MobiDB-lite 3.0: fast consensus annotation of intrinsic disorder flavors in proteins

Abstract Motivation The earlier version of MobiDB-lite is currently used in large-scale proteome annotation platforms to detect intrinsic disorder. However, new theoretical models allow for the classification of intrinsically disordered regions into subtypes from sequence features associated with specific polymeric properties or compositional bias. Results MobiDB-lite 3.0 maintains its previous speed and performance but also provides a finer classification of disorder by identifying regions with characteristics of polyolyampholytes, positive or negative polyelectrolytes, low-complexity regions or enriched in cysteine, proline or glycine or polar residues. Subregions are abundantly detected in IDRs of the human proteome. The new version of MobiDB-lite represents a new step for the proteome level analysis of protein disorder. Availability and implementation Both the MobiDB-lite 3.0 source code and a docker container are available from the GitHub repository: https://github.com/BioComputingUP/MobiDB-lit

Contacts prediction of linear peptides from genomic data

The rise of metagenomics and the technological improvements in the fields of bioinformatics and computational biology led to an exponential increase in the amount of biological data available to be studied. However, the rate at which biological data are studied is much slower than the rate at which they are stored. This issue pushed the development of programs capable of extracting significant information from newly sourced data without the need of human intervention. More specifically, some of these programs have been developed to infer structural information from protein sequences. Since the structure of a protein is strictly bound to its function, it is easy to understand the importance of such task. Among the structural information which can be inferred looking at a protein sequence, there are contact maps. Contact maps define whether two residues are functionally linked within the same protein chain or two different ones. Despite much work has been carried out for intra-chain contact maps prediction using sequence information, less can be found about inter-chain contact maps. Moreover, methods are usually presented and tested on benchmark dataset generated for such purpose. In this, a whole pipeline for both intra-chain and inter-chain contact predictions is presented. Instead of using a generic benchmark set of protein sequences as input, the pipeline starts from predictions of linear interacting peptides at residues level. Linear interacting peptides are regions in a protein sequence which are thought to not have a fixed folding, but to adapt their structure to the functional needs of the protein itself. Needles to say, fewer studies have been conducted about this specific issue in literature. Finally, an analysis of the results is carried out. The analysis focuses on the evaluation of methods implied for contact predictions over the given dataset. Particular attention is paid to the comparison of the performances on inter-chain alignments with respect to the ones achieved on intra-chain alignments. Furthermore, the effect of linear interacting peptides is taken into account

Feeding management of dairy cattle affect grassland dynamics in an alpine pasture

5This work was supported by the Autonomous Province of Trento (Provincia Autonoma di Trento) [Progetto ‘Forma’] (Italy) with the ‘Forma’ project.restrictedInternationalItalian coauthor/editorThe effect of different supplementary feeding rates for grazing cattle on high-altitude pastures dynamics was evaluated. A field experiment was carried out during three years in a subalpine pasture area of the Eastern Alps. The investigated pasture area was 40 ha, located between 1820 and 2230 m a.s.l. Two paddocks were chosen in the experiment and two herds of 12 cattle each were kept in the two enclosures for 5 weeks. For the first herd (HS), the supplementary feeding rate was 4.8 kg OM head−1 per day, while for the second herd (LS), the rate was 1.6 kg OM head−1 per day. The amount of herbage consumed by each cattle was determined using the n-alkane technique. To monitor the pasture vegetation dynamics, eight metal exclusion cages were placed in each paddock to determine herbage growth, utilization rates, vegetation composition and animal grazing selectivity. Grazing behaviour of dairy cattle, in terms of herbage intake and species selection was affected by the different feeding rates. Cattle grazing Paddock HS consumed 1.9 kg OM day−1 of herbage less than Paddock LS. In the LS paddock, cattle grazed higher phytomass rates. When the animals were fed by higher concentrate rates, a more selective grazing seemed to significantly increase the pasture necromass component. The lower grazing selectivity favoured the development of species as Nardus stricta and Deschampsia caespitosa, which are well known for their low palatability. Distinct vegetation dynamic patterns were observed, with a reduction of hair grass and an increase of legumes in the Paddock LS.restrictedGianelle, D.; Romanzin, A.; Clementel, F.; Vescovo, L.; Bovolenta, S.Gianelle, D.; Romanzin, A.; Clementel, F.; Vescovo, L.; Bovolenta, S

