bioRxiv Science⌕ Search

Biology subjects

Palopoli, N.

Publications and source records attributed to Palopoli, N..

13 recordsLinked to original sources

Molecular dynamics reveals a novel Regulatory Ca+2-Binding Site in the Mitochondrial Calcium Uniporter

The mitochondrial Ca{superscript 2} uniporter (MCU) channel is essential for energy production, cytosolic Ca{superscript 2} signalling, and regulation of cell death. Its activity is regulated by the core proteins MICU1 and MICU2, which respond to intracellular Ca{superscript 2} levels. In cardiomyocytes, MICU1 inhibits mtMCU activity at basal Ca{superscript 2}, with Ca{superscript 2}-binding relieving this inhibition via a conformational change. However, the precise molecular basis for this dual regulation is unclear. While twelve MICU1 structures exist, each is approximately 30% of their structure missing, omitting key flexible regions and limits the understanding of the Ca{superscript 2}-sensing mechanism. Here, we provide structural and computational evidence to address this gap. Using structural modelling, molecular dynamics simulations, and large-scale sequence analysis, we investigate MICU1s Ca{superscript 2} binding sites from both conformational and evolutionary perspectives. Simulations based on human MICU1 models revealed a previously uncharacterized pseudo-EF-hand (pEF-h) motif. Our findings indicate that this motif functions as an early Ca{superscript 2} sensor, triggering conformational transitions, including shifts in surface charge distribution and isoelectric point, that prime the canonical EF-hand sites for subsequent binding. This hierarchical activation mechanism refines MICU1s on-off regulation of the MCU. To link this mechanism to experimental observations, we simulated a series of point and double mutants targeting the pEF-h, EF-h1, and EF-h2 sites. Our simulations demonstrate that double mutants disrupt Ca{superscript 2} binding not only within the mutated site but also reduce the occupation of the other sites, reaffirming the cooperative nature of Ca{superscript 2} sensing in MICU1. The biological relevance of the EF-hand motifs would be supported by its evolutionary conservation. Therefore, we analysed the evolutionary shaping of MICU1 EF-hand motifs across major eukaryotic lineages using clustering analysis and found strong lineage-specific segregation: canonical DXN/DXD-type motifs predominated in EF-h1 and EF-h2 in plants and protists, while non-canonical EXE(X)DEG(X)E motifs were exclusive to Opisthokonts, coinciding with the emergence of the auxiliary subunit EMRE. This pattern suggests that high-affinity Ca{superscript 2} binding evolved in parallel with increasing regulatory complexity in metazoans. Together, these findings support previous research linking EF-hand function as sensors to specialised Ca{superscript 2} gatekeepers in multicellular lineages. By integrating structural and evolutionary perspectives, our study provides mechanistic insight into how MICU1 can act as a Ca{superscript 2}-dependent molecular switch, clarifying the cooperative and threshold-setting behaviour underlying its regulatory role in mitochondrial Ca{superscript 2} uptake. HighlightsO_LIThe hierarchical activation mechanism refines MICU1s on-off regulation of the MCU. C_LIO_LIA novel Ca{superscript 2}-binding site in human MICU1, featuring a unique helix-loop-{beta}-sheet structure, was identified and functionally characterized. C_LIO_LIThis new Ca{superscript 2}-binding site in MICU1 acts as an early sensor, triggering structural changes key to its regulatory function. C_LIO_LICa{superscript 2}-binding motif distributions and phylogenetic constraints indicate possible functional divergence. C_LI

bioinformatics↗

Ghost interactions: revealing missing protein-ligand interactions using AlphaFold predictions

Protein-ligand interactions represent an essential step in understanding molecular recognition, an intense field of research for many scientific areas. Structural biology has played a central role in unveiling protein-ligand interactions, but current techniques are still not able to reliably describe the interactions of ligands with highly flexible regions. In this work we explored the capacity of AlphaFold2 (AF2) to estimate the presence of interactions between ligands and residues belonging to disordered regions, which we called "ghost interactions" as they are missing in the crystallographic derived structures. We found that AF2 models are good predictors of regions associated with order-disorder transitions. Additionally, we found that AF2 predicts residues making ghost interactions with ligands, which are mostly buried and show a differential evolutionary conservation. Our findings could fuel current areas of research that consider intrinsically disordered proteins as potentially valuable targets for drug development, given their biological relevance and associated diseases.

