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bioRxiv2021

Mechanism of transcription modulation by the transcription-repair coupling factor

Elongation by RNA polymerase is dynamically modulated by accessory factors. The transcription-repair coupling factor (TRCF) recognizes distressed RNAPs and either rescues transcription or initiates transcription termination. Precisely how TRCFs choose to execute either outcome remains unclear. With Escherichia coli as a model, we used single-molecule assays to study dynamic modulation of elongation by Mfd, the bacterial TRCF. We found that nucleotide-bound Mfd converts the elongation complex (EC) into a catalytically poised state, presenting the EC with an opportunity to restart transcription. After long-lived residence in this catalytically poised state, ATP hydrolysis by Mfd remodels the EC through an irreversible process leading to loss of the RNA transcript. Further, biophysical studies revealed that the motor domain of Mfd binds and partially melts DNA containing a template strand overhang. The results explain pathway choice determining the fate of the EC and provide a molecular mechanism for transcription modulation by TRCF.

biophysics↗

bioRxiv2021

Identification of Structures for Ion Channel Kinetic Models

Markov models of ion channel dynamics have evolved as experimental advances have improved our understanding of channel function. Past studies have examined various topologies for Markov models of channel dynamics. We present a systematic method for identification of all possible Markov model topologies using experimental data for two types of native voltage-gated ion channel currents: mouse atrial sodium and human left ventricular fast transient outward potassium currents. In addition to optional biophysically inspired restrictions on the number of connections from a state and elimination of long-range connections, this study further suggests successful models have more than minimum number of connections for set number of states. When working with topologies with more than the minimum number of connections, the topologies with three and four connections to the open state tend to serve well as Markov models of ion channel dynamics. Significance StatementHere, we present a computational routine to thoroughly search for Markov model topologies for simulating whole-cell currents given an experimental dataset. We test this method on two distinct types of voltage-gated ion channels that function in the generation of cardiac action potentials. Particularly successful models have more than one connection between an open state and the rest of the model, and large models may benefit from having even more connections between the open state and the rest of the other states.

biophysics↗

bioRxiv2021

Emergent spatiotemporal population dynamics with cell-length control of synthetic microbial consortia

AO_SCPLOWBSTRACTC_SCPLOWIncreased complexity of engineered microbial biocircuits highlights the need for distributed cell functionality due to concomitant increases of metabolic and regulatory burdens imposed on single-strain topologies. Distributed systems, however, introduce additional challenges since consortium composition and spatiotemporal dynamics of constituent strains must be robustly controlled to achieve desired circuit behaviors. Here, we address these challenges with a modeling-based investigation of emergent spatiotemporal population dynamics that result from cell-length control of monolayer, two-strain bacterial consortia. We demonstrate that with dynamic control of a strains division length, nematic cell alignment in close-packed monolayers can be destabilized. We found this destabilization conferred an emergent, competitive advantage on smaller-length strains--but by mechanisms that differed depending on the spatial patterns of the population. We used complementary modeling approaches to elucidate underlying mechanisms: an agent-based model to simulate detailed mechanical and signaling interactions between the competing strains and a reductive, stochastic lattice model to represent cell-cell interactions with a single rotational parameter. Our modeling suggests that spatial strain-fraction oscillations can be generated when cell-length control is coupled to quorum-sensing signaling in negative feedback topologies. Our research employs novel methods of population control and points the way to programming strain fraction dynamics in consortial synthetic biology. Engineered microbial collectives are more versatile and robust than single strain populations. However, the function of such collectives is sensitive to their spatiotemporal organization. Here, we demonstrate control of the spatiotemporal composition of synthetic microbial consortia by dynamically modulating the average cell length of constituent strains. Such modulation confers an emergent "mechanical fitness" advantage upon the shorter length strain. We used both a biophysically realistic agent-based model to test the impact of cell shape on spatiotemporal dynamics and a conceptually simpler stochastic lattice model to explain the essential mechanisms driving the dynamics.

