Modeling the Structure and Interactions of Intrinsically Disordered Peptides with Multiple Replica, Metadynamics-Based Sampling Methods and Force-Field Combinations

Abstract

Intrinsically disordered proteins play a key role in many biological processes, including the formation of biomolecular condensates within cells. A detailed characterization of their configurational ensemble and structure–function paradigm is crucial for understanding their biological activity and for exploiting them as building blocks in material sciences. In this work, we incorporate bias-exchange metadynamics and parallel-tempering well-tempered metadynamics with CHARMM36m and CHARMM22* to explore the structural and thermodynamic characteristics of a short archetypal disordered sequence derived from a DEAD-box protein. The conformational landscapes emerging from our simulations are largely congruent across methods and force fields. Nevertheless, differences in fine details emerge from varying combinations of force-fields and sampling methods. For this protein, our analysis identifies features that help to explain the low propensity of this sequence to undergo self-association in vitro, which are common to all force-field/sampling method combinations. Overall, our work demonstrates the importance of using multiple force-field and sampling method combinations for accurate structural and thermodynamic information in the study of disordered proteins.

Salt-Induced Transitions in the Conformational Ensembles of Intrinsically Disordered Proteins

“…Computer simulations complement experiments and theory and are playing an important role in elucidating the behavior of IDPs. Simulations were pivotal in understanding the IDPs conformational ensembles and dynamics. − ,− Computer simulations using atomistic force fields matching the appropriate length and time scales of the biophysical phenomena have the advantage of providing detailed information about the biophysical processes. − However, the main drawbacks are the lack of reliable all-atom force fields to simulate the Hofmeister effect of salts, and it is computationally intensive to simulate large IDPs to obtain conformations representative of the equilibrium ensembles.…”

Myofilament-associated proteins with intrinsic disorder (MAPIDs) and their resolution by computational modeling

“…These categories of enhanced sampling techniques can be combined to improve predictions of an IDR ensemble. For example, in Li et al (2022) , replica-exchange and metadynamics were combined to reveal ensemble properties of a 46 amino acid IDR derived from the DEAD-box protein DHH1. By using the advanced sampling techniques, the authors determined the free energy landscape as a function of secondary structure content and determined that the IDP has a low propensity for self-aggregation ( Li et al, 2022 ).…”

“…For example, in Li et al (2022) , replica-exchange and metadynamics were combined to reveal ensemble properties of a 46 amino acid IDR derived from the DEAD-box protein DHH1. By using the advanced sampling techniques, the authors determined the free energy landscape as a function of secondary structure content and determined that the IDP has a low propensity for self-aggregation ( Li et al, 2022 ). Lastly, while most of these strategies have been developed for explicit, AAMD simulations, in principle they can be adapted to any number of molecular simulation approaches.…”

Protein compactness and interaction valency define the architecture of a biomolecular condensate across scales

“…Such simulations have also been combined with coarse-grained approaches and experiments ( Zheng et al, 2020 ) and have provided a detailed view of the key interactions behind protein condensate formation ( Conicella et al, 2020 ; Murthy et al, 2019 ; Ryan et al, 2018 ). Despite these important advances, however, the study of biomolecular condensates at the atomistic resolution is still at its beginning and many questions related to their most generalizable features are only starting to be addressed ( Conicella et al, 2020 ; Li et al, 2022 ; Murthy et al, 2019 ; Ryan et al, 2018 ). These, in particular, concern the complex interplay between structure, dynamics, and thermodynamics of biomolecules in crowded environments.…”