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      Connecting Coil-to-Globule Transitions to Full Phase Diagrams for Intrinsically Disordered Proteins

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          Abstract

          Phase separation is thought to underlie spatial and temporal organization that is required for controlling biochemical reactions in cells. Multivalence of interaction motifs, also known as stickers, is a defining feature of proteins that drive phase separation. Intrinsically disordered proteins with stickers uniformly distributed along the linear sequence can serve as scaffold molecules that drive phase separation. The sequence-intrinsic contributions of disordered proteins to phase separation can be discerned by computing or measuring sequence-specific phase diagrams. These help to delineate the combinations of protein concentration and a suitable control parameter, such as temperature, that support phase separation. Here, we present an approach that combines detailed simulations with a numerical adaptation of an analytical Gaussian cluster theory to enable the calculation of sequence-specific phase diagrams. Our approach leverages the known equivalence between the driving forces for single-chain collapse in dilute solutions and the driving forces for phase separation in concentrated solutions. We demonstrate the application of the theory-aided computations through calculation of phase diagrams for a set of archetypal intrinsically disordered low-complexity domains. We also leverage theories to compute sequence-specific percolation lines and thereby provide a thermodynamic framework for hardening transitions that have been observed for many biomolecular condensates.

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          Valence and patterning of aromatic residues determine the phase behavior of prion-like domains

          Prion-like domains (PLDs) can drive liquid-liquid phase separation (LLPS) in cells. Using an integrative biophysical approach that includes nuclear magnetic resonance spectroscopy, small-angle x-ray scattering, and multiscale simulations, we have uncovered sequence features that determine the overall phase behavior of PLDs. We show that the numbers (valence) of aromatic residues in PLDs determine the extent of temperature-dependent compaction of individual molecules in dilute solutions. The valence of aromatic residues also determines full binodals that quantify concentrations of PLDs within coexisting dilute and dense phases as a function of temperature. We also show that uniform patterning of aromatic residues is a sequence feature that promotes LLPS while inhibiting aggregation. Our findings lead to the development of a numerical stickers-and-spacers model that enables predictions of full binodals of PLDs from their sequences.
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            Free Energy of a Nonuniform System. I. Interfacial Free Energy

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              Conformations of intrinsically disordered proteins are influenced by linear sequence distributions of oppositely charged residues.

              The functions of intrinsically disordered proteins (IDPs) are governed by relationships between information encoded in their amino acid sequences and the ensembles of conformations that they sample as autonomous units. Most IDPs are polyampholytes, with sequences that include both positively and negatively charged residues. Accordingly, we focus here on the sequence-ensemble relationships of polyampholytic IDPs. The fraction of charged residues discriminates between weak and strong polyampholytes. Using atomistic simulations, we show that weak polyampholytes form globules, whereas the conformational preferences of strong polyampholytes are determined by a combination of fraction of charged residues values and the linear sequence distributions of oppositely charged residues. We quantify the latter using a patterning parameter κ that lies between zero and one. The value of κ is low for well-mixed sequences, and in these sequences, intrachain electrostatic repulsions and attractions are counterbalanced, leading to the unmasking of preferences for conformations that resemble either self-avoiding random walks or generic Flory random coils. Segregation of oppositely charged residues within linear sequences leads to high κ-values and preferences for hairpin-like conformations caused by long-range electrostatic attractions induced by conformational fluctuations. We propose a scaling theory to explain the sequence-encoded conformational properties of strong polyampholytes. We show that naturally occurring strong polyampholytes have low κ-values, and this feature implies a selection for random coil ensembles. The design of sequences with different κ-values demonstrably alters the conformational preferences of polyampholytic IDPs, and this ability could become a useful tool for enabling direct inquiries into connections between sequence-ensemble relationships and functions of IDPs.
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                Author and article information

                Contributors
                Journal
                Biophys J
                Biophys J
                Biophysical Journal
                The Biophysical Society
                0006-3495
                1542-0086
                23 June 2020
                21 July 2020
                23 June 2020
                : 119
                : 2
                : 402-418
                Affiliations
                [1 ]Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri
                [2 ]Center for Science & Engineering of Living Systems, Washington University in St. Louis, St. Louis, Missouri
                [3 ]Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri
                [4 ]Department of Biomedical Engineering, Duke University, Durham, North Carolina
                [5 ]Department of Structural Biology, St. Jude Children’s Research Hospital, Memphis, Tennessee
                Author notes
                []Corresponding author pappu@ 123456wustl.edu
                Article
                S0006-3495(20)30488-4
                10.1016/j.bpj.2020.06.014
                7376131
                32619404
                46063994-70a6-4f43-92b4-f70525c1992d
                © 2020 Biophysical Society.

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 13 May 2020
                : 11 June 2020
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                Biophysics
                Biophysics

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