Helical Content Correlations and Hydration Structures of the Folding Ensemble of the B Domain of Protein A.

The B domain of protein A (BdpA), a small three-helix bundle, folds on a time scale of a few microseconds with heterogeneous native and unfolded states. It is widely used as a model for understanding protein folding mechanisms. In this work, we use structure-based models (SBMs) and atomistic simulations to comprehensively investigate how BdpA folding is associated with the formation of its secondary structure. The energy landscape visualization method (ELViM) was used to characterize the pathways that connect the folded and unfolded states of BdpA as well as the sets of structures displaying specific ellipticity patterns. We show that the native state conformational diversity is due mainly to the conformational variability of helix I. Helices I, II, and III occur in a weakly correlated manner, with Spearman's rank correlation coefficients of 0.1539 (I and II), 0.1259 (I and III), and 0.2561 (II and III). These results, therefore, suggest the highest cooperativity between helices II and III. Our results allow the clustering of partially folded structures of folding of the B domain of protein A on the basis of its secondary structure, paving the way to an understanding of environmental factors in the relative stability of the basins of the folding ensemble, which are illustrated by the structural dependency of the protein hydration structures, as computed with minimum-distance distribution functions.

Structural discrimination analysis for constraint selection in protein modeling.

MOTIVATION: Protein structure modeling can be improved by the use of distance constraints between amino acid residues, provided such data reflects-at least partially-the native tertiary structure of the target system. In fact, only a small subset of the native contact map is necessary to successfully drive the model conformational search, so one important goal is to obtain the set of constraints with the highest true-positive rate, lowest redundancy and greatest amount of information. In this work, we introduce a constraint evaluation and selection method based on the point-biserial correlation coefficient, which utilizes structural information from an ensemble of models to indirectly measure the power of each constraint in biasing the conformational search toward consensus structures. RESULTS: Residue contact maps obtained by direct coupling analysis are systematically improved by means of discriminant analysis, reaching in some cases accuracies often seen only in modern deep-learning-based approaches. When combined with an iterative modeling workflow, the proposed constraint classification optimizes the selection of the constraint set and maximizes the probability of obtaining successful models. The use of discriminant analysis for the valorization of the information of constraint datasets is a general concept with possible applications to other constraint types and modeling problems. AVAILABILITY AND IMPLEMENTATION: MSA for the targets in this work is available on https://github.com/m3g/2021_Bottino_Biserial. Modeling data supporting the findings of this study was generated at the Center for Computing in Engineering and Sciences, and is available from the corresponding author LM on request. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Evaluation of sustainable susceptibility to Plasmodium vivax infection among colonized Anopheles darlingi and Anopheles deaneorum.

BACKGROUND: The colonization of mosquitoes susceptible to Plasmodium vivax via direct membrane feeding assay (DMFA) has the potential to significantly advance our knowledge of P. vivax biology, vector-parasite interaction and transmission-blocking vaccine research. Anopheles darlingi and Anopheles deaneorum are important vectors of malaria in the Western Brazilian Amazon. Since 2018, well-established colonies of these species have been maintained in order to mass produce mosquitoes destined for P. vivax infection. Plasmodium susceptibility was confirmed when the colonies were established, but susceptibility needs to be maintained for these colonies to remain good models for pathogen transmission. Thus, the susceptibility was assessed of colonized mosquitoes to P. vivax isolates circulating in the Western Amazon. METHODS: Laboratory-reared mosquitoes from F10-F25 generations were fed on P. vivax blood isolates via DMFA. Susceptibility was determined by prevalence and intensity of infection as represented by oocyst load seven days after blood feeding, and sporozoite load 14 days after blood feeding. The effect of infection on mosquito survival was evaluated from initial blood feeding until sporogonic development and survival rates were compared between mosquitoes fed on infected and uninfected blood. Correlation was calculated between gametocytaemia and prevalence/intensity of infection, and between oocyst and sporozoite load. RESULTS: Significant differences were found in prevalence and intensity of infection between species. Anopheles darlingi showed a higher proportion of infected mosquitoes and higher oocyst and sporozoite intensity than An. deaneorum. Survival analysis showed that An. deaneorum survival decreased drastically until 14 days post infection (dpi). Plasmodium vivax infection decreased survival in both species relative to uninfected mosquitoes. No correlation was observed between gametocytaemia and prevalence/intensity of infection, but oocyst and sporozoite load had a moderate to strong correlation. CONCLUSIONS: Colonized An. darlingi make excellent subjects for modelling pathogen transmission. On the other hand, An. deaneorum could serve as a model for immunity studies due the low susceptibility under current colonized conditions. In the application of DMFA, gametocyte density is not a reliable parameter for predicting mosquito infection by P. vivax, but oocyst intensity should be used to schedule sporozoite experiments.

