Current Research in Structural Biology最新文献

{"title":"Expose flexible conformations for intrinsically disordered protein","authors":"Jiaan Yang ,&nbsp;Wenxin Ji ,&nbsp;Wen Xiang Cheng ,&nbsp;Gang Wu ,&nbsp;Si Tong Sheng ,&nbsp;Peng Zhang ,&nbsp;Jun Lin ,&nbsp;Xiaojia Chen ,&nbsp;Qiong Shi","doi":"10.1016/j.crstbi.2025.100170","DOIUrl":"10.1016/j.crstbi.2025.100170","url":null,"abstract":"<div><div>The folding conformation of native protein has flexibility in different degrees, which may bring difficulty in presenting the structures, and also it causes complexity in understanding the relationship between structure and functions. Although many methods and databases provide information for intrinsically disordered protein (IDP), they are mainly limited to determining the intrinsically disordered regions (IDR) lacking knowledge of possible folding patterns. To overcome the barrier, the protein structure fingerprint technology has been developed, which includes PFSC (Protein Folding Shape Code) (Yang, 2008) and PFVM (Protein Folding Variation Matrix) (Yang et al., 2022) algorithms as well as FiveFold (Yang et al., 2025) approach for protein structure prediction, which are able explicitly to expose the possible conformational structures for intrinsically disordered protein. Three proteins, human cellular tumor antigen P53, human alpha-synuclein, and human protamine-2, are taken as samples for demonstration of how to obtain their folding conformation structures for intrinsically disordered proteins. The folding features for intrinsically disordered proteins with given structures may be revealed by the alignment of PFSC strings, and the folding possibility for intrinsically disordered proteins without a given structure can be exhibited by the local folding variations in PFVM. Furthermore, the multiple conformational 3D structures for intrinsically disordered protein can be predicted by FiveFold approach, which provides a significant tool further to understand the intrinsic disorder of proteins.</div></div>","PeriodicalId":10870,"journal":{"name":"Current Research in Structural Biology","volume":"10 ","pages":"Article 100170"},"PeriodicalIF":2.7,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144534378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Screening, docking, and molecular dynamics analysis of Mitragyna speciosa (Korth.) compounds for targeting HER2 in breast cancer","authors":"Nabila Hadiah Akbar ,&nbsp;Farendina Suarantika ,&nbsp;Taufik Muhammad Fakih ,&nbsp;Ariranur Haniffadli ,&nbsp;Khoirunnisa Muslimawati ,&nbsp;Aditya Maulana Perdana Putra","doi":"10.1016/j.crstbi.2025.100171","DOIUrl":"10.1016/j.crstbi.2025.100171","url":null,"abstract":"<div><div>Breast cancer remains the most commonly diagnosed cancer among women worldwide, with approximately 2.3 million new cases reported in 2022. In the United States alone, an estimated 310,720 new cases of female breast cancer are expected in 2024. HER2-positive breast cancer, characterized by the overexpression of the human epidermal growth factor receptor 2 (HER2), accounts for about 20 % of all breast cancer cases. The development of anti-HER2 therapies has significantly improved survival rates for patients with HER2-positive breast cancer. In this study, we employed in silico methods to evaluate the potential of natural alkaloids, Mitragynine and 7-Hydroxymitragynine, as HER2 inhibitors. Molecular docking revealed binding energies of −7.56 kcal/mol and −8.77 kcal/mol, respectively, with key interactions involving residues such as Leu726, Val734, Ala751, Lys753, Thr798, and Asp863. Molecular dynamics simulations demonstrated the stability of all three complexes, including Mitragynine, 7-Hydroxymitragynine, and Native (SYR127063), over the simulation period. Mitragynine exhibited stronger interaction stability, supported by a higher hydrogen bond occupancy of 39.19 %, compared to 4.32 % for 7-Hydroxymitragynine, while Native (SYR127063) displayed the highest occupancy at 49.66 %. MM-PBSA analysis further validated these findings, with Native (SYR127063) exhibiting the most favorable total binding energy of −163.448 ± 17.288 kJ/mol, followed by Mitragynine at −112.33 ± 22.41 kJ/mol, and 7-Hydroxymitragynine at −103.56 ± 15.61 kJ/mol. ADMET, physicochemical properties, and drug-likeness evaluations indicated that all compounds satisfy Lipinski, Ghose, Veber, Egan, and Muegge rules, confirming their suitability as lead-like molecules. Based on these findings, Mitragynine and 7-Hydroxymitragynine are promising candidates for HER2-targeted breast cancer therapy, with further experimental validation recommended to confirm their clinical potential.