Computational Approaches in Discovery and Design of Antimicrobial Peptides—3rd Edition
A special issue of Antibiotics (ISSN 2079-6382). This special issue belongs to the section "Antimicrobial Peptides".
Deadline for manuscript submissions: 30 November 2026 | Viewed by 262
Editors
Interests: drug discovery and molecular modeling; chemo-informatics; molecular descriptors definition for nucleic acids and proteins; molecular similarity and complex networks applied to analyze peptide databases; alignment-free models for protein classification problems
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2. Department of Biology, Faculty of Sciences, University of Porto, Rua do Campo Alegre 1021, 4169-007 Porto, Portugal
Interests: computational biology; biodiscovery; chemo- and bioinformatics; bioactive peptides; antimicrobial peptides (AMPs); biotechnology
Special Issues, Collections and Topics in MDPI journals
2. Department of Biology, Faculty of Sciences, University of Porto, Rua do Campo Alegre, 4169-007 Porto, Portugal
Interests: genomics (from animals to microorganisms); evolution, molecular ecology; conservation; biotechnology; bioinformatics; antimicrobial peptides
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The first two editions of the Special Issue “Computational Approaches in Discovery and Design of Antimicrobial Peptides” successfully brought together high-quality contributions from the scientific community, resulting in the publication of 10 and 8 articles receiving more than 72,200 and 30,500 views, respectively. The positive reception and growing interest in this topic have encouraged us to launch a third edition of this Special Issue.
Advances in modern artificial intelligence (AI) algorithms as well as computational biology, machine learning, and bioinformatics are rapidly transforming the discovery and design of antimicrobial peptides (AMPs), enabling more efficient identification, optimisation, and functional characterisation of novel peptide-based therapeutics.
This Special Issue welcomes original research articles that employ computational or in silico methodologies for the discovery, prediction, optimisation, or design of AMPs. Review articles addressing recent advances, methodological developments, and emerging computational strategies in AMP research are also encouraged.
We look forward to receiving your contributions and to further advancing the computational exploration of antimicrobial peptides.
Prof. Dr. Yovani Marrero-Ponce
Dr. Guillermin Agüero-Chapin
Prof. Dr. Agostinho Antunes
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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Antibiotics 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 2900 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
- search/design of AMPs
- bioinformatics
- machine-learning
- artificial intelligence
- biodiscovery
- computational analyses/tools
- omics sciences
- similarity networks
- in vitro evaluations
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