biophysics↗

bioRxiv2021

Conformational clamping by a membrane ligand activates the EphA2 receptor

The EphA2 receptor is a promising drug target for cancer treatment, since EphA2 activation can inhibit metastasis and tumor progression. It has been recently described that the TYPE7 peptide activates EphA2 using a novel mechanism that involves binding to the single transmembrane domain of the receptor. TYPE7 is a conditional transmembrane (TM) ligand, which only inserts into membranes at neutral pH in the presence of the TM region of EphA2. However, how membrane interactions can activate EphA2 is not known. We systematically altered the sequence of TYPE7 to identify the binding motif used to activate EphA2. With the resulting six peptides, we performed biophysical and cell migration assays that identified a new potent peptide variant. We also performed a mutational screen that determined the helical interface that mediates dimerization of the TM domain of EphA2 in cells. These results, together with molecular dynamic simulations, allowed to elucidate the molecular mechanism that TYPE7 uses to activate EphA2, where the membrane peptide acts as a molecular clamp that wraps around the TM dimer of the receptor. We propose that this binding mode stabilizes the active conformation of EphA2. Our data, additionally, provide clues into the properties that TM ligands need to have in order to achieve activation of membrane receptors.

biophysics↗

bioRxiv2021

Multi-parameter photon-by-photon hidden Markov modeling

Single-molecule Forster resonance energy transfer (smFRET) is a unique biophysical approach for studying conformational dynamics in biomacro-molecules. Photon-by-photon hidden Markov modelling (H2MM) is an analysis tool that can quantify FRET dynamics of single biomolecules, even if they occur on the sub-millisecond timescale. However, dye photophysical transitions intertwined with FRET dynamics may introduce artefacts. Here, we introduce multi-parameter H2MM (mpH2MM), which assists in identifying FRET dynamics based on simultaneous observation of multiple experimentally-derived parameters. We show the importance of using mpH2MM to decouple FRET dynamics caused by conformational changes from photophysical transitions in confocal-based smFRET measurements of a DNA hairpin, the maltose binding protein, MalE, and the type-III secretion system effector, YopO, from Yersinia species all exhibiting conformational dynamics ranging from the sub-second to microsecond timescales. Overall, we show that using mpH2MM facilitates the identification and quantification of biomolecular sub-populations and their origin.

biophysics↗

bioRxiv2021

Cryptic SARS-CoV2-spike-with-sugar interactions revealed by 'universal' saturation transfer analysis

