High resolution ensemble description of metamorphic and intrinsically disordered proteins using an efficient hybrid parallel tempering scheme

Abstract

Running title: Conformational sampling of proteins with funneled, multi-funneled and weakly multi-funneled free-energy landscapes Keywords: Intrinsically disordered proteins | metamorphic proteins | conformational ensemble | integrative modeling | parallel tempering Author Contributions: AR and AS conceived and designed the research; AR performed research; JN provided computational resources; AR, JN, and AS analyzed data; and AR and AS wrote the paper * Corresponding author: Anand Srivastava, anand@iisc.ac.in Abstract: Determining the conformational ensemble for proteins with multi-funneled complex free-energy landscapes is often not possible with classical structure-biology methods that produce time and ensemble averaged data. With vastly improved force fields and advances in rare-event sampling methods, molecular dynamics (MD) simulations offer a complementary approach towards determining the collection of 3-dimensional structures that proteins can adopt. However, in general, MD simulations need to either impose restraints or reweigh the generated data to match experiments. The limitations extend beyond systems with high free-energy barriers as is the case with metamorphic proteins such as RFA-H. The predicted structures in even weakly-funneled intrinsically disordered proteins (IDPs) such as Histatin-5 (His-5) are too compact relative to experiments. Here, we employ a new computationally-efficient parallel-tempering based advanced-sampling method applicable across proteins with extremely diverse free-energy landscapes. And we show that the calculated ensemble averages match reasonably well with the NMR, SAXS and other biophysical experiments without the need to reweigh. We benchmark our method against standard model systems such as alanine di-peptide, TRP-cage and β-hairpin and demonstrate significant enhancement in the sampling efficiency. The method successfully scales to large metamorphic proteins such as RFA-H and to highly disordered IDPs such as His-5 and produces experimentally-consistent ensemble. By allowing accurate sampling across diverse landscapes, the method enables for ensemble conformational sampling of deep multi-funneled metamorphic proteins as well as highly flexible IDPs with shallow multi-funneled free-energy landscape.Significance/Authors' Summary: Generating high-resolution ensemble of intrinsically disordered proteins, particularly the highly flexible ones with high-charge and low-hydrophobicity and with shallow multi-funneled free-energy landscape, is a daunting task and often not possible since information from biophysical experiments provide time and ensemble average data at low resolutions. At the other end of the spectrum are the metamorphic proteins with multiple deep funnels and elucidating the structures of the transition intermediates between the fold topologies is a non-trivial exercise. In this work, we propose a new parallel-tempering based advancedsampling method where the Hamiltonian is designed to allow faster decay of water orientation dynamics, which in turn facilitates...

Towards Convergence in Folding Simulations of RNA Tetraloops: Comparison of Enhanced Sampling Techniques and Effects of Force Field Corrections

“…As noted in the Introduction, efficiency of the RE methods is still a matter of debate. 14,[17][18][19][20][64][65][66][67][68] The sampling efficacy for a given system can be affected also by roughness of the free energy surface in a given ff.…”

“…While enhanced sampling methods work well for the simplest model systems their efficacy for more complex molecules is often a matter of debate and may vary in a systemmethod-specific manner. 8,[13][14][15][16][17][18] Another fundamental factor determining the usability of the MD technique to study RNA structural dynamics is the quality of the employed empirical potentials (force fields, ffs). MD simulations are now routinely used to study dynamics, folding and ligand binding, but the correct description of structure and dynamics of RNA molecules using ffs is more problematic than in the case of proteins.…”

“…However, there have also been many works suggesting that efficiency of these protocols may be highly-system dependent and in extreme cases can lead to no sampling enhancement. 14,[17][18][19][20][64][65][66][67][68] In this work, we address both sampling and ff issues simultaneously. We used massive enhanced sampling methods in order to study the folding of r(gcGAGAgc) and r(gcUUCGgc) 8mer TL sequences.…”

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“…While experimental studies probing the interconversion of the helical and sheet forms of RfaH are lacking, there are a number of computational studies addressing this question using methods such as targeted molecular dynamics [ 84 ], Markov state modelling [ 85 ], replica exchange [ 86 – 88 ] and quasi-continuous interpolation [ 89 ], coarse-grained simulations [ 90 ], dual-basin structure-based models [ 91 ] and pulling simulations [ 92 ]. There is general agreement that interconversion is triggered by the fraying of the N-terminal α-helix.…”

A Predictive Energy Landscape Model of Metamorphic Protein Conformational Specificity

“…To date, the small number of reported metamorphic proteins are only able to be documented because they exhibit simultaneous populations of both folds at equilibrium. Unfortunately, such coupled equilibria, at least for molecules as large as globular proteins, are at or beyond the limits of state-of-the-art all-atom simulations [26][27][28][29]. Moreover, physico-chemical processes are simply ignored in heuristic approaches based on sequence or secondary structure, and recent extraordinary deep-learning success in protein folding does not transfer to metamorphic protein sequences [30].…”