Literature DB >> 31063394

CGRtools: Python Library for Molecule, Reaction, and Condensed Graph of Reaction Processing.

Ramil I Nugmanov1, Ravil N Mukhametgaleev1, Tagir Akhmetshin1, Timur R Gimadiev1, Valentina A Afonina1, Timur I Madzhidov1, Alexandre Varnek2.   

Abstract

CGRtools is an open-source Python library aimed to handle molecular and reaction information. It is the sole library developed so far which can process condensed graph of reaction (CGR) handling. CGR provides the possibility for advanced operations with reaction information and could be used for reaction descriptor calculation, structure-reactivity modeling, atom-to-atom mapping comparison and correction, reaction center extraction, reaction balancing, and some other related tasks. Unlike other popular libraries, CGRtools is fully written in Python with minor dependencies on other libraries and cross-platform. Reaction, molecule, and CGR objects in CGRtools support native Python methods and are comparable with the help of operations "equal to", "less than", and "bigger than". CGRtools supports common structural formats. CGRtools is distributed via an L-GPL license and available on https://github.com/cimm-kzn/CGRtools .

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Year:  2019        PMID: 31063394     DOI: 10.1021/acs.jcim.9b00102

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  6 in total

1.  Molecular Scaffold Hopping via Holistic Molecular Representation.

Authors:  Francesca Grisoni; Gisbert Schneider
Journal:  Methods Mol Biol       Date:  2021

Review 2.  Molecular representations in AI-driven drug discovery: a review and practical guide.

Authors:  Laurianne David; Amol Thakkar; Rocío Mercado; Ola Engkvist
Journal:  J Cheminform       Date:  2020-09-17       Impact factor: 5.514

3.  Discovery of novel chemical reactions by deep generative recurrent neural network.

Authors:  William Bort; Igor I Baskin; Timur Gimadiev; Artem Mukanov; Ramil Nugmanov; Pavel Sidorov; Gilles Marcou; Dragos Horvath; Olga Klimchuk; Timur Madzhidov; Alexandre Varnek
Journal:  Sci Rep       Date:  2021-02-04       Impact factor: 4.379

4.  Prediction of Optimal Conditions of Hydrogenation Reaction Using the Likelihood Ranking Approach.

Authors:  Valentina A Afonina; Daniyar A Mazitov; Albina Nurmukhametova; Maxim D Shevelev; Dina A Khasanova; Ramil I Nugmanov; Vladimir A Burilov; Timur I Madzhidov; Alexandre Varnek
Journal:  Int J Mol Sci       Date:  2021-12-27       Impact factor: 5.923

Review 5.  Machine Learning of Reaction Properties via Learned Representations of the Condensed Graph of Reaction.

Authors:  Esther Heid; William H Green
Journal:  J Chem Inf Model       Date:  2021-11-04       Impact factor: 6.162

6.  Comprehensive Analysis of Applicability Domains of QSPR Models for Chemical Reactions.

Authors:  Assima Rakhimbekova; Timur I Madzhidov; Ramil I Nugmanov; Timur R Gimadiev; Igor I Baskin; Alexandre Varnek
Journal:  Int J Mol Sci       Date:  2020-08-03       Impact factor: 5.923

  6 in total

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