(190ah) Molecular and Coarse-Grained Analysis of Flap Motion In Lipase Enzymes

Lipase enzymes are a common component of
most pathways for metabolizing lipids. They catalyze the breakdown of large
lipid structures by means of hydrolyzing ester bonds.  Their importance in this role explains
why human lipases have been implicated in a variety of health conditions,
including heart disease and diabetes. Industrial utilization of lipases
(purified from various microorganisms) has predominantly been for food
production and in detergents, yet in the past decade for the production of
biodiesel and other sustainable fuels from plant-derived substrates.

Despite their importance in both
technological application and human health, little is known about the dynamics
of lipases at the atomic level. Previous experimental investigations have shown
a common structural motif among lipases is a flap-like domain that protects the
active site from the solvent until in the enzyme contacts a solvent-lipid
interface. The C. rugosa
lipase (CRL) structure has been resolved for both the flap-open and flap-closed
states. The two states have almost identical structure, except for the 26
amino-acid flap, which differs by 17 Angstrom between
the open and closed states. This similarity has led to the conclusion that the
flap-opening mechanism is a hinge-like motion.  Given the importance of this
conformational change in regulating lipase activity, the molecular details of the
flap mechanism are essential knowledge for engineering improved lipases.  However, direct observation of this process
is difficult or impossible via experiment alone.  Therefore, we have used molecular and
coarse-grained simulations to investigate the behavior of CRL in explicit
water.  The major challenge of using
classical MD in investigating conformational rearrangement and rare events
(e.g., flap opening/closing) lies in sufficient sampling.  As we demonstrate, even microsecond-long
simulations of the all-atom (AA) system cannot provide enough sampling to
calculate the equilibrium probability distribution of this process. We use the
AA simulation trajectories to develop coarse-grain (CG) models based on the
recently developed ED-CG [1] method. 
The ED-CG models help identify dynamically similar domains within the
open and closed states.  Finally, we
use the metadynamics [2] algorithm to calculate the free-energy landscape and
identify key structural transitions in the opening and closing process.

[1] Z. Zhang, L. Lu, W.G. Noid, V. Krishna, J. Pfaendtner,
and G.A. Voth (2008). "A Systematic Methodology for
Defining Course-Grained Sites in Large Biomolecules." Biophysical Journal
95: 5073-5083.

[2] A. Laio and M. Parrinello
(2002). "Escaping free-energy minima." PNAS 99(20): 12562-12566.