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      CAMP: a useful resource for research on antimicrobial peptides

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          Abstract

          Antimicrobial peptides (AMPs) are gaining popularity as better substitute to antibiotics. These peptides are shown to be active against several bacteria, fungi, viruses, protozoa and cancerous cells. Understanding the role of primary structure of AMPs in their specificity and activity is essential for their rational design as drugs. Collection of Anti-Microbial Peptides (CAMP) is a free online database that has been developed for advancement of the present understanding on antimicrobial peptides. It is manually curated and currently holds 3782 antimicrobial sequences. These sequences are divided into experimentally validated (patents and non-patents: 2766) and predicted (1016) datasets based on their reference literature. Information like source organism, activity (MIC values), reference literature, target and non-target organisms of AMPs are captured in the database. The experimentally validated dataset has been further used to develop prediction tools for AMPs based on the machine learning algorithms like Random Forests (RF), Support Vector Machines (SVM) and Discriminant Analysis (DA). The prediction models gave accuracies of 93.2% (RF), 91.5% (SVM) and 87.5% (DA) on the test datasets. The prediction and sequence analysis tools, including BLAST, are integrated in the database. CAMP will be a useful database for study of sequence-activity and -specificity relationships in AMPs. CAMP is freely available at http://www.bicnirrh.res.in/antimicrobial.

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          Most cited references36

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          R: A Language and Environment for Statistical Computing.

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            Comparison of the predicted and observed secondary structure of T4 phage lysozyme.

            Predictions of the secondary structure of T4 phage lysozyme, made by a number of investigators on the basis of the amino acid sequence, are compared with the structure of the protein determined experimentally by X-ray crystallography. Within the amino terminal half of the molecule the locations of helices predicted by a number of methods agree moderately well with the observed structure, however within the carboxyl half of the molecule the overall agreement is poor. For eleven different helix predictions, the coefficients giving the correlation between prediction and observation range from 0.14 to 0.42. The accuracy of the predictions for both beta-sheet regions and for turns are generally lower than for the helices, and in a number of instances the agreement between prediction and observation is no better than would be expected for a random selection of residues. The structural predictions for T4 phage lysozyme are much less successful than was the case for adenylate kinase (Schulz et al. (1974) Nature 250, 140-142). No one method of prediction is clearly superior to all others, and although empirical predictions based on larger numbers of known protein structure tend to be more accurate than those based on a limited sample, the improvement in accuracy is not dramatic, suggesting that the accuracy of current empirical predictive methods will not be substantially increased simply by the inclusion of more data from additional protein structure determinations.
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              Thermostability and aliphatic index of globular proteins.

              A Ikai (1980)
              A statistical analysis shows that the aliphatic index, which is defined as the relative volume of a protein occupied by aliphatic side chains (alanine, valine, isoleucine, and leucine), of proteins of thermophilic bacteria is significantly higher than that of ordinary proteins. The index may be regarded as a positive factor for the increase of thermostability of globular proteins.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                January 2010
                18 November 2009
                18 November 2009
                : 38
                : Database issue , Database issue
                : D774-D780
                Affiliations
                1Biomedical Informatics Center of Indian Council of Medical Research, National Institute for Research in Reproductive Health, Mumbai, India, 2School of Informatics, Indiana University, Indianapolis, IN 46202, USA and 3SECG, Center for Development of Advanced Computing, Pune University Campus, Pune, India
                Author notes
                *To whom correspondence should be addressed. Tel.: 91-22-24192107/04 Fax: 91-22-24139412; Email: thomass@ 123456nirrh.res.in ; susan@ 123456icmr.org.in
                Correspondence may also be addressed to V. K. Jayaraman. Tel.: 91-20-25704228; Fax: 91-20-25694004; Email: jayaramanv@ 123456cdac.in ; vkjayaram@ 123456yahoo.com
                Article
                gkp1021
                10.1093/nar/gkp1021
                2808926
                19923233
                1eae704f-3de2-4c37-ad4e-09ba67be06ec
                © The Author(s) 2009. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 13 August 2009
                : 16 October 2009
                : 20 October 2009
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                Genetics
                Genetics

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