Exploring conformational space using a mean field technique with MOLS sampling

Prasad, P. Arun; Vadivel, Kanagasabai; Arunachalam, J.; Gautham, N.

doi:10.1007/s12038-007-0091-3

Cited by 5 publications

(6 citation statements)

References 64 publications

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“…(Hao et al, 2008; Prasad et al, 2007; Sood and Baker, 2006) We developed our own flexible peptide docking algorithm to restrict the conformational search to a relatively local search because the end-goal is specificity determination, not structure prediction. The protease structure used for docking was obtained from the crystal structure of HIV-1 protease bound to the inhibitor Saquinavir (Krohn et al, 1991).…”

Section: Methodsmentioning

confidence: 99%

Identification of Structural Mechanisms of HIV-1 Protease Specificity Using Computational Peptide Docking: Implications for Drug Resistance

Chaudhury

Gray

2009

Structure

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Summary Drug-resistant mutations (DRMs) in HIV-1 protease are a major challenge to antiretroviral therapy. Protease-substrate interactions that are determined to be critical for native selectivity could serve as robust targets for drug design that are immune to DRMs. In order to identify the structural mechanisms of selectivity, we developed a peptide docking algorithm to predict the atomic structure of protease-substrate complexes and applied it to a large and diverse set of cleavable and non-cleavable peptides. Cleavable peptides showed significantly lower energies of interaction than non-cleavable peptides with six protease active-site residues playing the most significant role in discrimination. Surprisingly, all six residues correspond to sequence positions associated with drug resistance mutations, demonstrating that the very residues that are responsible for native substrate specificity in HIV-1 protease are altered during its evolution to drug resistance, suggesting that drug resistance and substrate selectivity may share common mechanisms.

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Section: Methodsmentioning

confidence: 99%

Identification of Structural Mechanisms of HIV-1 Protease Specificity Using Computational Peptide Docking: Implications for Drug Resistance

Chaudhury

Gray

2009

Structure

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“…They are also used to analyze protein homology,55–60 for example, for structure‐based phylogenetic study 61. Because of their flexible nature they raise crucial questions in protein docking approaches,62–64 to predict protein loop conformations,65–78 to enhance protein thermostability,79 to design proteins,80 or to obtain protein structures 81. According to the repetitive secondary structures of their extremities, connecting loops are of four distinct classes (α‐α, α‐β, β‐α, and β‐β) 46, 82–84.…”

Section: Introductionmentioning

confidence: 99%

Analysis of loop boundaries using different local structure assignment methods

et al. 2009

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Loops connect regular secondary structures. In many instances, they are known to play important biological roles. Analysis and prediction of loop conformations depend directly on the definition of repetitive structures. Nonetheless, the secondary structure assignment methods (SSAMs) often lead to divergent assignments. In this study, we analyzed, both structure and sequence point of views, how the divergence between different SSAMs affect boundary definitions of loops connecting regular secondary structures. The analysis of SSAMs underlines that no clear consensus between the different SSAMs can be easily found. Because these latter greatly influence the loop boundary definitions, important variations are indeed observed, that is, capping positions are shifted between different SSAMs. On the other hand, our results show that the sequence information in these capping regions are more stable than expected, and, classical and equivalent sequence patterns were found for most of the SSAMs. This is, to our knowledge, the most exhaustive survey in this field as (i) various databank have been used leading to similar results without implication of protein redundancy and (ii) the first time various SSAMs have been used. This work hence gives new insights into the difficult question of assignment of repetitive structures and addresses the issue of loop boundaries definition. Although SSAMs give very different local structure assignments capping sequence patterns remain efficiently stable.

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“…The MOLS technique to sample the conformational landscape of pentapeptides has been described in detail previously 16, 17, 30. A description of the method is available at http://www.unom.ac.in/Gautham_mols.pdf.…”

Section: Methodsmentioning

confidence: 99%

“…Earlier reports from our laboratory16–19, 30 had shown that MOLS sampling is extensive, and that the method identifies all experimental and computationally observed minimum energy structures of Met‐ and Leu‐enkephalin, besides locating other well‐folded structures of possible biological relevance. In this article, we compare the sampling behavior of the MD and MC simulations with that of the MOLS technique.…”

Section: Introductionmentioning

confidence: 99%

Conformational space exploration of met‐ and Leu‐enkephalin using the mols method, molecular dynamics, and Monte Carlo simulation—a comparative study

Ramya

Gautham

2011

Biopolymers

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We report here a comparative study of the molecular conformational energy landscape generated using the mutually orthogonal Latin squares (MOLS) method, molecular dynamics (MD), and Monte Carlo (MC) simulation. The MOLS method, as described earlier from our laboratory, uses an experimental design technique to rapidly and exhaustively sample the low energy conformations of a molecule. MD and MC simulations have been used to perform similar tasks. In the comparison reported here, the three methods were applied to a pair of neuropeptides, namely Met- and Leu-enkephalin. A set of 1500 conformations of these enkephalins were generated using these methods with CHARMM22 force field, and the resulting samples were analyzed to determine the extent and nature of coverage of the conformational space. The results indicate that the MOLS method samples a larger number of possible conformations and identifies conformations closer to the experimental structures than the MD and MC simulations.

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Exploring conformational space using a mean field technique with MOLS sampling

Cited by 5 publications

References 64 publications

Identification of Structural Mechanisms of HIV-1 Protease Specificity Using Computational Peptide Docking: Implications for Drug Resistance

Identification of Structural Mechanisms of HIV-1 Protease Specificity Using Computational Peptide Docking: Implications for Drug Resistance

Analysis of loop boundaries using different local structure assignment methods

Conformational space exploration of met‐ and Leu‐enkephalin using the mols method, molecular dynamics, and Monte Carlo simulation—a comparative study

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