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      GRIMD: distributed computing for chemists and biologists

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          Abstract

          Motivation: Biologists and chemists are facing problems of high computational complexity that require the use of several computers organized in clusters or in specialized grids. Examples of such problems can be found in molecular dynamics (MD), in silico screening, and genome analysis. Grid Computing and Cloud Computing are becoming prevalent mainly because of their competitive performance/cost ratio. Regrettably, the diffusion of Grid Computing is strongly limited because two main limitations: it is confined to scientists with strong Computer Science background and the analyses of the large amount of data produced can be cumbersome it. We have developed a package named GRIMD to provide an easy and flexible implementation of distributed computing for the Bioinformatics community. GRIMD is very easy to install and maintain, and it does not require any specific Computer Science skill. Moreover, permits preliminary analysis on the distributed machines to reduce the amount of data to transfer. GRIMD is very flexible because it shields the typical computational biologist from the need to write specific code for tasks such as molecular dynamics or docking calculations. Furthermore, it permits an efficient use of GPU cards whenever is possible. GRIMD calculations scale almost linearly and, therefore, permits to exploit efficiently each machine in the network. Here, we provide few examples of grid computing in computational biology (MD and docking) and bioinformatics (proteome analysis).

          Availability

          GRIMD is available for free for noncommercial research at www.yadamp.unisa.it/grimd

          Supplementary information

          www.yadamp.unisa.it/grimd/howto.aspx

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          YADAMP: yet another database of antimicrobial peptides.

          This work presents an antimicrobial peptide database (YADAMP) based on an extensive literature search. This database is focused primarily on bacteria, with detailed information for 2133 peptides active against bacteria. YADAMP was created to facilitate access to critical information on antimicrobial peptides (AMPs). The main difference between YADAMP and other web databases of AMPs is the explicit presence of antimicrobial activity against the most common bacterial strains. YADAMP allows complex queries, easily accessible through a web interface. Peptide information can be retrieved based on peptide name, number of amino acids, net charge, hydrophobic percentage, sequence motif, structure and activity against bacteria. YADAMP is suitable for reviewing information on AMPs and for structure-function analyses of peptides. The database can be accessed via a web-based browser at http://www.yadamp.unisa.it. Copyright © 2012 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.
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            Small azobenzene derivatives active against bacteria and fungi.

            ATP synthase and protein kinase (PKs) are prime targets for drug discovery in a variety of diseases. It is well known that numerous stilbenes are capable to interact and inhibit ATP synthase and PKs. This work focuses on a series of azobenzene based molecules having high structural similarity with antimicrobial stilbenes. An investigation was carried out analyzing the potential toxicity of a large set of molecules by means of computational analysis. A small selection of potential low toxic molecules have been therefore synthesized, characterized and finally microbiologically tested. The synthesized compounds show potent bactericidal activity against Gram+ and a fungus, and are capable of inhibiting biofilm formation. Finally, the compounds demonstrated a thermal stability that makes them potential candidates for incorporation in polymer matrix for application as biomedical devices and food packaging. Copyright © 2013 Elsevier Masson SAS. All rights reserved.
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              Is Open Access

              2-Hydroxy Arachidonic Acid: A New Non-Steroidal Anti-Inflammatory Drug

              Background Nonsteroidal anti-inflammatory drugs (NSAIDs) are a family of COX1 and COX2 inhibitors used to reduce the synthesis of pro-inflammatory mediators. In addition, inflammation often leads to a harmful generation of nitric oxide. Efforts are being done in discovering safer NSAIDs molecules capable of inhibiting the synthesis of pro-inflammatory lipid mediators and nitric oxide to reduce the side effects associated with long term therapies. Methodology/Principal Findings The analogue of arachidonic acid (AA), 2-hydroxy-arachidonic acid (2OAA), was designed to inhibit the activities of COX1 and COX2 and it was predicted to have similar binding energies as AA for the catalytic sites of COX1 and COX2. The interaction of AA and 2OAA with COX1 and COX2 was investigated calculating the free energy of binding and the Fukui function. Toxicity was determined in mouse microglial BV-2 cells. COX1 and COX2 (PGH2 production) activities were measured in vitro. COX1 and COX2 expression in human macrophage-like U937 cells were carried out by Western blot, immunocytochemistry and RT-PCR analysis. NO production (Griess method) and iNOS (Western blot) were determined in mouse microglial BV-2 cells. The comparative efficacy of 2OAA, ibuprofen and cortisone in lowering TNF-α serum levels was determined in C57BL6/J mice challenged with LPS. We show that the presence of the –OH group reduces the likelihood of 2OAA being subjected to H* abstraction in COX, without altering significantly the free energy of binding. The 2OAA inhibited COX1 and COX2 activities and the expression of COX2 in human U937 derived macrophages challenged with LPS. In addition, 2OAA inhibited iNOS expression and the production of NO in BV-2 microglial cells. Finally, oral administration of 2OAA decreased the plasma TNF-α levels in vivo. Conclusion/Significance These findings demonstrate the potential of 2OAA as a NSAID.
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                Author and article information

                Journal
                Bioinformation
                Bioinformation
                Bioinformation
                Bioinformation
                Biomedical Informatics
                0973-8894
                0973-2063
                2014
                29 January 2014
                : 10
                : 1
                : 43-47
                Affiliations
                [1 ]Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Salerno – Italy
                [2 ]Department of Computer Science, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Salerno – Italy
                [3 ]Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, Salerno – Italy
                Author notes
                [* ]Stefano Piotto: s.piotto@ 123456gmail.com
                Article
                97320630010043
                10.6026/97320630010043
                3916819
                13318f29-60cc-4f2e-9d86-6e7a29a6ccf1
                © 2014 Biomedical Informatics

                This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.

                History
                : 04 October 2013
                : 29 November 2013
                : 06 January 2014
                Categories
                Software

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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