Towards rational computational peptide design.
Towards rational computational peptide design.
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DOI：
10.3389/fbinf.2022.1046493
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Perez, Alberto
中科院分区：
文献类型：
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作者：
Chang, Liwei;Mondal, Arup;Perez, Alberto
肽在生物学中很普遍，介导多达 40% 的蛋白质-蛋白质相互作用，并参与其他细胞功能，例如运输和信号传导。它们的高特异性结合能力使它们成为具有介于小分子和大生物制剂之间的中间特性的有前途的治疗剂。除了其生物学作用之外，肽还可以通过编程进行自组装，并且它们已经被用于寡核苷酸递送、组织再生或药物等多种功能。然而，它们相互作用的瞬态性质限制了可用的结构数量和结合亲和力的知识，并且它们的灵活性限制了预测这些分子的结构和亲和力的计算管道的成功。幸运的是，实验和计算管道的最新进展正在为该领域创造新的机会。我们开始看到对复杂结构、热力学和动力学性质的有希望的预测。我们相信，在接下来的几年里，这将带来强大的合理肽设计管道，并取得与小分子药物发现类似的成功。
Peptides are prevalent in biology, mediating as many as 40% of protein-protein interactions, and involved in other cellular functions such as transport and signaling. Their ability to bind with high specificity make them promising therapeutical agents with intermediate properties between small molecules and large biologics. Beyond their biological role, peptides can be programmed to self-assembly, and they are already being used for functions as diverse as oligonuclotide delivery, tissue regeneration or as drugs. However, the transient nature of their interactions has limited the number of structures and knowledge of binding affinities available–and their flexible nature has limited the success of computational pipelines that predict the structures and affinities of these molecules. Fortunately, recent advances in experimental and computational pipelines are creating new opportunities for this field. We are starting to see promising predictions of complex structures, thermodynamic and kinetic properties. We believe in the following years this will lead to robust rational peptide design pipelines with success similar to those applied for small molecule drug discovery.