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Published online before print July 27, 2007
Protein Science, DOI: 10.1110/ps.072887807
Copyright © 2007 The Protein Society
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Loopholes and missing links in protein modeling

Karen A. Rossi, Carolyn A. Weigelt, Akbar Nayeem, and Stanley R. Krystek, Jr

Computer-Assisted Drug Design, Pharmaceutical Research Institute, Bristol-Myers Squibb Company, Princeton, New Jersey 08543 USA

(RECEIVED March 21, 2007; FINAL REVISION June 8, 2007; ACCEPTED June 9, 2007)

This paper provides an unbiased comparison of four commercially available programs for loop sampling, Prime, Modeler, ICM, and Sybyl, each of which uses a different modeling protocol. The study assesses the quality of results and examines the relative strengths and weaknesses of each method. The set of loops to be modeled varied in length from 4–12 amino acids. The approaches used for loop modeling can be classified into two methodologies: ab initio loop generation (Modeler and Prime) and database searches (Sybyl and ICM). Comparison of the modeled loops to the native structures was used to determine the accuracy of each method. All of the protocols returned similar results for short loop lengths (four to six residues), but as loop length increased, the quality of the results varied among the programs. Prime generated loops with RMSDs <2.5 Å for loops up to 10 residues, while the other three methods met the 2.5 Å criteria at seven-residue loops. Additionally, the ability of the software to utilize disulfide bonds and X-ray crystal packing influenced the quality of the results. In the final analysis, the top-ranking loop from each program was rarely the loop with the lowest RMSD with respect to the native template, revealing a weakness in all programs to correctly rank the modeled loops.

Keywords: loop modeling; homology modeling; protein structure


Reprint requests to: Karen A. Rossi, Bristol-Myers Squibb Company, 311 Pennington-Rocky Hill Road, Hopewell, NJ 08534-5400, USA; e-mail: karen.rossi{at}bms.com; fax: (609) 818-3545.

Article published online ahead of print. Article and publication date are at http://www.proteinscience.org/cgi/doi/10.1110/ps.072887807.


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