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Originally published In Press as doi:10.1074/jbc.M501657200 on March 7, 2005

J. Biol. Chem., Vol. 280, Issue 19, 19343-19349, May 13, 2005
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Prediction of Collagen Stability from Amino Acid Sequence*

Anton V. Persikov{ddagger}§, John A. M. Ramshaw¶, and Barbara Brodsky, Recipient of the Ruth Kirchstein National Research Service Award (National Institute of General Medical Sciences){ddagger}||

From the {ddagger}Department of Biochemistry, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, Piscataway, New Jersey 08854 and Commonwealth Scientific and Industrial Research Organisation, 343 Royal Parade, Parkville, Victoria 3052, Australia

An algorithm was derived to relate the amino acid sequence of a collagen triple helix to its thermal stability. This calculation is based on the triple helical stabilization propensities of individual residues and their intermolecular and intramolecular interactions, as quantitated by melting temperature values of host-guest peptides. Experimental melting temperature values of a number of triple helical peptides of varying length and sequence were successfully predicted by this algorithm. However, predicted Tm values are significantly higher than experimental values when there are strings of oppositely charged residues or concentrations of like charges near the terminus. Application of the algorithm to collagen sequences highlights regions of unusually high or low stability, and these regions often correlate with biologically significant features. The prediction of stability from sequence indicates an understanding of the major forces maintaining this protein motif. The use of highly favorable KGE and KGD sequences is seen to complement the stabilizing effects of imino acids in modulating stability and may become dominant in the collagenous domains of bacterial proteins that lack hydroxyproline. The effect of single amino acid mutations in the X and Y positions can be evaluated with this algorithm. An interactive collagen stability calculator based on this algorithm is available online.


Received for publication, February 14, 2005

* This work was supported in part by National Institutes of Health Grant GM60048 (to B. B.). The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

§ Supported by the Michael Geisman Fellowship from the Osteogenesis Imperfecta Foundation.

|| To whom correspondence should be addressed: Dept. of Biochemistry, University of Medicine and Dentistry of New Jersey-Robert Wood Johnson Medical School, 675 Hoes Lane, Piscataway, NJ 08854. Tel.: 732-235-4048; Fax: 732-235-4783; E-mail: brodsky{at}umdnj.edu.


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