Scopy
fixed mistake in ro5
Scopy ( crenning co mpounds in py thon), perpustakaan python desain negatif terintegrasi yang dirancang untuk menyaring senyawa yang tidak diinginkan dalam penemuan obat awal. Scopy mencakup enam modul, mencakup persiapan data , filter skrining , perhitungan perancah dan deskriptor , dan analisis visualisasi .
>>> conda install -c conda-forge rdkit
Scopy telah berhasil diuji pada sistem Linux, OSX dan Windows di bawah lingkungan Python3.
>>> git clone [email protected]:kotori-y/Scopy.git && cd scopy
>>> [sudo] python setup.py install
>>> conda install -c kotori_y scopy
>>> pip install scopy
(1) Versi online dari dokumentasi tersedia di sini: https://scopy.iamkotori.com/
(2) Contoh Mulai Cepat: https://scopy.iamkotori.com/user_guide.html
(3) Contoh aplikasi (pipa): https://scopy.iamkotori.com/application.html
Jika Anda memiliki pertanyaan atau saran, silakan hubungi: [email protected], dan [email protected].
Silakan lihat lisensi file untuk detail tentang lisensi "MIT" yang mencakup perangkat lunak ini dan data serta dokumen terkait.
Yang Zy, Yang ZJ, Lu AP, Hou TJ, Cao DS. Scopy: Perpustakaan Python desain negatif terintegrasi untuk desain database HTS/VS yang diinginkan [diterbitkan secara online di depan cetak, 2020 Sep 7]. Bioinform singkat . 2020; BBAA194. doi: 10.1093/bib/bbaa194
@article{10.1093/bib/bbaa194,
author = {Yang, Zi-Yi and Yang, Zhi-Jiang and Lu, Ai-Ping and Hou, Ting-Jun and Cao, Dong-Sheng},
title = "{Scopy: an integrated negative design python library for desirable HTS/VS database design}",
journal = {Briefings in Bioinformatics},
year = {2020},
month = {09},
abstract = "{High-throughput screening (HTS) and virtual screening (VS) have been widely used to identify potential hits from large chemical libraries. However, the frequent occurrence of ‘noisy compounds’ in the screened libraries, such as compounds with poor drug-likeness, poor selectivity or potential toxicity, has greatly weakened the enrichment capability of HTS and VS campaigns. Therefore, the development of comprehensive and credible tools to detect noisy compounds from chemical libraries is urgently needed in early stages of drug discovery.In this study, we developed a freely available integrated python library for negative design, called Scopy, which supports the functions of data preparation, calculation of descriptors, scaffolds and screening filters, and data visualization. The current version of Scopy can calculate 39 basic molecular properties, 3 comprehensive molecular evaluation scores, 2 types of molecular scaffolds, 6 types of substructure descriptors and 2 types of fingerprints. A number of important screening rules are also provided by Scopy, including 15 drug-likeness rules (13 drug-likeness rules and 2 building block rules), 8 frequent hitter rules (four assay interference substructure filters and four promiscuous compound substructure filters), and 11 toxicophore filters (five human-related toxicity substructure filters, three environment-related toxicity substructure filters and three comprehensive toxicity substructure filters). Moreover, this library supports four different visualization functions to help users to gain a better understanding of the screened data, including basic feature radar chart, feature-feature-related scatter diagram, functional group marker gram and cloud gram.Scopy provides a comprehensive Python package to filter out compounds with undesirable properties or substructures, which will benefit the design of high-quality chemical libraries for drug design and discovery. It is freely available at https://github.com/kotori-y/Scopy.}",
issn = {1477-4054},
doi = {10.1093/bib/bbaa194},
url = {https://doi.org/10.1093/bib/bbaa194},
note = {bbaa194},
eprint = {https://academic.oup.com/bib/advance-article-pdf/doi/10.1093/bib/bbaa194/33719387/bbaa194.pdf},
}
Terima kasih kepada kolega saya, Ziyi, karena telah membantu saya menyelesaikan penulisan dokumen dan artikel.
