9,774 research outputs found

    Effect of the explicit flexibility of the InhA enzyme from Mycobacterium tuberculosis in molecular docking simulations

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    Background: Protein/receptor explicit flexibility has recently become an important feature of molecular docking simulations. Taking the flexibility into account brings the docking simulation closer to the receptors’ real behaviour in its natural environment. Several approaches have been developed to address this problem. Among them, modelling the full flexibility as an ensemble of snapshots derived from a molecular dynamics simulation (MD) of the receptor has proved very promising. Despite its potential, however, only a few studies have employed this method to probe its effect in molecular docking simulations. We hereby use ensembles of snapshots obtained from three different MD simulations of the InhA enzyme from M. tuberculosis (Mtb), the wild-type (InhA_wt), InhA_I16T, and InhA_I21V mutants to model their explicit flexibility, and to systematically explore their effect in docking simulations with three different InhA inhibitors, namely, ethionamide (ETH), triclosan (TCL), and pentacyano (isoniazid)ferrate(II) (PIF). Results: The use of fully-flexible receptor (FFR) models of InhA_wt, InhA_I16T, and InhA_I21V mutants in docking simulation with the inhibitors ETH, TCL, and PIF revealed significant differences in the way they interact as compared to the rigid, InhA crystal structure (PDB ID: 1ENY). In the latter, only up to five receptor residues interact with the three different ligands. Conversely, in the FFR models this number grows up to an astonishing 80 different residues. The comparison between the rigid crystal structure and the FFR models showed that the inclusion of explicit flexibility, despite the limitations of the FFR models employed in this study, accounts in a substantial manner to the induced fit expected when a protein/receptor and ligand approach each other to interact in the most favourable manner. Conclusions: Protein/receptor explicit flexibility, or FFR models, represented as an ensemble of MD simulation snapshots, can lead to a more realistic representation of the induced fit effect expected in the encounter and proper docking of receptors to ligands. The FFR models of InhA explicitly characterizes the overall movements of the amino acid residues in helices, strands, loops, and turns, allowing the ligand to properly accommodate itself in the receptor’s binding site. Utilization of the intrinsic flexibility of Mtb’s InhA enzyme and its mutants in virtual screening via molecular docking simulation may provide a novel platform to guide the rational or dynamicalstructure-based drug design of novel inhibitors for Mtb’s InhA. We have produced a short video sequence of each ligand (ETH, TCL and PIF) docked to the FFR models of InhA_wt. These videos are available at http://www.inf.pucrs. br/~osmarns/LABIO/Videos_Cohen_et_al_19_07_2011.htm

    Survival after acute hemodialysis in Pennsylvania, 2005-2007: A retrospective cohort study

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    Background: Little is known about acute hemodialysis in the US. Here we describe predictors of receipt of acute hemodialysis in one state and estimate the marginal impact of acute hemodialysis on survival after accounting for confounding due to illness severity. Materials and Methods: This is a retrospective cohort study of acute-care hospitalizations in Pennsylvania from October 2005 to December 2007 using data from the Pennsylvania Health Care Cost Containment Council. Exposure variable is acute hemodialysis; dependent variable is survival following acute hemodialysis. We used multivariable logistic regression to determine propensity to receive acute hemodialysis and then, for a Cox proportional hazards model, matched acute hemodialysis and non-acute hemodialysis patients 1:5 on this propensity. Results: In 2,131,248 admissions of adults without end-stage renal disease, there were 6,657 instances of acute hemodialysis. In analyses adjusted for predicted probability of death upon admission plus other covariates and stratified on age, being male, black, and insured were independent predictors of receipt of acute hemodialysis. One-year post-admission mortality was 43% for those receiving acute hemodialysis, compared to 13% among those not receiving acute hemodialysis. After matching on propensity to receive acute hemodialysis and adjusting for predicted probability of death upon admission, patients who received acute hemodialysis had a higher risk of death than patients who did not over at least 1 year of follow-up (hazard ratio 1.82, 95% confidence interval 1.68-1.97). Conclusions: In a populous US state, receipt of acute hemodialysis varied by age, sex, race, and insurance status even after adjustment for illness severity. In a comparison of patients with similar propensity to receive acute hemodialysis, those who did receive it were less likely to survive than those who did not. These findings raise questions about reasons for lack of benefit. Š 2014 Ramer et al

    Sorafenib dose escalation is not uniformly associated with blood pressure elevations in normotensive patients with advanced malignancies.

