National Centre for Aquatic Animal Health, Cochin University of Science and Technology, Kochi, India.
Bioinformatics Facility, Rajiv Gandhi Centre for Biotechnology, Thiruvananthapuram, India.
Drug Dev Res. 2020 Sep;81(6):685-699. doi: 10.1002/ddr.21673. Epub 2020 Apr 23.
The designing of drugs that can simultaneously affect different protein targets is one novel and promising way to treat complex diseases. Multitarget drugs act on multiple protein receptors each implicated in the same disease state, and may be considered to be more beneficial than conventional drug therapies. For example, these drugs can have improved therapeutic potency due to synergistic effects on multiple targets, as well as improved safety and resistance profiles due to the combined regulation of potential primary therapeutic targets and compensatory elements and lower dosage typically required. This review analyzes in-silico methods that facilitate multitarget drug design that facilitate the discovery and development of novel therapeutic agents. Here presented is a summary of the progress in structure-based drug discovery techniques that study the process of molecular recognition of targets and ligands, moving from static molecular docking to improved molecular dynamics approaches in multitarget drug design, and the advantages and limitations of each.
设计能够同时影响不同蛋白质靶标的药物是治疗复杂疾病的一种新颖而有前途的方法。多靶标药物作用于多个与同一疾病状态相关的蛋白质受体,可能比传统药物治疗更有益。例如,这些药物由于对多个靶标产生协同作用,可能具有改善的治疗效力,并且由于对潜在主要治疗靶标和补偿元件的联合调节以及通常所需的较低剂量,具有改善的安全性和耐药性特征。本综述分析了促进多靶标药物设计的计算方法,这些方法促进了新型治疗剂的发现和开发。这里总结了基于结构的药物发现技术的进展,这些技术研究了靶标和配体的分子识别过程,从静态分子对接发展到多靶标药物设计中的改进分子动力学方法,以及每种方法的优缺点。