Weak-cooperative binding of a long single-stranded DNA chain on a surface.

Binding gene-wide single-stranded nucleic acids to surface-immobilized complementary probes is an important but challenging process for biophysical studies and diagnostic applications. The challenge comes from the conformational dynamics of the long chain that affects its accessibility and weakens its hybridization to the probes. We investigated the binding of bacteriophage genome M13mp18 on several different 20-mer probes immobilized on the surface of a multi-spot, label-free biosensor, and observed that only a few of them display strong binding capability with dissociation constant as low as 10 pM. Comparing experimental data and computational analysis of the M13mp18 chain structural features, we found that the capturing performance of a specific probe is directly related to the multiplicity of binding sites on the genomic strand, and poorly connected with the predicted secondary and tertiary structure. We show that a model of weak cooperativity of transient bonds is compatible with the measured binding kinetics and accounts for the enhancement of probe capturing observed when more than 20 partial pairings with binding free energy lower than -10 kcal mol-1 are present. This mechanism provides a specific pattern of response of a genomic strand on a panel of properly selected oligomer probe sequences.

Predicting inhibitor development using a random peptide phage-display library approach in the SIPPET cohort.

ABSTRACT: Inhibitor development is the most severe complication of hemophilia A (HA) care and is associated with increased morbidity and mortality. This study aimed to use a novel immunoglobulin G epitope mapping method to explore the factor VIII (FVIII)-specific epitope profile in the SIPPET cohort population and to develop an epitope mapping-based inhibitor prediction model. The population consisted of 122 previously untreated patients with severe HA who were followed up for 50 days of exposure to FVIII or 3 years, whichever occurred first. Sampling was performed before FVIII treatment and at the end of the follow-up. The outcome was inhibitor development. The FVIII epitope repertoire was assessed by means of a novel random peptide phage-display assay. A least absolute shrinkage and selection operator (LASSO) regression model and a random forest model were fitted on posttreatment sample data and validated in pretreatment sample data. The predictive performance of these models was assessed by the C-statistic and a calibration plot. We identified 27 775 peptides putatively directed against FVIII, which were used as input for the statistical models. The C-statistic of the LASSO and random forest models were good at 0.78 (95% confidence interval [CI], 0.69-0.86) and 0.80 (95% CI, 0.72-0.89). Model calibration of both models was moderately good. Two statistical models, developed on data from a novel random peptide phage display assay, were used to predict inhibitor development before exposure to exogenous FVIII. These models can be used to set up diagnostic tests that predict the risk of inhibitor development before starting treatment with FVIII.

YY1 mutations disrupt corticogenesis through a cell-type specific rewiring of cell-autonomous and non-cell-autonomous transcriptional programs.

Germline mutations of YY1 cause Gabriele-de Vries syndrome (GADEVS), a neurodevelopmental disorder featuring intellectual disability and a wide range of systemic manifestations. To dissect the cellular and molecular mechanisms underlying GADEVS, we combined large-scale imaging, single-cell multiomics and gene regulatory network reconstruction in 2D and 3D patient-derived physiopathologically relevant cell lineages. YY1 haploinsufficiency causes a pervasive alteration of cell type specific transcriptional networks, disrupting corticogenesis at the level of neural progenitors and terminally differentiated neurons, including cytoarchitectural defects reminiscent of GADEVS clinical features. Transcriptional alterations in neurons propagated to neighboring astrocytes through a major non-cell autonomous pro-inflammatory effect that grounds the rationale for modulatory interventions. Together, neurodevelopmental trajectories, synaptic formation and neuronal-astrocyte cross talk emerged as salient domains of YY1 dosage-dependent vulnerability. Mechanistically, cell-type resolved reconstruction of gene regulatory networks uncovered the regulatory interplay between YY1, NEUROG2 and ETV5 and its aberrant rewiring in GADEVS. Our findings underscore the reach of advanced in vitro models in capturing developmental antecedents of clinical features and exposing their underlying mechanisms to guide the search for targeted interventions.

Type 2M/2A von Willebrand disease: a shared phenotype between type 2M and 2A.

