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Protein-ligand interactions represent an essential step to understand the bases of molecular recognition, an intense field of research in 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. As these interactions are missing in the crystallographic-derived structures, we called them "ghost interactions". Using a set of protein structures experimentally obtained after AF2 was trained, we found that the obtained 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 differential evolutionary conservation with the rest of the residues located in the flexible region. Our findings could fuel current areas of research that consider, given their biological relevance and their involvement in diseases, intrinsically disordered proteins as potentially valuable targets for drug development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Nqo15 is a subunit of respiratory complex I of the bacterium Thermus thermophilus , with strong structural similarity to human frataxin (FXN), a protein involved in the mitochondrial disease Friedreich's ataxia (FRDA). Recently, we showed that the expression of recombinant Nqo15 can ameliorate the respiratory phenotype of FRDA patients' cells, and this prompted us to further characterize both the Nqo15 solution's behavior and its potential functional overlap with FXN, using a combination of in silico and in vitro techniques. We studied the analogy of Nqo15 and FXN by performing extensive database searches based on sequence and structure. Nqo15's folding and flexibility were investigated by combining nuclear magnetic resonance (NMR), circular dichroism, and coarse-grained molecular dynamics simulations. Nqo15's iron-binding properties were studied using NMR, fluorescence, and specific assays and its desulfurase activation by biochemical assays. We found that the recombinant Nqo15 isolated from complex I is monomeric, stable, folded in solution, and highly dynamic. Nqo15 does not share the iron-binding properties of FXN or its desulfurase activation function.

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)

One of the main topics of cardiovascular research is the study of calcium (Ca2+) handling, as even small changes in Ca2+ concentration can alter cell functionality (Bers, Annu Rev Physiol, 2014, 76, 107-127). Ionic calcium (Ca2+) plays the role of a second messenger in eukaryotic cells, associated with cellular functions such as cell cycle regulation, transport, motility, gene expression, and regulation. The use of fluorometric techniques in isolated cells loaded with Ca2+-sensitive fluorescent probes allows quantitative measurement of dynamic events occurring in living, functioning cells. The Cardiomyocytes Images Analyzer Python (CardIAP) application addresses the need to analyze and retrieve information from confocal microscopy images systematically, accurately, and rapidly. Here we present CardIAP, an open-source tool developed entirely in Python, freely available and useable in an interactive web application. In addition, CardIAP can be used as a standalone Python library and freely installed via PIP, making it easy to integrate into biomedical imaging pipelines. The images that can be generated in the study of the heart have the particularity of requiring both spatial and temporal analysis. CardIAP aims to open the field of cardiomyocytes and intact hearts image processing. The improvement in the extraction of information from the images will allow optimizing the usage of resources and animals. With CardIAP, users can run the analysis to both, the complete image, and portions of it in an easy way, and replicate it on a series of images. This analysis provides users with information on the spatial and temporal changes in calcium releases and characterizes them. The web application also allows users to extract calcium dynamics data in downloadable tables, simplifying the calculation of alternation and discordance indices and their classification. CardIAP aims to provide a tool that could assist biomedical researchers in studying the underlying mechanisms of anomalous calcium release phenomena., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Velez Rueda, Gonano, Smith, Parisi, Fornasari and Sommese.)

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., (© 2023 Wiley Periodicals LLC.)

Motivation: 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 obtained through ColabFold under this ensemble paradigm., Results: Using a curated collection of apo-holo pairs of conformers, 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 the same error for both conformers. More importantly, we found that AlphaFold2's 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., Availability and Implementation: Data and code used in this manuscript are publicly available at https://gitlab.com/sbgunq/publications/af2confdiv-oct2021., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Summary: 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 between all conformers within each cluster allows to measure the variability of the molecule. Additional annotations about structural features, molecular interactions and biological function are provided. All data in CoDNaS-RNA is free to download and available as a public website that can be of interest for researchers in computational biology and other life science disciplines., Availability and Implementation: The data underlying this article are available at http://ufq.unq.edu.ar/codnasrna or https://codnas-rna.bioinformatica.org/., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Every biologist knows that the word protein describes a group of macromolecules essential to sustain life on Earth. As biologists, we are invariably trained under a protein paradigm established since the early twentieth century. However, in recent years, the term protein unveiled itself as an euphemism to describe the overwhelming heterogeneity of these compounds. Most of our current studies are targeted on carefully selected subsets of proteins, but we tend to think and write about these as representative of the whole population. Here we discuss how seeking for universal definitions and general rules in any arbitrarily segmented study would be misleading about the conclusions. Of course, it is not our purpose to discourage the use of the word protein . Instead, we suggest to embrace the extended universe of proteins to reach a deeper understanding of their full potential, realizing that the term encompasses a group of molecules very heterogeneous in terms of size, shape, chemistry and functions, i.e. the term protein no longer means what it used to., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Gustavo Parisi reports financial support was provided by National University of Quilmes., (© 2021 The Authors.)

