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State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China
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State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Molecular Biophysics".

Deadline for manuscript submissions: closed (30 November 2024) | Viewed by 53956

Special Issue Editors

Prof. Dr. Zhiliang Ji

E-Mail Website
Collection Editor
School of Life Sciences, Xiamen University, Xiamen 360000, China
Interests: bioinformatics; systems biology; systems drug toxicology; pharmacogenomics; drug design; CADD; -omics; biomedical big data; machine learning
Prof. Dr. Ruhong Zhou

E-Mail Website
Collection Editor
Institute of Quantitative Biology, Zhejiang University, Hangzhou 310027, China
Interests: molecular dynamics; protein folding; protein-protein interaction; machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Xuanyu Meng

E-Mail Website
Collection Editor
Institute of Quantitative Biology and Medicine, Soochow University, Suzhou 215123, China
Interests: molecular dynamics simulation; molecular docking; ion channels
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Topical Collection include two main topics:

1. Modern biophysics, biochemistry and molecular biology emerged since the discovery of the double-helical structure model of DNA using X-ray crystallography in 1950s. Decoding the mystery of life from a microscopic point of view used to be very challenging but has recently come of age. Over the decades, progress in technologies such as single-particle cryo-electron microscopy, single-molecule fluorescence experiments, and molecular modellings, has enabled the studies of biomolecules covering from small organic molecules/drugs to proteins, DNA, RNA and cell membranes at biomolecular or even atomic levels. Particularly, introduction of novel machine learning algorithms to the field of structural and computational biology helps scientists to better characterize the interactions between biomolecules while revealing the mechanisms behind dynamic biological processes. Combination of lab experiments and in silico approaches is reshaping many aspects of nowadays biophysics, biochemistry and molecular biology.

In this Topical Collection, we encourage scientists in China from diverse backgrounds to contribute original research or review articles including but not limited to studies of protein/DNA/RNA/lipid interactions, bio-nano interfaces, functional biomolecule design, and molecular machines, etc.

2. As an integral part of nature, the health of human beings is inextricably linked with the inner and outer environment they live. Therefore, disease can be explained as an unbalanced state of the body caused by environmental change. To restore the harmonious human-environment relation, vaccines and drugs are thus designed to prevent or rectify the unbalance. In recent years, extensive efforts have been made to monitor human-environment interactions such as microbiota-host interactions, drug-microbiota interactions, and so on. Along with these efforts, a large volume of multimodal data is produced. Proper interpretation of these big data, in particular using state-of-art machine learning or AI technologies, will be the key to better understand the human-environment interactions and further translate the knowledge to improve human health.

We also welcome contributions that (1) Interpretation of multiple omics data to unveil complex interaction patterns between microbiota and environment, microbiota and host, human behavior and environment, and so on. (2) Integration of multimodal data to reveal key molecules, biomarkers, or therapeutic targets in understanding, diagnosing, and rectifying the unbalanced state of complex diseases. (3) Development of in silico techniques to assist in designing broad-spectrum or highly specific microbial vaccines, microbicides, and so on.

We aim to present innovative and exciting research in biophysics, biochemistry and molecular biology that are currently happening in the region of China. We look forward to receiving your contributions.

Prof. Dr. Zhiliang Ji
Prof. Dr. Ruhong Zhou
Dr. Xuanyu Meng
Collection Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomolecules is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Molecular modelling
  • molecular dynamics simulation
  • protein-protein interaction
  • protein folding
  • Bioinformatics
  • molecular docking
  • drug design
  • bio-nanomaterial interface
  • molecular machine
  • functional biomacromolecule design and optimization
  • functional regulation of RNA/DNA
  • microbiota
  • multimodal data
  • machine learning
  • vaccines

