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BuildAMol: a versatile Python toolkit for fragment-based molecular design.
- Source :
-
Journal of Cheminformatics . 8/25/2024, Vol. 16 Issue 1, p1-13. 13p. - Publication Year :
- 2024
-
Abstract
- In recent years computational methods for molecular modeling have become a prime focus of computational biology and cheminformatics. Many dedicated systems exist for modeling specific classes of molecules such as proteins or small drug-like ligands. These are often heavily tailored toward the automated generation of molecular structures based on some meta-input by the user and are not intended for expert-driven structure assembly. Dedicated manual or semi-automated assembly software tools exist for a variety of molecule classes but are limited in the scope of structures they can produce. In this work we present BuildAMol, a highly flexible and extendable, general-purpose fragment-based molecular assembly toolkit. Written in Python and featuring a well-documented, user-friendly API, BuildAMol empowers researchers with a framework for detailed manual or semi-automated construction of diverse molecular models. Unlike specialized software, BuildAMol caters to a broad range of applications. We demonstrate its versatility across various use cases, encompassing generating metal complexes or the modeling of dendrimers or integrated into a drug discovery pipeline. By providing a robust foundation for expert-driven model building, BuildAMol holds promise as a valuable tool for the continuous integration and advancement of powerful deep learning techniques. Scientific contribution BuildAMol introduces a cutting-edge framework for molecular modeling that seamlessly blends versatility with user-friendly accessibility. This innovative toolkit integrates modeling, modification, optimization, and visualization functions within a unified API, and facilitates collaboration with other cheminformatics libraries. BuildAMol, with its shallow learning curve, serves as a versatile tool for various molecular applications while also laying the groundwork for the development of specialized software tools, contributing to the progress of molecular research and innovation. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 17582946
- Volume :
- 16
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Journal of Cheminformatics
- Publication Type :
- Academic Journal
- Accession number :
- 179257740
- Full Text :
- https://doi.org/10.1186/s13321-024-00900-6