Evaluating AI and machine learning models in cheminformatics: benchmarking techniques and case studies

Edited by:

Gonzalo Colmenarejo, PhD, Cheminformatics & AI group, IMDEA Food Institute, Spain
Sebastian Lobentanzer, PhD, Helmholtz Centre Munich, Germany
Oscar M茅ndez-Lucio, PhD, Recursion, Spain

Submission Status: Open | Submission Deadline: 16 January 2026

is calling for submissions to our Collection on Evaluating AI and machine learning models in cheminformatics: benchmarking techniques and case studies. This collection aims to advance the field by presenting benchmarking methodologies and case studies that highlight the use of AI and machine learning models in cheminformatics. We seek contributions that provide detailed evaluations of computational tools, innovative benchmarking frameworks, and comprehensive case studies demonstrating the effectiveness of these models in predicting chemical properties.

Image credit: 漏 Yuichiro Chino/Moment/Gettyimages

About the Collection

is calling for submissions to our Collection on Evaluating AI and machine learning models in cheminformatics: benchmarking techniques and case studies. This collection aims to advance the field by presenting benchmarking methodologies and case studies that highlight the use of AI and machine learning models in cheminformatics. We seek contributions that provide detailed evaluations of computational tools, innovative benchmarking frameworks, and comprehensive case studies demonstrating the effectiveness of these models in predicting chemical properties. Possible topics can include:

鈥�   Novel methodologies for benchmarking AI and machine learning models
鈥�   Evaluation of generative models for de novo drug and material design
鈥�   Comparative analysis of molecular fingerprints and descriptors in virtual screening
鈥�   Performance metrics for assessing model robustness and reliability
鈥�   Use of curated validation datasets to test external predictivity
鈥�   Case studies showcasing successful applications of benchmarking techniques in cheminformatics
鈥�   Challenges and future directions in the benchmarking of cheminformatics models

We seek original research articles, reviews, and case studies that provide insights into this topic.

There are currently no articles in this collection.

Submission Guidelines

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This Collection welcomes submission of original research articles, reviews, and case studies. Should you wish to submit a different article type, please read our to confirm that type is accepted by the journal.

Articles for this Collection should be submitted via our submission system, . Please, select the appropriate Collection title 鈥淓valuating AI and machine learning models in cheminformatics: benchmarking techniques and case studies鈥� under the 鈥淒etails鈥� tab during the submission stage.

Articles will undergo the journal鈥檚 and are subject to all the journal鈥檚 standard policies. Articles will be added to the Collection as they are published.

The Editors have no competing interests with the submissions which they handle through the peer-review process. The peer-review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.

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