mCSM-AB: a web server for predicting antibody-antigen affinity changes upon mutation with graph-based signatures.

Computational methods have traditionally struggled to predict the effect of mutations in antibody-antigen complexes on binding affinity. This has limited their usefulness during antibody engineering and development, and their ability to predict biologically relevant escape mutations. Here we present mCSM-AB, a user-friendly web server for accurately predicting antibody-antigen affinity changes upon mutation which relies on graph-based signatures. We show that mCSM-AB performs better than comparable methods that have been previously used for antibody engineering. mCSM-AB web server is available at http://structure.bioc.cam.ac.uk/mcsm_ab.This is the final published version. It first appeared at http://nar.oxfordjournals.org/content/early/2016/05/23/nar.gkw458.full

Known allosteric proteins have central roles in genetic disease

Allostery is a form of protein regulation, where ligands that bind sites located apart from the active site can modify the activity of the protein. The molecular mechanisms of allostery have been extensively studied, because allosteric sites are less conserved than active sites, and drugs targeting them are more specific than drugs binding the active sites. Here we quantify the importance of allostery in genetic disease. We show that 1) known allosteric proteins are central in disease networks, and contribute to genetic disease and comorbidities much more than non-allosteric proteins, in many major disease types like hematopoietic diseases, cardiovascular diseases, cancers, diabetes, or diseases of the central nervous system. 2) variants from cancer genome-wide association studies are enriched near allosteric proteins, indicating their importance to polygenic traits; and 3) the importance of allosteric proteins in disease is due, at least partly, to their central positions in protein-protein interaction networks, and probably not due to their dynamical properties

Flexibility and small pockets at protein-protein interfaces: New insights into druggability.

The transient assembly of multiprotein complexes mediates many aspects of cell regulation and signalling in living organisms. Modulation of the formation of these complexes through targeting protein-protein interfaces can offer greater selectivity than the inhibition of protein kinases, proteases or other post-translational regulatory enzymes using substrate, co-factor or transition state mimetics. However, capitalising on protein-protein interaction interfaces as drug targets has been hindered by the nature of interfaces that tend to offer binding sites lacking the well-defined large cavities of classical drug targets. In this review we posit that interfaces formed by concerted folding and binding (disorder-to-order transitions on binding) of one partner and other examples of interfaces where a protein partner is bound through a continuous epitope from a surface-exposed helix, flexible loop or chain extension may be more tractable for the development of "orthosteric", competitive chemical modulators; these interfaces tend to offer small-volume but deep pockets and/or larger grooves that may be bound tightly by small chemical entities. We discuss examples of such protein-protein interaction interfaces for which successful chemical modulators are being developed.We thank our colleagues Alicia Higueruelo, Douglas Pires, Bernardo Ochoa and Chris Radoux for helpful comments and discussions. D.B.A is the recipient of a C. J. Martin Research Fellowship from the National Health and Medical Research Council of Australia (APP1072476). H.J. is supported by a CASE Studentship from the UCB and the Biotechnology and Biological Sciences Research Council (BBSRC) (Grant: BB/J500574/1). T.L.B. receives funding from University of Cambridge and The Wellcome Trust for facilities and support.This is the accepted manuscript of a paper published in Progress in Biophysics and Molecular Biology (Jubb H, Blundell TL, Ascher DB, Progress in Biophysics and Molecular Biology 2015, doi:10.1016/j.pbiomolbio.2015.01.009). The final version is available at http://dx.doi.org/10.1016/j.pbiomolbio.2015.01.009

Modeling planar degenerate wetting and anchoring in nematic liquid crystals

We propose a simple surface potential favoring the planar degenerate anchoring of nematic liquid crystals, i.e., the tendency of the molecules to align parallel to one another along any direction parallel to the surface. We show that, at lowest order in the tensorial Landau-de Gennes order-parameter, fourth-order terms must be included. We analyze the anchoring and wetting properties of this surface potential. In the nematic phase, we find the desired degenerate planar anchoring, with positive scalar order-parameter and some surface biaxiality. In the isotropic phase, we find, in agreement with experiments, that the wetting layer may exhibit a uniaxial ordering with negative scalar order-parameter. For large enough anchoring strength, this negative ordering transits towards the planar degenerate state

mCSM-lig: quantifying the effects of mutations on protein-small molecule affinity in genetic disease and emergence of drug resistance.