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The Protein Ensemble Database (PED) (https://proteinensemble.org), which holds structural ensembles of intrinsically disordered proteins (IDPs), has been significantly updated and upgraded since its last release in 2016. The new version, PED 4.0, has been completely redesigned and reimplemented with cutting-edge technology and now holds about six times more data (162 versus 24 entries and 242 versus 60 structural ensembles) and a broader representation of state of the art ensemble generation methods than the previous version. The database has a completely renewed graphical interface with an interactive feature viewer for region-based annotations, and provides a series of descriptors of the qualitative and quantitative properties of the ensembles. High quality of the data is guaranteed by a new submission process, which combines both automatic and manual evaluation steps. A team of biocurators integrate structured metadata describing the ensemble generation methodology, experimental constraints and conditions. A new search engine allows the user to build advanced queries and search all entry fields including cross-references to IDP-related resources such as DisProt, MobiDB, BMRB and SASBDB. We expect that the renewed PED will be useful for researchers interested in the atomic-level understanding of IDP function, and promote the rational, structure-based design of IDP-targeting drugs., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The RepeatsDB database (URL: https://repeatsdb.org/) provides annotations and classification for protein tandem repeat structures from the Protein Data Bank (PDB). Protein tandem repeats are ubiquitous in all branches of the tree of life. The accumulation of solved repeat structures provides new possibilities for classification and detection, but also increasing the need for annotation. Here we present RepeatsDB 3.0, which addresses these challenges and presents an extended classification scheme. The major conceptual change compared to the previous version is the hierarchical classification combining top levels based solely on structural similarity (Class > Topology > Fold) with two new levels (Clan > Family) requiring sequence similarity and describing repeat motifs in collaboration with Pfam. Data growth has been addressed with improved mechanisms for browsing the classification hierarchy. A new UniProt-centric view unifies the increasingly frequent annotation of structures from identical or similar sequences. This update of RepeatsDB aligns with our commitment to develop a resource that extracts, organizes and distributes specialized information on tandem repeat protein structures., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Massive parallel sequencing technologies are facilitating the faster identification of sequence variants with the consequent capability of untangling the molecular bases of many human genetic syndromes. However, it is not always easy to understand the impact of novel variants, especially for missense changes, which can lead to a spectrum of phenotypes. This study presents a custom-designed multistep methodology to evaluate the impact of novel variants aggregated in the genome aggregation database for the HBB, HBA2, and HBA1 genes, by testing and improving its performance with a dataset of previously described alterations affecting those same genes. This approach scored high sensitivity and specificity values and showed an overall better performance than sequence-derived predictors, highlighting the importance of protein conformation and interaction specific analyses in curating variant databases. This study also describes the strengths and limitations of these structural studies and allows identifying residues in the globin chains more prone to tolerate substitutions., (© 2019 Wiley Periodicals, Inc.)

Revenant is a database of resurrected proteins coming from extinct organisms. Currently, it contains a manually curated collection of 84 resurrected proteins derived from bibliographic data. Each protein is extensively annotated, including structural, biochemical and biophysical information. Revenant contains a browse capability designed as a timeline from where the different proteins can be accessed. The oldest Revenant entries are between 4200 and 3500 million years ago, while the younger entries are between 8.8 and 6.3 million years ago. These proteins have been resurrected using computational tools called ancestral sequence reconstruction techniques combined with wet-laboratory synthesis and expression. Resurrected proteins are commonly used, with a noticeable increase during the past years, to explore and test different evolutionary hypotheses such as protein stability, to explore the origin of new functions, to get biochemical insights into past metabolisms and to explore specificity and promiscuous behaviour of ancient proteins., (© The Author(s) 2020. Published by Oxford University Press.)