ABSTRACT: Four variants have been continuously subjected to debate and received different von Willebrand disease (VWD) classifications: p.R1315L, p.R1315C, p.R1374H, and p.R1374C. We chose to comprehensively investigate these variants with full set of VWD tests, protein-modeling predictions and applying structural biology. Patients with p.R1315L, p.R1315C, p.R1374H, and p.R1374C were included. A group with type 2A and 2M was included to better understand similarities and differences. Patients were investigated for phenotypic assays and underlying disease mechanisms. We applied deep protein modeling predictions and structural biology to elucidate the causative effects of variants. Forty-three patients with these variants and 70 with 2A (n = 35) or 2M (n = 35) were studied. Patients with p.R1315L, p.R1374H, or p.R1374C showed a common phenotype between 2M and 2A using von Willebrand factor (VWF):GPIbR/VWF:Ag and VWF:CB/VWF:Ag ratios and VWF multimeric profile, whereas p.R1315C represented a type 2M phenotype. There was an overall reduced VWF synthesis or secretion in 2M and cases with p.R1315L, p.R1374H, and p.R1374C, but not in 2A. Reduced VWF survival was observed in most 2A (77%), 2M (80%), and all 40 cases with p.R1315L, p.R1374H, and p.R1374C. These were the only variants that fall at the interface between the A1-A2 domains. p.R1315L/C mutants induce more compactness and internal mobility, whereas p.R1374H/C display a more extended overall geometry. We propose a new classification of type 2M/2A for p.R1315L, p.R1374H, and p.R1374C because they share a common phenotype with 2M and 2A. Our structural analysis shows the unique location of these variants on the A1-A2 domains and their distinctive effect on VWF.

Recognition Mechanisms between a Nanobody and Disordered Epitopes of the Human Prion Protein: An Integrative Molecular Dynamics Study.

Immunotherapy using antibodies to target the aggregation of flexible proteins holds promise for therapeutic interventions in neurodegenerative diseases caused by protein misfolding. Prions or PrPSc, the causal agents of transmissible spongiform encephalopathies (TSE), represent a model target for immunotherapies as TSE are prototypical protein misfolding diseases. The X-ray crystal structure of the wild-type (WT) human prion protein (HuPrP) bound to a camelid antibody fragment, denoted as Nanobody 484 (Nb484), has been previously solved. Nb484 was found to inhibit prion aggregation in vitro through a unique mechanism of structural stabilization of two disordered epitopes, that is, the palindromic motif (residues 113-120) and the ß2-α2 loop region (residues 164-185). The study of the structural basis for antibody recognition of flexible proteins requires appropriate sampling techniques for the identification of conformational states occurring in disordered epitopes. To elucidate the Nb484-HuPrP recognition mechanisms, here we applied molecular dynamics (MD) simulations complemented with available NMR and X-ray crystallography data collected on the WT HuPrP to describe the conformational spaces occurring on HuPrP prior to Nb484 binding. We observe the experimentally determined binding competent conformations within the ensembles of pre-existing conformational states in solution before binding. We also described the Nb484 recognition mechanisms in two HuPrP carrying a polymorphism (E219K) and a TSE-causing mutation (V210I). Our hybrid approaches allow the identification of dynamic conformational landscapes existing on HuPrP and highly characterized by molecular disorder to identify physiologically relevant and druggable transitions.

An overview of structural approaches to study therapeutic RNAs.

RNAs provide considerable opportunities as therapeutic agent to expand the plethora of classical therapeutic targets, from extracellular and surface proteins to intracellular nucleic acids and its regulators, in a wide range of diseases. RNA versatility can be exploited to recognize cell types, perform cell therapy, and develop new vaccine classes. Therapeutic RNAs (aptamers, antisense nucleotides, siRNA, miRNA, mRNA and CRISPR-Cas9) can modulate or induce protein expression, inhibit molecular interactions, achieve genome editing as well as exon-skipping. A common RNA thread, which makes it very promising for therapeutic applications, is its structure, flexibility, and binding specificity. Moreover, RNA displays peculiar structural plasticity compared to proteins as well as to DNA. Here we summarize the recent advances and applications of therapeutic RNAs, and the experimental and computational methods to analyze their structure, by biophysical techniques (liquid-state NMR, scattering, reactivity, and computational simulations), with a focus on dynamic and flexibility aspects and to binding analysis. This will provide insights on the currently available RNA therapeutic applications and on the best techniques to evaluate its dynamics and reactivity.

Carbohydrate-carbohydrate interaction drives the preferential insertion of dirhamnolipid into glycosphingolipid enriched membranes.

