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The interpretation of ligand–target interactions at atomistic resolution is central to most efforts in computational drug discovery and optimization. However, the highly dynamic nature of protein targets, as well as possible induced fit effects, makes difficult to sample many interactions effectively with docking studies or even with large-scale molecular dynamics (MD) simulations. We propose a novel application of Self-Organizing Maps (SOMs) to address the sampling and dynamic mapping tasks, particularly in cases involving ligand flexibility and induced fit. The SOM approach offers a data-driven strategy to create a map of the interaction process and pathways based on unbiased MD. Furthermore, we show how the preliminary SOM mapping is complementary to kinetic analysis, with the employment of both network-based approaches and Markov state models. We demonstrate the method by comprehensively mapping a large dataset of 640 μs of unbiased trajectories sampling the recognition process between the phosphorylated YEEI peptide and its high-specificity target lck-SH2. The integration of SOM into unbiased simulation protocols significantly advances our understanding of the ligand binding mechanism. This approach serves as a potent tool for mapping intricate ligand–target interactions with unprecedented detail, thereby enhancing the characterization of kinetic properties crucial to drug design. [ABSTRACT FROM AUTHOR]

Abstract AGel amyloidosis, formerly known as familial amyloidosis of the Finnish-type, is caused by pathological aggregation of proteolytic fragments of plasma gelsolin. So far, four mutations in the gelsolin gene have been reported as responsible for the disease. Although D187N is the first identified variant and the best characterized, its structure has been hitherto elusive. Exploiting a recently-developed nanobody targeting gelsolin, we were able to stabilize the G2 domain of the D187N protein and obtained, for the first time, its high-resolution crystal structure. In the nanobody-stabilized conformation, the main effect of the D187N substitution is the impairment of the calcium binding capability, leading to a destabilization of the C-terminal tail of G2. However, molecular dynamics simulations show that in the absence of the nanobody, D187N-mutated G2 further misfolds, ultimately exposing its hydrophobic core and the furin cleavage site. The nanobody's protective effect is based on the enhancement of the thermodynamic stability of different G2 mutants (D187N, G167R and N184K). In particular, the nanobody reduces the flexibility of dynamic stretches, and most notably decreases the conformational entropy of the C-terminal tail, otherwise stabilized by the presence of the Ca2+ ion. A Caenorhabditis elegans -based assay was also applied to quantify the proteotoxic potential of the mutants and determine whether nanobody stabilization translates into a biologically relevant effect. Successful protection from G2 toxicity in vivo points to the use of C. elegans as a tool for investigating the mechanisms underlying AGel amyloidosis and rapidly screen new therapeutics. Graphical abstract Unlabelled Image Highlights • D187N gelsolin variant is responsible for the most common form of AGel amyloidosis • We obtained the crystal structure of the second domain of D187N in complex with a nanobody • D187N substitution increases the conformational flexibility of the protein, nanobody binding shifts D187N towards a WT-like conformation • The same nanobody binds to and protects other gelsolin pathological variants (N184K and G167R) • The nanobody protects from the toxicity induced by gelsolin mutants in C. elegans [ABSTRACT FROM AUTHOR]

In vivo studies have investigated the role of β-cell dysfunction in type 2 diabetes (T2D), whereas in vitro research on islets has elucidated key mechanisms that control the insulin secretion rate. However, the relevance of the cellular mechanisms identified in vitro (i.e., the triggering and amplifying pathways) has not been established in vivo. Furthermore, the mechanisms underpinning β-cell dysfunction in T2D remain undetermined. We propose a unifying explanation of several characteristic features of insulin secretion both in vitro and in vivo by using a mathematical model. The model describes the triggering and amplifying pathways and reproduces a variety of in vitro and in vivo tests in subjects with and without T2D, identifies the mechanisms modulating first-phase insulin secretion rate in response to basal hyperglycemia or insulin resistance, and shows that β-cell dysfunction in T2D can be explained by an impaired amplifying pathway with no need to postulate defects in intracellular calcium handling. [ABSTRACT FROM AUTHOR]

Allogeneic hematopoietic stem cell transplantation (SCT) is the only curative option for patients with primary myelofibrosis (PMF), but information on its net advantage over conventional therapies is lacking. Using ad hoc statistical analysis, we determined outcomes in 438 patients <65 years old at diagnosis who received allogenic SCT (n = 190) or conventional therapies (n = 248). Among patients at low risk per the Dynamic International Prognostic Scoring System (DIPSS) model, the relative risk of death after allogenic SCT vs those treated with nontransplant modalities was 5.6 (95% Cl, 1.7-19; P= .0051); for intermediate-1 risk it was 1.6 (95% Cl, 0.79-3.2; P= .19), for intermediate-2 risk, 0.55 (95% Cl, 0.36-0.83; P = .005), and for high risk, 0.37 (95% Cl, 0.21-0.66; P = .0007). Thus, patients with intermediate-2 or high-risk PMF clearly benefit from allogenic SCT. Patients at low risk should receive nontransplant therapy, whereas individual counseling is indicated for patients at intermediate-1 risk. [ABSTRACT FROM AUTHOR]

