Tavares Camila A, Santos Taináh M R, Gonçalves Mateus A, da Cunha Elaine F F, Ramalho Teodorico C
Laboratory of Molecular Modelling, Department of Chemistry, Federal University of Lavras, Lavras - MG, 37200-000, Brazil.
Department of Chemistry, Faculty of Science, University of Hradec Králové, Hradec Králové, 500 03, Czech Republic.
Mini Rev Med Chem. 2024;24(11):1063-1069. doi: 10.2174/0113895575250433231103063707.
Since its early days in the 19th century, medicinal chemistry has concentrated its efforts on the treatment of diseases, using tools from areas such as chemistry, pharmacology, and molecular biology. The understanding of biological mechanisms and signaling pathways is crucial information for the development of potential agents for the treatment of diseases mainly because they are such complex processes. Given the limitations that the experimental approach presents, computational chemistry is a valuable alternative for the study of these systems and their behavior. Thus, classical molecular dynamics, based on Newton's laws, is considered a technique of great accuracy, when appropriated force fields are used, and provides satisfactory contributions to the scientific community. However, as many configurations are generated in a large MD simulation, methods such as Statistical Inefficiency and Optimal Wavelet Signal Compression Algorithm are great tools that can reduce the number of subsequent QM calculations. Accordingly, this review aims to briefly discuss the importance and relevance of medicinal chemistry allied to computational chemistry as well as to present a case study where, through a molecular dynamics simulation of AMPK protein (50 ns) and explicit solvent (TIP3P model), a minimum number of snapshots necessary to describe the oscillation profile of the protein behavior was proposed. For this purpose, the RMSD calculation, together with the sophisticated OWSCA method was used to propose the minimum number of snapshots.
自19世纪初期以来，药物化学一直致力于利用化学、药理学和分子生物学等领域的工具来治疗疾病。对生物机制和信号通路的理解是开发潜在疾病治疗药物的关键信息，主要是因为这些过程非常复杂。鉴于实验方法存在的局限性，计算化学是研究这些系统及其行为的一种有价值的替代方法。因此，基于牛顿定律的经典分子动力学，在使用合适的力场时，被认为是一种精度很高的技术，并为科学界做出了令人满意的贡献。然而，由于在大型分子动力学模拟中会生成许多构型，统计无效率和最优小波信号压缩算法等方法是可以减少后续量子力学计算数量的强大工具。因此，本综述旨在简要讨论药物化学与计算化学相结合的重要性和相关性，并通过对AMPK蛋白（50纳秒）和显式溶剂（TIP3P模型）进行分子动力学模拟的案例研究，提出描述蛋白质行为振荡轮廓所需的最少快照数量。为此，使用均方根偏差计算以及复杂的最优小波信号压缩算法来提出最少快照数量。
