uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Computational Modelling in Drug Discovery: Application of Structure-Based Drug Design, Conformal Prediction and Evaluation of Virtual Screening
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Organic Pharmaceutical Chemistry. (Anders Karlèn, Mats Larhed)ORCID iD: 0000-0002-4420-772X
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Structure-based drug design and virtual screening are areas of computational medicinal chemistry that use 3D models of target proteins. It is important to develop better methods in this field with the aim of increasing the speed and quality of early stage drug discovery.

The first part of this thesis focuses on the application of structure-based drug design in the search for inhibitors for the protein 1-deoxy-D-xylulose-5-phosphate reductoisomerase (DXR), one of the enzymes in the DOXP/MEP synthetic pathway. This pathway is found in many bacteria (such as Mycobacterium tuberculosis) and in the parasite Plasmodium falciparum.

In order to evaluate and improve current virtual screening methods, a benchmarking data set was constructed using publically available high-throughput screening data. The exercise highlighted a number of problems with current data sets as well as with the use of publically available high-throughput screening data. We hope this work will help guide further development of well designed benchmarking data sets for virtual screening methods.

Conformal prediction is a new method in the computer-aided drug design toolbox that gives the prediction range at a specified level of confidence for each compound. To demonstrate the versatility and applicability of this method we derived models of skin permeability using two different machine learning methods; random forest and support vector machines.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2017. , p. 47
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 235
Keywords [en]
drug discovery, docking, virtual screening, tuberculosis, conformal prediction
National Category
Medicinal Chemistry
Identifiers
URN: urn:nbn:se:uu:diva-328505ISBN: 978-91-513-0049-8 (print)OAI: oai:DiVA.org:uu-328505DiVA, id: diva2:1135858
Public defence
2017-10-13, B/B42, Husargatan 3, Uppsala, 09:00 (English)
Opponent
Supervisors
Available from: 2017-09-21 Created: 2017-08-24 Last updated: 2018-01-13
List of papers
1. Design, Synthesis, and X-ray Crystallographic Studies of alpha-Aryl Substituted Fosmidomycin Analogues as Inhibitors of Mycobacterium tuberculosis 1-Deoxy-D-xylulose 5-Phosphate Reductoisomerase
Open this publication in new window or tab >>Design, Synthesis, and X-ray Crystallographic Studies of alpha-Aryl Substituted Fosmidomycin Analogues as Inhibitors of Mycobacterium tuberculosis 1-Deoxy-D-xylulose 5-Phosphate Reductoisomerase
Show others...
2011 (English)In: Journal of Medicinal Chemistry, ISSN 0022-2623, E-ISSN 1520-4804, Vol. 54, no 14, p. 4964-4976Article in journal (Refereed) Published
Abstract [en]

The natural antibiotic fosmidomycin acts via inhibition of 1-deoxy-D-xylulose 5-phosphate reductoisomerase (DXR), an essential enzyme in the non-mevalonate pathway of isoprenoid biosynthesis. Fosmidomycin is active on Mycobacterium tuberculosis DXR (MtDXR), but it lacks antibacterial activity probably because of poor uptake. alpha-Aryl substituted fosmidomycin analogues have more favorable physicochemical properties and are also more active in inhibiting malaria parasite growth. We have solved crystal structures of MtDXR in complex with 3,4-dichlorophenyl substituted fosmidomycin analogues; these show important differences compared to our previously described forsmidomycin-DXR complex. Our best inhibitor has an IC(50) = 0.15 mu M on MtDXR but still lacked activity in a mycobacterial growth assay (MIC > 32 mu g/mL). The combined results, however, provide insights into how DXR accommodates the new inhibitors and serve as an excellent starting point for the design of other novel and more potent inhibitors, particularly against pathogens where uptake is less of a problem, such as the malaria parasite.

