Renxiao Wang
Shanghai Institute of Organic Chemistry, State Key Laboratory of Bioorganic Chemistry, Shanghai 200032, China

Abstract:

Docking-based virtual screening of large compound databases has been widely applied to lead discovery in structure-based drug design. However, other computational methods, such as de novo design methods, have to be employed in subsequent lead optimization. We have developed an automatic method, namely Automatic Tailoring and Transplanting (AT&T), which can effectively utilize the outcomes of virtual screening in lead optimization. This method recognizes the suitable fragments on virtual screening hits and then transplants them onto appropriate sites on the lead compound to generate new ligand molecules. Binding affinities, synthetic feasibilities and drug-likeness properties are considered in the selection of final outputs. In this study, our AT&T program was tested on three different target proteins, including p38 mitogen-activated protein kinases, PPAR-α, and Mcl-1. In the first two cases, AT&T was able to produce molecules identical or similar to known inhibitors with better potency than the lead compound. In the third case, we demonstrated how to apply the AT&T program to generate novel ligand molecules from scratch. Our AT&T method has certain technical advantages over conventional de novo design methods. Compared to the outcomes produced by LUDI and EA-Inventor, our AT&T method produced structurally more diverse designs with generally better binding scores in all three test cases. More importantly, our method expands the use of virtual screening. Considering the vast popularity of virtual screening, AT&T may become a valuable tool for performing lead optimization in structure-based drug design.

Keywords: Structure-based drug design, lead optimization, virtual screening, de novo design, AT&T.