Abstract
The use of computational tools for virtual screening provides a cost-efficient approach to select starting points for drug development. We have developed VSpipe, a user-friendly semi-automated pipeline for structure-based virtual screening. VSpipe uses the existing tools AutoDock and OpenBabel together with software developed in-house, to create an end-to-end virtual screening workflow ranging from the preparation of receptor and ligands to the visualisation of results. VSpipe is efficient and flexible, allowing the users to make choices at different steps, and it is amenable to use in both local and cluster mode. We have validated VSpipe using the human protein tyrosine phosphatase PTP1B as a case study. Using a combination of blind and targeted docking VSpipe identified both new and known functional ligand binding sites. Assessment of different binding clusters using the ligand efficiency plots created by VSpipe, defined a drug-like chemical space for development of PTP1B inhibitors with potential applications to other PTPs. In this study, we show that VSpipe can be deployed to identify and compare different modes of inhibition thus guiding the selection of initial hits for drug discovery.
Highlights
The success of a drug discovery programme involves the optimisation of a large number of parameters that combine both target properties and ligand properties
Computational screening or virtual screening (VS) is relatively cheap and in principle there is no limitation on the chemical space to search
The results show how the docking is faster when using the High Performance Computing (HPC) cluster, where the parallelised versions of AutoDock [14] (AD4) and the multithreaded Vina are used, as opposed to a local computer
Summary
The success of a drug discovery programme involves the optimisation of a large number of parameters that combine both target properties (biological space) and ligand properties (chemical space). Achieving the right balance of potency and pharmacological properties is what determines the success of a drug candidate in the clinic. This process is long and complex, speeding up the early stages of hit identification and lead selection are critical. VS offers advantages at the early stage of drug discovery to identify compounds with potential inhibitory activity towards the target of interest [1,2]
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