Many host pathogen interactions such as human viruses (including non-SARS-coronaviruses) rely on attachment to host cell-surface glycans. There are conflicting reports about whether the Spike protein of SARS-CoV-2 binds to sialic acid commonly found on host cell-surface N-linked glycans. In the absence of a biochemical assay, the ability to analyze the binding of glycans to heavily- modified proteins and resolve this issue is limited. Classical Saturation Transfer Difference (STD) NMR can be confounded by overlapping sugar resonances that compound with known experimental constraints. Here we present universal saturation transfer analysis (uSTA), an NMR method that builds on existing approaches to provide a general and automated workflow for studying protein-ligand interactions. uSTA reveals that B-origin-lineage-SARS-CoV-2 spike trimer binds sialoside sugars in an end on manner and modelling guided by uSTA localises binding to the spike N-terminal domain (NTD). The sialylated-polylactosamine motif is found on tetraantennary human N-linked-glycoproteins in deeper lung and may have played a role in zoonosis. Provocatively, sialic acid binding is abolished by mutations in some subsequent SARS- CoV-2 variants-of-concern. A very high resolution cryo-EM structure confirms the NTD location and end on mode; it rationalises the effect of NTD mutations and the structure-activity relationship of sialic acid analogues. uSTA is demonstrated to be a robust, rapid and quantitative tool for analysis of binding, even in the most demanding systems. Extended AbstractThe surface proteins found on both pathogens and host cells mediate entry (and exit) and influence disease progression and transmission. Both types can bear host-generated post- translational modifications such as glycosylation that are essential for function but can confound biophysical methods used for dissecting key interactions. Several human viruses (including non- SARS-coronaviruses) attach to host cell-surface N-linked glycans that include forms of sialic acid (sialosides). There remains, however, conflicting evidence as to if or how SARS-associated coronaviruses might use such a mechanism. Here, we demonstrate quantitative extension of saturation transfer protein NMR methods to a complete mathematical model of the magnetization transfer caused by interactions between protein and ligand. The method couples objective resonance-identification via a deconvolution algorithm with Bloch-McConnell analysis to enable a structural, kinetic and thermodynamic analysis of ligand binding beyond previously-perceived limits of exchange rates, concentration or system. Using an automated and openly available workflow this universal saturation transfer analysis (uSTA) can be readily-applied in a range of even heavily-modified systems in a general manner to now obtain quantitative binding interaction parameters (KD, kEx). uSTA proved critical in mapping direct interactions between natural sialoside sugar ligands and relevant virus-surface attachment glycoproteins - SARS-CoV-2-spike and influenza-H1N1-haemagglutinin variants - by quantitating ligand signal in spectral regions otherwise occluded by resonances from mobile protein glycans (that also include sialosides). In B- origin-lineage-SARS-CoV-2 spike trimer end on-binding to sialoside sugars was revealed contrasting with extended surface-binding for heparin sugar ligands; uSTA-derived constraints used in structural modelling suggested sialoside-glycan binding sites in a beta-sheet-rich region of spike N-terminal domain (NTD). Consistent with this, uSTA-glycan binding was minimally- perturbed by antibodies that neutralize the ACE2-binding domain (RBD) but strongly disrupted in spike from the B1.1.7/alpha and B1.351/beta variants-of-concern, which possess hotspot mutations in the NTD. Sialoside binding in B-origin-lineage-NTD was unequivocally pinpointed by cryo-EM to a site that is created from residues that are notably deleted in variants (e.g. H69,V70,Y145 in alpha). An analysis of beneficial genetic variances in cohorts of patients from early 2020 suggests a model in which this site in the NTD of B-origin-lineage-SARS-CoV-2 (but not in alpha/beta-variants) may have exploited a specific sialylated-polylactosamine motif found on tetraantennary human N-linked-glycoproteins in deeper lung. Together these confirm a novel binding mode mediated by the unusual NTD of SARS-CoV-2 and suggest how it may drive virulence and/or zoonosis via modulation of glycan attachment. Since cell-surface glycans are widely relevant to biology and pathology, uSTA can now provide ready, quantitative, widespread analysis of complex, host-derived and post-translationally modified proteins with putative ligands relevant to disease even in previously confounding complex systems.

biophysics↗

bioRxiv2021

Membrane surfaces regulate assembly of a ribonucleoprotein condensate

Biomolecular condensates organize biochemistry in time and space, yet little is known about how cells control either the position or scale of these assemblies. In cells, condensates often appear as dispersed, relatively small assemblies that do not grow (coarsen) into a single droplet despite their propensity to coalesce. Here we report that ribonucleoprotein condensates of the Q-rich protein Whi3 interact with the endoplasmic reticulum, prompting us to hypothesize that membrane association controls the position and size of condensates. Reconstitution of Whi3 condensates on supported lipid bilayers reveals that association with a diffusive lipid surface promotes condensation at both physiological ionic strength and protein concentration. Notably, these assemblies rapidly arrest, matching size distributions seen in cells. The timing of the arrest is influenced by the ordering of protein-protein and protein-RNA interactions and controlled by the slow diffusion of complexes induced by the membrane. This slowed diffusion limits both transfer of small protein-RNA complexes between condensates and their coalescence, thus driving coarsening to arrest. Our experiments reveal a tradeoff between locally-enhanced protein concentration at membranes, which favors condensation, and an accompanying reduction in diffusion, which restricts coarsening. Thus, membranes can maintain a population of small condensates in the absence of active mechanisms. Given that many condensates are bound to endomembranes, we predict that the biophysical properties of lipid bilayers are key for controlling condensate sizes throughout the cell. One sentence summaryAssembly on a membrane surface positions and scales biomolecular condensates by controlling relative diffusion rates of proteins and nucleic acids.

biophysics↗

bioRxiv2021

Possible link between higher transmissibility of B.1.617 and B.1.1.7 variants of SARS-CoV-2 and increased structural stability of its spike protein and hACE2 affinity

