Predicting in vivo compound brain penetration using multi-task graph neural networks
Assessing whether compounds penetrate the brain can become critical in drug discovery,
either to prevent adverse events or to reach the biological target. Generally, pre-clinical in …
either to prevent adverse events or to reach the biological target. Generally, pre-clinical in …
A comprehensive review of artificial intelligence for pharmacology research
With the innovation and advancement of artificial intelligence, more and more artificial
intelligence techniques are employed in drug research, biomedical frontier research, and …
intelligence techniques are employed in drug research, biomedical frontier research, and …
Re-routing drugs to blood brain barrier: A comprehensive analysis of machine learning approaches with fingerprint amalgamation and data balancing
Computational drug repurposing is an efficient method to utilize existing knowledge for
understanding and predicting their effect on neurological diseases. The ability of a molecule …
understanding and predicting their effect on neurological diseases. The ability of a molecule …
Development of QSAR models to predict blood-brain barrier permeability
Assessing drug permeability across the blood-brain barrier (BBB) is important when
evaluating the abuse potential of new pharmaceuticals as well as develo** novel …
evaluating the abuse potential of new pharmaceuticals as well as develo** novel …
ADMET property prediction via multi-task graph learning under adaptive auxiliary task selection
It is a critical step in lead optimization to evaluate the absorption, distribution, metabolism,
excretion, and toxicity (ADMET) properties of drug-like compounds. Classical single-task …
excretion, and toxicity (ADMET) properties of drug-like compounds. Classical single-task …
Relational graph convolutional networks for predicting blood–brain barrier penetration of drug molecules
Motivation Evaluating the blood–brain barrier (BBB) permeability of drug molecules is a
critical step in brain drug development. Traditional methods for the evaluation require …
critical step in brain drug development. Traditional methods for the evaluation require …
Drug repurposing, a fast-track approach to develop effective treatments for glioblastoma
Simple Summary Introducing novel and effective treatments against glioblastoma (GBM)
remains an arduous journey as reflected in the negative outcome of most clinical trials. The …
remains an arduous journey as reflected in the negative outcome of most clinical trials. The …
Design, pharmacokinetic profiling, and assessment of kinetic and thermodynamic stability of novel anti-Salmonella typhi imidazole analogues
Background Typhoid fever, a disease caused by a gram negative bacterial species known
as Salmonella typhi, constitutes a significant cause of morbidity and mortality, especially in …
as Salmonella typhi, constitutes a significant cause of morbidity and mortality, especially in …
[HTML][HTML] An Optimized Deep Learning Approach for Blood-Brain Barrier Permeability Prediction with ODE Integration
Blood-brain barrier (BBB) permeability prediction plays a pivotal role in drug discovery for
neurological disorders which is essential for the development of central nervous system …
neurological disorders which is essential for the development of central nervous system …
MTGL-ADMET: a novel multi-task graph learning framework for ADMET prediction enhanced by status-theory and maximum flow
It is a vital step to evaluate drug-like compounds in terms of absorption, distribution,
metabolism, excretion, and toxicity (ADMET) in drug design. Classical single-task learning …
metabolism, excretion, and toxicity (ADMET) in drug design. Classical single-task learning …