin (1-15) was reported to enhance the antidepressant effects of fluoxetine through the putative formation of GalR1-GalR2-5-HT1A heteroreceptor complexes. Taken together, these novel 5-HT1A receptor complexes offer new targets for treatment of depression.

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  • 26.
    Borroto-Escuela, Dasiel O.
    et al.
    Karolinska Inst, Dept Neurosci, Biomed, Stockholm, Sweden; Univ Urbino, Dept Biomol Sci, Sect Physiol, Campus Sci Enrico Mattei, Urbino, Italy; Grp Bohio Estudio, Observ Cubano Neurociencias, Yaguajay, Cuba.
    Narváez, Manuel
    Univ Malaga, Inst Invest Biomed Malaga, Fac Med, Malaga, Spain.
    Romero Fernández, Wilber
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Pinton, Luca
    Karolinska Inst, Dept Neurosci, Biomed, Stockholm, Sweden.
    Wydra, Karolina
    Polish Acad Sci, Inst Pharmacol, Dept Drug Addict Pharmacol, Krakow, Poland.
    Filip, Malgorzata
    Polish Acad Sci, Inst Pharmacol, Dept Drug Addict Pharmacol, Krakow, Poland.
    Beggiato, Sarah
    Univ Ferrara, Dept Life Sci & Biotechnol SVEB, Ferrara, Italy.
    Tanganelli, Sergio
    Univ Ferrara, Dept Life Sci & Biotechnol SVEB, Ferrara, Italy.
    Ferraro, Luca
    Univ Ferrara, Dept Life Sci & Biotechnol SVEB, Ferrara, Italy.
    Fuxe, Kjell
    Karolinska Inst, Dept Neurosci, Biomed, Stockholm, Sweden.
    Acute Cocaine Enhances Dopamine D2R Recognition and Signaling and Counteracts D2R Internalization in Sigma1R-D2R Heteroreceptor Complexes2019In: Molecular Neurobiology, ISSN 0893-7648, E-ISSN 1559-1182, Vol. 56, no 10, p. 7045-7055Article in journal (Refereed)
    Abstract [en]

    The current study was performed to establish the actions of nanomolar concentrations of cocaine, not blocking the dopamine transporter, on dopamine D2 receptor (D2R)-sigma 1 receptor (delta 1R) heteroreceptor complexes and the D2R protomer recognition, signaling and internalization in cellular models. We report the existence of D2R-delta 1R heteroreceptor complexes in subcortical limbic areas as well as the dorsal striatum, with different distribution patterns using the in situ proximity ligation assay. Also, through BRET, these heteromers were demonstrated in HEK293 cells. Furthermore, saturation binding assay demonstrated that in membrane preparations of HEK293 cells coexpressing D2R and delta 1R, cocaine (1 nM) significantly increased the D2R B-max values over cells singly expressing D2R. CREB reporter luc-gene assay indicated that coexpressed delta 1R significantly reduced the potency of the D2R-like agonist quinpirole to inhibit via D2R activation the forskolin induced increase of the CREB signal. In contrast, the addition of 100 nM cocaine was found to markedly increase the quinpirole potency to inhibit the forskolin-induced increase of the CREB signal in the D2R-delta 1R cells. These events were associated with a marked reduction of cocaine-induced internalization of D2R protomers in D2R-delta 1R heteromer-containing cells vs D2R singly expressing cells as studied by means of confocal analysis of D2R-delta 1R trafficking and internalization. Overall, the formation of D2R-delta 1R heteromers enhanced the ability of cocaine to increase the D2R protomer function associated with a marked reduction of its internalization. The existence of D2R-delta 1R heteromers opens up a new understanding of the acute actions of cocaine.

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  • 27.
    Borroto-Escuela, Dasiel O.
    et al.
    Karolinska Inst, Dept Neurosci, Stockholm, Sweden.
    Rodriguez, David
    Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Stockholm, Sweden.
    Romero Fernandez, Wilber
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Kapla, Jon
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Jaiteh, Mariama
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Ranganathan, Anirudh
    Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, Stockholm, Sweden.
    Lazarova, Tzvetana
    Autonomous Univ Barcelona, Fac Med, Dept Biochem & Mol Biol, Inst Neurosci, Barcelona, Spain.
    Fuxe, Kjell
    Karolinska Inst, Dept Neurosci, Stockholm, Sweden.