The Severe Acute syndrome corona Virus 2 (SARS-CoV-2) outbreak in December 2019 has caused a global pandemic. The rapid mutation rate in the virus has caused alarming situations worldwide and is being attributed to the false negativity in RT-PCR tests, which also might lead to inefficacy of the available drugs. It has also increased the chances of reinfection and immune escape. We have performed Molecular Dynamic simulations of three different Spike-ACE2 complexes, namely Wildtype (WT), B.1.1.7 variant (N501Y Spike mutant) and B.1.617 variant (L452R, E484Q Spike mutant) and compared their dynamics, binding energy and molecular interactions. Our result shows that mutation has caused the increase in the binding energy between the Spike and hACE2. In the case of B.1.617 variant, the mutations at L452R and E484Q increased the stability and intra-chain interactions in the Spike protein, which may change the interaction ability of human antibodies to this Spike variant. Further, we found that the B.1.1.7 variant had increased hydrogen interaction with LYS353 of hACE2 and more binding affinity in comparison to WT. The current study provides the biophysical basis for understanding the molecular mechanism and rationale behind the increase in the transmissivity and infectivity of the mutants compared to wild-type SARS-CoV-2.

biophysics↗

bioRxiv2021

Phase separation in fluids with many interacting components

Fluids in natural systems, like the cytoplasm of a cell, often contain thousands of molecular species that are organized into multiple coexisting phases that enable diverse and specific functions. How interactions between numerous molecular species encode for various emergent phases is not well understood. Here we leverage approaches from random matrix theory and statistical physics to describe the emergent phase behavior of fluid mixtures with many species whose interactions are drawn randomly from an underlying distribution. Through numerical simulation and stability analyses, we show that these mixtures exhibit staged phase separation kinetics and are characterized by multiple coexisting phases at equilibrium with distinct compositions. Random-matrix theory predicts the number of existing phases at equilibrium, validated by simulations with diverse component numbers and interaction parameters. Surprisingly, this model predicts an upper bound on the number of phases, derived from dynamical considerations, that is much lower than the limit from the Gibbs phase rule, which is obtained from equilibrium thermodynamic constraints. Using a biophysically motivated model of pairwise interactions between components, we design ensembles that encode either linear or non-monotonic scaling relationships between number of components and co-existing phases, which we validate through simulation and theory. Finally, inspired by parallels in biological systems, we show that including nonequilibrium turnover of components through chemical reactions can tunably modulate the number of coexisting phases at steady-state without changing overall fluid composition. Together, our study provides a model framework that describes the emergent dynamical and steady-state phase behavior of liquid-like mixtures with many interacting constituents.

biophysics↗

bioRxiv2021

Disentangling cadherin-mediated cell-cell interactions in collective cancer cell migration

Cell dispersion from a confined area is fundamental in a number of biological processes, including cancer metastasis. To date, a quantitative understanding of the interplay of single cell motility, cell proliferation, and intercellular contacts remains elusive. In particular, the role of E- and N-Cadherin junctions, central components of intercellular contacts, is still controversial. Combining theoretical modeling with in vitro observations, we investigate the collective spreading behavior of colonies of human cancer cells (T24). Inhibition of E- and N-Cadherin junctions decreases colony spreading and average spreading velocities, without affecting the strength of correlations in spreading velocities of neighboring cells. Based on a biophysical simulation model for cell migration, we show that the behavioral changes upon disruption of these junctions can be explained by reduced repulsive excluded volume interactions between cells. This suggests that cadherin-based intercellular contacts sharpen cell boundaries leading to repulsive rather than cohesive interactions between cells, thereby promoting efficient cell spreading during collective migration.

biophysics↗

bioRxiv2021

Energy Landscape of the SARS-CoV-2 Reveals Extensive Conformational Heterogeneity

