Combining Protein Conformational Diversity and Phylogenetic Information Using CoDNaS and CoDNaS-Q

CoDNaS (http://ufq.unq.edu.ar/codnas/) and CoDNaS-Q (http://ufq.unq.edu.ar/codnasq) are repositories of proteins with different degrees of conformational diversity. Following the ensemble nature of the native state, conformational diversity represents the structural differences between the conformers in the ensemble. Each entry in CoDNaS and CoDNaS-Q contains a redundant collection of experimentally determined conformers obtained under different conditions. These conformers represent snapshots of the protein dynamism. While CoDNaS contains examples of conformational diversity at the tertiary level, a recent development, CoDNaS-Q, contains examples at the quaternary level. In the emerging age of accurate protein structure prediction by machine learning approaches, many questions remain open regarding the characterization of protein dynamism. In this context, most bioinformatics resources take advantage of distinct features derived from protein alignments, however, the complexity and heterogeneity of information makes it difficult to recover reliable biological signatures. Here we present five protocols to explore tertiary and quaternary conformational diversity at the individual protein level as well as for the characterization of the distribution of conformational diversity at the protein family level in a phylogenetic context. These protocols can provide curated protein families with experimentally known conformational diversity, facilitating the exploration of sequence determinants of protein dynamism. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Assessing conformational diversity with CoDNaS. Alternate Protocol 1: Assessing conformational diversity at the quaternary level with CoDNaS-Q. Basic Protocol 2: Exploring conformational diversity in a protein family. Alternate Protocol 2: Exploring quaternary conformational diversity in a protein family. Basic Protocol 3: Representing conformational diversity in a phylogenetic context.Fil: Escobedo, Nahuel Abel. Universidad Nacional de Quilmes; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Monzon, Alexander Miguel. Università di Padova; ItaliaFil: Fornasari, Maria Silvina. Universidad Nacional de Quilmes; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Palopoli, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes; ArgentinaFil: Parisi, Gustavo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes; Argentin

ProtMiscuity: a database of promiscuous proteins

Promiscuous behaviour in proteins and enzymes remains a challenging feature to understand the structure-function relationship. Here we present ProtMiscuity, a manually curated online database of proteins showing catalytic promiscuity. ProtMiscuity contains information about canonical and promiscuous activities comprising 88 different reactions in 57 proteins from 40 different organisms. It can be searched or browsed by protein names, organisms and descriptions of canonical and promiscuous reactions. Entries provide information on reaction substrates, products and kinetic parameters, mapping of active sites to sequence and structure and links to external resources with biological and functional annotations. ProtMiscuity could assist in studying the underlying mechanisms of promiscuous reactions by offering a unique and curated collection of experimentally derived data that is otherwise hard to find, retrieve and validate from literature.Fil: Velez Rueda, Ana Julia. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Palopoli, Nicolás. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Zacarías, Matías. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Sommese, Leandro Matías. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Parisi, Gustavo Daniel. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

The articles.ELM resource: Simplifying access to protein linear motif literature by annotation, text-mining and classification

Modern biology produces data at a staggering rate. Yet, much of these biological data is still isolated in the text, figures, tables and supplementary materials of articles. As a result, biological information created at great expense is significantly underutilised. The protein motif biology field does not have sufficient resources to curate the corpus of motif-related literature and, to date, only a fraction of the available articles have been curated. In this study, we develop a set of tools and a web resource, 'articles.ELM', to rapidly identify the motif literature articles pertinent to a researcher's interest. At the core of the resource is a manually curated set of about 8000 motif-related articles. These articles are automatically annotated with a range of relevant biological data allowing in-depth search functionality. Machine-learning article classification is used to group articles based on their similarity to manually curated motif classes in the Eukaryotic Linear Motif resource. Articles can also be manually classified within the resource. The 'articles.ELM' resource permits the rapid and accurate discovery of relevant motif articles thereby improving the visibility of motif literature and simplifying the recovery of valuable biological insights sequestered within scientific articles. Consequently, this web resource removes a critical bottleneck in scientific productivity for the motif biology field.Fil: Palopoli, Nicolás. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Iserte, Javier Alonso. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Chemes, Lucia Beatriz. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas; ArgentinaFil: Marino Buslje, Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Parisi, Gustavo Daniel. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gibson, Toby James. Ruprecht Karls Universitat Heidelberg; AlemaniaFil: Davey, N.E.. The Institute of Cancer Research; Reino Unid