Wrapping Up Viruses at Multiscale Resolution: Optimizing PACKMOL and SIRAH Execution for Simulating the Zika Virus.

Simulating huge biomolecular complexes of million atoms at relevant biological time scales is becoming accessible to the broad scientific community. That proves to be crucial for urgent responses against emergent diseases in real time. Yet, there are still issues to sort regarding the system setup so that molecular dynamics (MD) simulations can be run in a simple and standard way. Here, we introduce an optimized pipeline for building and simulating enveloped virus-like particles (VLP). First, the membrane packing problem is tackled with new features and optimized options in PACKMOL. This allows preparing accurate membrane models of thousands of lipids in the context of a VLP within a few hours using a single CPU. Then, the assembly of the VLP system is done within the multiscale framework of the coarse-grained SIRAH force field. Finally, the equilibration protocol provides a system ready for production MD simulations within a few days on broadly accessible GPU resources. The pipeline is applied to study the Zika virus as a test case for large biomolecular systems. The VLP stabilizes at approximately 0.5 µs of MD simulation, reproducing correlations greater than 0.90 against experimental density maps from cryo-electron microscopy. Detailed structural analysis of the protein envelope also shows very good agreement in root-mean-square deviations and B-factors with the experimental data. The level of details attained shows for the first time a possible role for anionic phospholipids in stabilizing the envelope. Combining an efficient and reliable setup procedure with an accurate coarse-grained force field provides a valuable pipeline for simulating arbitrary viral systems or subcellular compartments, paving the way toward whole-cell simulations.

Single-cell transcriptomic analysis identifies extensive heterogeneity in the cellular composition of mouse Achilles tendons.

Tendon is a dense connective tissue that stores and transmits forces between muscles and bones. Cellular heterogeneity is increasingly recognized as an important factor in the biological basis of tissue homeostasis and disease, yet little is known about the diversity of cell types that populate tendon. To address this, we determined the heterogeneity of cell populations within mouse Achilles tendons using single-cell RNA sequencing. In assembling a transcriptomic atlas of Achilles tendons, we identified 11 distinct types of cells, including three previously undescribed populations of tendon fibroblasts. Prior studies have indicated that pericytes, which are found in the vasculature of tendons, could serve as a potential source of progenitor cells for adult tendon fibroblasts. Using trajectory inference analysis, we provide additional support for the notion that pericytes are likely to be at least one of the progenitor cell populations for the fibroblasts that compose adult tendons. We also modeled cell-cell interactions and identified previously undescribed ligand-receptor signaling interactions involved in tendon homeostasis. Our novel and interactive tendon atlas highlights previously underappreciated heterogeneity between and within tendon cell populations. The atlas also serves as a resource to further the understanding of tendon extracellular matrix assembly and maintenance and in the design of therapies for tendinopathies.

Structural complementarity of distance constraints obtained from chemical cross-linking and amino acid coevolution.

The analysis of amino acid coevolution has emerged as a practical method for protein structural modeling by providing structural contact information from alignments of amino acid sequences. In parallel, chemical cross-linking/mass spectrometry (XLMS) has gained attention as a universally applicable method for obtaining low-resolution distance constraints to model the quaternary arrangements of proteins, and more recently even protein tertiary structures. Here, we show that the structural information obtained by XLMS and coevolutionary analysis are effectively complementary: the distance constraints obtained by each method are almost exclusively associated with non-coincident pairs of residues, and modeling results obtained by the combination of both sets are improved relative to considering the same total number of constraints of a single type. The structural rationale behind the complementarity of the distance constraints is discussed and illustrated for a representative set of proteins with different sizes and folds.