National Category
Biochemistry and Molecular Biology Other Basic Medicine
Identifiers
urn:nbn:se:uu:diva-156614 (URN)10.1021/jm2000085 (DOI)000292892300003 ()21678907 (PubMedID)
Available from: 2011-08-07 Created: 2011-08-04 Last updated: 2018-01-12Bibliographically approved
2. Substitution of the phosphonic acid and hydroxamic acid functionalities of the DXR inhibitor FR900098: An attempt to improve the activity against Mycobacterium tuberculosis
Open this publication in new window or tab >>Substitution of the phosphonic acid and hydroxamic acid functionalities of the DXR inhibitor FR900098: An attempt to improve the activity against Mycobacterium tuberculosis
Show others...
2011 (English)In: Bioorganic & Medicinal Chemistry Letters, ISSN 0960-894X, E-ISSN 1090-2120, Vol. 21, no 18, p. 5403-5407Article in journal (Refereed) Published
Abstract [en]

Two series of FR900098/fosmidomycin analogs were synthesized and evaluated for MtDXR inhibition and Mycobacterium tuberculosis whole-cell activity. The design rationale of these compounds involved the exchange of either the phosphonic acid or the hydroxamic acid part for alternative acidic and metal-coordinating functionalities. The best inhibitors provided IC(50) values in the micromolar range, with a best value of 41 mu M.

Keywords
Tuberculosis, DXR, Enzyme inhibitor, Fosmidomycin, FR900098
National Category
Chemical Sciences
Identifiers
urn:nbn:se:uu:diva-158288 (URN)10.1016/j.bmcl.2011.07.005 (DOI)000294051800057 ()
Available from: 2011-09-07 Created: 2011-09-06 Last updated: 2017-12-08
3. DXR Inhibition by Potent Mono- and Disubstituted Fosmidomycin Analogues
Open this publication in new window or tab >>DXR Inhibition by Potent Mono- and Disubstituted Fosmidomycin Analogues
Show others...
2013 (English)In: Journal of Medicinal Chemistry, ISSN 0022-2623, E-ISSN 1520-4804, Vol. 56, no 15, p. 6190-6199Article in journal (Refereed) Published
Abstract [en]

The antimalarial compound fosmidomycin targets DXR, the enzyme that catalyzes the first committed step in the MEP pathway producing the universally essential isoprenoid precursors, isopentenyl diphosphate and dimethylallyl diphosphate. The MEP pathway is used by a number of pathogens, including Mycobacterium tuberculosis and apicomplexan parasites, and differs from the classical mevalonate pathway that is essential in humans. Using a structure-based approach, we designed a number of analogues of fosmidomycin, including a series that are substituted in both the Cα and the hydroxamate positions. The latter proved to be a stable framework for the design of inhibitors that extend from the cramped substrate-binding site and can, for the first time, bridge the substrate and cofactor binding sites. A number of these compounds are more potent than fosmidomycin in terms of killing Plasmodium falciparum in an in vitro assay; the best has an IC50 of 40 nM.

Keywords
Mycobacterium tuberculosis, 1-deoxy-D-xylulose 5-phosphate reductoisomerase, DXR
National Category
Structural Biology
Research subject
Biology with specialization in Structural Biology; Medicinal Chemistry
Identifiers
urn:nbn:se:uu:diva-196616 (URN)10.1021/jm4006498 (DOI)000323082400015 ()
Funder
Swedish Foundation for Strategic Research Swedish Research Council
Note

De tre (3) första författarna delar förstaförfattarskapet.