The conformations accessible to proteins are determined by the inter-residue interactions between amino acid residues. During evolution, structural constraints that are required for protein function providing biologically relevant information can exist. Here, we studied the proportion of sites evolving under structural constraints in two very different types of ensembles, those coming from ordered and 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., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

The dynamic nature of technological developments invites us to rethink the learning spaces. In this context, science education can be enriched by the contribution of new computational resources, making the educational process more up-to-date, challenging, and attractive. Bioinformatics is a key interdisciplinary field, contributing to the understanding of biological processes that is often underrated in secondary schools. As a useful resource in learning activities, bioinformatics could help in engaging students to integrate multiple fields of knowledge (logical-mathematical, biological, computational, etc.) and generate an enriched and long-lasting learning environment. Here, we report our recent project in which high school students learned basic concepts of programming applied to solving biological problems. The students were taught the Python syntax, and they coded simple tools to answer biological questions using resources at hand. Notably, these were built mostly on the students' own smartphones, which proved to be capable, readily available, and relevant complementary tools for teaching. This project resulted in an empowering and inclusive experience that challenged differences in social background and technological accessibility., Competing Interests: The authors have declared that no competing interests exist.

Major scientific challenges that are beyond the capability of individuals need to be addressed by multi-disciplinary and multi-institutional consortia. Examples of these endeavours include the Human Genome Project, and more recently, the Structural Genomics (SG) initiative. The SG initiative pursues the expansion of structural coverage to include at least one structural representative for each protein family to derive the remaining structures using homology modelling. However, biological function is inherently connected with protein dynamics that can be studied by knowing different structures of the same protein. This ensemble of structures provides snapshots of protein conformational diversity under native conditions. Thus, sequence redundancy in the Protein Data Bank (PDB) (i.e. crystallization of the same protein under different conditions) is therefore an essential input contributing to experimentally based studies of protein dynamics and providing insights into protein function. In this work, we show that sequence redundancy, a key concept for exploring protein dynamics, is highly biased and fundamentally incomplete in the PDB. Additionally, our results show that dynamical behaviour of proteins cannot be inferred using homologous proteins. Minor to moderate changes in sequence can produce great differences in dynamical behaviour. Nonetheless, the structural and dynamical incompleteness of the PDB is apparently unrelated concepts in SG. While the first could be reversed by promoting the extension of the structural coverage, we would like to emphasize that further focused efforts will be needed to amend the incompleteness of the PDB in terms of dynamical information content, essential to fully understand protein function.

The native state of proteins is composed of conformers in dynamical equilibrium. In this chapter, different issues related to conformational diversity are explored using a curated and experimentally based database called CoDNaS (Conformational Diversity in the Native State). This database is a collection of redundant structures for the same sequence. CoDNaS estimates the degree of conformational diversity using different global and local structural similarity measures. It allows the user to explore how structural differences among conformers change as a function of several structural features providing further biological information. This chapter explores the measurement of conformational diversity and its relationship with sequence divergence. Also, it discusses how proteins with high conformational diversity could affect homology modeling techniques.

Epidermal growth factor receptor (EGFR) is a prototypical cell-surface receptor that plays a key role in the regulation of cellular signaling, proliferation and differentiation. Mutations of its kinase domain have been associated with the development of a variety of cancers and, therefore, it has been the target of drug design. Single amino acid substitutions (SASs) in this domain have been proven to alter the equilibrium of pre-existing conformer populations. Despite the advances in structural descriptions of its so-called active and inactive conformations, the associated dynamics aspects that characterize them have not been thoroughly studied yet. As the dynamic behaviors and molecular motions of proteins are important for a complete understanding of their structure-function relationships we present a novel procedure, using (or based on) normal mode analysis, to identify the collective dynamics shared among different conformers in EGFR kinase. The method allows the comparison of patterns of low-frequency vibrational modes defining representative directions of motions. Our procedure is able to emphasize the main similarities and differences between the collective dynamics of different conformers. In the case of EGFR kinase, two representative directions of motions have been found as dynamics fingerprints of the active conformers. Protein motion along both directions reveals to have a significant impact on the cavity volume of the main pocket of the active site. Otherwise, the inactive conformers exhibit a more heterogeneous distribution of collective motions. © 2018 Wiley Periodicals, Inc., (© 2018 Wiley Periodicals, Inc.)

