{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/pyscreener-a-python-wrapper-for-computational","title":"pyscreener: A Python Wrapper for Computational Docking Software","arxiv_id":"2112.10575","date":"2021-12-17","proceeding":null,"authors":["David E. Graff","Connor W. Coley"],"abstract":"pyscreener is a Python library that seeks to alleviate the challenges of large-scale structure-based design using computational docking. It provides a simple and uniform interface that is agnostic to the backend docking engine with which to calculate the docking score of a given molecule in a specified active site. Additionally, pyscreener features first-class support for task distribution, allowing users to seamlessly scale their code from a local, multi-core setup to a large, heterogeneous resource allocation.","url_abs":"https://arxiv.org/abs/2112.10575v1","url_pdf":"https://arxiv.org/pdf/2112.10575v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"pyscreener-a-python-wrapper-for-computational","repo_url":"https://github.com/coleygroup/pyscreener","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}