From Laptop to Benchtop to Bedside: Structure-based Drug Design on Protein Targets

Lu Chen, John K. Morrow, Hoang T. Tran, Sharangdhar S. Phatak, Lei Du-Cuny, Shuxing Zhang
<span title="2012-03-01">2012</span> <i title="Bentham Science Publishers Ltd."> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zicjy4mtnrfahfmtoo4ufy5g6u" style="color: black;">Current drug metabolism</a> </i> &nbsp;
As an important aspect of computer-aided drug design, structure-based drug design brought a new horizon to pharmaceutical development. This in silico method permeates all aspects of drug discovery today, including lead identification, lead optimization, ADMET prediction and drug repurposing. Structure-based drug design has resulted in fruitful successes drug discovery targeting protein-ligand and protein-protein interactions. Meanwhile, challenges, noted by low accuracy and combinatoric issues,
more &raquo; ... may also cause failures. In this review, state-of-the-art techniques for protein modeling (e.g. structure prediction, modeling protein flexibility, etc.), hit identification/optimization (e.g. molecular docking, focused library design, fragment-based design, molecular dynamic, etc.), and polypharmacology design will be discussed. We will explore how structure-based techniques can facilitate the drug discovery process and interplay with other experimental approaches. Keywords Structure-based drug design; protein modeling; focused library design; pharmacophore; flexible docking; high-throughput virtual screening; de novo design; protein-protein interaction; polypharmacology Modern computational-aided drug design established a novel platform by which researchers perform in-depth in silico simulation prior to labor-extensive wet-lab validation [1] . It comprises of two major parts corresponding to the information of molecular source it utilizes: structure-based (or receptor-based) drug design and ligand-based drug design. Structure-based drug design, which relies on the knowledge of biological target structures, aims to discover small molecules/peptides leads with desired chemistry properties, and orchestrate the following experimental validation and lead optimization. Structure-based approach provides mechanism-based basis, where potential ligands are excavated using receptor-dependent parameters, while ligand-based approaches bypass the consideration of complex biomolecular "black box" in a living cell. This in silico method permeates all aspects of drug discovery today [2], and we expect it will draw more attentions with the unprecedented advances of computational power and modeling accuracy in this decade.
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