1,172 research outputs found

    Tributes to Professor Cyril A. Fox, Jr.

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    Cy Fox often forgets that he was supposed to be “only” an academic. For three decades, as he helped thousands of law students through the intricacies of the Rule in Shelley’s Case, or watched them calculate a “life in being plus twenty one years” for the Rule Against Perpetuities, he failed to appreciate that law school was supposed to be an amalgam of theory and confusion, not the place for his teaching law students about helping real people solve real life problems

    PCV34 FINANCIAL ASSESSMENT OF A COMPREHENSIVE CARDIAC CARE PROGRAM FOR PATIENTS WITH OCCULSIVE CORONARY ARTERY DISEASE

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    Oncomodulin, an EF-hand Ca2+ buffer, is critical for maintaining cochlear function in mice

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    UNLABELLED: Oncomodulin (Ocm), a member of the parvalbumin family of calcium binding proteins, is expressed predominantly by cochlear outer hair cells in subcellular regions associated with either mechanoelectric transduction or electromotility. Targeted deletion of Ocm caused progressive cochlear dysfunction. Although sound-evoked responses are normal at 1 month, by 4 months, mutants show only minimal distortion product otoacoustic emissions and 70-80 dB threshold shifts in auditory brainstem responses. Thus, Ocm is not critical for cochlear development but does play an essential role for cochlear function in the adult mouse. SIGNIFICANCE STATEMENT: Numerous proteins act as buffers, sensors, or pumps to control calcium levels in cochlear hair cells. In the inner ear, EF-hand calcium buffers may play a significant role in hair cell function but have been very difficult to study. Unlike other reports of genetic disruption of EF-hand calcium buffers, deletion of oncomodulin (Ocm), which is predominately found in outer hair cells, leads to a progressive hearing loss after 1 month, suggesting that Ocm critically protects hearing in the mature ear

    Aneuploidy Detection in Pigs Using Comparative Genomic Hybridization: From the Oocytes to Blastocysts

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    Data on the frequency of aneuploidy in farm animals are lacking and there is the need for a reliable technique which is capable of detecting all chromosomes simultaneously in a single cell. With the employment of comparative genomic hybridization coupled with the whole genome amplification technique, this study brings new information regarding the aneuploidy of individual chromosomes in pigs. Focus is directed on in vivo porcine blastocysts and late morulas, 4.7% of which were found to carry chromosomal abnormality. Further, ploidy abnormalities were examined using FISH in a sample of porcine embryos. True polyploidy was relatively rare (1.6%), whilst mixoploidy was presented in 46.8% of embryos, however it was restricted to only a small number of cells per embryo. The combined data indicates that aneuploidy is not a prevalent cause of embryo mortality in pigs

    Role of the Subunits Interactions in the Conformational Transitions in Adult Human Hemoglobin: an Explicit Solvent Molecular Dynamics Study

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    Hemoglobin exhibits allosteric structural changes upon ligand binding due to the dynamic interactions between the ligand binding sites, the amino acids residues and some other solutes present under physiological conditions. In the present study, the dynamical and quaternary structural changes occurring in two unligated (deoxy-) T structures, and two fully ligated (oxy-) R, R2 structures of adult human hemoglobin were investigated with molecular dynamics. It is shown that, in the sub-microsecond time scale, there is no marked difference in the global dynamics of the amino acids residues in both the oxy- and the deoxy- forms of the individual structures. In addition, the R, R2 are relatively stable and do not present quaternary conformational changes within the time scale of our simulations while the T structure is dynamically more flexible and exhibited the T\rightarrow R quaternary conformational transition, which is propagated by the relative rotation of the residues at the {\alpha}1{\beta}2 and {\alpha}2{\beta}1 interface.Comment: Reprinted (adapted) with permission from J. Phys. Chem. B DOI:10.1021/jp3022908. Copyright (2012) American Chemical Societ

    Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structure-based virtual screening

