Literature DB >> 24935111

Evaluation of active designs of cephalosporin C acylase by molecular dynamics simulation and molecular docking.

Qing Li1, Xiaoqiang Huang, Yushan Zhu.   

Abstract

Optimization to identify the global minimum energy conformation sequence in in silico enzyme design is computationally non-deterministic polynomial-time (NP)-hard, with the search time growing exponentially as the number of design sites increases. This drawback forces the modeling of protein-ligand systems to adopt discrete amino acid rotamers and ligand conformers, as well as continuum solvent treatment of the environment; however, such compromises produce large numbers of false positives in sequence selection. In this report, cephalosporin acylase, which catalyzes the hydrolytic reaction of cephalosporin C to 7-aminocephalosporanic acid, was used to investigate the dynamic features of active-site-transition-state complex structures using molecular dynamics (MD) simulations to potentially eliminate false positives. The molecular docking between cephalosporin C and wild type acylase N176 and its eight mutants showed that the rate-limiting step in the hydrolytic reaction of cephalosporin C is the acylation process. MD simulations of the active-site-transition-state complex structures of the acylation processes for N176 and its eight mutants showed that the geometrical constraints between catalytic residues and small molecule transition states are always well maintained during the 20 ns simulation for mutants with higher activities, and more hydrogen bonds between binding residues and functional groups of the ligand side chain in the active pocket are formed for mutants with higher activities. The conformations of the ligand transition states were changed greatly after the simulation. This indicates that the hydrogen bond network between the ligand and protein could be improved to enhance the activity of cephalosporin C acylase in subsequent design.

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Year:  2014        PMID: 24935111     DOI: 10.1007/s00894-014-2314-5

Source DB:  PubMed          Journal:  J Mol Model        ISSN: 0948-5023            Impact factor:   1.810


  26 in total

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6.  Systematic optimization model and algorithm for binding sequence selection in computational enzyme design.

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Authors:  Anastassia N Alexandrova; Daniela Röthlisberger; David Baker; William L Jorgensen
Journal:  J Am Chem Soc       Date:  2008-11-26       Impact factor: 15.419

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2.  Using molecular dynamics simulations to evaluate active designs of cephradine hydrolase by molecular mechanics/Poisson-Boltzmann surface area and molecular mechanics/generalized Born surface area methods.

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