Hemoglobinopathies are the most common autosomal recessive disorders and are mostly inherited in a recessive manner. However, certain mutations can affect the globin chain stability, leading to dominant forms of thalassemia. The aim of this work was the molecular and structural characterization of two heterozygous in-frame deletions, leading to β-globin variants in pediatric patients in Argentina. The HBB gene of the probands and their parents was sequenced, and other markers of globin chain imbalance were analyzed. Several structural analyses were performed, and the effect of the mutations on the globin chain stability was analyzed. In Hb JC-Paz, HBB:c.29_37delCTGCCGTTA (p.Ala10_Thr12del), detected in an Argentinean boy, one α-helix turn is expected to be lost. In Hb Tavapy, HBB:c.182_187delTGAAGG (p.Val60_Lys61del), the deleted residues are close to distal histidine (His63) in the heme pocket. Both mutations are predicted to have a destabilizing effect. The development of computational structural models and bioinformatics algorithms is expected to become a useful tool to understand the impact of the mutations leading to dominant thalassemia., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

[This corrects the article DOI: 10.1371/journal.pone.0189147.].

Epidermal Growth Factor Receptor (EGFR), a tyrosine kinase receptor, is one of the main tumor markers in different types of cancers. The kinase native state is mainly composed of two populations of conformers: active and inactive. Several sequence variations in EGFR kinase region promote the differential enrichment of conformers with higher activity. Some structural characteristics have been proposed to differentiate kinase conformations, but these considerations could lead to ambiguous classifications. We present a structural characterisation of EGFR kinase conformers, focused on active site pocket comparisons, and the mapping of known pathological sequence variations. A structural based clustering of this pocket accurately discriminates active from inactive, well-characterised conformations. Furthermore, this main pocket contains, or is in close contact with, ≈65% of cancer-related variation positions. Although the relevance of protein dynamics to explain biological function has been extensively recognised, the usage of the ensemble of conformations in dynamic equilibrium to represent the functional state of proteins and the importance of pockets, cavities and/or tunnels was often neglected in previous studies. These functional structures and the equilibrium between them could be structurally analysed in wild type as well as in sequence variants. Our results indicate that biologically important pockets, as well as their shape and dynamics, are central to understanding protein function in wild-type, polymorphic or disease-related variations.

Protein motions are a key feature to understand biological function. Recently, a large-scale analysis of protein conformational diversity showed a positively skewed distribution with a peak at 0.5 Å C-alpha root-mean-square-deviation (RMSD). To understand this distribution in terms of structure-function relationships, we studied a well curated and large dataset of ~5,000 proteins with experimentally determined conformational diversity. We searched for global behaviour patterns studying how structure-based features change among the available conformer population for each protein. This procedure allowed us to describe the RMSD distribution in terms of three main protein classes sharing given properties. The largest of these protein subsets (~60%), which we call "rigid" (average RMSD = 0.83 Å), has no disordered regions, shows low conformational diversity, the largest tunnels and smaller and buried cavities. The two additional subsets contain disordered regions, but with differential sequence composition and behaviour. Partially disordered proteins have on average 67% of their conformers with disordered regions, average RMSD = 1.1 Å, the highest number of hinges and the longest disordered regions. In contrast, malleable proteins have on average only 25% of disordered conformers and average RMSD = 1.3 Å, flexible cavities affected in size by the presence of disordered regions and show the highest diversity of cognate ligands. Proteins in each set are mostly non-homologous to each other, share no given fold class, nor functional similarity but do share features derived from their conformer population. These shared features could represent conformational mechanisms related with biological functions.

