Frustraevo: a web server to localize and quantify the conservation of local energetic frustration in protein families.

According to the Principle of Minimal Frustration, folded proteins can only have a minimal number of strong energetic conflicts in their native states. However, not all interactions are energetically optimized for folding but some remain in energetic conflict, i.e. they are highly frustrated. This remaining local energetic frustration has been shown to be statistically correlated with distinct functional aspects such as protein-protein interaction sites, allosterism and catalysis. Fuelled by the recent breakthroughs in efficient protein structure prediction that have made available good quality models for most proteins, we have developed a strategy to calculate local energetic frustration within large protein families and quantify its conservation over evolutionary time. Based on this evolutionary information we can identify how stability and functional constraints have appeared at the common ancestor of the family and have been maintained over the course of evolution. Here, we present FrustraEvo, a web server tool to calculate and quantify the conservation of local energetic frustration in protein families.

FrustratometeR: an R-package to compute local frustration in protein structures, point mutants and MD simulations.

SUMMARY: Once folded, natural protein molecules have few energetic conflicts within their polypeptide chains. Many protein structures do however contain regions where energetic conflicts remain after folding, i.e. they are highly frustrated. These regions, kept in place over evolutionary and physiological timescales, are related to several functional aspects of natural proteins such as protein-protein interactions, small ligand recognition, catalytic sites and allostery. Here, we present FrustratometeR, an R package that easily computes local energetic frustration on a personal computer or a cluster. This package facilitates large scale analysis of local frustration, point mutants and molecular dynamics (MD) trajectories, allowing straightforward integration of local frustration analysis into pipelines for protein structural analysis. AVAILABILITY AND IMPLEMENTATION: https://github.com/proteinphysiologylab/frustratometeR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Local frustration around enzyme active sites.

Conflicting biological goals often meet in the specification of protein sequences for structure and function. Overall, strong energetic conflicts are minimized in folded native states according to the principle of minimal frustration, so that a sequence can spontaneously fold, but local violations of this principle open up the possibility to encode the complex energy landscapes that are required for active biological functions. We survey the local energetic frustration patterns of all protein enzymes with known structures and experimentally annotated catalytic residues. In agreement with previous hypotheses, the catalytic sites themselves are often highly frustrated regardless of the protein oligomeric state, overall topology, and enzymatic class. At the same time a secondary shell of more weakly frustrated interactions surrounds the catalytic site itself. We evaluate the conservation of these energetic signatures in various family members of major enzyme classes, showing that local frustration is evolutionarily more conserved than the primary structure itself.

Reconstructing complex lineage trees from scRNA-seq data using MERLoT.

Advances in single-cell transcriptomics techniques are revolutionizing studies of cellular differentiation and heterogeneity. It has become possible to track the trajectory of thousands of genes across the cellular lineage trees that represent the temporal emergence of cell types during dynamic processes. However, reconstruction of cellular lineage trees with more than a few cell fates has proved challenging. We present MERLoT (https://github.com/soedinglab/merlot), a flexible and user-friendly tool to reconstruct complex lineage trees from single-cell transcriptomics data. It can impute temporal gene expression profiles along the reconstructed tree. We show MERLoT's capabilities on various real cases and hundreds of simulated datasets.

Reflections on a journey: a retrospective of the ISCB Student Council symposium series.

This article describes the motivation, origin and evolution of the student symposia series organised by the ISCB Student Council. The meeting series started thirteen years ago in Madrid and has spread to four continents. The article concludes with the highlights of the most recent edition of annual Student Council Symposium held in conjunction with the 25th Conference on Intelligent Systems for Molecular Biology and the 16th European Conference on Computational Biology, in Prague, in July 2017.

Inferring repeat-protein energetics from evolutionary information.