MobiDB: 10 years of intrinsically disordered proteins

: The MobiDB database (URL: https://mobidb.org/) is a knowledge base of intrinsically disordered proteins. MobiDB aggregates disorder annotations derived from the literature and from experimental evidence along with predictions for all known protein sequences. MobiDB generates new knowledge and captures the functional significance of disordered regions by processing and combining complementary sources of information. Since its first release 10 years ago, the MobiDB database has evolved in order to improve the quality and coverage of protein disorder annotations and its accessibility. MobiDB has now reached its maturity in terms of data standardization and visualization. Here, we present a new release which focuses on the optimization of user experience and database content. The major advances compared to the previous version are the integration of AlphaFoldDB predictions and the re-implementation of the homology transfer pipeline, which expands manually curated annotations by two orders of magnitude. Finally, the entry page has been restyled in order to provide an overview of the available annotations along with two separate views that highlight structural disorder evidence and functions associated with different binding modes

A STRP-ed definition of Structured Tandem Repeats in Proteins

: Tandem Repeat Proteins (TRPs) are a class of proteins with repetitive amino acid sequences that have been studied extensively for over two decades. Different features at the level of sequence, structure, function and evolution have been attributed to them by various authors. And yet many of its salient features appear only when looking at specific subclasses of protein tandem repeats. Here, we attempt to rationalize the existing knowledge on Tandem Repeat Proteins (TRPs) by pointing out several dichotomies. The emerging picture is more nuanced than generally assumed and allows us to draw some boundaries of what is not a "proper" TRP. We conclude with an operational definition of a specific subset, which we have denominated STRPs (Structural Tandem Repeat Proteins), which separates a subclass of tandem repeats with distinctive features from several other less well-defined types of repeats. We believe that this definition will help researchers in the field to better characterize the biological meaning of this large yet largely understudied group of proteins

DisProt in 2024: improving function annotation of intrinsically disordered proteins

DisProt (URL: https://disprot.org) is the gold standard database for intrinsically disordered proteins and regions, providing valuable information about their functions. The latest version of DisProt brings significant advancements, including a broader representation of functions and an enhanced curation process. These improvements aim to increase both the quality of annotations and their coverage at the sequence level. Higher coverage has been achieved by adopting additional evidence codes. Quality of annotations has been improved by systematically applying Minimum Information About Disorder Experiments (MIADE) principles and reporting all the details of the experimental setup that could potentially influence the structural state of a protein. The DisProt database now includes new thematic datasets and has expanded the adoption of Gene Ontology terms, resulting in an extensive functional repertoire which is automatically propagated to UniProtKB. Finally, we show that DisProt's curated annotations strongly correlate with disorder predictions inferred from AlphaFold2 pLDDT (predicted Local Distance Difference Test) confidence scores. This comparison highlights the utility of DisProt in explaining apparent uncertainty of certain well-defined predicted structures, which often correspond to folding-upon-binding fragments. Overall, DisProt serves as a comprehensive resource, combining experimental evidence of disorder information to enhance our understanding of intrinsically disordered proteins and their functional implications.Fil: Aspromonte, Maria Cristina. Università di Padova; ItaliaFil: Nugnes, María Victoria. Università di Padova; Italia. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Quaglia, Federica. Università di Padova; ItaliaFil: Bouharoua, Adel. Università di Padova; ItaliaFil: Sagris, Vasileios. UNIVERSITY OF CYPRUS (UC);Fil: Promponas, Vasilis J.. UNIVERSITY OF CYPRUS (UC);Fil: Chasapi, Anastasia. Centre For Research And Technology - Hellas ; Chemical Process & Energy Resources Institute;Fil: Fichó, Erzsébet. Cytocast Hungary; HungríaFil: Balatti, Galo Ezequiel. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Parisi, Gustavo Daniel. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: González Buitrón, Martín. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Erdos, Gabor. Eötvös University; ArgentinaFil: Pajkos, Matyas. Eotvos University, Budapest. Department Of Materials Physics; ArgentinaFil: Dosztányi, Zsuzsanna. Eotvos University, Budapest. Department Of Materials Physics; ArgentinaFil: Dobson, Laszlo. Semmelweis University; HungríaFil: Conte, Alessio Del. Università di Padova; ItaliaFil: Clementel, Damiano. Università di Padova; ItaliaFil: Salladini, Edoardo. Università di Padova; ItaliaFil: DisProt Consortium. Università di Padova; ItaliaFil: Ku, Luiggi G Tenorio. Università di Padova; ItaliaFil: Monzon, Alexander Miguel. Università di Padova; ItaliaFil: Tompa, Peter. Vrije Unviversiteit Brussel; BélgicaFil: Lazar, Tamas. Vrije Unviversiteit Brussel; BélgicaFil: Tosatto, Silvio C E. Università di Padova; ItaliaFil: Piovesan, Damiano. Università di Padova; Itali