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    Hypertension after treatment with vascular endothelial growth factor (VEGF) receptor inhibitors is associated with superior treatment outcomes for advanced cancer patients. To determine whether increased sorafenib doses cause incremental increases in blood pressure (BP), we measured 12-h ambulatory BP in 41 normotensive advanced solid tumor patients in a randomized dose-escalation study. After 7 days' treatment (400 mg b.i.d.), mean diastolic BP (DBP) increased in both study groups. After dose escalation, group A (400 mg t.i.d.) had marginally significant further increase in 12-h mean DBP (P = 0.053), but group B (600 mg b.i.d.) did not achieve statistically significant increases (P = 0.25). Within groups, individuals varied in BP response to sorafenib dose escalation, but these differences did not correlate with changes in steady-state plasma sorafenib concentrations. These findings in normotensive patients suggest BP is a complex pharmacodynamic biomarker of VEGF inhibition. Patients have intrinsic differences in sensitivity to sorafenib's BP-elevating effects

    Dynamic Set Intersection

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    Consider the problem of maintaining a family FF of dynamic sets subject to insertions, deletions, and set-intersection reporting queries: given S,S′∈FS,S'\in F, report every member of S∩S′S\cap S' in any order. We show that in the word RAM model, where ww is the word size, given a cap dd on the maximum size of any set, we can support set intersection queries in O(dw/log⁡2w)O(\frac{d}{w/\log^2 w}) expected time, and updates in O(log⁡w)O(\log w) expected time. Using this algorithm we can list all tt triangles of a graph G=(V,E)G=(V,E) in O(m+mαw/log⁡2w+t)O(m+\frac{m\alpha}{w/\log^2 w} +t) expected time, where m=∣E∣m=|E| and α\alpha is the arboricity of GG. This improves a 30-year old triangle enumeration algorithm of Chiba and Nishizeki running in O(mα)O(m \alpha) time. We provide an incremental data structure on FF that supports intersection {\em witness} queries, where we only need to find {\em one} e∈S∩S′e\in S\cap S'. Both queries and insertions take O\paren{\sqrt \frac{N}{w/\log^2 w}} expected time, where N=∑S∈F∣S∣N=\sum_{S\in F} |S|. Finally, we provide time/space tradeoffs for the fully dynamic set intersection reporting problem. Using MM words of space, each update costs O(Mlog⁡N)O(\sqrt {M \log N}) expected time, each reporting query costs O(Nlog⁡NMop+1)O(\frac{N\sqrt{\log N}}{\sqrt M}\sqrt{op+1}) expected time where opop is the size of the output, and each witness query costs O(Nlog⁡NM+log⁡N)O(\frac{N\sqrt{\log N}}{\sqrt M} + \log N) expected time.Comment: Accepted to WADS 201

    FReDoWS: a method to automate molecular docking simulations with explicit receptor flexibility and snapshots selection

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    <p>Abstract</p> <p>Background</p> <p><it>In silico</it> molecular docking is an essential step in modern drug discovery when driven by a well defined macromolecular target. Hence, the process is called structure-based or rational drug design (RDD). In the docking step of RDD the macromolecule or receptor is usually considered a rigid body. However, we know from biology that macromolecules such as enzymes and membrane receptors are inherently flexible. Accounting for this flexibility in molecular docking experiments is not trivial. One possibility, which we call a fully-flexible receptor model, is to use a molecular dynamics simulation trajectory of the receptor to simulate its explicit flexibility. To benefit from this concept, which has been known since 2000, it is essential to develop and improve new tools that enable molecular docking simulations of fully-flexible receptor models.</p> <p>Results</p> <p>We have developed a Flexible-Receptor Docking Workflow System (FReDoWS) to automate molecular docking simulations using a fully-flexible receptor model. In addition, it includes a snapshot selection feature to facilitate acceleration the virtual screening of ligands for well defined disease targets. FReDoWS usefulness is demonstrated by investigating the docking of four different ligands to flexible models of <it>Mycobacterium tuberculosis’</it> wild type InhA enzyme and mutants I21V and I16T. We find that all four ligands bind effectively to this receptor as expected from the literature on similar, but wet experiments.</p> <p>Conclusions</p> <p>A work that would usually need the manual execution of many computer programs, and the manipulation of thousands of files, was efficiently and automatically performed by FReDoWS. Its friendly interface allows the user to change the docking and execution parameters. Besides, the snapshot selection feature allowed the acceleration of docking simulations. We expect FReDoWS to help us explore more of the role flexibility plays in receptor-ligand interactions. FReDoWS can be made available upon request to the authors.</p

    Stellar Dynamics and Black Holes

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    Chandrasekhar's most important contribution to stellar dynamics was the concept of dynamical friction. I briefly review that work, then discuss some implications of Chandrasekhar's theory of gravitational encounters for motion in galactic nuclei.Comment: Talk presented at the "Chandrasekhar Centenary Conference" (2010
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