The understanding of protein-ligand binding is of critical importance for biomedical research, yet the process itself has been very difficult to study because of its intrinsically dynamic character. Here, we have been able to quantitatively reconstruct the complete binding process of the enzyme-inhibitor complex trypsin-benzamidine by performing 495 molecular dynamics simulations of free ligand binding of 100 ns each, 187 of which produced binding events with an rmsd less than 2 Å compared to the crystal structure. The binding paths obtained are able to capture the kinetic pathway of the inhibitor diffusing from solvent (S0) to the bound (S4) state passing through two metastable intermediate states S2 and S3. Rather than directly entering the binding pocket the inhibitor appears to roll on the surface of the protein in its transition between S3 and the final binding pocket, whereas the transition between S2 and the bound pose requires rediffusion to S3. An estimation of the standard free energy of binding gives ΔG° = -5.2 ± 0.4 kcal/mol (cf. the experimental value -6.2 kcal/mol), and a two-states kinetic model kon = (1.5 ± 0.2) × 108 M-1 s-1 and koff = (9.5 ± 3.3) × 104 s-1 for unbound to bound transitions. The ability to reconstruct by simple diffusion the binding pathway of an enzyme-inhibitor binding process demonstrates the predictive power of unconventional high-throughput molecular simulations. Moreover, the methodology is directly applicable to other molecular systems and thus of general interest in biomedical and pharmaceutical research. [ABSTRACT FROM AUTHOR]

Summary: Objective: The purpose of this study was to assess the performance of a real-time (“open-end”) version of the dynamic time warping (DTW) algorithm for the recognition of motor exercises. Given a possibly incomplete input stream of data and a reference time series, the open-end DTW algorithm computes both the size of the prefix of reference which is best matched by the input, and the dissimilarity between the matched portions. The algorithm was used to provide real-time feedback to neurological patients undergoing motor rehabilitation. Methods and materials: We acquired a dataset of multivariate time series from a sensorized long-sleeve shirt which contains 29 strain sensors distributed on the upper limb. Seven typical rehabilitation exercises were recorded in several variations, both correctly and incorrectly executed, and at various speeds, totaling a data set of 840 time series. Nearest-neighbour classifiers were built according to the outputs of open-end DTW alignments and their global counterparts on exercise pairs. The classifiers were also tested on well-known public datasets from heterogeneous domains. Results: Nonparametric tests show that (1) on full time series the two algorithms achieve the same classification accuracy (p-value ); (2) on partial time series, classifiers based on open-end DTW have a far higher accuracy ( versus ); and (3) the prediction of the matched fraction follows closely the ground truth (root mean square ). The results hold for the motor rehabilitation and the other datasets tested, as well. Conclusions: The open-end variant of the DTW algorithm is suitable for the classification of truncated quantitative time series, even in the presence of noise. Early recognition and accurate class prediction can be achieved, provided that enough variance is available over the time span of the reference. Therefore, the proposed technique expands the use of DTW to a wider range of applications, such as real-time biofeedback systems. [Copyright &y& Elsevier]

Summary: Recent advances in automatic speech recognition and related technologies allow computers to carry on conversations by telephone. We developed an intelligent dialogue system that interacts with hypertensive patients to collect data about their health status. Patients thus avoid the inconvenience of traveling for frequent face to face visits to monitor the clinical variables they can easily measure at home; the physician is facilitated in acquiring patient information and cardiovascular risk, which is evaluated from the data according to noted guidelines. Controlled trials to assess the clinical efficacy are under way. [Copyright &y& Elsevier]

