Evidence map›Paper›PMID 41331400›Full record

ArticleJournal of computer-aided molecular design2025

MetAP DB and Metal-FP: a database and fingerprint framework for advancing metal-based drug discovery.

Edgar López-López, José L Medina-Franco

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In one paragraph

Article in Journal of computer-aided molecular design, 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

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Edgar López-LópezDIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, 04510, Mexico City, Mexico. elopez.lopez@cinvestav.mx.ORCID http://orcid.org/0000-0002-7422-6059
José L Medina-FrancoDIFACQUIM Research Group, Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, 04510, Mexico City, Mexico. medinajl@unam.mx.ORCID http://orcid.org/0000-0003-4940-1107

Funding

Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica (PAPIIT) IG200124
6 · The paper itself

Abstract

Metal-based drugs have historically been used for different therapeutic and diagnostic applications. The need to advance metal-based drugs and drug candidates has contributed to the development of computational strategies to handle metal-containing chemical structures for drug discovery applications. However, most of them have limitations related to their computational cost, scalability, capacity to be used in different chemical contexts, and data accessibility. This study introduces the first open-access metal-based approved drug database (MetAP DB) with FDA-approved drugs across various therapeutic applications and clinical diagnostic outcomes. It also introduces the first versions of molecular metal-based fingerprints (Metal-FP) representations proposed as a general protocol for representing metal-based compounds. The proposed fingerprints encode chemical data related to the presence of metals, their valence and oxidation states, the presence of specific functional groups, and the atom connectivity of metal-based compounds. The fingerprints Metal-FP2 and Metal-FP3 showed highlighting the effectiveness in differentiating metal-based compounds according to distance metrics, data visualizations, random forest, and logistic regression algorithms.

Indexed as

Databases, PharmaceuticalDrug DiscoveryMetalsAlgorithmsDatabases, FactualHumansMetalsChemical spaceChemoinformaticsDatabaseMetallodrugsMolecular representationMolecular similarityVirtual screening

Identifiers

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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.