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The proposal that enzymatic catalysis is due to conformational fluctuations has been previously promoted by means of indirect considerations. However, recent works have focused on cases where the relevant motions have components toward distinct conformational regions, whose population could be manipulated by mutations. In particular, a recent work has claimed to provide direct experimental evidence for a dynamical contribution to catalysis in dihydrofolate reductase, where blocking a relevant conformational coordinate was related to the suppression of the motion toward the occluded conformation. The present work utilizes computer simulations to elucidate the true molecular basis for the experimentally observed effect. We start by reproducing the trend in the measured change in catalysis upon mutations (which was assumed to arise as a result of a "dynamical knockout" caused by the mutations). This analysis is performed by calculating the change in the corresponding activation barriers without the need to invoke dynamical effects. We then generate the catalytic landscape of the enzyme and demonstrate that motions in the conformational space do not help drive catalysis. We also discuss the role of flexibility and conformational dynamics in catalysis, once again demonstrating that their role is negligible and that the largest contribution to catalysis arises from electrostatic preorganization. Finally, we point out that the changes in the reaction potential surface modify the reorganization free energy (which includes entropic effects), and such changes in the surface also alter the corresponding motion. However, this motion is never the reason for catalysis, but rather simply a reflection of the shape of the reaction potential surface.

An important mechanism for generation of new genes is by duplication-divergence of existing genes. Duplication-divergence includes several different sub-models, such as subfunctionalization where after accumulation of neutral mutations the original function is distributed between two partially functional and complementary genes, and neofunctionalization where a new function evolves in one of the duplicated copies while the old function is maintained in another copy. The likelihood of these mechanisms depends on the longevity of the duplicated state, which in turn depends on the fitness cost and genetic stability of the duplications. Here, we determined the fitness cost and stability of defined gene duplications/amplifications on a low copy number plasmid. Our experimental results show that the costs of carrying extra gene copies are substantial and that each additional kbp of DNA reduces fitness by approximately 0.15%. Furthermore, gene amplifications are highly unstable and rapidly segregate to lower copy numbers in absence of selection. Mathematical modelling shows that the fitness costs and instability strongly reduces the likelihood of both sub- and neofunctionalization, but that these effects can be off-set by positive selection for novel beneficial functions.

Nanofluidic channels have become a versatile tool to manipulate single DNA molecules. They allow investigation of confined single DNA molecules from a fundamental polymer physics perspective as well as for example in DNA barcoding techniques.

The wealth of structural and biochemical data now available for protein synthesis on the ribosome presents major new challenges for computational biochemistry. Apart from technical difficulties in modeling ribosome systems, the complexity of the overall translation cycle with a multitude of different kinetic steps presents a formidable problem for computational efforts where we have only seen the beginning. However, a range of methodologies including molecular dynamics simulations, free energy calculations, molecular docking and quantum chemical approaches have already been put to work with promising results. In particular, the combined efforts of structural biology, biochemistry, kinetics and computational modeling can lead towards a quantitative structure-based description of translation.

Background: A(3)AR antagonists are promising drug candidates as neuroprotective agents as well as for the treatment of inflammation or glaucoma. The most widely known A(3)AR antagonists are derived from polyheteroaromatic scaffolds, which usually show poor pharmacokinetic properties. Accordingly, the identification of structurally simple A(3)AR antagonists by the exploration of novel diversity spaces is a challenging goal. Results: A convergent and efficient Ugi-based multicomponent approach enabled the discovery of pyrazin-2(1H)-ones as a novel class of A(3)AR antagonists. A combined experimental/computational strategy accelerated the establishment of the most salient features of the structure-activity and structure-selectivity relationships in this series. Conclusion: The optimization process provided pyrazin-2(1H)-ones with improved affinity and a plausible hypothesis regarding their binding modes was proposed.

A gene for membrane-integral inorganic pyrophosphatase (miPPase) was found in the composite genome of the extremophile archaeon Candidatus Korarchaeum cryptofilum (CKc). This korarchaeal genome shows unusual partial similarity to both major archaeal phyla Crenarchaeota and Euryarchaeota. Thus this Korarchaeote might have retained features that represent an ancestral archaeal form, existing before the occurrence of the evolutionary bifurcation into Crenarchaeota and Euryarchaeota. In addition, CKc lacks five genes that are common to early genomes at the LUCA border. These two properties independently suggest a pre-LUCA evolutionary position of this extremophile. Our finding of the miPPase gene in the CKc genome points to a role for the enzyme in the energy conversion of this very early archaeon. The structural features of its miPPase indicate that it can pump protons through membranes. An miPPase from the extremophile bacterium Caldicellulosiruptor saccharolyticus also has a sequence indicating a proton pump. Recent analysis of the three-dimensional structure of the miPPase from Vigna radiata has resulted in the recognition of a strongly acidic substrate (orthophosphate: Pi, pyrophosphate: PPi) binding pocket, containing 11 Asp and one Glu residues. Asp (aspartic acid) is an evolutionarily very early proteinaceous amino acid as compared to the later appearing Glu (glutamic acid). All the Asp residues are conserved in the miPPase of CKc, V. radiata and other miPPases. The high proportion of Asp, as compared to Glu, seems to strengthen our argument that biological energy conversion with binding and activities of orthophosphate (Pi) and energy-rich pyrophosphate (PPi) in connection with the origin and early evolution of life may have started with similar or even more primitive acidic peptide funnels and/or pockets.