DisProt in 2024: improving function annotation of intrinsically disordered proteins

DisProt (URL: https://disprot.org) is the gold standard database for intrinsically disordered proteins and regions, providing valuable information about their functions. The latest version of DisProt brings significant advancements, including a broader representation of functions and an enhanced curation process. These improvements aim to increase both the quality of annotations and their coverage at the sequence level. Higher coverage has been achieved by adopting additional evidence codes. Quality of annotations has been improved by systematically applying Minimum Information About Disorder Experiments (MIADE) principles and reporting all the details of the experimental setup that could potentially influence the structural state of a protein. The DisProt database now includes new thematic datasets and has expanded the adoption of Gene Ontology terms, resulting in an extensive functional repertoire which is automatically propagated to UniProtKB. Finally, we show that DisProt's curated annotations strongly correlate with disorder predictions inferred from AlphaFold2 pLDDT (predicted Local Distance Difference Test) confidence scores. This comparison highlights the utility of DisProt in explaining apparent uncertainty of certain well-defined predicted structures, which often correspond to folding-upon-binding fragments. Overall, DisProt serves as a comprehensive resource, combining experimental evidence of disorder information to enhance our understanding of intrinsically disordered proteins and their functional implications

CAID prediction portal: a comprehensive service for predicting intrinsic disorder and binding regions in proteins

International audienceIntrinsic disorder (ID) in proteins is well-established in structural biology, with increasing evidence for its involvement in essential biological processes. As measuring d ynamic ID beha vior e xperimentall y on a large scale remains difficult, scores of published ID predictor s ha ve tried to fill this gap. Unfortunatel y, their heterogeneity makes it difficult to compare perf ormance, conf ounding biologists wanting to make an informed choice. To address this issue, the Critical Assessment of protein Intrinsic Disorder (CAID) benchmarks predictors for ID and binding regions as a community blind-test in a standardized computing environment. Here we present the CAID Prediction Portal, a web server executing all CAID methods on user-defined sequences. The server generates standardized output and facilitates comparison between methods, producing a consensus prediction highlighting high-confidence ID regions. The website contains extensive documentation explaining the meaning of different CAID statistics and providing a brief description of all methods. Predictor output is visualized in an interactive feature viewer and made available for download in a single table, with the option to recover previous sessions via a priv ate dashboar d. The CAID Prediction Portal is a valuable resource for researchers interested in studying ID in proteins. The server is available at the URL: https://caid.idpcentral.org