Large protein databases reveal structural complementarity and functional locality DOI Creative Commons
Paweł Szczerbiak, Lukasz M. Szydlowski, Witold Wydmański

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Авг. 17, 2024

Abstract Recent breakthroughs in protein structure prediction have led to an unprecedented surge high-quality 3D models, highlighting the need for efficient computational solutions manage and analyze this wealth of structural data. In our work, we comprehensively examine clusters obtained from AlphaFold Protein Structure Database (AFDB), a subset ESMAtlas, Microbiome Immunity Project (MIP). We create single cohesive low-dimensional representation resulting space. Our results show that, while each database occupies distinct regions within space, they collectively exhibit significant overlap their functional profiles. High-level biological functions tend cluster particular regions, revealing shared landscape despite diverse sources By creating single, space integrating data sources, localizing annotations providing open-access web-server exploration, work offers insights future research concerning sequence-structure-function relationships, enabling various questions be asked about taxonomic assignments, environmental factors, or specificity. This approach is generalizable other datasets, further discovery beyond findings presented here.

Язык: Английский

AFflecto: A web server to generate conformational ensembles of flexible proteins from AlphaFold models DOI Creative Commons
Mátyás Pajkos,

Ilinka Clerc,

Christophe Zanon

и другие.

Journal of Molecular Biology, Год журнала: 2025, Номер unknown, С. 169003 - 169003

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

2
The 2025 Nucleic Acids Research database issue and the online molecular biology database collection DOI Creative Commons
Daniel J. Rigden, Xosé M. Fernández

Nucleic Acids Research, Год журнала: 2024, Номер 53(D1), С. D1 - D9

Опубликована: Дек. 10, 2024

The 2025 Nucleic Acids Research database issue contains 185 papers spanning biology and related areas. Seventy three new databases are covered, while resources previously described in the account for 101 update articles. Databases most recently published elsewhere a further 11 papers. acid include EXPRESSO multi-omics of 3D genome structure (this issue's chosen Breakthrough Resource Article) NAIRDB Fourier transform infrared data. New protein predictions human isoforms at ASpdb viral proteins BFVD. UniProt, Pfam InterPro have all provided updates: metabolism signalling covered by descriptions STRING, KEGG CAZy, updated microbe-oriented Enterobase, VFDB PHI-base. Biomedical research is supported, among others, ClinVar, PubChem DrugMAP. Genomics-related Ensembl, UCSC Genome Browser dbSNP. plant cover Solanaceae (SolR) Asteraceae (AMIR) families an from NCBI Taxonomy also features. Database Issue freely available on website (https://academic.oup.com/nar). At NAR online Molecular Biology Collection (http://www.oxfordjournals.org/nar/database/c/), 932 entries been reviewed last year, 74 added 226 discontinued URLs eliminated bringing current total to 2236 databases.

Язык: Английский

Процитировано

3
Functional and structural insights into α-L-Rhamnosidase: cloning, characterization, and decoding evolutionary constraints through structural motif DOI

Yupeng Liang,

Yalan Zhao,

Zhongwei Yin

и другие.

Archives of Microbiology, Год журнала: 2025, Номер 207(3)

Опубликована: Фев. 15, 2025

Язык: Английский

Процитировано

0
The hidden hand of molecular chirality in marine biogeochemistry DOI
Le Liu, Min Zhong, Quanrui Chen

и другие.

Trends in Chemistry, Год журнала: 2025, Номер unknown

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0
Tools for Structural Lectinomics: From Structures to Lectomes DOI Creative Commons
Frédérique Lisacek,

Boris Schnider,

Anne Imberty

и другие.

BBA Advances, Год журнала: 2025, Номер unknown, С. 100154 - 100154

Опубликована: Март 1, 2025

Lectins are ubiquitous proteins that interact with glycans in a variety of molecular processes and as such, also play role diseases, whether infectious, chronic or cancer-related. The systematic study lectins is therefore essential, particular for understanding cell-cell communication. Accumulated protein three-dimensional structural data the past decades boosted advance AI-based prediction opened up new options to characterise known often be multimeric multivalent. This article reviews methods obtain structures lectins, current available lectin 3D their interactions, how this knowledge used classify these shows combination an array bioinformatics tools should make binding specificity possible near future.

