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Advances in the Computational Identification of Allosteric Sites and Pathways in Proteins

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Protein Allostery in Drug Discovery

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1163))

Abstract

With the increasing difficulty to develop new drugs and the emergence of resistance to traditional orthosteric-site inhibitors, the search for alternatives is finally approaching the focus on allosteric sites. Allosteric sites offer opportunities to regulate many pharmacologically targeted pathways by inhibition or activation. In addition, allosteric sites tend to be less conserved than the functional site, which may facilitate the design of specific effectors in the protein families for which specific orthosteric inhibitors have proved difficult to design. Furthermore, recent evidence suggests that all proteins might be susceptible of allosteric regulation, increasing the space of druggable targets. Computational identification of allosteric sites has therefore become an active field of research. The problem can be approached from two sides: (1) the identification of allosteric-communication pathways between the functional site and potential allosteric sites and (2) the functional-site-independent identification of allosteric sites. While the first approach tends to be more laborious and thus restricted to a single protein, the second tends to be more amenable to larger-scale analysis, thus providing tools for the two drug discovery scenarios: the analysis of known targets and the screening for new potential targets. Here, I show some basic concepts and methods useful to the identification of allosteric sites and pathways, in line with these two approaches. I describe them in some detail to build a clear framework, at the risk of losing the interest of experts. Examples of recent studies involving these methods are also illustrated, focusing on the techniques rather than on their findings on allosterism.

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Acknowledgements

The Spanish Ministry for Science, Innovation and Universities is acknowledged for financial support under grant BIO2015-66674-R.

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  1. Catalan Institution for Research and Advanced Studies (ICREA) and Institute of Biotechnology and Biomedicine, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain

    Xavier Daura

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Correspondence to Xavier Daura .

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  1. Department of Pathophysiology, Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University, School of Medicine, Shanghai, China

    Jian Zhang

  2. Cancer and Inflammation Program, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD, USA, Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel

    Ruth Nussinov

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Daura, X. (2019). Advances in the Computational Identification of Allosteric Sites and Pathways in Proteins. In: Zhang, J., Nussinov, R. (eds) Protein Allostery in Drug Discovery. Advances in Experimental Medicine and Biology, vol 1163. Springer, Singapore. https://doi.org/10.1007/978-981-13-8719-7_7

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