Proteins are polymers of amino acids that are linked by peptide bonds and they are one of the major classes of bio-molecules existing in a living organism. Proteins are involved in various cellular functions and events like cell signaling, cell adhesion, metabolic reactions, in the generation of immune response and many more.
Proteins are known to interact physico-chemically with other proteins for maintaining regular physiological functions. These interactions are known as protein-protein interactions (PPIs). Any form of malfunctioning in proteins will lead to a disturbance in the homeostasis and, ultimately, all the physiological functions of the body can be disturbed. In reaction to several environmental and biochemical stimuli, a normal protein can be mutated and start interacting with another protein leading to the formation of anomalous PPIs. Similarly, a pathogenic protein may also be formed which becomes an integral part of pathogenesis leading to detrimental effects on the host cell. In brief, protein-protein interactions (PPIs) are considered as the critical property of cell sustenance.
From the past several years, experimental and computational approaches have been applied on PPIs for the determination of their interactions, abnormalities and various causes which lead to diseases or disruption in cell functionality.
This detailed review by Krishna Mohan Poluri and colleagues gives readers an insight into methods that help researchers understand the processes in which PPIs are involved in various clinical diseases and how these PPIs can be detected through computational means. The review covers computational methods used to predict, store and visualize PPIs. This is followed by an explanation of the decoding processes in these computational approaches to determine factors such as the source of infectious agents or specific disease states that affect PPIs. They then focused on computational methods used for designing novel small molecule inhibitors that can disrupt protein-protein interactions and act efficiently against the effects of debilitating diseases. The researchers have provided useful charts which list different computational tools and databases. These charts can help readers select their methods for their research projects. A summary of the challenges faced by researchers investigating PPIs through computational methods is also presented in their concluding remarks.
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