title: Substrate specificity in HIV-1 protease by a biased sequence search method.
abstract: Drug resistance in HIV-1 protease can also occasionally confer a change in the substrate specificity. Through the use of computational techniques, a relationship can be determined between the substrate sequence and three-dimensional structure of HIV-1 protease, and be utilized to predict substrate specificity. In this study, we introduce a biased sequence search threading (BSST) methodology to analyze the preferences of substrate positions and correlations between them that might also identify which positions within known substrates can likely tolerate sequence variability and which cannot. The potential sequence space was efficiently explored using a low-resolution knowledge-based scoring function. The low-energy substrate sequences generated by the biased search are correlated with the natural substrates. Octameric sequences were predicted using the probabilities of residue positions in the sequences generated by BSST in three ways: considering each position in the substrate independently, considering pairwise interdependency, and considering triple-wise interdependency. The prediction of octameric sequences using the triple-wise conditional probabilities produces the most accurate results, reproducing most of the sequences for five of the nine natural substrates and implying that there is a complex interdependence between the different substrate residue positions. This likely reflects that HIV-1 protease recognizes the overall shape of the substrate more than its specific sequence.
authors.affiliation: Polymer Research Center and Chemical Engineering Department, Bogazici University, Bebek, Istanbul, Turkey.
authors.forename: Nevra
authors.initials: N
authors.lastname: Ozer
authors.forename: Turkan
authors.initials: T
authors.lastname: Haliloglu
authors.forename: Celia A
authors.initials: CA
authors.lastname: Schiffer
mesh_terms: D000595:Amino Acid Sequence; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D018360:Crystallography, X-Ray; D016333:HIV Protease / Q000737:chemistry*; D015233:Models, Statistical; D008969:Molecular Sequence Data; D010455:Peptides / Q000737:chemistry; D011336:Probability; D011487:Protein Conformation; D040901:Proteomics / Q000379:methods*; D012984:Software; D013379:Substrate Specificity
chemical_list: D010455:Peptides; D016333:HIV Protease