Developing target-specific scoring using black-box optimisation
by Elham Shamsara; Jamal Shamsara
International Journal of Computational Biology and Drug Design (IJCBDD), Vol. 10, No. 1, 2017

Abstract: In this study, the screening power of a AutoDock Vina scoring function was considered as an optimisation problem. It was hypothesised that the screening power of the AutoDock Vina scoring function can be optimised by a black-box optimiser. The weights of the energy terms of the AutoDock Vina scoring function were considered as input parameters for the black-box optimiser. This was implemented in Python. The study was designed to develop target-specific weights for six protein targets using active/decoy datasets retrieved from a database of useful (docking) decoys (DUD-E). The results demonstrated some improvements in the area under the curve (AUC) of the ROC curve and in the enrichment factor of both the training and test sets.

Online publication date: Tue, 07-Mar-2017

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