抗细菌
虚拟筛选
结核分枝杆菌
生物信息学
配体(生物化学)
组合化学
肺结核
计算生物学
化学
计算机科学
生物
医学
药物发现
生物化学
受体
病理
基因
作者
Fabrizio Manetti,Matteo Magnani,Daniele Castagnolo,Laura Passalacqua,Maurizio Botta,Federico Corelli,Manuela Saddi,Delia Deidda,Alessandro De Logu
出处
期刊:ChemMedChem
[Wiley]
日期:2006-09-01
卷期号:1 (9): 973-989
被引量:45
标识
DOI:10.1002/cmdc.200600026
摘要
Abstract In an attempt to identify new inhibitors of the growth of Mycobacterium tuberculosis (MTB), the causative agent of tuberculosis, a procedure for the generation, design, and screening of a ligand‐based virtual library was applied. This used both an in silico protocol centered on a recursive partitioning (RP) model described herein, and a pharmacophoric model for antitubercular agents previously generated by our research group. Two candidates emerged from databases of commercially available compounds, both characterized by a minimum inhibitory concentration (MIC) of 25 μg mL −1 . Based on these compounds, two series of derivatives were synthesized by both parallel solution‐phase and microwave‐assisted synthesis, leading to enhanced antimycobacterial activity. During both the design and synthesis, attention was focused on the efficient allocation of available resources with the aim of reducing the overall costs associated with calculation and synthesis.
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