Polymer Properties that Predict Protein Structure Class from the Primary Sequence
Date
2022-12
Authors
Khaodeuanepheng, Nathan
Journal Title
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Abstract
Within cells, membrane-free compartments form spontaneously and reversibly in a
process referred to as “phase separation”. By forming specific compartments and microenvironments, these membraneless organelles, for example, Cajal bodies, the nucleolus,
stress granules, and P-bodies, are used to regulate a myriad of cellular functions via control
of the spatial organization of biological matter and the concomitant modulation of
biochemical reactivity. Proteins have a prominent role driving phase separation and, among
phase-separating (PS) proteins, many have intrinsically disordered regions (IDRs) that are
needed for phase separation to occur. Previous work created a computer algorithm called
ParSe (Partition Sequence) that successfully identifies PS IDRs from the protein primary
sequence starting from predictions of hydrodynamic size, which is indicative of the relative
strength of intramolecular as compared to solvent interactions. The key assumption of
ParSe is that intramolecular cohesion that compacts monomeric proteins is correlated with
intermolecular cohesion that drives phase separation. To assess hydrodynamic size, ParSe
uses a sequence-based model of the polymer scaling exponent, vmodel, that when paired with
a second sequence-based parameter, the intrinsic propensity for a sequence to form β-turns,
can distinguish between sequences belonging to one of three classes of protein regions:
folded, ID, and PS ID. However, the prior study did not test whether the combination of
vmodel and β-turn propensity is unique in its predictive power, as would be required if
hydrodynamic size and turn structures are indeed mechanistically linked to protein phase
separation. Here, it is shown that vmodel and β-turn propensity are not unique in their ability to identify PS IDRs but rather this can be done with similar fidelity using vmodel paired with
a range of different types of conformational propensity scales or hydrophobicity scales.
Thus, structural hypotheses relating to the mechanistic details of protein phase separation
cannot be established based on these results. Moreover, when applying ParSe to verified
globular proteins, we noticed that these proteins often contain short regions that are
incorrectly predicted to be ID. We hypothesize that these predicted short IDRs within
known folded regions represent segments within a folded domain that have low structural
stability. To test this hypothesis, ParSe calculations were compared to hydrogen-deuterium
exchange (HDX) data measured in four folded proteins. Good agreement between the
locations of ParSe-predicted IDRs and regions with low stability as inferred by HDX rates
were found.
Description
Keywords
LLPS, Phase separation, Proteins, Primary sequence prediction
Citation
Khaodeuanepheng, N. (2022). <i>Polymer properties that predict protein structure class from the primary sequence</i> (Unpublished thesis). Texas State University, San Marcos, Texas.