Identification and characterization of a nonbiological small-molecular mimic of a Zika virus conformational neutralizing epitope.

Antigenic similarities between Zika virus (ZIKV) and other flaviviruses pose challenges to the development of virus-specific diagnostic tools and effective vaccines. Starting with a DNA-encoded one-bead-one-compound combinatorial library of 508,032 synthetic, non-natural oligomers, we selected and characterized small molecules that mimic ZIKV epitopes. High-throughput fluorescence-activated cell sorter-based bead screening was used to select molecules that bound IgG from ZIKV-immune but not from dengue-immune sera. Deep sequencing of the DNA from the "Zika-only" beads identified 40 candidate molecular structures. A lead candidate small molecule "CZV1-1" was selected that correctly identifies serum specimens from Zika-experienced patients with good sensitivity and specificity (85.3% and 98.4%, respectively). Binding competition studies of purified anti-CZV1-1 IgG against known ZIKV-specific monoclonal antibodies (mAbs) showed that CZV1-1 mimics a nonlinear, neutralizing conformational epitope in the domain III of the ZIKV envelope. Purified anti-CZV1-1 IgG neutralized infection of ZIKV in cell cultures with potencies comparable to highly specific ZIKV-neutralizing mAbs. This study demonstrates an innovative approach for identification of synthetic non-natural molecular mimics of conformational virus epitopes. Such molecular mimics may have value in the development of accurate diagnostic assays for Zika, as well as for other viruses.

Evolutionary deletions within the SARS-CoV-2 genome as signature trends for virus fitness and adaptation.

Coronaviruses are large RNA viruses that can infect and spread among humans and animals. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for coronavirus disease 2019, has evolved since its first detection in December 2019. Deletions are a common occurrence in SARS-CoV-2 evolution, particularly in specific genomic sites, and may be associated with the emergence of highly competent lineages. While deletions typically have a negative impact on viral fitness, some persist and become fixed in viral populations, indicating that they may confer advantageous benefits for the virus's adaptive evolution. This work presents a literature review and data analysis on structural losses in the SARS-CoV-2 genome and the potential relevance of specific signatures for enhanced viral fitness and spread.

Determination of prognostic markers for COVID-19 disease severity using routine blood tests and machine learning.

The need for the identification of risk factors associated to COVID-19 disease severity remains urgent. Patients' care and resource allocation can be potentially different and are defined based on the current classification of disease severity. This classification is based on the analysis of clinical parameters and routine blood tests, which are not standardized across the globe. Some laboratory test alterations have been associated to COVID-19 severity, although these data are conflicting partly due to the different methodologies used across different studies. This study aimed to construct and validate a disease severity prediction model using machine learning (ML). Seventy-two patients admitted to a Brazilian hospital and diagnosed with COVID-19 through RT-PCR and/or ELISA, and with varying degrees of disease severity, were included in the study. Their electronic medical records and the results from daily blood tests were used to develop a ML model to predict disease severity. Using the above data set, a combination of five laboratorial biomarkers was identified as accurate predictors of COVID-19 severe disease with a ROC-AUC of 0.80 ​±â€‹ 0.13. Those biomarkers included prothrombin activity, ferritin, serum iron, ATTP and monocytes. The application of the devised ML model may help rationalize clinical decision and care.

An artificial neural network model to predict structure-based protein-protein free energy of binding from Rosetta-calculated properties.

The prediction of the free energy (ΔG) of binding for protein-protein complexes is of general scientific interest as it has a variety of applications in the fields of molecular and chemical biology, materials science, and biotechnology. Despite its centrality in understanding protein association phenomena and protein engineering, the ΔG of binding is a daunting quantity to obtain theoretically. In this work, we devise a novel Artificial Neural Network (ANN) model to predict the ΔG of binding for a given three-dimensional structure of a protein-protein complex with Rosetta-calculated properties. Our model was tested using two data sets, and it presented a root-mean-square error ranging from 1.67 kcal mol-1 to 2.45 kcal mol-1, showing a better performance compared to the available state-of-the-art tools. Validation of the model for a variety of protein-protein complexes is showcased.

GM2/GM3 controls the organizational status of CD82/Met microdomains: further studies in GM2/GM3 complexation.

