International Journal of Molecular Sciences

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18 pages, 5135 KiB

Open AccessArticle

Efficient Estimates of Surface Diffusion Parameters for Spatio-Temporally Resolved Virus Replication Dynamics

by Markus M. Knodel, Gabriel Wittum and Jürgen Vollmer

Int. J. Mol. Sci. 2024, 25(5), 2993; https://doi.org/10.3390/ijms25052993 - 5 Mar 2024

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Advanced methods of treatment are needed to fight the threats of virus-transmitted diseases and pandemics. Often, they are based on an improved biophysical understanding of virus replication strategies and processes in their host cells. For instance, an essential component of the replication of [...] Read more.

Advanced methods of treatment are needed to fight the threats of virus-transmitted diseases and pandemics. Often, they are based on an improved biophysical understanding of virus replication strategies and processes in their host cells. For instance, an essential component of the replication of the hepatitis C virus (HCV) proceeds under the influence of nonstructural HCV proteins (NSPs) that are anchored to the endoplasmatic reticulum (ER), such as the NS5A protein. The diffusion of NSPs has been studied by in vitro fluorescence recovery after photobleaching (FRAP) experiments. The diffusive evolution of the concentration field of NSPs on the ER can be described by means of surface partial differential equations (sufPDEs). Previous work estimated the diffusion coefficient of the NS5A protein by minimizing the discrepancy between an extended set of sufPDE simulations and experimental FRAP time-series data. Here, we provide a scaling analysis of the sufPDEs that describe the diffusive evolution of the concentration field of NSPs on the ER. This analysis provides an estimate of the diffusion coefficient that is based only on the ratio of the membrane surface area in the FRAP region to its contour length. The quality of this estimate is explored by a comparison to numerical solutions of the sufPDE for a flat geometry and for ten different 3D embedded 2D ER grids that are derived from fluorescence z-stack data of the ER. Finally, we apply the new data analysis to the experimental FRAP time-series data analyzed in our previous paper, and we discuss the opportunities of the new approach. Full article

(This article belongs to the Special Issue Advanced Research in Prediction of Protein Structure and Function)

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16 pages, 3013 KiB

Open AccessArticle

Solution Structures of Two Different FRP-OCP Complexes as Revealed via SEC-SANS

by Mina Hajizadeh, Maksym Golub, Marcus Moldenhauer, Olga Matsarskaia, Anne Martel, Lionel Porcar, Eugene Maksimov, Thomas Friedrich and Jörg Pieper

Int. J. Mol. Sci. 2024, 25(5), 2781; https://doi.org/10.3390/ijms25052781 - 28 Feb 2024

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Abstract

Photosynthetic organisms have established photoprotective mechanisms in order to dissipate excess light energy into heat, which is commonly known as non-photochemical quenching. Cyanobacteria utilize the orange carotenoid protein (OCP) as a high-light sensor and quencher to regulate the energy flow in the photosynthetic [...] Read more.

Photosynthetic organisms have established photoprotective mechanisms in order to dissipate excess light energy into heat, which is commonly known as non-photochemical quenching. Cyanobacteria utilize the orange carotenoid protein (OCP) as a high-light sensor and quencher to regulate the energy flow in the photosynthetic apparatus. Triggered by strong light, OCP undergoes conformational changes to form the active red state (OCP^R). In many cyanobacteria, the back conversion of OCP to the dark-adapted state is assisted by the fluorescence recovery protein (FRP). However, the exact molecular events involving OCP and its interaction with FRP remain largely unraveled so far due to their metastability. Here, we use small-angle neutron scattering combined with size exclusion chromatography (SEC-SANS) to unravel the solution structures of FRP-OCP complexes using a compact mutant of OCP lacking the N-terminal extension (^∆NTEOCP^O) and wild-type FRP. The results are consistent with the simultaneous presence of stable 2:2 and 2:1 FRP-^∆NTEOCP^O complexes in solution, where the former complex type is observed for the first time. For both complex types, we provide ab initio low-resolution shape reconstructions and compare them to homology models based on available crystal structures. It is likely that both complexes represent intermediate states of the back conversion of OCP to its dark-adapted state in the presence of FRP, which are of transient nature in the photocycle of wild-type OCP. This study demonstrates the large potential of SEC-SANS in revealing the solution structures of protein complexes in polydisperse solutions that would otherwise be averaged, leading to unspecific results. Full article

