Prediction and simulation of motion in pairs of transmembrane alpha-helices

Encoding molecular motions in voxel maps

This paper builds on the combination of robotic path planning algorithms and molecular modeling methods for computing large-amplitude molecular motions, and introduces voxel maps as a computational tool to encode and to represent such motions. We investigate several applications and show results that illustrate the interest of such representation.

Simulating ligand-induced conformational changes in proteins using a mechanical disassembly method

Simulating protein conformational changes induced or required by the internal diffusion of a ligand is important for the understanding of their interaction mechanisms. Such simulations are challenging for currently available computational methods. In this paper, the problem is formulated as a mechanical disassembly problem where the protein and the ligand are modeled like articulated mechanisms, and an efficient method for computing molecular disassembly paths is described. The method extends recent techniques developed in the framework of robot motion planning. Results illustrating the capacities of the approach are presented on two biologically interesting systems involving ligand-induced conformational changes: lactose permease (LacY), and the beta(2)-adrenergic receptor.

Interaction and conformational dynamics of membrane-spanning protein helices

Within 1 or 2 decades, the reputation of membrane-spanning alpha-helices has changed dramatically. Once mostly regarded as dull membrane anchors, transmembrane domains are now recognized as major instigators of protein-protein interaction. These interactions may be of exquisite specificity in mediating assembly of stable membrane protein complexes from cognate subunits. Further, they can be reversible and regulatable by external factors to allow for dynamic changes of protein conformation in biological function. Finally, these helices are increasingly regarded as dynamic domains. These domains can move relative to each other in different functional protein conformations. In addition, small-scale backbone fluctuations may affect their function and their impact on surrounding lipid shells. Elucidating the ways by which these intricate structural features are encoded by the amino acid sequences will be a fascinating subject of research for years to come.

Rapid sampling of molecular motions with prior information constraints

Proteins are active, flexible machines that perform a range of different functions. Innovative experimental approaches may now provide limited partial information about conformational changes along motion pathways of proteins. There is therefore a need for computational approaches that can efficiently incorporate prior information into motion prediction schemes. In this paper, we present PathRover, a general setup designed for the integration of prior information into the motion planning algorithm of rapidly exploring random trees (RRT). Each suggested motion pathway comprises a sequence of low-energy clash-free conformations that satisfy an arbitrary number of prior information constraints. These constraints can be derived from experimental data or from expert intuition about the motion. The incorporation of prior information is very straightforward and significantly narrows down the vast search in the typically high-dimensional conformational space, leading to dramatic reduction in running time. To allow the use of state-of-the-art energy functions and conformational sampling, we have integrated this framework into Rosetta, an accurate protocol for diverse types of structural modeling. The suggested framework can serve as an effective complementary tool for molecular dynamics, Normal Mode Analysis, and other prevalent techniques for predicting motion in proteins. We applied our framework to three different model systems. We show that a limited set of experimentally motivated constraints may effectively bias the simulations toward diverse predicates in an outright fashion, from distance constraints to enforcement of loop closure. In particular, our analysis sheds light on mechanisms of protein domain swapping and on the role of different residues in the motion.

Generation, comparison, and merging of pathways between protein conformations: gating in K-channels

We present a general framework for the generation, alignment, comparison, and hybridization of motion pathways between two known protein conformations. The framework, which is rooted in probabilistic motion-planning techniques in robotics, allows for the efficient generation of collision-free motion pathways, while considering a wide range of degrees of freedom involved in the motion. Within the framework, we provide the means to hybridize pathways, thus producing, the motion pathway of the lowest energy barrier out of the many pathways proposed by our algorithm. This method for comparing and hybridizing pathways is modular, and may be used within the context of molecular dynamics and Monte Carlo simulations. The framework was implemented within the Rosetta software suite, where the protein is represented in atomic detail. The K-channels switch between open and closed conformations, and we used the overall framework to investigate this transition. Our analysis suggests that channel-opening may follow a three-phase pathway. First, the channel unlocks itself from the closed state; second, it opens; and third, it locks itself in the open conformation. A movie that depicts the proposed pathway is available in the Supplementary Material (Movie S1) and at http://www.cs.tau.ac.il/~angela/SuppKcsA.html.

An NMA-guided path planning approach for computing large-amplitude conformational changes in proteins

This paper presents a new method for computing macromolecular motions based on the combination of path planning algorithms, originating from robotics research, and elastic network normal mode analysis. The low-frequency normal modes are regarded as the collective degrees of freedom of the molecule. Geometric path planning algorithms are used to explore these collective degrees of freedom in order to find possible large-amplitude conformational changes. To overcome the limits of the harmonic approximation, which is valid in the vicinity of the minimum energy structure, and to get larger conformational changes, normal mode calculations are iterated during the exploration. Initial results show the efficiency of our method, which requires a small number of normal mode calculations to compute large-amplitude conformational transitions in proteins. A detailed analysis is presented for the computed transition between the open and closed structures of adenylate kinase. This transition, important for its biological function, involves large-amplitude domain motions. The obtained motion correlates well with results presented in related works.