Available from: 2013-03-11 Created: 2013-03-11 Last updated: 2017-12-06Bibliographically approved
4. Toward a Benchmarking Data Set Able to Evaluate Ligand- and Structure-based Virtual Screening Using Public HTS Data
Open this publication in new window or tab >>Toward a Benchmarking Data Set Able to Evaluate Ligand- and Structure-based Virtual Screening Using Public HTS Data
Show others...
2015 (English)In: Journal of Chemical Information and Modeling, ISSN 1549-9596, Vol. 55, no 2, p. 343-353Article in journal (Refereed) Published
Abstract [en]

Virtual screening has the potential to accelerate and reduce costs of probe development and drug discovery. To develop and benchmark virtual screening methods, validation data sets are commonly used. Over the years, such data sets have been constructed to overcome the problems of analogue bias and artificial enrichment. With the rapid growth of public domain databases containing high-throughput screening data, such as the PubChem BioAssay database, there is an increased possibility to use such data for validation. In this study, we identify PubChem data sets suitable for validation of both structure- and ligand-based virtual screening methods. To achieve this, high-throughput screening data for which a crystal structure of the bioassay target was available in the PDB were identified. Thereafter, the data sets were inspected to identify structures and data suitable for use in validation studies. In this work, we present seven data sets (MMP13, DUSP3, PTPN22, EPHX2, CTDSP1, MAPK10, and CDK5) compiled using this method. In the seven data sets, the number of active compounds varies between 19 and 369 and the number of inactive compounds between 59 405 and 337 634. This gives a higher ratio of the number of inactive to active compounds than what is found in most benchmark data sets. We have also evaluated the screening performance using docking and 3D shape similarity with default settings. To characterize the data sets, we used physicochemical similarity and 2D fingerprint searches. We envision that these data sets can be a useful complement to current data sets used for method evaluation.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2015
National Category
Structural Biology Pharmaceutical Chemistry
Research subject
Chemistry with specialization in Bioorganic Chemistry
Identifiers
urn:nbn:se:uu:diva-248018 (URN)10.1021/ci5005465 (DOI)000349943100014 ()25564966 (PubMedID)
Available from: 2015-03-26 Created: 2015-03-26 Last updated: 2018-03-05Bibliographically approved
5. Predicting the Rate of Skin Penetration Using an Aggregated Conformal Prediction Framework
Open this publication in new window or tab >>Predicting the Rate of Skin Penetration Using an Aggregated Conformal Prediction Framework
2017 (English)In: Molecular Pharmaceutics, ISSN 1543-8384, E-ISSN 1543-8392, Vol. 14, no 5, p. 1571-1576Article in journal (Refereed) Published
Abstract [en]

Skin serves as a drug administration route, and skin permeability of chemicals is of significant interest in the pharmaceutical and cosmetic industries. An aggregated conformal prediction (ACP) framework was used to build models, for predicting the permeation rate (log K-p) of chemical compounds through human skin. The conformal prediction method gives as an output the prediction range at a given level of confidence for each compound, which enables the user to make a more informed decision when, for example, suggesting the next compound to prepare, Predictive models were built using;both the random forest and the support vector machine methods and were based on experimentally derived permeability data on 211 diverse compounds. The derived models were of similar predictive quality as compared to earlier published models but have the extra advantage of not only presenting a single predicted value for each, compound but also a reliable, individually assigned prediction range. The models use calculated descriptors and can quickly predict the skin permeation rate of new compounds.

Keywords
conformal prediction, skin penetration nonconformist, Scikit Learn, random forest, Support vector machines
National Category
Basic Medicine
Identifiers
urn:nbn:se:uu:diva-323448 (URN)10.1021/acs.molpharmaceut.7b00007 (DOI)000400633300024 ()28335598 (PubMedID)
Available from: 2017-07-04 Created: 2017-07-04 Last updated: 2018-01-13Bibliographically approved

Open Access in DiVA

fulltext(850 kB)512 downloads
File information
File name FULLTEXT01.pdfFile size 850 kBChecksum SHA-512
b1452dac23f9b91e79ef38b8011840ddff5296787ea8f02ca144456cebd00e60268d051cf4937f14c290952703ef6d4f6738e8fc52f76d0f7e2358aebf9d919c
Type fulltextMimetype application/pdf
Buy this publication >>

Search in DiVA

By author/editor
Lindh, Martin
By organisation
Organic Pharmaceutical Chemistry
Medicinal Chemistry

Search outside of DiVA

GoogleGoogle Scholar
Total: 512 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 812 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf