Biophysical Society Thematic Meeting - November 16-20, 2015

Biophysics in the Understanding, Diagnosis, and Treatment of Infectious Diseases Poster Abstracts

35-POS Board 35 Prediction of Cleavage Specificity in Proteases by Biased Sequence Search Threading Gonca Ozdemir Isik, Asuman Nevra Ozer . Marmara University, Istanbul, Turkey. The assessment of substrate specificity in infectious disease-related proteases is crucial in drug development studies, where interpreting the adaptability of residue positions can be useful in understanding how inhibitors might best fit within the substrate binding sites. In this work, the substrate variability and substrate specificity of the Human Immunodeficiency Virus 1 (HIV-1) protease, the Hepatitis C Virus (HCV) NS3/4A serine protease and the Adenovirus 2 (AdV2) cysteine protease were investigated by the computational biased sequence search threading (BSST) methodology. Available crystal structures and template structures for the substrate- bound proteases, which were created in silico by performing various peptide building and docking procedures followed by energy minimization and molecular dynamics simulations, were utilized. BSST was performed starting with known binding, nonbinding and random peptide sequences that were threaded onto the template complex structures, and low energy sequences were searched using low-resolution knowledge-based potentials. Then, target sequences of yet unidentified potential substrates were predicted by statistical probability approaches applied on the low energy sequences. The results show that the majority of the predicted substrate positions correspond to the natural substrate sequences with conserved amino acid preferences. Overall, supported by the successful outcomes with the case studies of HIV-1 protease, HCV NS3/4A serine protease and AdV2 cysteine protease here, BSST seems to be a powerful methodology for prediction of substrate specificity in protease systems.

75