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

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.