使用 AutoDock4 进行的蛋白质-配体对接模拟侧重于 SARS-CoV-2 的主要蛋白酶

Title:Protein-Ligand Docking Simulations with AutoDock4 Focused on the Main Protease of SARS-CoV-2

Volume: 28 Issue: 37

关键词: COVID-19、SARS-CoV-2、蛋白质-配体相互作用、autoDock4、对接、机器学习、主蛋白酶。

摘要:

Background: The main protease of SARS-CoV-2 (M^pro) is one of the targets identified in SARS-CoV-2, the causative agent of COVID-19. The application of X-ray diffraction crystallography made available the three-dimensional structure of this protein target in complex with ligands, which paved the way for docking studies.

Objective: Our goal here is to review recent efforts in the application of docking simulations to identify inhibitors of the M^pro using the program AutoDock4.

Methods: We searched PubMed to identify studies that applied AutoDock4 for docking against this protein target. We used the structures available for M^pro to analyze intermolecular interactions and reviewed the methods used to search for inhibitors.

Results: The application of docking against the structures available for the M^pro found ligands with an estimated inhibition in the nanomolar range. Such computational approaches focused on the crystal structures revealed potential inhibitors of M^pro that might exhibit pharmacological activity against SARS-CoV-2. Nevertheless, most of these studies lack the proper validation of the docking protocol. Also, they all ignored the potential use of machine learning to predict affinity.

Conclusion: The combination of structural data with computational approaches opened the possibility to accelerate the search for drugs to treat COVID-19. Several studies used AutoDock4 to search for inhibitors of M^pro. Most of them did not employ a validated docking protocol, which lends support to critics of their computational methodology. Furthermore, one of these studies reported the binding of chloroquine and hydroxychloroquine to M^pro. This study ignores the scientific evidence against the use of these antimalarial drugs to treat COVID-19.

Cite this article as:

Protein-Ligand Docking Simulations with AutoDock4 Focused on the Main Protease of SARS-CoV-2, Current Medicinal Chemistry 2021; 28 (37) . https://dx.doi.org/10.2174/0929867328666210329094111