Abstract

Autotaxin (ATX) has become an attractive target with a huge pharmacological and pharmacochemical interest in LPA-related diseases and to date many small organic molecules have been explored as potential ATX inhibitors. As a useful aid in the various efforts of identifying novel effective ATX inhibitors, in silico methods can serve as an important and valuable tool. Especially, Virtual Screening (VS) has recently received increased attention due to the large datasets made available, the development of advanced VS techniques and the encouraging fact that VS has contributed to the discovery of several compounds that have either reached the market or entered clinical trials. Different techniques and workflows have been reported in literature with the goal to prioritize possible potent hits. In this review article several deployed virtual screening strategies for the identification of novel potent ATX inhibitors are described.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call