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14 pages, 3800 KiB  
Article
Novel Inhibitory Role of Fenofibric Acid by Targeting Cryptic Site on the RBD of SARS-CoV-2
by Jianxiang Huang, Kevin C. Chan and Ruhong Zhou
Biomolecules 2023, 13(2), 359; https://doi.org/10.3390/biom13020359 - 14 Feb 2023
Cited by 2 | Viewed by 2746
Abstract
The emergence of the recent pandemic causing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created an alarming situation worldwide. It also prompted extensive research on drug repurposing to find a potential treatment for SARS-CoV-2 infection. An active metabolite of the hyperlipidemic drug [...] Read more.
The emergence of the recent pandemic causing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created an alarming situation worldwide. It also prompted extensive research on drug repurposing to find a potential treatment for SARS-CoV-2 infection. An active metabolite of the hyperlipidemic drug fenofibrate (also called fenofibric acid or FA) was found to destabilize the receptor-binding domain (RBD) of the viral spike protein and therefore inhibit its binding to human angiotensin-converting enzyme 2 (hACE2) receptor. Despite being considered as a potential drug candidate for SARS-CoV-2, FA’s inhibitory mechanism remains to be elucidated. We used molecular dynamics (MD) simulations to investigate the binding of FA to the RBD of the SARS-CoV-2 spike protein and revealed a potential cryptic FA binding site. Free energy calculations were performed for different FA-bound RBD complexes. The results suggest that the interaction of FA with the cryptic binding site of RBD alters the conformation of the binding loop of RBD and effectively reduces its binding affinity towards ACE2. Our study provides new insights for the design of SARS-CoV-2 inhibitors targeting cryptic sites on the RBD of SARS-CoV-2. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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17 pages, 2854 KiB  
Article
SARS-CoV-2 Delta Variant: Interplay between Individual Mutations and Their Allosteric Synergy
by Kevin C. Chan, Yi Song, Zheng Xu, Chun Shang and Ruhong Zhou
Biomolecules 2022, 12(12), 1742; https://doi.org/10.3390/biom12121742 - 23 Nov 2022
Cited by 8 | Viewed by 2304
Abstract
Since its first appearance in April 2021, B.1.617.2, also termed variant Delta, catalyzed one major worldwide wave dominating the second year of coronavirus disease 2019 (COVID-19) pandemic. Despite its quick disappearance worldwide, the strong virulence caused by a few point mutations remains an [...] Read more.
Since its first appearance in April 2021, B.1.617.2, also termed variant Delta, catalyzed one major worldwide wave dominating the second year of coronavirus disease 2019 (COVID-19) pandemic. Despite its quick disappearance worldwide, the strong virulence caused by a few point mutations remains an unsolved problem largely. Along with the other two sublineages, the Delta variant harbors an accumulation of Spike protein mutations, including the previously identified L452R, E484Q, and the newly emerged T478K on its receptor binding domain (RBD). We used molecular dynamics (MD) simulations, in combination with free energy perturbation (FEP) calculations, to examine the effects of two combinative mutation sets, L452R + E484Q and L452R + T478K. Our dynamic trajectories reveal an enhancement in binding affinity between mutated RBD and the common receptor protein angiotensin converting enzyme 2 (ACE2) through a net increase in the buried molecular surface area of the binary complex. This enhanced binding, mediated through Gln493, sets the same stage for all three sublineages due to the presence of L452R mutation. The other mutation component, E484Q or T478K, was found to impact the RBD-ACE2 binding and help the variant to evade several monoclonal antibodies (mAbs) in a distinct manner. Especially for L452R + T478K, synergies between mutations are mediated through a complex residual and water interaction network and further enhance its binding to ACE2. Taking together, this study demonstrates that new variants of SARS-CoV-2 accomplish both “attack” (infection) and “defense” (antibody neutralization escape) with the same “polished sword” (mutated Spike RBD). Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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14 pages, 2731 KiB  
Article
In Silico Maturation of a Nanomolar Antibody against the Human CXCR2
by Damiano Buratto, Yue Wan, Xiaojie Shi, Guang Yang and Francesco Zonta
Biomolecules 2022, 12(9), 1285; https://doi.org/10.3390/biom12091285 - 13 Sep 2022
Cited by 5 | Viewed by 2334
Abstract
The steady increase in computational power in the last 50 years is opening unprecedented opportunities in biology, as computer simulations of biological systems have become more accessible and can reproduce experimental results more accurately. Here, we wanted to test the ability of computer [...] Read more.