Statistical force-field for structural modeling using chemical cross-linking/mass spectrometry distance constraints.

MOTIVATION: Chemical cross-linking/mass spectrometry (XLMS) is an experimental method to obtain distance constraints between amino acid residues which can be applied to structural modeling of tertiary and quaternary biomolecular structures. These constraints provide, in principle, only upper limits to the distance between amino acid residues along the surface of the biomolecule. In practice, attempts to use of XLMS constraints for tertiary protein structure determination have not been widely successful. This indicates the need of specifically designed strategies for the representation of these constraints within modeling algorithms. RESULTS: A force-field designed to represent XLMS-derived constraints is proposed. The potential energy functions are obtained by computing, in the database of known protein structures, the probability of satisfaction of a topological cross-linking distance as a function of the Euclidean distance between amino acid residues. First, the strategy suggests that XL constraints should be set to shorter distances than usually assumed. Second, the complete statistical force-field improves the models obtained and can be easily incorporated into current modeling methods and software. The force-field was implemented and is distributed to be used within the Rosetta ab initio relax protocol. AVAILABILITY AND IMPLEMENTATION: Force-field parameters and usage instructions are freely available online (http://m3g.iqm.unicamp.br/topolink/xlff). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

TopoLink: evaluation of structural models using chemical crosslinking distance constraints.

SUMMARY: A software was developed to evaluate structural models using chemical crosslinking experiments. The user provides the types of linkers used and their reactivity, and the observed crosslinks and dead-ends. The software computes the minimum length of a physically inspired linker that connects the reactive atoms of interest, and reports the consistency of each distance with the experimental observation. Statistics on model consistency with the links are provided. Tools to evaluate the correlation of crosslinks in ensembles of models were developed. TopoLink was used to evaluate the potential crosslinks of all structures of the CATH database. The number of crosslinks expected as a function of protein size and linker length can be used as guide for experimental design. AVAILABILITY AND IMPLEMENTATION: TopoLink is available as free software at http://m3g.iqm.unicamp.br/topolink, and distributed as source code with a user-friendly graphical interface for Windows. A web server is also provided. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Evidence for an extinct lineage of angiosperms from the Early Cretaceous of Patagonia and implications for the early radiation of flowering plants.

The pinnately lobed Aptian leaf fossil Mesodescolea plicata was originally described as a cycad, but new evidence from cuticle structure suggests that it is an angiosperm. Here we document the morphology and cuticle anatomy of Mesodescolea and explore its significance for early angiosperm evolution. We observed macrofossils and cuticles of Mesodescolea with light, scanning electron and transmission electron microscopy, and used phylogenetic methods to test its relationships among extant angiosperms. Mesodescolea has chloranthoid teeth and tertiary veins forming elongate areoles. Its cuticular morphology and ultrastructure reject cycadalean affinities, whereas its guard cell shape and stomatal ledges are angiospermous. It shares variable stomatal complexes and epidermal oil cells with angiosperm leaves from the lower Potomac Group. Phylogenetic analyses and hypothesis testing support its placement within the basal ANITA grade, most likely in Austrobaileyales, but it diverges markedly in leaf form and venation. Although many Early Cretaceous angiosperms fall within the morphological range of extant taxa, Mesodescolea reveals unexpected early morphological and ecophysiological trends. Its similarity to other Early Cretaceous lobate leaves, many identified previously as eudicots but in some cases pre-dating the appearance of tricolpate pollen, may indicate that Mesodescolea is part of a larger extinct lineage of angiosperms.

On the Interpretation of subtilisin Carlsberg Time-Resolved Fluorescence Anisotropy Decays: Modeling with Classical Simulations.

