Integrated Computational Approaches and Tools for Allosteric Drug Discovery

Authors

Olivier Sheik Amamuddy, Rhodes University
Wayde Veldman, Rhodes University
Colleen Manyumwa, Rhodes University
Afrah Khairallah, Rhodes University
Steve Agajanian, Chapman University
Odeyemi Oluyemi, Chapman University
Gennady M. Verkhivker, Chapman UniversityFollow
Özlem Tastan Bishop, Rhodes University

Document Type

Article

Publication Date

1-28-2020

Abstract

Understanding molecular mechanisms underlying the complexity of allosteric regulation in proteins has attracted considerable attention in drug discovery due to the benefits and versatility of allosteric modulators in providing desirable selectivity against protein targets while minimizing toxicity and other side effects. The proliferation of novel computational approaches for predicting ligand–protein interactions and binding using dynamic and network-centric perspectives has led to new insights into allosteric mechanisms and facilitated computer-based discovery of allosteric drugs. Although no absolute method of experimental and in silico allosteric drug/site discovery exists, current methods are still being improved. As such, the critical analysis and integration of established approaches into robust, reproducible, and customizable computational pipelines with experimental feedback could make allosteric drug discovery more efficient and reliable. In this article, we review computational approaches for allosteric drug discovery and discuss how these tools can be utilized to develop consensus workflows for in silico identification of allosteric sites and modulators with some applications to pathogen resistance and precision medicine. The emerging realization that allosteric modulators can exploit distinct regulatory mechanisms and can provide access to targeted modulation of protein activities could open opportunities for probing biological processes and in silico design of drug combinations with improved therapeutic indices and a broad range of activities.

Comments

This article was originally published in International Journal of Molecular Sciences, volume 21, in 2020. https://doi.org/10.3390/ijms21030847

Recommended Citation

Amamuddy, O.S.; Veldman, W.; Manyumwa, C.; Khairallah, A.; Agajanian, S.; Oluyemi, O.; Verkhivker, G.M.; Bishop, O.T. Integrated computational approaches and tools for allosteric drug discovery. International Journal of Molecular Sciences 2020, 21, 847. https://doi.org/10.3390/ijms21030847

Peer Reviewed

1

Copyright

The authors

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.