Structural differences between conformers sustain protein biological function. Here, we studied in a large dataset of 745 intrinsically disordered proteins, how ordered-disordered transitions modulate structural differences between conformers as derived from crystallographic data. We found that almost 50% of the proteins studied show no transitions and have low conformational diversity while the rest show transitions and a higher conformational diversity. In this last subset, 60% of the proteins become more ordered after ligand binding, while 40% more disordered. As protein conformational diversity is inherently connected with protein function our analysis suggests differences in structure-function relationships related to order-disorder transitions., (© 2016 The Protein Society.)

Computational modeling of tertiary structures has become of standard use to study proteins that lack experimental characterization. Unfortunately, 3D structure prediction methods and model quality assessment programs often overlook that an ensemble of conformers in equilibrium populates the native state of proteins. In this work we collected sets of publicly available protein models and the corresponding target structures experimentally solved and studied how they describe the conformational diversity of the protein. For each protein, we assessed the quality of the models against known conformers by several standard measures and identified those models ranked best. We found that model rankings are defined by both the selected target conformer and the similarity measure used. 70% of the proteins in our datasets show that different models are structurally closest to different conformers of the same protein target. We observed that model building protocols such as template-based or ab initio approaches describe in similar ways the conformational diversity of the protein, although for template-based methods this description may depend on the sequence similarity between target and template sequences. Taken together, our results support the idea that protein structure modeling could help to identify members of the native ensemble, highlight the importance of considering conformational diversity in protein 3D quality evaluations and endorse the study of the variability of the native structure for a meaningful biological analysis.

CoDNaS (conformational diversity of the native state) is a protein conformational diversity database. Conformational diversity describes structural differences between conformers that define the native state of proteins. It is a key concept to understand protein function and biological processes related to protein functions. CoDNaS offers a well curated database that is experimentally driven, thoroughly linked, and annotated. CoDNaS facilitates the extraction of key information on small structural differences based on protein movements. CoDNaS enables users to easily relate the degree of conformational diversity with physical, chemical and biological properties derived from experiments on protein structure and biological characteristics. The new version of CoDNaS includes ∼70% of all available protein structures, and new tools have been added that run sequence searches, display structural flexibility profiles and allow users to browse the database for different structural classes. These tools facilitate the exploration of protein conformational diversity and its role in protein function. Database URL:http://ufq.unq.edu.ar/codnas., (© The Author(s) 2016. Published by Oxford University Press.)

Somatic sequence variants in the epidermal growth factor receptor (EGFR) kinase domain are associated with sensitivity to tyrosine kinase inhibitors (TKIs) in patients with nonsmall cell lung cancer (NSCLC). Patients exhibiting sequence variants in this domain that produce kinase activity enhancement, are more likely to benefit from TKIs than patients with EGFR wild-type disease. Although most NSCLC EGFR-related alleles are concentrated in a few positions, established protocols recommend sequencing EGFR exons 18-21. In this study, 21 novel somatic variants belonging to such exons in adult Argentinean patients affected with NSCLC are reported. Of these, 18 were single amino acid substitutions (SASs), occurring alone or in combination with another genetic alteration (complex cases), one was a short deletion, one was a short deletion-short insertion combination, and one was a duplication. New variants and different combinations of previously reported variants were also found. Moreover, two of the reported SASs occurred in previously unreported positions of the EGFR kinase domain. In order to characterize the new sequence variants, physicochemical, sequence and conformational analyses were also performed. A better understanding of sequence variants in NSCLC may facilitate the most appropriate treatment choice for this complex disease., (© 2015 John Wiley & Sons Ltd/University College London.)