In this work, we discuss the challenging time-resolved fluorescence anisotropy of subtilisin Carlsberg (SC), which contains a single Trp residue and is a model fluorescence system. Experimental decay rates and quenching data suggest that the fluorophore should be exposed to water, but the Trp is partially buried in a hydrophobic pocket in the crystallographic structure. In order to study this inconsistency, molecular dynamics simulations were performed to predict the anisotropy decay rates and emission wavelengths of the Trp. We confirmed the inconsistency of the crystallographic structure with the experimentally observed fluorescence data and performed free energy calculations to show that the buried Trp conformation is 2 orders of magnitude (∼3 kcal/mol) more stable than the solvent-exposed one. However, molecular dynamics simulations in which the Trp side chain was restricted to solvent-exposed conformations displayed a maximum Trp emission wavelength shifted toward lower energies and decay rates compatible with the experimentally probed rates. Therefore, if the solvent-exposed conformations are the most important emitters, the experimental anisotropy can be compatibilized with the crystallographic structure. The most likely explanation is that the fluorescence of the most probable conformation in solution, observed in the crystal, is quenched, and this is consistent with the low quantum yield of Trp113 of SC. Additionally, some experiments might have probed denatured or lysed SC structures. SC anisotropy provides an interesting target for the study of fluorescence anisotropy using simulations, which can be used to test and exemplify how modeling can aid the interpretation of experimental data in a system where structure and solution experiments appear to be inconsistent.

Correction to: In silico evaluation and in vitro growth inhibition of Plasmodium falciparum by natural amides and synthetic analogs.

The original version of the article above contained an error in the text.

In silico evaluation and in vitro growth inhibition of Plasmodium falciparum by natural amides and synthetic analogs.

Malaria, caused by protozoa of the genus Plasmodium, is a disease that infects hundreds of millions of people annually, causing an enormous social burden in many developing countries. Since current antimalarial drugs are starting to face resistance by the parasite, the development of new therapeutic options has been prompted. The enzyme Plasmodium falciparum enoyl-ACP reductase (PfENR) has a determinant role in the fatty acid biosynthesis of this parasite and is absent in humans, making it an ideal target for new antimalarial drugs. In this sense, the present study aimed at evaluating the in silico binding affinity of natural and synthetic amides through molecular docking, in addition to their in vitro activity against P. falciparum by means of the SYBR Green Fluorescence Assay. The in vitro results revealed that the natural amide piplartine (1a) presented partial antiplasmodial activity (20.54 µM), whereas its synthetic derivatives (1m-IC50 104.45 µM), (1b, 1g, 1k, and 14f) and the natural amide piperine (18a) were shown to be inactive (IC50 > 200 µM). The in silico physicochemical analyses demonstrated that compounds 1m and 14f violated the Lipinski's rule of five. The in silico analyses showed that 14f presented the best binding affinity (- 13.047 kcal/mol) to PfENR and was also superior to the reference inhibitor triclosan (- 7.806 kcal/mol). In conclusion, we found that the structural modifications in 1a caused a significant decrease in antiplasmodial activity. Therefore, new modifications are encouraged in order to improve the activity observed.

Elucidating the Structural Basis of the Intracellular pH Sensing Mechanism of TASK-2 K2P Channels.

Two-pore domain potassium (K2P) channels maintain the cell's background conductance by stabilizing the resting membrane potential. They assemble as dimers possessing four transmembrane helices in each subunit. K2P channels were crystallized in "up" and "down" states. The movements of the pore-lining transmembrane TM4 helix produce the aperture or closure of side fenestrations that connect the lipid membrane with the central cavity. When the TM4 helix is in the up-state, the fenestrations are closed, while they are open in the down-state. It is thought that the fenestration states are related to the activity of K2P channels and the opening of the channels preferentially occurs from the up-state. TASK-2, a member of the TALK subfamily of K2P channels, is opened by intracellular alkalization leading the deprotonation of the K245 residue at the end of the TM4 helix. This charge neutralization of K245 could be sensitive or coupled to the fenestration state. Here, we describe the relationship between the states of the intramembrane fenestrations and K245 residue in TASK-2 channel. By using molecular modeling and simulations, we show that the protonated state of K245 (K245+) favors the open fenestration state and, symmetrically, that the open fenestration state favors the protonated state of the lysine residue. We show that the channel can be completely blocked by Prozac, which is known to induce fenestration opening in TREK-2. K245 protonation and fenestration aperture have an additive effect on the conductance of the channel. The opening of the fenestrations with K245+ increases the entrance of lipids into the selectivity filter, blocking the channel. At the same time, the protonation of K245 introduces electrostatic potential energy barriers to ion entrance. We computed the free energy profiles of ion penetration into the channel in different fenestration and K245 protonation states, to show that the effects of the two transformations are summed up, leading to maximum channel blocking. Estimated rates of ion transport are in qualitative agreement with experimental results and support the hypothesis that the most important barrier for ion transport under K245+ and open fenestration conditions is the entrance of the ions into the channel.

