RosettaDDGPrediction for high-throughput mutational scans: From stability to binding

Reliable prediction of free energy changes upon amino acid substitutions (ΔΔGs) is crucial to investigate their impact on protein stability and protein–protein interaction. Advances in experimental mutational scans allow high-throughput studies thanks to multiplex techniques. On the other hand, genomics initiatives provide a large amount of data on disease-related variants that can benefit from analyses with structure-based methods. Therefore, the computational field should keep the same pace and provide new tools for fast and accurate high-throughput ΔΔG calculations. In this context, the Rosetta modeling suite implements effective approaches to predict folding/unfolding ΔΔGs in a protein monomer upon amino acid substitutions and calculate the changes in binding free energy in protein complexes. However, their application can be challenging to users without extensive experience with Rosetta. Furthermore, Rosetta protocols for ΔΔG prediction are designed considering one variant at a time, making the setup of high-throughput screenings cumbersome. For these reasons, we devised RosettaDDGPrediction, a customizable Python wrapper designed to run free energy calculations on a set of amino acid substitutions using Rosetta protocols with little intervention from the user. Moreover, RosettaDDGPrediction assists with checking completed runs and aggregates raw data for multiple variants, as well as generates publication-ready graphics. We showed the potential of the tool in four case studies, including variants of uncertain significance in childhood cancer, proteins with known experimental unfolding ΔΔGs values, interactions between target proteins and disordered motifs, and phosphomimetics. RosettaDDGPrediction is available, free of charge and under GNU General Public License v3.0, at https://github.com/ELELAB/RosettaDDGPrediction .     

Thermodynamic coupling between neighboring binding sites in homo‐oligomeric ligand sensing proteins from mass resolved ligand‐dependent population distributions

Homo‐oligomeric ligand‐activated proteins are ubiquitous in biology. The functions of such molecules are commonly regulated by allosteric coupling between ligand‐binding sites. Understanding the basis for this regulation requires both quantifying the free energy ΔG transduced between sites, and the structural basis by which it is transduced. We consider allostery in three variants of the model ring‐shaped homo‐oligomeric trp RNA‐binding attenuation protein (TRAP). First, we developed a nearest‐neighbor statistical thermodynamic binding model comprising microscopic free energies for ligand binding to isolated sites ΔG ₀, and for coupling between adjacent sites, ΔG _α . Using the resulting partition function (PF) we explored the effects of these parameters on simulated population distributions for the 2 ^N possible liganded states. We then experimentally monitored ligand‐dependent population shifts using conventional spectroscopic and calorimetric methods and using native mass spectrometry (MS). By resolving species with differing numbers of bound ligands by their mass, native MS revealed striking differences in their ligand‐dependent population shifts. Fitting the populations to a binding polynomial derived from the PF yielded coupling free energy terms corresponding to orders of magnitude differences in cooperativity. Uniquely, this approach predicts which of the possible 2 ^N liganded states are populated at different ligand concentrations, providing necessary insights into regulation. The combination of statistical thermodynamic modeling with native MS may provide the thermodynamic foundation for a meaningful understanding of the structure–thermodynamic linkage that drives cooperativity.     

dGPredictor: Automated fragmentation method for metabolic reaction free energy prediction and de novo pathway design

Group contribution (GC) methods are conventionally used in thermodynamics analysis of metabolic pathways to estimate the standard Gibbs energy change (Δ_rG′^o) of enzymatic reactions from limited experimental measurements. However, these methods are limited by their dependence on manually curated groups and inability to capture stereochemical information, leading to low reaction coverage. Herein, we introduce an automated molecular fingerprint-based thermodynamic analysis tool called dGPredictor that enables the consideration of stereochemistry within metabolite structures and thus increases reaction coverage. dGPredictor has comparable prediction accuracy compared to existing GC methods and can capture Gibbs energy changes for isomerase and transferase reactions, which exhibit no overall group changes. We also demonstrate dGPredictor’s ability to predict the Gibbs energy change for novel reactions and seamless integration within de novo metabolic pathway design tools such as novoStoic for safeguarding against the inclusion of reaction steps with infeasible directionalities. To facilitate easy access to dGPredictor, we developed a graphical user interface to predict the standard Gibbs energy change for reactions at various pH and ionic strengths. The tool allows customized user input of known metabolites as KEGG IDs and novel metabolites as InChI strings (https://github.com/maranasgroup/dGPredictor).     

