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A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Biophysics".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 7664

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Special Issue Editor

Dr. Dominik Gront

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Guest Editor

Biological and Chemical Research Center, Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland
Interests: molecular simulations; coarse-grained modeling

Special Issue Information

Dear Colleagues,

In this Special Issue, we focus on the latest developments in the fields of protein structure prediction and design. Protein structure prediction is a branch of research with a rich history spanning four decades. The great progress made in this field has also greatly influenced the field of computational protein design. In fact, the two fields are tightly connected as they are based on the same principles and share similar methods, algorithms, and software.

In recent years, we witnessed unprecedented progress in the successful application of machine learning methods in the field of protein structure prediction with the development of several methods, such as the AlphaFold, trRosetta, or RoseTTAFold methods. Therefore, some of these topics will be dedicated to the application of deep learning in structure prediction and design. The most recent advances in other key parts of the methodology (such as force fields and algorithms) will also be discussed.

As the Guest Editor of this Special Issue of IJMS, entitled “Advances in the Protein Structure Prediction and Design”, we welcome you to contribute a paper on the topic of protein structures.

Dr. Dominik Gront
Guest Editor

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Keywords

protein design
protein structure prediction
learning in protein engineering

Published Papers (3 papers)

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Research

31 pages, 10968 KiB

Open AccessArticle

Quantum Entanglement and State-Transference in Fenna–Matthews–Olson Complexes: A Post-Experimental Simulation Analysis in the Computational Biology Domain

by Francisco Delgado and Marco Enríquez

Int. J. Mol. Sci. 2023, 24(13), 10862; https://doi.org/10.3390/ijms241310862 - 29 Jun 2023

Cited by 1 | Viewed by 986

Abstract

Fenna-Mathews-Olson complexes participate in the photosynthetic process of Sulfur Green Bacteria. These biological subsystems exhibit quantum features which possibly are responsible for their high efficiency; the latter may comprise multipartite entanglement and the apparent tunnelling of the initial quantum state. At first, to study these aspects, a multidisciplinary approach including experimental biology, spectroscopy, physics, and math modelling is required. Then, a global computer modelling analysis is achieved in the computational biology domain. The current work implements the Hierarchical Equations of Motion to numerically solve the open quantum system problem regarding this complex. The time-evolved states obtained with this method are then analysed under several measures of entanglement, some of them already proposed in the literature. However, for the first time, the maximum overlap with respect to the closest separable state is employed. This authentic multipartite entanglement measure provides information on the correlations, not only based on the system bipartitions as in the usual analysis. Our study has led us to note a different view of FMO multipartite entanglement as tiny contributions to the global entanglement suggested by other more basic measurements. Additionally, in another related trend, the initial state, considered as a Förster Resonance Energy Transfer, is tracked using a novel approach, considering how it could be followed under the fidelity measure on all possible permutations of the FMO subsystems through its dynamical evolution by observing the tunnelling in the most probable locations. Both analyses demanded significant computational work, making for a clear example of the complexity required in computational biology. Full article

(This article belongs to the Special Issue The Research about Structural and Computational Biology)

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15 pages, 5684 KiB

Open AccessArticle

Structural Insight into the Working Mechanism of the FAD Synthetase from the Human Pathogen Streptococcus pneumoniae: A Molecular Docking Simulation Study

by Sunghark Kwon

Int. J. Mol. Sci. 2023, 24(4), 3121; https://doi.org/10.3390/ijms24043121 - 4 Feb 2023

Cited by 1 | Viewed by 1338

Abstract

Flavin adenine dinucleotide synthetases (FADSs) catalyze FAD biosynthesis through two consecutive catalytic reactions, riboflavin (RF) phosphorylation and flavin mononucleotide (FMN) adenylylation. Bacterial FADSs have RF kinase (RFK) and FMN adenylyltransferase (FMNAT) domains, whereas the two domains are separated into two independent enzymes in human FADSs. Bacterial FADSs have attracted considerable attention as drug targets due to the fact that they differ from human FADSs in structure and domain combinations. In this study, we analyzed the putative FADS structure from the human pathogen Streptococcus pneumoniae (SpFADS) determined by Kim et al., including conformational changes of key loops in the RFK domain upon substrate binding. Structural analysis and comparisons with a homologous FADS structure revealed that SpFADS corresponds to a hybrid between open and closed conformations of the key loops. Surface analysis of SpFADS further revealed its unique biophysical properties for substrate attraction. In addition, our molecular docking simulations predicted possible substrate-binding modes at the active sites of the RFK and FMNAT domains. Our results provide a structural basis to understand the catalytic mechanism of SpFADS and develop novel SpFADS inhibitors. Full article

(This article belongs to the Special Issue The Research about Structural and Computational Biology)

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34 pages, 5753 KiB

Open AccessArticle

Using Alphafold2 to Predict the Structure of the Gp5/M Dimer of Porcine Respiratory and Reproductive Syndrome Virus

by Michael Veit, Mohamed Rasheed Gadalla and Minze Zhang

Int. J. Mol. Sci. 2022, 23(21), 13209; https://doi.org/10.3390/ijms232113209 - 30 Oct 2022

Cited by 3 | Viewed by 4755

Abstract

Porcine reproductive and respiratory syndrome virus is a positive-stranded RNA virus of the family Arteriviridae. The Gp5/M dimer, the major component of the viral envelope, is required for virus budding and is an antibody target. We used alphafold2, an artificial-intelligence-based system, to predict a credible structure of Gp5/M. The short disulfide-linked ectodomains lie flat on the membrane, with the exception of the erected N-terminal helix of Gp5, which contains the antibody epitopes and a hypervariable region with a changing number of carbohydrates. The core of the dimer consists of six curved and tilted transmembrane helices, and three are from each protein. The third transmembrane regions extend into the cytoplasm as amphiphilic helices containing the acylation sites. The endodomains of Gp5 and M are composed of seven β-strands from each protein, which interact via β-strand seven. The area under the membrane forms an open cavity with a positive surface charge. The M and Orf3a proteins of coronaviruses have a similar structure, suggesting that all four proteins are derived from the same ancestral gene. Orf3a, like Gp5/M, is acylated at membrane-proximal cysteines. The role of Gp5/M during virus replication is discussed, in particular the mechanisms of virus budding and models of antibody-dependent virus neutralization. Full article

(This article belongs to the Special Issue The Research about Structural and Computational Biology)

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