At cell surface gangliosides might associate with signal transducers proteins, grown factor receptors, integrins, small G-proteins and tetraspanins establishing microdomains, which play important role in cell adhesion, cell activation, motility, and growth. Previously, we reported that GM2 and GM3 form a heterodimer that interacts with the tetraspanin CD82, controlling epithelial cell mobility by inhibiting integrin-hepatocyte growth factor-induced cMet tyrosine kinase signaling. By using molecular dynamics simulations to study the molecular basis of GM2/GM3 interaction we demonstrate, here, that intracellular levels of Ca2+ mediate GM2/GM3 complexation via electrostatic interaction with their carboxyl groups, while hydrogen bonds between the ceramide groups likely aid stabilizing the complex. The presence of GM2/GM3 complex alters localization of CD82 on cell surface and therefore downstream signalization. These data contribute for the knowledge of how glycosylation may control signal transduction and phenotypic changes.

Differential Frequencies of HLA-DRB1, DQA1, and DQB1 Alleles and Haplotypes Are Observed in the Arbovirus-Related Neurological Syndromes.

BACKGROUND: We took advantage of the 2015-2016 Brazilian arbovirus outbreak (Zika [ZIKV]/dengue/chikungunya viruses) associated with neurological complications to type HLA-DRB1/DQA1/DQB1 variants in patients exhibiting neurological complications and in bone marrow donors from the same endemic geographical region. METHODS: DRB1/DQA1/DQB1 loci were typed using sequence-specific oligonucleotides. In silico studies were performed using X-ray resolved dimer constructions. RESULTS: The DQA1*01, DQA1*05, DQB1*02, or DQB1*06 genotypes/haplotypes and DQA1/DQB1 haplotypes that encode the putative DQA1/DQB1 dimers were overrepresented in the whole group of patients and in patients exhibiting peripheral neurological spectrum disorders (PSD) or encephalitis spectrum disorders (ESD). The DRB1*04, DRB1*13, and DQA1*03 allele groups protected against arbovirus neurological manifestation, being underrepresented in whole group of patients and ESD and PSD groups. Genetic and in silico studies revealed that DQA1/DQB1 dimers (1) were primarily associated with susceptibility to arbovirus infections; (2) can bind to a broad range of ZIKV peptides (235 of 1878 peptides, primarily prM and NS2A); and (3) exhibited hydrophilic and highly positively charged grooves when compared to the DRA1/DRB1 cleft. The protective dimer (DRA1/DRB1*04) bound a limited number of ZIKV peptides (40 of 1878 peptides, primarily prM). CONCLUSION: Protective haplotypes may recognize arbovirus peptides more specifically than susceptible haplotypes.

SuAVE: A Tool for Analyzing Curvature-Dependent Properties in Chemical Interfaces.

Curvature is an intrinsic feature of biological membranes underlying vital cellular processes such as endocytosis, membrane fusion-fission, trafficking, and remodeling. The continuous expansion of the spatiotemporal scales accessible to computational simulations nowadays makes possible quasi-atomistic molecular dynamics simulations of these processes. In despite of that, computation of the shapes and curvatures associated with the dynamics of biological membranes remains challenging. For this reason, the effect of curvature is often neglected in the analysis of quantities essential for the accurate description of membrane properties (e.g., area and volume per lipid, density profiles, membrane thickness). We propose an algorithm for surface assessment via grid evaluation (SuAVE) that relies on the application of a radial base function to interpolate points scattered across an interface of any shape. This enables the representation of the chemical interface as fully differentiable so that related geometrical properties can be calculated through the straightforward employment of well-established differential geometry techniques. Hence, the effect of different types or degrees of curvature can be accurately taken into account in the calculations of structural properties of any interfaces regardless of chemical composition, asymmetry, and level of atom coarseness. The main functionalities implemented in SuAVE are featured for a number of tetraacylated and hexaacylated Lipid-A membranes of distinct curvatures and a surfactant micelle. We show that the properties calculated for moderately to highly curved membranes differ significantly between curvature-dependent and -independent algorithms. The SuAVE software is freely available from www.biomatsite.net/suave-software .

