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首页> 外文期刊>Journal of molecular modeling >Identification of potent L,D-transpeptidase 5 inhibitors for Mycobacterium tuberculosis as potential anti-TB leads: virtual screening and molecular dynamics simulations
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Identification of potent L,D-transpeptidase 5 inhibitors for Mycobacterium tuberculosis as potential anti-TB leads: virtual screening and molecular dynamics simulations

机译:鉴定效率L,D-转肽酶5分枝杆菌抑制剂的抑制剂作为潜在的抗TB引线:虚拟筛选和分子动力学模拟

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摘要

Virtual screening is a useful in silico approach to identify potential leads against various targets. It is known that carbapenems (doripenem and faropenem) do not show any reasonable inhibitory activities against L,D-transpeptidase 5 (Ldt(Mt5)) and also an adduct of meropenem exhibited slow acylation. Since these drugs are active against L,D-transpeptidase 2 (Ldt(Mt2)), understanding the differences between these two enzymes is essential. In this study, a ligand-based virtual screening of 12,766 compounds followed by molecular dynamics (MD) simulations was applied to identify potential leads against Ldt(Mt5). To further validate the obtained virtual screening ranking for Ldt(Mt5), we screened the same libraries of compounds against Ldt(Mt2) which had more experimetal and calculated binding energies reported. The observed consistency between the binding affinities of Ldt(Mt2) validates the obtained virtual screening binding scores for Ldt(Mt5). We subjected 37 compounds with docking scores ranging from - 7.2 to - 9.9 kcal mol(-1) obtained from virtual screening for further MD analysis. A set of compounds (n = 12) from four antibiotic classes with <= - 30 kcal mol(-1) molecular mechanics/generalized born surface area (MM-GBSA) binding free energies (Delta G(bind)) was characterized. A final set of that, all beta-lactams (n = 4), was considered. The outcome of this study provides insight into the design of potential novel leads for Ldt(Mt5).
机译:虚拟筛选是一种有用的硅方法,以识别针对各种目标的潜在导致。众所周知,CarbapeNems(Doripenem和Faropenem)没有针对L,D-转蛋白酶5(LDT(MT5))的任何合理的抑制作用,并且梅洛涅克的加合物表现出缓慢酰化。由于这些药物对L,D-转琥珀酶2(LDT(MT2))有效,因此了解这两种酶之间的差异是必不可少的。在该研究中,应用了12,766种化合物的基于配体的虚拟筛选,其次是分子动力学(MD)模拟,以识别对抗LDT(MT5)的潜在导致。为了进一步验证所获得的LDT(MT5)的虚拟筛选排名,我们筛选了对LDT(MT2)的相同文库,其具有更多报道的经验和计算的结合能。 LDT(MT2)的结合亲和力之间观察到的一致性验证了LDT(MT5)的获得的虚拟筛选结合分数。我们将37种化合物与从虚拟筛选获得的-7.2至-9.9 kcal(-1)的对接分数进行,以进行进一步的MD分析。特征在于,将来自四种抗生素类别的一组化合物(n = 12)来自具有<= - 30kcal摩尔(-1)分子机械/广义出生的表面积(MM-GBSA)的粘合剂(Delta g(结合))。考虑了所有β-内酰胺(n = 4)的最后一组。本研究的结果为LDT(MT5)的潜在新颖性的设计提供了深入了解。

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