JRgui: A Python Program of Joback and Reid Method
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...
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| Veröffentlicht in: | ACS omega Jg. 2; H. 12; S. 8682 - 8688 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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American Chemical Society
31.12.2017
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| ISSN: | 2470-1343, 2470-1343 |
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| 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. |
|---|---|
| AbstractList | 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. 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. Using the modern object-oriented programing language Python (e.g., and 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. 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.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. |
| Author | Shi, Chenyang Borchardt, Thomas B |
| AuthorAffiliation | Drug Product Development |
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| Author_xml | – sequence: 1 givenname: Chenyang orcidid: 0000-0002-2291-7325 surname: Shi fullname: Shi, Chenyang email: chenyang.shi@abbvie.com – sequence: 2 givenname: Thomas B surname: Borchardt fullname: Borchardt, Thomas B |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31457399$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1021_acs_jchemed_9b00818 crossref_primary_10_3389_fphar_2024_1441587 crossref_primary_10_3390_biom10101385 crossref_primary_10_1016_j_compbiomed_2022_105573 crossref_primary_10_3389_fmolb_2020_556481 crossref_primary_10_1002_minf_202300190 crossref_primary_10_3390_life11111140 crossref_primary_10_3390_metabo12030199 crossref_primary_10_1016_j_cej_2023_141952 crossref_primary_10_1016_j_molliq_2022_120620 crossref_primary_10_1007_s10953_018_0821_1 crossref_primary_10_1016_j_dt_2023_08_014 |
| Cites_doi | 10.1007/978-1-4020-6291-9 10.1021/ci400127q 10.1016/j.fluid.2006.11.014 10.1002/1520-6017(200102)90:2<234::AID-JPS14>3.0.CO;2-V 10.1016/S0378-3812(01)00431-9 10.1002/jps.2600690814 10.1021/ci990307l 10.1080/00986448708960487 10.1063/1.1744688 10.1002/aic.690300119 10.1002/jps.21494 10.1529/biophysj.107.124784 10.1021/ci0500132 10.1002/aic.690210607 10.1002/aic.690401011 10.1021/acs.jcim.5b00674 10.1021/acs.jcim.6b00654 |
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| Title | JRgui: A Python Program of Joback and Reid Method |
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