We describe here the molecular and hematological characteristics of novel frameshift mutations in exon 2 of the HBB gene (in heterozygous state) found in two Argentinean pediatric patients with dominant β-thalassemia-like features. In Hb Wilde, HBB:c.270_273delTGAG(p.Glu90Cysfs*67), we detected the deletion of the third base of the codon 89 (T) and the codon 90 (GAG), whereas in Hb Patagonia, HBB:c.296_297dupGT(p.Asp99Trpfs*59), the frameshift mutation was due to a duplication of a 'GT' dinucleotide after the second base of codon 98 (GTG). The Hb Patagonia and Hb Wilde mutations would result in elongated β-globin chains with modified C-terminal sequences and a total of 155 and 157 amino acids residues, respectively. Based on bioinformatics and structural analysis, as well as protein modeling, we predict that the elongated β-globins would affect the formation of the αβ dimers and their stability, which would further support the mechanism for the observed clinical features in both patients., (© 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Motivation: Conformational diversity is a key concept in the understanding of different issues related with protein function such as the study of catalytic processes in enzymes, protein-protein recognition, protein evolution and the origins of new biological functions. Here, we present a database of proteins with different degrees of conformational diversity. Conformational Diversity of Native State (CoDNaS) is a redundant collection of three-dimensional structures for the same protein derived from protein data bank. Structures for the same protein obtained under different crystallographic conditions have been associated with snapshots of protein dynamism and consequently could characterize protein conformers. CoDNaS allows the user to explore global and local structural differences among conformers as a function of different parameters such as presence of ligand, post-translational modifications, changes in oligomeric states and differences in pH and temperature. Additionally, CoDNaS contains information about protein taxonomy and function, disorder level and structural classification offering useful information to explore the underlying mechanism of conformational diversity and its close relationship with protein function. Currently, CoDNaS has 122 122 structures integrating 12 684 entries, with an average of 9.63 conformers per protein., Availability: The database is freely available at http://www.codnas.com.ar/.

Native state of proteins is better represented by an ensemble of conformers in equilibrium than by only one structure. The extension of structural differences between conformers characterizes the conformational diversity of the protein. In this study, we found a negative correlation between conformational diversity and protein evolutionary rate. Conformational diversity was expressed as the maximum root mean square deviation (RMSD) between the available conformers in Conformational Diversity of Native State database. Evolutionary rate estimations were calculated using 16 different species compared with human sharing at least 700 orthologous proteins with known conformational diversity extension. The negative correlation found is independent of the protein expression level and comparable in magnitude and sign with the correlation between gene expression level and evolutionary rate. Our findings suggest that the structural constraints underlying protein dynamism, essential for protein function, could modulate protein divergence.

It is well established that the conservation of protein structure during evolution constrains sequence divergence. The conservation of certain physicochemical environments to preserve protein folds and then the biological function originates a site-specific structurally constrained substitution pattern. However, protein native structure is not unique. It is known that the native state is better described by an ensemble of conformers in a dynamic equilibrium. In this work, we studied the influence of conformational diversity in sequence divergence and protein evolution. For this purpose, we derived a set of 900 proteins with different degrees of conformational diversity from the PCDB database, a conformer database. With the aid of a structurally constrained protein evolutionary model, we explored the influence of the different conformations on sequence divergence. We found that the presence of conformational diversity strongly modulates the substitution pattern. Although the conformers share several of the structurally constrained sites, 30% of them are conformer specific. Also, we found that in 76% of the proteins studied, a single conformer outperforms the others in the prediction of sequence divergence. It is interesting to note that this conformer is usually the one that binds ligands participating in the biological function of the protein. The existence of a conformer-specific site-substitution pattern indicates that conformational diversity could play a central role in modulating protein evolution. Furthermore, our findings suggest that new evolutionary models and bioinformatics tools should be developed taking into account this substitution bias.

Background: Non-synonymous coding SNPs (nsSNPs) that are associated to disease can also be related with alterations in protein stability. Computational methods are available to predict the effect of single amino acid substitutions (SASs) on protein stability based on a single folded structure. However, the native state of a protein is not unique and it is better represented by the ensemble of its conformers in dynamic equilibrium. The maintenance of the ensemble is essential for protein function. In this work we investigated how protein conformational diversity can affect the discrimination of neutral and disease related SASs based on protein stability estimations. For this purpose, we used 119 proteins with 803 associated SASs, 60% of which are disease related. Each protein was associated with its corresponding set of available conformers as found in the Protein Conformational Database (PCDB). Our dataset contains proteins with different extensions of conformational diversity summing up a total number of 1023 conformers., Results: The existence of different conformers for a given protein introduces great variability in the estimation of the protein stability (ΔΔG) after a single amino acid substitution (SAS) as computed with FoldX. Indeed, in 35% of our protein set at least one SAS can be described as stabilizing, destabilizing or neutral when a cutoff value of ±2 kcal/mol is adopted for discriminating neutral from perturbing SASs. However, when the ΔΔG variability among conformers is taken into account, the correlation among the perturbation of protein stability and the corresponding disease or neutral phenotype increases as compared with the same analysis on single protein structures. At the conformer level, we also found that the different conformers correlate in a different way to the corresponding phenotype., Conclusions: Our results suggest that the consideration of conformational diversity can improve the discrimination of neutral and disease related protein SASs based on the evaluation of the corresponding Gibbs free energy change.