Rotational Profiler: A Fast, Automated, and Interactive Server to Derive Torsional Dihedral Potentials for Classical Molecular Simulations.

Rotational Profiler provides an analytical algorithm to compute sets of classical torsional dihedral parameters by fitting an empirical energy profile to a reference one that can be obtained experimentally or by quantum-mechanical methods. The resulting profiles are compatible with the functional forms in the most widely used biomolecular force fields (e.g., GROMOS, AMBER, OPLS, and CHARMM). The linear least-squares regression method is used to generate sets of parameters that best satisfy the fitting. Rotational Profiler is free to use, analytical, and force field/package independent. The formalism is herein described, and its usage, in an interactive and automated manner, is made available as a Web server at http://rotprof.lncc.br.

Influence of directional positive Darwinian selection-driven evolution on arboviruses Dengue and Zika virulence and pathogenesis.

Dengue (DENV) and Zika (ZIKV) viruses are antigenically and evolutionarily related; immunological cross-reactions between them have been associated to both cross-protection and infection-enhanced mechanisms. Here, DENV-1-4 and ZIKV were investigated through Bayesian coalescent-based approaches and selection-driven Darwinian evolution methods using robust datasets. Our findings show that both DENV and ZIKV, driven essentially by directional positive selection, have undergone evolution and diversification and that their entire polyproteins are subject to an intense directional evolution. Interestingly, positively selected codons mapped here are directly associated to DENV-1-2 virulence as well as the ZIKV burgeoning 2015-16 outbreak in the Americas, therefore, having impact on the pathogenesis of these viruses. Biochemical prediction analysis focusing on markers involved in virulence and viral transmission dynamics identified alterations in N-Glycosylation-, Phosphorylation- and Palmitoylation-sites in ZIKV sampled from different countries, hosts and isolation sources. Taking into account both DENV-ZIKV co-circulation either into and/or out of flavivirus-endemic regions, as well as recombination and quasispecies scenarios, these results indicate the action of a selection-driven evolution affecting the biology, virulence and pathogenesis of these pathogens in a non-randomized environment.

Amino acid polymorphisms in the fibronectin-binding repeats of fibronectin-binding protein A affect bond strength and fibronectin conformation.

The Staphylococcus aureus cell surface contains cell wall-anchored proteins such as fibronectin-binding protein A (FnBPA) that bind to host ligands (e.g. fibronectin; Fn) present in the extracellular matrix of tissue or coatings on cardiac implants. Recent clinical studies have found a correlation between cardiovascular infections caused by S. aureus and nonsynonymous SNPs in FnBPA. Atomic force microscopy (AFM), surface plasmon resonance (SPR), and molecular simulations were used to investigate interactions between Fn and each of eight 20-mer peptide variants containing amino acids Ala, Asn, Gln, His, Ile, and Lys at positions equivalent to 782 and/or 786 in Fn-binding repeat-9 of FnBPA. Experimentally measured bond lifetimes (1/koff) and dissociation constants (Kd = koff/kon), determined by mechanically dissociating the Fn·peptide complex at loading rates relevant to the cardiovascular system, varied from the lowest-affinity H782A/K786A peptide (0.011 s, 747 µm) to the highest-affinity H782Q/K786N peptide (0.192 s, 15.7 µm). These atomic force microscopy results tracked remarkably well to metadynamics simulations in which peptide detachment was defined solely by the free-energy landscape. Simulations and SPR experiments suggested that an Fn conformational change may enhance the stability of the binding complex for peptides with K786I or H782Q/K786I (Kdapp = 0.2-0.5 µm, as determined by SPR) compared with the lowest-affinity double-alanine peptide (Kdapp = 3.8 µm). Together, these findings demonstrate that amino acid substitutions in Fn-binding repeat-9 can significantly affect bond strength and influence the conformation of Fn upon binding. They provide a mechanistic explanation for the observation of nonsynonymous SNPs in fnbA among clinical isolates of S. aureus that cause endovascular infections.

Conformational stability of the epidermal growth factor (EGF) receptor as influenced by glycosylation, dimerization and EGF hormone binding.