Cryo-electron microscopy (cryo-EM) has produced a number of structural models of the SARS-CoV-2 spike, already prompting biomedical outcomes. However, these reported models and their associated electrostatic potential maps represent an unknown admixture of conformations stemming from the underlying energy landscape of the spike protein. As for any protein, some of the spikes conformational motions are expected to be biophysically relevant, but cannot be interpreted only by static models. Using experimental cryo-EM images, we present the energy landscape of the spike protein conformations, and identify molecular rearrangements along the most-likely conformational path in the vicinity of the open (so called 1RBD-up) state. The resulting global and local atomic refinements reveal larger movements than those expected by comparing the reported 1RBD-up and 1RBD-down cryo-EM models. Here we report greater degrees of "openness" in global conformations of the 1RBD-up state, not revealed in the single-model interpretations of the density maps, together with conformations that overlap with the reported models. We discover how the glycan shield contributes to the stability of these conformations along the minimum free-energy pathway. A local analysis of seven key binding pockets reveals that six out them, including those for engaging ACE2, therapeutic mini-proteins, linoleic acid, two different kinds of antibodies, and protein-glycan interaction sites, switch conformations between their known apo- and holo-conformations, even when the global spike conformation is 1RBD-up. This is reminiscent of a conformational pre-equilibrium. We found only one binding pocket, namely antibody AB-C135 to remain closed along the entire minimum free energy path, suggesting an induced fit mechanism for this enzyme.

biophysics↗

bioRxiv2021

Height, but not binding epitope, affects the potency of synthetic TCR agonists

Under physiological conditions, peptide-MHC (pMHC) molecules can trigger T-cell receptors (TCRs) as monovalent ligands that are sparsely distributed on the plasma membrane of an antigen-presenting cell. TCR can also be activated by artificial clustering, such as with pMHC tetramers or antibodies; however, these strategies circumvent many of the natural ligand discrimination mechanisms of the T cell and can elicit non-physiological signaling activity. We have recently introduced a synthetic TCR agonist composed of an anti-TCR{beta} Fab antibody fragment covalently bound to a DNA oligonucleotide, which serves as a membrane anchor. This Fab-DNA ligand efficiently activates TCR as a monomer when membrane-associated and exhibits a potency and activation profile resembling agonist pMHC. In this report, we explore the geometric requirements for effective TCR triggering and cellular activation by Fab-DNA ligands. We find that T cells are insensitive to the ligand binding epitope on the TCR complex, but that length of the DNA tether is important. Increasing the intermembrane distance spanned by Fab-DNA:TCR complexes decreases TCR triggering efficiency and T cell activation potency, consistent with the kinetic-segregation model of TCR triggering. These results establish design parameters for construction of synthetic TCR agonists that are able to activate polyclonal T cell populations, such as T cells from a human patient, in a similar manner as the native pMHC ligand. STATEMENT OF SIGNIFICANCEWe report geometric requirements for potent T cell activation by synthetic TCR ligands that mimic biophysical properties of the native pMHC ligand, but have the additional ability to activate polyclonal T cell populations. We find that increasing the space between apposed membranes at TCR binding events decreases ligand potency, but that changing the ligands binding epitope on the TCR has essentially no effect. The observed decrease in potency with increased ligand height is attributed to the longer ligands attenuated ability to trigger TCR at binding events.

biophysics↗

bioRxiv2021

Conformational buffering underlies functional selection in intrinsically disordered protein regions

Many disordered proteins conserve essential functions in the face of extensive sequence variation. This makes it challenging to identify the forces responsible for functional selection. Viruses are robust model systems to investigate functional selection and they take advantage of protein disorder to acquire novel traits. Here, we combine structural and computational biophysics with evolutionary analysis to determine the molecular basis for functional selection in the intrinsically disordered adenovirus early gene 1A (E1A) protein. E1A competes with host factors to bind the retinoblastoma (Rb) protein, triggering early S-phase entry and disrupting normal cellular proliferation. We show that the ability to outcompete host factors depends on the picomolar binding affinity of E1A for Rb, which is driven by two binding motifs tethered by a hypervariable disordered linker. Binding affinity is determined by the spatial dimensions of the linker, which constrain the relative position of the two binding motifs. Despite substantial sequence variation across evolution, the linker dimensions are finely optimized through compensatory changes in amino acid sequence and sequence length, leading to conserved linker dimensions and maximal affinity. We refer to the mechanism that conserves spatial dimensions despite large-scale variations in sequence as conformational buffering. Conformational buffering explains how variable disordered proteins encode functions and could be a general mechanism for functional selection within disordered protein regions.

biophysics↗

bioRxiv2021

Rules for designing protein fold switches and their implications for the folding code

