Proteins-Structure Function and Bioinformatics最新文献

{"title":"Enhancing Functional Protein Design Using Heuristic Optimization and Deep Learning for Anti-Inflammatory and Gene Therapy Applications.","authors":"Ayşenur Soytürk Patat, Özkan Ufuk Nalbantoğlu","doi":"10.1002/prot.26810","DOIUrl":"10.1002/prot.26810","url":null,"abstract":"<p><p>Protein sequence design is a highly challenging task, aimed at discovering new proteins that are more functional and producible under laboratory conditions than their natural counterparts. Deep learning-based approaches developed to address this problem have achieved significant success. However, these approaches often do not adequately emphasize the functional properties of proteins. In this study, we developed a heuristic optimization method to enhance key functionalities such as solubility, flexibility, and stability, while preserving the structural integrity of proteins. This method aims to reduce laboratory demands by enabling a design that is both functional and structurally sound. This approach is particularly valuable for the synthetic production of proteins with anti-inflammatory properties and those used in gene therapy. The designed proteins were initially evaluated for their ability to preserve natural structures using recovery and confidence metrics, followed by assessments with the AlphaFold tool. Additionally, natural protein sequences were mutated using a genetic algorithm and compared with those designed by our method. The results demonstrate that the protein sequences generated by our method exhibit much greater similarity to native protein sequences and structures. The code and sequences for the designed proteins are available at https://github.com/aysenursoyturk/HMHO.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":"1238-1256"},"PeriodicalIF":3.2,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12127714/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143476550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shear-Induced Structural Changes Drive Amorphous Aggregate Formation of Human Insulin.","authors":"Chinmaya Panda, Sachin Kumar, Sharad Gupta, Lalit M Pandey","doi":"10.1002/prot.70015","DOIUrl":"https://doi.org/10.1002/prot.70015","url":null,"abstract":"<p><p>The aggregation of protein-based biopharmaceutical formulations constitutes a major challenge in the pharmaceutical industry, where physicochemical stressors, viz., temperature, pH, shear, and high concentrations, synergistically compromise structural integrity, stability, and therapeutic efficacy. While human insulin (HI) aggregation under pH and temperature variations has been extensively studied, the combined effects of pH, shear, and thermal stress on its conformational behavior remain underexplored. This study assessed the HI aggregation kinetics under varying (1-1000 s^-1) and constant shear rates (50, 100, 300, and 500 s^-1) at four temperatures (25°C, 37°C, 50°C, and 60°C). At 60°C and low pH, HI exhibited non-Newtonian rheological behavior, initially undergoing shear thickening due to higher-order structure formation, followed by shear thinning as aggregates fragmented. Shear-induced dissipation energy exceeded the free energy of unfolding (ΔG_unfold) of HI, catalyzing the unfolding, aberrant β-sheet propagation, and eventual aggregate formation. Fluorometry employing thioflavin-T and intrinsic tyrosine fluorescence indicated a time-dependent effect of shear in insulin unfolding. Thioflavin fluorescence showed an 80-fold reduction in fibrillation lag time, highlighting shear as a potent catalyst of aggregation. Tyr^A19 and Tyr^B26 mediated interchain interactions supported fluorometric findings. Circular dichroism revealed α-helix content plummeting to 16% within 2 min at 500 s^-1 shear at 60°C. Transmission electron microscopic studies showed fibrillar-to-amorphous aggregate transition under shear. Native PAGE and BCA assays confirmed monomer depletion, while cytotoxicity studies indicated 53% cell viability after 10 min of HI incubation at 60°C and 500 s^-1 shear. These findings emphasize the necessity of stringent control of thermomechanical stressors in insulin bioprocessing, transport, and storage to mitigate aggregation-related complications to enhance biopharmaceutical stability.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144531318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced MD Simulation Methods Uncover Mechanisms of SH3 Domain Functions in Small GTPase Signaling.","authors":"Muslum Yildiz","doi":"10.1002/prot.70006","DOIUrl":"https://doi.org/10.1002/prot.70006","url":null,"abstract":"<p><p>The protein complex comprising the SH3 domain and DLC1 proteins plays a vital role in various cellular processes and diseases, including cancer. Essential dynamics for the stability of this complex, which cannot be elucidated by static X-ray crystal structures, have significant implications for understanding cellular physiology and critical diseases. We thoroughly investigated this complex using advanced molecular dynamics, Adaptively Biased Force MD (ABF-MD), and conventional MD (cMD) simulation methods. Radial distribution function (RDF) calculations demonstrate that the interaction between the two proteins is highly specific, as all mutations exhibit a single peak, indicating no additional interacting sites. The probabilities of