Biology subjects

Fornasari, M. S.

Publications and source records attributed to Fornasari, M. S..

11 recordsLinked to original sources

bioRxiv2026

Transposable elements as evolutionary substrates of proteindisorder in the human proteome

Intrinsically disordered regions (IDRs) are central contributors to protein function, evolution and human disease, yet the evolutionary routes that seed new disordered segments within pre-existing proteins are still poorly understood. Sequence insertions provide a powerful mechanism for disorder expansion, but the genomic donors of inserted IDR and its long-term conformational fate remain largely unknown. Transposable elements (TEs), abundant mobile genetic elements with distinctive compositional biases, represent compelling candidates for generating disorder within proteins. Here, we systematically mapped TE-derived segments across human proteins and isoforms, and we found that these insertions are strongly enriched in intrinsic disorder. The structural consequences of their insertion are shaped by TE class and family, reflecting the sequence biases of the elements from which they originate. Recent, Primate-specific insertions preferentially generate disordered segments, whereas older insertions more frequently occupy ordered structural contexts, revealing an age-dependent transition in the conformational state of TE-derived sequences. TE-containing isoforms are expressed at lower levels than TE-free isoforms, particularly when insertions are young and disorder-rich, suggesting that intrinsic disorder may constrain the cellular tolerance of newly exonized sequences. These findings identify TEs as a major evolutionary mechanism linking genome mobility to the emergence of new disordered conformational ensembles in the human proteome.

bioinformatics↗

bioRxiv2025

Small heat shock protein HSPB5 uses disorder to bind zinc with high affinity.

Zinc is an essential metal that supports diverse cellular functions. Zinc exerts its biological activity through protein binding, serving as catalytic cofactors and structural stabilizers of many enzymes, transcription factors, and ubiquitin E3 ligases, among others. Despite total cellular zinc concentrations reaching hundreds of micromolar, free zinc levels are tightly buffered. Elevated free zinc promotes mismetalation and protein aggregation. While zinc is redox-inert, its cysteine-based protein ligands are readily oxidized. Oxidative modification of cysteines leads to zinc dissociation and a rapid increase in free zinc. With [~]3000 proteins in the human zinc proteome, uncontrolled zinc release could be highly deleterious. Metallothioneins buffer zinc under basal conditions, but their re-synthesis following oxidative inactivation occurs on the scale of hours, raising the question of how free zinc is managed in the interim. Histidine, the second most prevalent zinc-coordinating residue, is resistant to oxidative modification. We characterized zinc binding by the small heat shock protein HSPB5 (B-crystallin), a cysteine-free, histidine-rich protein chaperone that responds to cellular stress and found: (1) HSPB5 binds zinc with high affinity and rapid reversibility; (2) zinc binding requires the disordered HSPB5 N-terminal region; (3) zinc binding increases HSPB5 disorder; and (4) prolonged zinc exposure promotes formation of assemblies of oligomers cross-bridged by zinc. We propose that HSPB5 has evolved specialized zinc-dependent properties distinct among human sHSPs, enabling it to function not only as a protein chaperone but also as a conditional zinc reservoir under oxidative stress.

biophysics↗

bioRxiv2025

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↗

bioRxiv2024

Coevolution in Small Heat Shock Protein 1 (HSPB1) is Promoted by Interactions between the Alpha-Crystallin Domain and the Disordered Regions

Human HSPB1, a member of the small heat shock protein (sHSP) family, functions as an ATP-independent molecular chaperone crucial for protein quality control and is implicated in several pathologies, including Charcot-Marie-Tooth neuropathy. This study investigates the coevolution of the disordered N-terminal and C-terminal regions (NTR and CTR) with the structured Alpha-Crystallin domain (ACD) of human HSPB1, focusing on interactions that regulate its chaperone activity. Using a manually curated dataset of HSPB1 orthologs, the composition of critical motifs within the NTR (6VPFSLL11) and CTR (179ITIPV183) that interact with the ACD was analyzed and evolutionary rates per site for the human HSPB1 sequence were estimated. Additionally, structural modeling with AlphaFold 2 was employed to assess the prevalence of these contacts in human HSPB1 models. The results reveal that while the disordered regions globally evolve faster than the structured ACD, specific residues within the 6VPFSLL11 and 179ITIPV183 motifs exhibit reduced evolutionary rates, reflecting evolutionary constraints imposed by the conservation of the proteins function. Structural modeling further indicates that coevolutionary-like information about the interaction between the 6VPFSLL11 motif and the ACD is encoded in the multiple sequence alignment used by Alphafold 2. Altogether, these findings suggest that the disordered regions and the ACD of human HSPB1 likely coevolved, preserving interactions crucial for its chaperone activity self-regulation. This evolutionary mechanism may also be extended to other sHSP featuring interacting motifs in the NTR, CTR, or both, and provides a framework to elucidate why pathogenic variants occurring in regions involved in these contacts contribute to disease.

biochemistry↗

bioRxiv2023

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↗

bioRxiv2022

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↗

bioRxiv2022

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↗

bioRxiv2021

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↗

bioRxiv2020

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↗

bioRxiv2020

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↗

bioRxiv2018

Ensembles from ordered and disordered proteins reveal similar structural constraints during evolution

Inter-residue contacts determine the structural properties for each conformer in the ensembles describing the native state of proteins. Structural constraints during evolution could then provide biologically relevant information about the conformational ensembles and their relationship with protein function. Here, we studied the proportion of sites evolving under structural constraints in two very different types of ensembles, those coming from ordered or disordered proteins. Using a structurally constrained model of protein evolution we found that both types of ensembles show comparable, near 40%, number of positions evolving under structural constraints. Among these sites, ~68% are in disordered regions and ~57% of them show long-range inter-residue contacts. Also, we found that disordered ensembles are redundant in reference to their structurally constrained evolutionary information and could be described on average with ~11 conformers. Despite the different complexity of the studied ensembles and proteins, the similar constraints reveal a comparable level of selective pressure to maintain their biological functions. These results highlight the importance of the evolutionary information to recover meaningful biological information to further characterize conformational ensembles.

bioinformatics↗