We have engineered switches between the three most common small folds, 3, 4{beta}+, and /{beta}-plait, referred to here as A, B, and S, respectively. Mutations were introduced into the natural S protein until sequences were created that have a stable S-fold in their longer ([~]90 amino acid) form and have an alternative fold (either A or B) in their shorter (56 amino acid) form. Five sequence pairs were designed and key structures were determined using NMR spectroscopy. Each protein pair is 100% identical in the 56 amino acid region of overlap. Several rules for engineering switches emerged. First, designing one sequence with good native state interactions in two folds requires care but is feasible. Once this condition is met, fold populations are determined by the stability of the embedded A- or B-fold relative to the S-fold and the conformational propensities of the ends that are generated in the switch to the embedded fold. If the stabilities of the embedded fold and the longer fold are similar, conformation is highly sensitive to mutation so that even a single amino acid substitution can radically shift the population to the alternative fold. The results provide insight into why dimorphic sequences can be engineered and sometimes exist in nature, while most natural protein sequences populate single folds. Proteins may evolve toward unique folds because dimorphic sequences generate interactions that destabilize and can produce aberrant functions. Thus, two-state behavior may result from natures negative design rather than being an inherent property of the folding code. Significance StatementWe establish general rules for designing protein fold switches by engineering dimorphic sequences that link the three most common small folds. The fact that switches can be engineered in arbitrary and common protein folds, sheds light on several important questions: 1) What is the generality of fold switching? 2) What types of folds are amenable to switching? 3) What properties are shared by sequences that can fold into two completely different structures? This work has implications for understanding how amino acid sequence encodes structure, how proteins evolve, how mutation is related to disease, and how function is annotated to sequences of unknown structure. ClassificationBiological Sciences: Biochemistry; Physical Sciences: Biophysics and Computational Biology

biophysics↗

bioRxiv2021

Anchored and labile pools of Calcineurin are enabled by a disordered AKAP scaffold

Disordered scaffold proteins provide multivalent landing pads that, via a series of embedded Short Linear Motifs (SLiMs), bring together the components of a complex to orchestrate precise spatial and temporal regulation of cellular processes. One such protein is AKAP5, which contains SLiMs that anchor PKA and Calcineurin, and recruit substrate (the TRPV1 receptor). Calcineurin is anchored to AKAP5 by a well-characterised PxIxIT SLiM. Here we show, using a combination of biochemical and biophysical approaches, that the Calcineurin PxIxIT-binding groove also recognises several hitherto unknown lower-affinity SLiMs in addition to the PxIxIT motif. We demonstrate that the assembly is in reality a complex system with conserved SLiMs spanning a wide affinity range. The capture is analogous to that seen for many DNA-binding proteins that have a weak non-specific affinity for DNA outside the canonical binding site, but different in that it involves (i) two proteins, and (ii) hydrophobic rather than electrostatic interactions. It is also compatible with the requirement for both stable anchoring of the enzyme and responsive downstream signalling. We conclude that the AKAP5 C-terminus is enriched in lower-affinity/mini-SLiMs that, together with the canonical SLiM, maintain a structurally disordered but tightly regulated signalosome.

biophysics↗

bioRxiv2021

Probing DNA-protein interactions using single-molecule diffusivity contrast

Single-molecule fluorescence investigations of protein-nucleic acid interactions require robust means to identify the binding state of individual substrate molecules in real time. Here we show that diffusivity contrast, widely used in fluorescence correlation spectroscopy at the ensemble level and in single-particle tracking on individual (but slowly diffusing) species, can be used as a general readout to determine the binding state of single DNA molecules with unlabeled proteins in solution. We first describe the technical basis of drift-free single-molecule diffusivity measurements in an Anti-Brownian ELetrokinetic (ABEL) trap. We then cross-validate our method with protein-induced fluorescence enhancement (PIFE), a popular technique to detect protein binding on nucleic acid substrates with single-molecule sensitivity. We extend an existing hydrodynamic modeling framework to link measured diffusivity to particular DNA-protein structures and obtain good agreement between the measured and predicted diffusivity values. Finally, we show that combining diffusivity contrast with PIFE allows simultaneous mapping of binding stoichiometry and location on individual DNA-protein complexes, potentially enhancing single-molecule views of relevant biophysical processes.

biophysics↗

bioRxiv2021

Refining conformational ensembles of flexible proteins against small-angle X-ray scattering data

