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Protein Science (2007), 16:1266-1273. Published by Cold Spring Harbor Laboratory Press. Copyright © 2007 The Protein Society
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Using surface envelopes to constrain molecular modeling

Jonathan M. Dugan and Russ B. Altman

Department of Genetics, Stanford University, Stanford, California 94305-5120, USA

(RECEIVED December 17, 2006; FINAL REVISION March 11, 2007; ACCEPTED March 12, 2007)

Molecular density information (as measured by electron microscopic reconstructions or crystallographic density maps) can be a powerful source of information for molecular modeling. Molecular density constrains models by specifying where atoms should and should not be. Low-resolution density information can often be obtained relatively quickly, and there is a need for methods that use it effectively. We have previously described a method for scoring molecular models with surface envelopes to discriminate between plausible and implausible fits. We showed that we could successfully filter out models with the wrong shape based on this discrimination power. Ideally, however, surface information should be used during the modeling process to constrain the conformations that are sampled. In this paper, we describe an extension of our method for using shape information during computational modeling. We use the envelope scoring metric as part of an objective function in a global optimization that also optimizes distances and angles while avoiding collisions. We systematically tested surface representations of proteins (using all nonhydrogen heavy atoms) with different abundance of distance information and showed that the root mean square deviation (RMSD) of models built with envelope information is consistently improved, particularly in data sets with relatively small sets of short-range distances.

Keywords: surface; fitness function; shape; molecular modeling; principal components


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