The steady increase in computational power in the last 50 years is opening unprecedented opportunities in biology, as computer simulations of biological systems have become more accessible and can reproduce experimental results more accurately. Here, we wanted to test the ability of computer simulations to replace experiments in the limited but practically useful scope of improving the biochemical characteristics of the abN48 antibody, a nanomolar antagonist of the CXC chemokine receptor 2 (CXCR2) that was initially selected from a combinatorial antibody library. Our results showed a good correlation between the computed binding energies of the antibody to the peptide target and the experimental binding affinities. Moreover, we showed that it is possible to design new antibody sequences in silico with a higher affinity to the desired target using a Monte Carlo Metropolis algorithm. The newly designed sequences had an affinity comparable to the best ones obtained using in vitro affinity maturation and could be obtained within a similar timeframe. The methodology proposed here could represent a valid alternative for improving antibodies in cases in which experiments are too expensive or technically tricky and could open an opportunity for designing antibodies for targets that have been elusive so far. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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11 pages, 2247 KiB  
Article
CoVM2: Molecular Biological Data Integration of SARS-CoV-2 Proteins in a Macro-to-Micro Method
by Hongjun Chen, Xiaotian Hu, Yanshi Hu, Jiawen Zhou and Ming Chen
Biomolecules 2022, 12(8), 1067; https://doi.org/10.3390/biom12081067 - 2 Aug 2022
Cited by 1 | Viewed by 2905
Abstract
The COVID-19 pandemic has been a major public health event since 2020. Multiple variant strains of SARS-CoV-2, the causative agent of COVID-19, were detected based on the mutation sites in their sequences. These sequence mutations may lead to changes in the protein structures [...] Read more.
The COVID-19 pandemic has been a major public health event since 2020. Multiple variant strains of SARS-CoV-2, the causative agent of COVID-19, were detected based on the mutation sites in their sequences. These sequence mutations may lead to changes in the protein structures and affect the binding states of SARS-CoV-2 and human proteins. Experimental research on SARS-CoV-2 has accumulated a large amount of structural data and protein-protein interactions (PPIs), but the studies on the SARS-CoV-2–human PPI networks lack integration of physical associations with possible protein docking information. In addition, the docking structures of variant viral proteins with human receptor proteins are still insufficient. This study constructed SARS-CoV-2–human protein–protein interaction network with data integration methods. Crystal structures were collected to map the interaction pairs. The pairs of direct interactions and physical associations were selected and analyzed for variant docking calculations. The study examined the structures of spike (S) glycoprotein of variants Delta B.1.617.2, Omicron BA.1, and Omicron BA.2. The calculated docking structures of S proteins and potential human receptors were obtained. The study integrated binary protein interactions with 3D docking structures to fulfill an extended view of SARS-CoV-2 proteins from a macro- to micro-scale. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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9 pages, 1359 KiB  
Article
CavitySpace: A Database of Potential Ligand Binding Sites in the Human Proteome
by Shiwei Wang, Haoyu Lin, Zhixian Huang, Yufeng He, Xiaobing Deng, Youjun Xu, Jianfeng Pei and Luhua Lai
Biomolecules 2022, 12(7), 967; https://doi.org/10.3390/biom12070967 - 11 Jul 2022
Cited by 23 | Viewed by 4374
Abstract
Location and properties of ligand binding sites provide important information to uncover protein functions and to direct structure-based drug design approaches. However, as binding site detection depends on the three-dimensional (3D) structural data of proteins, functional analysis based on protein ligand binding sites [...] Read more.
Location and properties of ligand binding sites provide important information to uncover protein functions and to direct structure-based drug design approaches. However, as binding site detection depends on the three-dimensional (3D) structural data of proteins, functional analysis based on protein ligand binding sites is formidable for proteins without structural information. Recent developments in protein structure prediction and the 3D structures built by AlphaFold provide an unprecedented opportunity for analyzing ligand binding sites in human proteins. Here, we constructed the CavitySpace database, the first pocket library for all the proteins in the human proteome, using a widely-applied ligand binding site detection program CAVITY. Our analysis showed that known ligand binding sites could be well recovered. We grouped the predicted binding sites according to their similarity which can be used in protein function prediction and drug repurposing studies. Novel binding sites in highly reliable predicted structure regions provide new opportunities for drug discovery. Our CavitySpace is freely available and provides a valuable tool for drug discovery and protein function studies. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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12 pages, 1731 KiB  
Article
Triglycerides as Biomarker for Predicting Systemic Lupus Erythematosus Related Kidney Injury of Negative Proteinuria
by Mingjun Si, Danyang Li, Ting Liu, Yuanyan Cai, Jingyu Yang, Lili Jiang and Haitao Yu
Biomolecules 2022, 12(7), 945; https://doi.org/10.3390/biom12070945 - 5 Jul 2022
Cited by 5 | Viewed by 2667
Abstract