two key interactions, Glu298-Arg1114 and Lys292-Leu1239, were observed to increase in cancer-related mutations but not in other mutations known to disrupt complex formation. Using a Markov State Model (MSM), we identified a key intermediate in the wild type that was absent in other variants. Correlation analysis of deviations in distances among key interacting residues showed values greater than 0.95, indicating cooperativity among interacting residues. cMD simulations also revealed increased distance values between interacting residues in complex-disrupting mutations, but not in cancer-related mutations. Principal component analysis (PCA) further revealed significant conformational changes, indicating important distinct conformations potentially involved in complex formation. Specifically, the loop region between residues 1236-1261 exhibits distinct conformations upon mutations among variants. This distinct conformation, particularly in the L1267D mutation, leads to the displacement of the SH3 domain from the binding site, which may contribute to complex destabilization. Additionally, PCA analysis suggests that complex-disrupting mutations significantly increase the ability of the loop region to explore different conformations compared to the wild type. In contrast, the cancer-related mutation, V1227M, does not significantly affect protein flexibility or its capacity to stay in a stable conformation. The binding energy analysis reveals that the wild-type DLC1 complex has moderate stability (-8.87 ± 1.31 kcal/mol), and the V1227M variant shows the most stable binding (-6.89 ± 1.04 kcal/mol) among other mutants. In contrast, L1267D, R1114A, and R1114E variants exhibit weaker binding affinities (-5.89 ± 1.01, -3.18 ± 1.04, and - 0.58 ± 1.11 kcal/mol, respectively), indicating reduced complex stability.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144499680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the Context-Dependent Phase Separation of Human HOX Transcription Factors.","authors":"Srijeeb Karmakar, Jishnu Manglam, Krishna Kant, Soumya De","doi":"10.1002/prot.70009","DOIUrl":"https://doi.org/10.1002/prot.70009","url":null,"abstract":"<p><p>Homeobox (HOX) transcription factors are essential for gene expression during embryonic development and hematopoiesis, and their dysregulation is potentially linked to several types of cancer. Recently, liquid-liquid phase separation (LLPS) has been proposed as a key mechanism in various physiological processes. Using computational tools and molecular dynamics (MD) simulations, we found that the human HOX transcription factors have a strong propensity to undergo phase separation. The large disordered regions of the HOX factors drive phase separation via a fly-casting like mechanism, where the terminal segments of the disordered regions extend out to interact with and draw in neighboring molecules. Also, formation of short transient secondary structures in the disordered regions was observed in MD simulations. The sequences of the transient structures match short linear motifs (SliMs), which are hotspots for interaction with partner molecules. Thus, the HOX transcription factors may act as scaffold proteins and recruit partner molecules, such as TALE proteins, in the biomolecular cocondensates, via interaction with these preformed structural elements. A total of 352 SliMs were mapped with the droplet-promoting disordered regions of the human HOX transcription factors, which indicated an abundance of possible binding sites. These results have been curated in an interactive webpage (https://pel.iitkgp.ac.in/) that generates motif maps, indicating the location of the motifs in the disordered regions of the HOX transcription factors. Overall, this work highlights the potential of phase separation of the human HOX factors, particularly through the lens of context-dependent interactions, which may lead to novel insights into HOX-related processes.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144487252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interaction of Phosphorylated C5aR1 With β-Arrestin1: A Comparative Structural Modeling Study.","authors":"Pulkit Kr Gupta, Aditi Singh, Soumendra Rana","doi":"10.1002/prot.70007","DOIUrl":"https://doi.org/10.1002/prot.70007","url":null,"abstract":"<p><p>The complement system is an essential element of the immune response, significantly contributing to the body's defense against pathogens by augmenting inflammation, opsonizing pathogens, and promoting cell lysis. The C5aR1 and C5aR2, which interact with the highly potent complement fragment C5a, are a crucial part of this system. C5aR1, a classical G protein-coupled receptor (GPCR), activates G-proteins upon binding C5a and triggers the proinflammatory signaling cascades. However, C5aR1, upon phosphorylation, also interacts with β-arrestins, which desensitize G-protein signaling and activate alternative signaling pathways, thereby influencing immune responses and triggering receptor internalization. Thus, structurally establishing the interaction between the binary complex of C5a-C5aR1 and β-arrestins is essential for effectively targeting C5aR1 signaling pathways. Notably, we have earlier elaborated the model ternary complex of unphosphorylated C5aR2 with β-arrestin1. In the absence of structural data related to the fully active ternary complex of C5a-C5aR1-β-arrestin1, the current study hypothesizes two plausible models (\"front-end\" and \"back-end\"), focusing on the cytosolic side interaction of the fully phosphorylated C-terminus peptide stretch of C5aR1 with the β-arrestin1, as the interaction of this section is not resolved in any reported ternary complexes of other GPCRs, including C5aR1. The two model complexes have been subjected to 1 μs of molecular dynamics (MD) simulations each and further compared energetically for their physical sustainability. The proposed ternary model complexes of C5a-C5aR1-β-arrestin1 fill the gulf and enhance the existing structural knowledge regarding the interactions of β-arrestins with C5aR1, which may open new avenues for targeting G-protein or β-arrestin-biased signaling.