Biology subjects

Gnanakaran, S.

Publications and source records attributed to Gnanakaran, S..

26 records · Page 2Linked to original sources

bioRxiv2021

SARS-CoV-2 variant B.1.1.7 is susceptible to neutralizing antibodies elicited by ancestral Spike vaccines

The SARS-CoV-2 Spike glycoprotein mediates virus entry and is a major target for neutralizing antibodies. All current vaccines are based on the ancestral Spike with the goal of generating a protective neutralizing antibody response. Several novel SARS-CoV-2 variants with multiple Spike mutations have emerged, and their rapid spread and potential for immune escape have raised concerns. One of these variants, first identified in the United Kingdom, B.1.1.7 (also called VUI202012/01), contains eight Spike mutations with potential to impact antibody therapy, vaccine efficacy and risk of reinfection. Here we employed a lentivirus-based pseudovirus assay to show that variant B.1.1.7 remains sensitive to neutralization, albeit at moderately reduced levels (~2-fold), by serum samples from convalescent individuals and recipients of two different vaccines based on ancestral Spike: mRNA-1273 (Moderna), and protein nanoparticle NVX-CoV2373 (Novavax). Some monoclonal antibodies to the receptor binding domain (RBD) of Spike were less effective against the variant while others were largely unaffected. These findings indicate that B.1.1.7 is not a neutralization escape variant that would be a major concern for current vaccines, or for an increased risk of reinfection.

immunology↗

bioRxiv2020

The SARS-CoV-2 Spike Variant D614G Favors an Open Conformational State

The COVID-19 pandemic underwent a rapid transition with the emergence of a SARS-CoV-2 variant that carried the amino acid substitution D614G in the Spike protein that became globally prevalent. The G-form is both more infectious in vitro and associated with increased viral loads in infected people. To gain insight into the mechanism underlying these distinctive characteristics, we employed multiple replicas of microsecond all-atom simulations to probe the molecular-level impact of this substitution on Spikes closed and open states. The open state enables Spike interactions with its human cellular receptor, ACE2. Here we show that changes in the inter-protomer energetics due to the D614G substitution favor a higher population of infection-capable (open) states. The inter-protomer interactions between S1 and S2 subunits in the open state of the D-form are asymmetric. This asymmetry is resolved in the G-form due to the release of tensile hydrogen bonds resulting in an increased population of open conformations. Thus, the increased infectivity of the G-form is likely due to a higher rate of profitable binding encounters with the host receptor. It is also predicted to be more neutralization sensitive due to enhanced exposure of the receptor binding domain, a key target region for neutralizing antibodies.

biophysics↗

bioRxiv2020

Multiscale Characterization of Complex Binding Interactions of Cellulolytic Enzymes Highlights Limitations of Classical Approaches

Cellulolytic microorganisms, like Trichoderma reesei or Clostridium thermocellum, frequently have non-catalytic carbohydrate-binding modules (CBMs) associated with secreted or cell surface bound multidomain carbohydrate-active enzymes (CAZymes) like cellulases. Mostly type-A family CBMs are known to promote cellulose deconstruction by increasing the substrate-bound concentration of cognate cellulase catalytic domains. However, due to the interfacial nature of cellulose hydrolysis and the structural heterogeneity of cellulose, it has been challenging to fully understand the role of CBMs on cellulase activity using classical protein-ligand binding assays. Here, we report a single-molecule CAZyme assay for an industrially relevant processive cellulase Cel7A (from T. reesei) to reveal how subtle CBM1 binding differences can drastically impact cellulase motility/velocity and commitment to initial processive motion for deconstruction of two well-studied crystalline cellulose allomorphs (namely cellulose I and III). We take a multifaceted approach to characterize the complex binding interactions of all major type-A family representative CBMs including CBM1, using an optical-tweezers based single-molecule CBM-cellulose bond rupture assay to complement several classical bulk ensemble protein-ligand binding characterization methods. While our work provides a basis for the cautious use of Langmuir-type adsorption models to characterize classical protein-ligand binding assay data, we highlight the critical limitations of using such overly simplistic models to gain a truly molecular-level understanding of interfacial protein binding interactions at heterogeneous solid-liquid interfaces. Finally, molecular dynamics simulations provided a theoretical basis for the complex binding behavior seen for CBM1 towards two distinct cellulose allomorphs reconciling experimental findings from multiscale analytical methods. Significance StatementMultimodal biomolecular binding interactions involving carbohydrate polymers (e.g., cellulose, starch, chitin, glycosaminoglycans) are fundamental molecular processes relevant to the recognition, biosynthesis, and degradation of all major terrestrial and aquatic biomass. Protein-carbohydrate binding interactions are also critical to industrial biotechnology operations such as enzymatically-catalyzed bioconversion of starch and lignocellulose into biochemicals like ethanol. However, despite the ubiquitous importance of such interfacial processes, we have a poor molecular-level understanding of protein-polysaccharide binding interactions. Here, we provide a comprehensive experimental and theoretical analysis of bulk ensemble versus single-molecule binding interactions of enzyme motors and associated non-catalytic binding domains with cellulosic polysaccharides to highlight the critical limitations of applying classical biochemical assay techniques alone to understanding protein adsorption or biological activity at solid-liquid interfaces.

