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Sequence co-evolution gives 3D contacts and structures of protein complexes

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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.

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Journal ArticleDOI

The HADDOCK2.2 Web Server: User-Friendly Integrative Modeling of Biomolecular Complexes.

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

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

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
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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

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, +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.
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