Frustration-guided motion planning reveals conformational transitions in proteins

Abstract

Proteins exist as conformational ensembles, exchanging between substates to perform their function. Advances in experimental techniques yield unprecedented access to structural snapshots of their conformational landscape. However, computationally modeling how proteins use collective motions to transition between substates is challenging owing to a rugged landscape and large energy barriers. Here, we present a new, robotics-inspired motion planning procedure called dCC-RRT that navigates the rugged landscape between substates by introducing dynamic, interatomic constraints to modulate frustration. The constraints balance non-native contacts and flexibility, and instantaneously redirect the motion towards sterically favorable conformations. On a test set of eight proteins determined in two conformations separated by, on average, 7.5 Å root mean square deviation (RMSD), our pathways reduced the Cα atom RMSD to the goal conformation by 78%, outperforming peer methods. We then applied dCC-RRT to examine how collective, small-scale motions of four side-chains in the active site of cyclophilin A propagate through the protein. dCC-RRT uncovered a spatially contiguous network of residues linked by steric interactions and collective motion connecting the active site to a recently proposed, non-canonical capsid binding site 25 Å away, rationalizing NMR and multi-temperature crystallography experiments. In all, dCC-RRT can reveal detailed, all-atom molecular mechanisms for small and large amplitude motions. Source code and binaries are freely available at https://github.com/ExcitedStates/KGS/.

Collision‐free poisson motion planning in ultra high‐dimensional molecular conformation spaces

“…In addition to constraints defined by native contacts, such as hydrogen bonds, we designed a new procedure to modulate non‐native contacts by adding 1‐D dynamic clash‐avoiding constraints (dCC). Whenever a perturbation in leads to a prohibitive steric clash between atoms, the conformation cannot be accepted.…”

Driving Protein Conformational Cycles in Physiology and Disease: “Frustrated” Amino Acid Interaction Networks Define Dynamic Energy Landscapes

“…These transient interactions may help further guide the protein through its conformational cycle. [ 94–96 ]…”

Kino‐Geometric Modeling: Insights into Protein Molecular Mechanisms

“…It models dihedral (torsional) angles of rotatable, covalent single bonds as degrees of freedom and non-covalent interactions such as hydrogen bonds or hydrophobics as constraints [1][2][3][4]. It models dihedral (torsional) angles of rotatable, covalent single bonds as degrees of freedom and non-covalent interactions such as hydrogen bonds or hydrophobics as constraints [1][2][3][4].…”

“…Our algorithms are based on a rapidly exploring random tree (RRT [6]) that is guided by the principal of minimal frustration to automatically explore energetically accessible regions of conformation 2 of 2 Section 1: Multi-body dynamics space. 1, bottom left) in a matter of hours [3]. For example, providing the closed form of ADK as a second structural input (Fig.…”

“…Our Kino-Geometric Sampling (KGS) and modeling approach originates in traditional robotics and efficiently captures smalland large-scale collective motions in the molecule. It models dihedral (torsional) angles of rotatable, covalent single bonds as degrees of freedom and non-covalent interactions such as hydrogen bonds or hydrophobics as constraints [1][2][3][4]. Thereby, our model takes advantage of the collective, coordinated motions of dihedral angles that entirely preserve the global constraint network [1], or perturb it only slightly in a hierarchical manner [2].…”