Biology subjects

Mallimadugula, U. L.

Publications and source records attributed to Mallimadugula, U. L..

6 recordsLinked to original sources

bioRxiv2024

The probability of cryptic pocket opening controls functional tradeoffs in filovirus immune evasion.

Cryptic pockets are of growing interest as potential drug targets, particularly to control protein-nucleic acid interactions that often occur via flat surfaces. However, it remains unclear whether cryptic pockets contribute to protein function or if they are merely happenstantial features that can easily be evolved away to achieve drug resistance. Here, we explore whether a cryptic pocket in the Interferon Inhibitory Domain (IID) of viral protein 35 (VP35) of Zaire ebolavirus aids its ability to bind double-stranded RNA (dsRNA). We use simulations and experiments to study the relationship between cryptic pocket opening and dsRNA binding of the IIDs of two other filoviruses, Reston and Marburg. These homologs have nearly identical structures but block different interferon pathways due to different affinities for blunt ends and backbone of the dsRNA. Simulations and thiol-labeling experiments demonstrate that the homologs have varying probabilities of pocket opening. Subsequent dsRNA-binding assays suggest that closed conformations preferentially bind dsRNA blunt ends while open conformations prefer binding the backbone. Point mutations that modulate pocket opening proteins further confirm this preference. These results demonstrate the open cryptic pocket has a function, suggesting cryptic pockets are under selective pressure and may be difficult to evolve away to achieve drug resistance.

biophysics↗

bioRxiv2024

Accounting for fast vs slow exchange in single molecule FRET experiments reveals hidden conformational states

Proteins are dynamic systems whose structural preferences determine their function. Unfortunately, building atomically detailed models of protein structural ensembles remains challenging, limiting our understanding of the relationships between sequence, structure, and function. Combining single molecule Forster resonance energy transfer (smFRET) experiments with molecular dynamics simulations could provide experimentally grounded, all-atom models of a proteins structural ensemble. However, agreement between the two techniques is often insufficient to achieve this goal. Here, we explore whether accounting for important experimental details like averaging across structures sampled during a given smFRET measurement is responsible for this apparent discrepancy. We present an approach to account for this time-averaging by leveraging the kinetic information available from Markov state models of a proteins dynamics. This allows us to accurately assess which timescales are averaged during an experiment. We find this approach significantly improves agreement between simulations and experiments in proteins with varying degrees of dynamics, including the well-ordered protein T4 lysozyme, the partially disordered protein apolipoprotein E (ApoE), and a disordered amyloid protein (A{beta}40). We find evidence for hidden states that are not apparent in smFRET experiments because of time averaging with other structures, akin to states in fast exchange in NMR, and evaluate different force fields. Finally, we show how remaining discrepancies between computations and experiments can be used to guide additional simulations and build structural models for states that were previously unaccounted for. We expect our approach will enable combining simulations and experiments to understand the link between sequence, structure, and function in many settings.

biophysics↗

bioRxiv2022

Apolipoprotein E4 has extensive conformational heterogeneity in lipid free and bound forms

The {varepsilon}4-allele variant of Apolipoprotein E (ApoE4) is the strongest genetic risk factor for Alzheimers disease, though it only differs from its neutral counterpart ApoE3 by a single amino acid substitution. While ApoE4 influences the formation of plaques and neurofibrillary tangles, the structural determinants of pathogenicity remain undetermined due to limited structural information. We apply a combination of single-molecule spectroscopy and molecular dynamics simulations to construct an atomically-detailed model of monomeric ApoE4 and probe the effect of lipid association. Our data reveal that ApoE4 is far more disordered than previously thought and retains significant conformational heterogeneity after binding lipids. In particular, the behavior of the hinge region and C-terminal domain of ApoE4 differs substantially from that proposed in previous models and provides a crucial foundation for understanding how ApoE4 differs from non-pathogenic and protective variants of the protein.