Fewer biomarkers can be used to predict systemic lupus erythematosus (SLE) related kidney injury. This paper presents an apriori algorithm of association rules to mine the predictive biomarkers for SLE-related kidney injury of negative proteinuria. An apriori algorithm of association rules was employed [...] Read more.
Fewer biomarkers can be used to predict systemic lupus erythematosus (SLE) related kidney injury. This paper presents an apriori algorithm of association rules to mine the predictive biomarkers for SLE-related kidney injury of negative proteinuria. An apriori algorithm of association rules was employed to identify biomarkers, and logistic regression analysis and spearman correlation analysis were used to evaluate the correlation between triglycerides and SLE-related kidney injury of negative proteinuria. Triglycerides were mined out by the apriori algorithm of association rules. The level of triglycerides was significantly higher, and it was an independent risk factor for SLE-related kidney injury. In the high-triglycerides group, the number of patients with SLE-related kidney injury, SLEDAI-2K, urine P-CAST, the level of blood urea nitrogen, serum creatinine, and proteinuria were increased. Triglycerides level was positively correlated with proteinuria and P-CAST and negatively correlated with albumin and IgG. The area under the ROC curve of triglycerides and triglycerides combined proteinuria was 0.72 and 0.82, respectively. Significantly, 50% of SLE-related kidney injuries of negative proteinuria could be identified by high triglycerides levels. High triglycerides level was found at the time of onset of kidney injury, and it was opposite to glomerular filtration rate. Triglycerides may be a potential marker for predicting SLE-related kidney injury, especially in SLE-related kidney injury of negative proteinuria. Triglycerides combined proteinuria could predict SLE-related kidney injury effectively. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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18 pages, 4755 KiB  
Article
Comparing Bayesian-Based Reconstruction Strategies in Topology-Based Pathway Enrichment Analysis
by Yajunzi Wang, Jing Li, Daiyun Huang, Yang Hao, Bo Li, Kai Wang, Boya Chen, Ting Li and Xin Liu
Biomolecules 2022, 12(7), 906; https://doi.org/10.3390/biom12070906 - 28 Jun 2022
Cited by 3 | Viewed by 2645
Abstract
The development of high-throughput omics technologies has enabled the quantification of vast amounts of genes and gene products in the whole genome. Pathway enrichment analysis (PEA) provides an intuitive solution for extracting biological insights from massive amounts of data. Topology-based pathway analysis (TPA) [...] Read more.
The development of high-throughput omics technologies has enabled the quantification of vast amounts of genes and gene products in the whole genome. Pathway enrichment analysis (PEA) provides an intuitive solution for extracting biological insights from massive amounts of data. Topology-based pathway analysis (TPA) represents the latest generation of PEA methods, which exploit pathway topology in addition to lists of differentially expressed genes and their expression profiles. A subset of these TPA methods, such as BPA, BNrich, and PROPS, reconstruct pathway structures by training Bayesian networks (BNs) from canonical biological pathways, providing superior representations that explain causal relationships between genes. However, these methods have never been compared for their differences in the PEA and their different topology reconstruction strategies. In this study, we aim to compare the BN reconstruction strategies of the BPA, BNrich, PROPS, Clipper, and Ensemble methods and their PEA and performance on tumor and non-tumor classification based on gene expression data. Our results indicate that they performed equally well in distinguishing tumor and non-tumor samples (AUC > 0.95) yet with a varying ranking of pathways, which can be attributed to the different BN structures resulting from the different cyclic structure removal strategies. This can be clearly seen from the reconstructed JAK-STAT networks by different strategies. In a nutshell, BNrich, which relies on expert intervention to remove loops and cyclic structures, produces BNs that best fit the biological facts. The plausibility of the Clipper strategy can also be partially explained by intuitive biological rules and theorems. Our results may offer an informed reference for the proper method for a given data analysis task. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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16 pages, 2656 KiB  
Article
Glutamine Metabolism Is Required for Alveolar Regeneration during Lung Injury
by Sisi Wang, Xue Li, Qingwen Ma, Qi Wang, Junping Wu, Hongzhi Yu, Kuan Li, Yu Li, Jianhai Wang, Qiuyang Zhang, Youwei Wang, Qi Wu and Huaiyong Chen
Biomolecules 2022, 12(5), 728; https://doi.org/10.3390/biom12050728 - 22 May 2022
Cited by 16 | Viewed by 4660
Abstract
(1) Background: Abnormal repair after alveolar epithelial injury drives the progression of idiopathic pulmonary fibrosis (IPF). The maintenance of epithelial integrity is based on the self-renewal and differentiation of alveolar type 2 (AT2) cells, which require sufficient energy. However, the role of glutamine [...] Read more.
