AIMC Topic: Membrane Proteins
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Oral ENPP1 inhibitor designed using generative AI as next generation STING modulator for solid tumors.
Nature communications
May 23, 2025
Despite the STING-type-I interferon pathway playing a key role in effective anti-tumor immunity, the therapeutic benefit of direct STING agonists appears limited. In this study, we use several artificial intelligence techniques and patient-based mult...
Discovering Novel Biomarkers and Potential Therapeutic Targets of Amyotrophic Lateral Sclerosis Through Integrated Machine Learning and Gene Expression Profiling.
Journal of molecular neuroscience : MN
Apr 30, 2025
Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder that has multiple factors that make its molecular pathogenesis difficult to understand and its diagnosis and treatment during the early stages difficult to determine. Dis...
CLIC1 and IFITM2 expression in brain tissue correlates with cognitive impairment via immune dysregulation in sepsis and Alzheimer's disease.
International immunopharmacology
Apr 10, 2025
BACKGROUND: Sepsis, a life-threatening condition driven by dysregulated host responses to infection, is associated with long-term cognitive impairments resembling Alzheimer's disease (AD). However, the molecular mechanisms linking sepsis-induced cogn...
NA_mCNN: Classification of Sodium Transporters in Membrane Proteins by Integrating Multi-Window Deep Learning and ProtTrans for Their Therapeutic Potential.
Journal of proteome research
Apr 7, 2025
Sodium transporters maintain cellular homeostasis by transporting ions, minerals, and nutrients across the membrane, and Na+/K+ ATPases facilitate the cotransport of solutes in neurons, muscle cells, and epithelial cells. Sodium transporters are impo...
Genome data based deep learning identified new genes predicting pharmacological treatment response of attention deficit hyperactivity disorder.
Translational psychiatry
Feb 7, 2025
Although the efficacy of pharmacy in the treatment of attention deficit/hyperactivity disorder (ADHD) has been well established, the lack of predictors of treatment response poses great challenges for personalized treatment. The current study employe...
Golgi protein 73: charting new territories in diagnosing significant fibrosis in MASLD: a prospective cross-sectional study.
Frontiers in endocrinology
Jan 13, 2025
OBJECTIVES: To explore the correlation between serum Golgi protein 73 (GP73) levels and the degree of fibrosis in Metabolic dysfunction associated steatotic liver disease (MASLD); to establish a non-invasive diagnostic algorithm based on serum GP73 a...
PRAF2 as a novel biomarker for breast cancer with machine learning and experimentation validation.
BMC cancer
Jan 8, 2025
BACKGROUND: Breast cancer (BC) is the most prevalent malignancy in women. Potential therapeutic targets for BC are of great significance. In our previous study, we found that prenylated rab acceptor 1 domain family member 2 (PRAF2) is an oncogene in ...
Harnessing machine learning and multi-omics to explore tumor evolutionary characteristics and the role of AMOTL1 in prostate cancer.
International journal of biological macromolecules
Dec 4, 2024
Although recent advancements have shed light on the crucial role of coordinated evolution among cell subpopulations in influencing disease progression, the full potential of these insights has not yet been fully harnessed in the clinical application ...
Analysis of solid-state NMR data facilitated by MagRO_NMRViewJ with Graph_Robot: Application for membrane protein and amyloid.
Biophysical chemistry
Nov 17, 2024
Solid-state NMR (ssNMR) methods have continued to be developed in recent years for the efficient assignment of signals and 3D structure modeling of biomacromolecules. Consequently, we are approaching an era in which vigorous applications of these met...
Machine learning model identifies genetic predictors of cisplatin-induced ototoxicity in CERS6 and TLR4.
Computers in biology and medicine
Nov 1, 2024
BACKGROUND: Cisplatin-induced ototoxicity remains a significant concern in pediatric cancer treatment due to its permanent impact on quality of life. Previously, genetic association analyses have been performed to detect genetic variants associated w...
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