The epidermal growth factor receptor (EGFR) is an important transmembrane glycoprotein kinase involved the initiation or perpetuation of signal transduction cascades within cells. These processes occur after EGFR binds to a ligand [epidermal growth factor (EGF)], thus inducing its dimerization and tyrosine autophosphorylation. Previous publications have highlighted the importance of glycosylation and dimerization for promoting proper function of the receptor and conformation in membranes; however, the effects of these associations on the protein conformational stability have not yet been described. Molecular dynamics simulations were performed to characterize the conformational preferences of the monomeric and dimeric forms of the EGFR extracellular domain upon binding to EGF in the presence and absence of N-glycan moieties. Structural stability analyses revealed that EGF provides the most conformational stability to EGFR, followed by glycosylation and dimerization, respectively. The findings also support that EGF-EGFR binding takes place through a large-scale induced-fitting mechanism. Proteins 2017; 85:561-570. © 2016 Wiley Periodicals, Inc.

Polymyxin Binding to the Bacterial Outer Membrane Reveals Cation Displacement and Increasing Membrane Curvature in Susceptible but Not in Resistant Lipopolysaccharide Chemotypes.

Lipid-A is the causative agent of Gram-negative sepsis and is responsible for an increasingly high mortality rate among hospitalized patients. Compounds that bind Lipid-A can limit this inflammatory process. The cationic antimicrobial peptide polymyxin B (Pmx-B) is one of the simplest molecules capable of selectively binding to Lipid-A and may serve as a model for further development of Lipid-A binding agents. Gram-negative bacteria resistance to Pmx-B relies on the upregulation of a number of regulatory systems, which promote chemical modifications of the lipopolysaccharide (LPS) structure and leads to major changes in the physical-chemical properties of the outer membrane. A detailed understanding of how the chemical structure of the LPS modulates macroscopic properties of the outer membrane is paramount for the design and optimization of novel drugs targeting clinically relevant strains. We have performed a systematic investigation of Pmx-B binding to outer membrane models composed of distinct LPS chemotypes experimentally shown to be either resistant or susceptible to the peptide. Molecular dynamics simulations were carried out for Pmx-B bound to the penta- and hexa-acylated forms of Lipid-A (more susceptible) and Lipid-A modified with 4-amino-4-deoxy-l-arabinose (resistant) as well as the penta-acylated form of LPS Re (less susceptible). The present simulations show that upon binding to the bacterial outer membrane surface, Pmx-B promotes cation displacement and structural changes in membrane curvature and integrity as a function of the LPS chemotype susceptibility or resistance to the antimicrobial peptide.

Molecularly Smooth Self-Assembled Monolayer for High-Mobility Organic Field-Effect Transistors.

Despite the need for molecularly smooth self-assembled monolayers (SAMs) on silicon dioxide surfaces (the most common dielectric surface), current techniques are limited to nonideal silane grafting. Here, we show unique bioinspired zwitterionic molecules forming a molecularly smooth and uniformly thin SAM in "water" in <1 min on various dielectric surfaces, which enables a dip-coating process that is essential for organic electronics to become reality. This monomolecular layer leads to high mobility of organic field-effect transistors (OFETs) based on various organic semiconductors and source/drain electrodes. A combination of experimental and computational techniques confirms strong adsorption (Wad > 20 mJ m-2), uniform thickness (∼0.5 or ∼1 nm) and orientation (all catechol head groups facing the oxide surface) of the "monomolecular" layers. This robust (strong adsorption), rapid, and green SAM represents a promising advancement toward the next generation of nanofabrication compared to the current nonuniform and inconsistent polysiloxane-based SAM involving toxic chemicals, long processing time (>10 h), or heat (>80 °C).

Endovascular infections caused by methicillin-resistant Staphylococcus aureus are linked to clonal complex-specific alterations in binding and invasion domains of fibronectin-binding protein A as well as the occurrence of fnbB.

