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Cavity/Binding Site Prediction Approaches and Their Applications

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Computer-Aided Drug Design

Abstract

The binding site of a protein governs its function by allowing binding of small and macromolecules such as nucleic acids, proteins, and other molecules. These binding molecules, also known as ligands, generally form non-covalent bonds and have transient interactions and dissociate after performing a function. The binding sites are unique and have shape complementarity to its ligands to maintain the specificity and affinity. For example, molecules such as hormones, activators, inhibitors, neuro-transmitters, and toxins have specificity in their binding sites. A ligand-binding site entails vast information about its biological function, such as the geometry, physicochemical properties, and electrostatic charge, which in turn allows binding for the highly specific ligand. Various experimental methods such as X-ray crystallography, mass spectrometry, nuclear magnetic resonance, and isothermal titration calorimetry are used to determine the binding site of proteins. For drug discovery, it is inevitable to use high throughput screening of binding sites of proteins, and computational methods give an efficient and cost-effective way of analyzing the same. Several algorithms, tools, and software are available to detect protein cavities computationally. The study of binding sites is relevant to various fields of research, including computer-aided drug design, agrochemical design, cancer mechanisms, drug formulation, and physiological regulation.

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The authors declare that they have no competing interests.

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Authors and Affiliations

  1. Department of Computational Biology and Bioinformatics, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj, Uttar Pradesh, India

    Himanshu Avashthi

  2. College of Biotechnology, Uttar Pradesh Pandit Deen Dayal Upadhyaya Pashu Chikitsa Vigyan Vishwavidyalaya Evam Go-Anusandhan Sansthan, Mathura, Uttar Pradesh, India

    Himanshu Avashthi

  3. Department of Biotechnology, Indian Institute of Technology, Madras, Chennai, Tamil Nadu, India

    Ambuj Srivastava

  4. Department of Biotechnology, Institute of Biosciences and Biotechnology, Chhatrapati Shahu Ji Maharaj University, Kanpur, Uttar Pradesh, India

    Dev Bukhsh Singh

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  1. Department of Biotechnology, Institute of Biosciences and Biotechnology, Chhatrapati Shahu Ji Maharaj University, Kanpur, Uttar Pradesh, India

    Dev Bukhsh Singh

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Avashthi, H., Srivastava, A., Singh, D.B. (2020). Cavity/Binding Site Prediction Approaches and Their Applications. In: Singh, D.B. (eds) Computer-Aided Drug Design. Springer, Singapore. https://doi.org/10.1007/978-981-15-6815-2_3

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