Chemoinformatics and Molecular Modeling of Pharmacologically Active Biomolecules: A Themed Issue in Honor of Prof. José L. Medina-Franco

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Bioinformatics and Systems Biology".

Deadline for manuscript submissions: 28 February 2025 | Viewed by 3159

Special Issue Editors


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Guest Editor
Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB T6E 2E1, Canada
Interests: FOXM1; transcription factors; cancer; drug design; computer simulations

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Guest Editor
Laboratory of Biosensors and Molecular Modelling, Departamento de Bioquímica, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico
Interests: molecular modeling; docking; virtual screening; molecular dynamics simulations; biosensors; fluorescence

Special Issue Information

Dear Colleagues,

In the rapidly evolving field of chemoinformatics, data-driven approaches have emerged as indispensable tools for accelerating drug design and drug discovery, materials science, clinical, and chemical research. Accordingly, this Special Issue aims to showcase the latest innovations, methodologies, and applications that harness the power of chemical data analytics and computational approaches used to generate meaningful and potentially applicable insights in medicinal chemistry.

The key topics and themes included in this Special Issue include:

  1. Machine learning and deep learning in chemoinformatics: highlighting novel algorithms, models, and approaches for predictive modeling, property prediction, and virtual screening of chemical compounds.
  2. Chemoinformatics for drug discovery: featuring case studies, tools, and strategies for optimizing drug candidate selection, drug design, and target identification through computational methods.
  3. Big data analytics in chemistry: discussing how chemoinformatics is used in large-scale chemical data including the development of databases, data integration, and data mining techniques.
  4. Chemoinformatics in materials science: exploring the role of this scientific area in designing novel materials with tailored properties for various applications.
  5. Chemoinformatics for the environment and toxicological studies: investigating the use of this approach in assessing chemical toxicity, environmental impact, and the design of safer chemicals.
  6. Chemoinformatics tools and software: presenting innovative software tools, platforms, and workflows that facilitate chemoinformatics research and their practical applications.
  7. Interdisciplinary collaborations: encouraging contributions that showcase successful or ongoing interdisciplinary collaborations between chemoinformaticians, biologists, chemists, and materials scientists.
  8. Ethical and regulatory challenges: addressing ethical issues, privacy concerns, and regulatory challenges in chemoinformatics, especially in the context of data sharing and utilization.

We are inviting researchers from academia, industry, and government agencies to contribute original research articles, reviews, and perspectives to this Special Issue, which seeks to generate a deeper understanding of the evolving landscape of chemoinformatics and its increasing role in advancing chemical and materials research. We highly encourage authors to share their work and insights, innovative methodologies, and applications, thus contributing to the ever-expanding impact of this dynamic field.

We very much look forward to receiving your contributions.

Dr. Carlos A. Velázquez-Martínez
Dr. Martín González-Andrade
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomolecules is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • drug design
  • molecular modelling
  • chemoinformatics
  • materials science
  • big data
  • machine learning
  • predictive modeling
  • toxicology

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Published Papers (1 paper)

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Research

32 pages, 14477 KiB  
Article
De Novo Design of Inhibitors of DNA Methyltransferase 1: A Critical Comparison of Ligand- and Structure-Based Approaches
by Diana L. Prado-Romero, Fernanda I. Saldívar-González, Iván López-Mata, Pedro A. Laurel-García, Adrián Durán-Vargas, Enrique García-Hernández, Norberto Sánchez-Cruz and José L. Medina-Franco
Biomolecules 2024, 14(7), 775; https://doi.org/10.3390/biom14070775 - 28 Jun 2024
Viewed by 2053
Abstract
Designing and developing inhibitors against the epigenetic target DNA methyltransferase (DNMT) is an attractive strategy in epigenetic drug discovery. DNMT1 is one of the epigenetic enzymes with significant clinical relevance. Structure-based de novo design is a drug discovery strategy that was used in [...] Read more.
Designing and developing inhibitors against the epigenetic target DNA methyltransferase (DNMT) is an attractive strategy in epigenetic drug discovery. DNMT1 is one of the epigenetic enzymes with significant clinical relevance. Structure-based de novo design is a drug discovery strategy that was used in combination with similarity searching to identify a novel DNMT inhibitor with a novel chemical scaffold and warrants further exploration. This study aimed to continue exploring the potential of de novo design to build epigenetic-focused libraries targeted toward DNMT1. Herein, we report the results of an in-depth and critical comparison of ligand- and structure-based de novo design of screening libraries focused on DNMT1. The newly designed chemical libraries focused on DNMT1 are freely available on GitHub. Full article
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