Evidence map›Paper›PMID 39780770›Full record

ArticleIn silico pharmacology2025

Identification of potential MMP-8 inhibitors through virtual screening of natural product databases.

Yi Wang, Xiushan Chen

Abstract read
In one paragraph

Article in In silico pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yi WangChinese Materia Medica Pharmacology, Shandong Academy of Chinese Medicine, Jinan, 250014 China.
Xiushan ChenCollege of Chemistry and Chemical Engineering, China University of Petroleum, Qingdao, 266580 China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Matrix metalloproteinase-8 (MMP-8), a type II collagenase, is a key enzyme in the degradation of collagens and is implicated in various pathological processes, making it a promising target for drug discovery. Despite advancements in the development of MMP-8 inhibitors, concerns over potential adverse effects persist. This study aims to address these concerns by focusing on the development of novel compounds with improved safety profiles while maintaining efficacy. In this study, we employed a computational approach to screen potent and safe inhibitors of MMP-8 from the Natural Product Activity and Species Source Database (NPASS). Initially, we constructed a pharmacophore model based on the crystal structure of the MMP-8-FIN complex (PDB ID: 4EY6) utilizing the Pharmit tool. This model then guided the selection of 44 promising molecules from NPASS, setting the stage for further analysis and evaluation. We comprehensively evaluated their drug-likeness and toxicity profiles. Molecules 21, 4, and 44 were identified as potentially effective MMP-8 inhibitors through a robust pipeline that included ADMET profiling, molecular docking, and molecular dynamics simulations. Notably, molecule 21 stood out for its low toxicity, high binding stability, and favorable ADMET profile, while molecule 44 demonstrated excellent affinity. These compounds offer structural novelty compared to known MMP-8 inhibitors. These computational results can be combined with in vitro experiments in the future to validate their activity and safety. These findings provide an important reference for drug design of MMP-8 inhibitors.

Indexed as

ADMETComputer-aided drug designMMP-8Molecular dockingMolecular dynamics simulationsPharmacophore-based virtual screening

Identifiers

PMID39780770
PMCPMC11704116

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.