Molecular modeling-guided optimization of acetylcholinesterase reactivators: A proof for reactivation of covalently inhibited targets.

Abstract

Covalent drugs have been intensively studied in some very important fields such as anti-tumor and anti-virus, including the currently global-spread SARS-CoV-2. However, these drugs may interact with a variety of biological macromolecules and cause serious toxicology, so how to reactivate the inhibited targets seems to be imperative in the near future. Organophosphate was an extreme example, which could form a covalent bound easily with acetylcholinesterase and irreversibly inhibited the enzyme, causing high toxicology. Some nucleophilic oxime reactivators for organophosphate poisoned acetylcholinesterase had been developed, but the reactivation process was still less understanding. Herein, we proposed there should be a pre-reactivated pose during the reactivating process and compounds whose binding pose was easy to transfer to the pre-reactivated pose might be efficient reactivators. Then we refined the previous reactivators based on the molecular dynamic simulation results, the resulting compounds L7R3 and L7R5 were proven as much more efficient reactivators for organophosphate inhibited acetylcholinesterase than currently used oximes. This work might provide some insights for constructing reactivators of covalently inhibited targets by using computational methods.