Slice'N'Dice: maximizing the value of predicted models for structural biologists.


Simpkin, Adam J ORCID: 0000-0003-1883-9376, Elliot, Luc G, Joseph, Agnel Praveen, Burnley, Tom ORCID: 0000-0001-5307-348X, Stevenson, Kyle, Sánchez Rodríguez, Filomeno, Fando, Maria, Krissinel, Eugene ORCID: 0000-0003-1267-7185, McNicholas, Stuart, Rigden, Daniel J ORCID: 0000-0002-7565-8937 et al (show 1 more authors) (2025) Slice'N'Dice: maximizing the value of predicted models for structural biologists. Acta crystallographica. Section D, Structural biology, 81 (Pt 3). pp. 105-121. ISSN 2059-7983, 2059-7983

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Abstract

With the advent of next-generation modelling methods, such as AlphaFold2, structural biologists are increasingly using predicted structures to obtain structure solutions via molecular replacement (MR) or model fitting in single-particle cryogenic sample electron microscopy (cryoEM). Differences between the domain-domain orientations represented in a predicted model and a crystal structure are often a key limitation when using predicted models. Slice'N'Dice is a software package designed to address this issue by first slicing models into distinct structural units and then automatically placing the slices using either Phaser, MOLREP or PowerFit. The slicing step can use the AlphaFold predicted aligned error (PAE) or can operate via a variety of C<sup>α</sup>-atom-based clustering algorithms, extending the applicability to structures of any origin. The number of splits can either be selected by the user or determined automatically. Slice'N'Dice is available for both MR and automated map fitting in the CCP4 and CCP-EM software suites.

Item Type: Article
Uncontrolled Keywords: Proteins, Cryoelectron Microscopy, Protein Conformation, Algorithms, Models, Molecular, Software
Divisions: Faculty of Health and Life Sciences
Faculty of Health and Life Sciences > Institute of Systems, Molecular and Integrative Biology
Depositing User: Symplectic Admin
Date Deposited: 24 Apr 2025 08:46
Last Modified: 20 May 2025 17:14
DOI: 10.1107/s2059798325001251
Open Access URL: https://doi.org/10.1107/S2059798325001251
Related Websites:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3191578
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