Literature DB >> 10024025

What determines the van der Waals coefficient beta in the LIE (linear interaction energy) method to estimate binding free energies using molecular dynamics simulations?

W Wang1, J Wang, P A Kollman.   

Abstract

Recently a semiempirical method has been proposed by Aqvist et al. to calculate absolute and relative binding free energies. In this method, the absolute binding free energy of a ligand is estimated as deltaGbind = alpha<Vel(bound) - Vel(free)> + beta<Vvdw(bound) - Vvdw(free)>, where Vel(bound) and Vvdw(bound) are the electrostatic and van der Waals interaction energies between the ligand and the solvated protein from an molecular dynamics (MD) trajectory with ligand bound to protein and Vel(free) and Vel(free) and Vvdw(free) are the electrostatic and van der Waals interaction energies between the ligand and the water from an MD trajectory with the ligand in water. A set of values, alpha = 0.5 and beta = 0.16, was found to give results in good agreement with experimental data. Later, however, different optimal values of beta were found in studies of compounds binding to P450cam and avidin. The present work investigates how the optimal value of beta depends on the nature of binding sites for different protein-ligand interactions. By examining seven ligands interacting with five proteins, we have discovered a linear correlation between the value of beta and the weighted non-polar desolvation ratio (WNDR), with a correlation coefficient of 0.96. We have also examined the ability of this correlation to predict optimal values of beta for different ligands binding to a single protein. We studied twelve neutral compounds bound to avidin. In this case, the WNDR approach gave a better estimate of the absolute binding free energies than results obtained using the fixed value of beta found for biotin-avidin. In terms of reproducing the relative binding free energy to biotin, the fixed-beta value gave better results for compounds similar to biotin, but for compounds less similar to biotin, the WNDR approach led to better relative binding free energies.

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Year:  1999        PMID: 10024025

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


  31 in total

1.  Molecular dynamics and free-energy calculations applied to affinity maturation in antibody 48G7.

Authors:  L T Chong; Y Duan; L Wang; I Massova; P A Kollman
Journal:  Proc Natl Acad Sci U S A       Date:  1999-12-07       Impact factor: 11.205

2.  Protein-ligand binding free energy estimation using molecular mechanics and continuum electrostatics. Application to HIV-1 protease inhibitors.

Authors:  V Zoete; O Michielin; M Karplus
Journal:  J Comput Aided Mol Des       Date:  2003-12       Impact factor: 3.686

3.  Trypsin specificity as elucidated by LIE calculations, X-ray structures, and association constant measurements.

Authors:  Hanna-Kirsti Schrøder Leiros; Bjørn Olav Brandsdal; Ole Andreas Andersen; Vibeke Os; Ingar Leiros; Ronny Helland; Jacek Otlewski; Nils Peder Willassen; Arne O Smalås
Journal:  Protein Sci       Date:  2004-04       Impact factor: 6.725

4.  Steered molecular dynamics simulations of ligand-receptor interaction in lipocalins.

Authors:  Janne Kalikka; Jaakko Akola
Journal:  Eur Biophys J       Date:  2010-11-13       Impact factor: 1.733

5.  A combination of docking, QM/MM methods, and MD simulation for binding affinity estimation of metalloprotein ligands.

Authors:  Akash Khandelwal; Viera Lukacova; Dogan Comez; Daniel M Kroll; Soumyendu Raha; Stefan Balaz
Journal:  J Med Chem       Date:  2005-08-25       Impact factor: 7.446

6.  Structure-based model of the stepping motor of PcrA helicase.

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Journal:  Biophys J       Date:  2006-06-30       Impact factor: 4.033

7.  Enantioselective substrate binding in a monooxygenase protein model by molecular dynamics and docking.

Authors:  K Anton Feenstra; Karin Hofstetter; Rolien Bosch; Andreas Schmid; Jan N M Commandeur; Nico P E Vermeulen
Journal:  Biophys J       Date:  2006-08-11       Impact factor: 4.033

8.  Calculation of protein-ligand binding free energy by using a polarizable potential.

Authors:  Dian Jiao; Pavel A Golubkov; Thomas A Darden; Pengyu Ren
Journal:  Proc Natl Acad Sci U S A       Date:  2008-04-21       Impact factor: 11.205

9.  Computational analysis of binding of P1 variants to trypsin.

Authors:  B O Brandsdal; J Aqvist; A O Smalås
Journal:  Protein Sci       Date:  2001-08       Impact factor: 6.725

10.  Molecular dynamics simulations reveal that Tyr-317 phosphorylation reduces Shc binding affinity for phosphotyrosyl residues of epidermal growth factor receptor.

Authors:  Atsushi Suenaga; Mariko Hatakeyama; Anatoly B Kiyatkin; Ravi Radhakrishnan; Makoto Taiji; Boris N Kholodenko
Journal:  Biophys J       Date:  2009-03-18       Impact factor: 4.033

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