Chemoinformatic Approaches for Inhibitors of DNA Methyltransferases: Comprehensive Characterization of Screening Libraries

Abstract

Virtual screening of compound databases is a promising approach to identify inhibitors of DNA methyltransferases and other epigenetic targets. An important first step before conducting virtual screening is to characterize the structural diversity and chemical space coverage of the screening collections. Herein, we report a comprehensive chemoinformatic characterization of novel screening libraries, including a focused collection directed to inhibitors of DNA methyltransferases (DNMTs), and two natural product databases. The compound databases were assessed in terms of physicochemical properties, molecular scaffolds, and fingerprints. As part of the scaffold diversity analysis, a recently developed method, based on Shannon Entropy, was used. The overall approach enabled the analysis of property space coverage, degree of overlap between collections, scaffold and structural diversity. Overall, the analysis of the distribution of physicochemical properties indicates that the DNMT focused library and the two natural products collections have molecules with properties similar to approved drugs. Moreover, the natural products databases analyzed in this work have different chemical structures from approved drugs and synthetic databases and therefore are attractive for virtual screening for DNMT inhibitors. The scaffold analysis revealed that the focused library has, overall, the largest scaffold diversity and that the most frequent scaffolds are not identified in the other analyzed collections. Therefore, the focused library is also attractive to perform virtual and experimental screening for novel inhibitors. This study represents a first step towards the virtual screening of novel compound databases to identify inhibitors of DNMTs. Results of this study are general and can be used for the virtual screening of the compound databases against targets directed to other therapeutic applications.

Activity landscape of DNA methyltransferase inhibitors bridges chemoinformatics with epigenetic drug discovery

“…Analyses of libraries enlisting DNMTi have been performed in order to characterize the chemical space of DNMTi using physicochemical properties and fingerprints to assess similarity of the compounds [9,53]. Nonetheless, research addressing the SAR of large sets of DNMTi is scarce [9].…”

Molecular Scaffold Analysis of Natural Products Databases in the Public Domain

“…A remarkable feature of the scaffolds of Johnson and Xu to compare compound collections is that molecules classified in a scaffold do not lie in any other chemotype class (39). The MEQI approach has been extensively used to classify compound collections (23,31,40,41).…”

“…Therefore, SSE values closer to 1.0 indicate large diversity within the n most populated scaffolds. This measure is discussed elsewhere (23,41).…”

Inhibitors of DNA Methyltransferases: Insights from Computational Studies

“…Molecular dynamics simulations of different methyltransferases and docking models of inhibitors bound to DNMT1 and DNMT3B have provided additional structural information of the protein-ligand recognition process and the role of the cofactor SAM in this process. Virtual screening using similarity searching with recently developed DNMT focused libraries is an attractive alternative approach to identify novel inhibitors [84]. It is expected that the further integration of molecular modeling and chemoinformatics with experimental approaches will continue to advance the development of epigenetic therapies targeting DNA methyltransferases.…”