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Molecular Structure

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NP-Scout: Machine Learning Approach for the Quantification and Visualization of the Natural Product-Likeness of Small Molecules.

Biomolecules
Natural products (NPs) remain the most prolific resource for the development of smallmolecule drugs. Here we report a new machine learning approach that allows the identification of natural products with high accuracy. The method also generates simil...

Machine Learning Models for the Prediction of Chemotherapy-Induced Peripheral Neuropathy.

Pharmaceutical research
PURPOSE: Chemotherapy-induced peripheral neuropathy (CIPN) is a common adverse side effect of cancer chemotherapy that can be life debilitating and cause extreme pain. The multifactorial and poorly understood mechanisms of toxicity have impeded the i...

Prediction of matrix metal proteinases-12 inhibitors by machine learning approaches.

Journal of biomolecular structure & dynamics
Matrix metal proteinases-12 (MMP-12) is a hot pharmaceutical target on the treatment of many human diseases. There's a crying need for designing and finding new MMP-12 inhibitors. In this work, four machine learning approaches, support vector machine...

De Novo Molecule Design by Translating from Reduced Graphs to SMILES.

Journal of chemical information and modeling
A key component of automated molecular design is the generation of compound ideas for subsequent filtering and assessment. Recently deep learning approaches have been explored as alternatives to traditional de novo molecular design techniques. Deep l...

Near-infrared mito-specific fluorescent probe for ratiometric detection and imaging of alkaline phosphatase activity with high sensitivity.

Journal of materials chemistry. B
Fluorescent probe-based analytical methods for biological species have gained increasing attention for their powerful detection and imaging capabilities. However, it is still occasionally problematic for accurate analyses due to the influence of the ...

Peroxidase-like activity of acetylcholine-based colorimetric detection of acetylcholinesterase activity and an organophosphorus inhibitor.

Journal of materials chemistry. B
Colorimetric detection of acetylcholinesterase (AChE) and its inhibitor organophosphates (OPs) is attractive for its convenience, but the addition of exogenous catalyst to produce a chromogenic agent may result in complexity and interference. Herein,...

Using Data Mining To Search for Perovskite Materials with Higher Specific Surface Area.

Journal of chemical information and modeling
The specific surface area (SSA) of ABO-type perovskite is one of the important properties associated with photocatalytic ability. In this work, data mining methods were used to explore the relationship between the SSA (in the range of 1-60 m g) of pe...

High-throughput brain activity mapping and machine learning as a foundation for systems neuropharmacology.

Nature communications
Technologies for mapping the spatial and temporal patterns of neural activity have advanced our understanding of brain function in both health and disease. An important application of these technologies is the discovery of next-generation neurotherap...

Vibrational Properties of Metastable Polymorph Structures by Machine Learning.

Journal of chemical information and modeling
Despite vibrational properties being critical for the ab initio prediction of finite-temperature stability as well as thermal conductivity and other transport properties of solids, their inclusion in ab initio materials repositories has been hindered...