Title:Computational Strategy Revealing the Structural Determinant of Ligand Selectivity towards Highly Similar Protein Targets
Volume: 21
Issue: 1
Author(s): Hanxun Wang, Yinli Gao, Jian Wang*Maosheng Cheng
Affiliation:
- Key Laboratory of Structure-Based Drug Design & Discovery, Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016, Liaoning,China
Keywords:
Computational strategy, allosteric regulation, selectivity mechanism, drug development, toxicity, drug discovery.
Abstract:
Background: Poor selectivity of drug candidates may lead to toxicity and side effects accounting
for as high as 60% failure rate, thus, the selectivity is consistently significant and challenging
for drug discovery.
Objective: To find highly specific small molecules towards very similar protein targets, multiple strategies
are always employed, including (1) To make use of the diverse shape of binding pocket to avoid
steric bump; (2) To increase binding affinities for favorite residues; (3) To achieve selectivity through
allosteric regulation of target; (4) To stabalize the inactive conformation of protein target and (5) To
occupy dual binding pockets of single target.
Conclusion: In this review, we summarize computational strategies along with examples of their successful
applications in designing selective ligands, with the aim to provide insights into everdiversifying
drug development practice and inspire medicinal chemists to utilize computational strategies
to avoid potential side effects due to low selectivity of ligands.
