Molecular Bio-Computation & Drug Design Lab, School of Health Sciences, University of KwaZulu-Natal, Westville, Durban, 4000, South Africa.
Faculté Des Sciences Semlalia, Département de Chimie, Université Cadi Ayyad, Av. My Abdellah, BP2390, Marrakech, Morocco.
Protein J. 2020 Apr;39(2):97-105. doi: 10.1007/s10930-020-09884-2.
The pace and efficiency of drug target strategies have been emanating debates among researchers in the field of drug development. Covalent inhibitors possess significant advantages over non-covalent inhibitors, such that covalent warheads can target rare residues of a particular target protein, thus leading to the development of highly selective inhibitors. However, toxicity can be a real challenge related to this class of therapeutics. From the challenges of irreversible drug toxicity to the declining reactivity of reversible drugs, herein we provide justifications from the computational point of view. It was evident that both classes had its merits; however, with the increase in drug resistance, covalent inhibition seemed more suitable. There also seems to be enhanced selectivity of the covalent systems, proving its use as a therapeutic regimen worldwide. We believe that this study will assist researchers in making informed decisions on which drug class to choose as lead compounds in the drug discovery pipeline.
药物靶点策略的速度和效率一直在引发药物开发领域研究人员的争论。共价抑制剂相对于非共价抑制剂具有显著优势，使得共价弹头可以靶向特定靶蛋白的罕见残基，从而开发出高选择性抑制剂。然而，毒性可能是与这类治疗剂相关的一个真正挑战。从不可逆药物毒性的挑战到可逆药物反应性的下降，本文从计算角度提供了理由。显然，这两类药物都有其优点；然而，随着耐药性的增加，共价抑制似乎更合适。共价系统的选择性似乎也有所提高，证明了它在全球范围内作为一种治疗方案的应用。我们相信，这项研究将帮助研究人员在药物发现管道中选择哪个药物类别作为先导化合物做出明智的决策。