Prediction of kinetics of protein folding with non-redundant contact information.

Motivation: The majority of the inter-residue distances in a protein structure are correlated given a fixed topology. Here, we investigate whether we are able to predict a structure's folding rate, which is known to depend on the complexity of its fold, while considering only a small, uncorrelated fraction of its contacts. Results: We define an expression for the probabilistic information content associated to the relative position of a pair of amino acid residues in a protein structure. By means of fitting the protein chain to a self-avoiding random walk model, we derive a probability distribution for the distance between residues as a function of their separation along the sequence. We then show that the average information content for all residue pairs in a structure, considered as an estimate of its fold's complexity, is well correlated to the logarithm of its folding rate. Moreover, the same information content measure may be exploited to rank contacts and identify redundancies, allowing the prediction the structure's folding rate with similar accuracy while taking into account less than 5% of its contacts. Availability and implementation: An implementation of the described model and the experimental data are available at http://github.com/luciano-censoni/sarw-lnkf.

Enhancing protein fold determination by exploring the complementary information of chemical cross-linking and coevolutionary signals.

Motivation: Elucidation of protein native states from amino acid sequences is a primary computational challenge. Modern computational and experimental methodologies, such as molecular coevolution and chemical cross-linking mass-spectrometry allowed protein structural characterization to previously intangible systems. Despite several independent successful examples, data from these distinct methodologies have not been systematically studied in conjunction. One challenge of structural inference using coevolution is that it is limited to sequence fragments within a conserved and unique domain for which sufficient sequence datasets are available. Therefore, coupling coevolutionary data with complimentary distance constraints from orthogonal sources can provide additional precision to structure prediction methodologies. Results: In this work, we present a methodology to combine residue interaction data obtained from coevolutionary information and cross-linking/mass spectrometry distance constraints in order to identify functional states of proteins. Using a combination of structure-based models (SBMs) with optimized Gaussian-like potentials, secondary structure estimation and simulated annealing molecular dynamics, we provide an automated methodology to integrate constraint data from diverse sources in order to elucidate the native conformation of full protein systems with distinct complexity and structural topologies. We show that cross-linking mass spectrometry constraints improve the structure predictions obtained from SBMs and coevolution signals, and that the constraints obtained by each method have a useful degree of complementarity that promotes enhanced fold estimates. Availability and implementation: Scripts and procedures to implement the methodology presented herein are available at https://github.com/mcubeg/DCAXL. Supplementary information: Supplementary data are available at Bioinformatics online.

Prognostic significance of α- and ß2-adrenoceptor gene expression in breast cancer patients.

AIMS: Breast cancer is the most frequently diagnosed and leading cause of cancer death among women worldwide. It was classified within molecular intrinsic subtypes: luminal A, luminal B, human epidermal growth factor receptor 2-enriched and basal-like. Epinephrine and norepinephrine, released during stress, bind to adrenoceptors. α2 -adrenoceptors are encoded by the ADRA2A, ADRA2B and ADRA2C genes and ß2 by ADRB2. METHODS: We compiled several publicly available Affymetrix gene expression datasets, obtaining a large cohort of 1924 patients with distant metastasis-free survival (DMFS) data and evaluated the association between adrenoceptor expression, clinicopathological markers and outcome. RESULTS: ADRA2A high expressing tumours also expressed hormone receptors and presented diminished tumour size, grade and not compromised lymph nodes. ADRB2 high expression was found in smaller, low grade, oestrogen receptor-positive tumours. Both were significantly associated with the absence of metastasis. High expression of ADRA2C was positively associated with increased tumour size and metastatic relapse. We observed a significant increase in DMFS of patients with high ADRA2A (hazard ratio 0.54, 95% CI 0.45-0.65, P < .001) and ADRB2 (0.77, 0.64-0.93, P = .006) expression and a decrease with ADRA2C high expression (1.45, 1.16-1.81, P = .001). For patients with luminal tumours, ADRA2A was the only factor that retained its significance as an independent predictor of DMFS while ADRA2C expression was an independent predictor for worse prognosis in basal-like tumours. CONCLUSIONS: We herein provide new insight for a potential role of ADRA2A and ADRA2C in breast cancer. In low- and medium-income countries, their incorporation to routine immunohistochemistry analysis of biopsies or tumour samples, could provide additional low-cost prognostic factors.

