Disentangling polydispersity in the PCNA−p15PAF complex, a disordered, transient and multivalent macromolecular assembly

Abstract

The intrinsically disordered p15PAF regulates DNA replication and repair when interacting with the Proliferating Cell Nuclear Antigen (PCNA) sliding clamp. As many interactions between disordered proteins and globular partners involved in signaling and regulation, the complex between p15PAF and trimeric PCNA is of low affinity, forming a transient complex that is difficult to characterize at a structural level due to its inherent polydispersity. We have determined the structure, conformational fluctuations, and relative population of the five species that coexist in solution by combining small-angle X-ray scattering (SAXS) with molecular modelling. By using explicit ensemble descriptions for the individual species, built using integrative approaches and molecular dynamics (MD) simulations, we collectively interpreted multiple SAXS profiles as population-weighted thermodynamic mixtures. The analysis demonstrates that the N-terminus of p15PAF penetrates the PCNA ring and emerges on the back face. This observation substantiates the role of p15PAF as a drag regulating PCNA processivity during DNA repair. Our study reveals the power of ensemble-based approaches to decode structural, dynamic, and thermodynamic information from SAXS data. This strategy paves the way for deciphering the structural bases of flexible, transient and multivalent macromolecular assemblies involved in pivotal biological processes.

How to learn from inconsistencies: Integrating molecular simulations with experimental data

“…Experiments are employed to characterise thermodynamic and kinetic quantities of the system under study and simulations aid the interpretation of or complement these results thanks to their high spatial and time resolutions. However, technological [17][18][19][20] and theoretical [3,21] advancements in the field of molecular mechanics have highlighted the existence of discrepancies between simulations and experiments [11][12][13][14][15][16]. In this review, we have approached this issue through a specific perspective: inconsistencies between computational and experimental results carry information that can be systematically extracted and exploited to improve our understanding of biochemical entities and more general biophysical models.…”

“…Fitting data tightly to gain full consistency by imposing constraints might, however, be unrealistic and lead to overfitting because of errors in the data and in the model [33]. Indeed, experimental observables are only known with some limited certainty and, likewise, forward models used to calculate observables from simulations have an associated uncertainty [16]. Systematic errors in the data lead to further disagreement with the model [22,37,38], and finally, the finite number of structures N used to compute the theoretical observable (see Eq.…”

“…NMR chemical shifts, where σ exp σ model . SAXS forward models share similar problems [16], while sometimes the source of the model inaccuracy might come from neglecting an intrinsic time-dependency of the observable (e.g. spin diffusion or dynamic effects in the estimation of NOEs [132]).…”

“…As simulations are in essence a theoretical framework, experimental verification is pivotal and there are still, in many cases, significant differences between experimental data and the corresponding observables calculated from state-ofthe art simulations [10]. These discrepancies are usually due to imperfect force fields [11][12][13][14], insufficient sampling [15] or inaccurate forward models [16]. Even with accurate forward models and robust sampling, however, the quality of the simulation results are bound by the accuracy of the underlying force field [13].…”

Structure-based screening of binding affinities via small-angle X-ray scattering

“…The precision is such that SAXS can track subtle changes regardless of whether the biomolecules are composed of well-folded domains (11,12) or disordered chains. (13,14) This capability has been leveraged to conduct titrations of diverse biomolecular systems: proteins, (15)(16)(17)(18)(19)(20) nucleic acids, (21,22) detergents, (23,24) and others, in order to expose possible structural mechanisms that underlie their functional behavior.…”