Literature DB >> 24123494

Extending RosettaDock with water, sugar, and pH for prediction of complex structures and affinities for CAPRI rounds 20-27.

Krishna Praneeth Kilambi1, Michael S Pacella, Jianqing Xu, Jason W Labonte, Justin R Porter, Pravin Muthu, Kevin Drew, Daisuke Kuroda, Ora Schueler-Furman, Richard Bonneau, Jeffrey J Gray.   

Abstract

Rounds 20-27 of the Critical Assessment of PRotein Interactions (CAPRI) provided a testing platform for computational methods designed to address a wide range of challenges. The diverse targets drove the creation of and new combinations of computational tools. In this study, RosettaDock and other novel Rosetta protocols were used to successfully predict four of the 10 blind targets. For example, for DNase domain of Colicin E2-Im2 immunity protein, RosettaDock and RosettaLigand were used to predict the positions of water molecules at the interface, recovering 46% of the native water-mediated contacts. For α-repeat Rep4-Rep2 and g-type lysozyme-PliG inhibitor complexes, homology models were built and standard and pH-sensitive docking algorithms were used to generate structures with interface RMSD values of 3.3 Å and 2.0 Å, respectively. A novel flexible sugar-protein docking protocol was also developed and used for structure prediction of the BT4661-heparin-like saccharide complex, recovering 71% of the native contacts. Challenges remain in the generation of accurate homology models for protein mutants and sampling during global docking. On proteins designed to bind influenza hemagglutinin, only about half of the mutations were identified that affect binding (T55: 54%; T56: 48%). The prediction of the structure of the xylanase complex involving homology modeling and multidomain docking pushed the limits of global conformational sampling and did not result in any successful prediction. The diversity of problems at hand requires computational algorithms to be versatile; the recent additions to the Rosetta suite expand the capabilities to encompass more biologically realistic docking problems.
Copyright © 2013 Wiley Periodicals, Inc.

Entities:  

Keywords:  CAPRI; binding; protein docking; protein interactions

Mesh:

Substances:

Year:  2013        PMID: 24123494      PMCID: PMC4037910          DOI: 10.1002/prot.24425

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  51 in total

1.  The Protein Data Bank.

Authors:  H M Berman; J Westbrook; Z Feng; G Gilliland; T N Bhat; H Weissig; I N Shindyalov; P E Bourne
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  CAPRI: a Critical Assessment of PRedicted Interactions.

Authors:  Joël Janin; Kim Henrick; John Moult; Lynn Ten Eyck; Michael J E Sternberg; Sandor Vajda; Ilya Vakser; Shoshana J Wodak
Journal:  Proteins       Date:  2003-07-01

3.  Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations.

Authors:  Jeffrey J Gray; Stewart Moughon; Chu Wang; Ora Schueler-Furman; Brian Kuhlman; Carol A Rohl; David Baker
Journal:  J Mol Biol       Date:  2003-08-01       Impact factor: 5.469

4.  An efficient hybrid explicit/implicit solvent method for biomolecular simulations.

Authors:  Michael S Lee; Freddie R Salsbury; Mark A Olson
Journal:  J Comput Chem       Date:  2004-12       Impact factor: 3.376

5.  Structure of the ultra-high-affinity colicin E2 DNase--Im2 complex.

Authors:  Justyna Aleksandra Wojdyla; Sarel J Fleishman; David Baker; Colin Kleanthous
Journal:  J Mol Biol       Date:  2012-01-27       Impact factor: 5.469

6.  Templates are available to model nearly all complexes of structurally characterized proteins.

Authors:  Petras J Kundrotas; Zhengwei Zhu; Joël Janin; Ilya A Vakser
Journal:  Proc Natl Acad Sci U S A       Date:  2012-05-29       Impact factor: 11.205

7.  Toward high-resolution de novo structure prediction for small proteins.

Authors:  Philip Bradley; Kira M S Misura; David Baker
Journal:  Science       Date:  2005-09-16       Impact factor: 47.728

