Sequence co-evolution gives 3D contacts and structures of protein complexes
Thomas A. Hopf,Charlotta P I Schärfe,Charlotta P I Schärfe,João P. G. L. M. Rodrigues,Anna G. Green,Oliver Kohlbacher,Chris Sander,Alexandre M. J. J. Bonvin,Debora S. Marks +8 more
Reads0
Chats0
TLDR
Analysis of correlated evolutionary sequence changes across proteins identifies residues that are close in space with sufficient accuracy to determine the three-dimensional structure of the protein complexes, and predicts protein–protein contacts in 32 complexes of unknown structure.Abstract:
DNA is often referred to as the ‘blueprint of life’, as this molecule contains the instructions that are required to build a living organism from a single cell. But these instructions largely play out through the proteins that DNA encodes; and most proteins do not work alone. Instead they come together in different combinations, or complexes, and a single protein may participate in many complexes with different activities. Proteins are so small that it is difficult to get clear information about what they look like. Visualizing protein complexes is even harder. Most protein–protein interactions remain poorly understood, even in the best-studied organisms such as humans, yeast, and bacteria. Proteins are made from smaller molecules, called amino acids, strung together one after the other. The order in which different amino acids are arranged in a protein determines the protein’s shape and ultimately its function. Like DNA, protein sequences can change over time. Sometimes, the sequence of one protein changes in a way that prevents it binding to another protein. If these two proteins must work together for an organism to survive, the second protein will often develop a compensating change that allows the protein–protein complex to reform. Identifying pairs of changes in the sequences of pairs of proteins suggests that the two proteins interact and gives some information about how the proteins fit together. Different species can have copies of the same proteins that have slightly different sequences. Since the DNA sequences from many different organisms are already known, there are now many opportunities to find sites in pairs of proteins that have evolved together, or co-evolved, over time. To find sites that seem to have co-evolved, Hopf et al. used a computer program based on an approach from statistical physics to look at pairs of proteins that were already known to form complexes. Co-evolving sites were found in over 300 pairs of proteins; including 76 where the structure of the complex was already known. When sites that were predicted to be co-evolving were then mapped to these known complex structures, the co-evolving sites were remarkably close to the true protein–protein contacts. This indicates that the information from the co-evolved sequences is sufficient to show how two proteins fit together. Hopf et al. then turned their attention to 82 pairs of proteins that were thought to interact, but where a structure was unavailable. For 32 of these pairs, structures of the entire complex could be predicted, showing how the two proteins might interact. Furthermore, when other researchers subsequently worked out the structure of one of these complexes, the prediction was a good match to the solved complex structure. The machinery of life is largely made up of proteins, which must interact in ever-changing but precise ways. The new methods developed by Hopf et al. provide a new way to discover and investigate the details of these interactions.read more
Citations
More filters
Journal ArticleDOI
SWISS-MODEL: homology modelling of protein structures and complexes.
Andrew Waterhouse,Andrew Waterhouse,Martino Bertoni,Martino Bertoni,Stefan Bienert,Stefan Bienert,Gabriel Studer,Gabriel Studer,Gerardo Tauriello,Gerardo Tauriello,Rafal Gumienny,Rafal Gumienny,Florian T Heer,Florian T Heer,Tjaart A. P. de Beer,Tjaart A. P. de Beer,Christine Rempfer,Christine Rempfer,Lorenza Bordoli,Lorenza Bordoli,Rosalba Lepore,Rosalba Lepore,Torsten Schwede,Torsten Schwede +23 more
TL;DR: An update to the SWISS-MODEL server is presented, which includes the implementation of a new modelling engine, ProMod3, and the introduction a new local model quality estimation method, QMEANDisCo.
Journal ArticleDOI
The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular Complexes.
G. C. P. van Zundert,João P. G. L. M. Rodrigues,Mikael Trellet,Christophe Schmitz,Panagiotis L. Kastritis,Ezgi Karaca,Adrien S. J. Melquiond,M. van Dijk,S.J. de Vries,Alexandre M. J. J. Bonvin +9 more
TL;DR: The updated version 2.2.2 of the HADDOCK portal is presented, which offers new features such as support for mixed molecule types, additional experimental restraints and improved protocols, all of this in a user-friendly interface.
Posted ContentDOI
Protein complex prediction with AlphaFold-Multimer
Richard Evans,Michael J. O'Neill,Alexander Pritzel,Natasha Antropova,Andrew W. Senior,Tim Green,Augustin Žídek,Russell Bates,Sam Blackwell,Jason Yim,Olaf Ronneberger,Sebastian Bodenstein,Michal Zielinski,Alex Bridgland,Anna Potapenko,Andrew Cowie,Kathryn Tunyasuvunakool,R. D. Jain,Ellen Clancy,Pushmeet Kohli,John M. Jumper,Demis Hassabis +21 more
TL;DR: In this article, an AlphaFold model trained specifically for multimeric inputs of known stoichiometry was proposed, which significantly increases the accuracy of predicted multimimeric interfaces over input-adapted single-chain AlphaFolds.
Journal ArticleDOI
Robust and accurate prediction of residue-residue interactions across protein interfaces using evolutionary information.
TL;DR: It is found that residue pairs identified using a pseudo-likelihood-based method to covary across protein–protein interfaces in the 50S ribosomal unit and 28 additional bacterial protein complexes with known structure are almost always in contact in the complex.
Journal ArticleDOI
Modeling protein quaternary structure of homo- and hetero-oligomers beyond binary interactions by homology
Martino Bertoni,Martino Bertoni,Florian Kiefer,Florian Kiefer,Marco Biasini,Marco Biasini,Lorenza Bordoli,Lorenza Bordoli,Torsten Schwede,Torsten Schwede +9 more
TL;DR: A description of protein-protein interface conservation as a function of evolutionary distance to reduce the noise in deep multiple sequence alignments and a distance measure to structurally compare homologous multimeric protein complexes are defined.
References
More filters
Journal ArticleDOI
Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments
TL;DR: It is shown that database enrichment is improved with proper preparation and that neglecting certain steps of the preparation process produces a systematic degradation in enrichments, which can be large for some targets.
Journal ArticleDOI
IPython: A System for Interactive Scientific Computing
Fernando Perez,Brian E. Granger +1 more
TL;DR: The IPython project as mentioned in this paper provides an enhanced interactive environment that includes, among other features, support for data visualization and facilities for distributed and parallel computation for interactive work and a comprehensive library on top of which more sophisticated systems can be built.
Journal ArticleDOI
HADDOCK: a protein-protein docking approach based on biochemical or biophysical information.
TL;DR: An approach called HADDOCK (High Ambiguity Driven protein-protein Docking) that makes use of biochemical and/or biophysical interaction data such as chemical shift perturbation data resulting from NMR titration experiments or mutagenesis data to drive the docking process.
Journal ArticleDOI
Activities at the Universal Protein Resource (UniProt)
Rolf Apweiler,Alex Bateman,Maria Jesus Martin,Claire O'Donovan,Michele Magrane,Yasmin Alam-Faruque,Emanuele Alpi,Ricardo Antunes,J Arganiska,EB Casanova,Benoit Bely,M Bingley,Carlos Bonilla,Ramona Britto,Borisas Bursteinas,WM Chan,Gayatri Chavali,Elena Cibrian-Uhalte,A Da Silva,M De Giorgi,Tunca Doğan,F. Fazzini,Paul Gane,Leyla Jael Garcia Castro,Penelope Garmiri,Emma Hatton-Ellis,Reija Hieta,Rachael P. Huntley,Duncan Legge,W Liu,Jie Luo,Alistair MacDougall,Prudence Mutowo,Andrew Nightingale,Sandra Orchard,Klemens Pichler,Diego Poggioli,Sangya Pundir,L Pureza,Guoying Qi,S. Rosanoff,Rabie Saidi,Tony Sawford,Aleksandra Shypitsyna,Edd Turner,Volynkin,Tony Wardell,Xavier Watkins,Hermann Zellner,Matthew Corbett,M Donnelly,P van Rensburg,Mickael Goujon,Hamish McWilliam,Rodrigo Lopez,Ioannis Xenarios,Lydie Bougueleret,Alan Bridge,Sylvain Poux,Nicole Redaschi,Lucila Aimo,Andrea H. Auchincloss,Kristian B. Axelsen,Parit Bansal,Delphine Baratin,P-A Binz,M. C. Blatter,Brigitte Boeckmann,Jerven Bolleman,Emmanuel Boutet,Lionel Breuza,C Casal-Casas,E de Castro,Lorenzo Cerutti,Elisabeth Coudert,Béatrice A. Cuche,M Doche,Dolnide Dornevil,Séverine Duvaud,Anne Estreicher,L Famiglietti,M Feuermann,Elisabeth Gasteiger,Sebastien Gehant,Gerritsen,Arnaud Gos,Nadine Gruaz-Gumowski,Ursula Hinz,Chantal Hulo,J. James,Florence Jungo,Guillaume Keller,Lara,P Lemercier,J Lew,Damien Lieberherr,Thierry Lombardot,Xavier D. Martin,Patrick Masson,Anne Morgat,Teresa Batista Neto,Salvo Paesano,Ivo Pedruzzi,Sandrine Pilbout,Monica Pozzato,Manuela Pruess,Catherine Rivoire,Bernd Roechert,Maria Victoria Schneider,Christian J. A. Sigrist,K Sonesson,S Staehli,Andre Stutz,Shyamala Sundaram,Michael Tognolli,Laure Verbregue,A-L Veuthey,Cathy H. Wu,Cecilia N. Arighi,Leslie Arminski,Chuming Chen,Yongxing Chen,John S. Garavelli,Hongzhan Huang,Kati Laiho,Peter B. McGarvey,Darren A. Natale,Baris E. Suzek,C. R. Vinayaka,Qinghua Wang,Yuqi Wang,L-S Yeh,Yerramalla,Jie Zhang +133 more
TL;DR: The mission of the Universal Protein Resource (UniProt) is to provide the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequences and functional annotation.
Journal ArticleDOI
Version 1.2 of the Crystallography and NMR system
TL;DR: An improved model for the treatment of disordered solvent for crystallographic refinement that employs a combined grid search and least-squares optimization of the bulk solvent model parameters is included, resulting in lower R values.