Glucagon signalling in the dorsal vagal complex is sufficient and necessary for high‐protein feeding to regulate glucose homeostasis in vivo

High‐protein feeding acutely lowers postprandial glucose concentration compared to low‐protein feeding, despite a dichotomous rise of circulating glucagon levels. The physiological role of this glucagon rise has been largely overlooked. We here first report that glucagon signalling in the dorsal vagal complex (DVC) of the brain is sufficient to lower glucose production by activating a Gcgr–PKA–ERK–K_ATP channel signalling cascade in the DVC of rats in vivo. We further demonstrate that direct blockade of DVC Gcgr signalling negates the acute ability of high‐ vs. low‐protein feeding to reduce plasma glucose concentration, indicating that the elevated circulating glucagon during high‐protein feeding acts in the brain to lower plasma glucose levels. These data revise the physiological role of glucagon and argue that brain glucagon signalling contributes to glucose homeostasis during dietary protein intake.     

Ascochyta rabiei: A threat to global chickpea production

The necrotrophic fungus Ascochyta rabiei causes Ascochyta blight (AB) disease in chickpea. A. rabiei infects all aerial parts of the plant, which results in severe yield loss. At present, AB disease occurs in most chickpea‐growing countries. Globally increased incidences of A. rabiei infection and the emergence of new aggressive isolates directed the interest of researchers toward understanding the evolution of pathogenic determinants in this fungus. In this review, we summarize the molecular and genetic studies of the pathogen along with approaches that are helping in combating the disease. Possible areas of future research are also suggested.Taxonomykingdom Mycota, phylum Ascomycota, class Dothideomycetes, subclass Coelomycetes, order Pleosporales, family Didymellaceae, genus Ascochyta, species rabiei. Primary host A. rabiei survives primarily on Cicer species.Disease symptoms A. rabiei infects aboveground parts of the plant including leaves, petioles, stems, pods, and seeds. The disease symptoms first appear as watersoaked lesions on the leaves and stems, which turn brown or dark brown. Early symptoms include small circular necrotic lesions visible on the leaves and oval brown lesions on the stem. At later stages of infection, the lesions may girdle the stem and the region above the girdle falls off. The disease severity increases at the reproductive stage and rounded lesions with concentric rings, due to asexual structures called pycnidia, appear on leaves, stems, and pods. The infected pod becomes blighted and often results in shrivelled and infected seeds.Disease management strategiesCrop failures may be avoided by judicious practices of integrated disease management based on the use of resistant or tolerant cultivars and growing chickpea in areas where conditions are least favourable for AB disease development. Use of healthy seeds free of A. rabiei, seed treatments with fungicides, and proper destruction of diseased stubbles can also reduce the fungal inoculum load. Crop rotation with nonhost crops is critical for controlling the disease. Planting moderately resistant cultivars and prudent application of fungicides is also a way to combat AB disease. However, the scarcity of AB‐resistant accessions and the continuous evolution of the pathogen challenges the disease management process.Useful websites https://www.ndsu.edu/pubweb/pulse‐info/resourcespdf/Ascochyta%20blight%20of%20chickpea.pdf https://saskpulse.com/files/newsletters/180531_ascochyta_in_chickpeas‐compressed.pdf http://www.pulseaus.com.au/growing‐pulses/bmp/chickpea/ascochyta‐blight http://agriculture.vic.gov.au/agriculture/pests‐diseases‐and‐weeds/plant‐diseases/grains‐pulses‐and‐cereals/ascochyta‐blight‐of‐chickpea http://www.croppro.com.au/crop_disease_manual/ch05s02.php https://www.northernpulse.com/uploads/resources/722/handout‐chickpeaascochyta‐nov13‐2011.pdf http://oar.icrisat.org/184/1/24_2010_IB_no_82_Host_Plant https://www.crop.bayer.com.au/find‐crop‐solutions/by‐pest/diseases/ascochyta‐blight     

Assembly of Collagen Matrices as a Phase Transition Revealed by Structural and Rheologic Studies

