Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session K06: Physics of Proteins III: Evolution and Function of Molecular InteractionsFocus Session Recordings Available
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Sponsoring Units: DBIO Chair: Tatjana Skrbic, University of Oregon Room: McCormick Place W-178B |
Tuesday, March 15, 2022 3:00PM - 3:36PM |
K06.00001: Conservative interactions in protein evolution Invited Speaker: Wouter D Hoff Patterns of sequence conservation are widely used in studies of proteins. Protein families, and more recently also protein superfamilies, are characterized by a shared three-dimensional structure and patterns of conservation of amino acid sequence. Obtaining a comprehensive understanding of the factors that drive the conservation of residues at specific positions in a protein is an important challenge in understanding protein structure, function, and evolution. We explore this question in the PAS domain superfamily. PAS domains form a diverse superfamily of signaling proteins defined by a weak but characteristic pattern of sequence conservation. The 9 most strongly PAS-conserved residues are located at structurally inconspicuous positions that remain largely unstudied. Thus, while evolution indicates that these residues are critical, the mechanistic reason for their conservation remains unresolved. Two candidate functions are in PAS domain folding/stability and in allosteric switching for signaling. Our experimental data on photoactive yellow protein argue against a role in allosteric switching or protein stability. However, we observed that mutations at these residues often substantially reduce the degree of protein production. Further analysis revealed conserved residues that affect protein stability and in vivo protein production, indicating that both effects drive evolutionary conservation in PYP, but through two largely distinct sets of residues. Bioinformatics analysis of contact maps in PAS domains revealed conserved networks of interactions, where side chain identity is variable, but a cluster of inter-residue interactions is retained. We propose that such conservative interactions is important for efficient protein production. |
Tuesday, March 15, 2022 3:36PM - 3:48PM |
K06.00002: On the role of multiple states in allostery Eric Rouviere, Olivier Rivoire, Rama Ranganathan Several physical mechanisms have been proposed to explain allostery. They differ by the number of internal states that they assume a protein to occupy, leaving open the question of what controls the emergence of one or several of these states. We study this question by introducing and analyzing a simplified model of protein allostery under a diversity of physical and evolutionary constraints. We find that two archetypal mechanisms can emerge through evolution, depending on the nature of these constraints: a single-state mechanism where ligand binding induces a displacement along a soft normal mode or a multi-state mechanism where ligand binding induces a switch across an energy barrier to a different stable state. Importantly, whenever the two mechanisms are possible, the second confers a stronger allosteric effect and thus a selective advantage. Our results provide an experimentally testable hypothesis for the functional importance of multiple states in proteins. |
Tuesday, March 15, 2022 3:48PM - 4:00PM |
K06.00003: Quantifying protein interactions in a living organism Aniket Ravan, Yann R Chemla, Martin Gruebele In recent years, experiments have shown that weak protein-protein interactions are influenced by enthalpic ('sticking') and entropic ('crowding') effects of their environment. The chaperoning activity of the molecular chaperone Hsp70 and its client Phosphoglycerate Kinase (PGK) lies in the realm of weak protein-protein interactions. In this work, we demonstrate a pipeline to study such protein interactions in different tissues of live zebrafish larvae. Using meganuclease-mediated transformation, we induce mosaic bicistronic expression of fluorescently tagged HspA1A variant of Hsp70 and a low melting point mutant of yeast PGK. We subject anesthetized larvae to a heat shock to induce measurable chaperoning interactions in its transformed cells. Using fluorescence resonance energy transfer (FRET), we detect the onset of binding of the two proteins near the melting temperature of PGK in the larval myocytes. Our experiments aim at quantitatively comparing these interactions in different tissues of the larvae as well as comparing the chaperoning activity of Hsp70 and the constitutively expressed homolog, heat shock cognate protein Hsc70 (HSPA8). |
Tuesday, March 15, 2022 4:00PM - 4:36PM |
K06.00004: Many sequence-diverse protein domains switch between α-helix and β-sheet folds Invited Speaker: Lauren Porter The protein folding paradigm asserts that the three-dimensional structure of a protein is determined by its amino acid sequence. Here we show that a substantial population of proteins from the NusG superfamily of transcription factors do not adhere to this paradigm. Previous work demonstrated that one member of this superfamily has a regulatory domain that completely switches between α-helical and β-sheet folds, but the pervasiveness of this fold-switching mechanism is uncertain. To address this question, we developed a sequence-based predictor, which suggested that thousands of proteins from this superfamily switch folds. Circular dichroism and nuclear magnetic resonance spectroscopies of 10 sequence-diverse variants confirmed our predictions. By contrast, state-of-the-art methods based on the protein folding paradigm assume that related sequences adopt the same fold and thus predicted that the regulatory domains of all variants adopt only one fold, almost always β-sheet. Removal of this bias revealed that residue-residue contacts from both α-helical and β-sheet folds are conserved in a large subpopulation of fold-switching domains, poising them to assume disparate conformations. Our results suggest that fold switching is a pervasive mechanism of transcriptional regulation in all kingdoms of life and indicate that expanding the protein folding paradigm may reveal the involvement of fold-switching proteins in diverse biological processes. |
Tuesday, March 15, 2022 4:36PM - 4:48PM |
