Identification and Dynamics Understanding of Novel Inhibitors of Peptidase Domain of Collagenase G from Clostridium histolyticum

IF 1.9 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
F. Anjum, Ali Hazazi, F. Alsaeedi, Maha Bakhuraysah, Alaa Shafie, Norah Ali Alshehri, Nahed Hawsawi, A. Ashour, H. Banjer, Afaf Alharthi, Maryam Ishrat Niaz
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引用次数: 0

Abstract

Clostridium histolyticum is a Gram-positive anaerobic bacterium belonging to the Clostridium genus. It produces collagenase, an enzyme involved in breaking down collagen which is a key component of connective tissues. However, antimicrobial resistance (AMR) poses a great challenge in combating infections caused by this bacteria. The lengthy nature of traditional drug development techniques has resulted in a shift to computer-aided drug design and other modern drug discovery approaches. The above method offers a cost-effective means for gathering comprehensive information about how ligands interact with their target proteins. The objective of this study is to create novel, explicit drugs that specifically inhibit the C. histolyticum collagenase enzyme. Through structure-based virtual screening, a library containing 1830 compounds was screened to identify potential drug candidates against collagenase enzymes. Following that, molecular dynamic (MD) simulation was performed in an aqueous solution to evaluate the behavior of protein and ligand in a dynamic environment while density functional theory (DFT) analysis was executed to predict the molecular properties and structure of lead compounds, and the WaterSwap technique was utilized to obtain insights into the drug–protein interaction with water molecules. Furthermore, principal component analysis (PCA) was performed to reveal conformational changes, salt bridges to express electrostatic interaction and protein stability, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) to assess the pharmacokinetics profile of top compounds and control molecules. Three potent drug candidates were identified MSID000001, MSID000002, MSID000003, and the control with a binding score of −10.7 kcal/mol, −9.8 kcal/mol, −9.5 kcal/mol, and −8 kcal/mol, respectively. Furthermore, Molecular Mechanics Poisson–Boltzmann Surface Area (MMPBSA) analysis of the simulation trajectories revealed energy scores of −79.54 kcal/mol, −73.99 kcal/mol, −62.26 kcal/mol, and −70.66 kcal/mol, correspondingly. The pharmacokinetics properties exhibited were under the acceptable range. The compounds hold the potential to be novel drugs; therefore, further investigation needs to be conducted to find out their anti-collagenase action against C. histolyticum infections and antibiotic resistance.
组织溶解梭菌胶原酶 G 肽酶域新型抑制剂的鉴定与动力学理解
组织溶解梭菌是一种革兰氏阳性厌氧细菌,属于梭菌属。它能产生胶原酶,这是一种参与分解胶原蛋白的酶,而胶原蛋白是结缔组织的重要组成部分。然而,抗菌药耐药性(AMR)给抗击这种细菌引起的感染带来了巨大挑战。传统的药物开发技术耗时较长,因此已转向计算机辅助药物设计和其他现代药物发现方法。上述方法为收集配体与其靶蛋白相互作用的全面信息提供了一种经济有效的手段。本研究的目的是开发出能特异性抑制溶组织胞胶原酶的新型明确药物。通过基于结构的虚拟筛选,对包含 1830 种化合物的文库进行了筛选,以确定针对胶原蛋白酶的潜在候选药物。随后,在水溶液中进行了分子动力学(MD)模拟,以评估蛋白质和配体在动态环境中的行为,同时执行了密度泛函理论(DFT)分析,以预测先导化合物的分子特性和结构,并利用 WaterSwap 技术深入了解药物-蛋白质与水分子的相互作用。此外,还通过主成分分析(PCA)揭示构象变化,通过盐桥表达静电相互作用和蛋白质稳定性,以及通过吸收、分布、代谢、排泄和毒性(ADMET)评估先导化合物和对照分子的药代动力学特征。最终确定了三种强效候选药物 MSID000001、MSID000002、MSID000003 和对照组,其结合得分分别为 -10.7 kcal/mol、-9.8 kcal/mol、-9.5 kcal/mol 和 -8 kcal/mol。此外,对模拟轨迹进行的分子力学泊松-玻尔兹曼表面积(MMPBSA)分析显示,能量得分分别为-79.54 kcal/mol、-73.99 kcal/mol、-62.26 kcal/mol和-70.66 kcal/mol。这些化合物的药代动力学特性均在可接受的范围内。这些化合物具有成为新型药物的潜力;因此,还需要进一步研究它们对溶组织胞杆菌感染和抗生素耐药性的抗胶原酶作用。
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来源期刊
Computation
Computation Mathematics-Applied Mathematics
CiteScore
3.50
自引率
4.50%
发文量
201
审稿时长
8 weeks
期刊介绍: Computation a journal of computational science and engineering. Topics: computational biology, including, but not limited to: bioinformatics mathematical modeling, simulation and prediction of nucleic acid (DNA/RNA) and protein sequences, structure and functions mathematical modeling of pathways and genetic interactions neuroscience computation including neural modeling, brain theory and neural networks computational chemistry, including, but not limited to: new theories and methodology including their applications in molecular dynamics computation of electronic structure density functional theory designing and characterization of materials with computation method computation in engineering, including, but not limited to: new theories, methodology and the application of computational fluid dynamics (CFD) optimisation techniques and/or application of optimisation to multidisciplinary systems system identification and reduced order modelling of engineering systems parallel algorithms and high performance computing in engineering.
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