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The emerging discipline of mathematical pharmacology occupies the space between advanced pharmacometrics and systems biology. A characteristic feature of the approach is application of advance mathematical methods to study the behavior of biological systems as described by mathematical (most often differential) equations. One of the early application of mathematical pharmacology (that was not called this name at the time) was formulation and investigation of the target-mediated drug disposition (TMDD) model and its approximations. The model was shown to be remarkably successful, not only in describing the observed data for drug-target interactions, but also in advancing the qualitative and quantitative understanding of those interactions and their role in pharmacokinetic and pharmacodynamic properties of biologics. The TMDD model in its original formulation describes the interaction of the drug that has one binding site with the target that also has only one binding site. Following the framework developed earlier for drugs with one-to-one binding, this work aims to describe a rigorous approach for working with similar systems and to apply it to drugs that bind to targets with two binding sites. The quasi-steady-state, quasi-equilibrium, irreversible binding, and Michaelis-Menten approximations of the model are also derived. These equations can be used, in particular, to predict concentrations of the partially bound target (RC). This could be clinically important if RC remains active and has slow internalization rate. In this case, introduction of the drug aimed to suppress target activity may lead to the opposite effect due to RC accumulation.
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http://dx.doi.org/10.1007/s10928-017-9546-9 | DOI Listing |
PLoS One
September 2025
School of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao, Shandong, China.
Drug-target interaction (DTI) prediction is essential for the development of novel drugs and the repurposing of existing ones. However, when the features of drug and target are applied to biological networks, there is a lack of capturing the relational features of drug-target interactions. And the corresponding multimodal models mainly depend on shallow fusion strategies, which results in suboptimal performance when trying to capture complex interaction relationships.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
Objective: This study employs integrated network toxicology and molecular docking to investigate the molecular basis underlying 4-nonylphenol (4-NP)-mediated enhancement of breast cancer susceptibility.
Methods: We integrated data from multiple databases, including ChEMBL, STITCH, Swiss Target Prediction, GeneCards, OMIM and TTD. Core compound-disease-associated target genes were identified through Protein-Protein Interaction (PPI) network analysis.
ACS Appl Mater Interfaces
September 2025
Faculty of Chemistry, Jagiellonian University, Gronostajowa 2, Kraków 30-387, Poland.
The multifunctional systems presented here introduce an innovative and deeply thought-out approach to the more effective and safer use of temozolomide (TMZ) in treating glioma. The developed hydrogel-based flakes were designed to address the issues of local GBL therapy, bacterial neuroinfections, and the bleeding control needed during tumor resection. The materials obtained comprise TMZ and vancomycin (VANC) loaded into cyclodextrin/polymeric capsules and embedded into gelatin/hyaluronic acid/chitosan-based hydrogel films cross-linked with genipin.
View Article and Find Full Text PDFChemMedChem
September 2025
Laboratorio de Síntesis Orgánica, Facultad de Farmacia, Universidad Central de Venezuela, Apartado 47206, Los Chaguaramos, Caracas, 1041-A, Venezuela.
Due to the advantages of drug repurposing, the discovery of new chemotherapeutic agents for the treatment of Chagas disease based on approved drugs has become a strategy for identifying new candidates. In this work, the antidepressant drug sertraline is reported, with an IC of 7.8 ± 1.
View Article and Find Full Text PDFMol Biol Rep
September 2025
Department of Biochemistry, Pasteur Institute of Iran, Tehran, Iran.
Background: Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. The tumor microenvironment (TME), particularly the interactions between endothelial cells and cancer-associated fibroblasts (CAFs), plays a pivotal role in promoting tumor growth, angiogenesis, oxidative stress, and therapy resistance. The HUVEC-fibroblast co-culture model closely mimics stromal-endothelial interactions observed in CRC, enabling mechanistic insights not achievable in monocultures.
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