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Multiscale Estimation of Binding Kinetics Using Brownian Dynamics, Molecular Dynamics and Milestoning.

ABSTRACT: The kinetic rate constants of binding were estimated for four biochemically relevant molecular systems by a method that uses milestoning theory to combine Brownian dynamics simulations with more detailed molecular dynamics simulations. The rate constants found using this method agreed well with experimentally and theoretically obtained values. We predicted the association rate of a small charged molecule toward both a charged and an uncharged spherical receptor and verified the estimated value with Smoluchowski theory. We also calculated the kon rate constant for superoxide dismutase with its natural substrate, O2-, in a validation of a previous experiment using similar methods but with a number of important improvements. We also calculated the kon for a new system: the N-terminal domain of Troponin C with its natural substrate Ca2+. The kon calculated for the latter two systems closely resemble experimentally obtained values. This novel multiscale approach is computationally cheaper and more parallelizable when compared to other methods of similar accuracy. We anticipate that this methodology will be useful for predicting kinetic rate constants and for understanding the process of binding between a small molecule and a protein receptor.

SUBMITTER: Votapka LW

PROVIDER: S-EPMC4624728 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Multiscale Estimation of Binding Kinetics Using Brownian Dynamics, Molecular Dynamics and Milestoning.

Votapka Lane W LW Amaro Rommie E RE

PLoS computational biology 20151027 10

The kinetic rate constants of binding were estimated for four biochemically relevant molecular systems by a method that uses milestoning theory to combine Brownian dynamics simulations with more detailed molecular dynamics simulations. The rate constants found using this method agreed well with experimentally and theoretically obtained values. We predicted the association rate of a small charged molecule toward both a charged and an uncharged spherical receptor and verified the estimated value w ...[more]

PMID: 26505480

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Project description:The flavoenzyme monomeric sarcosine oxidase (MSOX) catalyzes a complex set of reactions currently lacking a consensus mechanism. A key question that arises in weighing competing mechanistic models of MSOX function is to what extent ingress of O2 from the solvent (and its egress after an unsuccessful oxidation attempt) limits the overall catalytic rate. To address this question, we have applied to the MSOX/O2 system the relatively new simulation method of Markovian milestoning molecular dynamics simulations, which, as we recently showed [ Yu et al. J. Am. Chem. Soc. 2015 , 137 , 3041 ], accurately predicted the entry and exit kinetics of CO in myoglobin. We show that the mechanism of O2 entry and exit, in terms of which possible solvent-to-active-site channels contribute to the flow of O2, is sensitive to the presence of the substrate-mimicking competitive inhibitor 2-furoate in the substrate site. The second-order O2 entry rate constants were computed to be 8.1 × 10(6) and 3.1 × 10(6) M(-1) s(-1) for bound and apo MSOX, respectively, both of which moderately exceed the experimentally determined second-order rate constant of (2.83 ± 0.07) × 10(5) M(-1) s(-1) for flavin oxidation by O2 in MSOX. This suggests that the rate of flavin oxidation by O2 is likely not strongly limited by diffusion from the solvent to the active site. The first-order exit rate constants were computed to be 10(7) s(-1) and 7.2 × 10(6) s(-1) for the apo and bound states, respectively. The predicted faster entry and slower exit of O2 for the bound state indicate a longer residence time within MSOX, increasing the likelihood of collisions with the flavin isoalloxazine ring, a step required for reduction of molecular O2 and subsequent reoxidation of the flavin. This is also indirectly supported by previous experimental evidence favoring the so-called modified ping-pong mechanism, the distinguishing feature of which is an intermediate complex involving O2, the flavin, and the oxidized substrate simultaneously in the cavity. These findings demonstrate the utility of the Markovian milestoning approach in contributing new understanding of complicated enyzmatic function.

Project description:Network representations are becoming increasingly popular for analyzing kinetic data from techniques like Milestoning, Markov State Models, and Transition Path Theory. Mapping continuous phase space trajectories into a relatively small number of discrete states helps in visualization of the data and in dissecting complex dynamics to concrete mechanisms. However, not only are molecular networks derived from molecular dynamics simulations growing in number, they are also getting increasingly complex, owing partly to the growth in computer power that allows us to generate longer and better converged trajectories. The increased complexity of the networks makes simple interpretation and qualitative insight of the molecular systems more difficult to achieve. In this paper, we focus on various network representations of kinetic data and algorithms to identify important edges and pathways in these networks. The kinetic data can be local and partial (such as the value of rate coefficients between states) or an exact solution to kinetic equations for the entire system (such as the stationary flux between vertices). In particular, we focus on the Milestoning method that provides fluxes as the main output. We proposed Global Maximum Weight Pathways as a useful tool for analyzing molecular mechanism in Milestoning networks. A closely related definition was made in the context of Transition Path Theory. We consider three algorithms to find Global Maximum Weight Pathways: Recursive Dijkstra's, Edge-Elimination, and Edge-List Bisection. The asymptotic efficiency of the algorithms is analyzed and numerical tests on finite networks show that Edge-List Bisection and Recursive Dijkstra's algorithms are most efficient for sparse and dense networks, respectively. Pathways are illustrated for two examples: helix unfolding and membrane permeation. Finally, we illustrate that networks based on local kinetic information can lead to incorrect interpretation of molecular mechanisms.

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Multiscale Estimation of Binding Kinetics Using Brownian Dynamics, Molecular Dynamics and Milestoning.

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Multiscale Estimation of Binding Kinetics Using Brownian Dynamics, Molecular Dynamics and Milestoning.

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