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    Recently much effort has been invested in using convolutional neural network (CNN) models trained on 3D structural images of protein-ligand complexes to distinguish binding from non-binding ligands for virtual screening. However, the dearth of reliable protein-ligand x-ray structures and binding affinity data has required the use of constructed datasets for the training and evaluation of CNN molecular recognition models. Here, we outline various sources of bias in one such widely-used dataset, the Directory of Useful Decoys: Enhanced (DUDE). We have constructed and performed tests to investigate whether CNN models developed using DUD-E are properly learning the underlying physics of molecular recognition, as intended, or are instead learning biases inherent in the dataset itself. We find that superior enrichment efficiency in CNN models can be attributed to the analogue and decoy bias hidden in the DUD-E dataset rather than successful generalization of the pattern of proteinligand interactions. Comparing additional deep learning models trained on PDBbind datasets, we found that their enrichment performances using DUD-E are not superior to the performance of the docking program AutoDock Vina. Together, these results suggest that biases that could be present in constructed datasets should be thoroughly evaluated before applying them to machine learning based methodology development

    Hidden bias in the DUD-E dataset leads to misleading performance of deep learning in structure-based virtual screening

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    Recently much effort has been invested in using convolutional neural network (CNN) models trained on 3D structural images of protein-ligand complexes to distinguish binding from non-binding ligands for virtual screening. However, the dearth of reliable protein-ligand x-ray structures and binding affinity data has required the use of constructed datasets for the training and evaluation of CNN molecular recognition models. Here, we outline various sources of bias in one such widely-used dataset, the Directory of Useful Decoys: Enhanced (DUDE). We have constructed and performed tests to investigate whether CNN models developed using DUD-E are properly learning the underlying physics of molecular recognition, as intended, or are instead learning biases inherent in the dataset itself. We find that superior enrichment efficiency in CNN models can be attributed to the analogue and decoy bias hidden in the DUD-E dataset rather than successful generalization of the pattern of proteinligand interactions. Comparing additional deep learning models trained on PDBbind datasets, we found that their enrichment performances using DUD-E are not superior to the performance of the docking program AutoDock Vina. Together, these results suggest that biases that could be present in constructed datasets should be thoroughly evaluated before applying them to machine learning based methodology development

    Strength of Hydrogen Bond Network Takes Crucial Roles in the Dissociation Process of Inhibitors from the HIV-1 Protease Binding Pocket

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    To understand the underlying mechanisms of significant differences in dissociation rate constant among different inhibitors for HIV-1 protease, we performed steered molecular dynamics (SMD) simulations to analyze the entire dissociation processes of inhibitors from the binding pocket of protease at atomistic details. We found that the strength of hydrogen bond network between inhibitor and the protease takes crucial roles in the dissociation process. We showed that the hydrogen bond network in the cyclic urea inhibitors AHA001/XK263 is less stable than that of the approved inhibitor ABT538 because of their large differences in the structures of the networks. In the cyclic urea inhibitor bound complex, the hydrogen bonds often distribute at the flap tips and the active site. In contrast, there are additional accessorial hydrogen bonds formed at the lateral sides of the flaps and the active site in the ABT538 bound complex, which take crucial roles in stabilizing the hydrogen bond network. In addition, the water molecule W301 also plays important roles in stabilizing the hydrogen bond network through its flexible movement by acting as a collision buffer and helping the rebinding of hydrogen bonds at the flap tips. Because of its high stability, the hydrogen bond network of ABT538 complex can work together with the hydrophobic clusters to resist the dissociation, resulting in much lower dissociation rate constant than those of cyclic urea inhibitor complexes. This study may provide useful guidelines for design of novel potent inhibitors with optimized interactions

    Absolute Single-Molecule Entropies from Quasi-Harmonic Analysis of Microsecond Molecular Dynamics: Correction Terms and Convergence Properties

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    The convergence properties of the absolute single-molecule configurational entropy and the correction terms used to estimate it are investigated using microsecond molecular dynamics simulation of a peptide test system and an improved methodology. The results are compared with previous applications for systems of diverse chemical nature. It is shown that (i) the effect of anharmonicity is small, (ii) the effect of pairwise correlation is typically large, and (iii) the latter affects to a larger extent the entropy estimate of thermodynamic states characterized by a higher motional correlation. The causes of such deviations from a quasi-harmonic behavior are explained. This improved approach provides entropies also for molecular systems undergoing conformational transitions and characterized by highly frustrated energy surfaces, thus not limited to systems sampling a single quasi-harmonic basin. Overall, this study emphasizes the need for extensive phase-space sampling in order to obtain a reliable estimation of entropic contributions
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