(1) Background: Abnormal repair after alveolar epithelial injury drives the progression of idiopathic pulmonary fibrosis (IPF). The maintenance of epithelial integrity is based on the self-renewal and differentiation of alveolar type 2 (AT2) cells, which require sufficient energy. However, the role of glutamine metabolism in the maintenance of the alveolar epithelium remains unclear. In this study, we investigated the role of glutamine metabolism in AT2 cells of patients with IPF and in mice with bleomycin-induced fibrosis. (2) Methods: Single-cell RNA sequencing (scRNA-seq), transcriptome, and metabolomics analyses were conducted to investigate the changes in the glutamine metabolic pathway during pulmonary fibrosis. Metabolic inhibitors were used to stimulate AT2 cells to block glutamine metabolism. Regeneration of AT2 cells was detected using bleomycin-induced mouse lung fibrosis and organoid models. (3) Results: Single-cell analysis showed that the expression levels of catalytic enzymes responsible for glutamine catabolism were downregulated (p < 0.001) in AT2 cells of patients with IPF, suggesting the accumulation of unusable glutamine. Combined analysis of the transcriptome (p < 0.05) and metabolome (p < 0.001) revealed similar changes in glutamine metabolism in bleomycin-induced pulmonary fibrosis in mice. Mechanistically, inhibition of the key enzymes involved in glucose metabolism, glutaminase-1 (GLS1) and glutamic-pyruvate transaminase-2 (GPT2) leads to reduced proliferation (p < 0.01) and differentiation (p < 0.01) of AT2 cells. (4) Conclusions: Glutamine metabolism is required for alveolar epithelial regeneration during lung injury. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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15 pages, 4833 KiB  
Article
Mutational Effect of Some Major COVID-19 Variants on Binding of the S Protein to ACE2
by Zhendong Li and John Z. H. Zhang
Biomolecules 2022, 12(4), 572; https://doi.org/10.3390/biom12040572 - 13 Apr 2022
Cited by 6 | Viewed by 2849
Abstract
COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has many variants that accelerated the spread of the virus. In this study, we investigated the quantitative effect of some major mutants of the spike protein of SARS-CoV-2 binding to the [...] Read more.
COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has many variants that accelerated the spread of the virus. In this study, we investigated the quantitative effect of some major mutants of the spike protein of SARS-CoV-2 binding to the human angiotensin-converting enzyme 2 (ACE2). These mutations are directly related to the Variant of Concern (VOC) including Alpha, Beta, Gamma, Delta and Omicron. Our calculations show that five major mutations (N501Y, E484K, L452R, T478K and K417N), first reported in Alpha, Beta, Gamma and Delta variants, all increase the binding of the S protein to ACE2 (except K417N), consistent with the experimental findings. We also studied an additional eight mutations of the Omicron variant that are located on the interface of the receptor binding domain (RDB) and have not been reported in other VOCs. Our study showed that most of these mutations (except Y505H and G446S) enhance the binding of the S protein to ACE2. The computational predictions helped explain why the Omicron variant quickly became dominant worldwide. Finally, comparison of several different computational methods for binding free energy calculation of these mutants was made. The alanine scanning method used in the current calculation helped to elucidate the residue-specific interactions responsible for the enhanced binding affinities of the mutants. The results show that the ASGB (alanine scanning with generalized Born) method is an efficient and reliable method for these binding free energy calculations due to mutations. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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16 pages, 3675 KiB  
Article
The Molecular Mechanism of Human Voltage-Dependent Anion Channel 1 Blockade by the Metallofullerenol Gd@C82(OH)22: An In Silico Study
by Xiuxiu Wang, Nan Yang, Juan Su, Chenchen Wu, Shengtang Liu, Lei Chang, Leigh D. Plant and Xuanyu Meng
Biomolecules 2022, 12(1), 123; https://doi.org/10.3390/biom12010123 - 12 Jan 2022
Cited by 5 | Viewed by 2369
Abstract
The endohedral metallofullerenol Gd@C82(OH)22 has been identified as a possible antineoplastic agent that can inhibit both the growth and metastasis of cancer cells. Despite these potentially important effects, our understanding of the interactions between Gd@C82(OH)22 and biomacromolecules [...] Read more.
The endohedral metallofullerenol Gd@C82(OH)22 has been identified as a possible antineoplastic agent that can inhibit both the growth and metastasis of cancer cells. Despite these potentially important effects, our understanding of the interactions between Gd@C82(OH)22 and biomacromolecules remains incomplete. Here, we study the interaction between Gd@C82(OH)22 and the human voltage-dependent anion channel 1 (hVDAC1), the most abundant porin embedded in the mitochondrial outer membrane (MOM), and a potential druggable target for novel anticancer therapeutics. Using in silico approaches, we observe that Gd@C82(OH)22 molecules can permeate and form stable interactions with the pore of hVDAC1. Further, this penetration can occur from either side of the MOM to elicit blockage of the pore. The binding between Gd@C82(OH)22 and hVDAC1 is largely driven by long-range electrostatic interactions. Analysis of the binding free energies indicates that it is thermodynamically more favorable for Gd@C82(OH)22 to bind to the hVDAC1 pore when it enters the channel from inside the membrane rather than from the cytoplasmic side of the protein. Multiple factors contribute to the preferential penetration, including the surface electrostatic landscape of hVDAC1 and the unique physicochemical properties of Gd@C82(OH)22. Our findings provide insights into the potential molecular interactions of macromolecular biological systems with the Gd@C82(OH)22 nanodrug. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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10 pages, 3723 KiB  