Noncovalent interactions and physicochemical properties of amino acids are important topics in biochemistry courses. Here, we present a computational laboratory where the capacity of each of the 20 amino acids to maintain different noncovalent interactions are used to investigate the stabilizing forces in a set of proteins coming from organisms adapted to different environments. Using protein sequence and structure information it is possible to evaluate the noncovalent contributions to the stabilization of a given protein fold. As a case study, we use the protein lumazine synthase from three different organisms adapted to live in extreme temperatures: one psychrophilic (optimal growth temperature, 0-20 °C), one mesophilic (optimal growth temperature, 20-50 °C), and one thermophilic (optimal growth temperature, 80-110 °C). We found that this computational laboratory for biochemistry and molecular biology courses enhances student amino acid noncovalent interaction understanding and how these interactions are involved in protein stability., (Copyright © 2008 International Union of Biochemistry and Molecular Biology, Inc.)

Glycogen and starch are the major energy storage compounds in most living organisms. The metabolic pathways leading to their synthesis involve the action of several enzymes, among which glycogen synthase (GS) or starch synthase (SS) catalyze the elongation of the alpha-1,4-glucan backbone. At least five SS isoforms were described in Arabidopsis thaliana; it has been reported that the isoform III (SSIII) has a regulatory function on the synthesis of transient plant starch. The catalytic C-terminal domain of A. thaliana SSIII (SSIII-CD) was cloned and expressed. SSIII-CD fully complements the production of glycogen by an Agrobacterium tumefaciens glycogen synthase null mutant, suggesting that this truncated isoform restores in vivo the novo synthesis of bacterial glycogen. In vitro studies revealed that recombinant SSIII-CD uses with more efficiency rabbit muscle glycogen than amylopectin as primer and display a high apparent affinity for ADP-Glc. Fold class assignment methods followed by homology modeling predict a high global similarity to A. tumefaciens GS showing a fully conservation of the ADP-binding residues. On the other hand, this comparison revealed important divergences of the polysaccharide binding domain between AtGS and SSIII-CD., ((c) 2007 Wiley-Liss, Inc.)

The starch-synthase III (SSIII), with a total of 1025 residues, is one of the enzymes involved in plants starch synthesis. SSIII from Arabidopsis thaliana contains a putative N-terminal transit peptide followed by a 557-amino acid SSIII-specific domain (SSIII-SD) with three internal repeats and a C-terminal catalytic domain of 450 amino acids. Here, using computational characterization techniques, we show that each of the three internal repeats encodes a starch-binding domain (SBD). Although the SSIII from A. thaliana and its close homologous proteins show no detectable sequence similarity with characterized SBD sequences, the amino acid residues known to be involved in starch binding are well conserved., (Proteins 2006. (c) 2006 Wiley-Liss, Inc.)

We report the identification by two hybrid screens of two novel similar proteins, called Arabidopsis thaliana gamma carbonic anhydrase like1 and 2 (AtgammaCAL1 and AtgammaCAL2), that interact specifically with putative Arabidopsis thaliana gamma Carbonic Anhydrase (AtgammaCA) proteins in plant mitochondria. The interaction region that was located in the N-terminal 150 amino acids of mature AtgammaCA and AtgammaCA like proteins represents a new interaction domain. In vitro experiments indicate that these proteins are imported into mitochondria and are associated with mitochondrial complex I as AtgammaCAs. All plant species analyzed contain both AtgammaCA and AtgammaCAL sequences indicating that these genes were conserved throughout plant evolution. Structural modeling of AtgammaCAL sequences show a deviation of functionally important active site residues with respect to gammaCAs but could form active interfaces in the interaction with AtgammaCAs. We postulate a CA complex tightly associated to plant mitochondrial complex.