The shift in urea orientation at protein surfaces at low pH is compatible with a direct mechanism of protein denaturation.

Surface-specific spectroscopic data has shown that urea undergoes a shift in orientation at protein surfaces in acidic media. Since urea denatures proteins at a wide range of pHs, the variable chemical nature of protein-urea interactions has been used to support an indirect mechanism of urea-induced denaturation. Here, we use molecular dynamics simulations, minimum-distance distribution functions (MDDFs), and hydrogen-bond analysis, to characterize the interactions of urea with proteins at neutral and low pH, as defined by the protonation state of acidic residues. We obtain the expected preferential solvation by urea and dehydration, consistently with urea-induced denaturation, while the MDDFs allow for a solvent-shell perspective of protein-urea interactions. The distribution functions are decomposed into atomic contributions to show that there is indeed a shift in the orientation of urea molecules in the vicinity of acidic side-chains, as shown by the experimental spectroscopic data. However, this effect is local, and the interactions of urea with the other side chains and with the protein backbone are essentially unaffected at low pH. Therefore, hydrophobic solvation and urea-backbone hydrogen bonds can play a role in a direct mechanism of urea-induced protein denaturation without contradicting the observed variations in the chemical nature of protein-urea interactions as a function of the acidity of the solution.

Parametric models to compute tryptophan fluorescence wavelengths from classical protein simulations.

Fluorescence spectroscopy is an important method to study protein conformational dynamics and solvation structures. Tryptophan (Trp) residues are the most important and practical intrinsic probes for protein fluorescence due to the variability of their fluorescence wavelengths: Trp residues emit in wavelengths ranging from 308 to 360 nm depending on the local molecular environment. Fluorescence involves electronic transitions, thus its computational modeling is a challenging task. We show that it is possible to predict the wavelength of emission of a Trp residue from classical molecular dynamics simulations by computing the solvent-accessible surface area or the electrostatic interaction between the indole group and the rest of the system. Linear parametric models are obtained to predict the maximum emission wavelengths with standard errors of the order 5 nm. In a set of 19 proteins with emission wavelengths ranging from 308 to 352 nm, the best model predicts the maximum wavelength of emission with a standard error of 4.89 nm and a quadratic Pearson correlation coefficient of 0.81. These models can be used for the interpretation of fluorescence spectra of proteins with multiple Trp residues, or for which local Trp environmental variability exists and can be probed by classical molecular dynamics simulations. © 2018 Wiley Periodicals, Inc.

A network model predicts the intensity of residue-protein thermal coupling.

MOTIVATION: The flow of vibrational energy in proteins has been shown not to obey expectations for isotropic media. The existence of preferential pathways for energy transport, with probable connections to allostery mechanisms, has been repeatedly demonstrated. Here, we investigate whether, by representing a set of protein structures as networks of interacting amino acid residues, we are able to model heat diffusion and predict residue-protein vibrational couplings, as measured by the Anisotropic Thermal Diffusion (ATD) computational protocol of modified molecular dynamics simulations. RESULTS: We revisit the structural rationales for the precise definition of a contact between amino acid residues. Using this definition to describe a set of proteins as contact networks where each node corresponds to a residue, we show that node centrality, particularly closeness centrality and eigenvector centrality , correlates to the strength of the vibrational coupling of each residue to the rest of the structure. We then construct an analytically solvable model of heat diffusion on a network, whose solution incorporates an explicit dependence on the connectivity of the heated node, as described by a perturbed graph Laplacian Matrix. AVAILABILITY AND IMPLEMENTATION: An implementation of the described model is available at http://leandro.iqm.unicamp.br/atd-scripts . CONTACT: leandro@iqm.unicamp.br.