Article
Planar Boronic Graphene and Nitrogenized Graphene Heterostructure for Protein Stretch and Confinement
by Xuchang Su, Zhi He, Lijun Meng, Hong Liang and Ruhong Zhou
Biomolecules 2021, 11(12), 1756; https://doi.org/10.3390/biom11121756 - 24 Nov 2021
Cited by 1 | Viewed by 2148
Abstract
Single-molecule techniques such as electron tunneling and atomic force microscopy have attracted growing interests in protein sequencing. For these methods, it is critical to refine and stabilize the protein sample to a “suitable mode” before applying a high-fidelity measurement. Here, we show that [...] Read more.
Single-molecule techniques such as electron tunneling and atomic force microscopy have attracted growing interests in protein sequencing. For these methods, it is critical to refine and stabilize the protein sample to a “suitable mode” before applying a high-fidelity measurement. Here, we show that a planar heterostructure comprising boronic graphene (BC3) and nitrogenized graphene (C3N) sandwiched stripe (BC3/C3N/BC3) is capable of the effective stretching and confinement of three types of intrinsically disordered proteins (IDPs), including amyloid-β (1–42), polyglutamine (Q42), and α-Synuclein (61–95). Our molecular dynamics simulations demonstrate that the protein molecules interact more strongly with the C3N stripe than the BC3 one, which leads to their capture, elongation, and confinement along the center C3N stripe of the heterostructure. The conformational fluctuations of IDPs are substantially reduced after being stretched. This design may serve as a platform for single-molecule protein analysis with reduced thermal noise. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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16 pages, 2840 KiB  
Article
Revealing Topological Barriers against Knot Untying in Thermal and Mechanical Protein Unfolding by Molecular Dynamics Simulations
by Yan Xu, Runshan Kang, Luyao Ren, Lin Yang and Tongtao Yue
Biomolecules 2021, 11(11), 1688; https://doi.org/10.3390/biom11111688 - 13 Nov 2021
Cited by 3 | Viewed by 2521
Abstract
The knot is one of the most remarkable topological features identified in an increasing number of proteins with important functions. However, little is known about how the knot is formed during protein folding, and untied or maintained in protein unfolding. By means of [...] Read more.
The knot is one of the most remarkable topological features identified in an increasing number of proteins with important functions. However, little is known about how the knot is formed during protein folding, and untied or maintained in protein unfolding. By means of all-atom molecular dynamics simulation, here we employ methyltransferase YbeA as the knotted protein model to analyze changes of the knotted conformation coupled with protein unfolding under thermal and mechanical denaturing conditions. Our results show that the trefoil knot in YbeA is occasionally untied via knot loosening rather than sliding under enhanced thermal fluctuations. Through correlating protein unfolding with changes in the knot position and size, several aspects of barriers that jointly suppress knot untying are revealed. In particular, protein unfolding is always prior to knot untying and starts preferentially from separation of two α-helices (α1 and α5), which protect the hydrophobic core consisting of β-sheets (β1–β4) from exposure to water. These β-sheets form a loop through which α5 is threaded to form the knot. Hydrophobic and hydrogen bonding interactions inside the core stabilize the loop against loosening. In addition, residues at N-terminal of α5 define a rigid turning to impede α5 from sliding out of the loop. Site mutations are designed to specifically eliminate these barriers, and easier knot untying is achieved under the same denaturing conditions. These results provide new molecular level insights into the folding/unfolding of knotted proteins. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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13 pages, 18816 KiB  
Article
Computational Insights into the Binding Mechanism of OxyS sRNA with Chaperone Protein Hfq
by Mengxin Li, Yalong Cong, Yifei Qi and John Z. H. Zhang
Biomolecules 2021, 11(11), 1653; https://doi.org/10.3390/biom11111653 - 8 Nov 2021
Cited by 1 | Viewed by 1909
Abstract
Under the oxidative stress condition, the small RNA (sRNA) OxyS that acts as essential post-transcriptional regulators of gene expression is produced and plays a regulatory function with the assistance of the RNA chaperone Hfq protein. Interestingly, experimental studies found that the N48A mutation [...] Read more.