BackgroundA detailed genotype-phenotype evaluation is presented by studying the enzyme activities of five rare amino acid substitutions (Arg233Gly, Ala265Ser, Arg341Trp, Arg366Cys and Met473Ile) identified in the CYP21A2 gene in patients investigated for Congenital adrenal hyperplasia (CAH). ObjectiveTo investigate whether the mutations identified in the CYP21A2 gene are disease causing and to establish a gradient for the degree of enzyme impairment to improve prediction of patient phenotype. Design and patientsThe CYP21A2 genes of seven patients investigated for CAH were sequenced and five mutations were identified. The mutant proteins were expressed in vitro in COS-1 cells, and the enzyme activities towards the two natural substrates were determined to verify the disease-causing state of the mutations. The in vitro activities of these rare mutations were also compared with the activities of four mutations known to cause nonclassic CAH (Pro30Leu, Val281Leu, Pro453Ser and Pro482Ser) in addition to an in silico structural evaluation of the novel mutants. Main outcome measureTo verify the disease-causing state of novel mutations. ResultsFive CYP21A2 mutations were identified (Arg233Gly, Ala265Ser, Arg341Trp, Arg366Cys and Met473Ile). All mutant proteins exhibited enzyme activities above 5%, and four mutations were classified as nonclassic and one as a normal variant. By comparing the investigated protein changes with four common mutations causing nonclassic CAH, a gradient for the degree of enzyme impairment could be established. Studying rare mutations in CAH increases our knowledge regarding the molecular mechanisms that render a mutation pathogenic. It also improves phenotype predictions and genetic counselling for future generations.

Vesicular stomatitis virus expressing Zaire Ebola virus (EBOV) glycoprotein (VSV Delta G/EBOVgp) could be used as a vaccine to meet the 2014 Ebola virus outbreak. To characterize the host response to this vaccine, we used mRNA sequencing to analyze peripheral blood mononuclear cells (PBMCs) from cynomolgus macaques after VSV Delta G/EBOVgp immunization and subsequent EBOV challenge. We found a controlled transcriptional response that transitioned to immune regulation as the EBOV was cleared. This observation supports the safety of the vaccine.

Pathology resulting from human immunodeficiency virus (HIV) infection is driven by protracted inflammation; the primary loss of CD4(+) T cells is caused by activation-driven apoptosis. Recent studies of nonhuman primates (NHPs) have suggested that during the acute phase of infection, antiviral mucosal immunity restricts viral replication in the primary infection compartment. These studies imply that HIV achieves systemic infection as a consequence of a failure in host antiviral immunity. Here, we used high-dose intrarectal inoculation of rhesus macaques with simian immunodeficiency virus (SIV) SIVmac251 to examine how the mucosal immune system is overcome by SIV during acute infection. The host response in rectal mucosa was characterized by deep mRNA sequencing (mRNA-seq) at 3 and 12 days postinoculation (dpi) in 4 animals for each time point. While we observed a strong host transcriptional response at 3 dpi, functions relating to antiviral immunity were absent. Instead, we observed a significant number of differentially expressed genes relating to cell adhesion and reorganization of the cytoskeleton. We also observed downregulation of genes encoding members of the claudin family of cell adhesion molecules, which are coexpressed with genes associated with pathology in the colorectal mucosa, and a large number of noncoding transcripts. In contrast, at 12 dpi the differentially expressed genes were enriched in those involved with immune system functions, in particular, functions relating to T cells, B cells, and NK cells. Our findings indicate that host responses that negatively affect mucosal integrity occur before inflammation. Consequently, when inflammation is activated at peak viremia, mucosal integrity is already compromised, potentially enabling rapid tissue damage, driving further inflammation. IMPORTANCE The HIV pandemic is one of the major threats to human health, causing over a million deaths per year. Recent studies have suggested that mucosal antiviral immune responses play an important role in preventing systemic infection after exposure to the virus. Yet, despite their potential role in decreasing transmission rates between individuals, these antiviral mechanisms are poorly understood. Here, we carried out the first deep mRNA sequencing analysis of mucosal host responses in the primary infection compartment during acute SIV infection. We found that during acute infection, a significant host response was mounted in the mucosa before inflammation was triggered. Our analysis indicated that the response has a detrimental effect on tissue integrity, causing increased permeability, tissue damage, and recruitment of SIV target cells. These results emphasize the importance of mucosal host responses preceding immune activation in preventing systemic SIV infection.

