In Silico Drug Repurposing Framework Predicts Repaglinide, Agomelatine and Protokylol as TRPV1 Modulators with Analgesic Activity

Current Status and Future Prospects of Lyotropic Liquid Crystals as a Nanocarrier Delivery System for the Treatment of Cancer

Multidrug resistance (MDR) poses a significant challenge in cancer treatment by reducing the efficacy of therapies. This review highlights the potential of lyotropic liquid crystals (LLCs) as innovative nanocarrier systems to overcome MDR. LLCs are characterized by their highly ordered internal structures, which can self-assemble into various phases, including lamellar, hexagonal, and cubic geometries. These structures allow LLCs to encapsulate and release cargo with diverse sizes and polarities, making them promising candidates for drug delivery applications. The phase of LLCs-whether cubic, hexagonal, or lamellar-can influence the physicochemical properties of encapsulated drugs, enabling tailored release profiles such as sustained, controlled, or targeted delivery. This review also explores the transitions in molecular geometry of amphiphilic compounds, additives, and hydrotrope molecules, which affect the formation and stability of LLC phases with varying pore sizes and water channels. The conclusion underscores the importance of ongoing research into LLCs for addressing cancer treatment challenges, including MDR. The versatility of LLCs extends beyond drug delivery to theranostic and diagnostic applications. By leveraging responsive smart drug delivery systems or incorporating natural compounds, LLCs offer a multifaceted approach to cancer therapy, highlighting their potential as a breakthrough in the field.

Machine Learning-Assisted Drug Repurposing Framework for Discovery of Aurora Kinase B Inhibitors

Background: Aurora kinase B (AurB) is a pivotal regulator of mitosis, making it a compelling target for cancer therapy. Despite significant advances in protein kinase inhibitor development, there are currently no AurB inhibitors readily available for therapeutic use. Methods: This study introduces a machine learning-assisted drug repurposing framework integrating quantitative structure-activity relationship (QSAR) modeling, molecular fingerprints-based classification, molecular docking, and molecular dynamics (MD) simulations. Using this pipeline, we analyzed 4680 investigational and approved drugs from DrugBank database. Results: The machine learning models trained for drug repurposing showed satisfying performance and yielded the identification of saredutant, montelukast, and canertinib as potential AurB inhibitors. The candidates demonstrated strong binding energies, key molecular interactions with critical residues (e.g., Phe88, Glu161), and stable MD trajectories, particularly saredutant, a neurokinin-2 (NK2) antagonist. Conclusions: Beyond identifying potential AurB inhibitors, this study highlights an integrated methodology that can be applied to other challenging drug targets.

A Comprehensive Review on the Regulatory Action of TRP Channels: A Potential Therapeutic Target for Nociceptive Pain

The transient receptor potential (TRP) superfamily of ion channels in humans comprises voltage-gated, non-selective cation channels expressed both in excitable as well as non-excitable cells. Four TRP channel subunits associate to create functional homo- or heterotetramers that allow the influx of calcium, sodium, and/or potassium. These channels are highly abundant in the brain and kidney and are important mediators of diverse biological functions including thermosensation, vascular tone, flow sensing in the kidney and irritant stimuli sensing. Inherited or acquired dysfunction of TRP channels influences cellular functions and signaling pathways resulting in multifaceted disorders affecting skeletal, renal, cardiovascular, and nervous systems. Studies have demonstrated the involvement of these channels in the generation and transduction of pain. Based on the multifaceted role orchestrated by these TRP channels, modulation of the activity of these channels presents an important strategy to influence cellular function by regulating intracellular calcium levels as well as membrane excitability. Therefore, there has been a remarkable pharmaceutical inclination toward TRP channels as therapeutic interventions. Several candidate drugs influencing the activity of these channels are already in the clinical trials pipeline. The present review encompasses the current understanding of TRP channels and TRP modulators in pain and pain management.

Progress in the development of TRPV1 small-molecule antagonists: Novel Strategies for pain management

Transient receptor potential vanilloid 1 (TRPV1) channels are widely distributed in sensory nerve endings, the central nervous system, and other tissues, functioning as ion channel proteins responsive to thermal pain and chemical stimuli. In recent years, the TRPV1 receptor has garnered significant interest as a potential therapeutic approach for various pain-related disorders, particularly TRPV1 antagonists. The present review offers a comprehensive, systematic exploration of both first- and second-generation TRPV1 antagonists in the context of pain management. Antagonists are categorized and explicated according to their structural characteristics. Detailed examination of binding modes, structural features, and pharmacological activities, alongside a critical appraisal of the advantages and limitations inherent to typical compounds within each structural category, are undertaken. Detailed discussions of the binding modes, structural features, pharmacological activities, advantages, and limitations of typical compounds within each structural category offer valuable insights and guidance for the future research and development of safer, more effective, and more targeted TRPV1 antagonists.

Discovery of novel TRPV1 modulators through machine learning-based molecular docking and molecular similarity searching

The transient receptor potential vanilloid 1 (TRPV1) channel belongs to the transient receptor potential channel superfamily and participates in many physiological processes. TRPV1 modulators (both agonists and antagonists) can effectively inhibit pain caused by various factors and have curative effects in various diseases, such as itch, cancer, and cardiovascular diseases. Therefore, the development of TRPV1 channel modulators is of great importance. In this study, the structure-based virtual screening and ligand-based virtual screening methods were used to screen compound databases respectively. In the structure-based virtual screening route, a full-length human TRPV1 protein was first constructed, three molecular docking methods with different precisions were performed based on the hTRPV1 structure, and a machine learning-based rescoring model by the XGBoost algorithm was constructed to enrich active compounds. In the ligand-based virtual screening route, the ROCS program was used for 3D shape similarity searching and the EON program was used for electrostatic similarity searching. Final 77 compounds were selected from two routes for in vitro assays. The results showed that 8 of them were identified as active compounds, including three hits with IC50 values close to capsazepine. In addition, one hit is a partial agonist with both agonistic and antagonistic activity. The mechanisms of some active compounds were investigated by molecular dynamics simulation, which explained their agonism or antagonism.

Recent Advances in Computer-Aided Structure-Based Drug Design on Ion Channels

Ion channels play important roles in fundamental biological processes, such as electric signaling in cells, muscle contraction, hormone secretion, and regulation of the immune response. Targeting ion channels with drugs represents a treatment option for neurological and cardiovascular diseases, muscular degradation disorders, and pathologies related to disturbed pain sensation. While there are more than 300 different ion channels in the human organism, drugs have been developed only for some of them and currently available drugs lack selectivity. Computational approaches are an indispensable tool for drug discovery and can speed up, especially, the early development stages of lead identification and optimization. The number of molecular structures of ion channels has considerably increased over the last ten years, providing new opportunities for structure-based drug development. This review summarizes important knowledge about ion channel classification, structure, mechanisms, and pathology with the main focus on recent developments in the field of computer-aided, structure-based drug design on ion channels. We highlight studies that link structural data with modeling and chemoinformatic approaches for the identification and characterization of new molecules targeting ion channels. These approaches hold great potential to advance research on ion channel drugs in the future.

In Silico Pharmacology for Evidence-Based and Precision Medicine

Personalized/precision medicine (PM) originates from the application of molecular pharmacology in clinical practice, representing a new era in healthcare that aims to identify and predict optimum treatment outcomes for a patient or a cohort with similar genotype/phenotype characteristics [...].