Literature DB >> 19719121

No electron left behind: a rule-based expert system to predict chemical reactions and reaction mechanisms.

Jonathan H Chen1, Pierre Baldi.   

Abstract

Predicting the course and major products of arbitrary reactions is a fundamental problem in chemistry, one that chemists must address in a variety of tasks ranging from synthesis design to reaction discovery. Described here is an expert system to predict organic chemical reactions based on a knowledge base of over 1500 manually composed reaction transformation rules. Novel rule extensions are introduced to enable robust predictions and describe detailed reaction mechanisms at the level of electron flows in elementary reaction steps, ensuring that all reactions are properly balanced and atom-mapped. The core reaction prediction functionalities of this expert system are illustrated with applications including: (1) prediction of detailed reaction mechanisms; (2) computer-based learning in organic chemistry; (3) retrosynthetic analysis; and (4) combinatorial library design. Select applications are available via http://cdb.ics.uci.edu.

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Mesh:

Year:  2009        PMID: 19719121      PMCID: PMC2758223          DOI: 10.1021/ci900157k

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


  12 in total

1.  Simulation of organic reactions: from the degradation of chemicals to combinatorial synthesis

Authors: 
Journal:  J Chem Inf Comput Sci       Date:  2000-03

2.  A graph-based toy model of chemistry.

Authors:  Gil Benkö; Christoph Flamm; Peter F Stadler
Journal:  J Chem Inf Comput Sci       Date:  2003 Jul-Aug

Review 3.  Computer-aided organic synthesis.

Authors:  Matthew H Todd
Journal:  Chem Soc Rev       Date:  2005-02-08       Impact factor: 54.564

4.  Rapid evaluation of synthetic and molecular complexity for in silico chemistry.

Authors:  Tharun Kumar Allu; Tudor I Oprea
Journal:  J Chem Inf Model       Date:  2005 Sep-Oct       Impact factor: 4.956

5.  ROBIA: a reaction prediction program.

Authors:  Ingrid M Socorro; Keith Taylor; Jonathan M Goodman
Journal:  Org Lett       Date:  2005-08-04       Impact factor: 6.005

6.  Virtual exploration of the chemical universe up to 11 atoms of C, N, O, F: assembly of 26.4 million structures (110.9 million stereoisomers) and analysis for new ring systems, stereochemistry, physicochemical properties, compound classes, and drug discovery.

Authors:  Tobias Fink; Jean-Louis Reymond
Journal:  J Chem Inf Model       Date:  2007-01-30       Impact factor: 4.956

7.  ChemDB update--full-text search and virtual chemical space.

Authors:  Jonathan H Chen; Erik Linstead; S Joshua Swamidass; Dennis Wang; Pierre Baldi
Journal:  Bioinformatics       Date:  2007-06-28       Impact factor: 6.937

8.  Route Designer: a retrosynthetic analysis tool utilizing automated retrosynthetic rule generation.

Authors:  James Law; Zsolt Zsoldos; Aniko Simon; Darryl Reid; Yang Liu; Sing Yoong Khew; A Peter Johnson; Sarah Major; Robert A Wade; Howard Y Ando
Journal:  J Chem Inf Model       Date:  2009-03       Impact factor: 4.956

Review 9.  Recent trends in library design: 'rational design' revisited.

Authors:  Dora M Schnur
Journal:  Curr Opin Drug Discov Devel       Date:  2008-05

10.  Computer-assisted analysis in organic synthesis.

Authors:  E J Corey; A K Long; S D Rubenstein
Journal:  Science       Date:  1985-04-26       Impact factor: 47.728

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  9 in total

1.  Learning to predict chemical reactions.

Authors:  Matthew A Kayala; Chloé-Agathe Azencott; Jonathan H Chen; Pierre Baldi
Journal:  J Chem Inf Model       Date:  2011-09-02       Impact factor: 4.956

2.  Toward Automated Inventory Modeling in Life Cycle Assessment: The Utility of Semantic Data Modeling to Predict Real-World Chemical Production.

Authors:  Vinit K Mittal; Sidney C Bailin; Michael A Gonzalez; David E Meyer; William M Barrett; Raymond L Smith
Journal:  ACS Sustain Chem Eng       Date:  2017-12-06       Impact factor: 8.198

Review 3.  Automating drug discovery.

Authors:  Gisbert Schneider
Journal:  Nat Rev Drug Discov       Date:  2017-12-15       Impact factor: 84.694

4.  Learning To Predict Reaction Conditions: Relationships between Solvent, Molecular Structure, and Catalyst.

Authors:  Eric Walker; Joshua Kammeraad; Jonathan Goetz; Michael T Robo; Ambuj Tewari; Paul M Zimmerman
Journal:  J Chem Inf Model       Date:  2019-08-19       Impact factor: 4.956

5.  COBRA: a computational brewing application for predicting the molecular composition of organic aerosols.

Authors:  David R Fooshee; Tran B Nguyen; Sergey A Nizkorodov; Julia Laskin; Alexander Laskin; Pierre Baldi
Journal:  Environ Sci Technol       Date:  2012-05-18       Impact factor: 9.028

6.  Alternative methods of processing bio-feedstocks in formulated consumer product design.

Authors:  Nicolai Peremezhney; Philipp-Maximilian Jacob; Alexei Lapkin
Journal:  Front Chem       Date:  2014-05-13       Impact factor: 5.221

7.  Neural Networks for the Prediction of Organic Chemistry Reactions.

Authors:  Jennifer N Wei; David Duvenaud; Alán Aspuru-Guzik
Journal:  ACS Cent Sci       Date:  2016-10-14       Impact factor: 14.553

8.  Efficient prediction of reaction paths through molecular graph and reaction network analysis.

Authors:  Yeonjoon Kim; Jin Woo Kim; Zeehyo Kim; Woo Youn Kim
Journal:  Chem Sci       Date:  2017-12-12       Impact factor: 9.825

9.  Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models.

Authors:  Bowen Liu; Bharath Ramsundar; Prasad Kawthekar; Jade Shi; Joseph Gomes; Quang Luu Nguyen; Stephen Ho; Jack Sloane; Paul Wender; Vijay Pande
Journal:  ACS Cent Sci       Date:  2017-09-05       Impact factor: 18.728

  9 in total

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