(This article belongs to the Special Issue Advanced Research in Prediction of Protein Structure and Function)

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14 pages, 6166 KiB

Open AccessArticle

Computational Exploration of Minimum Energy Reaction Pathway of N₂O Formation from Intermediate I of P450nor Using an Active Center Model

by Yusuke Kanematsu, Hiroko X. Kondo and Yu Takano

Int. J. Mol. Sci. 2023, 24(24), 17172; https://doi.org/10.3390/ijms242417172 - 6 Dec 2023

Viewed by 721

Abstract

P450nor is a heme-containing enzyme that catalyzes the conversion of nitric oxide (NO) to nitrous oxide (N₂O). Its catalytic mechanism has attracted attention in chemistry, biology, and environmental engineering. The catalytic cycle of P450nor is proposed to consist of three major [...] Read more.

P450nor is a heme-containing enzyme that catalyzes the conversion of nitric oxide (NO) to nitrous oxide (N₂O). Its catalytic mechanism has attracted attention in chemistry, biology, and environmental engineering. The catalytic cycle of P450nor is proposed to consist of three major steps. The reaction mechanism for the last step, N₂O generation, remains unknown. In this study, the reaction pathway of the N₂O generation from the intermediate I was explored with the B3LYP calculations using an active center model after the examination of the validity of the model. In the validation, we compared the heme distortions between P450nor and other oxidoreductases, suggesting a small effect of protein environment on the N₂O generation reaction in P450nor. We then evaluated the electrostatic environment effect of P450nor on the hydride affinity to the active site with quantum mechanics/molecular mechanics (QM/MM) calculations, confirming that the affinity was unchanged with or without the protein environment. The active center model for P450nor showed that the N₂O generation process in the enzymatic reaction undergoes a reasonable barrier height without protein environment. Consequently, our findings strongly suggest that the N₂O generation reaction from the intermediate I depends sorely on the intrinsic reactivity of the heme cofactor bound on cysteine residue. Full article

(This article belongs to the Special Issue Advanced Research in Prediction of Protein Structure and Function)

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18 pages, 11276 KiB

Open AccessArticle

New Insights into Radio-Resistance Mechanism Revealed by (Phospho)Proteome Analysis of Deinococcus Radiodurans after Heavy Ion Irradiation

by Shihao Liu, Fei Wang, Heye Chen, Zhixiang Yang, Yifan Ning, Cheng Chang and Dong Yang

Int. J. Mol. Sci. 2023, 24(19), 14817; https://doi.org/10.3390/ijms241914817 - 1 Oct 2023

Cited by 1 | Viewed by 1189

Abstract

Deinococcus radiodurans (D. radiodurans) can tolerate various extreme environments including radiation. Protein phosphorylation plays an important role in radiation resistance mechanisms; however, there is currently a lack of systematic research on this topic in D. radiodurans. Based on label-free (phospho)proteomics, [...] Read more.

Deinococcus radiodurans (D. radiodurans) can tolerate various extreme environments including radiation. Protein phosphorylation plays an important role in radiation resistance mechanisms; however, there is currently a lack of systematic research on this topic in D. radiodurans. Based on label-free (phospho)proteomics, we explored the dynamic changes of D. radiodurans under various doses of heavy ion irradiation and at different time points. In total, 2359 proteins and 1110 high-confidence phosphosites were identified, of which 66% and 23% showed significant changes, respectively, with the majority being upregulated. The upregulated proteins at different states (different doses or time points) were distinct, indicating that the radio-resistance mechanism is dose- and stage-dependent. The protein phosphorylation level has a much higher upregulation than protein abundance, suggesting phosphorylation is more sensitive to irradiation. There were four distinct dynamic changing patterns of phosphorylation, most of which were inconsistent with protein levels. Further analysis revealed that pathways related to RNA metabolism and antioxidation were activated after irradiation, indicating their importance in radiation response. We also screened some key hub phosphoproteins and radiation-responsive kinases for further study. Overall, this study provides a landscape of the radiation-induced dynamic change of protein expression and phosphorylation, which provides a basis for subsequent functional and applied studies. Full article