Intracerebral hemorrhages are recognized risk factors for neurodevelopmental disorders and represent early biomarkers for cognitive dysfunction and mental disability, but the pathways leading to their occurrence are not well defined. We report that a single intrauterine exposure of the immunostimulant Poly I:C to pregnant mice at gestational day 9, which models a prenatal viral infection and the consequent maternal immune activation, induces the defective formation of brain vessels and causes intracerebral hemorrhagic events, specifically in male offspring. We demonstrate that maternal immune activation promotes the production of the TGF‐β1 active form and the consequent enhancement of pSMAD1‐5 in males' brain endothelial cells. TGF‐β1, in combination with IL‐1β, reduces the endothelial expression of CD146 and claudin‐5, alters the endothelium–pericyte interplay resulting in low pericyte coverage, and increases hemorrhagic events in the adult offspring. By showing that exposure to Poly I:C at the beginning of fetal cerebral angiogenesis results in sex‐specific alterations of brain vessels, we provide a mechanistic framework for the association between intragravidic infections and anomalies of the neural vasculature, which may contribute to neuropsychiatric disorders. Synopsis: A mouse model of viral infection during pregnancy shows that maternal immune activation results in male‐specific defects in the formation of brain vasculature in the offspring leading to fragile and hemorrhage‐prone blood vessels.A single intrauterine exposure to Poly I:C in pregnant mice leads to disruption of endothelial cell–pericyte interplay in the brain–blood vessels of the offspring.Breakdown of the neurovascular unit results in hemorrhage‐prone vessels.Maternal immune activation leads to the induction of TGF‐β and reduced endothelial expression of CD146 selectively in male mice.Male brain–blood vessels show a reduced number of pericytes and concomitant disruption of the tight junction protein CLND5. [ABSTRACT FROM AUTHOR]

A goal in the kinetic characterization of a macromolecular system is the description of its slow relaxation processes via (i) identification of the structural changes involved in these processes and (ii) estimation of the rates or timescales at which these slow processes occur. Most of the approaches to this task, including Markov models, master-equation models, and kinetic network models, start by discretizing the high-dimensional state space and then characterize relaxation processes in terms of the eigenvectors and eigenvalues of a discrete transition matrix. The practical success of such an approach depends very much on the ability to finely discretize the slow order parameters. How can this task be achieved in a high-dimensional configuration space without relying on subjective guesses of the slow order parameters? In this paper, we use the variational principle of conformation dynamics to derive an optimal way of identifying the 'slow subspace' of a large set of prior order parameters - either generic internal coordinates or a user-defined set of parameters. Using a variational formulation of conformational dynamics, it is shown that an existing method-the time-lagged independent component analysis-provides the optional solution to this problem. In addition, optimal indicators-order parameters indicating the progress of the slow transitions and thus may serve as reaction coordinates-are readily identified. We demonstrate that the slow subspace is well suited to construct accurate kinetic models of two sets of molecular dynamics simulations, the 6-residue fluorescent peptide MR121-GSGSW and the 30-residue intrinsically disordered peptide kinase inducible domain (KID). The identified optimal indicators reveal the structural changes associated with the slow processes of the molecular system under analysis. [ABSTRACT FROM AUTHOR]

Mutations in the gelsolin protein are responsible for a rare conformational disease known as AGel amyloidosis. Four of these mutations are hosted by the second domain of the protein (G2): D187N/Y, G167R and N184K. The impact of the latter has been so far evaluated only by studies on the isolated G2. Here we report the characterization of full-length gelsolin carrying the N184K mutation and compare the findings with those obtained on the wild type and the other variants. The crystallographic structure of the N184K variant in the Ca2+-free conformation shows remarkable similarities with the wild type protein. Only minimal local rearrangements can be observed and the mutant is as efficient as the wild type in severing filamentous actin. However, the thermal stability of the pathological variant is compromised in the Ca2+-free conditions. These data suggest that the N to K substitution causes a local disruption of the H-bond network in the core of the G2 domain. Such a subtle rearrangement of the connections does not lead to significant conformational changes but severely affects the stability of the protein. [ABSTRACT FROM AUTHOR]

The second domain of gelsolin (G2) hosts mutations responsible for a hereditary form of amyloidosis. The active form of gelsolin is Ca2+-bound; it is also a dynamic protein, hence structural biologists often rely on the study of the isolated G2. However, the wild type G2 structure that have been used so far in comparative studies is bound to a crystallographic Cd2+, in lieu of the physiological calcium. Here, we report the wild type structure of G2 in complex with Ca2+ highlighting subtle ion-dependent differences. Previous findings on different G2 mutations are also briefly revised in light of these results. • The structure of gelsolin G2 bound to Ca2+ is proposed as a novel 3D reference. • Subtle ion-dependent structural differences are reported. • High flexibility of the hinge loop is a hallmark of the pathogenic variants. [ABSTRACT FROM AUTHOR]

Although interdisciplinarity is often touted as a necessity for modern research, the evidence on the relative impact of sectorial versus to interdisciplinary science is qualitative at best. In this paper we leverage the bibliographic data set of the American Physical Society to quantify the role of interdisciplinarity in physics, and that of talent and luck in achieving success in scientific careers. We analyze a period of 30 years (1980-2009) tagging papers and their authors by means of the Physics and Astronomy Classification Scheme (PACS), to show that some degree of interdisciplinarity is quite helpful to reach success, measured as a proxy of either the number of articles or the citations score. We also propose an agent-based model of the publication-reputation-citation dynamics which reproduces the trends observed in the APS data set. On the one hand, the results highlight the crucial role of randomness and serendipity in real scientific research; on the other, they shed light on a counterintuitive effect indicating that the most talented authors are not necessarily the most successful ones. [ABSTRACT FROM AUTHOR]

