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This molecular docking study reported that danoprevir, remdesivir, and saridegib exhibit stronger binding affinities to the main protease of SARS-CoV-2 than the control, suggesting their potential as inhibitors of the virus's replication process.

This study demonstrated that a computational screening process can identify existing drugs and natural compounds with potential anti-COVID-19 activity, highlighting some candidates for further experimental validation.

This study found that minoxidil had the highest solubility in shea butter, stearic acid, and rosemary oil, suggesting these natural oils may improve drug loading and encapsulation efficiency in lipid nanocarrier formulations for potential hair growth applications.

This study suggests that three mushroom-derived bioactive compounds, Zhankuic acid A, Sterenin M, and Melleolide K, may effectively inhibit SRD5A2 and stabilize its interaction, indicating potential for treating androgenic alopecia.

This study screened a compound library against the PIEZO1+MLCK axis and identified candidate scaffolds with potential topical use for treating hair follicle miniaturization, though findings are in silico and need validation.

This study identified 19 specific genes involved in root hair growth and morphogenesis in Arabidopsis, using a combination of computational and experimental methods.

This study discovered a potential new 5α-reductase type II inhibitor with higher predicted activity than finasteride, suggesting it as a promising candidate for treating benign prostatic hyperplasia.

This study found that humulen, a phytoconstituent of Cyperus Rotundus Linn., showed the highest binding affinity in molecular docking with the 5 α reductase enzyme, suggesting potential anti-androgenic effects for hirsutism treatment.

In this study, phytochemical analysis and molecular docking suggested that bioactive compounds in several Ayurvedic herbs may interact persistently with hair growth and antifungal protein targets, indicating potential as plant-based treatments for dandruff and hair loss.

This review discusses the potential of using high-throughput and high-content screening methods for drug repositioning in rare diseases and reports no new results.

Accurate protein modeling can help develop new treatments for prostate cancer and other diseases.

In this study, researchers used computational modeling and virtual screening to identify two FDA-approved drugs, Tadalafil and Finasteride, that may effectively inhibit key proteins involved in melanoma progression, suggesting potential for new therapeutic strategies against aggressive melanoma.

This review discusses how recent advancements in computational and lab-based methods have enhanced peptide drug discovery, noting the efficiency and cost benefits over traditional approaches and the potential for targeting difficult protein interactions, including protein degradation using proteolysis-targeting chimeras.

In this study, researchers validated a computational workflow for repurposing non-antibacterial drugs as antibacterial agents and highlighted daprodustat, combined with an efflux pump inhibitor, as a promising strategy against bacterial pathogens.

This study introduced ElixirSeeker2, a computational framework for designing anti-aging peptides, and found that some newly identified peptides significantly delayed cellular senescence and enhanced cellular and locomotor functions in aged Caenorhabditis elegans.

This review examines advances in computer-aided drug design for targeting membrane proteins in prostate cancer but reports no new clinical results; it emphasizes the potential of structural insights and compound screening for therapeutic development.

This study found that the peptides RMYYY and VMYMI displayed stronger binding energy and more frequent interactions with HPGDS compared to the native inhibitor, suggesting potential as future therapeutic drugs.

This review discusses the development and potential applications of organoids for human disease modeling and regenerative medicine but reports no new experimental results.

This study developed and validated a radiomics-based clinical nomogram using routine renal ultrasound and clinical data to predict early diabetic kidney injury in a community cohort, finding it significantly outperformed clinical-only models in predicting risk and showed potential as a cost-effective screening tool.

This study identified procyanidin B2 and leucopelargonidin from Saraca asoca as potential inhibitors in PCOS by showing high binding energy scores against key enzymes involved in estrogen and testosterone biosynthesis.

This study reviews the potential of dibenzo derivatives as safer cancer treatments but finds conflicting evidence about their effectiveness, possibly due to structural differences among the compounds, and reports no new results.

This study found that the ethyl acetate extract of Semecarpus anacardium leaves demonstrated cytotoxicity against MCF-7 cancer cells and induced apoptosis, suggesting potential as a cancer treatment with fewer side effects.

This study suggests that finasteride may inhibit the enzyme PNMT, potentially contributing to its sexual and psychological side effects.

This study used machine learning models to analyze PCOS symptoms for early diagnosis, finding Support Vector Machine and VGG16 algorithms achieved high accuracy rates of 94.44% and 98.29% respectively.

This study identified neprilysin as a potential target of the pharmacological agent arteannuin, which may guide future research into its clinical applications, although experimental verification is needed.

This study discusses the rising interest in drug repositioning, particularly in response to COVID-19, and highlights various computational and experimental approaches used for repurposing existing drugs across different diseases, including rare conditions and chronic kidney disease.

This review discusses the integration of drug repurposing with personalized medicine through off-label prescribing and reports no new results, highlighting the potential for systematic exploration using omics technologies.

This review discusses the use of the zebrafish lateral line system as a model to study hair cell loss, protection, and regeneration, with potential implications for human hearing research.

This study identified a series of novel β-glucuronidase inhibitors that may help mitigate adverse effects of first-line anti-cancer drugs by targeting gut bacteria, based on virtual high-throughput screening findings.

This study reviews the transformative role of artificial intelligence in biomaterial design, highlighting its ability to reduce costs through virtual screening, enhance material performance, and predict biological interactions to advance personalized and precision medicine.