(This article belongs to the Special Issue Advanced Research in Prediction of Protein Structure and Function)

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20 pages, 11658 KiB

Open AccessArticle

Complement System Inhibitory Drugs in a Zebrafish (Danio rerio) Model: Computational Modeling

by Dayanne Carla Fernandes and Denise V. Tambourgi

Int. J. Mol. Sci. 2023, 24(18), 13895; https://doi.org/10.3390/ijms241813895 - 9 Sep 2023

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Abstract

The dysregulation of complement system activation usually results in acute or chronic inflammation and can contribute to the development of various diseases. Although the activation of complement pathways is essential for innate defense, exacerbated activity of this system may be harmful to the [...] Read more.

The dysregulation of complement system activation usually results in acute or chronic inflammation and can contribute to the development of various diseases. Although the activation of complement pathways is essential for innate defense, exacerbated activity of this system may be harmful to the host. Thus, drugs with the potential to inhibit the activation of the complement system may be important tools in therapy for diseases associated with complement system activation. The synthetic peptides Cp40 and PMX205 can be highlighted in this regard, given that they selectively inhibit the C3 and block the C5a receptor (C5aR1), respectively. The zebrafish (Danio rerio) is a robust model for studying the complement system. The aim of the present study was to use in silico computational modeling to investigate the hypothesis that these complement system inhibitor peptides interact with their target molecules in zebrafish, for subsequent in vivo validation. For this, we analyzed molecular docking interactions between peptides and target molecules. Our study demonstrated that Cp40 and the cyclic peptide PMX205 have positive interactions with their respective zebrafish targets, thus suggesting that zebrafish can be used as an animal model for therapeutic studies on these inhibitors. Full article

(This article belongs to the Special Issue Advanced Research in Prediction of Protein Structure and Function)

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12 pages, 1963 KiB

Open AccessArticle

Intelligent De Novo Design of Novel Antimicrobial Peptides against Antibiotic-Resistant Bacteria Strains

by Tzu-Tang Lin, Li-Yen Yang, Chung-Yen Lin, Ching-Tien Wang, Chia-Wen Lai, Chi-Fong Ko, Yang-Hsin Shih and Shu-Hwa Chen

Int. J. Mol. Sci. 2023, 24(7), 6788; https://doi.org/10.3390/ijms24076788 - 5 Apr 2023

Cited by 4 | Viewed by 2709

Abstract

Because of the growing number of clinical antibiotic resistance cases in recent years, novel antimicrobial peptides (AMPs) may be ideal for next-generation antibiotics. This study trained a Wasserstein generative adversarial network with gradient penalty (WGAN-GP) based on known AMPs to generate novel AMP [...] Read more.

Because of the growing number of clinical antibiotic resistance cases in recent years, novel antimicrobial peptides (AMPs) may be ideal for next-generation antibiotics. This study trained a Wasserstein generative adversarial network with gradient penalty (WGAN-GP) based on known AMPs to generate novel AMP candidates. The quality of the GAN-designed peptides was evaluated in silico, and eight of them, named GAN-pep 1–8, were selected by an AMP Artificial Intelligence (AI) classifier and synthesized for further experiments. Disc diffusion testing and minimum inhibitory concentration (MIC) determinations were used to identify the antibacterial effects of the synthesized GAN-designed peptides. Seven of the eight synthesized GAN-designed peptides displayed antibacterial activity. Additionally, GAN-pep 3 and GAN-pep 8 presented a broad spectrum of antibacterial effects and were effective against antibiotic-resistant bacteria strains, such as methicillin-resistant Staphylococcus aureus and carbapenem-resistant Pseudomonas aeruginosa. GAN-pep 3, the most promising GAN-designed peptide candidate, had low MICs against all the tested bacteria. In brief, our approach shows an efficient way to discover AMPs effective against general and antibiotic-resistant bacteria strains. In addition, such a strategy also allows other novel functional peptides to be quickly designed, identified, and synthesized for validation on the wet bench. Full article