Under the oxidative stress condition, the small RNA (sRNA) OxyS that acts as essential post-transcriptional regulators of gene expression is produced and plays a regulatory function with the assistance of the RNA chaperone Hfq protein. Interestingly, experimental studies found that the N48A mutation of Hfq protein could enhance the binding affinity with OxyS while resulting in the defection of gene regulation. However, how the Hfq protein interacts with sRNA OxyS and the origin of the stronger affinity of N48A mutation are both unclear. In this paper, molecular dynamics (MD) simulations were performed on the complex structure of Hfq and OxyS to explore their binding mechanism. The molecular mechanics generalized born surface area (MM/GBSA) and interaction entropy (IE) method were combined to calculate the binding free energy between Hfq and OxyS sRNA, and the computational result was correlated with the experimental result. Per-residue decomposition of the binding free energy revealed that the enhanced binding ability of the N48A mutation mainly came from the increased van der Waals interactions (vdW). This research explored the binding mechanism between Oxys and chaperone protein Hfq and revealed the origin of the strong binding affinity of N48A mutation. The results provided important insights into the mechanism of gene expression regulation affected by protein mutations. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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16 pages, 5467 KiB  
Article
Computational Analysis of Naturally Occurring Aristolochic Acid Analogues and Their Biological Sources
by Tingjun Xu, Weiming Chen, Junhong Zhou, Jingfang Dai, Yingyong Li and Yingli Zhao
Biomolecules 2021, 11(9), 1344; https://doi.org/10.3390/biom11091344 - 11 Sep 2021
Cited by 11 | Viewed by 3204
Abstract
Aristolochic acids are known for nephrotoxicity, and implicated in multiple cancer types such as hepatocellular carcinomas demonstrated by recent studies. Natural products that are analogues to aristolochic acids have been constantly isolated from organisms; a larger chemical space of these compounds and a [...] Read more.
Aristolochic acids are known for nephrotoxicity, and implicated in multiple cancer types such as hepatocellular carcinomas demonstrated by recent studies. Natural products that are analogues to aristolochic acids have been constantly isolated from organisms; a larger chemical space of these compounds and a wider coverage of biological sources should be determined in consideration of the potential hazard of aristolochic acid analogues and the wide distribution of their biological sources in the nature. Therefore, we carried out an in silico research of naturally occurring aristolochic acid analogues and their biological sources, as a supplement to existing studies. The result shows a chemical space of 238 naturally occurring aristolochic acid analogues that are present in 175 species of biological sources including 44 traditional medicines. With the computational estimation for toxicity and the implication in hazard assessment of a biological source with the presence of aristolochic acid analogues, we propose that additional awareness should be raised to the public for avoidance of toxic species, especially those that are used as herbal medicines and easily accessible. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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15 pages, 5993 KiB  
Article
Revealing the Mutation Patterns of Drug-Resistant Reverse Transcriptase Variants of Human Immunodeficiency Virus through Proteochemometric Modeling
by Jingxuan Qiu, Xinxin Tian, Jiangru Liu, Yulong Qin, Junjie Zhu, Dongpo Xu and Tianyi Qiu
Biomolecules 2021, 11(9), 1302; https://doi.org/10.3390/biom11091302 - 2 Sep 2021
Cited by 2 | Viewed by 2185
Abstract
Drug-resistant cases of human immunodeficiency virus (HIV) nucleoside reverse transcriptase inhibitors (NRTI) are constantly accumulating due to the frequent mutations of the reverse transcriptase (RT). Predicting the potential drug resistance of HIV-1 NRTIs could provide instructions for the proper clinical use of available [...] Read more.
Drug-resistant cases of human immunodeficiency virus (HIV) nucleoside reverse transcriptase inhibitors (NRTI) are constantly accumulating due to the frequent mutations of the reverse transcriptase (RT). Predicting the potential drug resistance of HIV-1 NRTIs could provide instructions for the proper clinical use of available drugs. In this study, a novel proteochemometric (PCM) model was constructed to predict the drug resistance between six NRTIs against different variants of RT. Forty-seven dominant mutation sites were screened using the whole protein of HIV-1 RT. Thereafter, the physicochemical properties of the dominant mutation sites can be derived to generate the protein descriptors of RT. Furthermore, by combining the molecular descriptors of NRTIs, PCM modeling can be constructed to predict the inhibition ability between RT variants and NRTIs. The results indicated that our PCM model could achieve a mean AUC value of 0.946 and a mean accuracy of 0.873 on the external validation set. Finally, based on PCM modeling, the importance of features was calculated to reveal the dominant amino acid distribution and mutation patterns on RT, to reflect the characteristics of drug-resistant sequences. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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Review

