Division of Cancer Research and Training, Department of Internal Medicine, Charles R. Drew University of Medicine and Science, David Geffen UCLA School of Medicine and UCLA Jonsson Comprehensive Cancer Center, Los Angeles, CA 90095, USA.
Division of Cancer Research and Training, Department of Internal Medicine, Charles R. Drew University of Medicine and Science, David Geffen UCLA School of Medicine and UCLA Jonsson Comprehensive Cancer Center, Los Angeles, CA 90095, USA; School of Pharmacy, American University of Health Sciences, Signal Hill, CA 90755, USA.
Drug Discov Today. 2023 Oct;28(10):103730. doi: 10.1016/j.drudis.2023.103730. Epub 2023 Aug 1.
In this review, we outline recent advancements in small molecule drug design from a structural perspective. We compare protein structure prediction methods and explore the role of the ligand binding pocket in structure-based drug design. We examine various structural features used to optimize drug candidates, including functional groups, stereochemistry, and molecular weight. Computational tools such as molecular docking and virtual screening are discussed for predicting and optimizing drug candidate structures. We present examples of drug candidates designed based on their molecular structure and discuss future directions in the field. By effectively integrating structural information with other valuable data sources, we can improve the drug discovery process, leading to the identification of novel therapeutics with improved efficacy, specificity, and safety profiles.
在这篇综述中，我们从结构的角度概述了小分子药物设计的最新进展。我们比较了蛋白质结构预测方法，并探讨了配体结合口袋在基于结构的药物设计中的作用。我们研究了各种用于优化药物候选物的结构特征，包括官能团、立体化学和分子量。讨论了诸如分子对接和虚拟筛选等计算工具，以预测和优化药物候选物的结构。我们给出了基于分子结构设计的药物候选物的实例，并讨论了该领域的未来方向。通过有效地将结构信息与其他有价值的数据源相结合，我们可以改善药物发现过程，从而鉴定出具有更好疗效、特异性和安全性的新型治疗药物。
