Abstract
Autotaxin (ATX) is a secreted glycoprotein, widely present in biological fluids, largely responsible for extracellular lysophosphatidic acid (LPA) production. LPA is a bioactive growth-factor-like lysophospholipid that exerts pleiotropic effects in almost all cell types, exerted through at least six G-protein-coupled receptors (LPAR1-6). Increased ATX expression has been detected in different chronic inflammatory diseases, while genetic or pharmacological studies have established ATX as a promising therapeutic target, exemplified by the ongoing phase III clinical trial for idiopathic pulmonary fibrosis. In this report, we employed an in silico drug discovery workflow, aiming at the identification of structurally novel series of ATX inhibitors that would be amenable to further optimization. Towards this end, a virtual screening protocol was applied involving the search into molecular databases for new small molecules potentially binding to ATX. The crystal structure of ATX in complex with a known inhibitor (HA-155) was used as a molecular model docking reference, yielding a priority list of 30 small molecule ATX inhibitors, validated by a well-established enzymatic assay of ATX activity. The two most potent, novel and structurally different compounds were further structurally optimized by deploying further in silico tools, resulting to the overall identification of six new ATX inhibitors that belong to distinct chemical classes than existing inhibitors, expanding the arsenal of chemical scaffolds and allowing further rational design.
Funder
General Secretariat for Research and Technology
Subject
Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献