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From Drug Design to Mechanistic Understanding and Resistance
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From Drug Design to Mechanistic Understanding and Resistance

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 June 2026 | Viewed by 2233

Special Issue Editors

Dr. Yuan Ma

E-Mail Website
Guest Editor
School of Chinese Medicine, The Chinese University of Hong Kong, Hong Kong 999077, China
Interests: aptamer; target protein degradation; drug resistance
Dr. Yan-Fang Xian

E-Mail Website
Guest Editor
School of Chinese Medicine, The Chinese University of Hong Kong, Hong Kong, China
Interests: Chinese medicine; pancreatic cancer; prostate cancer; herb-drug interaction; resistance
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to establish an interdisciplinary forum dedicated to addressing contemporary challenges in drug discovery and development, with a focus on rational design, mechanistic investigation, and drug resistance. A precise understanding of a drug's mechanism of action is essential for its optimization, and the emergence of resistance serves as a critical test of that mechanistic knowledge. Consequently, insights derived from resistance mechanisms directly inform the subsequent development of therapeutic agents.

The principal objective is to advance this integrative perspective by featuring pioneering research that connects design, mechanism, and resistance into a coherent cycle. We invite submissions that extend beyond the introduction of novel chemical or biological entities to include rigorous elucidation of their target interactions and the processes by which these interactions are compromised under selective pressure. The ultimate goal is to assemble contributions that offer strategic progress against drug resistance, thereby promoting the development of more durable and sustainable treatment solutions.

This journal encompasses a broad range of disciplines, from computational chemistry and structural biology to cell biology, microbiology, oncology, pharmacology, and clinical medicine. Relevant therapeutic areas include anti-infective agents (targeting bacterial, fungal, viral, and parasitic pathogens), anticancer drugs, and therapeutics for chronic diseases where resistance is a principal concern, such as kinase inhibitor resistance in oncology and tolerance to neuropsychiatric drugs.

Emphasis is placed on the integration of fundamental science with translational relevance. Submissions may address early discovery, preclinical development, or translational research that clarifies resistance mechanisms or informs clinical strategy. Studies employing innovative methodologies to bridge these domains are particularly encouraged.

Topics of interest include, but are not limited to, the following themes. Integrative studies connecting multiple themes are strongly encouraged.

1. Innovative Drug Design and Discovery Methods

(1) Computationally Guided Design: AI/ML-enabled virtual screening, de novo design, and ADMET prediction; structure-based optimization targeting mutant or resistance-associated proteins.
(2) Targeted Protein Degradation: Design and application of novel PROTACs, molecular glues, and related technologies, emphasizing their potential to overcome resistance to conventional inhibitors.
(3) Emerging Therapeutic Modalities: Development and optimization of Antibody-Drug Conjugates (ADCs), peptide therapeutics, and nucleic acid-based drugs for intractable targets or resistant disease states.

2. Mechanistic Investigation

(1) Structural Biology: Application of cryo-electron microscopy, X-ray crystallography, and NMR to determine high-resolution structures of drug-target complexes, elucidating binding modes, allosteric regulation, and conformational dynamics.
(2) Chemical Biology Tools: Development and application of functional probes to study target engagement, pathway modulation, and off-target effects within complex biological systems at high resolution.
(3) Systems Pharmacology and Multi-Omics Integration: Synthesis of genomic, transcriptomic, proteomic, and metabolomic data to map systemic drug effects, identify novel biomarkers, and anticipate adverse outcomes.

Suitable submissions include original research articles, high-quality reviews (systematic or perspective), short communications, and perspective articles. Review articles should provide critical synthesis and novel conceptual insights into a defined field, rather than solely summarizing the published literature.

Dr. Yuan Ma
Dr. Yan-Fang Xian
Guest Editor

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

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. 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

  • drug resistance
  • drug discovery
  • targeted protein degradation
  • systems pharmacology
  • structural biology

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Published Papers (3 papers)

