ArticleJournal of molecular biology2023
Designed Loop Extension Followed by Combinatorial Screening Confers High Specificity to a Broad Matrix MetalloproteinaseInhibitor.
Article in Journal of molecular biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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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.
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Who cites it
10 citing papers in PubMed, 16 citations in OpenAlex.
- Matrix Metalloproteinase 14 in Corneal Neovascularization.International journal of molecular sciences · 2026Review
- Allosteric and energetic remodeling of a PDZ domain by protein domain extensions.Nature communications · 2026Article
- Engineered N-TIMP2 Variant Specifically Targeting MMP-9 Exhibits Potent Anti-Glioblastoma Activity.Biomolecules · 2025Article
- Matrix metalloproteinase-driven epithelial-mesenchymal transition: implications in health and disease.Journal of translational medicine · 2025Review
- Mirror-Image Random Nonstandard Peptides Integrated Discovery (MI-RaPID) Technology Yields Highly Stable and Selective Macrocyclic Peptide Inhibitors for Matrix Metallopeptidase 7.Angewandte Chemie (International ed. in English) · 2025Article
- Engineered TIMP2 with narrow MMP-9 specificity is an effective inhibitor of invasion and proliferation of triple-negative breast cancer cells.The Journal of biological chemistry · 2024Article
- Improving Circulation Half-Life of Therapeutic Candidate N-TIMP2 by Unfolded Peptide Extension.Biomolecules · 2024Article
- Improving Circulation Half-Life of Therapeutic Candidate N-TIMP2 by Unfolded Peptide Extension.bioRxiv : the preprint server for biology · 2024Article
- Engineering metalloproteinase inhibitors: tissue inhibitors of metalloproteinases or antibodies, that is the question.Current opinion in biotechnology · 2024Review
- Structure and computation-guided yeast surface display for the evolution of TIMP-based matrix metalloproteinase inhibitors.Frontiers in molecular biosciences · 2023Review
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 3 countries.
Funding
Abstract
Matrix metalloproteinases (MMPs) are key drivers of various diseases, including cancer. Development of probes and drugs capable of selectively inhibiting the individual members of the large MMP family remains a persistent challenge. The inhibitory N-terminal domain of tissue inhibitor of metalloproteinases-2 (N-TIMP2), a natural broad MMP inhibitor, can provide a scaffold for protein engineering to create more selective MMP inhibitors. Here, we pursued a unique approach harnessing both computational design and combinatorial screening to confer high binding specificity toward a target MMP in preference to an anti-target MMP. We designed a loop extension of N-TIMP2 to allow new interactions with the non-conserved MMP surface and generated an efficient focused library for yeast surface display, which was then screened for high binding to the target MMP-14 and low binding to anti-target MMP-3. Deep sequencing analysis identified the most promising variants, which were expressed, purified, and tested for selectivity of inhibition. Our best N-TIMP2 variant exhibited 29 pM binding affinity to MMP-14 and 2.4 µM affinity to MMP-3, revealing 7500-fold greater specificity than WT N-TIMP2. High-confidence structural models were obtained by including NGS data in the AlphaFold multiple sequence alignment. The modeling together with experimental mutagenesis validated our design predictions, demonstrating that the loop extension packs tightly against non-conserved residues on MMP-14 and clashes with MMP-3. This study demonstrates how introduction of loop extensions in a manner guided by target protein conservation data and loop design can offer an attractive strategy to achieve specificity in design of protein ligands.
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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.