Rhamnolipids (RLs) are among the most important biosurfactants produced by microorganisms, and have been widely investigated because of their multiple biological activities. Their action appears to depend on their structural interference with lipid membranes, therefore several studies have been performed to investigate this aspect. We studied by X-ray scattering, neutron reflectometry and molecular dynamic simulations the insertion of dirhamnolipid (diRL), the most abundant RL, in model cellular membranes made of phospholipids and glycosphingolipids. In our model systems the affinity of diRL to the membrane is highly promoted by the presence of the glycosphingolipids and molecular dynamics simulations unveil that this evidence is related to sugar-sugar attractive interactions at the membrane surface. Our results improve the understanding of the plethora of activities associated with RLs, also opening new perspectives in their selective use for pharmaceutical and cosmetics formulations. Additionally, they shed light on the still debated role of carbohydrate-carbohydrate interactions as driving force for molecular contacts at membrane surface.

Structural Basis for Chaperone-Independent Ubiquitination of Tau Protein by Its E3 Ligase CHIP.

The multi-site ubiquitination of Tau protein found in Alzheimer's disease filaments hints at the failed attempt of neurons to remove early toxic species. The ubiquitin-dependent degradation of Tau is regulated in vivo by the E3 ligase CHIP, a quality controller of the cell proteome dedicated to target misfolded proteins for degradation. In our study, by using site-resolved NMR, biochemical and computational methods, we elucidate the structural determinants underlying the molecular recognition between the ligase and its intrinsically disordered substrate. We reveal a multi-domain dynamic interaction that explains how CHIP can direct ubiquitination of Tau at multiple sites even in the absence of chaperones, including its typical partner Hsp70/Hsc70. Our findings thus provide mechanistic insight into the chaperone-independent engagement of a disordered protein by its E3 ligase.

Inducing pH control over the critical micelle concentration of zwitterionic surfactants via polyacids adsorption: Effect of chain length and structure.

HYPOTHESIS: The critical concentration above which micelles form from zwitterionic surfactant solutions and their thermodynamic stability is affected by the interaction with weak Brønsted polyacid chains (An) via the formation of charged hydrogen bonds between the latter and anionic moieties. EXPERIMENTS: The interaction between zwitterionic micelles and polyacids capable of forming hydrogen bonds, and its dependence on the environmental pH and polymer structure, has been studied with constant-pH simulations and a restricted primitive model for all electrolytes. FINDINGS: At low pH, the formation of polyacid/micelle complexes is witnessed independently of the polymer size or structure, so that the concentration above which micelles form is substantially decreased compared to polyacid-free cases. Upon rising pH, polymer desorption takes place within a narrow range of pH values, its location markedly depending on the size and structure of polyacids, and on the relative disposition between headgroup charged moieties. Thus, the desorption onset for long linear polyacids (A60) interacting with sulphobetainic headgroups is roughly two pH units higher than for six decameric chains (6A10) adsorbed onto micelles bearing phosphorylcholinic headgroups. This effect, together with the preferential desorption of chain ends at intermediate pH, may be exploited for drug delivery purposes or building advanced metamaterials.

A Simplified Amino Acidic Alphabet to Unveil the T-Cells Receptors Antigens: A Computational Perspective.

The exposure to pathogens triggers the activation of adaptive immune responses through antigens bound to surface receptors of antigen presenting cells (APCs). T cell receptors (TCR) are responsible for initiating the immune response through their physical direct interaction with antigen-bound receptors on the APCs surface. The study of T cell interactions with antigens is considered of crucial importance for the comprehension of the role of immune responses in cancer growth and for the subsequent design of immunomodulating anticancer drugs. RNA sequencing experiments performed on T cells represented a major breakthrough for this branch of experimental molecular biology. Apart from the gene expression levels, the hypervariable CDR3α/ß sequences of the TCR loops can now be easily determined and modelled in the three dimensions, being the portions of TCR mainly responsible for the interaction with APC receptors. The most direct experimental method for the investigation of antigens would be based on peptide libraries, but their huge combinatorial nature, size, cost, and the difficulty of experimental fine tuning makes this approach complicated time consuming, and costly. We have implemented in silico methodology with the aim of moving from CDR3α/ß sequences to a library of potentially antigenic peptides that can be used in immunologically oriented experiments to study T cells' reactivity. To reduce the size of the library, we have verified the reproducibility of experimental benchmarks using the permutation of only six residues that can be considered representative of all ensembles of 20 natural amino acids. Such a simplified alphabet is able to correctly find the poses and chemical nature of original antigens within a small subset of ligands of potential interest. The newly generated library would have the advantage of leading to potentially antigenic ligands that would contribute to a better understanding of the chemical nature of TCR-antigen interactions. This step is crucial in the design of immunomodulators targeted towards T-cells response as well as in understanding the first principles of an immune response in several diseases, from cancer to autoimmune disorders.

Monte Carlo study of the effects of macroion charge distribution on the ionization and adsorption of weak polyelectrolytes and concurrent counterion release.

