Evidence map›Paper›PMID 31216704›Full record

ReviewMolecules (Basel, Switzerland)2019

Inhibitory Antibodies Designed for Matrix Metalloproteinase Modulation.

Thomas Fischer, Rainer Riedl

Open access · goldAbstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
2.2field-weighted citation impact, top 12% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 50 citations in OpenAlex.

  1. Review
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  4. A tailored 4GRSC advances · 2025
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4 · The record

Corrections and comments

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 at 1 institution in 1 country.

Thomas FischerInstitute of Chemistry and Biotechnology, Center of Organic and Medicinal Chemistry, Zurich University of Applied Sciences, Einsiedlerstrasse 31, 8820 Wädenswil, Switzerland. thomas.fischer@zhaw.ch.
Rainer RiedlInstitute of Chemistry and Biotechnology, Center of Organic and Medicinal Chemistry, Zurich University of Applied Sciences, Einsiedlerstrasse 31, 8820 Wädenswil, Switzerland. rainer.riedl@zhaw.ch.ORCID 0000-0003-2534-1963
ZHAW Zurich University of Applied Sciences · CH

Funding

ZHAW 9710.3.18.5.0179
6 · The paper itself

Abstract

The family of matrix metalloproteinases (MMPs) consists of a set of biological targets that are involved in a multitude of severe pathogenic events such as different forms of cancers or arthritis. Modulation of the target class with small molecule drugs has not led to the anticipated success until present, as all clinical trials failed due to unacceptable side effects or a lack of therapeutic outcome. Monoclonal antibodies offer a tremendous therapeutic potential given their high target selectivity and good pharmacokinetic profiles. For the treatment of a variety of diseases there are already antibody therapies available and the number is increasing. Recently, several antibodies were developed for the selective inhibition of single MMPs that showed high potency and were therefore investigated in in vivo studies with promising results. In this review, we highlight the progress that has been achieved toward the design of inhibitory antibodies that successfully modulate MMP-9 and MMP-14.

Indexed as

Drug DesignAmino Acid SequenceAnimalsAntibodies, MonoclonalBinding SitesHumansMatrix Metalloproteinase InhibitorsMatrix MetalloproteinasesMolecular ConformationMolecular Docking SimulationMolecular Dynamics SimulationProtein BindingStructure-Activity RelationshipAntibodies, MonoclonalMatrix Metalloproteinase InhibitorsMatrix Metalloproteinasesdrug designinhibitory antibodymatrix metalloproteinaseselectivitytissue inhibitors of metalloproteinases

Identifiers

PMID31216704
PMCPMC6631688
OpenAlexW2949826890

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.