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This study used machine learning to develop classifiers for identifying effective inhibitors of 5α-reductase isozyme 2, achieving high performance in distinguishing potent from weak inhibitors.

In this study, the researchers performed a comparative analysis of drug-target interaction data from multiple databases to refine drug repurposing strategies, revealing potential associations between drug characteristics and therapeutic groups, and predicting repositioning opportunities for FDA-approved drugs across major cancer types.

In this study, researchers evaluated drug-target interaction data from three major resources and developed a framework for drug repurposing, revealing associations between drug properties and therapeutic groups to aid in compound prioritization and predicting repositioning opportunities for existing drugs, particularly in cancer treatment.

This review discusses the data resources and computational models used in drug repositioning, highlighting their role in discovering unknown drug mechanisms and reports no new empirical results.

This review examines the current landscape of drug repositioning, highlighting that computational methods expand possibilities for reusing existing drugs to treat unmet medical needs. The authors discuss both the potential of these methods and the challenges faced in identifying new therapeutic applications.

This review examines studies from 2019-2022 on dietary treatments for skin diseases, highlighting various foods and supplements that may aid in managing conditions like acne, psoriasis, and alopecia areata.

This study introduced the KRDQN predictive framework, which outperformed existing methods in predicting adverse drug reactions and provided interpretable insights into drug mechanisms, aiding pharmacovigilance and clinical decision-making.

This study identified several compounds from traditional Chinese medicines that may inhibit prostaglandin D2 synthase, potentially providing promising candidates for treating androgenic alopecia with minimal adverse skin reactions.

In this article, the authors describe how drug repurposing, supported by large-scale data and artificial intelligence, can make drug discovery more cost-effective and expedient compared to traditional methods, despite certain regulatory challenges.

This study explored the optimization of phytochemicals from Alstonia boonei to develop potential 5-alpha reductase inhibitors for Benign Prostatic Hyperplasia, finding promising analogs with enhanced binding affinity and stability compared to Finasteride, warranting further experimental validation.

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 SARS-CoV-2 hijacks the host factor IGF2BP1 to stabilize its RNA and enhance translation, and identified Cepharanthine and Trifluoperazine as potential treatments against the virus.

This study identified ten novel compounds that may effectively target steroid 5 alpha-reductase 2 (5αR-2) for potential treatment of benign prostate hyperplasia, exhibiting comparable binding energies to existing drugs like finasteride and dutasteride.

This study used an in silico/in vitro approach to identify potential inhibitors of the enzyme SRD5A2, finding that the androgen receptor modulator MK-0773 is a moderate inhibitor, although it does not act as a covalent inhibitor like finasteride.

This study identified seven novel CYP17A1 inhibitor scaffolds as potential leads for treating polycystic ovary syndrome through an in silico approach, demonstrating favorable interactions, drug-like properties, and predicted bioactivities warranting further experimental validation.

This study found that altered amino acid metabolism, specifically involving glutamic and aspartic acids, promotes neurovascular reactivity in rosacea, suggesting a potential metabolic target for treatment.

This study suggests that hydroxytyrosol may influence inflammation and oxidative stress pathways in androgenetic alopecia, particularly through interaction with the PTGS2 gene, warranting further experimental validation.

This study used machine learning to identify FDA-approved drugs afatinib, neratinib, and zanubrutinib as potential KRASG12C inhibitors for resistant non-small-cell lung cancer, highlighting the potential of AI in drug repurposing.

This review outlines computational strategies, including chemogenomics and drug repositioning, for coronavirus drug discovery and reports no new clinical findings; the authors highlight the advantages of these methods in rapidly identifying therapeutic candidates.

This study found that β-sitosterol, a brain-penetrable phytosterol, reduced melanoma cell growth and brain metastasis formation by interfering with mitochondrial respiration, suggesting its potential as an adjuvant therapy to BRAF inhibitors for patients with melanoma brain metastases.

In this paper, Chemistry42—a software integrating AI with computational and medicinal chemistry—demonstrated efficiency in designing novel molecular structures targeting DDR1 and CDK20, with properties validated in both in vitro and in vivo studies.

This study demonstrated that α-phellandrene promotes dermal papilla cell proliferation through a cAMP-mediated pathway and upregulates VEGF expression, suggesting its potential use in hair loss prevention.

This study found that purified humic acids from oxidized coal enhance plant growth by modulating oxidative stress and influencing photobiological processes, with improved root growth and enzyme activity linked to antioxidant and pro-oxidant properties.

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

This study demonstrates that Bazi Bushen capsules may have therapeutic potential against skin photoaging in mice by enhancing NRF2 expression and targeting the KEAP1-NRF2 pathway.

This review discusses the potential topical benefits of cannabidiol in dermatology and cosmetics, highlighting its diverse effects and therapeutic roles but reports no new clinical results, emphasizing the need for further research.

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 study used a multi-layer in silico framework to evaluate Korean herbal compounds for androgenetic alopecia, identifying Biochanin A, Saponin Re, and Emodin as potential topical candidates with distinct safety and affinity profiles, although these findings remain purely computational without experimental validation.

This study evaluated Korean herbal compounds in silico and identified Biochanin A, Saponin Re, and Emodin as potential topical treatments for androgenetic alopecia, each with specific safety and efficacy considerations.

In this study, in silico analysis identified Saponin Re and Emodin as promising candidates for topical treatment of androgenetic alopecia, with Biochanin A having the most favorable safety profile among the tested compounds.