The oxoeicosanoid receptor 1 (OXER1) is a member of the G-protein coupled receptors (GPCR) family, and is involved in inflammatory processes and oncogenesis. As such it is an attractive target for pharmacological intervention. The present study aimed to shed light on the molecular fundaments of OXER1 modulation using chemical probes structurally related to the natural agonist 5-oxo-ETE. In a first step, 5-oxo-ETE and its closely related derivatives (5-oxo-EPE and 4-oxo-DHA) were obtained by conducting concise and high-yielding syntheses. The biological activity of obtained compounds was assessed in terms of potency (EC 50 ) and efficacy (E max ) for arrestin recruitment. Finally, molecular modelling and simulation were used to explore binding characteristics of 5-oxo-ETE and derivatives with the aim to rationalize biological activity. Our data suggest that the tested 5-oxo-ETE derivatives (i) insert quickly into the membrane, (ii) access the receptor via transmembrane helices (TMs) 5 and 6 from the membrane side and (iii) drive potency and efficacy by differential interaction with TM5 and 7. Most importantly, we found that the methyl ester of 5-oxo-ETE ( 1a ) showed even a higher maximum response than the natural agonist ( 1 ). In contrast, shifting the 5-oxo group into position 4 results in inactive compounds (4-oxo DHA compounds ( 3 ) and ( 3a )). All in all, our study provides relevant structural data that help understanding better OXER1 functionality and its modulation. The structural information presented herein will be useful for designing new lead compounds with desired signalling profiles. [ABSTRACT FROM AUTHOR]

Substantial data indicate that amyloid-β (Aβ), the major component of senile plaques, plays a central role in Alzheimer’s Disease and indeed the assembly of naturally occurring amyloid peptides into cytotoxic aggregates is linked to the disease pathogenesis. Although Aβ42 is a highly aggregating form of Aβ, the co-occurrence of shorter Aβ peptides might affect the aggregation potential of the Aβ pool. In this study we aimed to assess whether the structural behavior of human Aβ42 peptide inside the brain is influenced by the concomitant presence of N-terminal fragments produced by the proteolytic activity of glial cells. We show that the occurrence of the human C-terminal truncated 1–24 Aβ fragment impairs Aβ42 clearance through blood brain barrier and promotes the formation of Aβ42 aggregates even in the healthy brain. By showing that Aβ1-24 has seeding properties for aggregate formation in intracranially injected wild type mice, our study provide the proof-of-concept that peptides produced upon Aβ42 cleavage by activated glial cells may cause phenotypic defects even in the absence of genetic mutations associated with Alzheimer’s Disease, possibly contributing to the development of the sporadic form of the pathology. [ABSTRACT FROM AUTHOR]

Lipid composition is expected to play an important role in modulating membrane enzyme activity, in particular if the substrates are themselves lipid molecules. A paradigmatic case is FAAH (fatty acid amide hydrolase), an enzyme critical in terminating endocannabinoid signalling and an important therapeutic target. In the present study, using a combined experimental and computational approach, we show that membrane lipids modulate the structure, subcellular localization and activity of FAAH.We report that the FAAHdimer is stabilized by the lipid bilayer and shows a highermembrane-binding affinity and enzymatic activity within membranes containing both cholesterol and the natural FAAH substrate AEA (anandamide). Additionally, co-localization of cholesterol, AEA and FAAH in mouse neuroblastoma cells suggests a mechanism through which cholesterol increases the substrate accessibility of FAAH. [ABSTRACT FROM AUTHOR]

Summary: Computer simulations are giving way to more complex and accurate studies of biological membranes by molecular dynamics (MD) simulations. The analysis of MD trajectories comprises the biophysical characterization of membrane properties or the study of protein–lipid interactions and dynamics. However, there is a lack of automated tools to analyse MD simulations of complex membrane or membrane-protein systems. Here we present MEMBPLUGIN, a plugin for the Visual Molecular Dynamics package that provides algorithms to measure a host of essential biophysical properties in simulated membranes. MEMBPLUGIN features are accessible both through a user-friendly graphical interface and as command-line procedures to be invoked in analysis scripts.Availability and implementation: MEMBPLUGIN is a VMD extension written in Tcl. Multi-platform source code, documentation and tutorials are freely available at http://membplugin.sourceforge.net.Contact: toni.giorgino@isib.cnr.it or jana.selent@upf.eduSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]