Building Biological Relevance Into Integrative Modelling of Macromolecular Assemblies

Abstract

Recent advances in structural biophysics and integrative modelling methods now allow us to decipher the structures of large macromolecular assemblies. Understanding the dynamics and mechanisms involved in their biological function requires rigorous integration of all available data. We have developed a complete modelling pipeline that includes analyses to extract biologically significant information by consistently combining automated and interactive human-guided steps. We illustrate this idea with two examples. First, we describe the ryanodine receptor, an ion channel that controls ion flux across the cell membrane through transitions between open and closed states. The conformational changes associated with the transitions are small compared to the considerable system size of the receptor; it is challenging to consistently track these states with the available cryo-EM structures. The second example involves homologous recombination, in which long filaments of a recombinase protein and DNA catalyse the exchange of homologous DNA strands to reliably repair DNA double-strand breaks. The nucleoprotein filament reaction intermediates in this process are short-lived and heterogeneous, making their structures particularly elusive. The pipeline we describe, which incorporates experimental and theoretical knowledge combined with state-of-the-art interactive and immersive modelling tools, can help overcome these challenges. In both examples, we point to new insights into biological processes that arise from such interdisciplinary approaches.

Modeling the Homologous Recombination Process: Methods, Successes and Challenges

“…When addressing macromolecular complexes at the atomic level, the most robust method is molecular dynamics (MD) simulation [37][38][39][40][41]. It is built on force fields that were optimized over decades (see for example [27,42]) to the point where simulations are now routinely used to fill spatial or temporal gaps in experimental information [22,26]. The principle is to compute forces on each atom resulting from its interactions with the rest of the system, to let the atoms change their position in response to the forces using Newton's equations of motion during very short time steps (femtoseconds) and to reiterate the process.…”

“…The simulations also resulted in the stabilization of the kink in 3 of the exchanged base pairs in an orientation strikingly similar to that found in DNA in complex with polymerases (PDB ID 4IRC [123]). This similarity served as a basis to model the association of DinB DNA polymerase with the RecA filament, described below [22,124].…”

“…Structural snapshots by themselves are not sufficient to inform about the details of dynamic steps. Their interpretation needs to integrate a wide range of published observations, including modeling studies [22,127,128]. Cryo-EM and modeling approaches, both prone to biases (the modeling possible biases were described in part 1, the Cryo-EM potential biases reside in the need to stabilize dynamic structure intermediates), provide complementary information that is beneficial to integrate.…”

“…A model of DinB bound to both the RecA units and the three DNA strands resulting from strand exchange was proposed based on the crystal structure of the free DinB-DNA complex, and a model of post-synaptic nucleofilament resulting from the Yang et al simulation [87]. Coarse grained interactive simulation was used in order to accommodate the very crowded environment of the filament deep groove to the polymerase, while keeping the polymerase structure and its interactions with the DNA strands mainly unchanged [22,124]. The resulting model shows a flexible L2 loop deeply buried in the catalytic cleft of the polymerase [22], providing a structural interpretation to puzzling previous experimental observations on DinB association with isolated RecA proteins that had identified patches of catalytic cleft residues among the strongly interacting regions [5].…”

“…We report gained knowledge, success stories and pending challenges. Finally, we argue how the specificity of the HR nucleoprotein filaments as mechanically driven molecular assemblies [21,22] explains why fundamental structural information could be revealed as far as 30 years ago using low-resolution methods and why modeling can still be expected to provide keys for the comprehension of the system.…”