Dataset Information

Design of MMP-1 inhibitors via SAR transfer and experimental validation.

ABSTRACT: New matrix metalloproteinase 1 (MMP-1) inhibitors were predicted using the structure-activity relationship (SAR) transfer method based on a series of analogues of kinesin-like protein 11 (KIF11) inhibitors. Compounds 5-7 predicted to be highly potent against MMP-1 were synthesized and tested for MMP-1 inhibitory activity. Among these, compound 6 having a Cl substituent at the R¹ site was found to possess ca. 3.5 times higher inhibitory activity against MMP-1 than the previously reported compound 4. The observed potency was consistent with the presence of an SAR transfer event between analogous MMP-1 and KIF11 inhibitors. Pharmacophore fitting revealed that the higher inhibitory activity of compound 6 compared to compound 4 against MMP-1 might be due to a halogen bond interaction between the Cl substituent of compound 6 and residue ARG214 of MMP-1.

SUBMITTER: Umedera K

PROVIDER: S-EPMC9719525 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Design of MMP-1 inhibitors via SAR transfer and experimental validation.

Umedera Kohei K Yoshimori Atsushi A Bajorath Jürgen J Nakamura Hiroyuki H

Scientific reports 20221203 1

New matrix metalloproteinase 1 (MMP-1) inhibitors were predicted using the structure-activity relationship (SAR) transfer method based on a series of analogues of kinesin-like protein 11 (KIF11) inhibitors. Compounds 5-7 predicted to be highly potent against MMP-1 were synthesized and tested for MMP-1 inhibitory activity. Among these, compound 6 having a Cl substituent at the R<sup>1</sup> site was found to possess ca. 3.5 times higher inhibitory activity against MMP-1 than the previously report ...[more]

PMID: 36463250

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Project description:Histones are small proteins critical to the efficient packaging of DNA in the nucleus. DNA–protein complexes, known as nucleosomes, are formed when the DNA winds itself around the surface of the histones. The methylation of histone residues by enhancer of zeste homolog 2 (EZH2) maintains gene repression over successive cell generations. Overexpression of EZH2 can silence important tumor suppressor genes leading to increased invasiveness of many types of cancers. This makes the inhibition of EZH2 an important target in the development of cancer therapeutics. We employed a three-stage computational de novo peptide design method to design inhibitory peptides of EZH2. The method consists of a sequence selection stage and two validation stages for fold specificity and approximate binding affinity. The sequence selection stage consists of an integer linear optimization model that was solved to produce a rank-ordered list of amino acid sequences with increased stability in the bound peptide-EZH2 structure. These sequences were validated through the calculation of the fold specificity and approximate binding affinity of the designed peptides. Here we report the discovery of novel EZH2 inhibitory peptides using the de novo peptide design method. The computationally discovered peptides were experimentally validated in vitro using dose titrations and mechanism of action enzymatic assays. The peptide with the highest in vitro response, SQ037, was validated in nucleo using quantitative mass spectrometry-based proteomics. This peptide had an IC50 of 13.5 mM, demonstrated greater potency as an inhibitor when compared to the native and K27A mutant control peptides, and demonstrated competitive inhibition versus the peptide substrate. Additionally, this peptide demonstrated high specificity to the EZH2 target in comparison to other histone methyltransferases. The validated peptides are the first computationally designed peptides that directly inhibit EZH2. These inhibitors should prove useful for further chromatin biology investigations.

Project description:Histones are small proteins critical to the efficient packaging of DNA in the nucleus. DNA-protein complexes, known as nucleosomes, are formed when the DNA winds itself around the surface of the histones. The methylation of histone residues by enhancer of zeste homolog 2 (EZH2) maintains gene repression over successive cell generations. Overexpression of EZH2 can silence important tumor suppressor genes leading to increased invasiveness of many types of cancers. This makes the inhibition of EZH2 an important target in the development of cancer therapeutics. We employed a three-stage computational de novo peptide design method to design inhibitory peptides of EZH2. The method consists of a sequence selection stage and two validation stages for fold specificity and approximate binding affinity. The sequence selection stage consists of an integer linear optimization model that was solved to produce a rank-ordered list of amino acid sequences with increased stability in the bound peptide-EZH2 structure. These sequences were validated through the calculation of the fold specificity and approximate binding affinity of the designed peptides. Here we report the discovery of novel EZH2 inhibitory peptides using the de novo peptide design method. The computationally discovered peptides were experimentally validated in vitro using dose titrations and mechanism of action enzymatic assays. The peptide with the highest in vitro response, SQ037, was validated in nucleo using quantitative mass spectrometry-based proteomics. This peptide had an IC50 of 13.5 [Formula: see text]M, demonstrated greater potency as an inhibitor when compared to the native and K27A mutant control peptides, and demonstrated competitive inhibition versus the peptide substrate. Additionally, this peptide demonstrated high specificity to the EZH2 target in comparison to other histone methyltransferases. The validated peptides are the first computationally designed peptides that directly inhibit EZH2. These inhibitors should prove useful for further chromatin biology investigations.

Dataset Information

Design of MMP-1 inhibitors via SAR transfer and experimental validation.

Publications

Design of MMP-1 inhibitors via SAR transfer and experimental validation.

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