Document Type

Article

Publication Date

2024

DOI

10.1093/bioadv/vbae181

Publication Title

Bioinformatics Advances

Volume

Article in Press

Pages

vbae181 (1-11)

Abstract

Motivation: This study investigates the flexible refinement of AlphaFold2 models against corresponding cryo-electron microscopy (cryo-EM) maps using normal modes derived from elastic network models (ENMs) as basis functions for displacement. AlphaFold2 generally predicts highly accurate structures, but 18 of the 137 models of isolated chains exhibit a TM-score below 0.80. We achieved a significant improvement in four of these deviating structures and used them to systematically optimize the parameters of the ENM motion model.

Results: We successfully refined four AlphaFold2 models with notable discrepancies: lipid-preserved respiratory supercomplex (TM-score increased from 0.52 to 0.69), flagellar L-ring protein (TM-score increased from 0.53 to 0.64), cation diffusion facilitator YiiP (TM-score increased from 0.76 to 0.83), and Sulfolobus islandicus pilus (TM-score increased from 0.77 to 0.85). We explored the effect of three different mode ranges (modes 1–9, 7–9, and 1–12), masked or box-cropped density maps, numerical optimization methods, and two similarity measures (Pearson correlation and inner product). The best results were achieved for the widest mode range (modes 1–12), masked maps, inner product, and local Powell optimization. These optimal parameters were implemented in the flexible fitting utility elforge.py in version 1.4 of our Python-based ModeHunter package.

Availability: https://modehunter.biomachina.org.

Rights

© The Author(s) 2024.

This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License, which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Data Availability

Article states: "The source of ModeHunter can be freely downloaded at https://modehunter.biomachina.org in ModeHunter version 1.4."

Original Publication Citation

Alshammari, M., He, J., & Wriggers, W. (2024). Flexible fitting of AlphaFold2-predicted models to cryo-EM density maps using elastic network models: A methodical affirmation. Bioinformatics Advances. Advance online publication. https://doi.org/10.1093/bioadv/vbae181

ORCID

0000-0002-1386-5447 (Alshammari), 0000-0001-5326-3152 (Wriggers)

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