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Research

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24 pages, 1236 KB  
Article
Statistical Inference of Phenotype-Specific Molecular Mechanisms from Cell Line-Specific Gene Regulatory Networks with Application to Quizartinib Sensitivity
by Jooee Oh and Heewon Park
Int. J. Mol. Sci. 2026, 27(9), 3885; https://doi.org/10.3390/ijms27093885 - 27 Apr 2026
Viewed by 226
Abstract
Gene regulatory networks differ substantially across individual cell lines, and population-level network inferences often fail to capture the underlying biological heterogeneity. To better capture this heterogeneity, cell line-specific gene network analysis is required. However, interpreting such high-dimensional cell line-specific networks remains a major [...] Read more.
Gene regulatory networks differ substantially across individual cell lines, and population-level network inferences often fail to capture the underlying biological heterogeneity. To better capture this heterogeneity, cell line-specific gene network analysis is required. However, interpreting such high-dimensional cell line-specific networks remains a major challenge in the field of network biology. One interpretative approach is to identify differentially regulated gene networks (DGNs) between phenotypes because these networks can highlight phenotype-specific regulatory mechanisms. Although several methods have been proposed for DGN analysis, they are not suitable for cell line-specific gene network analysis, which is characterized by pronounced heterogeneity across individual networks. To address this problem, we proposed a novel statistical method for identifying DGNs in a cell line-specific scenario. The proposed framework integrates cell line-specific network estimation, a Kullback–Leibler divergence-based comparison of multivariate distributions, and a DKL-ratio statistic to quantify between-phenotype heterogeneity relative to within-phenotype homogeneity. Our method evaluates both between-phenotype heterogeneity and within-phenotype homogeneity, ensuring the robust detection of phenotype-specific network structures. Through Monte Carlo simulation studies, we systematically evaluated the performance of the proposed method and demonstrated that our strategy consistently outperformed existing methods in terms of accuracy, precision, true positive rate (TPR), true negative rate (TNR), and F-measure across diverse network structures and mean shift scenarios. Statistical significance was assessed using a permutation-based framework, confirming that the identified networks are unlikely to arise from random variation. We further applied our strategy to Quizartinib sensitivity-specific gene network analysis and identified immune-related subnetworks enriched in antigen processing and presentation pathways. These subnetworks included hub genes such as IFIT1, PSMB9, and HLA-B, which are known to be associated with immune evasion and drug resistance in acute myeloid leukemia. Our findings demonstrate that the proposed method enables statistically reliable and biologically interpretable identification of phenotype-specific gene regulatory mechanisms, providing insights into potential therapeutic targets. Full article
(This article belongs to the Special Issue From Drug Design to Mechanistic Understanding and Resistance)
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34 pages, 3999 KB  
Article
Structure-Based Design of New Series of Sulfonates with Potent and Specific BChE Inhibition and Anti-Inflammatory Effects
by Siva Hariprasad Kurma, Camila Adarvez-Feresin, Oscar Parravicini, Adriana Garro, Sarka Stepankova, Jan Hosek, Karel Pauk, Jovana Lisicic, Josef Jampilek, Ricardo Daniel Enriz and Ales Imramovsky
Int. J. Mol. Sci. 2026, 27(7), 3109; https://doi.org/10.3390/ijms27073109 - 29 Mar 2026
Viewed by 500
Abstract
In the present work, a novel series of eleven sulfonate derivatives with potent inhibitory activity against butyrylcholinesterase (BChE) is reported. Of these, compounds 2-[(E)-(2-Benzoylhydrazinylidene)methyl]phenyl 5-(dimethylamino)naphthalene-1-sulfonate (5c, IC50 = 1.11 µM) and tert-butyl (2E)-2-[(2-{[5-(dimethylamino)naphthalene-1-sulfonyl]oxy}phenyl)methylidene]hydrazine-1-carboxylate (5b [...] Read more.
In the present work, a novel series of eleven sulfonate derivatives with potent inhibitory activity against butyrylcholinesterase (BChE) is reported. Of these, compounds 2-[(E)-(2-Benzoylhydrazinylidene)methyl]phenyl 5-(dimethylamino)naphthalene-1-sulfonate (5c, IC50 = 1.11 µM) and tert-butyl (2E)-2-[(2-{[5-(dimethylamino)naphthalene-1-sulfonyl]oxy}phenyl)methylidene]hydrazine-1-carboxylate (5b, IC50 = 11.51 µM) exhibit stronger inhibitory activity than rivastigmine, the reference compound, and exhibit high selectivity for BChE over AChE (e.g., selectivity index 57 for 5c). Interestingly, compound 5c also exhibited anti-inflammatory effects, which is important for potential therapeutic applications, especially in Alzheimer’s disease. These new compounds were designed through a structure-based approach using molecular modeling techniques (docking, molecular dynamic (MD) simulations, and QTAIM (quantum theory of atoms in molecules) calculations). The most promising compounds show no detectable toxic effects and satisfy Lipinski’s rule of five, indicating that they represent attractive starting structures for the design of new derivatives acting as specific BChE inhibitors. In addition, our results indicate that relatively simple computational techniques such as docking calculations and toxicity prediction programs can be valuable when properly used in the search of new candidates for this particular target. Docking calculations show that the more active compounds of this series reach the bottom region of the gorge interacting with residues within the active site of BChE. However, our data further suggest that the use of more precise techniques, such as MD simulations and QTAIM analysis, is necessary to obtain detailed insight into ligand–enzyme interactions. Regarding QTAIM calculations, they demonstrate that such computations are very useful to evaluate the molecular interactions of the different molecular complexes. In summary, we report a new series of sulfonate derivatives as promising starting structures for the development of new selective BChE inhibitors. Full article
(This article belongs to the Special Issue From Drug Design to Mechanistic Understanding and Resistance)
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Review

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34 pages, 2040 KB  
Review
Myostatin Research: From Molecular Understanding to Clinical Translation for Musculoskeletal and Metabolic Disorders
by Chongguang Lei, Hewen Jiang, Xin Yang, Shijian Ding, Yuanyuan Yu, Zongkang Zhang, Luyao Wang, Chong Gao, Aiping Lyu, Ling Qin, Ge Zhang and Bao-Ting Zhang
Int. J. Mol. Sci. 2026, 27(9), 3836; https://doi.org/10.3390/ijms27093836 - 25 Apr 2026
Viewed by 1008
Abstract
Myostatin (Mstn), a well-characterized member of the transforming growth factor-β (TGF-β) superfamily, serves as a key negative regulator of skeletal muscle mass. Its overactivation is closely associated with the pathogenesis of various musculoskeletal and metabolic disorders. Over the past decades, inhibiting Mstn has [...] Read more.
Myostatin (Mstn), a well-characterized member of the transforming growth factor-β (TGF-β) superfamily, serves as a key negative regulator of skeletal muscle mass. Its overactivation is closely associated with the pathogenesis of various musculoskeletal and metabolic disorders. Over the past decades, inhibiting Mstn has emerged as a promising therapeutic strategy to promote muscle growth. A range of Mstn-targeted inhibitors has been developed, yielding encouraging preclinical and clinical outcomes. These include small molecules, monoclonal antibodies, peptibodies, and gene therapy-based approaches. This review summarizes the biological structure and function of Mstn, provides a comprehensive overview of recent advances in Mstn-targeted therapeutics, and offers critical insights into future directions for drug development and clinical translation. Full article
(This article belongs to the Special Issue From Drug Design to Mechanistic Understanding and Resistance)
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