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Identification of RdRp inhibitors against SARS-CoV-2 through E-pharmacophore-based virtual screening, molecular docking and MD simulations approaches

虚拟筛选 药效团 广告 生物信息学 计算生物学 药物发现 对接(动物) 药品 药理学 计算机科学 生物 生物信息学 医学 遗传学 基因 护理部
作者
Hafiz Muzzammel Rehman,Muhammad Sajjad,Muhammad Akhtar Ali,Roquyya Gul,Muhammad Naveed,Muhammad Aslam,Khyber Shinwari,Munir Ahmad Bhinder,Muhammad Usman Ghani,Mahjabeen Saleem,Mohd Ashraf Rather,Ishtiyaq Ahmad,Adnan Amin
出处
期刊:International Journal of Biological Macromolecules [Elsevier]
卷期号:237: 124169-124169 被引量:26
标识
DOI:10.1016/j.ijbiomac.2023.124169
摘要

The outbreak of novel Coronavirus, an enduring pandemic declared by WHO, has consequences to an alarming ongoing public health menace which has already claimed several million human lives. In addition to numerous vaccinations and medications for mild to moderate COVID-19 infection, lack of promising medication or therapeutic pharmaceuticals remains a serious concern to counter the ongoing coronavirus infections and to hinder its dreadful spread. Global health emergencies have called for urgency for potential drug discovery and time is the biggest constraint apart from the financial and human resources required for the high throughput drug screening. However, computational screening or in-silico approaches appeared to be an effective and faster approach to discover potential molecules without sacrificing the model animals. Accumulated shreds of evidence on computational studies against viral diseases have revealed significance of in-silico drug discovery approaches especially in the time of urgency. The central role of RdRp in SARS-CoV-2 replication makes it promising drug target to curtain on going infection and its spread. The present study aimed to employ E-pharmacophore-based virtual screening to reveal potent inhibitors of RdRp as potential leads to block the viral replication. An energy-optimised pharmacophore model was generated to screen the Enamine REAL DataBase (RDB). Then, ADME/T profiles were determined to validate the pharmacokinetics and pharmacodynamics properties of the hit compounds. Moreover, High Throughput Virtual Screening (HTVS) and molecular docking (SP & XP) were employed to screen the top hits from pharmacophore-based virtual screening and ADME/T screen. The binding free energies of the top hits were calculated by conducting MM-GBSA analysis followed by MD simulations to determine the stability of molecular interactions between top hits and RdRp protein. These virtual investigations revealed six compounds having binding free energies of -57.498, -45.776, -46.248, -35.67, -25.15 and -24.90 kcal/mol respectively as calculated by the MM-GBSA method. The MD simulation studies confirmed the stability of protein ligand complexes, hence, indicating as potent RdRp inhibitors and are promising candidate drugs to be further validated and translated into clinics in future.

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