biophysics↗

bioRxiv2021

Opening of a Cryptic Pocket in β-lactamase Increases Penicillinase Activity

Understanding the functional role of protein excited states has important implications in protein design and drug discovery. However, because these states are difficult to find and study, it is still unclear if excited states simply result from thermal fluctuations and generally detract from function or if these states can actually enhance protein function. To investigate this question, we consider excited states in {beta}-lactamases and particularly a subset of states containing a cryptic pocket which forms under the {Omega}-loop. Given the known importance of the {Omega}-loop and the presence of this pocket in at least two homologs, we hypothesized that these excited states enhance enzyme activity. Using thiol labeling assays to probe {Omega}-loop pocket dynamics and kinetic assays to probe activity, we find that while this pocket is not completely conserved across {beta}-lactamase homologs, those with the {Omega}-loop pocket have a higher activity against the substrate benzylpenicillin. We also find that this is true for TEM {beta}-lactamase variants with greater open {Omega}-loop pocket populations. We further investigate the open population using a combination of NMR CEST experiments and molecular dynamics simulations. To test our understanding of the {Omega}-loop pockets functional role, we designed mutations to enhance/suppress pocket opening and observed that benzylpenicillin activity is proportional to the probability of pocket opening in our designed variants. The work described here suggests that excited states containing cryptic pockets can be advantageous for function and may be favored by natural selection, increasing the potential utility of such cryptic pockets as drug targets.

biophysics↗

bioRxiv2020

Citizen Scientists Create an Exascale Computer to Combat COVID-19

SARS-CoV-2 has intricate mechanisms for initiating infection, immune evasion/suppression, and replication, which depend on the structure and dynamics of its constituent proteins. Many protein structures have been solved, but far less is known about their relevant conformational changes. To address this challenge, over a million citizen scientists banded together through the Folding@home distributed computing project to create the first exascale computer and simulate an unprecedented 0.1 seconds of the viral proteome. Our simulations capture dramatic opening of the apo Spike complex, far beyond that seen experimentally, which explains and successfully predicts the existence of cryptic epitopes. Different Spike homologues modulate the probabilities of open versus closed structures, balancing receptor binding and immune evasion. We also observe dramatic conformational changes across the proteome, which reveal over 50 cryptic pockets that expand targeting options for the design of antivirals. All data and models are freely available online, providing a quantitative structural atlas.

biophysics↗

bioRxiv2020

A Parallel Ratchet-Stroke Mechanism Leads to an Optimum Force for Molecular Motor Function.

Molecular motors convert chemical potential energy into mechanical work and perform a great number of critical biological functions. Examples include the polymerization and manipulation of nucleic acids, the generation of cellular motility and contractility, the formation and maintenance of cell shape, and the transport of materials within cells. The mechanisms underlying these molecular machines are routinely divided into two categories: Brownian ratchet and power stroke. While a ratchet uses chemical energy to bias thermally activated motion, a stroke depends on a direct coupling between chemical events and motion. However, the multi-dimensional nature of protein energy landscapes allows for the possibility of multiple reaction paths connecting two states. Here, we investigate the properties of a hypothetical molecular motor able to utilize parallel ratchet and stroke translocation mechanisms. We explore motor velocity and force-dependence as a function of the energy landscape of each path and reveal the potential for such a mechanism to result in an optimum force for motor function. We explore how the presence of this optimum depends on the rates of the individual paths and show that the distribution of stepping times characterized by the randomness parameter may be used to test for parallel path mechanisms. Lastly, we caution that experimental data consisting solely of measurements of velocity as a function of ATP concentration and force cannot be used to eliminate the possibility of such a parallel path mechanism. SIGNIFICANCEMolecular motors perform various mechanical functions in cells allowing them to move, replicate and perform various housekeeping functions required for life. Biophysical studies often aim to determine the molecular mechanism by which these motors convert chemical energy to mechanical work by fitting experimental data with kinetic models that fall into one of two classes: Brownian ratchets or power strokes. However, nothing a priori requires that a motor function via a single mechanism. Here, we consider a theoretical construct where a motor has access to both class of mechanism in parallel. Combining stochastic simulations and analytical solutions we describe unique signatures of such a mechanism that could be observed experimentally. We also show that absence of these signatures does not formally eliminate the existence of such a parallel mechanism. These findings expand our theoretical understanding of the potential motor behaviors with which to interpret experimental results.

biophysics↗