Computational Modeling of a Biocatalyst at a Hydrophobic Substrate Interface

Sven Benson and Jürgen Pleiss ()
Additional contact information
Sven Benson: University of Stuttgart, Institute of Technical Biochemistry
Jürgen Pleiss: University of Stuttgart, Institute of Technical Biochemistry

A chapter in High Performance Computing in Science and Engineering ’15, 2016, pp 241-253 from Springer

Abstract: Abstract Solvent molecules play a crucial role in the function of proteins. The solvent flux method (SFM) was developed to comprehensively characterize the influx of solvent molecules from the solvent environment into the active site of a protein by molecular dynamics simulations. This was achieved by introducing a solvent concentration gradient and by reorienting and rescaling the velocity vector of all solvent molecules contained within a spherical volume enclosing the protein, thus inducing an accelerated solvent influx toward the active site. In addition to the detection of solvent access pathway within the protein structure, it is hereby possible to identify potential amino acid positions relevant to solvent-related enzyme engineering with high statistical significance. The method is particularly aimed at improving the reverse hydrolysis reaction rates in nonaqueous media. Candida antarctica lipase B (CALB) binds to a triglyceride-water interface with its substrate entrance channel oriented toward the hydrophobic substrate interface. The lipase-triglyceride-water system served as a model system for SFM to evaluate the influx of water molecules to the active site. As a proof of principle for SFM, a previously known water access pathway in CALB was identified as the primary water channel. In addition, a secondary water channel and two pathways for water access which contribute to water leakage between the protein and the triglyceride-water interface were identified.

Keywords: Access Pathway; Candida Antarctica Lipase; Triglyceride Molecule; Active Site Cavity; Substrate Channel (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-24633-8_16

Ordering information: This item can be ordered from
http://www.springer.com/9783319246338

DOI: 10.1007/978-3-319-24633-8_16

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().