</div></div>","PeriodicalId":10870,"journal":{"name":"Current Research in Structural Biology","volume":"10 ","pages":"Article 100171"},"PeriodicalIF":2.7,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144366520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of the structural models of the human reference proteome: AlphaFold2 versus ESMFold","authors":"Matteo Manfredi ,&nbsp;Castrense Savojardo ,&nbsp;Pier Luigi Martelli ,&nbsp;Rita Casadio","doi":"10.1016/j.crstbi.2025.100167","DOIUrl":"10.1016/j.crstbi.2025.100167","url":null,"abstract":"<div><div>The human reference proteome is routinely modelled with predictive tools such as AlphaFold2. We recently released a database in which, for each human protein, the AlphaFold2 model is paired with its ESMFold counterpart. The two predictive methods take advantage of different procedures and it is interesting to compare them in relation to their quality, particularly when an experimental protein structure is not available. Here, we select three state-of-the-art quality assessment methods and we adopt them to compare 42,942 pairs of models. This procedure helps to find the most reliable models for human proteins, particularly for the set of proteins for which structure prediction methods give dissimilar results. We obtain that when predicted structures are similar, AlphaFold2 models consistently receive higher scores than the ESMFold counterparts. When predicted structures differ, the ESMFold model is the best choice for 49 % of the proteins according to a consensus of the three QA tools.</div></div>","PeriodicalId":10870,"journal":{"name":"Current Research in Structural Biology","volume":"9 ","pages":"Article 100167"},"PeriodicalIF":2.7,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144167366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigations on genomic, topological and structural properties of diguanylate cyclases involved in Vibrio cholerae biofilm signalling using in silico techniques: Promising drug targets in combating cholera","authors":"Tuhin Manna ,&nbsp;Subhamoy Dey ,&nbsp;Monalisha Karmakar ,&nbsp;Amiya Kumar Panda ,&nbsp;Chandradipa Ghosh","doi":"10.1016/j.crstbi.2025.100166","DOIUrl":"10.1016/j.crstbi.2025.100166","url":null,"abstract":"<div><div>During various stages of its life cycle, <em>Vibrio cholerae</em> initiate biofilm signalling cascade. Intercellular high level of the signalling nucleotide 3′-5′ cyclic dimeric guanosine monophosphate (c-di-GMP), synthesized by diguanylate cyclases (DGCs) from its precursor molecule GTP, is crucial for biofilm formation. Present study endeavours to <em>in silico</em> approaches in evaluating genomic, physicochemical, topological and functional properties of six c-di-GMP regulatory DGCs (CdgA, CdgH, CdgK, CdgL, CdgM, VpvC) of <em>V. cholerae</em>. Genomic investigations unveiled that codon preferences were inclined towards AU ending over GC ending codons and overall GC content ranged from 44.6 to 49.5 with codon adaptation index ranging from 0.707 to 0.783. Topological analyses deciphered the presence of transmembrane domains in all proteins. All the DGCs were acidic, hydrophilic and thermostable. Only CdgA, CdgH and VpvC were predicted to be stable during <em>in vitro</em> conditions. Non-polar amino acids with leucine being the most abundant amino acid among these DGCs with α-helix as the predominant secondary structure, responsible for forming the transmembrane regions by secondary structure analysis. Tertiary structures of the proteins were obtained by computation using AlphaFold and trRosetta. Predicted structures by both the servers were compared in various aspects using PROCHECK, ERRAT and Modfold8 servers. Selected 3D structures were refined using GalaxyRefine. InterPro Scan revealed presence of a conserved GGDEF domain in all DGCs and predicted the active site residues in the GGDEF domain. Molecular docking studies using CB-DOCK 2 tool revealed that among the DGCs, VpvC exhibited highest affinity for GTP (−5.6 kcal/mol), which was closely followed by CdgL (−5.5 kcal/mol). MD simulations depicted all DGC-GTP complexes to be stable due to its considerably low eigenvalues. Such studies are considered to provide maiden insights into the genomic and structural properties of <em>V. cholerae</em> DGCs, actively involved in biofilm signalling systems, and it is projected to be beneficial in the discovery of novel DGC inhibitors that can target and downregulate the c-di-GMP regulatory system to develop anti-biofilm strategies against the cholera pathogen.</div></div>","PeriodicalId":10870,"journal":{"name":"Current Research in Structural Biology","volume":"9 ","pages":"Article 100166"},"PeriodicalIF":2.7,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The structural basis of the G protein–coupled receptor and ion channel axis","authors":"Yulin Luo ,&nbsp;Liping Sun ,&nbsp;Yao Peng","doi":"10.1016/j.crstbi.2025.100165","DOIUrl":"10.1016/j.crstbi.2025.100165","url":null,"abstract":"<div><div>Sensory neurons play an essential role in recognizing and responding to detrimental, irritating, and inflammatory stimuli from our surroundings, such as pain, itch, cough, and neurogenic inflammation. The transduction of these physiological signals is chiefly mediated by G protein-coupled receptors (GPCRs) and ion channels. The binding of ligands to GPCRs triggers a signaling cascade, recruiting G proteins or β-arrestins, which subsequently interact with ion channels (e.g., GIRK and TRP channels). This interaction leads to the sensitization and activation of these channels, initiating the neuron's protective mechanisms. This review delves into the complex interplay between GPCRs and ion channels that underpin these physiological processes, with a particular focus on the role of structural biology in enhancing our comprehension. Through unraveling the intricacies of the GPCR-ion channel axis, we aim to shed light on the sophisticated intermolecular dynamics within these pivotal membrane protein families, ultimately guiding the development of precise therapeutic interventions.