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@article{193386,
        author = {Konarachapalle Nagalakshmi and Muplam Preethika and Pillikandla Sukumari and Seelam Buttagandla Pujitha and Mohammad Irfan Khan and Baragaj Shaik china Peeravalli},
        title = {QSAR AND MOLECULAR MODELLING APPORACHES FOR DESIGNING NEXT GENERATION ENZYME INHIBITORS: A COMPHRENSIVE REVIEW},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {411-424},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=193386},
        abstract = {The design of next-generation enzyme inhibitors has evolved from a process of serendipitous discovery into an era of rational, atomic-scale engineering. This review provides a comprehensive analysis of the contemporary landscape of (QSAR) and Molecular Modeling approaches, highlighting their indispensable role in the development of highly selective and potent therapeutics. We evaluate the transition from traditional 2D/3D-QSAR to advanced machine learning-integrated models that predict not only potency but also complex ADMET profiles and off-target liabilities. Furthermore, this review explores the integration of Molecular Dynamics and Quantum Mechanics/Molecular Mechanics (QM/MM) simulations in refining binding site interactions, moving beyond static docking to capture the critical nuances of protein flexibility and electronic polarization. Specialized strategies for designing allosteric, covalent, and multi-kinase inhibitors are discussed, alongside the emerging role of Generative Artificial Intelligence in de novo scaffold design. By synthesizing recent clinical successes and examining the learned from failed computational models, this work offers a road map for leveraging integrated in silico toolkits to overcome drug resistance and achieve superior selectivity in modern drug discovery.},
        keywords = {Molecular Modeling, Enzyme Inhibition, Drug Design, Machine Learning, Allosteric Regulation, In Silico Screening, etc.},
        month = {March},
        }