Literature DB >> 28318014

"Solvent hydrogen-bond occlusion": A new model of polar desolvation for biomolecular energetics.

Andrea Bazzoli1,2, John Karanicolas1,3,4.   

Abstract

Water engages in two important types of interactions near biomolecules: it forms ordered "cages" around exposed hydrophobic regions, and it participates in hydrogen bonds with surface polar groups. Both types of interaction are critical to biomolecular structure and function, but explicitly including an appropriate number of solvent molecules makes many applications computationally intractable. A number of implicit solvent models have been developed to address this problem, many of which treat these two solvation effects separately. Here, we describe a new model to capture polar solvation effects, called SHO ("solvent hydrogen-bond occlusion"); our model aims to directly evaluate the energetic penalty associated with displacing discrete first-shell water molecules near each solute polar group. We have incorporated SHO into the Rosetta energy function, and find that scoring protein structures with SHO provides superior performance in loop modeling, virtual screening, and protein structure prediction benchmarks. These improvements stem from the fact that SHO accurately identifies and penalizes polar groups that do not participate in hydrogen bonds, either with solvent or with other solute atoms ("unsatisfied" polar groups). We expect that in future, SHO will enable higher-resolution predictions for a variety of molecular modeling applications.
© 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Entities:  

Keywords:  Rosetta energy function; hydration thermodynamics; implicit solvation

Mesh:

Substances:

Year:  2017        PMID: 28318014      PMCID: PMC5407913          DOI: 10.1002/jcc.24740

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  61 in total

1.  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

2.  Structural and energetic consequences of disruptive mutations in a protein core.

Authors:  W A Lim; D C Farruggio; R T Sauer
Journal:  Biochemistry       Date:  1992-05-05       Impact factor: 3.162

3.  Protein-protein docking with backbone flexibility.

Authors:  Chu Wang; Philip Bradley; David Baker
Journal:  J Mol Biol       Date:  2007-08-02       Impact factor: 5.469

4.  Role of the active-site solvent in the thermodynamics of factor Xa ligand binding.

Authors:  Robert Abel; Tom Young; Ramy Farid; Bruce J Berne; Richard A Friesner
Journal:  J Am Chem Soc       Date:  2008-02-12       Impact factor: 15.419

5.  Hydrophobic interactions and hydrogen bonds in β-sheet formation.

Authors:  Chitra Narayanan; Cristiano L Dias
Journal:  J Chem Phys       Date:  2013-09-21       Impact factor: 3.488

6.  Atomic interactions and profile of small molecules disrupting protein-protein interfaces: the TIMBAL database.

Authors:  Alícia P Higueruelo; Adrian Schreyer; G Richard J Bickerton; Will R Pitt; Colin R Groom; Tom L Blundell
Journal:  Chem Biol Drug Des       Date:  2009-11       Impact factor: 2.817

7.  Conformer generation with OMEGA: learning from the data set and the analysis of failures.

Authors:  Paul C D Hawkins; Anthony Nicholls
Journal:  J Chem Inf Model       Date:  2012-11-12       Impact factor: 4.956

8.  Close agreement between the orientation dependence of hydrogen bonds observed in protein structures and quantum mechanical calculations.

Authors:  Alexandre V Morozov; Tanja Kortemme; Kiril Tsemekhman; David Baker
Journal:  Proc Natl Acad Sci U S A       Date:  2004-04-26       Impact factor: 11.205

9.  Structural properties of non-traditional drug targets present new challenges for virtual screening.

Authors:  Ragul Gowthaman; Eric J Deeds; John Karanicolas
Journal:  J Chem Inf Model       Date:  2013-08-13       Impact factor: 4.956

10.  Improvements to robotics-inspired conformational sampling in rosetta.

Authors:  Amelie Stein; Tanja Kortemme
Journal:  PLoS One       Date:  2013-05-21       Impact factor: 3.240

View more
  1 in total

1.  The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design.

Authors:  Rebecca F Alford; Andrew Leaver-Fay; Jeliazko R Jeliazkov; Matthew J O'Meara; Frank P DiMaio; Hahnbeom Park; Maxim V Shapovalov; P Douglas Renfrew; Vikram K Mulligan; Kalli Kappel; Jason W Labonte; Michael S Pacella; Richard Bonneau; Philip Bradley; Roland L Dunbrack; Rhiju Das; David Baker; Brian Kuhlman; Tanja Kortemme; Jeffrey J Gray
Journal:  J Chem Theory Comput       Date:  2017-05-12       Impact factor: 6.006

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.