</div></div>","PeriodicalId":10870,"journal":{"name":"Current Research in Structural Biology","volume":"9 ","pages":"Article 100165"},"PeriodicalIF":2.7,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-based quality assessment methods for protein structure models from cryo-EM","authors":"Han Zhu ,&nbsp;Genki Terashi ,&nbsp;Farhanaz Farheen ,&nbsp;Tsukasa Nakamura ,&nbsp;Daisuke Kihara","doi":"10.1016/j.crstbi.2025.100164","DOIUrl":"10.1016/j.crstbi.2025.100164","url":null,"abstract":"<div><div>Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology, with an increasing number of structures being determined by cryo-EM each year, many at higher resolutions. However, challenges remain in accurately interpreting cryo-EM maps. Inaccuracies can arise in regions of locally low resolution, where manual model building is more prone to errors. Validation scores for structure models have been developed to assess both the compatibility between map density and the structure, as well as the geometric and stereochemical properties of protein models. Recent advancements have introduced artificial intelligence (AI) into this field. These emerging AI-driven tools offer unique capabilities in the validation and refinement of cryo-EM-derived protein atomic models, potentially leading to more accurate protein structures and deeper insights into complex biological systems.</div></div>","PeriodicalId":10870,"journal":{"name":"Current Research in Structural Biology","volume":"9 ","pages":"Article 100164"},"PeriodicalIF":2.7,"publicationDate":"2025-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143193904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An easy-to-use three-dimensional protein-structure-prediction online platform \"DPL3D\" based on deep learning algorithms","authors":"Yunlong Gao ,&nbsp;He Wang ,&nbsp;Jiapeng Zhou ,&nbsp;Yan Yang","doi":"10.1016/j.crstbi.2024.100163","DOIUrl":"10.1016/j.crstbi.2024.100163","url":null,"abstract":"<div><div>The change in the three-dimensional (3D) structure of a protein can affect its own function or interaction with other protein(s), which may lead to disease(s). Gene mutations, especially missense mutations, are the main cause of changes in protein structure. Due to the lack of protein crystal structure data, about three-quarters of human mutant proteins cannot be predicted or accurately predicted, and the pathogenicity of missense mutations can only be indirectly evaluated by evolutionary conservation. Recently, many computational methods have been developed to predict protein 3D structures with accuracy comparable to experiments. This progress enables the information of structural biology to be further utilized by clinicians. Thus, we developed a user-friendly platform named DPL3D (<span><span>http://nsbio.tech:3000</span><svg><path></path></svg></span>) which can predict and visualize the 3D structure of mutant proteins. The crystal structure and other information of proteins were downloaded together with the software including AlphaFold 2, RoseTTAFold, RoseTTAFold All-Atom, and trRosettaX-Single. We implemented a query module for 210,180 molecular structures, including 52,248 human proteins. Visualization of protein two-dimensional (2D) and 3D structure prediction can be generated via LiteMol automatically or manually and interactively. This platform will allow users to easily and quickly retrieve large-scale structural information for biological discovery.</div></div>","PeriodicalId":10870,"journal":{"name":"Current Research in Structural Biology","volume":"9 ","pages":"Article 100163"},"PeriodicalIF":2.7,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11761317/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143045823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In silico approaches for developing sesquiterpene derivatives as antagonists of human nicotinic acetylcholine receptors (nAChRs) for nicotine addiction treatment","authors":"Taufik Muhammad Fakih ,&nbsp;Aden Dhana Rizkita ,&nbsp;Sintia Ayu Dewi ,&nbsp;Muchtaridi Muchtaridi","doi":"10.1016/j.crstbi.2024.100162","DOIUrl":"10.1016/j.crstbi.2024.100162","url":null,"abstract":"<div><div>Cinnamomum, a genus within the Lauraceae family, has gained global recognition due to its wide-ranging utility. Extensive research has been dedicated to exploring its phytochemical composition and pharmacological effects. Notably, the uniqueness of Cinnamomum lies in its terpenoid content, characterized by distinctive structures and significant biological implications. An intriguing discovery is that sesquiterpene compounds originating from Cinnamomum possess the capacity to function as antagonists for human nicotinic acetylcholine receptors (nAChRs), specifically the nAChRÿ3 subtype, rendering them potential candidates for nicotine replacement therapy (NRT) to aid active smokers. This investigation employed molecular docking and molecular dynamics simulations to assess the inhibitory effects of these compounds on nAChRÿ3. Among the 55 compounds examined, Dihydroxyeudesmene, Gibberodione, and Germacrene-E exhibited the highest binding affinities. These compounds demonstrated robust interactions with the nAChRÿ3 receptor, as evidenced by elevated molecular mechanics general surface area (MM/GBSA) values (ΔG Bind = Dihydroxyeudesmene: −36.45 kcal/mol, Gibberodione: −36.51 kcal/mol, and Germacrene-E: −36.51 kcal/mol). Molecular dynamics simulations further confirmed the stability of these three compounds, indicating their potential to effectively compete with native ligands. However, comprehensive in vitro, in vivo, and clinical investigations are imperative to ascertain the efficacy of these promising therapeutic candidates.</div></div>","PeriodicalId":10870,"journal":{"name":"Current Research in Structural Biology","volume":"9 ","pages":"Article 100162"},"PeriodicalIF":2.7,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11753972/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143045827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular structural modeling and physical characteristics of anti-breast cancer drugs via some novel topological descriptors and regression models","authors":"Summeira Meharban ,&nbsp;Asad Ullah ,&nbsp;Shahid Zaman ,&nbsp;Anila Hamraz ,&nbsp;Abdul Razaq","doi":"10.1016/j.crstbi.2024.100134","DOIUrl":"https://doi.org/10.1016/j.crstbi.2024.100134","url":null,"abstract":"<div><p>Research is continuously being pursued to treat cancer patients and prevent the disease by developing new medicines. However, experimental drug design and development is a costly, time-consuming, and challenging process. Alternatively, computational and mathematical techniques play an important role in optimally achieving this goal. Among these mathematical techniques, topological indices (TIs) have many applications in the drugs used for the treatment of breast cancer. TIs can be utilized to forecast the effectiveness of drugs by providing molecular structure information and related properties of the drugs. In addition, these can assist in the design and discovery of new drugs by providing insights into the structure-property/structure-activity relationships. In this article, a Quantitative Structure Property Relationship (QSPR) analysis is carried out using some novel degree-based molecular descriptors and regression models to predict various properties (such as boiling point, melting point, enthalpy, flashpoint, molar refraction, molar volume, and polarizability) of 14 drugs used for the breast cancer treatment. The molecular structures of these drugs are topologically modeled through vertex and edge partitioning techniques of graph theory, and then linear regression models are developed to correlate the computed values with the experimental properties of the drugs to investigate the performance of TIs in predicting these properties. The results confirmed the potential of the considered topological indices as a tool for drug discovery and design in the field of breast cancer treatment.</p></div>","PeriodicalId":10870,"journal":{"name":"Current Research in Structural Biology","volume":"7 ","pages":"Article 100134"},"PeriodicalIF":2.8,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665928X24000114/pdfft?md5=4e0b564e56e1dd72c10d1bc8f75eba85&pid=1-s2.0-S2665928X24000114-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140135141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Specific binding of G-quadruplex in SARS-CoV-2 RNA by RHAU peptide","authors":"Le Tuan Anh Nguyen ,&nbsp;Thao Thu Thi Nguyen ,&nbsp;Dung Thanh Dang","doi":"10.1016/j.crstbi.2024.100126","DOIUrl":"10.1016/j.crstbi.2024.100126","url":null,"abstract":"<div><p>G-quadruplexes (G4s) are reported to present on the SARS-CoV-2 RNA genome and control various viral activities. Specific ligands targeting those viral nucleic acid structures could be investigated as promising detection methods or antiviral reagents to suppress this menacing virus. Herein, we demonstrate the binding between a G4 structure in the RNA of SARS-CoV-2 and a fluorescent probe created by fusing a parallel-G4 specific RHAU53 and a cyan fluorescent protein. The specific binding of G4 in SARS-CoV-2 by RHAU peptide was easily detected under the fluorescence spectrometer. The drawbacks of this approach and potential solutions are also discussed.</p></div>","PeriodicalId":10870,"journal":{"name":"Current Research in Structural Biology","volume":"7 ","pages":"Article 100126"},"PeriodicalIF":2.8,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2665928X24000035/pdfft?md5=36e9958a61277baeaf9b9c540a395f47&pid=1-s2.0-S2665928X24000035-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139393094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}