Literature DB >> 16471897

Optimization of the GB/SA solvation model for predicting the structure of surface loops in proteins.

Agnieszka Szarecka1, Hagai Meirovitch.   

Abstract

Implicit solvation models are commonly optimized with respect to experimental data or Poisson-Boltzmann (PB) results obtained for small molecules, where the force field is sometimes not considered. In previous studies, we have developed an optimization procedure for cyclic peptides and surface loops in proteins based on the entire system studied and the specific force field used. Thus, the loop has been modeled by the simplified solvation function E(tot) = E(FF) (epsilon = 2r) + Sigma(i) sigma(i)A(i), where E(FF) (epsilon = nr) is the AMBER force field energy with a distance-dependent dielectric function, epsilon = nr, A(i) is the solvent accessible surface area of atom i, and sigma(i) is its atomic solvation parameter. During the optimization process, the loop is free to move while the protein template is held fixed in its X-ray structure. To improve on the results of this model, in the present work we apply our optimization procedure to the physically more rigorous solvation model, the generalized Born with surface area (GB/SA) (together with the all-atom AMBER force field) as suggested by Still and co-workers (J. Phys. Chem. A 1997, 101, 3005). The six parameters of the GB/SA model, namely, P(1)-P(5) and the surface area parameter, sigma (programmed in the TINKER package) are reoptimized for a "training" group of nine loops, and a best-fit set is defined from the individual sets of optimized parameters. The best-fit set and Still's original set of parameters (where Lys, Arg, His, Glu, and Asp are charged or neutralized) were applied to the training group as well as to a "test" group of seven loops, and the energy gaps and the corresponding RMSD values were calculated. These GB/SA results based on the three sets of parameters have been found to be comparable; surprisingly, however, they are somewhat inferior (e.g, of larger energy gaps) to those obtained previously from the simplified model described above. We discuss recent results for loops obtained by other solvation models and potential directions for future studies.

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Year:  2006        PMID: 16471897      PMCID: PMC1945207          DOI: 10.1021/jp055771+

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  87 in total

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Authors:  A E García; K Y Sanbonmatsu
Journal:  Proteins       Date:  2001-02-15

2.  A critical analysis of continuum electrostatics: the screened Coulomb potential--implicit solvent model and the study of the alanine dipeptide and discrimination of misfolded structures of proteins.

Authors:  Sergio A Hassan; Ernest L Mehler
Journal:  Proteins       Date:  2002-04-01

3.  Solvation parameters for predicting the structure of surface loops in proteins: transferability and entropic effects.

Authors:  Bedamati Das; Hagai Meirovitch
Journal:  Proteins       Date:  2003-05-15

4.  Free energy surfaces of beta-hairpin and alpha-helical peptides generated by replica exchange molecular dynamics with the AGBNP implicit solvent model.

Authors:  Anthony K Felts; Yuichi Harano; Emilio Gallicchio; Ronald M Levy
Journal:  Proteins       Date:  2004-08-01

5.  A hierarchical approach to all-atom protein loop prediction.

Authors:  Matthew P Jacobson; David L Pincus; Chaya S Rapp; Tyler J F Day; Barry Honig; David E Shaw; Richard A Friesner
Journal:  Proteins       Date:  2004-05-01

6.  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

7.  Prediction of the folding of short polypeptide segments by uniform conformational sampling.

Authors:  R E Bruccoleri; M Karplus
Journal:  Biopolymers       Date:  1987-01       Impact factor: 2.505

Review 8.  Modeling mutations and homologous proteins.

Authors:  A Sali
Journal:  Curr Opin Biotechnol       Date:  1995-08       Impact factor: 9.740

9.  Comparison of systematic search and database methods for constructing segments of protein structure.

Authors:  K Fidelis; P S Stern; D Bacon; J Moult
Journal:  Protein Eng       Date:  1994-08

Review 10.  Computer simulation of the free energy of peptides with the local states method: analogues of gonadotropin releasing hormone in the random coil and stable states.

Authors:  H Meirovitch; S C Koerber; J E Rivier; A T Hagler
Journal:  Biopolymers       Date:  1994-07       Impact factor: 2.505

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  3 in total

1.  Minimalist explicit solvation models for surface loops in proteins.

Authors:  Ronald P White; Hagai Meirovitch
Journal:  J Chem Theory Comput       Date:  2006       Impact factor: 6.006

2.  Use of decoys to optimize an all-atom force field including hydration.

Authors:  Yelena A Arnautova; Harold A Scheraga
Journal:  Biophys J       Date:  2008-05-23       Impact factor: 4.033

3.  Exploring the binding of BACE-1 inhibitors using comparative binding energy analysis (COMBINE).

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  3 in total

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