Literature DB >> 17407347

Side-chain and backbone ordering in homopolymers.

Yanjie Wei1, Walter Nadler, Ulrich H E Hansmann.   

Abstract

In order to study the relation between backbone and side-chain ordering in proteins, we have performed multicanonical simulations of deka-peptide chains with various side groups. Glu(10), Gln(10), Asp(10), Asn(10), and Lys(10) were selected to cover a wide variety of possible interactions between the side chains of the monomers. All homopolymers undergo helix-coil transitions. We found that peptides with long side chains that are capable of hydrogen bonding, i.e., Glu(10), and Gln(10), exhibit a second transition at lower temperatures connected with side-chain ordering. This occurs in the gas phase as well as in solvent, although the character of the side-chain structure is different in each case. However, in polymers with short side chains capable of hydrogen bonding, i.e., Asp(10) and Asn(10), side-chain ordering takes place over a wide temperature range and exhibits no phase transition-like character. Moreover, non-backbone hydrogen bonds show enhanced formation and fluctuations already at the helix-coil transition temperature, indicating competition between side-chain and backbone hydrogen bond formation. Again, these results are qualitatively independent of the environment. Side-chain ordering in Lys(10), whose side groups are long and polar, also takes place over a wide temperature range and exhibits no phase transition-like character in both environments. Reasons for the observed chain length threshold and consequences from these results for protein folding are discussed.

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Year:  2007        PMID: 17407347     DOI: 10.1021/jp071127e

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  1 in total

1.  DeepBindPoc: a deep learning method to rank ligand binding pockets using molecular vector representation.

Authors:  Haiping Zhang; Konda Mani Saravanan; Jinzhi Lin; Linbu Liao; Justin Tze-Yang Ng; Jiaxiu Zhou; Yanjie Wei
Journal:  PeerJ       Date:  2020-04-06       Impact factor: 2.984

  1 in total

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