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        <identifier>oai:figshare.com:article/33823543</identifier>
        <datestamp>2026-09-15T21:04:49Z</datestamp>
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          <dc:title>Data for A minimalistic cyclic ice-binding peptide from phage display</dc:title>
          <dc:creator>Corey A. Stevens (3365495)</dc:creator>
          <dc:creator>Fabienne Bachtiger (12190371)</dc:creator>
          <dc:creator>Xu-Dong Kong (1837174)</dc:creator>
          <dc:creator>Luciano A. Abriata (695158)</dc:creator>
          <dc:creator>Gabriele C. Sosso (1304346)</dc:creator>
          <dc:creator>Matthew I. Gibson (1273788)</dc:creator>
          <dc:creator>Harm-Anton Klok (1488928)</dc:creator>
          <dc:subject>Antifreeze proteins</dc:subject>
          <dc:subject>Migrated from ePrints</dc:subject>
          <dc:description>Developing molecules that emulate the properties of naturally occurring ice-binding proteins (IBPs) is a daunting challenge. Rather than relying on the (limited) existing structure–property relationships that have been established for IBPs, here we report the use of phage display for the identification of short peptide mimics of IBPs. To this end, an ice-affinity selection protocol is developed, which enables the selection of a cyclic ice-binding peptide containing just 14 amino acids. Mutational analysis identifies three residues, Asp8, Thr10 and Thr14, which are found to be essential for ice binding. Molecular dynamics simulations reveal that the side chain of Thr10 hydrophobically binds to ice revealing a potential mechanism. To demonstrate the biotechnological potential of this peptide, it is expressed as a fusion (‘Ice-Tag’) with mCherry and used to purify proteins directly from cell lysate.&lt;br&gt;&lt;br&gt;1. Nclust contains the data on all 20 independent simulations and the various amount the ice front has grown by. It's measured by the number of OWs in the largest ice cluster at each time step.  2.S_S_torsional looks at the torisonal angles as a function of time between the disulphide bridges for each simulation  3. dist_THR looks at the distances between the methyl groups on threonine as a function of time for all simulations.  4. Input_data contains a represntative sample of input files used to run the simulations</dc:description>
          <dc:date>2021-05-24T00:00:00Z</dc:date>
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          <dc:identifier>10.82444/warw.33823543.v1</dc:identifier>
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          <dc:rights>CC BY-NC 4.0</dc:rights>
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