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Computational and Synthetic Approaches in Drug Design: Novel Methodologies and Applications

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Pharmacology".

Deadline for manuscript submissions: 30 July 2026 | Viewed by 2978

Special Issue Editor


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Department of Pharmaceutical Sciences, Università degli Studi di Milano, Via Mangiagalli 25, 20133 Milano, Italy
Interests: medicinal chemistry; drug discovery; enzyme inhibitors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The process of drug discovery has undergone a profound transformation over the past decades, driven by advances in computational science, synthetic chemistry, and molecular biology. The integration of in silico methodologies with synthetic approaches has significantly accelerated the identification, optimization, and validation of bioactive compounds, offering new opportunities to address complex biological targets and unmet medical needs. In this context, computational and synthetic strategies have emerged as complementary and indispensable pillars of modern drug design.

Advanced computational approaches enable the efficient and rational exploration of chemical space by predicting molecular properties, target interactions, and pharmacokinetic behavior, significantly accelerating drug discovery. Recent progress in artificial intelligence and data-driven methods has further expanded these capabilities, allowing the analysis of large datasets and the design of novel molecular scaffolds. Complementing these advances, modern synthetic methodologies translate computational insights into experimentally accessible compounds, with increasing attention to sustainability and synthetic accessibility.

The close interplay between computational design and synthetic feasibility is therefore essential for the rapid optimization of drug candidates with enhanced potency, selectivity, and drug-like properties. On this ground, this Special Issue aims to present cutting-edge research that leverages computational and/or synthetic approaches for the discovery and optimization of novel bioactive compounds, offering an overview of the current state of the art in this rapidly evolving field. Topics include the development of new in silico methodologies for drug discovery, as well as the application of established techniques, such as molecular docking, molecular dynamics, pharmacophore modeling, homology modeling, QSAR, and data-driven approaches, together with innovative and highly sustainable synthetic strategies. Submissions may comprise original research articles or reviews in which computational and/or synthetic methods are used to identify new drug candidates, guide compound synthesis, optimize hit-to-lead molecules, perform structure–activity relationship studies, analyze ligand-target interactions, or predict ADME/Tox profiles and key molecular properties of drug-like compounds.

Dr. Francesca Mancuso (francesca.mancuso@unime.it), is from Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina, Viale F. Stagno d’Alcontres 31, 98166, Messina, Italy. Dr. Mancuso serves as the Guest Editor Assistant, supporting Dr. Serena Vittorio in managing this special issue.

Dr. Serena Vittorio
Guest Editor

Manuscript Submission Information

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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. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

  • drug discovery
  • medicinal chemistry
  • computer-aided drug design
  • molecular modelling and simulation
  • synthetic methodologies
  • sustainable chemistry
  • artificial intelligence
  • ADME/Tox profiling
  • hit-to-lead optimization
  • structure–activity relationship

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Published Papers (1 paper)

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Review

41 pages, 3961 KB  
Review
Open-Source Molecular Docking and AI-Augmented Structure-Based Drug Design: Current Workflows, Challenges, and Opportunities
by Faizul Azam and Suliman A. Almahmoud
Int. J. Mol. Sci. 2026, 27(7), 3302; https://doi.org/10.3390/ijms27073302 - 5 Apr 2026
Viewed by 2672
Abstract
Molecular docking is a foundational technique in computational drug discovery, widely used to generate binding hypotheses, prioritize compounds, and support target-selectivity studies. The continued growth of open-source docking resources, together with improvements in scoring functions, sampling strategies, and hardware acceleration, has substantially lowered [...] Read more.
Molecular docking is a foundational technique in computational drug discovery, widely used to generate binding hypotheses, prioritize compounds, and support target-selectivity studies. The continued growth of open-source docking resources, together with improvements in scoring functions, sampling strategies, and hardware acceleration, has substantially lowered barriers to teaching, early-stage hit identification, and reproducible research. Beyond standalone docking engines, the open-source ecosystem now encompasses browser-accessible tools, preparation and analysis utilities, integrative modeling platforms, and AI-augmented methods for pose prediction, rescoring, and virtual screening. These developments have made docking workflows more accessible, customizable, and transparent across diverse research settings. This review examines open-source docking from a workflow-centered perspective, spanning study design, structural-data acquisition, binding-site definition, receptor and ligand preparation, docking execution, and post-docking validation. It further evaluates how open AI methods are being incorporated into these stages to expand structural coverage, improve screening efficiency, and support contemporary structure-based drug design. Collectively, this review outlines a practical and evidence-based framework for the effective use of open-source docking and virtual-screening pipelines in modern drug discovery. Full article
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