Язык: Английский

Процитировано

0
Computational studies reveal structural characterization and novel families of Puccinia striiformis f. sp. tritici effectors DOI Creative Commons

Raheel Asghar,

Nan Wu,

Noman Ali

и другие.

PLoS Computational Biology, Год журнала: 2025, Номер 21(3), С. e1012503 - e1012503

Опубликована: Март 28, 2025

Understanding the biological functions of Puccinia striiformis f. sp. tritici ( Pst ) effectors is fundamental for uncovering mechanisms pathogenicity and variability, thereby paving way developing durable effective control strategies stripe rust. However, due to lack an efficient genetic transformation system in , progress effector function studies has been slow. Here, we modeled structures 15,201 from twelve races or isolates, a isolate, one hordei isolate using AlphaFold2. Of these, 8,102 folds were successfully predicted, performed sequence- structure-based annotations these effectors. These classified into 410 structure clusters 1,005 sequence clusters. Sequence lengths varied widely, with concentration between 101-250 amino acids, motif analysis revealed that 47% 5.81% predicted contain known motifs [Y/F/W]xC RxLR, respectively highlighting structural conservation across substantial portion Subcellular localization predictions indicated predominant cytoplasmic localization, notable chloroplast nuclear presence. Structure-guided significantly enhances prediction efficiency as demonstrated by 75% among have annotation. The clustering annotation both based on homologies allowed us determine adopted folding fold families A common feature observed was formation different sequences. In our study, comparative analyses new family core four helices, including Pst27791, PstGSRE4, PstSIE1, which target key wheat immune pathway proteins, impacting host functions. Further showed similarities other pathogens, such AvrSr35, AvrSr50, Zt-KP4-1, MoHrip2, possibility convergent evolutionary strategies, yet be supported further data encompassing some evolutionarily distant species. Currently, initial most effectors’ sequence, relationships providing novel foundation advance future understanding evolution.

Язык: Английский

Процитировано

0
3‐D substructure search by transitive closure in AlphaFold database DOI Creative Commons
Haibo Liu,

Aleksi Laiho,

Petri Törönen

и другие.

Protein Science, Год журнала: 2025, Номер 34(6)

Опубликована: Май 22, 2025

Abstract Identifying structural relationships between proteins is crucial for understanding their functions and evolutionary histories. We present ISS_ProtSci, a Python package designed similarity searches within the AlphaFold Database v2 (AFDB2). ISS_ProtSci incorporates DaliLite to identify geometrically similar structures uses transitive closure algorithm iteratively explore neighboring shells of proteins. The precomputed all‐against‐all comparisons generated by Foldseek, chosen its speed, are validated precision. Search results annotated with metadata from UniProtKB Pfam protein family classifications, using hmmsearch domains. Outputs, including Dali pairwise alignment data, provided in TSV format easy filtering analysis. Our method offers significant improvement recall over existing tools like especially detecting more distantly related This particularly valuable structurally diverse families where traditional sequence‐based or fast methods struggle. delivers practical runtimes flexibility, allowing users input PDB file, define minimum size common core, evaluate clans. In evaluating our across 12 test cases based on clans, we achieved 99% relevant proteins, even challenging Foldseek's dropped below 50%. not only identifies closely but also uncovers previously unrecognized relationships, contributing accurate classifications. software can be downloaded http://ekhidna2.biocenter.helsinki.fi/ISS_ProtSci/ .

Язык: Английский

Процитировано

0
Genome-Wide Identification of the PR-1 Gene Family in Pyrus betulaefolia Bunge and Its Expression Analysis Under Fire Blight Stress DOI Open Access

Abudusufuer Wufuerjiang,

Jingyi Sai,

Yue Wen

и другие.

