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Techniques and Strategies in Drug Design and Discovery, 3rd Edition

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: 20 April 2026 | Viewed by 841

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Guest Editor
Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Carol Davila University of Medicine and Pharmacy, Traian Vuia 6, 020956 Bucharest, Romania
Interests: drug design; QSAR; molecular docking; anti-infective; MDR-bacteria
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Special Issue Information

Dear Colleagues,

Drug discovery is a very complex and difficult process that involves finding and developing novel therapeutic entities. In recent years, the methodology behind drug discovery has rapidly evolved to comprise a plethora of paradigms and techniques, but there remains no perfect algorithm for guaranteed success. Despite considerable research, fortunate discoveries and the incredible intuition, inspiration, and creativity of researchers still play a vital role in the field of drug discovery, which remains popular among many scientists. Novel approaches and innovations are needed to address the dominant challenge of cost efficiency. To address this pressing topic, we are pleased to announce the continuation of our previous Special Issue, which is dedicated to serving as a comprehensive platform for researchers working in this field. This Special Issue provides an inclusive space to present recent efforts aimed at enhancing current methodologies and discovering new molecular entities. We welcome innovative research contributions, as well as insightful reviews of existing practices, in all facets of drug discovery and drug development.

In the first edition and the second edition, more than 18 papers were published; we sincerely welcome you to read these papers and contribute to this third edition. We believe that through collaborative efforts and the exchange of knowledge in this Special Issue, we can drive significant advancements in drug discovery and ultimately improve global healthcare outcomes.

Prof. Dr. George Mihai Nitulescu
Guest Editor

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Keywords

  • drug discovery
  • drug development
  • target identification
  • computational drug design
  • structure-based drug design
  • ligand-based drug design

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Published Papers (2 papers)

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Research

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37 pages, 20768 KiB  
Article
Design, Synthesis, and Testing of 1,2,3-Triazolo-Quinobenzothiazine Hybrids for Cytotoxic and Immunomodulatory Activity
by Klaudia Giercuszkiewicz-Haśnik, Magdalena Skonieczna, Beata Morak-Młodawska and Małgorzata Jeleń
Int. J. Mol. Sci. 2025, 26(14), 6920; https://doi.org/10.3390/ijms26146920 - 18 Jul 2025
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Abstract
Phenothiazines, mainly known for their antipsychotic activity, have recently attracted attention as potential compounds with anticancer and immunomodulatory activity In this study, 20 new quinobenzothiazines (MJ1MJ20) were synthesized and their effects on normal cell lines (BEAS-2B, NHDF) and cancer [...] Read more.
Phenothiazines, mainly known for their antipsychotic activity, have recently attracted attention as potential compounds with anticancer and immunomodulatory activity In this study, 20 new quinobenzothiazines (MJ1MJ20) were synthesized and their effects on normal cell lines (BEAS-2B, NHDF) and cancer cell lines (HCT116, MCF7, A549, SH-SY5Y, U2OS) were investigated. The studies included cytotoxicity assessment, analysis of the expression of genes (BCL2, AIFM2, MDM2) and pro-inflammatory cytokines (IL6, IL8) using the RT-qPCR method, and prediction of biological activity using the PASS platform. The results indicate that the compounds MJ19 and MJ20 have the greatest effect on the induction of pro-inflammatory (IL6, IL8) and antiapoptotic (BCL2, MDM2) genes, suggesting their potential use in therapies for inflammatory and autoimmune diseases. Gene expression analysis showed that compound MJ2 in BEAS-2B cells significantly induced the expression of AIFM2, a protein responsible for protecting against ferroptosis, while moderately increasing the expression of BCL2 and MDM2, suggesting a potential role for MJ2 in the modulation of protective mechanisms of healthy cells, e.g., avoiding apoptosis death. These results emphasize the potential of quinobenzothiazines as multifunctional bioactive compounds, which require further studies to determine their mechanisms of action and specificity. Full article
(This article belongs to the Special Issue Techniques and Strategies in Drug Design and Discovery, 3rd Edition)
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Review

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20 pages, 1292 KiB  
Review
AI-Driven Polypharmacology in Small-Molecule Drug Discovery
by Mena Abdelsayed
Int. J. Mol. Sci. 2025, 26(14), 6996; https://doi.org/10.3390/ijms26146996 - 21 Jul 2025
Viewed by 234
Abstract
Polypharmacology, the rational design of small molecules that act on multiple therapeutic targets, offers a transformative approach to overcome biological redundancy, network compensation, and drug resistance. This review outlines the scientific rationale for polypharmacology, highlighting its success across oncology, neurodegeneration, metabolic disorders, and [...] Read more.
Polypharmacology, the rational design of small molecules that act on multiple therapeutic targets, offers a transformative approach to overcome biological redundancy, network compensation, and drug resistance. This review outlines the scientific rationale for polypharmacology, highlighting its success across oncology, neurodegeneration, metabolic disorders, and infectious diseases. Emphasis is placed on how polypharmacological agents can synergize therapeutic effects, reduce adverse events, and improve patient compliance compared to combination therapies. We also explore how computational methods—spanning ligand-based modeling, structure-based docking, network pharmacology, and systems biology—enable target selection and multi-target ligand prediction. Recent advances in artificial intelligence (AI), particularly deep learning, reinforcement learning, and generative models, have further accelerated the discovery and optimization of multi-target agents. These AI-driven platforms are capable of de novo design of dual and multi-target compounds, some of which have demonstrated biological efficacy in vitro. Finally, we discuss the integration of omics data, CRISPR functional screens, and pathway simulations in guiding multi-target design, as well as the challenges and limitations of current AI approaches. Looking ahead, AI-enabled polypharmacology is poised to become a cornerstone of next-generation drug discovery, with potential to deliver more effective therapies tailored to the complexity of human disease. Full article
(This article belongs to the Special Issue Techniques and Strategies in Drug Design and Discovery, 3rd Edition)
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