Treffer: molli: A General Purpose Python Toolkit for Combinatorial Small Molecule Library Generation, Manipulation, and Feature Extraction.

Title:
molli: A General Purpose Python Toolkit for Combinatorial Small Molecule Library Generation, Manipulation, and Feature Extraction.
Authors:
Shved AS; Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States., Ocampo BE; Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States., Burlova ES; Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States., Olen CL; Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States., Rinehart NI; Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States., Denmark SE; Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.
Source:
Journal of chemical information and modeling [J Chem Inf Model] 2024 Nov 11; Vol. 64 (21), pp. 8083-8090. Date of Electronic Publication: 2024 Oct 23.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: American Chemical Society Country of Publication: United States NLM ID: 101230060 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1549-960X (Electronic) Linking ISSN: 15499596 NLM ISO Abbreviation: J Chem Inf Model Subsets: MEDLINE
Imprint Name(s):
Original Publication: Washington, D.C. : American Chemical Society, c2005-
Substance Nomenclature:
0 (Small Molecule Libraries)
Entry Date(s):
Date Created: 20241023 Date Completed: 20241111 Latest Revision: 20241111
Update Code:
20250114
DOI:
10.1021/acs.jcim.4c00424
PMID:
39441186
Database:
MEDLINE

Weitere Informationen

The construction, management, and analysis of large in silico molecular libraries is critical in many areas of modern chemistry. Herein, we introduce the MOLecular LIibrary toolkit, "molli", which is a Python 3 cheminformatics module that provides a streamlined interface for manipulating large in silico libraries. Three-dimensional, combinatorial molecule libraries can be expanded directly from two-dimensional chemical structure fragments stored in CDXML files with high stereochemical fidelity. Geometry optimization, property calculation, and conformer generation are executed by interfacing with widely used computational chemistry programs such as OpenBabel, RDKit, ORCA, NWChem, and xTB/CREST. Conformer-dependent grid-based feature calculators provide numerical representation and interface to robust three-dimensional visualization tools that provide comprehensive images to enhance human understanding of libraries with thousands of members. The package includes a command-line interface in addition to Python classes to streamline frequently used workflows. Parallel performance is benchmarked on various hardware platforms, and common workflows are demonstrated for different tasks ranging from optimized grid-based descriptor calculation on catalyst libraries to an NMR chemical shift prediction workflow from CDXML files.