Literature DB >> 26626678

Efficient Generalized Born Models for Monte Carlo Simulations.

Julien Michel1, Richard D Taylor1, Jonathan W Essex1.   

Abstract

The Generalized Born Surface Area theory (GBSA) has become a popular method to model the solvation of biomolecules. While efficient in the context of molecular dynamics simulations, GBSA calculations do not integrate well with Monte Carlo simulations because of the nonlocal nature of the Generalized Born energy. We present a method by which Monte Carlo Generalized Born simulations can be made seven to eight times faster on a protein-ligand binding free energy calculation with little or no loss of accuracy. The method can be employed in any type of Monte Carlo or Hybrid Monte Carlo-molecular dynamics simulation and should prove useful in numerous applications.

Year:  2006        PMID: 26626678     DOI: 10.1021/ct600069r

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  7 in total

Review 1.  Prediction of protein-ligand binding affinity by free energy simulations: assumptions, pitfalls and expectations.

Authors:  Julien Michel; Jonathan W Essex
Journal:  J Comput Aided Mol Des       Date:  2010-05-28       Impact factor: 3.686

Review 2.  Open source molecular modeling.

Authors:  Somayeh Pirhadi; Jocelyn Sunseri; David Ryan Koes
Journal:  J Mol Graph Model       Date:  2016-07-30       Impact factor: 2.518

3.  Efficient equilibrium sampling of all-atom peptides using library-based Monte Carlo.

Authors:  Ying Ding; Artem B Mamonov; Daniel M Zuckerman
Journal:  J Phys Chem B       Date:  2010-05-06       Impact factor: 2.991

4.  Tunable, mixed-resolution modeling using library-based Monte Carlo and graphics processing units.

Authors:  Artem B Mamonov; Steven Lettieri; Ying Ding; Jessica L Sarver; Rohith Palli; Timothy F Cunningham; Sunil Saxena; Daniel M Zuckerman
Journal:  J Chem Theory Comput       Date:  2012-06-15       Impact factor: 6.006

5.  Automated sampling assessment for molecular simulations using the effective sample size.

Authors:  Xin Zhang; Divesh Bhatt; Daniel M Zuckerman
Journal:  J Chem Theory Comput       Date:  2010-09-01       Impact factor: 6.006

6.  Prediction of the water content in protein binding sites.

Authors:  Julien Michel; Julian Tirado-Rives; William L Jorgensen
Journal:  J Phys Chem B       Date:  2009-10-08       Impact factor: 2.991

7.  Binding Modes of Ligands Using Enhanced Sampling (BLUES): Rapid Decorrelation of Ligand Binding Modes via Nonequilibrium Candidate Monte Carlo.

Authors:  Samuel C Gill; Nathan M Lim; Patrick B Grinaway; Ariën S Rustenburg; Josh Fass; Gregory A Ross; John D Chodera; David L Mobley
Journal:  J Phys Chem B       Date:  2018-03-12       Impact factor: 2.991

  7 in total

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