Turner, J. P. | Search bioRxiv

bioRxiv2025

Design and Evaluation of PLGA-Based Nanocarriers for Targeted and Sustained Drug Delivery in Vascular Disorders

Vascular diseases, including atherosclerosis and vascular inflammation, have high incidence and mortality rates worldwide. Current drug therapies are limited by short circulation time, broad non-specific distribution, insufficient efficacy, and significant side effects. This study aimed to develop and optimize a targeted nanodrug delivery system based on poly(lactic-co-glycolic acid) (PLGA) to improve drug accumulation and therapeutic outcomes at vascular lesion sites. Nanoparticles prepared by the solvent evaporation-self-assembly method had an average diameter of 145.6 {+/-} 12.3 nm, a zeta potential of -21.4 {+/-} 3.7 mV, and showed uniform spherical morphology. The encapsulation efficiency (EE%) was 82.3 {+/-} 4.5%, and the drug loading (DL%) was 9.6 {+/-} 1.1%, indicating good drug-carrying ability. For surface modification, conjugation of ligands to the ends of PEG chains balanced the conflict between "stealth" and "affinity," maintaining circulation stability while restoring effective binding to vascular endothelial cells. Drug release experiments demonstrated a biphasic release profile in PBS (pH 7.4): about 40% was released within 0-12 h, and cumulative release reached 76.5 {+/-} 3.2% at 72 h. Kinetic analysis fitted the Higuchi model (R2 = 0.983), suggesting diffusion as the main driving mechanism. This predictable and controllable release behavior can provide both rapid effect in the acute phase and sustained therapy in the chronic phase. Overall, the PLGA nanocarrier system proposed in this study showed clear advantages in physicochemical properties, surface functionalization, and drug release kinetics. It can achieve prolonged circulation, high targeting efficiency, and controlled release in the treatment of vascular diseases. This work provides experimental evidence to overcome the limitations of conventional drug therapy and lays the foundation for developing multifunctional and clinically translatable nanodrug delivery platforms for personalized treatment.

bioengineering↗

bioRxiv2017

Drug Target Ontology to Classify and Integrate Drug Discovery Data

BackgroundOne of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research and development resources. The Illuminating the Druggable Genome (IDG) project develops resources to catalyze the development of likely targetable, yet currently understudied prospective drug targets. A central component of the IDG program is a comprehensive knowledge resource of the druggable genome.\n\nResultsAs part of that effort, we have been developing a framework to integrate, navigate, and analyze drug discovery data based on formalized and standardized classifications and annotations of druggable protein targets, the Drug Target Ontology (DTO). DTO was constructed by extensive curation and consolidation of various resources. DTO classifies the four major drug target protein families, GPCRs, kinases, ion channels and nuclear receptors, based on phylogenecity, function, target development level, disease association, tissue expression, chemical ligand and substrate characteristics, and target-family specific characteristics. The formal ontology was built using a new software tool to auto-generate most axioms from a database while also supporting manual knowledge acquisition. A modular, hierarchical implementation facilitates development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships.\n\nConclusionsDTO was built based on the need for a formal semantic model for druggable targets including various related information such as protein, gene, protein domain, protein structure, binding site, small molecule drug, mechanism of action, protein tissue localization, disease association, and many other types of information. DTO will further facilitate the otherwise challenging integration and formal linking to biological assays, phenotypes, disease models, drug poly-pharmacology, binding kinetics and many other processes, functions and qualities that are at the core of drug discovery. The first version of DTO is publically available via the website http://drugtargetontology.org/, Github (https://github.com/DrugTargetOntology/DTO), and the NCBO Bioportal (https://bioportal.bioontology.org/ontologies/DTO). The long-term goal of DTO is to provide such an integrative framework and to populate the ontology with this information as a community resource.

bioinformatics↗