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Biological Products

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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...

Deep learning based predictive modeling to screen natural compounds against TNF-alpha for the potential management of rheumatoid arthritis: Virtual screening to comprehensive in silico investigation.

PloS one
Rheumatoid arthritis (RA) affects an estimated 0.1% to 2.0% of the world's population, leading to a substantial impact on global health. The adverse effects and toxicity associated with conventional RA treatment pathways underscore the critical need ...

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...

Screening for Potential Antiviral Compounds from Cyanobacterial Secondary Metabolites Using Machine Learning.

Marine drugs
The secondary metabolites of seawater and freshwater blue-green algae are a rich natural product pool containing diverse compounds with various functions, including antiviral compounds; however, high-efficiency methods to screen such compounds are la...

Machine learning-assisted SERS sensor for fast and ultrasensitive analysis of multiplex hazardous dyes in natural products.

Journal of hazardous materials
The adulteration of natural products with multiple azo dyes has become a serious public health concern. Thus, on-site trace additive detection is demanded. Herein, we developed a gold-nanorod-based surface-enhanced Raman scattering (SERS) sensor to d...

Target Fisher: A Consensus Structure-Based Target Prediction Tool, and its Application in the Discovery of Selective MAO-B Inhibitors.

Chemistry (Weinheim an der Bergstrasse, Germany)
In this work we introduce Target Fisher, a consensus structure-based target prediction tool that integrates molecular docking and machine learning with the aim to aid in the identification of potential biological targets and the optimization of the u...

Natural compounds for Alzheimer's prevention and treatment: Integrating SELFormer-based computational screening with experimental validation.

Computers in biology and medicine
BACKGROUND: This study aimed to develop and apply a novel computational pipeline combining SELFormer, a transformer architecture-based chemical language model, with advanced deep learning techniques to predict natural compounds (NCs) with potential i...

Exploring a new paradigm for serum-accessible component rules of natural medicines using machine learning and development and validation of a direct predictive model.

International journal of pharmaceutics
In the field of pharmaceutical research, Lipinski's Rule of Five (RO5) was once widely regarded as the prevailing standard for the development of novel drugs. Despite the fact that an increasing number of recently approved drugs no longer adhere to t...

Machine Learning-Driven Discovery of Structurally Related Natural Products as Activators of the Cardiac Calcium Pump SERCA2a.

ChemMedChem
A key molecular dysfunction in heart failure is the reduced activity of the cardiac sarcoplasmic reticulum Ca-ATPase (SERCA2a) in cardiac muscle cells. Reactivating SERCA2a improves cardiac function in heart failure models, making it a validated targ...

Recommendations for Artificial Intelligence Application in Continued Process Verification: A Journey Toward the Challenges and Benefits of AI in the Biopharmaceutical Industry.

PDA journal of pharmaceutical science and technology
This review paper explores the transformative impact of Artificial Intelligence (AI) on Continued Process Verification (CPV) in the biopharmaceutical industry. Originating from the CPV of the Future project, the study investigates the challenges and ...