(This article belongs to the Special Issue Advanced Research in Prediction of Protein Structure and Function)

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16 pages, 2615 KiB

Open AccessArticle

A Protein Co-Conservation Network Model Characterizes Mutation Effects on SARS-CoV-2 Spike Protein

by Lianjie Zeng, Yitan Lu, Wenying Yan and Yang Yang

Int. J. Mol. Sci. 2023, 24(4), 3255; https://doi.org/10.3390/ijms24043255 - 7 Feb 2023

Cited by 3 | Viewed by 1477

Abstract

The emergence of numerous variants of SARS-CoV-2 has presented challenges to the global efforts to control the COVID-19 pandemic. The major mutation is in the SARS-CoV-2 viral envelope spike protein that is responsible for virus attachment to the host, and is the main [...] Read more.

The emergence of numerous variants of SARS-CoV-2 has presented challenges to the global efforts to control the COVID-19 pandemic. The major mutation is in the SARS-CoV-2 viral envelope spike protein that is responsible for virus attachment to the host, and is the main target for host antibodies. It is critically important to study the biological effects of the mutations to understand the mechanisms of how mutations alter viral functions. Here, we propose a protein co-conservation weighted network (PCCN) model only based on the protein sequence to characterize the mutation sites by topological features and to investigate the mutation effects on the spike protein from a network view. Frist, we found that the mutation sites on the spike protein had significantly larger centrality than the non-mutation sites. Second, the stability changes and binding free energy changes in the mutation sites were positively significantly correlated with their neighbors’ degree and the shortest path length separately. The results indicate that our PCCN model provides new insights into mutations on spike proteins and reflects the mutation effects on protein function alternations. Full article

(This article belongs to the Special Issue Advanced Research in Prediction of Protein Structure and Function)

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14 pages, 1606 KiB

Open AccessArticle

DeepTP: A Deep Learning Model for Thermophilic Protein Prediction

by Jianjun Zhao, Wenying Yan and Yang Yang

Int. J. Mol. Sci. 2023, 24(3), 2217; https://doi.org/10.3390/ijms24032217 - 22 Jan 2023

Cited by 13 | Viewed by 2816

Abstract

Thermophilic proteins have important value in the fields of biopharmaceuticals and enzyme engineering. Most existing thermophilic protein prediction models are based on traditional machine learning algorithms and do not fully utilize protein sequence information. To solve this problem, a deep learning model based [...] Read more.

Thermophilic proteins have important value in the fields of biopharmaceuticals and enzyme engineering. Most existing thermophilic protein prediction models are based on traditional machine learning algorithms and do not fully utilize protein sequence information. To solve this problem, a deep learning model based on self-attention and multiple-channel feature fusion was proposed to predict thermophilic proteins, called DeepTP. First, a large new dataset consisting of 20,842 proteins was constructed. Second, a convolutional neural network and bidirectional long short-term memory network were used to extract the hidden features in protein sequences. Different weights were then assigned to features through self-attention, and finally, biological features were integrated to build a prediction model. In a performance comparison with existing methods, DeepTP had better performance and scalability in an independent balanced test set and validation set, with AUC values of 0.944 and 0.801, respectively. In the unbalanced test set, DeepTP had an average precision (AP) of 0.536. The tool is freely available. Full article

(This article belongs to the Special Issue Advanced Research in Prediction of Protein Structure and Function)

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