Ben Geoffrey A S, Agrawal Deepak, Kulkarni Nagaraj M, Gunasekaran Manonmani
Sravathi AI Technology Pvt. Ltd., 63-B, First Floor, Bommasandra Industrial Area, Bengaluru 560099, Karnataka, India.
ACS Omega. 2025 Feb 5;10(7):6650-6662. doi: 10.1021/acsomega.4c08049. eCollection 2025 Feb 25.
Protein function modulation using small-molecule binding is an important therapeutic strategy for many diseases. However, many proteins remain undruggable due to the lack of suitable binding pockets for small-molecule binding. Proximity-induced protein degradation using molecular glues has recently been identified as an important strategy to target undruggable proteins. Molecular glues were discovered serendipitously and as such currently lack an established approach for in-silico-driven rationale design. In this work, we aim to establish an in-silico method for designing molecular glues. To achieve this, we leverage known molecular glue-mediated ternary complexes and derive a rationale for the in-silico design of molecular glues. Establishing an in-silico rationale for molecular glue design would significantly contribute to the literature and accelerate the discovery of molecular glues for targeting previously undruggable proteins. Our work presented here and named Molecular Glue-Designer-Evaluator (MOLDE) contributes to the growing literature of in-silico approaches to drug design in-silico literature.
利用小分子结合来调节蛋白质功能是治疗多种疾病的重要策略。然而,由于缺乏适合小分子结合的口袋,许多蛋白质仍然难以成药。最近,利用分子胶进行邻近诱导的蛋白质降解已被确定为靶向难以成药蛋白质的重要策略。分子胶是偶然发现的,因此目前缺乏用于计算机驱动的合理设计的既定方法。在这项工作中,我们旨在建立一种用于设计分子胶的计算机方法。为了实现这一目标,我们利用已知的分子胶介导的三元复合物,并推导分子胶计算机设计的基本原理。建立分子胶设计的计算机基本原理将对文献做出重大贡献,并加速发现用于靶向先前难以成药蛋白质的分子胶。我们在此展示的名为分子胶设计-评估器(MOLDE)的工作,为计算机辅助药物设计的文献不断增长做出了贡献。