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Molecular Structure

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Identification of herbal categories active in pain disorder subtypes by machine learning help reveal novel molecular mechanisms of algesia.

Pharmacological research
Chronic pain is highly prevalent and poorly controlled, of which the accurate underlying mechanisms need be further elucidated. Herbal drugs have been widely used for controlling various pain disorders. The systematic integration of pain herbal data ...

Big data and artificial intelligence discover novel drugs targeting proteins without 3D structure and overcome the undruggable targets.

Stroke and vascular neurology
The discovery of targeted drugs heavily relies on three-dimensional (3D) structures of target proteins. When the 3D structure of a protein target is unknown, it is very difficult to design its corresponding targeted drugs. Although the 3D structures ...

PTML Model of ChEMBL Compounds Assays for Vitamin Derivatives.

ACS combinatorial science
Determining the biological activity of vitamin derivatives is needed given that organic synthesis of analogs of vitamins is an active field of interest for medicinal chemistry, pharmaceuticals, and food additives. Accordingly, scientists from differe...

A deep learning approach for the blind logP prediction in SAMPL6 challenge.

Journal of computer-aided molecular design
Water octanol partition coefficient serves as a measure for the lipophilicity of a molecule and is important in the field of drug discovery. A novel method for computational prediction of logarithm of partition coefficient (logP) has been developed u...

Design of (quinolin-4-ylthio)carboxylic acids as new Escherichia coli DNA gyrase B inhibitors: machine learning studies, molecular docking, synthesis and biological testing.

Computational biology and chemistry
Spread of multidrug-resistant Escherichia coli clinical isolates is a main problem in the treatment of infectious diseases. Therefore, the modern scientific approaches in decision this problem require not only a prevention strategy, but also the deve...

Deep Learning to Generate Chemical Property Libraries and Candidate Molecules for Small Molecule Identification in Complex Samples.

Analytical chemistry
Comprehensive and unambiguous identification of small molecules in complex samples will revolutionize our understanding of the role of metabolites in biological systems. Existing and emerging technologies have enabled measurement of chemical properti...

Synthesis and in vitro activity of asymmetric indole-based bisamidine compounds against Gram-positive and Gram-negative pathogens.

Bioorganic & medicinal chemistry letters
A series of new asymmetric bisamidine was designed, synthesized, and tested for their in-vitro antibacterial activity using a range of Gram-positive and Gram-negative pathogens. Most compounds demonstrated powerful antibacterial activity, and interes...

Artificial intelligence and big data facilitated targeted drug discovery.

Stroke and vascular neurology
Different kinds of biological databases publicly available nowadays provide us a goldmine of multidiscipline big data. The Cancer Genome Atlas is a cancer database including detailed information of many patients with cancer. DrugBank is a database in...

LightGBM: An Effective and Scalable Algorithm for Prediction of Chemical Toxicity-Application to the Tox21 and Mutagenicity Data Sets.

Journal of chemical information and modeling
Machine learning algorithms have attained widespread use in assessing the potential toxicities of pharmaceuticals and industrial chemicals because of their faster speed and lower cost compared to experimental bioassays. Gradient boosting is an effect...

Graph Classification of Molecules Using Force Field Atom and Bond Types.

Molecular informatics
Classification of the biological activities of chemical substances is important for developing new medicines efficiently. Various machine learning methods are often employed to screen large libraries of compounds and predict the activities of new sub...