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Pharmacophore-based screening of diamidine small molecule inhibitors for protein arginine methyltransferases.

ABSTRACT: Protein arginine methyltransferases (PRMTs) are essential epigenetic and post-translational regulators in eukaryotic organisms. Dysregulation of PRMTs is intimately related to multiple types of human diseases, particularly cancer. Based on the previously reported PRMT1 inhibitors bearing the diamidine pharmacophore, we performed virtual screening to identify additional amidine-associated structural analogs. Subsequent enzymatic tests and characterization led to the discovery of a top lead K313 (2-(4-((4-carbamimidoylphenyl)amino)phenyl)-1H-indole-6-carboximidamide), which possessed low-micromolar potency with biochemical IC₅₀ of 2.6 μM for human PRMT1. Limited selectivity was observed over some other PRMT isoforms such as CARM1 and PRMT7. Molecular modeling and inhibition pattern studies suggest that K313 is a nonclassic noncompetitive inhibitor to PRMT1. K313 significantly inhibited cell proliferation and reduced the arginine asymmetric dimethylation level in the leukaemia cancer cells.

SUBMITTER: Qian K

PROVIDER: S-EPMC8130551 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Pharmacophore-based screening of diamidine small molecule inhibitors for protein arginine methyltransferases.

Qian Kun K Yan Chunli C Su Hairui H Dang Tran T Zhou Bo B Wang Zhenyu Z Zhao Xinyang X Ivanov Ivaylo I Ho Meng-Chiao MC Zheng Y George YG

RSC medicinal chemistry 20200930 1

Protein arginine methyltransferases (PRMTs) are essential epigenetic and post-translational regulators in eukaryotic organisms. Dysregulation of PRMTs is intimately related to multiple types of human diseases, particularly cancer. Based on the previously reported PRMT1 inhibitors bearing the diamidine pharmacophore, we performed virtual screening to identify additional amidine-associated structural analogs. Subsequent enzymatic tests and characterization led to the discovery of a top lead K313 ( ...[more]

PMID: 34046601

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Project description:Protein-protein interactions play important roles in virtually all cellular processes, making them enticing targets for modulation by small-molecule therapeutics: specific examples have been well validated in diseases ranging from cancer and autoimmune disorders, to bacterial and viral infections. Despite several notable successes, however, overall these remain a very challenging target class. Protein interaction sites are especially challenging for computational approaches, because the target protein surface often undergoes a conformational change to enable ligand binding: this confounds traditional approaches for virtual screening. Through previous studies, we demonstrated that biased "pocket optimization" simulations could be used to build collections of low-energy pocket-containing conformations, starting from an unbound protein structure. Here, we demonstrate that these pockets can further be used to identify ligands that complement the protein surface. To do so, we first build from a given pocket its "exemplar": a perfect, but nonphysical, pseudoligand that would optimally match the shape and chemical features of the pocket. In our previous studies, we used these exemplars to quantitatively compare protein surface pockets to one another. Here, we now introduce this exemplar as a template for pharmacophore-based screening of chemical libraries. Through a series of benchmark experiments, we demonstrate that this approach exhibits comparable performance as traditional docking methods for identifying known inhibitors acting at protein interaction sites. However, because this approach is predicated on ligand/exemplar overlays, and thus does not require explicit calculation of protein-ligand interactions, exemplar screening provides a tremendous speed advantage over docking: 6 million compounds can be screened in about 15 min on a single 16-core, dual-GPU computer. The extreme speed at which large compound libraries can be traversed easily enables screening against a "pocket-optimized" ensemble of protein conformations, which in turn facilitates identification of more diverse classes of active compounds for a given protein target.

Dataset Information

Pharmacophore-based screening of diamidine small molecule inhibitors for protein arginine methyltransferases.

Publications

Pharmacophore-based screening of diamidine small molecule inhibitors for protein arginine methyltransferases.

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