Getting Docking into Shape Using Negative Image-Based Rescoring.

ABSTRACT: The failure of default scoring functions to ensure virtual screening enrichment is a persistent problem for the molecular docking algorithms used in structure-based drug discovery. To remedy this problem, elaborate rescoring and postprocessing schemes have been developed with a varying degree of success, specificity, and cost. The negative image-based rescoring (R-NiB) has been shown to improve the flexible docking performance markedly with a variety of drug targets. The yield improvement is achieved by comparing the alternative docking poses against the negative image of the target protein's ligand-binding cavity. In other words, the shape and electrostatics of the binding pocket is directly used in the similarity comparison to rank the explicit docking poses. Here, the PANTHER/ShaEP-base

SUBMITTER: Kurkinen ST 

PROVIDER: S-EPMC6750746 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature