1. Computational approaches for the design of modulators targeting protein-protein interactions
- Author
-
Rehman, Ashfaq Ur, Khurshid, Beenish, Ali, Yasir, Rasheed, Salman, Wadood, Abdul, Ng, Ho-Leung, Chen, Hai-Feng, Wei, Zhiqiang, Luo, Ray, and Zhang, Jian
- Subjects
Pharmacology and Pharmaceutical Sciences ,Biomedical and Clinical Sciences ,Networking and Information Technology R&D (NITRD) ,Good Health and Well Being ,Humans ,Protein Binding ,Drug Discovery ,Proteins ,Molecular Dynamics Simulation ,Drug Delivery Systems ,Computational Biology ,Protein-protein interactions ,Computer-aided drug design ,computational approaches ,machine-based learning ,molecular dynamics simulations ,docking ,screening ,Pharmacology & Pharmacy ,Pharmacology and pharmaceutical sciences - Abstract
BackgroundProtein-protein interactions (PPIs) are intriguing targets for designing novel small-molecule inhibitors. The role of PPIs in various infectious and neurodegenerative disorders makes them potential therapeutic targets . Despite being portrayed as undruggable targets, due to their flat surfaces, disorderedness, and lack of grooves. Recent progresses in computational biology have led researchers to reconsider PPIs in drug discovery.Areas coveredIn this review, we introduce in-silico methods used to identify PPI interfaces and present an in-depth overview of various computational methodologies that are successfully applied to annotate the PPIs. We also discuss several successful case studies that use computational tools to understand PPIs modulation and their key roles in various physiological processes.Expert opinionComputational methods face challenges due to the inherent flexibility of proteins, which makes them expensive, and result in the use of rigid models. This problem becomes more significant in PPIs due to their flexible and flat interfaces. Computational methods like molecular dynamics (MD) simulation and machine learning can integrate the chemical structure data into biochemical and can be used for target identification and modulation. These computational methodologies have been crucial in understanding the structure of PPIs, designing PPI modulators, discovering new drug targets, and predicting treatment outcomes.
- Published
- 2023