Information theoretic measures for quantifying sequence-ensemble relationships of intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) contribute to a multitude of functions. De novo design of IDPs should open the door to modulating functions and phenotypes controlled by these systems. Recent design efforts have focused on compositional biases and specific sequence patterns as the design features. Analysis of the impact of these designs on sequence-function relationships indicates that individual sequence/compositional parameters are insufficient for describing sequence-function relationships in IDPs. To remedy this problem, we have developed information theoretic measures for sequence-ensemble relationships (SERs) of IDPs. These measures rely on prior availability of statistically robust conformational ensembles derived from all atom simulations. We show that the measures we have developed are useful for comparing sequence-ensemble relationships even when sequence is poorly conserved. Based on our results, we propose that de novo designs of IDPs, guided by knowledge of their SERs, should provide improved insights into their sequence-ensemble-function relationships

Crystal lattice properties fully determine short-range interaction parameters for alkali and halide ions

Accurate models of alkali and halide ions in aqueous solution are necessary for computer simulations of a broad variety of systems. Previous efforts to develop ion force fields have generally focused on reproducing experimental measurements of aqueous solution properties such as hydration free energies and ion-water distribution functions. This dependency limits transferability of the resulting parameters because of the variety and known limitations of water models. We present a solvent-independent approach to calibrating ion parameters based exclusively on crystal lattice properties. Our procedure relies on minimization of lattice sums to calculate lattice energies and interionic distances instead of equilibrium ensemble simulations of dense fluids. The gain in computational efficiency enables simultaneous optimization of all parameters for Li+, Na+, K+, Rb+, Cs+, F-, Cl-, Br-, and I- subject to constraints that enforce consistency with periodic table trends. We demonstrate the method by presenting lattice-derived parameters for the primitive model and the Lennard-Jones model with Lorentz-Berthelot mixing rules. The resulting parameters successfully reproduce the lattice properties used to derive them and are free from the influence of any water model. To assess the transferability of the Lennard-Jones parameters to aqueous systems, we used them to estimate hydration free energies and found that the results were in quantitative agreement with experimentally measured values. These lattice-derived parameters are applicable in simulations where coupling of ion parameters to a particular solvent model is undesirable. The simplicity and low computational demands of the calibration procedure make it suitable for parametrization of crystallizable ions in a variety of force fields.Comment: 9 pages, 5 table

Amyloids go genomic: insights regarding the sequence determinants of prion formation from genome-wide studies

[Image: see text] The availability of fully sequenced genomes provides a useful starting point for identifying putative amyloid and prion forming sequences through genome-wide scans. With an inventory in hand, one can assess the amyloid forming potential and the functional consequences of amyloid formation for each sequence. Thus, advancing our understanding of how cells process and utilize deleterious and functional aggregates, respectively

RNA-induced conformational switching and clustering of G3BP drive stress granule assembly by condensation

Stressed cells shut down translation, release mRNA molecules from polysomes, and form stress granules (SGs) via a network of interactions that involve G3BP. Here we focus on the mechanistic underpinnings of SG assembly. We show that, under non-stress conditions, G3BP adopts a compact auto-inhibited state stabilized by electrostatic intramolecular interactions between the intrinsically disordered acidic tracts and the positively charged arginine-rich region. Upon release from polysomes, unfolded mRNAs outcompete G3BP auto-inhibitory interactions, engendering a conformational transition that facilitates clustering of G3BP through protein-RNA interactions. Subsequent physical crosslinking of G3BP clusters drives RNA molecules into networked RNA/protein condensates. We show that G3BP condensates impede RNA entanglement and recruit additional client proteins that promote SG maturation or induce a liquid-to-solid transition that may underlie disease. We propose that condensation coupled to conformational rearrangements and heterotypic multivalent interactions may be a general principle underlying RNP granule assembly