Computational Approaches for Drug and Protein Design
A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Computational and Theoretical Chemistry".
Deadline for manuscript submissions: 31 October 2026 | Viewed by 18
Special Issue Editors
Interests: machine learning; data analysis; molecular dynamics simulations; computational drug design and development; molecular docking and virtual screening; protein structure; function and dynamics
Special Issues, Collections and Topics in MDPI journals
Interests: theoretical chemistry; physical chemistry; mathematical chemistry; computational chemistry; molecular modelling; simulation and design; computer-aided drug design and development; molecular graphics and representation of molecular properties
Special Issues, Collections and Topics in MDPI journals
Interests: computational chemistry/biochemistry/biophysics; molecular modeling; metals in biology and medicine
Special Issues, Collections and Topics in MDPI journals
Interests: theoretical chemistry; natural products; organic chemistry; phytochemistry; medicinal plant chemistry; food chemistry
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Computational methods have revolutionized the fields of drug discovery and protein engineering, enabling the rapid identification of promising therapeutic candidates and the optimization of biomolecular interactions. Advances in molecular modelling, artificial intelligence, and high-throughput simulations provide unprecedented insights into drug–target interactions, protein stability, and binding affinities. This Special Issue aims to highlight cutting-edge computational approaches that enhance drug design and protein engineering, including molecular docking, molecular dynamics simulations, quantum mechanics/molecular mechanics (QM/MM) approaches, artificial intelligence-driven modelling, generative AI, and structure-based drug design. We welcome original research articles and reviews that explore novel computational strategies, algorithmic innovations, and applications in drug and protein design. By gathering contributions from researchers across disciplines, this Special Issue will provide a comprehensive overview of state-of-the-art computational methodologies and their impact on accelerating drug discovery and protein engineering.
Dr. Shirin Jamshidi
Dr. Francisco Torrens
Prof. Dr. Todor Dudev
Prof. Dr. Gloria Castellano
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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly 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
- computational drug design
- molecular docking and molecular dynamics simulations
- generative-AI and machine learning in drug discovery
- protein structure prediction
- ligand-based/structure-based drug discovery
- biomolecular modelling
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