We have studied the structural and viscoelastic properties of assembling networks of the extracellular matrix protein type-I collagen by means of phase contrast microscopy and rotating disk rheometry. The initial stage of the assembly is a nucleation process of collagen monomers associating to randomly distributed branched clusters with extensions of several microns. Eventually a sol-gel transition takes place, which is due to the interconnection of these clusters. We analyzed this transition in terms of percolation theory. The viscoelastic parameters (storage modulus G′ and loss modulus G″) were measured as a function of time for five different frequencies ranging from ω = 0.2 rad/s to 6.9 rad/s. We found that at the gel point both G′ and G″ obey a scaling law , with the critical exponent Δ = 0.7 and a critical loss angle being independent of frequency as predicted by percolation theory. Gelation of collagen thus represents a second order phase transition.     

AB‐Bind: Antibody binding mutational database for computational affinity predictions

Antibodies (Abs) are a crucial component of the immune system and are often used as diagnostic and therapeutic agents. The need for high‐affinity and high‐specificity antibodies in research and medicine is driving the development of computational tools for accelerating antibody design and discovery. We report a diverse set of antibody binding data with accompanying structures that can be used to evaluate methods for modeling antibody interactions. Our Antibody‐Bind (AB‐Bind) database includes 1101 mutants with experimentally determined changes in binding free energies (ΔΔG) across 32 complexes. Using the AB‐Bind data set, we evaluated the performance of protein scoring potentials in their ability to predict changes in binding free energies upon mutagenesis. Numerical correlations between computed and observed ΔΔG values were low (r = 0.16–0.45), but the potentials exhibited predictive power for classifying variants as improved vs weakened binders. Performance was evaluated using the area under the curve (AUC) for receiver operator characteristic (ROC) curves; the highest AUC values for 527 mutants with |ΔΔG| > 1.0 kcal/mol were 0.81, 0.87, and 0.88 using STATIUM, FoldX, and Discovery Studio scoring potentials, respectively. Some methods could also enrich for variants with improved binding affinity; FoldX and Discovery Studio were able to correctly rank 42% and 30%, respectively, of the 80 most improved binders (those with ΔΔG < −1.0 kcal/mol) in the top 5% of the database. This modest predictive performance has value but demonstrates the continuing need to develop and improve protein energy functions for affinity prediction.     

A Real-Time All-Atom Structural Search Engine for Proteins

Protein designers use a wide variety of software tools for de novo design, yet their repertoire still lacks a fast and interactive all-atom search engine. To solve this, we have built the Suns program: a real-time, atomic search engine integrated into the PyMOL molecular visualization system. Users build atomic-level structural search queries within PyMOL and receive a stream of search results aligned to their query within a few seconds. This instant feedback cycle enables a new “designability”-inspired approach to protein design where the designer searches for and interactively incorporates native-like fragments from proven protein structures. We demonstrate the use of Suns to interactively build protein motifs, tertiary interactions, and to identify scaffolds compatible with hot-spot residues. The official web site and installer are located at http://www.degradolab.org/suns/ and the source code is hosted at https://github.com/godotgildor/Suns (PyMOL plugin, BSD license), https://github.com/Gabriel439/suns-cmd (command line client, BSD license), and https://github.com/Gabriel439/suns-search (search engine server, GPLv2 license).

This is a PLOS Computational Biology Software Article

     

High‐altitude adaptation in vertebrates as revealed by mitochondrial genome analyses

The high‐altitude environment may drive vertebrate evolution in a certain way, and vertebrates living in different altitude environments might have different energy requirements. We hypothesized that the high‐altitude environment might impose different influences on vertebrate mitochondrial genomes (mtDNA). We used selection pressure analyses and PIC (phylogenetic independent contrasts) analysis to detect the evolutionary rate of vertebrate mtDNA protein‐coding genes (PCGs) from different altitudes. The results showed that the ratio of nonsynonymous/synonymous substitutions (dN/dS) in the mtDNA PCGs was significantly higher in high‐altitude vertebrates than in low‐altitude vertebrates. The seven rapidly evolving genes were shared by the high‐altitude vertebrates, and only one positive selection gene (ND5 gene) was detected in the high‐altitude vertebrates. Our results suggest the mtDNA evolutionary rate in high‐altitude vertebrates was higher than in low‐altitude vertebrates as their evolution requires more energy in a high‐altitude environment. Our study demonstrates the high‐altitude environment (low atmospheric O₂ levels) drives vertebrate evolution in mtDNA PCGs.     