bioinformatics↗

Conformational epistasis impairs AlphaFold structural predictions

Protein structures have been massively predicted using homologous sequence information. AlphaFold2 (AF2) is a recent breakthrough to predict 3D models using machine learning approaches that reached an outstanding accuracy in recent quality evaluations. However, information derived from extant homologous sequences, as those used by AF2, might not contain enough information to accurately predict protein structure. This limitation could be related to the process known as epistasis, which describes the differential effect of a mutation on the evolutionary trajectory. Clear evidence of conformational epistasis, which has a specific impact on protein structure, was characterized in the evolutionary origin of the glucocorticoid receptor (GR) specificity during its functional divergence from the mineralocorticoid (MR) receptor. In this work we explore how AF2 can reproduce conformations derived from epistatic effects. Using structural clustering and principal component analysis to analyze the structural similarities in 16 and 13 extant GR and MR conformers, respectively, we found that AF2 models for human GR failed to reproduce extant GR conformations. Interestingly, AF2 models for human MR, for which no conformational epistasis was reported, were almost indistinguishable from extant MR. Our results showcase the importance of evolutionary trajectories to predict accurate 3D models.

bioinformatics↗

Expanding the repertoire of human tandem repeat RNA-binding proteins

Protein regions consisting of arrays of tandem repeats are known to bind other molecular partners, including nucleic acid molecules. Although the interactions between repeat proteins and DNA are already widely explored, studies characterising tandem repeat RNA-binding proteins are lacking. We performed a large-scale analysis of human proteins devoted to expanding the knowledge about tandem repeat proteins experimentally reported as RNA-binding molecules. This work is timely because of the release of a full set of accurate structural models for the human proteome amenable to repeat detection using structural methods. We identified 219 tandem repeat proteins that bind RNA molecules and characterised the overlap between repeat regions and RNA-binding regions as a first step towards assessing their functional relationship. Our results showed that the combination of sequence and structural methods finds more tandem repeat proteins than either method alone. We observed differences in the characteristics of regions predicted as repetitive by sequence-based or structure-based computational methods in terms of their sequence composition, their functions and their protein domains.

bioinformatics↗

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 proteins 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.

evolutionary biology↗

CaviDB: a database of cavities and their features in the structural and conformational space of proteins

Proteins are the functional and evolutionary units of cells. On their surface, proteins are sculpted into numerous concavities and bulges, offering unique microenvironments for ligand binding or catalysis. The dynamics, size, and chemical features of these cavities are essential for the mechanistic understanding of protein function. Here we present CaviDB (https://www.cavidb.org), a novel database of cavities and their features in known protein structures, which integrates the results from commonly used software for cavities detection with protein features obtained from sequence, structure, and function analyses. Additionally, each protein in CaviDB is associated with its corresponding conformers which help to analyze conformational changes in cavities as well. We were able to characterize a total number of 16,533,339 cavities, 62,0431 of them predicted as druggable targets. CaviDB contains 276,432 different proteins, with information about all their conformers. It also offers the capability to compare cavities and their features from different conformational states of the protein. Furthermore, we have recently added the available models from the AlphaFold database versions 2 and 3, which allow further cavity explorations and comparisons. Each entry information is organized in sections, highlighting the general cavities descriptors, including the inter-cavities contacts, activated residues per cavity, the information about druggable cavities, and the global protein descriptors. The data retrieved by the user can be downloaded in a format that is easy to parse and integrate with custom pipelines for protein analysis. CaviDB aims to offer a comprehensive database for use not only in different aspects of drug design and discovery but also to better understand the basis of the protein structure-function relationship better. With its unique approach, CaviDB provides an essential resource for the wide community of bioinformaticians in particular and biologists in general.

bioinformatics↗

MIADE metadata guidelines: Minimum Information About a Disorder Experiment

An unambiguous description of an experimental setup and analysis, and the subsequent biological observation is vital for accurate data interpretation and reproducible results. Consequently, experimental analyses should be described in a concise, unequivocal, and digestible manner. The aim of minimum information guidelines is to define the fundamental complement of data that can support an unambiguous conclusion on experimental observations. In this document, we present the Minimum Information About Disorder Experiments (MIADE) guidelines to define the minimal fundamental parameters required for non-experts to understand the key findings of an experiment studying intrinsically disordered proteins (IDPs) or intrinsically disordered protein regions (IDRs). MIADE guidelines provide recommendations for data producers to describe the results of their experiments at source, for curators to annotate experimental data to community resources and for database developers maintaining community resources to disseminate the data. We give examples of the application of these guidelines in common use cases and describe the implementation of an update to the DisProt IDP database to allow MIADE-compliant annotation. The MIADE guidelines will improve the interpretability of experimental results for data consumers, facilitate direct data submission, simplify data curation, improve data exchange among repositories and standardise the dissemination of the key metadata on an IDP experiment by IDP data sources.

scientific communication and education↗

CoDNaS-Q: a database of conformational diversity of the native state of proteins with quaternary structure

