Protein–Ligand Informatics Force Field (PLIff): Toward a Fully Knowledge Driven “Force Field” for Biomolecular Interactions

• Published in: Journal of medicinal chemistry 2016-07, Vol.59 (14), p.6891-6902
• Main Authors: Verdonk, Marcel L, Ludlow, R. Frederick, Giangreco, Ilenia, Rathi, Prakash Chandra
• Format: Article
• Language: English
• Subjects: Algorithms; Computational Biology; Databases, Protein; Knowledge Bases; Ligands; Models, Molecular; Molecular Structure; Proteins - chemistry; Structure-Activity Relationship
• ISSN: 0022-2623; 1520-4804
• DOI: 10.1021/acs.jmedchem.6b00716

The Protein Data Bank (PDB) contains a wealth of data on nonbonded biomolecular interactions. If this information could be distilled down to nonbonded interaction potentials, these would have some key advantages over standard force fields. However, there are some important outstanding issues to address in order to do this successfully. This paper introduces the protein–ligand informatics “force field”, PLIff, which begins to address these key challenges (https://bitbucket.org/AstexUK/pli). As a result of their knowledge-based nature, the next-generation nonbonded potentials that make up PLIff automatically capture a wide range of interaction types, including special interactions that are often poorly described by standard force fields. We illustrate how PLIff may be used in structure-based design applications, including interaction fields, fragment mapping, and protein–ligand docking. PLIff performs at least as well as state-of-the art scoring functions in terms of pose predictions and ranking compounds in a virtual screening context.