ArticleInternational journal of biological sciences2018
Identification of Inhibitors of MMPS Enzymes via a Novel Computational Approach.
Article in International journal of biological sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 20 citations in OpenAlex.
- Photodynamic Therapy Targeting Matrix Metalloproteases in Cancer: Standpoint for an Innovative Anticancer Strategy.Current issues in molecular biology · 2026Review
- Cardiac Fibroblasts Enhance MMP2 Activity to Suppress Gap Junction Function in Cardiomyocytes.Applied biochemistry and biotechnology · 2024Article
- Non-Canonical Amino Acids in Analyses of Protease Structure and Function.International journal of molecular sciences · 2023Review
- Myeloperoxidase: a new target for the treatment of stroke?Neural regeneration research · 2022Review
- Machine Learning Approaches for Metalloproteins.Molecules (Basel, Switzerland) · 2022Review
- Predicting MHC class I binder: existing approaches and a novel recurrent neural network solution.Briefings in bioinformatics · 2021Article
- Impact of non-proteinogenic amino acids in the discovery and development of peptide therapeutics.Amino acids · 2020Review
- Advances in Therapeutic Targeting of Cancer Stem Cells within the Tumor Microenvironment: An Updated Review.Cells · 2020Review
- Discovering Cancer Subtypes via an Accurate Fusion Strategy on Multiple Profile Data.Frontiers in genetics · 2019Article
- Special issue on Computational Resources and Methods in Biological Sciences.International journal of biological sciences · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Matrix metalloproteases (MMPs) are a family of zinc-dependent proteinases that play complex and diverse roles in metabolism, which are vital for physiological development. In this paper, we present a novel method to identify peptide binding to seven matrix metalloproteases. First, we propose a novel sampling criteria for constructing a training set for each new peptide motif. Then, we select nine physicochemical properties of amino acids and compute their auto-cross covariance to effectively extract features for both natural and non-natural amino acids. Finally, we adopt random forest to predict binding values of each peptide motif respectively with seven MMPs. Our method verifies on 1300 known peptide motifs binding to seven MMPs and achieved preeminent Pearson-product-moment correlation coefficient (PCC) and root mean squared error (RMSE) on all seven MMPs, especially of 0.9181 and 9.3827 on MMP-7. We predict binding values of 4000 peptide motifs and identify peptides preferentially bind to MMP-2 and MMP-7. We herein report 4 novel inhibitor candidates of Asp-Ile-Phe, Asp-Ile-Tyr, Asp-Ile-Lys and Hser-Gly-Phe with high potency and selectivity binding to MMP-2, as well as 6 novel inhibitor candidates of Chg-Ile-Ile, Chg-Ile-Leu, Chg-Ile-Glu, Chg-Ile-Met, Chg-Val-Ile and Chg-Val-Leu selectively binding to MMP-7. Our findings facilitate the identification of inhibitors with good potency as well as desirable selectivity, providing significant insights of candidate inhibitor drugs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.