8.  FunHunt: model selection based on energy landscape characteristics.

Authors:  Nir London; Ora Schueler-Furman
Journal:  Biochem Soc Trans       Date:  2008-12       Impact factor: 5.407

9.  Lattice Microbes: high-performance stochastic simulation method for the reaction-diffusion master equation.

Authors:  Elijah Roberts; John E Stone; Zaida Luthey-Schulten
Journal:  J Comput Chem       Date:  2012-09-25       Impact factor: 3.376

10.  The SWISS-MODEL Repository and associated resources.

Authors:  Florian Kiefer; Konstantin Arnold; Michael Künzli; Lorenza Bordoli; Torsten Schwede
Journal:  Nucleic Acids Res       Date:  2008-10-18       Impact factor: 16.971

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  12 in total

1.  Efficient flexible backbone protein-protein docking for challenging targets.

Authors:  Nicholas A Marze; Shourya S Roy Burman; William Sheffler; Jeffrey J Gray
Journal:  Bioinformatics       Date:  2018-10-15       Impact factor: 6.937

2.  Toward the computational design of protein crystals with improved resolution.

Authors:  Jeliazko R Jeliazkov; Aaron C Robinson; Bertrand García-Moreno E; James M Berger; Jeffrey J Gray
Journal:  Acta Crystallogr D Struct Biol       Date:  2019-11-01       Impact factor: 7.652

3.  Residue-centric modeling and design of saccharide and glycoconjugate structures.

Authors:  Jason W Labonte; Jared Adolf-Bryfogle; William R Schief; Jeffrey J Gray
Journal:  J Comput Chem       Date:  2016-11-30       Impact factor: 3.376

4.  PDEδ Binding to Ras Isoforms Provides a Route to Proper Membrane Localization.

Authors:  Serena Muratcioglu; Hyunbum Jang; Attila Gursoy; Ozlem Keskin; Ruth Nussinov
Journal:  J Phys Chem B       Date:  2017-06-07       Impact factor: 2.991

5.  Modeling oblong proteins and water-mediated interfaces with RosettaDock in CAPRI rounds 28-35.

Authors:  Nicholas A Marze; Jeliazko R Jeliazkov; Shourya S Roy Burman; Scott E Boyken; Frank DiMaio; Jeffrey J Gray
Journal:  Proteins       Date:  2016-10-24

6.  Protein-RNA complexes and efficient automatic docking: expanding RosettaDock possibilities.

Authors:  Adrien Guilhot-Gaudeffroy; Christine Froidevaux; Jérôme Azé; Julie Bernauer
Journal:  PLoS One       Date:  2014-09-30       Impact factor: 3.240

7.  Protein-protein docking with dynamic residue protonation states.

Authors:  Krishna Praneeth Kilambi; Kavan Reddy; Jeffrey J Gray
Journal:  PLoS Comput Biol       Date:  2014-12-11       Impact factor: 4.475

8.  OncoBinder facilitates interpretation of proteomic interaction data by capturing coactivation pairs in cancer.

Authors:  Samya Van Coillie; Lunxi Liang; Yao Zhang; Huanbin Wang; Jing-Yuan Fang; Jie Xu
Journal:  Oncotarget       Date:  2016-04-05

Review 9.  Protocols for Molecular Modeling with Rosetta3 and RosettaScripts.

Authors:  Brian J Bender; Alberto Cisneros; Amanda M Duran; Jessica A Finn; Darwin Fu; Alyssa D Lokits; Benjamin K Mueller; Amandeep K Sangha; Marion F Sauer; Alexander M Sevy; Gregory Sliwoski; Jonathan H Sheehan; Frank DiMaio; Jens Meiler; Rocco Moretti
Journal:  Biochemistry       Date:  2016-08-16       Impact factor: 3.162

10.  Structure-based cross-docking analysis of antibody-antigen interactions.

Authors:  Krishna Praneeth Kilambi; Jeffrey J Gray
Journal:  Sci Rep       Date:  2017-08-15       Impact factor: 4.379

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