Toward a robust computational screening strategy for identifying glycosaminoglycan sequences that display high specificity for target proteins.

ABSTRACT: Glycosaminoglycans (GAGs) interact with many proteins to regulate processes such as hemostasis, cell adhesion, growth and differentiation and viral infection. Yet, majority of these interactions remain poorly understood at a molecular level. A major reason for this state is the phenomenal structural diversity of GAGs, which has precluded analysis of specificity of their interactions. We had earlier presented a computational protocol for predicting "high-specificity" GAG sequences based on combinatorial virtual library screening (CVLS) technology. In this work, we expand the robustness of this technology through rigorous studies of parameters affecting GAG recognition of proteins, especially antithrombin and thrombin. The CVLS approach involves automated construction of a virtual library of

SUBMITTER: Sankaranarayanan NV 

PROVIDER: S-EPMC4296175 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature