PySmash: Python package and individual executable program for representative substructure generation and application

Zi-Yi Yang; Zhi-Jiang Yang; Yue Zhao; Ming-Zhu Yin; Ai-Ping Lu; Xiang Chen; Shao Liu; Ting-Jun Hou; Dong-Sheng Cao

doi:10.1093/bib/bbab017

PySmash: Python package and individual executable program for representative substructure generation and application

Brief Bioinform. 2021 Sep 2;22(5):bbab017. doi: 10.1093/bib/bbab017.

Authors

Zi-Yi Yang¹, Zhi-Jiang Yang², Yue Zhao³, Ming-Zhu Yin⁴, Ai-Ping Lu⁵, Xiang Chen⁴, Shao Liu⁶, Ting-Jun Hou⁷, Dong-Sheng Cao⁸

Affiliations

¹ Department of Pharmacy, Xiangya Hospital, Central South University and the Xiangya School of Pharmaceutical Sciences, Central South University, Sichuan, China.
² Xiangya School of Pharmaceutical Sciences, Central South University, Hunan, China.
³ Xiangya School of Pharmaceutical Sciences, Central South University (Changsha), Sichuan, China.
⁴ Department of Dermatology, Hunan Engineering Research Center of Skin Health and Disease, Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Hunan.
⁵ Institute for Advancing Translational Medicine in Bone and Joint Diseases, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong.
⁶ Department of Pharmacy, Xiangya Hospital, Central South University, Hunan.
⁷ College of Pharmaceutical Sciences, Zhejiang University, China.
⁸ Xiangya School of Pharmaceutical Sciences, Central South University, China.

PMID: 33709154
DOI: 10.1093/bib/bbab017

Abstract

Background: Substructure screening is widely applied to evaluate the molecular potency and ADMET properties of compounds in drug discovery pipelines, and it can also be used to interpret QSAR models for the design of new compounds with desirable physicochemical and biological properties. With the continuous accumulation of more experimental data, data-driven computational systems which can derive representative substructures from large chemical libraries attract more attention. Therefore, the development of an integrated and convenient tool to generate and implement representative substructures is urgently needed.

Results: In this study, PySmash, a user-friendly and powerful tool to generate different types of representative substructures, was developed. The current version of PySmash provides both a Python package and an individual executable program, which achieves ease of operation and pipeline integration. Three types of substructure generation algorithms, including circular, path-based and functional group-based algorithms, are provided. Users can conveniently customize their own requirements for substructure size, accuracy and coverage, statistical significance and parallel computation during execution. Besides, PySmash provides the function for external data screening.

Conclusion: PySmash, a user-friendly and integrated tool for the automatic generation and implementation of representative substructures, is presented. Three screening examples, including toxicophore derivation, privileged motif detection and the integration of substructures with machine learning (ML) models, are provided to illustrate the utility of PySmash in safety profile evaluation, therapeutic activity exploration and molecular optimization, respectively. Its executable program and Python package are available at https://github.com/kotori-y/pySmash.

Keywords: ADMET; Python package; QSAR; software; substructure screening.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Carcinogenicity Tests / methods
Carcinogens
Computational Biology / methods*
Drug Discovery / methods*
Drug Screening Assays, Antitumor / methods
Humans
Machine Learning*
Software*

Substances

Carcinogens