HYPOTHESIS: Adsorption of weak polyelectrolytes onto charged nanoparticles, and concurrent effects such as spatial partitioning of ions may be influenced by details of the polyelectrolyte structure (linear or star-like) and size, by the mobility of the nanoparticle surface charge, or the valence of the nanoparticle counterions. EXPERIMENTS: Ionization and complexation of weak polyelectrolytes on spherical macroions with monovalent and divalent countrions has been studied with constant-pH Monte Carlo titrations and primitive electrolyte models for linear and star-like polymers capable, also, of forming charged hydrogen bonds. Nanoparticles surface charge has been represented either as a single colloid-centered total charge (CCTC) or as surface-tethered mobile monovalent spherical charges (SMMSC). FINDINGS: Differences in the average number of adsorbed polyelectrolyte arms and their average charge, and in the relative amount of macroion counterions (m-CI's) released upon polymer adsorption are found between CCTC and SMMSC nanoparticles. The amount of the counterions released also depends on the polymer structure. As CCTC adsorbs a lower number of star-like species arms, the degree of condensation of polymer counterions (p-CI's) onto the polyelectrolyte is also substantially higher for the CCTC colloid, with a concurrent decrease of the osmotic coefficient values.

Copper reduction and dioxygen activation in Cu-amyloid beta peptide complexes: insight from molecular modelling.

Alzheimer's disease (AD) involves a number of factors including an anomalous interaction of copper with the amyloid peptide (Aß), inducing oxidative stress with radical oxygen species (ROS) production through a three-step cycle in which O2 is gradually reduced to superoxide, oxygen peroxide and finally OH radicals. The purpose of this work has been to investigate the reactivity of 14 different Cu(ii)-Aß coordination models with the aim of identifying on an energy basis (Density Functional Theory (DFT) and classical Molecular Dynamics (MD)) the redox competent form(s). Accordingly, we have specifically focused on the first three steps of the cycle, i.e. ascorbate binding to Cu(ii), Cu(ii) → Cu(i) reduction and O2 reduction to O2-. Compared to the recent literature, our results broaden the set of possible redox competent metallopeptide forms responsible for ROS production. Indeed, in addition to the three-coordinated species containing one His ligand, a N-terminal amine group and the carboxylate side chain of the Asp1 residue of Aß already proposed, we found two other Cu-Aß coordination modes involving two histidines.

Binding Residence Time through Scaled Molecular Dynamics: A Prospective Application to hDAAO Inhibitors.

Traditionally, a drug potency is expressed in terms of thermodynamic quantities, mostly Kd, and empirical IC50 values. Although binding affinity as an estimate of drug activity remains relevant, it is increasingly clear that it is also important to include (un)binding kinetic parameters in the characterization of potential drug-like molecules. Herein, we used standard in silico screening to identify a series of structurally related inhibitors of hDAAO, a flavoprotein involved in schizophrenia and neuropathic pain. We applied a novel methodology, based on scaled molecular dynamics, to rank them according to their residence times. Notably, we challenged the application in a prospective fashion for the first time. The good agreement between experimental residence times and the predicted residence times highlighted the procedure's reliability in both predictive and refinement scenarios. Additionally, through further inspection of the performed simulations, we substantiated a previous hypothesis on the involvement of a protein loop during ligand unbinding.

Molecular Bases of PDE4D Inhibition by Memory-Enhancing GEBR Library Compounds.

Selected members of the large rolipram-related GEBR family of type 4 phosphodiesterase (PDE4) inhibitors have been shown to facilitate long-term potentiation and to improve memory functions without causing emetic-like behavior in rodents. Despite their micromolar-range binding affinities and their promising pharmacological and toxicological profiles, few if any structure-activity relationship studies have been performed to elucidate the molecular bases of their action. Here, we report the crystal structure of a number of GEBR library compounds in complex with the catalytic domain of PDE4D as well as their inhibitory profiles for both the long PDE4D3 isoform and the catalytic domain alone. Furthermore, we assessed the stability of the observed ligand conformations in the context of the intact enzyme using molecular dynamics simulations. The longer and more flexible ligands appear to be capable of forming contacts with the regulatory portion of the enzyme, thus possibly allowing some degree of selectivity between the different PDE4 isoforms.

Structural and Kinetic Characterization of the Intrinsically Disordered Protein SeV NTAIL through Enhanced Sampling Simulations.

