Book of Abstracts: Albany 2011

category image Albany 2011
Conversation 17
June 14-18 2011
©Adenine Press (2010)

Transition Pathways of Enzymes Explored by Combining the Anisotropic Network Model, Molecular Dynamics Simulations and a Monte Carlo Sampling of Conformational Space

The conformational transition between the open and closed forms of Escherichia coli adenylate kinase (AK) is explored using a molecular dynamics (MD) simulation protocol which is guided by the normal modes derived from the coarse grained anisotropic network model (ANM). The methodology applies to the cases where the passage from one substate to another (e.g., the open and closed forms of an enzyme) within a global energy minimum (native state) involves relatively low energy barriers, based on the assumption that low energy barriers may be surmounted/overlooked by adopting a coarse-grained description of the structure and energetics, which smoothes out the energy landscape. The basic approach is to deform the structure along ANM modes, similar to the adaptive ANM (aANM) procedure adopted in our previous work,1 but with the major improvement that the intermediate structures are selected by a Monte Carlo scheme and energy minimized by short MD runs. While the detailed energy landscape may usually comprise multiple microstates and multiple barriers/pathways, the coarse-graining of the transition path between the open and closed forms of AK highlights three substates. In agreement with previous work, the conformational change is undergone in two steps: Closing of the LID (shown in red in Fig.1) region succeeded by that of the nucleotide binding domain (colored orange). Some residues are observed to experience high internal energies during the simulated transition, this highlighting the critical interactions that play a dominant role in destabilizing or stabilizing particular substates.

Support from NIH grants 1R01GM086238-01is gratefully acknowledged by I. Bahar.


  1. Zheng Yang , Peter Májek, Ivet Bahar (2009 Allosteric Transitions of Supramolecular Systems Explored by Network Models: Application to Chaperonin GroEL PLoS Comput Biol 5(4): e1000360.

Mert Gur
Ivet Bahar

Department of Computational and Systems Biology
School of Medicine
University of Pittsburgh
3501 Fifth Ave, Suite 3064 BST3
Pittsburgh, PA 15260 USA

Ph: (412) 648-3333
Fx: (412) 648-3163