K06.00005: Preferential Exclusion and Hydration Dynamics in Compatible Osmolyte Solutions Christina Othon, Nimesh Shukla, Erika Taylor, Brianna Bembenek Compatible osmolytes are a broad class of small organic molecules employed by living systems to combat environmental stress by enhancing native protein structure. The molecular features which make for a superior biopreservation remain elusive. Through use of time resolved and steady state spectroscopic techniques, in combination with molecular simulation, insight into what makes one molecule a more effective compatible osmolyte can be gained. Disaccharides differing only in their glycosodic bonds can exhibit different degrees of stabilization against thermal denaturation. The degree to which each sugar is preferentially excluded may explain these differences. |
Tuesday, March 15, 2022 4:48PM - 5:00PM |
K06.00006: Quantifying Tubulin Heterodimer Assembly in vitro and Cells Yuhan Wang, Mahima Unnikrishnan, Brooke Ramsey, Catherine J Murphy, Martin Gruebele As biophysics researchers delve deeper into biomolecular interaction networks, it becomes clear that many weak, nonspecific, transient interactions play a role in living cells. While extensive studies have been made to characterize strong “on-off” protein interactions in vitro, we are particularly interested in studying the role of the cellular environment on protein weak interactions. Here we present a new method to quantify protein-protein weak interactions in living cells. Our model system used human U2-OS cells as a substrate to determine the binding affinity of tubulin-like proteins BtubA and BtubB from the bacterial genus Prosthecobacter. The binding equilibrium was performed with microinjection and monitored using fluorescence resonance energy transfer. Comparing to in vitro results, we found that the cytoplasm matrix promotes the binding affinity of BtubA/B. The promotion is mainly contributed by macromolecular crowding and non-specific sticking effects in cells. A Monte-Carlo-sampling-based model is also developed to simulate the binding promotion from the cytoplasm matrix and fits our experimental results. |
Tuesday, March 15, 2022 5:00PM - 5:12PM |
K06.00007: Comparison of α-conotoxin free energy landscapes via simulation and dimensionality reduction Ré A Mansbach, Natalya Watson
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Tuesday, March 15, 2022 5:12PM - 5:24PM |
K06.00008: A Superstatistical Variational Model for Categorical Data: Applications to Protein Sequence Variation Hoda Akl, Purushottam Dixit, Xiaochuan Zhao Understanding the constraints on amino acid variation in protein sequences within a protein family is crucial to our understanding of evolutionary and biophysical forces that dictate protein structure and function. Unfortunately, however, available sequences of naturally occuring proteins likely cover only a limited region of the vast space of functionally viable sequences. In order to paint a better picture of what makes an amino acid sequence a functional protein, we need generative models that can sample de novo protein sequences. To that end, we present a variational data-driven model rooted in superstatistics that leverages the pre-existing information present in natural sequences for generative purposes; and thus can sample new protein sequences from the inferred latent space. The generated sequences are significantly different from known sequences in the family but accurately reproduce several lower order statistics (frequencies, correlations, etc.). Moreover, probabilities of point mutations are predictive of fitness effects with predicted high probability mutations corresponding to near-neutral fitness costs. The developed formalism generalizes to other categorical data (neuronal firing, graph edges, etc.) and thus has a wide range of applications. |
Tuesday, March 15, 2022 5:24PM - 5:36PM |
K06.00009: A mechanochemical protein model reveals the principles of molecular discrimination. John M McBride, Tsvi Tlusty, Jean-Pierre Eckmann Proteins need to selectively interact with specific targets among a multitude of similar molecules in the cell. Despite a firm physical understanding of pairwise binding interactions, a general theory that explains how proteins evolve high specificity is still lacking. Here, we present a genetic-mechano-chemical model of evolving protein-ligand interactions which offers a mechanistic understanding of molecular discrimination: More difficult discrimination tasks require more collective and precise interplay of structure, forces and dynamics. Proteins can achieve this through correlated mutations extending far from a binding site, which fine tune the localized interaction with the ligand. Thus, the solution of more complicated tasks requires larger proteins, and proteins become more evolvable and robust when they are even larger than the bare minimum required for discrimination. Our model makes specific predictions about the role of flexibility and shape in recognition, and how to decouple affinity and specificity. Thus, the proposed theory of molecular discrimination sheds light on a question that is often taken for granted – "why are proteins so big?" One possible answer is, "because molecular discrimination is often difficult." |
Tuesday, March 15, 2022 5:36PM - 5:48PM |
K06.00010: Modeling sequence-space exploration and emergence of epistatic signals in protein evolution Francesco Zamponi During their evolution, proteins explore sequence space via an interplay between random mutations and phenotypic selection. Here we build upon recent progress in reconstructing data-driven fitness landscapes for families of homologous proteins, to propose stochastic models of experimental protein evolution. These models predict quantitatively important features of experimentally evolved sequence libraries, like fitness distributions and position-specific mutational spectra. They also allow us to efficiently simulate sequence libraries for a vast array of combinations of experimental parameters like sequence divergence, selection strength and library size. We showcase the potential of the approach in re-analyzing two recent experiments to determine protein structure from signals of epistasis emerging in experimental sequence libraries. To be detectable, these signals require sufficiently large and sufficiently diverged libraries. Our modeling framework offers a quantitative explanation for the variable success of recently published experiments. Furthermore, we can forecast the outcome of time- and resource-intensive evolution experiments, opening thereby a way to computationally optimize experimental protocols. |
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