Literature DB >> 26587600

Electrostatically Embedded Molecular Tailoring Approach and Validation for Peptides.

Miho Isegawa1, Bo Wang1, Donald G Truhlar1.   

Abstract

We add higher-order electronic polarization effects to the molecular tailoring approach (MTA) by embedding each fragment in background charges as in combined quantum mechanical and molecular mechanical (QM/MM) methods; the resulting method considered here is called electrostatically embedded MTA (EE-MTA). We compare EE-MTA to MTA for a test peptide, Ace-(Ala)20-NMe, and we find that including background charges (embedding charges) greatly improves the performance. The fragmentation is performed on the basis of amino acids as monomers, and several sizes of fragment are tested. The fragments are capped with either hydrogen cap atoms or tuned fluorine cap atoms. The effective core potential of the tuned fluorine cap atom is optimized so as to reproduce the proton affinity for seven types of tetrapeptide, and the proton affinity calculated with the tuned cap atom shows a lower mean unsigned error than that obtained by using a hydrogen cap atom. In the application to the test peptide, these generically tuned cap atoms show better performance compared with the hydrogen cap atom for both the electronic energy and the energy difference between an α helix and a β sheet (in the latter case, 1.0% vs 2.7% when averaged over three sizes of fragments and two locations for cut bonds). Also, we compared the accuracy of several charge redistribution schemes, and we find that the results are not particularly sensitive to these choices for the Ace-(Ala)20-NMe peptide. We also illustrate the dependence on the choice of charge model for the embedding charges, including both fixed embedding charges and embedding charges that depend on conformation.

Entities:  

Year:  2013        PMID: 26587600     DOI: 10.1021/ct300845q

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  3 in total

1.  Interaction of metals from group 10 (Ni, Pd, and Pt) and 11 (Cu, Ag, and Au) with human blood δ-ALA-D: in vitro and in silico studies.

Authors:  Cláudia Vargas Klimaczewski; Pablo Andrei Nogara; Nilda Vargas Barbosa; João Batista Teixeira da Rocha
Journal:  Environ Sci Pollut Res Int       Date:  2018-09-01       Impact factor: 4.223

2.  Analysis of the Errors in the Electrostatically Embedded Many-Body Expansion of the Energy and the Correlation Energy for Zn and Cd Coordination Complexes with Five and Six Ligands and Use of the Analysis to Develop a Generally Successful Fragmentation Strategy.

Authors:  Elbek K Kurbanov; Hannah R Leverentz; Donald G Truhlar; Elizabeth A Amin
Journal:  J Chem Theory Comput       Date:  2013-06-11       Impact factor: 6.006

3.  Plasma protein binding prediction focusing on residue-level features and circularity of cyclic peptides by deep learning.

Authors:  Jianan Li; Keisuke Yanagisawa; Yasushi Yoshikawa; Masahito Ohue; Yutaka Akiyama
Journal:  Bioinformatics       Date:  2021-11-22       Impact factor: 6.937

  3 in total

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