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Molecular Structure

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Prediction of blood-brain barrier permeability of organic compounds.

Doklady. Biochemistry and biophysics
Using fragmental descriptors and artificial neural networks, a predictive model of the relationship between the structure of organic compounds and their blood-brain barrier permeability was constructed and the structural factors affecting the readine...

QSPR studies for predicting polarity parameter of organic compounds in methanol using support vector machine and enhanced replacement method.

SAR and QSAR in environmental research
In the present work, enhanced replacement method (ERM) and support vector machine (SVM) were used for quantitative structure-property relationship (QSPR) studies of polarity parameter (p) of various organic compounds in methanol in reversed phase liq...

A knowledge-based expert rule system for predicting mutagenicity (Ames test) of aromatic amines and azo compounds.

Toxicology
Cancer is one of the main causes of death in Western countries, and a major issue for human health. Prolonged exposure to a number of chemicals was observed to be one of the primary causes of cancer in occupationally exposed persons. Thus, the develo...

Machine Learning Prediction of the Energy Gap of Graphene Nanoflakes Using Topological Autocorrelation Vectors.

ACS combinatorial science
The possibility of band gap engineering in graphene opens countless new opportunities for application in nanoelectronics. In this work, the energy gaps of 622 computationally optimized graphene nanoflakes were mapped to topological autocorrelation ve...

ROCS-derived features for virtual screening.

Journal of computer-aided molecular design
Rapid overlay of chemical structures (ROCS) is a standard tool for the calculation of 3D shape and chemical ("color") similarity. ROCS uses unweighted sums to combine many aspects of similarity, yielding parameter-free models for virtual screening. I...

Molecular graph convolutions: moving beyond fingerprints.

Journal of computer-aided molecular design
Molecular "fingerprints" encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structur...

Developing a support vector machine based QSPR model for prediction of half-life of some herbicides.

Ecotoxicology and environmental safety
The half-life (t1/2) of 58 herbicides were modeled by quantitative structure-property relationship (QSPR) based molecular structure descriptors. After calculation and the screening of a large number of molecular descriptors, the most relevant those o...

Extending (Q)SARs to incorporate proprietary knowledge for regulatory purposes: A case study using aromatic amine mutagenicity.

Regulatory toxicology and pharmacology : RTP
Statistical-based and expert rule-based models built using public domain mutagenicity knowledge and data are routinely used for computational (Q)SAR assessments of pharmaceutical impurities in line with the approach recommended in the ICH M7 guidelin...

Structure-response relationship in electrospray ionization-mass spectrometry of sartans by artificial neural networks.

Journal of chromatography. A
Quantitative structure-property relationship (QSPR) methods are based on the hypothesis that changes in the molecular structure are reflected in changes in the observed property of the molecule. Artificial neural network is a technique of data analys...