AI Medical Compendium Journal:
Chemical communications (Cambridge, England)

Showing 11 to 20 of 23 articles

Modern machine learning for tackling inverse problems in chemistry: molecular design to realization.

Chemical communications (Cambridge, England)
The discovery of new molecules and materials helps expand the horizons of novel and innovative real-life applications. In pursuit of finding molecules with desired properties, chemists have traditionally relied on experimentation and recently on comb...

High-throughput screening, next generation sequencing and machine learning: advanced methods in enzyme engineering.

Chemical communications (Cambridge, England)
Enzyme engineering is an important biotechnological process capable of generating tailored biocatalysts for applications in industrial chemical conversion and biopharma. Typical enhancements sought in enzyme engineering and evolution campaigns inclu...

Deep learning-driven scaffold hopping in the discovery of Akt kinase inhibitors.

Chemical communications (Cambridge, England)
Scaffold hopping has been widely used in drug discovery and is a topic of high interest. Here a deep conditional transformer neural network, SyntaLinker, was applied for the scaffold hopping of a phase III clinical Akt inhibitor, AZD5363. A number of...

A pendant droplet-based sensor for the detection of acetylcholinesterase and its inhibitors.

Chemical communications (Cambridge, England)
In this work, a pendant droplet-based sensor is developed for the rapid and label-free detection of acetylcholinesterase (AChE) and its inhibitors. The detection limit of AChE reaches 0.17 mU mL. The pIC values of AChE inhibitors such as neostigmine,...

Homogeneous DNA-only keypad locks enable one-pot assay of multi-inputs.

Chemical communications (Cambridge, England)
Homogeneous DNA-only keypad locks were built with multi-stranded scalable junction substrates and a series of double-stranded eliminators to differentially process correctly- and wrongly-added DNA inputs, respectively. Unlike conventional strategies ...

Rosetta custom score functions accurately predict ΔΔG of mutations at protein-protein interfaces using machine learning.

Chemical communications (Cambridge, England)
Protein-protein interfaces play essential roles in a variety of biological processes and many therapeutic molecules are targeted at these interfaces. However, accurate predictions of the effects of interfacial mutations to identify "hotspots" have re...

Low-cost smartphone-based LIBS combined with deep learning image processing for accurate lithology recognition.

Chemical communications (Cambridge, England)
A low-cost and multi-channel smartphone-based spectrometer was developed for LIBS. As the CMOS detector is two-dimensional, simultaneous multichannel detection was achieved by coupling a linear array of fibres for light collection. Thus, besides the ...

A graph-convolutional neural network for addressing small-scale reaction prediction.

Chemical communications (Cambridge, England)
We describe a graph-convolutional neural network (GCN) model, the reaction prediction capabilities of which are as potent as those of the transformer model based on sufficient data, and we adopt the Baeyer-Villiger oxidation reaction to explore their...

Integration of ultra-high-pressure liquid chromatography-tandem mass spectrometry with machine learning for identifying fatty acid metabolite biomarkers of ischemic stroke.

Chemical communications (Cambridge, England)
We report for the first time the integration of ultra-high-pressure liquid chromatography-tandem mass spectrometry with machine learning for identifying fatty acid metabolite biomarkers of ischemic stroke. In particular, we develop an optimal model t...

Dissecting celastrol with machine learning to unveil dark pharmacology.

Chemical communications (Cambridge, England)
By coalescing bespoke machine learning and bioinformatics analyses with cell-based assays, we unveil the pharmacology of celastrol. Celastrol is a direct modulator of the progesterone and cannabinoid receptors, and its effects correlate with the anti...