Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Belgrade, Vojvode Stepe 450, 11000 Belgrade, Serbia.
EaStCHEM School of Chemistry and Biomedical Sciences Research Complex, University of St Andrews, St Andrews KY16 9ST, United Kingdom.
Curr Med Chem. 2019;26(21):3874-3889. doi: 10.2174/0929867324666170712115411.
Computer-Aided Drug Design has strongly accelerated the development of novel antineoplastic agents by helping in the hit identification, optimization, and evaluation.
Computational approaches such as cheminformatic search, virtual screening, pharmacophore modeling, molecular docking and dynamics have been developed and applied to explain the activity of bioactive molecules, design novel agents, increase the success rate of drug research, and decrease the total costs of drug discovery. Similarity, searches and virtual screening are used to identify molecules with an increased probability to interact with drug targets of interest, while the other computational approaches are applied for the design and evaluation of molecules with enhanced activity and improved safety profile.
In this review are described the main in silico techniques used in rational drug design of antineoplastic agents and presented optimal combinations of computational methods for design of more efficient antineoplastic drugs.
计算机辅助药物设计通过帮助命中鉴定、优化和评估，极大地加速了新型抗肿瘤药物的开发。
已经开发并应用了计算方法，如化学信息搜索、虚拟筛选、药效团建模、分子对接和动力学，以解释生物活性分子的活性、设计新型药物、提高药物研究成功率和降低药物发现的总成本。相似地，搜索和虚拟筛选用于识别与感兴趣的药物靶点相互作用概率增加的分子，而其他计算方法则用于设计和评估具有增强活性和改善安全性的分子。
本文描述了用于抗肿瘤药物合理设计的主要计算机辅助技术，并提出了用于设计更有效的抗肿瘤药物的计算方法的最佳组合。