CoDNaS-RNA: a database of Conformational Diversity in the Native State of RNA

Conformational changes in RNA native ensembles are central to fulfill many of their biological roles. Systematic knowledge of the extent and possible modulators of this conformational diversity is desirable to better understand the relationship between RNA dynamics and function.We have developed CoDNaS-RNA as the first database of conformational diversity in RNA molecules. Known RNA structures are retrieved and clustered to identify alternative conformers of each molecule. Pairwise structural comparisons within each cluster allows to measure the variability of the molecule. Additional data on structural features, molecular interactions and functional annotations are provided. CoDNaS-RNA is implemented as a public resource that can be of much interest for computational and bench scientists alike.Fil: González Buitrón, Martín. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Romario Tunque Cahui, Ronaldo. Pontificia Universidad Católica de Perú; PerúFil: García Ríos, Emilio. Pontificia Universidad Católica de Perú; PerúFil: Hirsh, Layla. Pontificia Universidad Católica de Perú; PerúFil: Fornasari, Maria Silvina. 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: Palopoli, Nicolás. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Evolutionary rates in human amyloid proteins reveal their intrinsic metastability

The emerging picture of protein nature reveals its intrinsic metastability. According to this idea, although a protein is kinetically trapped in a local free energy minimum that defines its native state, those kinetic barriers can be overcome by a complex mixture of the protein’s intrinsic properties and environmental conditions, promoting access to more stable states such as the amyloid fibril. Proteins that are strongly driven towards aggregation in the form of these fibrils are called amyloidogenic. In this work we study the evolutionary rates of 81 human proteins for which an in vivo amyloid state is supported by experiment-based evidence. We found that these proteins evolve faster when compared with a large dataset of ∼16,000 reference proteins from the human proteome. However, their evolutionary rates were indistinguishable from those of secreted proteins that are already known to evolve fast. After analyzing different parameters that correlate with evolutionary rates, we found that the evolutionary rates of amyloidogenic proteins could be modulated by factors associated with metastable transitions such as supersaturation and conformational diversity. Our results showcase the importance of protein metastability in evolutionary studies.Fil: Zea, Diego Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina. Universite Paris-saclay (universite Paris-saclay);Fil: Mac Donagh, Juan. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Benítez, Guillermo Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Guisande Donadio, Cristian Emanuel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Marchetti, Julia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Palopoli, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Fornasari, Maria Silvina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Parisi, Gustavo Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentin

Highlights of the 1st Argentine Symposium of Young Bioinformatics Researchers (1SAJIB) organized by the ISCB RSG-Argentina

The 1st Argentine Symposium of Young Bioinformatics Researchers took place on 9-10 May 2016 at Universidad de Buenos Aires, Buenos Aires, Argentina. This event evolved from a previous meeting series known as Argentine Student Council Symposium that have been successfully organized since 2012 by the Regional Student Group of Argentina (RSG-Argentina). The change in name reflects the new vision of the organizing committee to gather together all students at Bachelor, Master and PhD levels, postdocs and researchers that are still not Principal Investigator. Here we summarize the main activities and outcomes from this year’s meeting and offer some insights into our future plans.Fil: Parra, Rodrigo Gonzalo. Max Planck Institute for Biophysical Chemistry; Alemania. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Defelipe, Lucas Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Guzovsky, Ana Brenda. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Monzón, Alexander. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cravero, Fiorella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Mancini, Estefania. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Moreyra, Nicolás Nahuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; ArgentinaFil: Padilla Franzotti, Carla Luciana. Universidad Nacional de Tucumán. Facultad de Bioquímica, Química y Farmacia; ArgentinaFil: Revuelta, María Victoria. Cornell University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Freiberger, Maria Ines. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; ArgentinaFil: Gonzalez, Nahuel H.. Universidad Nacional de Entre Ríos. Facultad de Ingeniería; ArgentinaFil: Gonzalez, German Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Diversidad y Ecología Animal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Diversidad y Ecología Animal; ArgentinaFil: Orts, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Biológicas. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Biológicas; ArgentinaFil: Stocchi, Nicolas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Biológicas. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Biológicas; ArgentinaFil: Hasenahuer, Marcia Anahí. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: Teppa, Roxana Elin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Zea, Diego Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Palopoli, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentin

DisProt: intrinsic protein disorder annotation in 2020

The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the ‘dark’ proteome

Critical assessment of protein intrinsic disorder prediction

Abstract: Intrinsically disordered proteins, defying the traditional protein structure–function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has Fmax = 0.483 on the full dataset and Fmax = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with Fmax = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude

Evolution of SLiM-mediated hijack functions in intrinsically disordered viral proteins

Viruses and their hosts are involved in an ‘arms race’ where they continually evolve mechanisms to overcome each other. It has long been proposed that intrinsic disorder provides a substrate for the evolution of viral hijack functions and that short linear motifs (SLiMs) are important players in this process. Here, we review evidence in support of this tenet from two model systems: the papillomavirus E7 protein and the adenovirus E1A protein. Phylogenetic reconstructions reveal that SLiMs appear and disappear multiple times across evolution, providing evidence of convergent evolution within individual viral phylogenies. Multiple functionally related SLiMs show strong coevolution signals that persist across long distances in the primary sequence and occur in unrelated viral proteins. Moreover, changes in SLiMs are associated with changes in phenotypic traits such as host range and tropism. Tracking viral evolutionary events reveals that host switch events are associated with the loss of several SLiMs, suggesting that SLiMs are under functional selection and that changes in SLiMs support viral adaptation. Fine-tuning of viral SLiM sequences can improve affinity, allowing them to outcompete host counterparts. However, viral SLiMs are not always competitive by themselves, and tethering of two suboptimal SLiMs by a disordered linker may instead enable viral hijack. Coevolution between the SLiMs and the linker indicates that the evolution of disordered regions may be more constrained than previously thought. In summary, experimental and computational studies support a role for SLiMs and intrinsic disorder in viral hijack functions and in viral adaptive evolution.Fil: Glavina, Juliana. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas; ArgentinaFil: Palopoli, Nicolás. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Chemes, Lucia Beatriz. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Biotecnológicas; Argentin

Short linear motif core and flanking regions modulate retinoblastoma protein binding affinity and specificity

Pocket proteins retinoblastoma (pRb), p107 and p130 are negative regulators of cellular proliferation and multifunctional proteins regulating development, differentiation and chromatin structure. The retinoblastoma protein is a potent tumor suppressor mutated in a wide range of human cancers, and oncogenic viruses often interfere with cell cycle regulation by inactivating pRb. The LxCxE and pRb AB groove short linear motifs (SLiMs) are key to many pocket protein mediated interactions including host and viral partners. A review of available experimental evidence reveals that several core residues composing each motif instance are determinants for binding. In the LxCxE motif, a fourth hydrophobic position that might allow variable spacing is required for binding. In both motifs, flanking regions including charged stretches and phosphorylation sites can fine-tune the binding affinity and specificity of pocket protein SLiM-mediated interactions. Flanking regions can modulate pocket protein binding specificity, or tune the high affinity interactions of viral proteins that hijack the pRb network. The location of SLiMs within intrinsically disordered regions allows faster evolutionary rates that enable viruses to acquire a functional variant of the core motif by convergent evolution, and subsequently test numerous combinations of flanking regions towards maximizing interaction specificity and affinity. This knowledge can guide future efforts directed at the design of peptide-based compounds that can target pocket proteins to regulate the G1/S cell cycle checkpoint or impair viral mediated pRb inactivation.Fil: Palopoli, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina. Universidad Nacional de Quilmes. Departamento de Ciencia y Tecnología; ArgentinaFil: González Foutel, Nicolás Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Gibson, Toby J.. European Molecular Biology Laboratory; AlemaniaFil: Chemes, Lucia Beatriz. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Fisiología, Biología Molecular y Celular; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentin