Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, Pakistan.
HEJ Research Institute of Chemistry, International Center for Chemical and Biological Sciences, University of Karachi, Karachi, Pakistan.
J Biomol Struct Dyn. 2024;42(20):11080-11097. doi: 10.1080/07391102.2023.2260483. Epub 2023 Sep 25.
The Pantothenate synthetase (PS) from the () holds a crucial role in the survival and robust proliferation of bacteria through its catalysis of coenzyme A and acyl carrier protein synthesis. The present study undertook the PS drug target in complex with a co-crystallized ligand and subjected it to docking and virtual screening approaches. The experimental design encompassed three discrete datasets: an active dataset featuring 136 compounds, an inactive dataset comprising 56 compounds, and a decoys dataset curated from the zinc library, comprising an extensive compilation of approximately 53,000 compounds. The compounds' binding energies were observed to be in the range of -5 to ∼-14 kcal/mol. Additionally, binding energy results were further refined through Enrichment Factor analysis (EF). EF is a new statistical approach which uses the scores obtained from docking-based virtual screening and predicts the precision of the scoring function. Remarkably, the Enrichment Factor (EF) analysis produced exceptionally favorable outcomes, attaining an EF of approximately 49% within the uppermost 1% fraction of the compound distribution. Finally, a total of eight compounds, evenly distributed between the active dataset and the decoys dataset, emerged as potent inhibitors of the Pantothenate synthetase (PS) enzyme. The analysis of inhibition constants and binding energy revealed a notable correlation, with an r-squared value () of 0.912 between the two parameters. Furthermore, the shortlisted compounds were subjected to 100 ns MD simulation to determine their stability and dynamics behavior. The decoy compounds that have been identified, exhibiting properties comparable to the active compounds, are postulated as potential candidates for targeting the Pantothenate synthetase (PS) enzyme to treat infection. Nevertheless, in the pursuit of a comprehensive investigation, it is advisable to undertake additional experimental validation as a component of the subsequent study.Communicated by Ramaswamy H. Sarma.
泛酸合酶（PS）来自（）通过其催化辅酶 A 和酰基载体蛋白合成，在细菌的存活和旺盛增殖中起着关键作用。本研究采用与共结晶配体结合的 PS 药物靶点，并对其进行对接和虚拟筛选方法。实验设计包括三个离散数据集：一个包含 136 种化合物的活性数据集、一个包含 56 种化合物的非活性数据集和一个从锌库中 curated 的 decoys 数据集，其中包含大约 53,000 种化合物的广泛汇编。观察到化合物的结合能在-5 到～-14 kcal/mol 的范围内。此外，通过富集因子分析（EF）进一步细化结合能结果。EF 是一种新的统计方法，它使用从基于对接的虚拟筛选中获得的分数，并预测评分函数的精度。值得注意的是，富集因子（EF）分析产生了非常有利的结果，在化合物分布的最上面 1%的分数中获得了大约 49%的 EF。最后，从活性数据集和 decoys 数据集中均匀分布的总共 8 种化合物作为泛酸合酶（PS）酶的有效抑制剂出现。抑制常数和结合能的分析显示出显著的相关性，两个参数之间的 r-squared 值（）为 0.912。此外，对选定的化合物进行了 100 ns MD 模拟，以确定它们的稳定性和动力学行为。已经确定的 decoys 化合物表现出与活性化合物相当的性质，被认为是针对泛酸合酶（PS）酶治疗感染的潜在候选药物。然而，为了进行全面的研究，建议在随后的研究中进行额外的实验验证。由 Ramaswamy H. Sarma 传达。