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144477991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Results of the Protein Engineering Tournament: An Open Science Benchmark for Protein Modeling and Design.","authors":"Chase Armer, Hassan Kane, Dana L Cortade, Henning Redestig, David A Estell, Adil Yusuf, Nathan Rollins, Aviv Spinner, Debora Marks, T J Brunette, Peter J Kelly, Erika DeBenedictis","doi":"10.1002/prot.70008","DOIUrl":"https://doi.org/10.1002/prot.70008","url":null,"abstract":"<p><p>The grand challenge of protein engineering is the development of computational models to characterize and generate protein sequences for arbitrary functions. Progress is limited by lack of (1) benchmarking opportunities, (2) large protein function datasets, and (3) access to experimental protein characterization. We introduce the Protein Engineering Tournament-a fully-remote competition designed to foster the development and evaluation of computational approaches in protein engineering. The tournament consists of a predictive round, predicting biophysical properties from protein sequences, followed by a generative round where novel protein sequences are designed, expressed, and characterized using automated methods. Upon completion, all datasets, experimental protocols, and methods are made publicly available. We detail the structure and outcomes of a pilot Tournament involving seven protein design teams, powered by six multi-objective datasets, with experimental characterization by our partner, International Flavors and Fragrances. Forthcoming Protein Engineering Tournaments aim to mobilize the scientific community towards transparent evaluation of progress in the field.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144369660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Graph_RG: Dominating CASP16's Small Molecule Affinity Prediction Subcategory-A Pose-Free Framework for Billion-Scale Virtual Screening.","authors":"Haiping Zhang","doi":"10.1002/prot.70010","DOIUrl":"10.1002/prot.70010","url":null,"abstract":"<p><p>Protein-ligand interaction prediction is pivotal in early-stage drug development, enabling large-scale virtual screening, drug optimization, and reverse target searching. In this work, we present Graph_RG, our top-performing model in the CASP16 small molecule track's protein-ligand affinity prediction category, achieving a N-weighted Kendall's Tau of 0.42-significantly outperforming other submissions (second-best: 0.36). Beyond accuracy, Graph_RG is noncomplex dependent, hence exhibits exceptional computational efficiency, operating > 100 000× faster than conformation-search dependent prediction methods, thus enabling billion- to 10-billion-scale screening on standard servers. We further discuss the potential improvements for Graph_RG, including dataset optimization, atomic vector representation enhancements, and model architecture upgrades. We also introduce the potential broader applications in large-scale drug screening, reverse target identification, and GPCR-specific drug discovery. We also point out the development of an interactive web platform hosting Graph_RG and its derivative models to enhance accessibility. By integrating community feedback and iterative model refinement, this initiative bridges the gap between AI-driven predictions and practical drug discovery, fostering advancements in both computational methodologies and biomedical applications.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144334487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a Novel Method for Representing 3D Structures of Nucleotides Using the Concept of the TSR Algorithm and Evaluation of the Method Through Studying Specific Interactions Between DNAs and p53.","authors":"Krishna Rauniyar, Tarikul I Milon, Poorya Khajouie, Ramy Alabdulkarim, Yuwu Chen, Sarika Kondra, Vijay Raghavan, Wu Xu","doi":"10.1002/prot.70005","DOIUrl":"https://doi.org/10.1002/prot.70005","url":null,"abstract":"<p><p>Prior evidence has suggested that interactions between transcription factor amino acids and DNA nucleotides follow a recognition code. However, the recognition code remains poorly understood due to the inability of currently available computational methods to quantify and interpret subtle conformational changes of transcription factor amino acids and DNA nucleotides. In this study, we have developed a novel way of representing 3D structures of nucleotides of DNAs or RNAs by adapting the concept of the Triangular Spatial Relationship (TSR) from the TSR-based computational method originally designed for protein 