The ability to predict how a mutation affects ligand binding is an essential step in understanding, anticipating and improving the design of new treatments for drug resistance, and in understanding genetic diseases. Here we present mCSM-lig, a structure-guided computational approach for quantifying the effects of single-point missense mutations on affinities of small molecules for proteins. mCSM-lig uses graph-based signatures to represent the wild-type environment of mutations, and small-molecule chemical features and changes in protein stability as evidence to train a predictive model using a representative set of protein-ligand complexes from the Platinum database. We show our method provides a very good correlation with experimental data (up to ρ = 0.67) and is effective in predicting a range of chemotherapeutic, antiviral and antibiotic resistance mutations, providing useful insights for genotypic screening and to guide drug development. mCSM-lig also provides insights into understanding Mendelian disease mutations and as a tool for guiding protein design. mCSM-lig is freely available as a web server at http://structure.bioc.cam.ac.uk/mcsm_lig.Newton Fund RCUK-CONFAP Grant awarded by The Medical Research Council (MRC) and Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) [MR/M026302/1 to D.E.V.P, T.L.B. and D.B.A.]. René Rachou Research Center (CPqRR/FIOCRUZ Minas), Brazil [to D.E.V.P.]; NHMRC CJ Martin Fellowship [APP1072476 to D.B.A.]; University of Cambridge and The Wellcome Trust for facilities and support [to T.L.B.].This is the final version of the article. It first appeared from Nature Publishing Group at http://dx.doi.org/10.1038/srep29575

pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Using Graph-Based Signatures.

Drug development has a high attrition rate, with poor pharmacokinetic and safety properties a significant hurdle. Computational approaches may help minimize these risks. We have developed a novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development. pkCSM performs as well or better than current methods. A freely accessible web server (http://structure.bioc.cam.ac.uk/pkcsm), which retains no information submitted to it, provides an integrated platform to rapidly evaluate pharmacokinetic and toxicity properties.Newton Fund RCUK-CONFAP grant awarded by The Medical Research Council (MRC) and Fundac a o de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG) [to D.E.V.P., T.L.B,. and D.B.A.]; Conselho Nacional de Desenvolvimento Cienti fi co e Tecnolo gico (CNPq), and Centro de Pesquisas Rene Rachou (CPqRR/FIOCRUZ Minas), Brazil [to D.E.V.P.]; NHMRC CJ Martin Fellowship [APP1072476 to D.B.A.]; University of Cambridge and The Wellcome Trust for facilities and support [to T.L.B.]. Funding for open access charge: The Wellcome Trust.This is the final version. It was first published by ACS at http://pubs.acs.org/doi/abs/10.1021/acs.jmedchem.5b00104

Spherically symmetric Yang-Mills solutions in a (4+n)- dimensional space-time

We consider the Einstein-Yang-Mills Lagrangian in a (4+n)-dimensional space-time. Assuming the matter and metric fields to be independent of the n extra coordinates, a spherical symmetric Ansatz for the fields leads to a set of coupled ordinary differential equations. We find that for n > 1 only solutions with either one non-zero Higgs field or with all Higgs fields constant exist. We construct the analytic solutions which fulfill this conditions for arbitrary n, namely the Einstein-Maxwell-dilaton solutions. We also present generic solutions of the effective 4-dimensional Einstein-Yang-Mills-Higgs-dilaton model, which possesses n Higgs triplets coupled in a specific way to n independent dilaton fields. These solutions are the abelian Einstein-Maxwell- dilaton solutions and analytic non-abelian solutions, which have diverging Higgs fields. In addition, we construct numerically asymptotically flat and finite energy solutions for n=2.Comment: 15 Latex pages, 4 eps figures; v2: discussion of results revisite

DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach.

Cancer genome and other sequencing initiatives are generating extensive data on non-synonymous single nucleotide polymorphisms (nsSNPs) in human and other genomes. In order to understand the impacts of nsSNPs on the structure and function of the proteome, as well as to guide protein engineering, accurate in silicomethodologies are required to study and predict their effects on protein stability. Despite the diversity of available computational methods in the literature, none has proven accurate and dependable on its own under all scenarios where mutation analysis is required. Here we present DUET, a web server for an integrated computational approach to study missense mutations in proteins. DUET consolidates two complementary approaches (mCSM and SDM) in a consensus prediction, obtained by combining the results of the separate methods in an optimized predictor using Support Vector Machines (SVM). We demonstrate that the proposed method improves overall accuracy of the predictions in comparison with either method individually and performs as well as or better than similar methods. The DUET web server is freely and openly available at http://structure.bioc.cam.ac.uk/duet

DynaMut: predicting the impact of mutations on protein conformation, flexibility and stability.

Proteins are highly dynamic molecules, whose function is intrinsically linked to their molecular motions. Despite the pivotal role of protein dynamics, their computational simulation cost has led to most structure-based approaches for assessing the impact of mutations on protein structure and function relying upon static structures. Here we present DynaMut, a web server implementing two distinct, well established normal mode approaches, which can be used to analyze and visualize protein dynamics by sampling conformations and assess the impact of mutations on protein dynamics and stability resulting from vibrational entropy changes. DynaMut integrates our graph-based signatures along with normal mode dynamics to generate a consensus prediction of the impact of a mutation on protein stability. We demonstrate our approach outperforms alternative approaches to predict the effects of mutations on protein stability and flexibility (P-value < 0.001), achieving a correlation of up to 0.70 on blind tests. DynaMut also provides a comprehensive suite for protein motion and flexibility analysis and visualization via a freely available, user friendly web server at http://biosig.unimelb.edu.au/dynamut/