Intrinsically disordered proteins and flexible regions in multi-domain proteins display substantial conformational heterogeneity. Characterizing the conformational ensembles of these proteins in solution typically requires combining one or more biophysical techniques with computational modelling or simulations. Experimental data can either be used to assess the accuracy of a computational model or to refine the computational model to get a better agreement with the experimental data. In both cases, one generally needs a so-called forward model, i.e. an algorithm to calculate experimental observables from individual conformations or ensembles. In many cases, this involve one or more parameters that need to be set, and it is not always trivial to determine the optimal values or to understand the impact on the choice of parameters. For example, in the case of small-angle X-ray scattering (SAXS) experiments, many forward models include parameters that describe the contribution of the hydration layer and displaced solvent to the background-subtracted experimental data. Often, one also needs to fit a scale factor and a constant background for the SAXS data, but across the entire ensemble. Here, we present a protocol to dissect the effect of free-parameters on the calculated SAXS intensities, and to identify a reliable set of values. We have implemented this procedure in our Bayesian/Maximum Entropy framework for ensemble refinement, and demonstrate the results on four intrinsically disordered proteins and a three-domain protein connected by flexible linkers. Our results show that the resulting ensembles can depend on the parameters used for solvent effects, and suggests that these should be chosen carefully. We also find a set of parameters that work robustly across all proteins. SIGNIFICANCEThe flexibility of a protein is often key to its biological function, yet understanding and characterizing its conformational heterogeneity is difficult. We here describe a robust protocol for combining small-angle X-ray scattering experiments with computational modelling to obtain a conformational ensemble. In particular, we focus on the contribution of protein hydration to the experiments and how this is included in modelling the data. Our resulting algorithm and software should make modelling intrinsically disordered proteins and multi-domain proteins more robust, thus aiding in understanding the relationship between protein dynamics and biological function.

biophysics↗

bioRxiv2021

Probing Interactions of Therapeutic Antibodies with Serum via Second Virial Coefficient Measurements

Antibody-based therapeutics are the fastest growing drug class on the market, used to treat aggressive forms of cancer, chronic autoimmune conditions, and numerous other disease states. While the specificity, affinity, and versatility of therapeutic antibodies can provide an advantage over traditional small molecule drugs, their development and optimization can be much more challenging and time-consuming. This is, in part, because the ideal formulation buffer systems used for in vitro characterization inadequately reflect the crowded biological environments (serum, endosomal lumen, etc.) that these drugs experience once administered to a patient. Such environments can perturb the binding of antibodies to their antigens and receptors, as well as homo- and hetero-aggregation, in ways that are incompletely understood, thereby altering therapeutic effect and disposition. While excluded volume effects are classically thought to favor binding, weak interactions with co-solutes in crowded conditions can inhibit binding. The second virial coefficient (B2) parameter quantifies such weak interactions and can be determined by a variety of techniques in dilute solution, but analogous methods in complex biological fluids are not well established. Here, we demonstrate that fluorescence correlation spectroscopy (FCS) is able to measure diffusive B2 values directly in undiluted serum. Apparent second virial coefficient (B2,app) measurements of antibodies in serum reveal that changes in the balance between attractive and repulsive interactions can dramatically impact global nonideality. Furthermore, our findings suggest that the common approach of isolating specific components and completing independent cross-term virial coefficient measurements is an incomplete representation of nonideality in serum. The approach presented here could enrich our understanding of the effects of biological environments on proteins in general, and advance the development of therapeutic antibodies and other protein-based therapeutics. STATEMENT OF SIGNIFICANCEWe present FCS as an orthogonal method to traditional methods for characterizing weak, nonspecific homo- and hetero-interactions through determination of self- and cross-term second virial coefficients, respectively. We also characterize weak interactions between therapeutic antibodies and serum components through determination of an apparent second virial coefficient (B2,app) directly in undiluted serum. Our results suggest that global nonideality effects are antibody-dependent, and that attractive and repulsive interactions with co-solutes are occurring simultaneously. This approach could advance our understanding of the impact of nonideality to the biophysical and pharmacological properties of therapeutic antibodies and other engineered proteins in relevant biological environments, and could accelerate the development and optimization of protein-based therapeutics.

biophysics↗