International Journal of Molecular Sciences, Год журнала: 2025, Номер 26(11), С. 5074 - 5074

Опубликована: Май 24, 2025

Fire blight, caused by Erwinia amylovora, is a devastating bacterial disease threatening apple, pear, and other Rosaceae species. In our prior study, transcriptome analysis identified fire blight-resistant variety, Duli (Pyrus betulifolia Bunge), highlighted the PR1 gene as key resistance factor. Using Duli’s genomic data, we systematically characterized Pb-PR-1 family through bioinformatics analysis. A total of 31 genes were found, encoding proteins 123–341 amino acids. Phylogenetic grouped these into four subfamilies, with 27 distributed across seven chromosomes, all contain conserved CAP superfamily domain. Their promoter regions enriched in hormone stress-responsive elements. After inoculation E. susceptible showed lesion development day 2, rapid progression, while resistant plants exhibited slower advancement smaller lesions. Enzyme activity assays revealed that plants, PPO (polyphenol oxidase) CAT (catalase) activities peaked on 6, showing 2.4-fold 3.81-fold increase compared to Duli. At same time, MDA (malondialdehyde) content decreased 16.6%. The SOD (superoxide dismutase) PAL (phenylalanine ammonia-lyase) 4, increments 34.32% 47.1% over qRT-PCR significant differences expression between post-inoculation. Notably, Pb-PR-1-11, Pb-PR-1-21, Pb-PR-1-26 increased infection duration, aligning trends. Other high early but declined 6. Pb-PR-1-3, Pb-PR-1-6, Pb-PR-1-8, Pb-PR-1-16, Pb-PR-1-30 upregulated 13.17-fold average 2. summary, elevated during enhanced defense-related enzyme activities, improving plant resistance. This study provides foundation for understanding PR-1 family’s role advancing blight Pyrus

Язык: Английский

Процитировано

0
Unsupervised Domain Classification of AlphaFold2-Predicted Protein Structures DOI Creative Commons
Federico Barone, Alessandro Laio, Marco Punta

и другие.

PRX Life, Год журнала: 2025, Номер 3(2)

Опубликована: Май 27, 2025

The release of the AlphaFold database, which contains 214 million predicted protein structures, represents a major leap forward for proteomics and its applications. However, lack comprehensive annotation limits accessibility usability. Here, we present DPCstruct, an unsupervised clustering algorithm designed to provide domain-level classification structures. Using structural predictions from AlphaFold2 all-against-all local alignments Foldseek, DPCstruct identifies groups recurrent motifs into domain clusters. When applied Foldseek Cluster representative set proteins AlphaFoldDB, successfully recovers majority folds catalogued in established databases such as SCOP CATH. Out 28 246 clusters identified by 24% have no or sequence similarity known families. Supported modular efficient implementation, classifying 15 entries less than 48 h, is well suited large-scale metagenomics It also facilitates rapid incorporation updates latest prediction tools, ensuring that remains up-to-date. pipeline associated database are freely available dedicated repository, enhancing navigation AlphaFoldDB through annotations enabling other datasets. Published American Physical Society 2025

Язык: Английский

Процитировано

0
CATH v4.4: major expansion of CATH by experimental and predicted structural data DOI Creative Commons
Vaishali Waman, Nicola Bordin, Andy M. Lau

и другие.

Nucleic Acids Research, Год журнала: 2024, Номер 53(D1), С. D348 - D355

Опубликована: Ноя. 20, 2024

Abstract CATH (https://www.cathdb.info) is a structural classification database that assigns domains to the structures in Protein Data Bank (PDB) and AlphaFold Structure Database (AFDB) adds layers of biological information, including homology functional annotation. This article covers developments since 2021. We report significant expansion information (180-fold) for superfamilies through PDB predicted domain from Encyclopedia Domains (TED) resource. TED provides on AFDB. v4.4 represents an ∼64 844 experimentally determined PDB. also present mapping ∼90 million superfamilies. New data increases number 5841 6573, folds 1349 2078 architectures 41 77. comprises structures, so these new remain hypothetical until confirmed. classifies into families (FunFams) within superfamily. have updated sequences FunFams by scanning FunFam-HMMs against UniProt release 2024_02, giving 276% increase coverage. The has resulted 4-fold with information.

Язык: Английский

Процитировано

2