Functional Significance of Hierarchical Tiers in Carbonmonoxy Myoglobin:  Conformational Substates and Transitions Studied by Conformational Flooding Simulations

Abstract

The functional importance of large-scale motions and transitions of carbonmonoxy myoglobin (MbCO) conformational substates (CSs) has been studied by molecular dynamics (MD) and conformational flooding (CF) simulations. A flooding potential was constructed from an 800 ps MD trajectory of solvated MbCO to accelerate slower protein motions beyond the time scale of contemporary simulations. Two conformational transitions (tier-1 substates) resulting from seven principal molecular motions were assigned to the spectroscopic A 0 state (tier-0 substate) of MbCO, where His64 is solvated and not within the hydrophobic pocket binding site. The first computed conformational transition involves a distal pocket gate defined by the C and D helices and the interconnecting CD loop (residues 40-55). The gate-like motion is interpreted to regulate ligand access from the distal side of the heme. Simultaneously, a proximal pocket lever involving the F helix and surrounding EF and FG loops (residues 82-105) is found to shuttle the heme deep into the protein matrix (heme rmsd of 3.9 Å) as the distal pocket gate opened. The lever's effect on the heme motion is assumed to attract ligands into the heme pocket. The second major transition involves the compression and expansion of the cavity formed by the EF loop (residues 77-84) and the GH loop and H helix (residues 122-138). The motion is interpreted to modulate the hydrophobic pocket volume and regulate the ligand access from the proximal side of the heme. A third computed conformational transition was found to be a combination of the previous motions. For the first time, CF was applied in a series of room temperature simulations to accelerate molecular motions of the MbCO native fold and define the lower tier hierarchy of substate structure. The computed CSs and associated transitions coincide with previously suggested putative ligand escape pathways, and support a hierarchical description of protein dynamics and structure. A unified model that utilizes both mechanisms of distal His64 modulation (tier-0) and protein equilibrium fluctuations (tier-1) is presented to explain ligand diffusion in the MbCO dissociation reaction.

Combining docking and molecular dynamic simulations in drug design

“…Thermal heating of selected components of the system can also be used to selectively enhance the sampling of certain regions, while the barriers separating local minima can be lowered using the local elevation approach 175 or the conformational flooding technique. 176 These approaches, although faster than conventional MD simulations, are still much slower than typical docking techniques and could not be applied to more than a few examples. We review published studies below.…”

Sampling Conformation Space to Model Equilibrium Fluctuations in Proteins

“…Hence they also spend considerable time sampling rare events such as crossing maxima in the energy landscape. Extensions to enhance sampling include methods such as importance [38] and umbrella sampling [39], replica Monte Carlo [40], jump walking [41], multicanonical ensemble [42], entropic sampling [43], weighted histograms [44], local elevation [45], parallel tempering/replica exchange [46], smart walking [47], multicanonical jump walking [48], conformational flooding [49], local energy flattening [50], activation relaxation [51], Markov state models [52], and guided simulation techniques [53]- [55] that use experimental measurements to guide trajectories to relevant regions of conformation space.…”

Vibrational Dephasing of Carbonmonoxy Myoglobin

“…Myoglobin is a standard for the study, in the laboratory [19][20][21] and on the computer, [22][23][24][25][26] of relationships among protein structure, function, and dynamics. Fayer and co-workers [5][6][7][8][9][10] have performed vibrational echo studies on the dephasing of the CO vibration in carbonmonoxy myoglobin, MbCO, and have established the dependence of this dephasing rate on temperature, solvent viscosity, and mutations.…”