AIMC Topic: Biological Products
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Accurate Prediction of ωB97X-D/6-31G* Equilibrium Geometries from a Neural Net Starting from Merck Molecular Force Field (MMFF) Molecular Mechanics Geometries.
Journal of chemical information and modeling
Feb 17, 2025
Starting from Merck Molecular Force Field (MMFF) geometries, a neural-net based model has been formulated to closely reproduce ωB97X-D/6-31G* equilibrium geometries for organic molecules. The model involves training to >6 million energy and force cal...
Machine Learning-Based Bioactivity Classification of Natural Products Using LC-MS/MS Metabolomics.
Journal of natural products
Feb 7, 2025
The rediscovery of known drug classes represents a major challenge in natural products drug discovery. Compound rediscovery inhibits the ability of researchers to explore novel natural products and wastes significant amounts of time and resources. Th...
Machine Learning-Driven Discovery of Structurally Related Natural Products as Activators of the Cardiac Calcium Pump SERCA2a.
ChemMedChem
Feb 6, 2025
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...
Artificial Intelligence in Natural Product Drug Discovery: Current Applications and Future Perspectives.
Journal of medicinal chemistry
Feb 6, 2025
Drug discovery, a multifaceted process from compound identification to regulatory approval, historically plagued by inefficiencies and time lags due to limited data utilization, now faces urgent demands for accelerated lead compound identification. 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
Jan 16, 2025
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...
Natural compounds for Alzheimer's prevention and treatment: Integrating SELFormer-based computational screening with experimental validation.
Computers in biology and medicine
Dec 9, 2024
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...
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
Dec 5, 2024
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 ...
Machine learning-assisted SERS sensor for fast and ultrasensitive analysis of multiplex hazardous dyes in natural products.
Journal of hazardous materials
Nov 19, 2024
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)
Nov 14, 2024
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...
Screening for Potential Antiviral Compounds from Cyanobacterial Secondary Metabolites Using Machine Learning.
Marine drugs
Nov 5, 2024
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...
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