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1 Department of Biochemistry, Weill Medical College of Cornell University, New York, New York 10021, USA
2 Bioinformatics Laboratory, Department of Applied Mathematics and Statistics, State University of New York at Stony Brook, Stony Brook, New York 11794-3600, USA
Reprint requests to: Ilya A. Vakser, Bioinformatics Laboratory, Department of Applied Mathematics and Statistics, State University of New York at Stony Brook, Stony Brook, NY 11794-3600, USA; e-mail: vakser{at}ams.sunysb.edu; fax: (631) 632-8490.
A strong similarity between the major aspects of protein folding and protein recognition is one of the emerging fundamental principles in protein science. A crucial importance of steric complementarity in protein recognition is a well-established fact. The goal of this study was to assess the importance of the steric complementarity in protein folding, namely, in the packing of the secondary structure elements. Although the tight packing of protein structures, in general, is a well-known fact, a systematic study of the role of geometric complementarity in the packing of secondary structure elements has been lacking. To assess the role of the steric complementarity, we used a docking procedure to recreate the crystallographically determined packing of secondary structure elements in known protein structures by using the geometric match only. The docking results revealed a significant percentage of correctly predicted packing configurations. Different types of pairs of secondary structure elements showed different degrees of steric complementarity (from high to low: ß–ß, loop–loop, 
–, and –ß). Interestingly, the relative contribution of the steric match in different types of pairs was correlated with the number of such pairs in known protein structures. This effect may indicate an evolutionary pressure to select tightly packed elements of secondary structure to maximize the packing of the entire structure. The overall conclusion is that the steric match plays an essential role in the packing of secondary structure elements. The results are important for better understanding of principles of protein structure and may facilitate development of better methods for protein structure prediction.
Keywords: Docking; protein modeling; molecular recognition; protein folding; structural bioinformatics
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