Natural protein sequences contain a record of their history. A common constraint in a given protein family is the ability to fold to specific structures, and it has been shown possible to infer the main native ensemble by analyzing covariations in extant sequences. Still, many natural proteins that fold into the same structural topology show different stabilization energies, and these are often related to their physiological behavior. We propose a description for the energetic variation given by sequence modifications in repeat proteins, systems for which the overall problem is simplified by their inherent symmetry. We explicitly account for single amino acid and pair-wise interactions and treat higher order correlations with a single term. We show that the resulting evolutionary field can be interpreted with structural detail. We trace the variations in the energetic scores of natural proteins and relate them to their experimental characterization. The resulting energetic evolutionary field allows the prediction of the folding free energy change for several mutants, and can be used to generate synthetic sequences that are statistically indistinguishable from the natural counterparts.

Protein Frustratometer 2: a tool to localize energetic frustration in protein molecules, now with electrostatics.

The protein frustratometer is an energy landscape theory-inspired algorithm that aims at localizing and quantifying the energetic frustration present in protein molecules. Frustration is a useful concept for analyzing proteins' biological behavior. It compares the energy distributions of the native state with respect to structural decoys. The network of minimally frustrated interactions encompasses the folding core of the molecule. Sites of high local frustration often correlate with functional regions such as binding sites and regions involved in allosteric transitions. We present here an upgraded version of a webserver that measures local frustration. The new implementation that allows the inclusion of electrostatic energy terms, important to the interactions with nucleic acids, is significantly faster than the previous version enabling the analysis of large macromolecular complexes within a user-friendly interface. The webserver is freely available at URL: http://frustratometer.qb.fcen.uba.ar.

INSECT 2.0: a web-server for genome-wide cis-regulatory modules prediction.

UNLABELLED: INSECT is a user-friendly web server to predict the occurrence of Cis-Regulatory Modules (CRMs), which control gene expression. Here, we present a new release of INSECT which includes several new features, such as whole genome analysis, nucleosome occupancy predictions, and which provides additional links to third-party functional tools that complement user capabilities, CRM analysis and hypothesis construction. Improvements in the core implementation have led to a faster and more efficient tool. In addition, this new release introduces a new interface designed for a more integrative and dynamic user experience. AVAILABILITY AND IMPLEMENTATION: http://bioinformatics.ibioba-mpsp-conicet.gov.ar/INSECT2 CONTACT: pyankilevich@ibioba-mpsp-conicet.gov.ar.

Structural and Energetic Characterization of the Ankyrin Repeat Protein Family.

Ankyrin repeat containing proteins are one of the most abundant solenoid folds. Usually implicated in specific protein-protein interactions, these proteins are readily amenable for design, with promising biotechnological and biomedical applications. Studying repeat protein families presents technical challenges due to the high sequence divergence among the repeating units. We developed and applied a systematic method to consistently identify and annotate the structural repetitions over the members of the complete Ankyrin Repeat Protein Family, with increased sensitivity over previous studies. We statistically characterized the number of repeats, the folding of the repeat-arrays, their structural variations, insertions and deletions. An energetic analysis of the local frustration patterns reveal the basic features underlying fold stability and its relation to the functional binding regions. We found a strong linear correlation between the conservation of the energetic features in the repeat arrays and their sequence variations, and discuss new insights into the organization and function of these ubiquitous proteins.

RepeatsDB: a database of tandem repeat protein structures.

RepeatsDB (http://repeatsdb.bio.unipd.it/) is a database of annotated tandem repeat protein structures. Tandem repeats pose a difficult problem for the analysis of protein structures, as the underlying sequence can be highly degenerate. Several repeat types haven been studied over the years, but their annotation was done in a case-by-case basis, thus making large-scale analysis difficult. We developed RepeatsDB to fill this gap. Using state-of-the-art repeat detection methods and manual curation, we systematically annotated the Protein Data Bank, predicting 10,745 repeat structures. In all, 2797 structures were classified according to a recently proposed classification schema, which was expanded to accommodate new findings. In addition, detailed annotations were performed in a subset of 321 proteins. These annotations feature information on start and end positions for the repeat regions and units. RepeatsDB is an ongoing effort to systematically classify and annotate structural protein repeats in a consistent way. It provides users with the possibility to access and download high-quality datasets either interactively or programmatically through web services.

Capturing coevolutionary signals inrepeat proteins.

BACKGROUND: The analysis of correlations of amino acid occurrences in globular domains has led to the development of statistical tools that can identify native contacts - portions of the chains that come to close distance in folded structural ensembles. Here we introduce a direct coupling analysis for repeat proteins - natural systems for which the identification of folding domains remains challenging. RESULTS: We show that the inherent translational symmetry of repeat protein sequences introduces a strong bias in the pair correlations at precisely the length scale of the repeat-unit. Equalizing for this bias in an objective way reveals true co-evolutionary signals from which local native contacts can be identified. Importantly, parameter values obtained for all other interactions are not significantly affected by the equalization. We quantify the robustness of the procedure and assign confidence levels to the interactions, identifying the minimum number of sequences needed to extract evolutionary information in several repeat protein families. CONCLUSIONS: The overall procedure can be used to reconstruct the interactions at distances larger than repeat-pairs, identifying the characteristics of the strongest couplings in each family, and can be applied to any system that appears translationally symmetric.

Repeat proteins challenge the concept of structural domains.

Structural domains are believed to be modules within proteins that can fold and function independently. Some proteins show tandem repetitions of apparent modular structure that do not fold independently, but rather co-operate in stabilizing structural forms that comprise several repeat-units. For many natural repeat-proteins, it has been shown that weak energetic links between repeats lead to the breakdown of co-operativity and the appearance of folding sub-domains within an apparently regular repeat array. The quasi-1D architecture of repeat-proteins is crucial in detailing how the local energetic balances can modulate the folding dynamics of these proteins, which can be related to the physiological behaviour of these ubiquitous biological systems.

The upside of failure: how regional student groups learn from their mistakes.

Success is the result of planning, hard work, determination, foresight, and a little bit of luck. Unfortunately, nobody has thought to pave the road to success. Although failure can be discouraging and time-consuming, it presents incredible learning opportunities-the biggest difference between those who succeed and those who abandon their projects lies in their response to adversity. This article reviews events undertaken by the Regional Student Groups (RSGs) in India and Argentina, the problems they encountered, and what can be learned from them. RSG-India attempted to organize an online scientific meeting (also known as a virtual conference) with geographically dispersed stakeholders, a totally new concept for them. RSG-Argentina tackled the challenge of organizing a two-day symposium, their first event ever. Some of the complications they faced were easy to fix, others led to the cancellation of activities, and all of them resulted in valuable lessons. The main goal of this article is to highlight, through their experiences, the universal importance of a healthy panel of contingency plans.

Highlights from the 1st ISCB Latin American Student Council Symposium 2014. Introduction.

This report summarizes the scientific content and activities of the first edition of the Latin American Symposium organized by the Student Council of the International Society for Computational Biology (ISCB), held in conjunction with the Third Latin American conference from the International Society for Computational Biology (ISCB-LA 2014) in Belo Horizonte, Brazil, on October 27, 2014.

INSECT: IN-silico SEarch for Co-occurring Transcription factors.

MOTIVATION: Transcriptional regulation occurs through the concerted actions of multiple transcription factors (TFs) that bind cooperatively to cis-regulatory modules (CRMs) of genes. These CRMs usually contain a variable number of transcription factor-binding sites (TFBSs) involved in related cellular and physiological processes. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) has been effective in detecting TFBSs and nucleosome location to identify potential CRMs in genome-wide studies. Although several attempts were previously reported to predict the potential binding of TFs at TFBSs within CRMs by comparing different ChIP-seq data, these have been hampered by excessive background, usually emerging as a consequence of experimental conditions. To understand these complex regulatory circuits, it would be helpful to have reliable and updated user-friendly tools to assist in the identification of TFBSs and CRMs for gene(s) of interest. RESULTS: Here we present INSECT (IN-silico SEarch for Co-occurring Transcription factors), a novel web server for identifying potential TFBSs and CRMs in gene sequences. By combining several strategies, INSECT provides flexible analysis of multiple co-occurring TFBSs, by applying differing search schemes and restriction parameters. availability and implementation: INSECT is freely available as a web server at http://bioinformatics.ibioba-mpsp-conicet.gov.ar/INSECT .

Protein frustratometer: a tool to localize energetic frustration in protein molecules.

The frustratometer is an energy landscape theory-inspired algorithm that aims at quantifying the location of frustration manifested in protein molecules. Frustration is a useful concept for gaining insight to the proteins biological behavior by analyzing how the energy is distributed in protein structures and how mutations or conformational changes shift the energetics. Sites of high local frustration often indicate biologically important regions involved in binding or allostery. In contrast, minimally frustrated linkages comprise a stable folding core of the molecule that is conserved in conformational changes. Here, we describe the implementation of these ideas in a webserver freely available at the National EMBNet node-Argentina, at URL: http://lfp.qb.fcen.uba.ar/embnet/.

1st ASCS: Expanding the ISCB Student Council Symposia to Asia.

Since 2004, the ISCB Student Council (ISCB-SC) has successfully organized Student Council Symposia across several continents, including North America, Latin America, Europe, and Africa, as well as local events led by more than 25 Regional Student Groups (RSG) across the world. The ISCB-SC Symposia provide students and early career researchers the chance to showcase their work at an international venue in a format that includes keynote talks, round table discussions, workshops, and more. After several efforts spanning several years to build enough critical mass in the region, we have successfully organized the first Asian Student Council Symposium (1st ASCS). This article discusses the organizational details of this unprecedented event, the challenges faced, and the lessons learned.

ISCB Student Council Symposium 2021, a virtual global venue: challenges and lessons learned.

Since 2004, the ISCB Student Council has been organizing different symposia worldwide, gathering together the community of young computational biologists. Due to the coronavirus disease 2019 (COVID-19) pandemic situation, the world scientific community was forced to cancel in-person meetings for almost two years, imposing the adoption of virtual formats instead. After the successful editions of our continental symposia in 2020 in the USA, Latin America, and Europe, we organized our flagship global event, the Student Council Symposium (SCS) 2021, trying to apply all previous lessons learned and to exploit the advantages that virtuality has to offer.

Local energetic frustration conservation in protein families and superfamilies.

Energetic local frustration offers a biophysical perspective to interpret the effects of sequence variability on protein families. Here we present a methodology to analyze local frustration patterns within protein families and superfamilies that allows us to uncover constraints related to stability and function, and identify differential frustration patterns in families with a common ancestry. We analyze these signals in very well studied protein families such as PDZ, SH3, ɑ and ß globins and RAS families. Recent advances in protein structure prediction make it possible to analyze a vast majority of the protein space. An automatic and unsupervised proteome-wide analysis on the SARS-CoV-2 virus demonstrates the potential of our approach to enhance our understanding of the natural phenotypic diversity of protein families beyond single protein instances. We apply our method to modify biophysical properties of natural proteins based on their family properties, as well as perform unsupervised analysis of large datasets to shed light on the physicochemical signatures of poorly characterized proteins such as the ones belonging to emergent pathogens.

Resolving the fine structure in the energy landscapes of repeat proteins.

Ankyrin (ANK) repeat proteins are coded by tandem occurrences of patterns with around 33 amino acids. They often mediate protein-protein interactions in a diversity of biological systems. These proteins have an elongated non-globular shape and often display complex folding mechanisms. This work investigates the energy landscape of representative proteins of this class made up of 3, 4 and 6 ANK repeats using the energy-landscape visualisation method (ELViM). By combining biased and unbiased coarse-grained molecular dynamics AWSEM simulations that sample conformations along the folding trajectories with the ELViM structure-based phase space, one finds a three-dimensional representation of the globally funnelled energy surface. In this representation, it is possible to delineate distinct folding pathways. We show that ELViMs can project, in a natural way, the intricacies of the highly dimensional energy landscapes encoded by the highly symmetric ankyrin repeat proteins into useful low-dimensional representations. These projections can discriminate between multiplicities of specific parallel folding mechanisms that otherwise can be hidden in oversimplified depictions.