Abstract
GPCR modeling approaches are widely used in the hit-to-lead (H2L) and lead optimization (LO) stages of drug discovery. The aims of these modeling approaches are to predict the 3D structures of the receptor-ligand complexes, to explore the key interactions between the receptor and the ligand and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this book chapter, we present a brief survey of key computational approaches integrated with hierarchical GPCR modeling protocol (HGMP) used in hit-to-lead (H2L) and in lead optimization (LO) stages of structure-based drug discovery (SBDD). We outline the differences in modeling strategies used in H2L and LO of SBDD and illustrate how these tools have been applied in three drug discovery projects.
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References
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Acknowledgment
A.H. and A.T.-N. would like to acknowledge the support of EU H2020 CompBioMed project (http://www.compbiomed.eu/) and the BBSRC Flexible Interchanger Programme project (BB/P004245/1).
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Heifetz, A., Southey, M., Morao, I., Townsend-Nicholson, A., Bodkin, M.J. (2018). Computational Methods Used in Hit-to-Lead and Lead Optimization Stages of Structure-Based Drug Discovery. In: Heifetz, A. (eds) Computational Methods for GPCR Drug Discovery. Methods in Molecular Biology, vol 1705. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7465-8_19
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DOI: https://doi.org/10.1007/978-1-4939-7465-8_19
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