Jump to: Research

24 pages, 1431 KiB  
Review
Role of Cell-Cell Junctions in Oesophageal Squamous Cell Carcinoma
by Qian-Rui Xu, Xiao-Hui Du, Ting-Ting Huang, Yu-Chun Zheng, Yu-Ling Li, Dan-Yi Huang, Hao-Qiang Dai, En-Min Li and Wang-Kai Fang
Biomolecules 2022, 12(10), 1378; https://doi.org/10.3390/biom12101378 - 26 Sep 2022
Cited by 7 | Viewed by 3391
Abstract
Cell–cell junctions comprise various structures, including adherens junctions, tight junctions, desmosomes, and gap junctions. They link cells to each other in tissues and regulate tissue homeostasis in critical cellular processes. Recent advances in cell–cell junction research have led to critical discoveries. Cell–cell adhesion [...] Read more.
Cell–cell junctions comprise various structures, including adherens junctions, tight junctions, desmosomes, and gap junctions. They link cells to each other in tissues and regulate tissue homeostasis in critical cellular processes. Recent advances in cell–cell junction research have led to critical discoveries. Cell–cell adhesion components are important for the invasion and metastasis of tumour cells, which are not only related to cell–cell adhesion changes, but they are also involved in critical molecular signal pathways. They are of great significance, especially given that relevant molecular mechanisms are being discovered, there are an increasing number of emerging biomarkers, targeted therapies are becoming a future therapeutic concern, and there is an increased number of therapeutic agents undergoing clinical trials. Oesophageal squamous cell carcinoma (ESCC), the most common histological subtype of oesophageal cancer, is one of the most common cancers to affect epithelial tissue. ESCC progression is accompanied by the abnormal expression or localisation of components at cell–cell junctions. This review will discuss the recent scientific developments related to the molecules at cell–cell junctions and their role in ESCC to offer valuable insights for readers, provide a global view of the relationships between position, construction, and function, and give a reference for future mechanistic studies, diagnoses, and therapeutic developments. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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22 pages, 8915 KiB  
Review
Progress in Gene-Editing Technology of Zebrafish
by Yanling Li, Zhipeng Jia, Shuchao Zhang and Xiaozhen He
Biomolecules 2021, 11(9), 1300; https://doi.org/10.3390/biom11091300 - 1 Sep 2021
Cited by 18 | Viewed by 6181
Abstract
As a vertebrate model, zebrafish (Danio rerio) plays a vital role in the field of life sciences. Recently, gene-editing technology has become increasingly innovative, significantly promoting scientific research on zebrafish. However, the implementation of these methods in a reasonable and accurate [...] Read more.
As a vertebrate model, zebrafish (Danio rerio) plays a vital role in the field of life sciences. Recently, gene-editing technology has become increasingly innovative, significantly promoting scientific research on zebrafish. However, the implementation of these methods in a reasonable and accurate manner to achieve efficient gene-editing remains challenging. In this review, we systematically summarize the development and latest progress in zebrafish gene-editing technology. Specifically, we outline trends in double-strand break-free genome modification and the prospective applications of fixed-point orientation transformation of any base at any location through a multi-method approach. Full article
(This article belongs to the Special Issue State-of-the-Art Biophysics, Biochemistry and Molecular Biology in China)
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