The GRID/CPCA approach in drug discovery

Abstract

Importance of the field: Bimolecular recognition is the basis for almost all processes in biological systems. The geometrical and chemical complementarity of small molecule ligands and their macromolecular biological targets, matching paired interacting parts, can result in binding that will eventually yield a biological response.Areas covered in this review: The topics covered include the integration of molecular interaction fields and chemometrics, via the GRID/CPCA (consensus principal component analysis) method that is actively contributing to the optimization of potency and selectivity of ligands towards a chosen target. Key applications that hallmark the usefulness of the method are critically presented. By comparison of the GRID/CPCA and GRID/PCA, the breakthroughs and challenges are highlighted.What the reader will gain: Molecular recognition studies support the development of pharmacophore-based descriptors, which provide the means to identify new ligand templates (‘scaffold-hopping’). The GRID/CPCA approach can simultaneously reveal common trends in more than one block of data for more than two target proteins, with several three-dimensional structures per protein. It offers the benefit of improving the weighting between different interaction energy probes within the GRID parameterization. An important consequence is that hydrophobic interactions can be assessed for selectivity between proteins.Take home message: Molecular-field-based methods along with CPCA analysis are extremely powerful to understand bimolecular interactions. Because drug discovery and development is a costly, time consuming and high-risk activity and GRID/CPCA is at the forefront of the computer-aided design, it should be used as early as possible for discovering new drugs.