Jukič Marko, Kralj Sebastjan, Kolarič Anja, Bren Urban
Laboratory of Physical Chemistry and Chemical Thermodynamics, Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova ulica 17, SI-2000 Maribor, Slovenia.
Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška ulica 8, SI-6000 Koper, Slovenia.
Pharmaceuticals (Basel). 2023 Aug 17;16(8):1170. doi: 10.3390/ph16081170.
Peptides, or short chains of amino-acid residues, are becoming increasingly important as active ingredients of drugs and as crucial probes and/or tools in medical, biotechnological, and pharmaceutical research. Situated at the interface between small molecules and larger macromolecular systems, they pose a difficult challenge for computational methods. We report an in silico peptide library generation and prioritization workflow using CmDock for identifying tetrapeptide ligands that bind to Fc regions of antibodies that is analogous to known in vitro recombinant peptide libraries' display and expression systems. The results of our in silico study are in accordance with existing scientific literature on in vitro peptides that bind to antibody Fc regions. In addition, we postulate an evolving in silico library design workflow that will help circumvent the combinatorial problem of in vitro comprehensive peptide libraries by focusing on peptide subunits that exhibit favorable interaction profiles in initial in silico peptide generation and testing.
肽,即氨基酸残基的短链,作为药物的活性成分以及医学、生物技术和制药研究中的关键探针和/或工具,正变得越来越重要。肽位于小分子和大分子系统之间的界面,对计算方法构成了艰巨挑战。我们报告了一种使用CmDock进行计算机模拟肽库生成和优先级排序的工作流程,用于识别与抗体Fc区域结合的四肽配体,这类似于已知的体外重组肽库的展示和表达系统。我们计算机模拟研究的结果与现有关于结合抗体Fc区域的体外肽的科学文献一致。此外,我们提出了一种不断发展的计算机模拟库设计工作流程,该流程将通过关注在初始计算机模拟肽生成和测试中表现出良好相互作用特征的肽亚基,帮助规避体外综合肽库的组合问题。