3D structural comparisons. Representing nucleotide 3D structures using a vector of integers (TSR keys) is unique. We chose p53 as an example of a transcription factor to establish the structural basis for comprehending the recognition code. By taking advantage of the proposed representation of nucleotide 3D structures, we were able to demonstrate the structural differences between the nucleotides that interact with p53 and those that do not interact with p53 as well as the structural differences between the amino acids of p53 that interact with DNA and those that do not interact with DNA. In summary, this study demonstrates the capabilities of an advanced computational methodology with notable advantages for representing and quantifying nucleotide structures and for providing a comprehensive understanding of the structural specificity existing between p53 proteins and their binding DNAs. Such an analysis can also be extended to complexes involving other transcription factor-DNA pairs.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144327888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cyan Thermal Proteins Derived From Thermal Green Protein.","authors":"Acacia Jurkowski, Dhruv Sitapara, Austin Brown, Samantha Ball, Trey Norman, Anastasia Jones, Jessica Gilbert, Taryn Criblez, Andrew Yates, Shiv Bansal, Natasha M DeVore","doi":"10.1002/prot.70003","DOIUrl":"https://doi.org/10.1002/prot.70003","url":null,"abstract":"<p><p>Thermal green protein (TGP) is a consensus derived green fluorescent protein designed with extreme thermostability, high pH and chemical stability, as well as high quantum yield for use in more severe conditions. Our goal is to design a cyan version of TGP that maintains these characteristics. We were able to shift the fluorescence wavelength of TGP from green to cyan creating CTP 0.0 by incorporating a single chromophore mutation, Y67W, but this mutation also decreased the quantum yield to 0.056. Further mutations were incorporated to increase the quantum yield through incorporating hydrogen bonding interactions to the chromophore and to remove a kink present in beta strand seven. These proteins, CTP 0.5 (Y67W I199T) and CTP 1.0 (Y67W I199T W143L E144I P145D S146A), increased the quantum yield to 0.07 and 0.37, respectively and improved stability characteristics. CTP 0.75 incorporated another chromophore mutation into CTP 1.0 (Q66E) to increase the stability characteristics but decreased the quantum yield to 0.22. The CTP 1.0 cyan protein was also compared to mTurquoise2, one of the current best cyan fluorescent proteins based on GFP. CTP 1.0 had comparable chemical stability and improved acid stability. Crystal structures were solved for CTP 0.5 at pH 6.5 (2.00 Å), CTP 1.0 at pH 6.5 (1.70 Å), CTP 1.0 at pH 8.5 (1.60 Å), and CTP 0.75 at pH 7.4 (1.70 Å). Structural analysis of the proteins showed that while improvement to beta strand seven was unsuccessful, the increase in quantum yield is likely due to the incorporation of the T199 residue and subsequent hydrogen bonding interaction improvements with the chromophore.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144327887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative Dynamics Enables Discovery of Embedded Bacterial Ferredoxin Domains in Large Redox Enzymes.","authors":"Jan A Siess, Vikas Nanda","doi":"10.1002/prot.70004","DOIUrl":"https://doi.org/10.1002/prot.70004","url":null,"abstract":"<p><p>Bacterial ferredoxins are small iron-sulfur binding proteins that function as soluble electron shuttles between redox enzymes in the cell. Their simple 2×(β-α-β) fold, central metabolic function, and ubiquity across all kingdoms of life have led to the proposal that ferredoxins were likely among the earliest proteins. Today, ferredoxin-like folds are embedded in large, multidomain enzymes, suggesting ancient gene duplication and fusion events. In some cases, these embedded domains may have scant sequence or even structural homology to soluble counterparts, challenging the use of traditional phylogenetic tools to establish evolutionary relationships. In this study, we identify fragments of bacterial ferredoxins within larger oxidoreductases by integrating comparative sequence, structure, and dynamical attributes. Dynamics are computed using an elastic network model and analyzed for similarity of major normal modes. Using comparative dynamics, fragments of ferredoxin domains are found within larger proteins, even in cases of limited structural homology. This study also reveals a non-linear relationship between dynamical and structural similarities, suggesting that protein dynamics are more constrained than structure through evolutionary time. We propose that dynamical similarity is indicative of functional similarity, and since nature selects for function, that the inclusion of dynamical similarity, in addition to sequence and structure similarities, provides a more robust framework for inferring homology. Inclusion of dynamical attributes in comparative analysis will lead to a greater understanding of the deep-time evolution of modern protein nanomachines.</p>","PeriodicalId":56271,"journal":{"name":"Proteins-Structure Function and Bioinformatics","volume":" ","pages":""},"PeriodicalIF":3.2,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144327886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}