Literature DB >> 25420000

Prediction of synthetic accessibility based on commercially available compound databases.

Yoshifumi Fukunishi1, Takashi Kurosawa, Yoshiaki Mikami, Haruki Nakamura.   

Abstract

A compound's synthetic accessibility (SA) is an important aspect of drug design, since in some cases computer-designed compounds cannot be synthesized. There have been several reports on SA prediction, most of which have focused on the difficulties of synthetic reactions based on retro-synthesis analyses, reaction databases and the availability of starting materials. We developed a new method of predicting SA using commercially available compound databases and molecular descriptors. SA was estimated from the probability of existence of substructures consisting of the compound in question, the number of symmetry atoms, the graph complexity, and the number of chiral centers of the compound. The probabilities of the existence of given substructures were estimated based on a compound library. The predicted SA results reproduced the expert manual assessments with a Pearson correlation coefficient of 0.56. Since our method required a compound database and not a reaction database, it should be easy to customize the prediction for compound vendors. The correlation between the sales price of approved drugs and the SA values was also examined and found to be weak. The price most likely depends on the total cost of development and other factors.

Entities:  

Mesh:

Year:  2014        PMID: 25420000     DOI: 10.1021/ci500568d

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


  14 in total

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2.  SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules.

Authors:  Antoine Daina; Olivier Michielin; Vincent Zoete
Journal:  Sci Rep       Date:  2017-03-03       Impact factor: 4.379

3.  Nonpher: computational method for design of hard-to-synthesize structures.

Authors:  Milan Voršilák; Daniel Svozil
Journal:  J Cheminform       Date:  2017-03-20       Impact factor: 5.514

4.  Pushing the Ligand Efficiency Metrics: Relative Group Contribution (RGC) Model as a Helpful Strategy to Promote a Fragment "Rescue" Effect.

Authors:  Andrés Felipe Vásquez; Andrés González Barrios
Journal:  Front Chem       Date:  2019-08-16       Impact factor: 5.221

5.  SYBA: Bayesian estimation of synthetic accessibility of organic compounds.

Authors:  Milan Voršilák; Michal Kolář; Ivan Čmelo; Daniel Svozil
Journal:  J Cheminform       Date:  2020-05-20       Impact factor: 5.514

6.  Profiling and analysis of chemical compounds using pointwise mutual information.

Authors:  I Čmelo; M Voršilák; D Svozil
Journal:  J Cheminform       Date:  2021-01-10       Impact factor: 5.514

Review 7.  In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery.

Authors:  Lauro Ribeiro de Souza Neto; José Teófilo Moreira-Filho; Bruno Junior Neves; Rocío Lucía Beatriz Riveros Maidana; Ana Carolina Ramos Guimarães; Nicholas Furnham; Carolina Horta Andrade; Floriano Paes Silva
Journal:  Front Chem       Date:  2020-02-18       Impact factor: 5.221

8.  Computational Structure-Based De Novo Design of Hypothetical Inhibitors against the Anti- Inflammatory Target COX-2.

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Journal:  PLoS One       Date:  2015-08-04       Impact factor: 3.240

Review 9.  Miscellaneous Topics in Computer-Aided Drug Design: Synthetic Accessibility and GPU Computing, and Other Topics.

Authors:  Yoshifumi Fukunishi; Tadaaki Mashimo; Kiyotaka Misoo; Yoshinori Wakabayashi; Toshiaki Miyaki; Seiji Ohta; Mayu Nakamura; Kazuyoshi Ikeda
Journal:  Curr Pharm Des       Date:  2016       Impact factor: 3.116

10.  SAVI, in silico generation of billions of easily synthesizable compounds through expert-system type rules.

Authors:  Hitesh Patel; Wolf-Dietrich Ihlenfeldt; Philip N Judson; Yurii S Moroz; Yuri Pevzner; Megan L Peach; Victorien Delannée; Nadya I Tarasova; Marc C Nicklaus
Journal:  Sci Data       Date:  2020-11-11       Impact factor: 6.444

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