AI Medical Compendium Journal:
Physical chemistry chemical physics : PCCP

Showing 31 to 37 of 37 articles

Accurate predictions of aqueous solubility of drug molecules via the multilevel graph convolutional network (MGCN) and SchNet architectures.

Physical chemistry chemical physics : PCCP
Deep learning based methods have been widely applied to predict various kinds of molecular properties in the pharmaceutical industry with increasingly more success. In this study, we propose two novel models for aqueous solubility predictions, based ...

Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks.

Physical chemistry chemical physics : PCCP
Chemical representations derived from deep learning are emerging as a powerful tool in areas such as drug discovery and materials innovation. Currently, this methodology has three major limitations - the cost of representation generation, risk of inh...

Representing the potential-energy surface of protonated water clusters by high-dimensional neural network potentials.

Physical chemistry chemical physics : PCCP
Investigating the properties of protons in water is essential for understanding many chemical processes in aqueous solution. While important insights can in principle be gained by accurate and well-established methods like ab initio molecular dynamic...

Towards peptide-based tunable multistate memristive materials.

Physical chemistry chemical physics : PCCP
Development of new memristive hardware is a technological requirement towards widespread neuromorphic computing. Molecular spintronics seems to be a fertile field for the design and preparation of this hardware. Within molecular spintronics, recent r...

Application and assessment of deep learning for the generation of potential NMDA receptor antagonists.

Physical chemistry chemical physics : PCCP
Uncompetitive antagonists of the N-methyl d-aspartate receptor (NMDAR) have demonstrated therapeutic benefit in the treatment of neurological diseases such as Parkinson's and Alzheimer's, but some also cause dissociative effects that have led to the ...

Development and application of a comprehensive machine learning program for predicting molecular biochemical and pharmacological properties.

Physical chemistry chemical physics : PCCP
We establish a comprehensive quantitative structure-activity relationship (QSAR) model termed AlphaQ through the machine learning algorithm to associate the fully quantum mechanical molecular descriptors with various biochemical and pharmacological p...

Neural networks applied to determine the thermophysical properties of amino acid based ionic liquids.

Physical chemistry chemical physics : PCCP
A series of models based on artificial neural networks (ANNs) have been designed to estimate the thermophysical properties of different amino acid-based ionic liquids (AAILs). Three different databases of AAILs were modeled using these algorithms wit...