Efficiency of the multicanonical simulation method as applied to peptides of increasing size: The heptapeptide deltorphin

YAŞAR F., Arkin H., Celik T., Berg B., Meirovitch H.

JOURNAL OF COMPUTATIONAL CHEMISTRY, vol.23, no.12, pp.1127-1134, 2002 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 23 Issue: 12
  • Publication Date: 2002
  • Doi Number: 10.1002/jcc.10113
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1127-1134
  • Hacettepe University Affiliated: Yes


The advantage of the multicanonical MUCA) simulation method of Berg and coworkers over the conventional Metropolis method is in its ability to move a system effectively across energy barriers thereby providing results for a wide range of temperatures. However, a MUCA simulation is based on weights related to the density of states) that should be determined prior to a production run and their calculation is not straightforward. To overcome this difficulty a procedure has been developed by Berg that calculates the MUCA weights automatically. In a previous article (Yasar et al. J Comput Chem 2000, 14, 1251-1261) we extended this procedure to continuous systems and applied it successfully to the small pentapeptide Leu-enkephalin. To investigate the performance of the automated MUCA procedure for larger peptides, we apply it here to deltorphin, a linear heptapeptide with bulky side chains (H-Tyr(1)-D-Met(2)-Phe(3)-HiS(4)-Leu(5)-Met(6)-ASp(7)-NH2). As for Leu-enkephalin, deltorphin is modeled in vacuum by the potential energy function ECEPP, MUCA is found to perform well. A weak second peak is seen for the specific heat, which is given a special attention. By minimizing the energy of structures along the trajectory it is found that MUCA provides a good conformational coverage of the low energy region of the molecule. These latter results are compared with conformational coverage obtained by the Monte Carlo minimization method of Li and Scheraga.