SummaryA collection of conformers that exist in a dynamical equilibrium defines the native state of a protein. The structural differences between them describe their conformational diversity, a defining characteristic of the protein with an essential role in multiple cellular processes. Since most proteins carry out their functions by assembling into complexes, we have developed CoDNaS-Q, the first online resource to explore conformational diversity in homooligomeric proteins. It features a curated collection of redundant protein structures with known quaternary structure. CoDNaS-Q integrates relevant annotations that allow researchers to identify and explore the extent and possible reasons of conformational diversity in homooligomeric protein complexes. Availability and implementationCoDNaS-Q is freely accessible at http://ufq.unq.edu.ar/codnasq/. The data can be retrieved from the website. The source code of the database can be downloaded from https://github.com/SfrRonaldo/codnas-q. Contactnpalopoli@unq.edu.ar

bioinformatics↗

Impact of protein conformational diversity on AlphaFold predictions

After the outstanding breakthrough of AlphaFold in predicting protein 3D models, new questions appeared and remain unanswered. The ensemble nature of proteins, for example, challenges the structural prediction methods because the models should represent a set of conformers instead of single structures. The evolutionary and structural features captured by effective deep learning techniques may unveil the information to generate several diverse conformations from a single sequence. Here we address the performance of AlphaFold2 predictions under this ensemble paradigm. Using a curated collection of apo-holo conformations, we found that AlphaFold2 predicts the holo form of a protein in 70% of the cases, being unable to reproduce the observed conformational diversity with an equivalent error than in the estimation of a single conformation. More importantly, we found that AlphaFold2s performance worsens with the increasing conformational diversity of the studied protein. This impairment is related to the heterogeneity in the degree of conformational diversity found between different members of the homologous family of the protein under study. Finally, we found that main-chain flexibility associated with apo-holo pairs of conformers negatively correlates with the predicted local model quality score plDDT, indicating that plDDT values in a single 3D model could be used to infer local conformational changes linked to ligand binding transitions.

bioinformatics↗

Structural and evolutionary analysis unveil functional adaptations in the promiscuous behavior of serum albumins

Promiscuous activities have been related to the capacity to catalyze reactions different from those a protein has evolved to sustain. From this evolutionary perspective, we rethought the serum albumins promiscuous behavior. We found that the cross aldol condensation of acetone and p-formylbenzonitrile is a promiscuous reaction conserved in humans and other mammals. Structural and evolutionary analysis indicates that the involved residues could have evolved for a still unknown biological function. Our results could contribute to better characterize the serum albumin family and raise questions about the evolution of protein promiscuity and function.

bioinformatics↗

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. AvailabilityCoDNaS-RNA is freely accessible at http://ufq.unq.edu.ar/codnasrna Contactnpalopoli@unq.edu.ar

bioinformatics↗

Intrinsically disordered protein ensembles shape evolutionary rates revealing conformational patterns

Intrinsically disordered proteins (IDPs) lack stable tertiary structure under physiological conditions. The unique composition and complex dynamical behaviour of IDPs make them a challenge for structural biology and molecular evolution studies. Using NMR ensembles, we found that IDPs evolve under a strong site-specific evolutionary rate heterogeneity, mainly originated by different constraints derived from their inter-residue contacts. Evolutionary rate profiles correlate with the experimentally observed conformational diversity of the protein, allowing the description of different conformational patterns possibly related to their structure-function relationships. The correlation between evolutionary rates and contact information improves when structural information is taken not from any individual conformer or the whole ensemble, but from combining a limited number of conformers. Our results suggest that residue contacts in disordered regions constrain evolutionary rates to conserve the dynamic behaviour of the ensemble and that evolutionary rates can be used as a proxy for the conformational diversity of IDPs. Significance StatementIntrinsically disordered proteins (IDPs) challenge the structure-function relationship paradigm. In this work we found that individual sites of IDPs evolve under a strong rate heterogeneity, mainly due to the structural constraints imposed by contacts between their residues. This can be better explained if the contacts are taken from selected subsets of their alternative native conformations, rather than from individual conformations or the whole native ensemble. From an evolutionary point of view, this result indicates that experimentally-based ensembles are redundant. We also observed that the evolutionary rates follow the structural variability between conformers, unveiling conformational preferences. Our results set the stage for establishing novel evolutionary-based methods to study IDP ensembles.

bioinformatics↗

ProtMiscuity: a database of promiscuous proteins

SummaryProtMiscuity is a manually-curated database of promiscuous proteins. It is annotated with information about canonical and promiscuous activities comprising 88 different reactions in 57 proteins from 40 organisms. ProtMiscuity could assist in the study of the underlying mechanisms of promiscuous reactions by offering a collection of experimentally derived data, extensively linked with other databases providing biological, structural and functional information.\n\nAvailability and ImplementationThe responsive web interface of ProtMiscuity provides support for easier navigation and visualization of the database contents on multiple devices. It is implemented in HTML, CSS, JavaScript, Angular4 and NodeJS. ProtMiscuity is hosted on our server and can be freely accessed at http://ufq.unq.edu.ar/protmiscuity\n\nContactGustavo Parisi (gustavo@unq.edu.ar)

bioinformatics↗