RCSB Protein Data bank: Tools for visualizing and understanding biological macromolecules in 3D

Now in its 52nd year of continuous operations, the Protein Data Bank (PDB) is the premiere open‐access global archive housing three‐dimensional (3D) biomolecular structure data. It is jointly managed by the Worldwide Protein Data Bank (wwPDB) partnership. The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is funded by the National Science Foundation, National Institutes of Health, and US Department of Energy and serves as the US data center for the wwPDB. RCSB PDB is also responsible for the security of PDB data in its role as wwPDB‐designated Archive Keeper. Every year, RCSB PDB serves tens of thousands of depositors of 3D macromolecular structure data (coming from macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro‐electron diffraction). The RCSB PDB research‐focused web portal (RCSB.org) makes PDB data available at no charge and without usage restrictions to many millions of PDB data consumers around the world. The RCSB PDB training, outreach, and education web portal (PDB101.RCSB.org) serves nearly 700 K educators, students, and members of the public worldwide. This invited Tools Issue contribution describes how RCSB PDB (i) is organized; (ii) works with wwPDB partners to process new depositions; (iii) serves as the wwPDB‐designated Archive Keeper; (iv) enables exploration and 3D visualization of PDB data via RCSB.org; and (v) supports training, outreach, and education via PDB101.RCSB.org. New tools and features at RCSB.org are presented using examples drawn from high‐resolution structural studies of proteins relevant to treatment of human cancers by targeting immune checkpoints.     

Syn Wiki: Functional annotation of the first artificial organism Mycoplasma mycoides JCVI‐syn3A

The new field of synthetic biology aims at the creation of artificially designed organisms. A major breakthrough in the field was the generation of the artificial synthetic organism Mycoplasma mycoides JCVI‐syn3A. This bacterium possesses only 452 protein‐coding genes, the smallest number for any organism that is viable independent of a host cell. However, about one third of the proteins have no known function indicating major gaps in our understanding of simple living cells. To facilitate the investigation of the components of this minimal bacterium, we have generated the database SynWiki (http://synwiki.uni-goettingen.de/). SynWiki is based on a relational database and gives access to published information about the genes and proteins of M. mycoides JCVI‐syn3A. To gain a better understanding of the functions of the genes and proteins of the artificial bacteria, protein–protein interactions that may provide clues for the protein functions are included in an interactive manner. SynWiki is an important tool for the synthetic biology community that will support the comprehensive understanding of a minimal cell as well as the functional annotation of so far uncharacterized proteins.     

Molecular basis of cross‐species ACE2 interactions with SARS‐CoV‐2‐like viruses of pangolin origin

Correction to: The EMBO Journal (2021) 40: e107786. DOI 10.15252/embj.2021107786 | Published online 8 June 2021The authors would like to add three references to the paper: Starr et al and Zahradník et al also reported that the Q498H or Q498R mutation has enhanced binding affinity to ACE2; and Liu et al reported on the binding of bat coronavirus to ACE2.Starr et al and Zahradník et al have now been cited in the Discussion section, and the following sentence has been corrected from:“According to our data, the SARS‐CoV‐2 RBD with Q498H increases the binding strength to hACE2 by 5‐fold, suggesting the Q498H mutant is more ready to interact with human receptor than the wildtype and highlighting the necessity for more strict control of virus and virus‐infected animals”.to“Here, according to our data and two recently published papers, the SARS‐CoV‐2 RBD with Q498H or Q498R increases the binding strength to hACE2 (Starr et al, 2020; Zahradník et al, 2021), suggesting the mutant with Q498H or Q498R is more ready to interact with human receptor than the wild type and highlighting the necessity for more strict control of virus and virus‐infected animals”.The Liu et al citation has been added to the following sentence:“In another paper published by our group recently, RaTG13 RBD was found to bind to hACE2 with much lower binding affinity than SARS‐CoV‐2 though RaTG13 displays the highest whole‐genome sequence identity (96.2%) with the SARS‐CoV‐2 (Liu et al, 2021)”.Additionally, the authors have added the GISAID accession IDs to the sequence names of the SARS‐CoV‐2 in two human samples (Discussion section). To make identification unambiguous, the sequence names have been updated from “SA‐lsf‐27 and SA‐lsf‐37” to “GISAID accession ID: EPI_ISL_672581 and EPI_ISL_672589”.Lastly, the authors declare in the Materials and Methods section that all experiments employed SARS‐CoV‐2 pseudovirus in cultured cells. These experiments were performed in a BSL‐2‐level laboratory and approved by Science and Technology Conditions Platform Office, Institute of Microbiology, Chinese Academy of Sciences.These changes are herewith incorporated into the paper.     