Intrinsically disordered proteins (IDPs) are emerging as an important class of the proteome. Being able to interact with different molecular targets, they participate in many physiological and pathological activities. However, due to their intrinsically heterogeneous nature, determining the equilibrium properties of IDPs is still a challenge for biophysics. Herein, we applied state-of-the-art enhanced sampling methods to Sev NTAIL, a test case of IDPs, and constructed a bin-based kinetic model to unveil the underlying kinetics. To validate our simulation strategy, we compared the predicted NMR properties against available experimental data. Our simulations reveal a rough free-energy surface comprising multiple local minima, which are separated by low energy barriers. Moreover, we identified interconversion rates between the main kinetic states, which lie in the sub-µs time scales, as suggested in previous works for Sev NTAIL. Therefore, the emerging picture is in agreement with the atomic-level properties possessed by the free IDP in solution. By providing both a thermodynamic and kinetic characterization of this IDP test case, our study demonstrates how computational methods can be effective tools for studying this challenging class of proteins.

Binding Mechanisms of Intrinsically Disordered Proteins: Theory, Simulation, and Experiment.

In recent years, protein science has been revolutionized by the discovery of intrinsically disordered proteins (IDPs). In contrast to the classical paradigm that a given protein sequence corresponds to a defined structure and an associated function, we now know that proteins can be functional in the absence of a stable three-dimensional structure. In many cases, disordered proteins or protein regions become structured, at least locally, upon interacting with their physiological partners. Many, sometimes conflicting, hypotheses have been put forward regarding the interaction mechanisms of IDPs and the potential advantages of disorder for protein-protein interactions. Whether disorder may increase, as proposed, e.g., in the "fly-casting" hypothesis, or decrease binding rates, increase or decrease binding specificity, or what role pre-formed structure might play in interactions involving IDPs (conformational selection vs. induced fit), are subjects of intense debate. Experimentally, these questions remain difficult to address. Here, we review experimental studies of binding mechanisms of IDPs using NMR spectroscopy and transient kinetic techniques, as well as the underlying theoretical concepts and numerical methods that can be applied to describe these interactions at the atomic level. The available literature suggests that the kinetic and thermodynamic parameters characterizing interactions involving IDPs can vary widely and that there may be no single common mechanism that can explain the different binding modes observed experimentally. Rather, disordered proteins appear to make combined use of features such as pre-formed structure and flexibility, depending on the individual system and the functional context.

Molecular Dynamics Simulations and Kinetic Measurements to Estimate and Predict Protein-Ligand Residence Times.

Ligand-target residence time is emerging as a key drug discovery parameter because it can reliably predict drug efficacy in vivo. Experimental approaches to binding and unbinding kinetics are nowadays available, but we still lack reliable computational tools for predicting kinetics and residence time. Most attempts have been based on brute-force molecular dynamics (MD) simulations, which are CPU-demanding and not yet particularly accurate. We recently reported a new scaled-MD-based protocol, which showed potential for residence time prediction in drug discovery. Here, we further challenged our procedure's predictive ability by applying our methodology to a series of glucokinase activators that could be useful for treating type 2 diabetes mellitus. We combined scaled MD with experimental kinetics measurements and X-ray crystallography, promptly checking the protocol's reliability by directly comparing computational predictions and experimental measures. The good agreement highlights the potential of our scaled-MD-based approach as an innovative method for computationally estimating and predicting drug residence times.

Unveiling the Atomic-Level Determinants of Acylase-Ligand Complexes: An Experimental and Computational Study.

The industrial production of higher-generation semisynthetic cephalosporins starts from 7-aminocephalosporanic acid (7-ACA), which is obtained by deacylation of the naturally occurring antibiotic cephalosporin C (CephC). The enzymatic process in which CephC is directly converted into 7-ACA by a cephalosporin C acylase has attracted industrial interest because of the prospects of simplifying the process and reducing costs. We recently enhanced the catalytic efficiency on CephC of a glutaryl acylase from Pseudomonas N176 (named VAC) by a protein engineering approach and solved the crystal structures of wild-type VAC and the H57ßS-H70ßS VAC double variant. In the present work, experimental measurements on several CephC derivatives and six VAC variants were carried out, and the binding of ligands into the VAC active site was investigated at an atomistic level by means of molecular docking and molecular dynamics simulations and analyzed on the basis of the molecular geometry of encounter complex formation and protein-ligand potential of mean force profiles. The observed significant correlation between the experimental data and estimated binding energies highlights the predictive power of our computational method to identify the ligand binding mode. The present experimental-computational study is well-suited both to provide deep insight into the reaction mechanism of cephalosporin C acylase and to improve the efficiency of the corresponding industrial process.