Computational Approaches to the Discovery and Design of Pharmaceutical Drugs
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".
Deadline for manuscript submissions: 20 February 2026 | Viewed by 530
Special Issue Editors
Interests: quantitative structure–activity relationship; molecular topology; drug discovery
Special Issues, Collections and Topics in MDPI journals
Interests: antibacterials; antibiotics; computational chemistry; linear discriminant analysis; molecular topology; molecular connectivity; topological indices; quinolones; QSAR; drug repurposing; drug development; escherichia coli; anti-mrsa
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In molecular science, there is currently a vital and ongoing need for multidisciplinary collaboration between experimentalists and theoretical scientists from different fields. One of the more important forces driving this need is the accumulation of large amounts of data in the form of results from important advances in cheminformatics. Computational modelling is becoming increasingly important in biomedical research for understanding how biomolecules interact. In medicine, computational methods are fundamental for the discovery of drugs due to their range of uses in the collection, processing, analysis, and modelling of data. Drug design is a multi-objective process in which various characteristics, such as efficacy, pharmacokinetics, and safety, are optimized.
Since the introduction of quantitative structure–activity relationships (QSARs) in the 1960s, when the biological activities of molecules (potential drugs) were first modelled, the application of this methodology has extended to modelling a number of the physicochemical properties of molecules (QSPR). Initially, these models started as small sets of molecules that had a limited number of easily interpretable molecular descriptors. At present, QSAR/QSPR models have become a well-established field of scientific research and present the complex relationships between input descriptors and between the input descriptors and a modelled activity/property. In addition, numerous biological, physicochemical, or pharmacokinetic effects of molecules have been modelled, meaning that the QSAR/QSPR methodology is applied to detect predictive relationships between molecular structure and pharmacological activities, toxicological properties, and the adverse effects of molecules on public health.
In the proposed Special Issue, we aim to cover aspects connected to the improvement of QSAR/QSPR methodology and perform comparative studies of cheminformatic softwares or in silico modelling methods. Authors are also invited to pay attention to the applications of QSAR/QSPR methodology or different problems related to regression or classification endpoints in drug design within chemical, pharmaceutical, biotechnological or environmental sciences.
Dr. Jose Ignacio Bueso-Bordils
Dr. Pedro A. Alemán-López
Guest Editors
Manuscript Submission Information
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Keywords
- cheminformatics
- data mining
- drug discovery
- drug design
- graph theory
- molecular descriptors
- QSAR/QSPR modelling
- biological activity
- physicochemical property
- pharmacokinetic property
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