Endovascular infections caused by Staphylococcus aureus involve interactions with fibronectin present as extracellular matrix or surface ligand on host cells. We examined the expression, structure, and binding activity of the two major S. aureus fibronectin-binding proteins (FnBPA, FnBPB) in 10 distinct, methicillin-resistant clinical isolates from patients with either persistent or resolving bacteremia. The persistent bacteremia isolates (n = 5) formed significantly stronger bonds with immobilized fibronectin as determined by dynamic binding measurements performed with atomic force microscopy. Several notable differences were also observed when the results were grouped by clonal complex 5 (CC5) strains (n = 5) versus CC45 strains (n = 5). Fibronectin-binding receptors on CC5 formed stronger bonds with immobilized fibronectin (P < 0.001). The fnbA gene was expressed at higher levels in CC45, whereas fnbB was found in only CC5 isolates. The fnbB gene was not sequenced because all CC45 isolates lacked this gene. Instead, comparisons were made for fnbA, which was present in all 10 isolates. Sequencing of fnbA revealed discrete differences within high-affinity, fibronectin-binding repeats (FnBRs) of FnBPA that included (i) 5-amino-acid polymorphisms in FnBR-9, FnBR-10, and FnBR-11 involving charged or polar side chains, (ii) an extra, 38-amino-acid repeat inserted between FnBR-9 and FnBR-10 exclusively seen in CC45 isolates, and (iii) CC5 isolates had the SVDFEED epitope in FnBR-11 (a sequence shown to be essential for fibronectin binding), while this sequence was replaced in all CC45 isolates with GIDFVED (a motif known to favor host cell invasion at the cost of reduced fibronectin binding). These complementary sequence and binding data suggest that differences in fnbA and fnbB, particularly polymorphisms and duplications in FnBPA, give S. aureus two distinct advantages in human endovascular infections: (i) FnBPs similar to that of CC5 enhance ligand binding and foster initiation of disease, and (ii) CC45-like FnBPs promote cell invasion, a key attribute in persistent endovascular infections.

Assessing protein conformational sampling and structural stability via de novo design and molecular dynamics simulations.

Molecular dynamics and de novo techniques, associated to quality parameter sets, have excelled at determining the structure of small proteins with high accuracy. To achieve a detailed description of protein conformations, these methods must critically assess the thermodynamic features of the molecular ensembles. Here, a comparison of the conformational ensemble generated by molecular dynamics and de novo techniques were carried out for six Top7-based proteins carrying gp41 HIV-1 epitopes. The native Top7, a highly stable computationally designed protein, was used as benchmark. Structural stability, flexibility, and secondary structure content were assessed. The consistency of the latter was compared to experimental circular dichroism spectra for all proteins. While both methods are capable to identify the stable from unstable chimeric proteins, the sampled conformational space and flexibility differ significantly in both methods. Molecular dynamics simulations seem to better describe secondary structure content and identify regions responsible for conformational instability. The de novo method, as implemented in Rosetta-a prime tool for protein design, overestimates secondary structure content. On the other hand, its empirical energy function is capable to predict the threshold for protein stability.

Extension and validation of the GROMOS 53A6(GLYC) parameter set for glycoproteins.

An extension of the GROMOS 53A6GLYC force field for carbohydrates to encompass glycoprotein linkages is presented. The set includes new atomic charges and incorporates adequate torsional potential parameters for N-, S-, C-, P-, and O-glycosydic linkages, offering compatibility with the GROMOS force field family for proteins. Validation included the description of glycosydic linkage geometries between amino acid and monosaccharide residues, comparison of NMR-derived protein-carbohydrate and carbohydrate-carbohydrate nuclear overhauser effect (NOE) signals for glycoproteins and the effects of glycosylation on protein flexibility and dynamics.

Polymorphisms in fibronectin binding protein A of Staphylococcus aureus are associated with infection of cardiovascular devices.