Three genes from Arabidopsis thaliana with high sequence similarity to gamma carbonic anhydrase (gammaCA), a Zn containing enzyme from Methanosarcina thermophila (CAM), were identified and characterized. Evolutionary and structural analyses predict that these genes code for active forms of gammaCA. Phylogenetic analyses reveal that these Arabidopsis gene products cluster together with CAM and related sequences from alpha and gamma proteobacteria, organisms proposed as the mitochondrial endosymbiont ancestor. Indeed, in vitro and in vivo experiments indicate that these gene products are transported into the mitochondria as occurs with several mitochondrial protein genes transferred, during evolution, from the endosymbiotic bacteria to the host genome. Moreover, putative CAM orthologous genes are detected in other plants and green algae and were predicted to be imported to mitochondria. Structural modeling and sequence analysis performed in more than a hundred homologous sequences show a high conservation of functionally important active site residues. Thus, the three histidine residues involved in Zn coordination (His 81, 117 and 122), Arg 59, Asp 61, Gin 75, and Asp 76 of CAM are conserved and properly arranged in the active site cavity of the models. Two other functionally important residues (Glu 62 and Glu 84 of CAM) are lacking, but alternative amino acids that might serve to their roles are postulated. Accordingly, we propose that photosynthetic eukaryotic organisms (green algae and plants) contain gammaCAs and that these enzymes codified by nuclear genes are imported into mitochondria to accomplish their biological function.

Dynactin is a multimeric protein essential for the minus-end-directed transport driven by microtubule-based motor dynein. The pointed-end subcomplex in dynactin contains p62, p27, p25, and Arp11 subunits, and is thought to participate in interactions with membranous cargoes. We used sequence and structure prediction analysis to study dynactins p25 and p27. Here we present evidence that strongly supports that dynactins p27 and p25 contain the isoleucine-patch motif and adopt the left-handed parallel beta-helix fold. The structural models we obtained could contribute to the understanding of the complex interactions that dynactins are able to establish with cargo particles, microtubules or other dynactin subunits.

Riboflavin, an essential cofactor for all organisms, is biosynthesized in plants, fungi and microorganisms. The penultimate step in the pathway is catalyzed by the enzyme lumazine synthase. One of the most distinctive characteristics of this enzyme is that it is found in different species in two different quaternary structures, pentameric and icosahedral, built from practically the same structural monomeric unit. In fact, the icosahedral structure is best described as a capsid of twelve pentamers. Despite this noticeable difference, the active sites are virtually identical in all structurally studied members. Furthermore, the main regions involved in the catalysis are located at the interface between adjacent subunits in the pentamer. Thus, the two quaternary forms of the enzyme must meet similar structural requirements to achieve their function, but, at the same time, they should differ in the sequence traits responsible for the different quaternary structures observed. Here, we present a combined analysis that includes sequence-structure and evolutionary studies to find the sequence determinants of the different quaternary assemblies of this enzyme. A data set containing 86 sequences of the lumazine synthase family was recovered by sequence similarity searches. Seven of them had resolved three-dimensional structures. A subsequent phylogenetic reconstruction by maximum parsimony (MP) allowed division of the total set into two clusters in accord with their quaternary structure. The comparison between the patterns of three-dimensional contacts derived from the known three-dimensional structures and variation in sequence conservation revealed a significant shift in structural constraints of certain positions. Also, to explore the changes in functional constraints between the two groups, site-specific evolutionary rate shifts were analyzed. We found that the positions involved in icosahedral contacts suffer a larger increase in constraints than the rest. We found eight sequence sites that would be the most important icosahedral sequence determinants. We discuss our results and compare them with previous work. These findings should contribute to refinement of the current structural data, to the design of assays that explore the role of these positions, to the structural characterization of new sequences, and to initiation of a study of the underlying evolutionary mechanisms.