Dataset Information

SWISS-MODEL: homology modelling of protein structures and complexes.

ABSTRACT: Homology modelling has matured into an important technique in structural biology, significantly contributing to narrowing the gap between known protein sequences and experimentally determined structures. Fully automated workflows and servers simplify and streamline the homology modelling process, also allowing users without a specific computational expertise to generate reliable protein models and have easy access to modelling results, their visualization and interpretation. Here, we present an update to the SWISS-MODEL server, which pioneered the field of automated modelling 25 years ago and been continuously further developed. Recently, its functionality has been extended to the modelling of homo- and heteromeric complexes. Starting from the amino acid sequences of the interacting proteins, both the stoichiometry and the overall structure of the complex are inferred by homology modelling. Other major improvements include the implementation of a new modelling engine, ProMod3 and the introduction a new local model quality estimation method, QMEANDisCo. SWISS-MODEL is freely available at https://swissmodel.expasy.org.

SUBMITTER: Waterhouse A

PROVIDER: S-EPMC6030848 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

SWISS-MODEL: homology modelling of protein structures and complexes.

Waterhouse Andrew A Bertoni Martino M Bienert Stefan S Studer Gabriel G Tauriello Gerardo G Gumienny Rafal R Heer Florian T FT de Beer Tjaart A P TAP Rempfer Christine C Bordoli Lorenza L Lepore Rosalba R Schwede Torsten T

Nucleic acids research 20180701 W1

Homology modelling has matured into an important technique in structural biology, significantly contributing to narrowing the gap between known protein sequences and experimentally determined structures. Fully automated workflows and servers simplify and streamline the homology modelling process, also allowing users without a specific computational expertise to generate reliable protein models and have easy access to modelling results, their visualization and interpretation. Here, we present an ...[more]

PMID: 29788355

Similar Datasets

Project description:BACKGROUND: Structure-based computational methods are needed to help identify and characterize protein-protein complexes and their function. For individual proteins, the most successful technique is homology modelling. We investigate a simple extension of this technique to protein-protein complexes. We consider a large set of complexes of known structures, involving pairs of single-domain proteins. The complexes are compared with each other to establish their sequence and structural similarities and the relation between the two. Compared to earlier studies, a simpler dataset, a simpler structural alignment procedure, and an additional energy criterion are used. Next, we compare the Xray structures to models obtained by threading the native sequence onto other, homologous complexes. An elementary requirement for a successful energy function is to rank the native structure above any threaded structure. We use the DFIREbeta energy function, whose quality and complexity are typical of the models used today. Finally, we compare near-native models to distinctly non-native models. RESULTS: If weakly stable complexes are excluded (defined by a binding energy cutoff), as well as a few unusual complexes, a simple homology principle holds: complexes that share more than 35% sequence identity share similar structures and interaction modes; this principle was less clearcut in earlier studies. The energy function was then tested for its ability to identify experimental structures among sets of decoys, produced by a simple threading procedure. On average, the experimental structure is ranked above 92% of the alternate structures. Thus, discrimination of the native structure is good but not perfect. The discrimination of near-native structures is fair. Typically, a single, alternate, non-native binding mode exists that has a native-like energy. Some of the associated failures may correspond to genuine, alternate binding modes and/or native complexes that are artefacts of the crystal environment. In other cases, additional model filtering with more sophisticated tools is needed. CONCLUSION: The results suggest that the simple modelling procedure applied here could help identify and characterize protein-protein complexes. The next step is to apply it on a genomic scale.

Project description:Electron transfer reactions are essential for life because they underpin oxidative phosphorylation and photosynthesis, processes leading to the generation of ATP, and are involved in many reactions of intermediary metabolism. Key to these roles is the formation of transient inter-protein electron transfer complexes. The structural basis for the control of specificity between partner proteins is lacking because these weak transient complexes have remained largely intractable for crystallographic studies. Inter-protein electron transfer processes are central to all of the key steps of denitrification, an alternative form of respiration in which bacteria reduce nitrate or nitrite to N2 through the gaseous intermediates nitric oxide (NO) and nitrous oxide (N2O) when oxygen concentrations are limiting. The one-electron reduction of nitrite to NO, a precursor to N2O, is performed by either a haem- or copper-containing nitrite reductase (CuNiR) where they receive an electron from redox partner proteins a cupredoxin or a c-type cytochrome. Here we report the structures of the newly characterized three-domain haem-c-Cu nitrite reductase from Ralstonia pickettii (RpNiR) at 1.01?Å resolution and its M92A and P93A mutants. Very high resolution provides the first view of the atomic detail of the interface between the core trimeric cupredoxin structure of CuNiR and the tethered cytochrome c domain that allows the enzyme to function as an effective self-electron transfer system where the donor and acceptor proteins are fused together by genomic acquisition for functional advantage. Comparison of RpNiR with the binary complex of a CuNiR with a donor protein, AxNiR-cytc551 (ref. 6), and mutagenesis studies provide direct evidence for the importance of a hydrogen-bonded water at the interface in electron transfer. The structure also provides an explanation for the preferential binding of nitrite to the reduced copper ion at the active site in RpNiR, in contrast to other CuNiRs where reductive inactivation occurs, preventing substrate binding.

Dataset Information

SWISS-MODEL: homology modelling of protein structures and complexes.

Publications

SWISS-MODEL: homology modelling of protein structures and complexes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets