Roles of Virtual Screening and Molecular Dynamics Simulations in Discovering and Understanding Antimalarial Drugs

被引:11
作者
Duay, Searle S. [1 ]
Yap, Rianne Casey Y. [1 ]
Gaitano, Arturo L. [2 ]
Santos, June Alexis A. [2 ]
Macalino, Stephani Joy Y. [1 ]
机构
[1] De La Salle Univ, Dept Chem, Manila 0922, Philippines
[2] Adamson Univ, Chem Dept, Manila 1000, Philippines
关键词
malaria; in silico; virtual screening; machine learning; docking; molecular dynamics; MALARIAL DIHYDROFOLATE-REDUCTASE; DEPENDENT PROTEIN-KINASE; PLASMODIUM-FALCIPARUM; ANTIPLASMODIAL ACTIVITY; BIOLOGICAL EVALUATION; RELATIVE STABILITY; SURFACE-TOPOGRAPHY; GENETIC ALGORITHM; HIGH-THROUGHPUT; COMPUTED ATLAS;
D O I
10.3390/ijms24119289
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Malaria continues to be a global health threat, with approximately 247 million cases worldwide. Despite therapeutic interventions being available, patient compliance is a problem due to the length of treatment. Moreover, drug-resistant strains have emerged over the years, necessitating urgent identification of novel and more potent treatments. Given that traditional drug discovery often requires a great deal of time and resources, most drug discovery efforts now use computational methods. In silico techniques such as quantitative structure-activity relationship (QSAR), docking, and molecular dynamics (MD) can be used to study protein-ligand interactions and determine the potency and safety profile of a set of candidate compounds to help prioritize those tested using assays and animal models. This paper provides an overview of antimalarial drug discovery and the application of computational methods in identifying candidate inhibitors and elucidating their potential mechanisms of action. We conclude with the continued challenges and future perspectives in the field of antimalarial drug discovery.
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页数:33
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