4D-QSAR: perspectives in drug design

Abstract

Drug design is a process driven by innovation and technological breakthroughs involving a combination of advanced experimental and computational methods. A broad variety of medicinal chemistry approaches can be used for the identification of hits, generation of leads, as well as to accelerate the optimization of leads into drug candidates. The quantitative structure-activity relationship (QSAR) formalisms are among the most important strategies that can be applied for the successful design new molecules. This review provides a comprehensive review on the evolution and current status of 4D-QSAR, highlighting present challenges and new opportunities in drug design.

Figure 1

Schematic representation of the processes included in a lead optimization from the hit identification. QSAR methods are essential to reach this goal.

Figure 2

Schematic representation of the 4D-QSAR steps for the generation of models.

Figure 3

(A) Representation of the RI-4D-QSAR postulated “bioactive” conformation of the most potent inhibitor (ATT14) of the training set docked at the TMPKmt active site. Only the main interacting residues in the pocket of the binding site are shown in stick model representations (carbon atoms in gray). The inhibitor ATT14 is presented as stick models (carbon atoms in magenta). The GCODs of the best 4D-QSAR model are also shown in the active site of the crystal structure of TMPKmt, represented as spheres of 1 Å radius. Inhibition-enhancing and inhibition diminishing GCODs are shown, respectively, as yellow and red spheres. The IPEs atom types are as follows: A = any; NP = nonpolar; HA = hydrogen bond acceptor. (B) Chemical structure of ATT14, showing the main regions that contain pharmacophore sites, such as the sugar-pyrimidine ring structure and the 5′-arylthiourea moiety, which further can be explored to identify better inhibitors of TMPKmt.

Figure 4

Operational steps in performing a RD-4D-QSAR analysis.