Literature DB >> 17429495

Minimalist explicit solvation models for surface loops in proteins.

Ronald P White1, Hagai Meirovitch.   

Abstract

We have performed molecular dynamics simulations of protein surface loops solvated by explicit water, where a prime focus of the study is the small numbers (e.g., ~100) of explicit water molecules employed. The models include only part of the protein (typically 500 - 1000 atoms), and the water molecules are restricted to a region surrounding the loop. In this study, the number of water molecules (N(w)) is systematically varied, and convergence with large N(w) is monitored to reveal N(w)(min), the minimum number required for the loop to exhibit realistic (fully hydrated) behavior. We have also studied protein surface coverage, as well as diffusion and residence times for water molecules as a function of N(w). A number of other modeling parameters are also tested. These include the number of environmental protein atoms explicitly considered in the model, as well as two ways to constrain the water molecules to the vicinity of the loop (where we find one of these methods to perform better when N(w) is small). The results (for RMSD and its fluctuations for four loops) are further compared to much larger, fully solvated systems (using ~10,000 water molecules under periodic boundary conditions and Ewald electrostatics), and to results for the GBSA implicit solvation model. We find that the loop backbone can stabilize with a surprisingly small number of water molecules (as low as 5 molecules per amino acid residue). The side chains of the loop require somewhat larger N(w), where the atomic fluctuations become too small if N(w) is further reduced. Thus, in general, we find adequate hydration to occur at roughly 12 water molecules per residue. This is an important result, because at this hydration level, computational times are comparable to those required for GBSA. Therefore these "minimalist explicit models" can provide a viable and potentially more accurate alternative. The importance of protein loop modeling is discussed in the context of these, and other, loop models, along with other challenges including the relevance of appropriate free energy simulation methodology for assessment of conformational stability.

Entities:  

Year:  2006        PMID: 17429495      PMCID: PMC1851699          DOI: 10.1021/ct0503217

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


  62 in total

1.  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

2.  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

3.  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

4.  Modeling of globular proteins. A distance-based data search procedure for the construction of insertion/deletion regions and Pro----non-Pro mutations.

Authors:  N L Summers; M Karplus
Journal:  J Mol Biol       Date:  1990-12-20       Impact factor: 5.469

5.  Hydration of proteins. A comparison of experimental residence times of water molecules solvating the bovine pancreatic trypsin inhibitor with theoretical model calculations.

Authors:  R M Brunne; E Liepinsh; G Otting; K Wüthrich; W F van Gunsteren
Journal:  J Mol Biol       Date:  1993-06-20       Impact factor: 5.469

6.  Predicting antibody hypervariable loop conformations. II: Minimization and molecular dynamics studies of MCPC603 from many randomly generated loop conformations.

Authors:  R M Fine; H Wang; P S Shenkin; D L Yarmush; C Levinthal
Journal:  Proteins       Date:  1986-12

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

Review 9.  Omega loops: nonregular secondary structures significant in protein function and stability.

Authors:  J S Fetrow
Journal:  FASEB J       Date:  1995-06       Impact factor: 5.191

10.  Evaluation of the conformational free energies of loops in proteins.

Authors:  K C Smith; B Honig
Journal:  Proteins       Date:  1994-02
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  6 in total

1.  Relative stability of the open and closed conformations of the active site loop of streptavidin.

Authors:  Ignacio J General; Hagai Meirovitch
Journal:  J Chem Phys       Date:  2011-01-14       Impact factor: 3.488

2.  Entropy and Free Energy of a Mobile Loop Based on the Crystal Structures of the Free and Bound Proteins.

Authors:  Mihail Mihailescu; Hagai Meirovitch
Journal:  Entropy (Basel)       Date:  2010-08-25       Impact factor: 2.524

Review 3.  Conformational energy range of ligands in protein crystal structures: The difficult quest for accurate understanding.

Authors:  Megan L Peach; Raul E Cachau; Marc C Nicklaus
Journal:  J Mol Recognit       Date:  2017-02-24       Impact factor: 2.137

4.  Entropy and free energy of a mobile protein loop in explicit water.

Authors:  Srinath Cheluvaraja; Mihail Mihailescu; Hagai Meirovitch
Journal:  J Phys Chem B       Date:  2008-07-10       Impact factor: 2.991

5.  Absolute free energy and entropy of a mobile loop of the enzyme acetylcholinesterase.

Authors:  Mihail Mihailescu; Hagai Meirovitch
Journal:  J Phys Chem B       Date:  2009-06-04       Impact factor: 2.991

6.  Open and Closed Form of Maltose Binding Protein in Its Native and Molten Globule State As Studied by Electron Paramagnetic Resonance Spectroscopy.

Authors:  Benjamin Selmke; Peter P Borbat; Chen Nickolaus; Raghavan Varadarajan; Jack H Freed; Wolfgang E Trommer
Journal:  Biochemistry       Date:  2018-09-13       Impact factor: 3.162

  6 in total

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