Department of Biotechnology, Chemistry and Pharmacy (Dept. of Excellence 2018-2022), University of Siena, via A. Moro 2, 53100 Siena, Italy.
Toscana Life Sciences Foundation, via Fiorentina 1, 53100 Siena, Italy.
Curr Top Med Chem. 2019;19(7):534-554. doi: 10.2174/1568026619666190304153901.
Identification of Protein-Protein Interactions (PPIs) is a major challenge in modern molecular biology and biochemistry research, due to the unquestionable role of proteins in cells, biological process and pathological states. Over the past decade, the PPIs have evolved from being considered a highly challenging field of research to being investigated and examined as targets for pharmacological intervention.
Comprehension of protein interactions is crucial to known how proteins come together to build signalling pathways, to carry out their functions, or to cause diseases, when deregulated. Multiplicity and great amount of PPIs structures offer a huge number of new and potential targets for the treatment of different diseases.
Computational techniques are becoming predominant in PPIs studies for their effectiveness, flexibility, accuracy and cost. As a matter of fact, there are effective in silico approaches which are able to identify PPIs and PPI site. Such methods for computational target prediction have been developed through molecular descriptors and data-mining procedures.
In this review, we present different types of interactions between protein-protein and the application of in silico methods for design and development of drugs targeting PPIs. We described computational approaches for the identification of possible targets on protein surface and to detect of stimulator/ inhibitor molecules.
A deeper study of the most recent bioinformatics methodologies for PPIs studies is vital for a better understanding of protein complexes and for discover new potential PPI modulators in therapeutic intervention.
蛋白质-蛋白质相互作用(PPIs)的鉴定是现代分子生物学和生物化学研究的主要挑战,这是由于蛋白质在细胞、生物过程和病理状态中所起的不可置疑的作用。在过去的十年中,PPIs 已经从一个极具挑战性的研究领域发展成为药理学干预的研究和检验目标。
理解蛋白质相互作用对于了解蛋白质如何聚集形成信号通路、发挥其功能或在失调时导致疾病至关重要。大量的蛋白质相互作用结构为治疗不同疾病提供了大量新的和潜在的靶点。
计算技术在 PPIs 研究中因其有效性、灵活性、准确性和成本而占据主导地位。事实上,有一些有效的计算方法能够识别蛋白质相互作用和相互作用位点。这些用于计算靶点预测的方法是通过分子描述符和数据挖掘程序开发的。
在这篇综述中,我们介绍了蛋白质-蛋白质之间的不同类型的相互作用,以及计算方法在设计和开发针对 PPIs 的药物中的应用。我们描述了用于识别蛋白质表面上可能的靶点和检测刺激剂/抑制剂分子的计算方法。
深入研究最新的生物信息学方法对于更好地理解蛋白质复合物和发现治疗干预中的新的潜在 PPI 调节剂至关重要。