Medical implants, like cardiovascular devices, improve the quality of life for countless individuals but may become infected with bacteria like Staphylococcus aureus. Such infections take the form of a biofilm, a structured community of bacterial cells adherent to the surface of a solid substrate. Every biofilm begins with an attractive force or bond between bacterium and substratum. We used atomic force microscopy to probe experimentally forces between a fibronectin-coated surface (i.e., proxy for an implanted cardiac device) and fibronectin-binding receptors on the surface of individual living bacteria from each of 80 clinical isolates of S. aureus. These isolates originated from humans with infected cardiac devices (CDI; n = 26), uninfected cardiac devices (n = 20), and the anterior nares of asymptomatic subjects (n = 34). CDI isolates exhibited a distinct binding-force signature and had specific single amino acid polymorphisms in fibronectin-binding protein A corresponding to E652D, H782Q, and K786N. In silico molecular dynamics simulations demonstrate that residues D652, Q782, and N786 in fibronectin-binding protein A form extra hydrogen bonds with fibronectin, complementing the higher binding force and energy measured by atomic force microscopy for the CDI isolates. This study is significant, because it links pathogenic bacteria biofilms from the length scale of bonds acting across a nanometer-scale space to the clinical presentation of disease at the human dimension.

Structure-based computational design of antibody mimetics: challenges and perspectives.

The design of antibody mimetics holds great promise for revolutionizing therapeutic interventions by offering alternatives to conventional antibody therapies. Structure-based computational approaches have emerged as indispensable tools in the rational design of those molecules, enabling the precise manipulation of their structural and functional properties. This review covers the main classes of designed antigen-binding motifs, as well as alternative strategies to develop tailored ones. We discuss the intricacies of different computational protein-protein interaction design strategies, showcased by selected successful cases in the literature. Subsequently, we explore the latest advancements in the computational techniques including the integration of machine and deep learning methodologies into the design framework, which has led to an augmented design pipeline. Finally, we verse onto the current challenges that stand in the way between high-throughput computer design of antibody mimetics and experimental realization, offering a forward-looking perspective into the field and the promises it holds to biotechnology.

IMSPeptider: A computational peptide collision cross-section area calculator based on a novel molecular dynamics simulation protocol.

Introduction of ion mobility mass spectrometry (IMS/MS) into the proteomic workflow provides an orthogonal separation to the widely used LC-MS platforms. IMS also provides structural information that could facilitate peptide identification. However, the lack of tools capable of predictive power in a high-throughput fashion makes peptide global profiling quite challenging. To target this issue, a computational workflow was developed based on biophysical principles to predict the collision cross-section area (CCS) of peptides as measured from IMS/MS experiments. Hosted on a web server, it allows the user to input a primary sequence (query) and retrieve information on peptide structure, sequence, and corresponding CCS. The current version is designed to identify peptide sequences up to 23 residues in length, in its higher charge state, based on a match of the molecule m/z and CCS. The protocol was validated against a 128-sequences-dataset and CCS predicted within 2.8% average error.

Inhibition of 3-Hydroxykynurenine Transaminase from Aedes aegypti and Anopheles gambiae: A Mosquito-Specific Target to Combat the Transmission of Arboviruses.

Arboviral infections such as Zika, chikungunya, dengue, and yellow fever pose significant health problems globally. The population at risk is expanding with the geographical distribution of the main transmission vector of these viruses, the Aedes aegypti mosquito. The global spreading of this mosquito is driven by human migration, urbanization, climate change, and the ecological plasticity of the species. Currently, there are no specific treatments for Aedes-borne infections. One strategy to combat different mosquito-borne arboviruses is to design molecules that can specifically inhibit a critical host protein. We obtained the crystal structure of 3-hydroxykynurenine transaminase (AeHKT) from A. aegypti, an essential detoxification enzyme of the tryptophan metabolism pathway. Since AeHKT is found exclusively in mosquitoes, it provides the ideal molecular target for the development of inhibitors. Therefore, we determined and compared the free binding energy of the inhibitors 4-(2-aminophenyl)-4-oxobutyric acid (4OB) and sodium 4-(3-phenyl-1,2,4-oxadiazol-5-yl)butanoate (OXA) to AeHKT and AgHKT from Anopheles gambiae, the only crystal structure of this enzyme previously known. The cocrystallized inhibitor 4OB binds to AgHKT with K i of 300 µM. We showed that OXA binds to both AeHKT and AgHKT enzymes with binding energies 2-fold more favorable than the crystallographic inhibitor 4OB and displayed a 2-fold greater residence time τ upon binding to AeHKT than 4OB. These findings indicate that the 1,2,4-oxadiazole derivatives are inhibitors of the HKT enzyme not only from A. aegypti but also from A. gambiae.