Evidence map›Paper›PMID 41667067›Full record

ArticleJournal of chemical information and modeling2026

MolVE: An Open-Source Web Platform for Visualizing and Evaluating AI-Designed Molecules to Aid in Prioritization.

Davide Rigoni, Alessandro Sperduti, Stefano Moro

Abstract read
In one paragraph

Article in Journal of chemical information and modeling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Davide RigoniDepartment of Mathematics "Tullio Levi-Civita", University of Padova, Via Trieste 63, Padova 35131, Italy.ORCID 0000-0003-2092-3577
Alessandro SperdutiDepartment of Mathematics "Tullio Levi-Civita", University of Padova, Via Trieste 63, Padova 35131, Italy.
Stefano MoroDepartment of Pharmaceutical and Pharmacological Sciences, University of Padova Via Marzolo 5, Padova 35131, Italy.ORCID 0000-0002-7514-3802

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in artificial intelligence and deep generative models have enabled the rapid generation of novel molecular structures for advanced material science and drug discovery. However, the effective evaluation of these candidates still depends, in the end, on expert judgment, which is often fragmented and difficult to scale. This work introduces MolVE, an open-source, web-based platform designed to enable asynchronous, distributed, and collaborative evaluation of molecules by experts. The platform combines secure user authentication, data set management, and interactive 2D/3D visualizations, enabling chemists and pharmacologists to curate, annotate, and evaluate molecules efficiently. Additionally, it offers APIs for seamless integration with programming languages and provides a Python service to run machine learning and deep learning models. MolVE is a comprehensive, ready-to-deploy application built with React, Node.js, Express, and PostgreSQL, and is fully containerized using Docker. This setup enables scalable deployment in both academic and industrial settings.

Indexed as

Artificial IntelligenceDrug DiscoveryInternetSoftwareGenerative Artificial Intelligence

Identifiers

PMID41667067
PMCPMC12977061

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.