Leveraging AlphaFold2 structural space exploration for generating drug target structures in structure-based virtual screening.

ABSTRACT: Computational virtual screening (VS) plays a vital role in early-stage drug discovery by enabling the efficient selection of candidate compounds and reducing associated costs. However, the absence of experimentally determined three-dimensional protein structures often limits the applicability of structure-based VS. Advances in protein structure prediction, notably AlphaFold2, have begun to address this gap. Yet, studies indicate that direct use of AlphaFold2-predicted structures often leads to suboptimal VS performance-likely because these structures fail to capture ligand-induced conformational changes (apo-to-holo transitions). To overcome this, we propose an approach that explores and modifies the structural space of AlphaFold2 predictions to generate conformations more amenable to VS.

SUBMITTER: Uchikawa K 

PROVIDER: S-EPMC12275061 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature