Computational and structural biotechnology journal最新文献

{"title":"Molecular dynamics simulations reveal key roles of the LIF receptor in the assembly of human LIF signaling complex","authors":"Bo Gao ,&nbsp;Hanrui Liu ,&nbsp;Mengkai Zhu ,&nbsp;Shun Zhang ,&nbsp;Meiniang Wang ,&nbsp;Yijun Ruan ,&nbsp;Yue Zheng","doi":"10.1016/j.csbj.2025.01.014","DOIUrl":"10.1016/j.csbj.2025.01.014","url":null,"abstract":"<div><div>Leukemia inhibitory factor (LIF) is a critical cytokine involved in various biological processes, including stem cell self-renewal, inflammation, and cancer progression. Structural studies have revealed how LIF forms a functional signaling complex. However, the dynamic binding pattern of the complex remains inadequately clarified. In this study, we employed molecular dynamics (MD) simulations to investigate the recognition and binding mechanisms of LIF, revealing a preferential affinity for LIF Receptor (LIFR) over gp130, attributable to a larger buried surface area at the LIF–LIFR interface. Key residues F178 and K181 in FXXK motif, along with K124 in LIF helix B, mediate hydrophobic interactions, hydrogen bonding and allosteric regulation, collectively stabilizing the LIF-LIFR interaction. We propose that the unique N-terminal extension of LIF enables signaling without requiring the additional receptor subunit beyond gp130 and LIFR, as verified by cell proliferation assays, distinguishing it from other cytokines in the LIF family. Additionally, analysis of domain fluctuations revealed that the LIF–LIFR interface undergoes less angular displacement compared to the LIF–gp130 interface, indicating a more stable interaction with LIFR. Together, these findings provide valuable insights into the molecular basis of LIF recognition and binding, offering a dynamic foundation for cytokine engineering.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"Pages 585-594"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143227405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AlphaFold 2, but not AlphaFold 3, predicts confident but unrealistic β-solenoid structures for repeat proteins","authors":"Olivia S. Pratt ,&nbsp;Luc G. Elliott ,&nbsp;Margaux Haon ,&nbsp;Shahram Mesdaghi ,&nbsp;Rebecca M. Price ,&nbsp;Adam J. Simpkin ,&nbsp;Daniel J. Rigden","doi":"10.1016/j.csbj.2025.01.016","DOIUrl":"10.1016/j.csbj.2025.01.016","url":null,"abstract":"<div><div>AlphaFold 2 (AF2) has revolutionised protein structure prediction but, like any new tool, its performance on specific classes of targets, especially those potentially under-represented in its training data, merits attention. Prompted by a highly confident prediction for a biologically meaningless, randomly permuted repeat sequence, we assessed AF2 performance on sequences composed of perfect repeats of random sequences of different lengths. AF2 frequently folds such sequences into β-solenoids which, while ascribed high confidence, contain unusual and implausible features such as internally stacked and uncompensated charged residues. A number of sequences confidently predicted as β-solenoids are predicted by other advanced methods as intrinsically disordered. The instability of some predictions is demonstrated by molecular dynamics. Importantly, other deep learning-based structure prediction tools predict different structures or β-solenoids with much lower confidence suggesting that AF2 alone has an unreasonable tendency to predict confident but unrealistic β-solenoids for perfect repeat sequences. The potential implications for structure prediction of natural (near-)perfect sequence repeat proteins are also explored.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"Pages 467-477"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143150061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a new data management system for the study of the gut microbiome of children who are small for their gestational age","authors":"Felix Manske ,&nbsp;Magdalena Durda-Masny ,&nbsp;Norbert Grundmann ,&nbsp;Jan Mazela ,&nbsp;Monika Englert-Golon ,&nbsp;Marta Szymankiewicz-Bręborowicz ,&nbsp;Joanna Ciomborowska-Basheer ,&nbsp;Izabela Makałowska ,&nbsp;Anita Szwed ,&nbsp;Wojciech Makałowski","doi":"10.1016/j.csbj.2024.12.031","DOIUrl":"10.1016/j.csbj.2024.12.031","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Microbiome studies aim to answer the following questions: which organisms are in the sample and what is their impact on the patient or the environment? To answer these questions, investigators have to perform comparative analyses on their classified sequences based on the collected metadata, such as treatment, condition of the patient, or the environment. The integrity of sequences, classifications, and metadata is paramount for the success of such studies. Still, the area of data management for the preliminary study results appears to be neglected. Here, we present the development of MetagenomicsDB (&lt;span&gt;&lt;span&gt;http://github.com/IOB-Muenster/MetagenomicsDB&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;; accessed 2024/12/18), a central data management system for the study of the gut microbiome in children who are small for their gestational age (SGA). Our system provided more flexibility to conduct study-specific analyses and to integrate specific external resources than existing and necessarily more generic solutions. It supports short or long read data produced by virtually any sequencing instrument targeting (parts of) popular marker genes, such as the 16S rRNA gene and its variable regions. Classifications of these reads from the MetaG and Kraken 2 software are supported. The main goals of the system are to store the pre-computed study data securely under concurrent load and to make downstream analyses accessible to all researchers, regardless of programming proficiency. Thus, after initial plausibility checks on the input data to reduce human error, data are stored in a relational database and can be continuously updated over the whole life time of the study. We used a modular approach for MetagenomicsDB with comprehensive tests verifying the expected behavior and extensively described the underlying rational which allows users to adapt the system to their needs. We advocate the use of MetagenomicsDB as the backend for a graphical web interface. We showcase the potential of this approach at the example of our study on SGA children (&lt;span&gt;&lt;span&gt;http://www.bioinformatics.uni-muenster.de/tools/metagenomicsDB&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;; accessed 2024/12/02). Without restrictions caused by the level of programming proficiency, our team members could explore the study data and optionally filter them using the graphical interface, before exporting the data in a format directly suitable for external normalization of read counts and statistical analyses. Study results could be conveniently and transparently shared with the public, as demonstrated here. Links to external resources facilitated literature search with regard to the SGA condition and assessments of the potential pathogenicity of taxa. Since different users will have different demands regarding features, data security, and web environments, we provide our implementation of the web interface as a visual example. By providing users with the MetagenomicsDB backend which constitute","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"Pages 221-232"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11759542/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143045230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tumour heterogeneity and personalized treatment screening based on single-cell transcriptomics","authors":"Xinying Zhang ,&nbsp;Jiajie Xie ,&nbsp;Zixin Yang ,&nbsp;Carisa Kwok Wai Yu ,&nbsp;Yaohua Hu ,&nbsp;Jing Qin","doi":"10.1016/j.csbj.2024.12.020","DOIUrl":"10.1016/j.csbj.2024.12.020","url":null,"abstract":"<div><div>According to global cancer statistics for the year 2022, based on updated estimates from the International Agency for Research on Cancer, there were approximately 20 million new cases of cancer in 2022 alongside 9.7 million related deaths. Lung, breast, colorectal, gastric, and liver cancers are the most common types of cancer. Despite advancements in anticancer drugs and optimised chemotherapy regimens that have improved cure rates for malignant tumours, the presence of tumour heterogeneity has resulted in substantial variations among patients in terms of disease progression, clinical response, sensitivity to therapy, and prognosis, posing significant challenges in attaining optimal therapeutic outcomes for each patient. Here, we collected five single-cell transcriptome datasets from patients with lung, breast, colorectal, gastric, and liver cancers and constructed multiple cancer blueprints of tumour cell heterogeneity. By integrating multiple bioinformatics analyses, we explored the biological differences underlying tumour cell heterogeneity at the single-cell level and identified tumour cell subcluster-specific biomarkers and potential therapeutic drugs for each subcluster. Interestingly, although tumour cell subpopulations exhibit dramatic differences within the same cancer type and between different cancers at both the genomic and transcriptomic levels, some demonstrate similar oncogenic pathway activities and phenotypes. Tumour cell subpopulations from the five cancers listed above were classified into three major groups corresponding to different treatment strategies. The findings of this study not only focus on the differences but also on the similarities among tumour cell subpopulations across different cancers, providing new insights for individualised therapy.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"Pages 307-320"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11773088/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143058192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Common themes in architecture and interactions of prokaryotic PolB2 and Pol V mutasomes inferred from in silico studies","authors":"Kęstutis Timinskas,&nbsp;Albertas Timinskas,&nbsp;Česlovas Venclovas","doi":"10.1016/j.csbj.2025.01.010","DOIUrl":"10.1016/j.csbj.2025.01.010","url":null,"abstract":"<div><div>Translesion DNA synthesis (TLS) is typically performed by inherently error-prone Y-family DNA polymerases. Extensively studied <em>Escherichia coli</em> Pol V mutasome, composed of UmuC, an UmuD′ dimer and RecA is an example of a multimeric Y-family TLS polymerase. Less commonly TLS is performed by DNA polymerases of other families. One of the most intriguing such cases in B-family is represented by archaeal PolB2 and its bacterial homologs. Previously thought to be catalytically inactive, PolB2 was recently shown to be absolutely required for targeted mutagenesis in <em>Sulfolobus islandicus</em>. However, the composition and structure of the PolB2 holoenzyme remain unknown. We used highly accurate AlphaFold structural models, coupled with protein sequence and genome context analysis to comprehensively characterize PolB2 and its associated proteins, PPB2, a small helical protein, and iRadA, a catalytically inactive Rad51 homolog. We showed that these three proteins can form a heteropentameric PolB2 complex featuring high confidence modeling scores. Unexpectedly, we found that PolB2 binds iRadA through a structural motif reminiscent of RadA/Rad51 oligomerization motif. In some mutasomes we identified clamp binding motifs, present in either iRadA or PolB2, but rarely in both. We also used AlphaFold to derive a three-dimensional structure of Pol V, for which the experimental structure remains unsolved thus precluding comprehensive understanding of its molecular mechanism. Our analysis showed that the structural features of Pol V explain many of the puzzling previous experimental results. Even though models of PolB2 and Pol V mutasomes are structurally different, we found striking similarities in their architectural organization and interactions.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"Pages 401-410"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143098554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An optimized deep-forest algorithm using a modified differential evolution optimization algorithm: A case of host-pathogen protein-protein interaction prediction","authors":"Jerry Emmanuel ,&nbsp;Itunuoluwa Isewon ,&nbsp;Jelili Oyelade","doi":"10.1016/j.csbj.2025.01.020","DOIUrl":"10.1016/j.csbj.2025.01.020","url":null,"abstract":"<div><div>Deep Forest employs forest structures and leverages deep architecture to learn feature vector information adaptively. However, deep forest-based models have limitations such as manual hyperparameter optimization and time and memory usage inefficiencies. Bayesian optimization is a widely used model-based hyperparameter optimization method. Evolutionary algorithms such as Differential Evolution (DE) have recently been introduced to improve Bayesian optimization’s acquisition function. Despite its effectiveness, DE has a significant drawback as it relies on randomly selecting indices from the population of target vectors to construct donor vectors in search of optimal solutions. This randomness is ineffective, as suboptimal or redundant indices may be selected. Therefore, in this research we developed a modified differential evolution (DE) acquisition function for improved host-pathogen protein-protein interaction prediction. The modified DE introduces a weighted and adaptive donor vector technique that selects the best-fitted donor vectors as opposed to the random approach. This modified optimization approach was implemented in a deep forest model for automatic hyperparameter optimization. The performance of the optimized deep forest model was evaluated on human-<em>Plasmodium falciparum</em> protein sequence datasets using 10-fold cross-validation. The results were compared with standard optimization methods such as traditional Bayesian optimization, genetic algorithms, evolutionary strategies, and other machine learning models. The optimized model achieved an accuracy of 89.3 %, outperforming other models across all metrics, including a sensitivity of 85.4 % and a precision of 91.6 %. Additionally, the optimized model predicted seven novel host-pathogen interactions. Finally, the model was implemented as a web application which is accessible at <span><span>http://dfh3pi.covenantuniversity.edu.ng</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"Pages 595-611"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143227501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biotechnological tools boost the functional diversity of DNA-based data storage systems","authors":"Xiaoyuan Xu ,&nbsp;Wen Wang ,&nbsp;Zhi Ping","doi":"10.1016/j.csbj.2025.02.002","DOIUrl":"10.1016/j.csbj.2025.02.002","url":null,"abstract":"<div><div>DNA-based data storage has emerged as a groundbreaking solution to the growing demand for efficient, high-density, and long-term data storage. It is attracting many researchers’ attention, who are implementing functions such as random access, searching, and data operations apart from the existing capabilities, including reading and writing. We summarize the recent progress of how biotechnological tools, based on sequence specificity, encapsulation, and high-dimensional structures of DNA molecules, facilitate the implementation of various functions. The limitations of using biochemical reactions that hinder the development of more precise and efficient information storage systems are also discussed. Future advancements in molecular biology and nanotechnology are expected to improve the architecture, scalability, and efficiency of DNA storage, positioning it as a sustainable and dynamic alternative to conventional data storage systems.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"Pages 624-630"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Repurposing thioridazine as a potential CD2068 inhibitor to mitigate antibiotic resistance in Clostridioides difficile infection","authors":"Methinee Pipatthana ,&nbsp;Matthew Phanchana ,&nbsp;Apiwat Sangphukieo ,&nbsp;Sitthivut Charoensutthivarakul ,&nbsp;Phurt Harnvoravongchai ,&nbsp;Surang Chankhamhaengdecha ,&nbsp;Pattaneeya Prangthip ,&nbsp;Pattanai Konpetch ,&nbsp;Chanakarn Sripong ,&nbsp;Sarawut Wongphayak ,&nbsp;Tavan Janvilisri","doi":"10.1016/j.csbj.2025.02.036","DOIUrl":"10.1016/j.csbj.2025.02.036","url":null,"abstract":"<div><div><em>Clostridioides difficile</em> infection (CDI) is a major public health issue, driven by antibiotic resistance and frequent recurrence. CD2068, an ABC protein in <em>C. difficile</em>, is associated with drug resistance, making it a potential target for novel therapies. This study explored FDA-approved non-antibiotic drugs for their ability to inhibit CD2068 through drug screening and experimental validation. Thioridazine exhibited moderate binding affinity to CD2068 and inhibited its ATP hydrolysis activity. It also suppressed the growth of multiple <em>C. difficile</em> ribotypes at 64–128 µg/mL, with rapid-killing effects. When combined with sub-MIC levels of standard antibiotics, thioridazine significantly reduced bacterial growth. In a mouse CDI model, thioridazine demonstrated potential in restoring gut microbial balance and improving survival, although it did not show superiority to vancomycin. These findings suggest that thioridazine has potential as a novel therapeutic for CDI, either as an adjunct to existing antibiotics or as part of a combination therapy to combat antibiotic resistance. Further research, including replication studies and dose optimization, is needed to fully evaluate thioridazine’s therapeutic potential.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"Pages 887-895"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"uniDINO: Assay-independent feature extraction for fluorescence microscopy images","authors":"Flavio M. Morelli ,&nbsp;Vladislav Kim ,&nbsp;Franziska Hecker ,&nbsp;Sven Geibel ,&nbsp;Paula A. Marín Zapata","doi":"10.1016/j.csbj.2025.02.020","DOIUrl":"10.1016/j.csbj.2025.02.020","url":null,"abstract":"<div><div>High-content imaging (HCI) enables the characterization of cellular states through the extraction of quantitative features from fluorescence microscopy images. Despite the widespread availability of HCI data, the development of generalizable feature extraction models remains challenging due to the heterogeneity of microscopy images, as experiments often differ in channel count, cell type, and assay conditions. To address these challenges, we introduce uniDINO, a generalist feature extraction model capable of handling images with an arbitrary number of channels. We train uniDINO on a dataset of over 900,000 single-channel images from diverse experimental contexts and concatenate single-channel features to generate embeddings for multi-channel images. Our extensive validation across varied datasets demonstrates that uniDINO outperforms traditional computer vision methods and transfer learning from natural images, while also providing interpretability through channel attribution. uniDINO offers an out-of-the-box, computationally efficient solution for feature extraction in fluorescence microscopy, with the potential to significantly accelerate the analysis of HCI datasets.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"Pages 928-936"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562664","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computationally derived structural insights into Rare Earth selectivity in lanmodulin and its variants","authors":"Karuna Anna Sajeevan ,&nbsp;Bibek Acharya ,&nbsp;Sakib Ferdous ,&nbsp;Dan M. Park ,&nbsp;Joseph A. Cotruvo Jr. ,&nbsp;Ratul Chowdhury","doi":"10.1016/j.csbj.2025.02.005","DOIUrl":"10.1016/j.csbj.2025.02.005","url":null,"abstract":"<div><div>Understanding rare earth element (REE) binding to proteins enables the engineering of selective protein-based ligands for precise REE recovery. Lanmodulin (LanM), with notable REE selectivity and picomolar binding affinity, is a promising candidate. This study shows that LanM variants employ distinct inter-residue interactions for REE binding. We detail the thermodynamics and structural aspects of binding events in wild-type (WT) <em>Methylorubrum extorquens</em> LanM and five EF-hand residue variants (4P₂A and 4D₉X, X = N, A, H, M), using protein variant structure prediction, molecular dynamics simulations and binding motif exploration. We demonstrate strong agreement between experimental binding measurements (apparent <em>K</em>_<em>d</em>) and <em>in silico</em> binding energy scores of WT, 4 P₂A, and 4D₉X LanMs. We systematically investigate the role of solvent dielectric, sample multiple force fields, and initial protein structure bias on metal ion-binding energetics. In addition, we identify amino acids outside the direct metal binding motif crucial for coordinating the binding events which is corroborated with experimental binding characteristics of 4D₉X variants. Computationally measured binding affinity with contribution from this secondary set of residues show agreement with the experimental <em>K</em>_d values and suggests how some point mutations can induce long-range structural perturbations to regulate metal ion-protein recognition and interactions. Finally, we analyze structural changes arising from alterations in side-chain flexibility of each amino acid on the protein backbone at the instant of metal binding and recognition – which manifests as altered helicity at a specific locus of the protein, a result that is corroborative of the observations from circular dichroism experiments.</div></div>","PeriodicalId":10715,"journal":{"name":"Computational and structural biotechnology journal","volume":"27 ","pages":"Pages 639-648"},"PeriodicalIF":4.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143428824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}