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Drug Evaluation, Preclinical

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DeepScreening: a deep learning-based screening web server for accelerating drug discovery.

Database : the journal of biological databases and curation
Deep learning contributes significantly to researches in biological sciences and drug discovery. Previous studies suggested that deep learning techniques have shown superior performance to other machine learning algorithms in virtual screening, which...

Virtual Screening of Anti-Cancer Compounds: Application of Monte Carlo Technique.

Anti-cancer agents in medicinal chemistry
Possibility and necessity of standardization of predictive models for anti-cancer activity are discussed. The hypothesis about rationality of common quantitative analysis of anti-cancer activity and carcinogenicity is developed. Potential of optimal ...

Virtual Screening Meets Deep Learning.

Current computer-aided drug design
BACKGROUND: Automated compound testing is currently the de facto standard method for drug screening, but it has not brought the great increase in the number of new drugs that was expected. Computer- aided compounds search, known as Virtual Screening,...

Evaluation of the potential nephrotoxicity and mechanism in rats after long-term exposure to the traditional Tibetan medicine tsothel.

Pharmaceutical biology
CONTEXT: Tsothel, a traditional Tibetan medicine, is regarded as 'the king of essences'. Nevertheless, tsothel has aroused serious concern regarding its biosafety because its main component is HgS. Unfortunately, toxicological studies on tsothel are ...

Smart Data Analytics approach to model Complex Biochemical Oscillations in Hippocampal Neurons.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Calcium spiking can be used for drug screening studies in pharmaceutical industries. However, performing experiments for multiple drugs and doses are highly expensive. The oscillatory behavior of calcium spiking data demonstrates extreme nonlinearity...

WDL-RF: predicting bioactivities of ligand molecules acting with G protein-coupled receptors by combining weighted deep learning and random forest.

Bioinformatics (Oxford, England)
MOTIVATION: Precise assessment of ligand bioactivities (including IC50, EC50, Ki, Kd, etc.) is essential for virtual screening and lead compound identification. However, not all ligands have experimentally determined activities. In particular, many G...

Computational Identification of Chemical Compounds with Potential Activity against Leishmania amazonensis using Nonlinear Machine Learning Techniques.

Current topics in medicinal chemistry
Leishmaniasis is a poverty-related disease endemic in 98 countries worldwide, with morbidity and mortality increasing daily. All currently used first-line and second-line drugs for the treatment of leishmaniasis exhibit several drawbacks including to...

Machine Learning-based Virtual Screening and Its Applications to Alzheimer's Drug Discovery: A Review.

Current pharmaceutical design
BACKGROUND: Virtual Screening (VS) has emerged as an important tool in the drug development process, as it conducts efficient in silico searches over millions of compounds, ultimately increasing yields of potential drug leads. As a subset of Artifici...

[Machine Learning-based Prediction of Seizure-inducing Action as an Adverse Drug Effect].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
 During the preclinical research period of drug development, animal testing is widely used to help screen out a drug's dangerous side effects. However, it remains difficult to predict side effects within the central nervous system. Here, we introduce...