PDBsum extras: SARS‐CoV‐2 and AlphaFold models

The PDBsum web server provides structural analyses of the entries in the Protein Data Bank (PDB). Two recent additions are described here. The first is the detailed analysis of the SARS‐CoV‐2 virus protein structures in the PDB. These include the variants of concern, which are shown both on the sequences and 3D structures of the proteins. The second addition is the inclusion of the available AlphaFold models for human proteins. The pages allow a search of the protein against existing structures in the PDB via the Sequence Annotated by Structure (SAS) server, so one can easily compare the predicted model against experimentally determined structures. The server is freely accessible to all at http://www.ebi.ac.uk/pdbsum.     

BepiPred‐3.0: Improved B‐cell epitope prediction using protein language models

B‐cell epitope prediction tools are of great medical and commercial interest due to their practical applications in vaccine development and disease diagnostics. The introduction of protein language models (LMs), trained on unprecedented large datasets of protein sequences and structures, tap into a powerful numeric representation that can be exploited to accurately predict local and global protein structural features from amino acid sequences only. In this paper, we present BepiPred‐3.0, a sequence‐based epitope prediction tool that, by exploiting LM embeddings, greatly improves the prediction accuracy for both linear and conformational epitope prediction on several independent test sets. Furthermore, by carefully selecting additional input variables and epitope residue annotation strategy, performance was further improved, thus achieving unprecedented predictive power. Our tool can predict epitopes across hundreds of sequences in minutes. It is freely available as a web server and a standalone package at https://services.healthtech.dtu.dk/service.php?BepiPred-3.0 with a user‐friendly interface to navigate the results.     

Cold denaturation of monoclonal antibodies

The susceptibility of monoclonal antibodies (mAbs) to undergo cold denaturation remains unexplored. In this study, the phenomenon of cold denaturation was investigated for a mAb, mAb1, through thermodynamic and spectroscopic analyses. tryptophan fluorescence and circular dichroism (CD) spectra were recorded for the guanidine hydrochloride (GuHCl)-induced unfolding of mAb1 at pH 6.3 at temperatures ranging from −5 to 50°C. A three-state unfolding model incorporating the linear extrapolation method was fit to the fluorescence data to obtain an apparent free energy of unfolding, ΔG_u, at each temperature. CD studies revealed that mAb1 exhibited polyproline II helical structure at low temperatures and at high GuHCl concentrations. the Gibbs-Helmholtz expression fit to the ΔG_u versus temperature data from fluorescence gave a ΔC_p of 8.0 kcal mol⁻¹ K⁻¹, a maximum apparent stability of 23.7 kcal mol⁻¹ at 18°C, and an apparent cold denaturation temperature (T_CD) of −23°C. ΔG_u values for another mAb (mAb2) with a similar framework exhibited less stability at low temperatures, suggesting a depressed protein stability curve and a higher relative T_CD. Direct experimental evidence of the susceptibility of mAb1 and mAb2 to undergo cold denaturation in the absence of denaturant was confirmed at pH 2.5. thus, mAbs have a potential to undergo cold denaturation at storage temperatures near −20°C (pH 6.3), and this potential needs to be evaluated independently for individual mAbs.Key words: monoclonal antibodies, thermodynamic stability, cold denaturation, free energy, fluorescence     

Emergence of DNA Polymerase ε Antimutators That Escape Error-Induced Extinction in Yeast

