Project Title

Deconstruction of Cellulosic Biomass: Biofuels & Value Added Compounds

PI

Dr. C Mark Maupin

Email

cmmaupin@mines.edu

Department

Chemical & Biological Engineering

Project summary

In this research, we propose to examine the endocellulase's (Cel7B) enzymatic catalysis of cellulose using quantum mechanical (QM) methods in addition to transition path sampling simulations using the multi-state empirical valence bond methodology (MS-EVB). The use of the QM calculations will enable a detailed analysis of the enzyme reaction mechanism and energetics. The MS-EVB methodology, which enables dynamic simulations of reactive processes, in conjunction with the QM calculations will enable the systematic analysis of the overall energetics, both enthalpic and entropic. The MS-EVB simulations coupled to a transition path sampling approach will also probe the influence of dynamical interactions and motions on the catalytic mechanism and rate. Such state of the art simulations enable the investigation of the principles of chemical reactivity for complex homogeneous and heterogeneous catalysis. This is a feat that pushes the spatial and temporal boundaries of computational science.

Two objectives will test the hypothesis that dynamical motions and interactions of the cellulase-cellulose system are essential for efficient catalysis. Completion of these objectives will enable the use of rational design to favorable impact the reaction. The objectives are:

1. Conduct QM and ONIOM hybrid energy method calculations on the endocellulase-cellulose system (Cel7B). These calculations will identify the most energetically favorable reaction mechanism and illuminate vital enzyme-substrate interactions.

2. Create an MS-EVB force field and conduct MS-EVB transition path sampling simulations of the catalytic reaction in the presence and absence of a complete crystalline cellulose microfibril, thereby revealing critical dynamical factors that facilitate catalysis of enzymes acting on solid substrates.

Commercial software

AMBER 12

Gaussian09

Open Source software

None