Abstract
A key question confronting computational chemists concerns the preferable ligand geometry that fits complementarily into the receptor pocket. Typically, the postulated ‘bioactive’ 3D ligand conformation is constructed as a ‘sophisticated guess’ (unnecessarily geometry-optimized) mirroring the pharmacophore hypothesis—sometimes based on an erroneous prerequisite. Hence, 4D-QSAR scheme and its ‘dialects’ have been practically implemented as higher level of model abstraction that allows the examination of the multiple molecular conformation, orientation and protonation representation, respectively. Nearly a quarter of a century has passed since the eminent work of Hopfinger appeared on the stage; therefore the natural question occurs whether 4D-QSAR approach is still appealing to the scientific community? With no intention to be comprehensive, a review of the current state of art in the field of receptor-independent (RI) and receptor-dependent (RD) 4D-QSAR methodology is provided with a brief examination of the ‘mainstream’ algorithms. In fact, a myriad of 4D-QSAR methods have been implemented and applied practically for a diverse range of molecules. It seems that, 4D-QSAR approach has been experiencing a promising renaissance of interests that might be fuelled by the rising power of the graphics processing unit (GPU) clusters applied to full-atom MD-based simulations of the protein-ligand complexes.
Highlights
A quarter of a century has passed since the eminent work of Hopfinger appeared on the stage [1]; a natural question arises: Is the 4D-quantitative structure-activity relationship (QSAR) approach still attractive to computational chemists? A rational production/prediction of ADMET-tailored properties in the hit→lead→seed→drug cascade is a challenging object of interest for contemporary chemistry, that necessitates at least four German G’s: Glück, Geld, Geschick and Geduld—the rank order of which depends on the discovery project under scrutiny [2,3]
The application of alignment-independent descriptors does not address the issues of the proper conformer selection; 4D-QSAR scheme and its ‘dialects’ have been practically implemented as higher level of a model abstraction that allows the investigation of the multiple molecular conformation, orientation and protonation representation, respectively [25,26,27,28]
The adaptive and competitive Kohonen algorithm was used in order to produce planar (2D) topographic maps, that represent the signals from chosen atoms of the molecular trajectory
Summary
A quarter of a century has passed since the eminent work of Hopfinger appeared on the stage [1]; a natural question arises: Is the 4D-QSAR approach still attractive to computational chemists? A rational production/prediction of ADMET-tailored properties (in other words finding a ‘sweet spot’) in the hit→lead→seed→drug cascade is a challenging object of interest for contemporary chemistry, that necessitates at least four German G’s: Glück (luck), Geld (money), Geschick (skill) and Geduld (patience)—the rank order of which depends on the discovery project under scrutiny [2,3]. The application of alignment-independent descriptors does not address the issues of the proper conformer selection; 4D-QSAR scheme and its ‘dialects’ have been practically implemented as higher level of a model abstraction that allows the investigation of the multiple molecular conformation, orientation and protonation representation, respectively [25,26,27,28]. A distinct site-directed 4D-QSAR approach has been promoted recently, where the resultant 3D-pharmacophore pattern is directly dependent upon the explicit geometry of the binding/active pocket in order to capture the potential induced-fit phenomena, especially for the conformationally flexible ligand analogues [52,53,54,55]. RD 4D-QSAR models qualitatively ‘captured’ the valid regions of the TR receptor
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