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Adv Protein Chem Struct Biol. 2014;96:1-37. doi: 10.1016/bs.apcsb.2014.06.001. Epub 2014 Aug 24.

The interplay between molecular modeling and chemoinformatics to characterize protein-ligand and protein-protein interactions landscapes for drug discovery.

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Mayo Clinic, Scottsdale, Arizona, USA. Electronic address:
Unilever Centre for Molecular Science Informatics, Department of Chemistry, University of Cambridge, Cambridge, United Kingdom.
Instituto de Química, Universidad Nacional Autónoma de México, Mexico City, Mexico.


Protein-ligand and protein-protein interactions play a fundamental role in drug discovery. A number of computational approaches have been developed to characterize and use the knowledge of such interactions that can lead to drug candidates and eventually compounds in the clinic. With the increasing structural information of protein-ligand and protein-protein complexes, the combination of molecular modeling and chemoinformatics approaches are often required for the efficient analysis of a large number of such complexes. In this chapter, we review the progress on the developments of in silico approaches that are at the interface between molecular modeling and chemoinformatics. Although the list of methods and applications is not exhaustive, we aim to cover representative cases with a special emphasis on interaction fingerprints and their applications to identify "hot spots." We also elaborate on proteochemometric modeling and the emerging concept of activity landscape, structure-based interpretation of activity cliffs and structure-protein-ligand interaction relationships. Target-ligand relationships are discussed in the context of chemogenomics data sets.


2D interaction maps; 3D activity cliffs; Activity cliff generators; Hot spots; Interaction fingerprint; Pharmacophore; Protein–ligand interaction fingerprints; Proteochemometric modeling; Structure protein–ligand interaction relationships; Structure–activity relationships

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