Adaptive Accelerated Molecular Dynamics (Ad-AMD) Revealing the Molecular Plasticity of P450cam

Phineus R. L. Markwick, Levi C. T. Pierce, David B. Goodin, J. Andrew McCammon
2011 Journal of Physical Chemistry Letters  
An extended accelerated molecular dynamics (AMD) methodology called adaptive AMD is presented. Adaptive AMD (Ad-AMD) is an efficient and robust conformational space sampling algorithm that is particularly-well suited to proteins with highly structured potential energy surfaces exhibiting complex, large-scale collective conformational transitions. Ad-AMD simulations of substratefree P450cam reveal that this system exists in equilibrium between a fully and partially open conformational state. The
more » ... mechanism for substrate binding depends on the size of the ligand. Larger ligands enter the P450cam binding pocket, and the resulting substrate-bound system is trapped in an open conformation via a population shift mechanism. Small ligands, which fully enter the binding pocket, cause an induced-fit mechanism, resulting in the formation of an energetically stable closed conformational state. These results are corroborated by recent experimental studies and potentially provide detailed insight into the functional dynamics and conformational behavior of the entire cytochrome-P450 superfamily. SECTION Biophysical Chemistry T he function of biomacromolecules is determined by both their 3D structure and dynamics. 1,2 Proteins are inherently flexible systems displaying a broad range of dynamics over a hierarchy of time scales. Many biologically important processes, such as enzyme catalysis, 3 ligand binding, and signal transduction, 4 occur on the microsecondmillisecond time scale. 5 The study of such slow time scale dynamics remains a challenge to experimentalists and theoreticians alike. Despite the sustained and rapid increase in available computational power and the development of efficient simulation algorithms, MD simulations of large proteins and biomachines are generally limited to time scales of tens to hundreds of nanoseconds. Considerable progress has been made in the development of more sophisticated methods to sample the conformational space of proteins more efficiently, 6,7 allowing the study of functionally important slow molecular motions. In general, these methods can be divided into two groups. The first involves the identification of transition pathways between known initial and final states. Such methods include transition path sampling 8 and targeted molecular dynamics. 9 The second group contains those methods that efficiently sample low-energy molecular conformations, allowing the rapid identification of thermodynamically dominant regions on the potential energy surface (PES). These methods include replica exchange MD, 10 meta-dynamics, 11 and accelerated molecular dynamics (AMD). 12 The principle behind AMD is to add a continuous non-negative bias potential to the actual PES, which raises the low-energy regions on the potential energy landscape, decreasing the magnitude of the energy barriers and accelerating the exchange between low-energy conformational states while still maintaining the essential details of the underlying potential energy landscape. One of the favorable characteristics of this method is that it yields a canonical average of an observable, so that thermodynamic and other equilibrium properties can be determined. AMD has already been successfully employed to study slow time scale dynamics in small proteins, such as ubiquitin 13 and IκBR. 14 The enhanced conformational space sampling by AMD in these studies was shown to significantly improve the theoretical prediction of experimental NMR observables, such as residual dipolar couplings, 13,14 scalar J couplings, 13, 15 and chemical shifts 16 that are sensitive to dynamic averaging on the micro-to millisecond time scale. As a robust freeenergy sampling method, AMD has also been successfully combined with molecular modeling approaches to study the conformational behavior of natively unstructured proteins. 17
doi:10.1021/jz101462n pmid:21307966 pmcid:PMC3034398 fatcat:eqot3lu3mrh6dpuaojr66s25mi