AIMC Topic: Biological Products

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Computational screening of natural products as tryptophan 2,3-dioxygenase inhibitors: Insights from CNN-based QSAR, molecular docking, ADMET, and molecular dynamics simulations.

Computers in biology and medicine
Parkinson's disease (PD) is characterised by a complex array of motor, psychiatric, and gastrointestinal symptoms, many of which are linked to disruptions in neuroactive metabolites. Dysregulated activity of tryptophan 2,3-dioxygenase (TDO), a key en...

Molecular insights fast-tracked: AI in biosynthetic pathway research.

Natural product reports
Covering: 2000 to 2025This review explores the potential of artificial intelligence (AI) in addressing challenges and accelerating molecular insights in biosynthetic pathway research, which is crucial for developing bioactive natural products with ap...

Engineering the future of medicine: Natural products, synthetic biology and artificial intelligence for next-generation therapeutics.

Clinical and translational medicine
The eXchange Unit between Thiolation domains approach and artificial intelligence (AI)-driven tools like Synthetic Intelligence are transforming nonribosomal peptide synthetase and polyketide synthase engineering, enabling the creation of novel bioac...

Identification of CXCR4 inhibitory activity in natural compounds using cheminformatics-guided machine learning algorithms.

Integrative biology : quantitative biosciences from nano to macro
Neurodegenerative disorders are characterised by progressive damage to neurons that leads to cognitive impairment and motor dysfunction. Current treatment options focus only on symptom management and palliative care, without addressing their root cau...

Prediction of Anti-rheumatoid Arthritis Natural Products of Xanthocerais Lignum Based on LC-MS and Artificial Intelligence.

Combinatorial chemistry & high throughput screening
AIMS: Employing the technique of liquid chromatography-mass spectrometry (LCMS) in conjunction with artificial intelligence (AI) technology to predict and screen for antirheumatoid arthritis (RA) active compounds in Xanthocerais lignum.

Deep learning in template-free de novo biosynthetic pathway design of natural products.

Briefings in bioinformatics
Natural products (NPs) are indispensable in drug development, particularly in combating infections, cancer, and neurodegenerative diseases. However, their limited availability poses significant challenges. Template-free de novo biosynthetic pathway d...

Real-World Screening Data for Liver Fibrosis in Psoriasis Patients Treated with Biologics.

Journal of Nippon Medical School = Nippon Ika Daigaku zasshi
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is positively associated with the prevalence and severity of psoriasis. The fibrosis-4 (FIB-4) index was developed to predict significant liver fibrosis. Using the FIB-4 ind...

Explainable deep learning enhances robust and reliable real-time monitoring of a chromatographic protein A capture step.

Biotechnology journal
The application of model-based real-time monitoring in biopharmaceutical production is a major step toward quality-by-design and the fundament for model predictive control. Data-driven models have proven to be a viable option to model bioprocesses. I...

Image-Based Subtype Classification for Glioblastoma Using Deep Learning: Prognostic Significance and Biologic Relevance.

JCO clinical cancer informatics
PURPOSE: To apply deep learning algorithms to histopathology images, construct image-based subtypes independent of known clinical and molecular classifications for glioblastoma, and produce novel insights into molecular and immune characteristics of ...

New peperomin and polyketides from dichloromethane extract of Peperomia blanda Jack. (Kunth).

Tropical biomedicine
Much of the new research and investigation in pharmacy sciences are concerned with developing therapeutic agents, and identifying and finding new drugs with their chemical structure to treat different human diseases such as infectious diseases from n...