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JRgui: A Python Program of Joback and Reid Method.
Shi, Chenyang; Borchardt, Thomas B.
Afiliação
  • Shi C; Drug Product Development, AbbVie, 1 North Waukegan Road, North Chicago, Illinois 60064, United States.
  • Borchardt TB; Drug Product Development, AbbVie, 1 North Waukegan Road, North Chicago, Illinois 60064, United States.
ACS Omega ; 2(12): 8682-8688, 2017 Dec 31.
Article em En | MEDLINE | ID: mdl-31457399
ABSTRACT
Using the modern object-oriented programing language Python (e.g., tkinter and pandas modules) and a chemoinformatics open-source library (RDKit), the classic Joback and Reid group contribution method was revisited and written into a graphical user interface program, JRgui. The underlying algorithm behind the program is explained, herein, with the users being able to operate the program in either a manual or automatic mode. In the manual mode, the users are required to determine the type and occurrence of functional groups in the compound of interest and manually enter into the program. In the automatic mode, both of these parameters can be detected automatically via user input of the compound simplified molecular input line entry specification (SMILES) string. An additional advantage of the automatic mode is that a large number of molecules can be processed simultaneously by parsing their individual SMILES strings into a text file, which is read by the program. The resulting predicted physical properties along with approximately 200 molecular descriptors are saved in a spreadsheet file for subsequent analysis. The program is available for free at https//github.com/curieshicy/JRgui for Windows, Linux, and macOS 64-bit operating systems. It is hoped that the current work may facilitate the creation of other user-friendly programs in the chemoinformatics community using Python.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: ACS Omega Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: ACS Omega Ano de publicação: 2017 Tipo de documento: Article