Enzymes are tremendously proficient catalysts, which can be used as extracellular catalysts for a whole host of processes, from chemical synthesis to the generation of novel biofuels. For them to be more amenable to the needs of biotechnology, however, it is often necessary to be able to manipulate their physico-chemical properties in an efficient and streamlined manner, and, ideally, to be able to train them to catalyze completely new reactions. Recent years have seen an explosion of interest in different approaches to achieve this, both in the laboratory, and in silico. There remains, however, a gap between current approaches to computational enzyme design, which have primarily focused on the early stages of the design process, and laboratory evolution, which is an extremely powerful tool for enzyme redesign, but will always be limited by the vastness of sequence space combined with the low frequency for desirable mutations. This review discusses different approaches towards computational enzyme design and demonstrates how combining newly developed screening approaches that can rapidly predict potential mutation “hotspots” with approaches that can quantitatively and reliably dissect the catalytic step can bridge the gap that currently exists between computational enzyme design and laboratory evolution studies.

Over the past 40 years, it has been demonstrated that many enzymes are capable of promiscuous catalytic activities, facilitating the turnover of more than one chemically distinct substrate. This has been argued to play an important role in enzyme evolution, with highly promiscuous progenitor enzymes evolving under evolutionary pressure to modern day specialists, while still retaining some level of their former promiscuous activities¹. This theory has been extensively tested by different experiments using in vitro evolution². The alkaline phosphatase superfamily members provide a particularly attractive showcase for studying enzyme promiscuity, as they often show reciprocal promiscuity, in that the native reaction for one member is often a side-reaction for another³. While deceptively similar, their catalyzed reactions (cleavage of P-O and S-O bonds) proceed via distinct transition states and protonation requirements^4,5. We present detailed computational studies of the promiscuous catalytic activity of three evolutionarily related members: the arylsulfatase from Pseudomonas aeruginosa⁶, and the phosphonate monoester hydrolases from Burkholderia caryophili⁷and Rhizobium leguminosarum⁸. By tracking their structural and electrostatic features, and comparing to other known members of the superfamily, we provide an atomic-level map for functional evolution within this superfamily.

Density functional theory calculations were applied to investigate (13)C chemical shielding tensors in cryptolepine and its bromo-substituted analogs, 2-bromocryptolepine and 2,7-dibromocryptolepine. The fact that bromo-substituted cryptolepine shows higher antiplasmodial activity than cryptolepine raises the question of whether this effect can be related to the electronic properties around carbon atoms. The results show that changes to the principal components of the shielding tensors upon substitution are significant. In particular, sigma (33) is the most affected tensor for carbons in the substituted ring, which could be related to the increased antiplasmodial activity of bromosubstituted cryptolepine. The analyses were also focused on atomic charges and dipole moment.

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.

Time-resolved X-ray solution scattering is an increasingly popular method to measure conformational changes in proteins. Extracting structural information from the resulting difference X-ray scattering data is a daunting task. We present a method in which the limited but precious information encoded in such scattering curves is combined with the chemical knowledge of molecular force fields. The molecule of interest is then refined toward experimental data using molecular dynamics simulation. Therefore, the energy landscape is biased toward conformations that agree with experimental data. We describe and verify the method, and we provide an implementation in GROMACS.

As we gain increased understanding of genetic disorders and gene regulation more focus has turned towards complex interactions. Combinations of genes or gene and environmental factors have been suggested to explain the missing heritability behind complex diseases. Furthermore, gene activation and splicing seem to be governed by a complex machinery of histone modification (HM), transcription factor (TF), and DNA sequence signals. This thesis aimed to apply and develop multivariate machine learning methods for use on such biological problems. Monte Carlo feature selection was combined with rule-based classification to identify interactions between HMs and to study the interplay of factors with importance for asthma and allergy.

Firstly, publicly available ChIP-seq data (Paper I) for 38 HMs was studied. We trained a classifier for predicting exon inclusion levels based on the HMs signals. We identified HMs important for splicing and illustrated that splicing could be predicted from the HM patterns. Next, we applied a similar methodology on data from two large birth cohorts describing asthma and allergy in children (Paper II). We identified genetic and environmental factors with importance for allergic diseases which confirmed earlier results and found candidate gene-gene and gene-environment interactions.

In order to interpret and present the classifiers we developed Ciruvis, a web-based tool for network visualization of classification rules (Paper III). We applied Ciruvis on classifiers trained on both simulated and real data and compared our tool to another methodology for interaction detection using classification. Finally, we continued the earlier study on epigenetics by analyzing HM and TF signals in genes with or without evidence of bidirectional transcription (Paper IV). We identified several HMs and TFs with different signals between unidirectional and bidirectional genes. Among these, the CTCF TF was shown to have a well-positioned peak 60-80 bp upstream of the transcription start site in unidirectional genes.