Conformational sampling by self-organization.

Huafeng Xu; Sergei Izrailev; Dimitris K Agrafiotis

doi:10.1021/ci0340557

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PubMed · 12870910

Conformational sampling by self-organization.

Huafeng Xu·Sergei Izrailev·Dimitris K Agrafiotis

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Abstract

A new stochastic algorithm for conformational sampling is described. The algorithm generates molecular conformations that are consistent with a set of geometric constraints, which include interatomic distance bounds and chiral volumes derived from the molecular connectivity table. The algorithm repeatedly selects individual geometric constraints at random and updates the respective atomic coordinates toward satisfying the chosen constraint. When compared to a conventional distance geometry algorithm based on the same set of geometric constraints, our method is faster and generates conformations that are more diverse and more energetically favorable.

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Huafeng Xu, Sergei Izrailev, Dimitris K Agrafiotis. Conformational sampling by self-organization.. https://doi.org/10.1021/ci0340557

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