DNA polymerases (Pols) ε and δ perform the bulk of yeast leading- and lagging-strand DNA synthesis. Both Pols possess intrinsic proofreading exonucleases that edit errors during polymerization. Rare errors that elude proofreading are extended into duplex DNA and excised by the mismatch repair (MMR) system. Strains that lack Pol proofreading or MMR exhibit a 10- to 100-fold increase in spontaneous mutation rate (mutator phenotype), and inactivation of both Pol δ proofreading (pol3-01) and MMR is lethal due to replication error-induced extinction (EEX). It is unclear whether a similar synthetic lethal relationship exists between defects in Pol ε proofreading (pol2-4) and MMR. Using a plasmid-shuffling strategy in haploid Saccharomyces cerevisiae, we observed synthetic lethality of pol2-4 with alleles that completely abrogate MMR (msh2Δ, mlh1Δ, msh3Δ msh6Δ, or pms1Δ mlh3Δ) but not with partial MMR loss (msh3Δ, msh6Δ, pms1Δ, or mlh3Δ), indicating that high levels of unrepaired Pol ε errors drive extinction. However, variants that escape this error-induced extinction (eex mutants) frequently emerged. Five percent of pol2-4 msh2Δ eex mutants encoded second-site changes in Pol ε that reduced the pol2-4 mutator phenotype between 3- and 23-fold. The remaining eex alleles were extragenic to pol2-4. The locations of antimutator amino-acid changes in Pol ε and their effects on mutation spectra suggest multiple mechanisms of mutator suppression. Our data indicate that unrepaired leading- and lagging-strand polymerase errors drive extinction within a few cell divisions and suggest that there are polymerase-specific pathways of mutator suppression. The prevalence of suppressors extragenic to the Pol ε gene suggests that factors in addition to proofreading and MMR influence leading-strand DNA replication fidelity.     

Stimulation of Chromosomal Rearrangements by Ribonucleotides

We show by whole genome sequence analysis that loss of RNase H2 activity increases loss of heterozygosity (LOH) in Saccharomyces cerevisiae diploid strains harboring the pol2-M644G allele encoding a mutant version of DNA polymerase ε that increases ribonucleotide incorporation. This led us to analyze the effects of loss of RNase H2 on LOH and on nonallelic homologous recombination (NAHR) in mutant diploid strains with deletions of genes encoding RNase H2 subunits (rnh201Δ, rnh202Δ, and rnh203Δ), topoisomerase 1 (TOP1Δ), and/or carrying mutant alleles of DNA polymerases ε, α, and δ. We observed an ∼7-fold elevation of the LOH rate in RNase H2 mutants encoding wild-type DNA polymerases. Strains carrying the pol2-M644G allele displayed a 7-fold elevation in the LOH rate, and synergistic 23-fold elevation in combination with rnh201Δ. In comparison, strains carrying the pol2-M644L mutation that decreases ribonucleotide incorporation displayed lower LOH rates. The LOH rate was not elevated in strains carrying the pol1-L868M or pol3-L612M alleles that result in increased incorporation of ribonucleotides during DNA synthesis by polymerases α and δ, respectively. A similar trend was observed in an NAHR assay, albeit with smaller phenotypic differentials. The ribonucleotide-mediated increases in the LOH and NAHR rates were strongly dependent on TOP1. These data add to recent reports on the asymmetric mutagenicity of ribonucleotides caused by topoisomerase 1 processing of ribonucleotides incorporated during DNA replication.     

Echtvar: compressed variant representation for rapid annotation and filtering of SNPs and indels

Germline and somatic variants within an individual or cohort are interpreted with information from large cohorts. Annotation with this information becomes a computational bottleneck as population sets grow to terabytes of data. Here, we introduce echtvar, which efficiently encodes population variants and annotation fields into a compressed archive that can be used for rapid variant annotation and filtering. Most variants, represented by chromosome, position and alleles are encoded into 32-bits-half the size of previous encoding schemes and at least 4 times smaller than a naive encoding. The annotations, stored separately within the same archive, are also encoded and compressed. We show that echtvar is faster and uses less space than existing tools and that it can effectively reduce the number of candidate variants. We give examples on germ-line and somatic variants to document how echtvar can facilitate exploratory data analysis on genetic variants. Echtvar is available at https://github.com/brentp/echtvar under an MIT license.