Evidence map›Paper›PMID 40165823›Full record

ArticleComputational and structural biotechnology journal2025

Structural elucidation of four fungal hydrophobins belonging to classes I and II: Results from Alphafold and accelerated molecular dynamics simulations.

Derrick Agwora, Bonaya Gufu, Tamás Marik, Tamás Papp, Csaba Vágvölgyi, László Kredics, Chetna Tyagi

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Article in Computational and structural biotechnology journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 · Its place in the literature

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3 citing papers in PubMed.

  1. Article
  2. Article
  3. AlphaFold in protein structure and function prediction.Computational and structural biotechnology journal · 2025
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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Derrick AgworaDepartment of Biotechnology and Microbiology, Faculty of Science and Informatics, University of Szeged, Szeged, Hungary.
Bonaya GufuDepartment of Biotechnology and Microbiology, Faculty of Science and Informatics, University of Szeged, Szeged, Hungary.
Tamás MarikDepartment of Biotechnology and Microbiology, Faculty of Science and Informatics, University of Szeged, Szeged, Hungary.
Tamás PappDepartment of Biotechnology and Microbiology, Faculty of Science and Informatics, University of Szeged, Szeged, Hungary.
Csaba VágvölgyiDepartment of Biotechnology and Microbiology, Faculty of Science and Informatics, University of Szeged, Szeged, Hungary.
László KredicsDepartment of Biotechnology and Microbiology, Faculty of Science and Informatics, University of Szeged, Szeged, Hungary.
Chetna TyagiDepartment of Biotechnology and Microbiology, Faculty of Science and Informatics, University of Szeged, Szeged, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hydrophobins (HFB) find application in various industries including biotechnology and medical devices; therefore, it is imperative to elucidate and learn more about their folded structures. Few fungal HFB protein structures are available in the Protein Data Bank (PDB), and fewer have been elucidated using homology modeling or short molecular dynamics (MD) simulations in the literature. Moreover, many homology modeling algorithms will only model the region with sequence identity. Therefore, we turned towards the state-of-the-art, artificial intelligence powered AlphaFold. It performed well in predicting the core β-barrel, a characteristic of HFBs, except for HFB9A which was unfolded with low confidence scores. These initial structures were then prepared for accelerated MD simulation in the hope of observing higher protein folding. With 500 ns long aMD simulations, we were able to obtain folded and energetically stable conformations for all the proteins except HFB9A, which exhibited much higher disorder, connected with higher atomic fluctuation, lowest hydrophobicity and overall compactness, and lesser secondary structure formation as visualized during the aMD simulation. The underlying intrinsic disorder in the HFBs was found to be the basis of harder-to-reach folding by AF2 which can be compensated by enhanced sampling MD simulations like the aMD technique. The characteristic two disordered loops of class I HFBs were obtained for SC3, while HFB9A showed that not all class I HFBs contain them. Class II HFBs were more stable, folded and compact with secondary structure motifs conserved throughout the trajectory which can be correlated with their comparatively much lower intrinsic disorder.

Indexed as

Accelerated molecular dynamics simulationsAlphaFoldDisorderHydrophobins

Identifiers

PMID40165823
PMCPMC11957597

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