PEDS Advance Access published online on January 19, 2006
Protein Engineering Design and Selection, doi:10.1093/protein/gzj005
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1 Department of Biopharmaceutical Sciences, University of California at San Francisco, San Francisco, CA 94143, USA; Department of Pharmaceutical Chemistry, University of California at San Francisco, San Francisco, CA 94143, USA; Department of California Institute for Quantitative Biomedical Research, University of California at San Francisco, San Francisco, CA 94143, USA
* To whom correspondence should be addressed. The penalty for inserting gaps into an alignment between two protein sequences is a major determinant of the alignment accuracy. Here, we present an algorithm for finding a globally optimal alignment by dynamic programming that can use a variable gap penalty (VGP) function of any form. We also describe a specific function that depends on the structural context of an insertion or deletion. It penalizes gaps that are introduced within regions of regular secondary structure, buried regions, straight segments and also between two spatially distant residues. The parameters of the penalty function were optimized on a set of 240 sequence pairs of known structure, spanning the sequence identity range of 20-40%. We then tested the algorithm on another set of 238 sequence pairs of known structures. The use of the VGP function increases the number of correctly aligned residues from 81.0 to 84.5% in comparison with the optimized affine gap penalty function; this difference is statistically significant according to Student's t-test. We estimate that the new algorithm allows us to produce comparative models with an additional
Received October 31, 2005
Revised December 2, 2005
Accepted December 2, 2005
Short Communication
Variable gap penalty for protein sequence-structure alignment
M. S. Madhusudhan 1,
Marc A. Marti-Renom 1,
Roberto Sanchez 2,
and
Andrej Sali 1 *
2 Structural Biology Program, Mount Sinai School of Medicine, Box 1677, 1425 Madison Avenue, New York, NY 10029, USA
Andrej Sali, E-mail: sali{at}salilab.org
Abstract 
7 million accurately modeled residues in the 1.1 million proteins that are detectably related to a known structure.
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