BIBLIOMETRIC ANALYSIS OF ARTIFICIAL INTELLIGENCE IN HEALTHCARE RESEARCH: TRENDS AND FUTURE DIRECTIONS

Future Healthcare Journal, Год журнала: 2024, Номер 11(3), С. 100182 - 100182

Опубликована: Сен. 1, 2024

The presence of artificial intelligence (AI) in healthcare is a powerful and game-changing force that completely transforming the industry as whole. Using sophisticated algorithms data analytics, AI has unparalleled prospects for improving patient care, streamlining operational efficiency, fostering innovation across ecosystem. This study conducts comprehensive bibliometric analysis research on healthcare, utilising SCOPUS database primary source.

Язык: Английский

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Ligand-Induced Biased Activation of GPCRs: Recent Advances and New Directions from In Silico Approaches

Molecules, Год журнала: 2025, Номер 30(5), С. 1047 - 1047

Опубликована: Фев. 25, 2025

G-protein coupled receptors (GPCRs) are the largest family of membrane proteins engaged in transducing signals from extracellular environment into cell. GPCR-biased signaling occurs when two different ligands, sharing same binding site, induce distinct pathways. This selective offers significant potential for design safer and more effective drugs. Although its molecular mechanism remains elusive, big efforts made to try explain this using a wide range methods. Recent advances computational techniques AI technology have introduced variety simulations machine learning tools that facilitate modeling GPCR signal transmission analysis ligand-induced biased signaling. In review, we present current state silico approaches elucidate structural includes dynamics capture main interactions causing bias. We also highlight major contributions impacts transmembrane domains, loops, mutations mediating Moreover, discuss impact models on bias prediction diffusion-based generative ligands. Ultimately, review addresses future directions studying problem through approaches.

Язык: Английский

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Identification and Validation of New DNA-PKcs Inhibitors through High-Throughput Virtual Screening and Experimental Verification

International Journal of Molecular Sciences, Год журнала: 2024, Номер 25(14), С. 7982 - 7982

Опубликована: Июль 22, 2024

DNA-PKcs is a crucial protein target involved in DNA repair and response pathways, with its abnormal activity closely associated the occurrence progression of various cancers. In this study, we employed deep learning-based screening molecular dynamics (MD) simulation-based pipeline, identifying eight candidates for targets. Subsequent experiments revealed effective inhibition DNA-PKcs-mediated cell proliferation by three small molecules (5025-0002, M769-1095, V008-1080). These exhibited anticancer IC50 (inhibitory concentration at 50%) values 152.6 μM, 30.71 74.84 respectively. Notably, V008-1080 enhanced homology-directed (HDR) mediated CRISPR/Cas9 while inhibiting non-homologous end joining (NHEJ) efficiency. Further investigations into structure-activity relationships unveiled binding sites critical interactions between these DNA-PKcs. This first application DeepBindGCN_RG real drug task, successful discovery novel inhibitor demonstrates efficiency as core component pipeline. Moreover, study provides important insights exploring therapeutics advancing development gene editing techniques targeting

Язык: Английский

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Targeting ATP catalytic activity of chromodomain helicase CHD1L for the anticancer inhibitor discovery

International Journal of Biological Macromolecules, Год журнала: 2024, Номер unknown, С. 136678 - 136678

Опубликована: Окт. 1, 2024

Язык: Английский

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