Volume 20 No 20 (2022)
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APPLICATIONS OF COMPUTATIONAL CHEMISTRY IN DRUG DESIGN: A REVIEW
Trilochan Ram Sahu, Lalita Sahu
Abstract
Computational chemistry plays a pivotal role in modern drug discovery by facilitating the prediction of molecular interactions and optimizing lead compounds. This review explores the application of computational methods such as molecular docking, quantitative structure-activity relationships (QSAR), and molecular dynamics simulations in target identification and drug design. The principles, methodologies, and case studies of each approach are discussed, highlighting their contributions to accelerating the discovery of novel therapeutic agents. Additionally, emerging technologies including AI, machine learning, and quantum computing are examined for their potential to revolutionize computational chemistry in the pharmaceutical industry. Challenges such as computational resources, accuracy, and validation issues are also addressed, underscoring the need for advancements in these areas to enhance the efficacy and reliability of computational tools in drug discovery.
Keywords
Computational chemistry, drug design, molecular docking, QSAR, molecular dynamics simulations, AI, machine learning, quantum computing, pharmaceutical industry, challenges
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