biochemistry↗

bioRxiv2019

A Network-based approach for Quantifying the Resilience and Vulnerability of HIV-1 Native Glycan Shield

Dense surface glycosylation on the HIV-1 envelope (Env) protein acts as a shield from the adaptive immune system. However, the molecular complexity and flexibility of glycans make experimental studies a challenge. Here we have integrated high-throughput atomistic modeling of fully glycosylated HIV-1 Env with graph theory to capture immunologically important features of the shield topology. This is the first complete all-atom model of HIV-1 Env SOSIP glycan shield that includes both oligomannose and complex glycans, providing results which are physiologically more relevant than the previous models with uniform glycosylation. This integrated approach including quantitative comparison with cryo-electron microscopy data provides hitherto unexplored details of the native shield architecture and its difference from the high-mannose glycoform. We have also derived a measure to quantify the shielding effect over the antigenic protein surface that defines regions of relative vulnerability and resilience of the shield and can be harnessed for rational immunogen design.

biophysics↗

bioRxiv2019

Visualization of the HIV-1 Env Glycan Shield Across Scales

The dense array of N-linked glycans on the HIV-1 Envelope Glycoprotein (Env), known as the "glycan shield", is a key determinant of immunogenicity, yet intrinsic heterogeneity confounds typical structure-function analysis. Here we present an integrated approach of single-particle electron cryomicroscopy (cryo-EM), computational modeling, and site-specific mass-spectrometry (MS) to probe glycan shield structure and behavior at multiple levels. We found that dynamics lead to an extensive network of inter-glycan interactions that drive the formation of higher-order structure within the glycan shield. This structure defines diffuse boundaries between buried and exposed protein surface and creates a mapping of potentially immunogenic sites on Env. Analysis of Env expressed in different cell lines revealed how cryo-EM can detect subtle changes in glycan occupancy, composition, and dynamics that impact glycan shield structure and epitope accessibility. Importantly, this identified unforeseen changes in the glycan shield of Env obtained from expression in the same CHO cell line used for GMP production. Finally, by capturing the enzymatic deglycosylation of Env in a time-resolved manner we found that highly connected glycan clusters are resistant to digestion and help stabilize the pre-fusion trimer, suggesting the glycan shield may function beyond immune evasion. Significance StatementThe HIV-1 Env "glycan shield" masks the surface of the protein from immune recognition, yet intrinsic heterogeneity defies a typical structure-function description. Using a complementary approach of cryo-EM, computational modeling, and mass-spectrometry we show how heterogeneity and dynamics affect glycan shield structure across scales. Our combined approach facilitated the development of new cryo-EM data analysis methods and allowed for validation of models against experiment. Comparison of Env across a range of glycosylation states revealed how subtle differences in composition impact glycan shield structure and affect the accessibility of epitopes on the surface. Finally, time-resolved cryo-EM experiments uncovered how highly connected glycan clusters help stabilize the pre-fusion trimer, suggesting the glycan shield may function beyond immune evasion.

biophysics↗

bioRxiv2019

A Graph-Directed Approach for Creation of a Homology Modeling Library: Application to Venom Structure Prediction

Many toxins are short, cysteine-rich peptides that are of great interest as novel therapeutic leads and of great concern as lethal biological agents due to their high affinity and specificity for various receptors involved in neuromuscular transmission. To perform initial candidate identification for design of a drug impacting a particular receptor or for threat assessment as a harmful toxin, one requires a set of candidate structures of reasonable accuracy with potential for interaction with the target receptor. In this article, we introduce a graph-based algorithm for identifying good extant template structures from a library of evolutionarily-related cysteine-containing sequences for structural determination of target sequences by homology modeling. We employ this approach to study the conotoxins, a set of toxin peptides produced by the family of aquatic cone snails. Currently, of the approximately six thousand known conotoxin sequences, only about three percent have experimentally characterized three-dimensional structures, leading to a serious bottleneck in identifying potential drug candidates. We demonstrate that the conotoxin template library generated by our approach may be employed to perform homology modeling and greatly increase the number of characterized conotoxin structures. We also show how our approach can guide experimental design by identifying and ranking sequences for structural characterization in a similar manner. Overall, we present and validate an approach for venom structure modeling and employ it to expand the library of extant conotoxin structures by almost 300% through homology modeling employing the template library determined in our approach.

bioinformatics↗

bioRxiv2019

Unsupervised Machine Learning for Analysis of Coexisting Lipid Phases and Domain Growth in Biological Membranes

Phase separation in mixed lipid systems has been extensively studied both experimentally and theoretically because of its biological importance. A detailed description of such complex systems undoubtedly requires novel mathematical frameworks that are capable to decompose and categorize the evolution of thousands if not millions of lipids involved in the phenomenon. The interpretation and analysis of Molecular Dynamics (MD) simulations representing temporal and spatial changes in such systems is still a challenging task. Here, we present a new unsupervised machine learning approach based on Nonnegative Matrix Factorization, called NMFk, that successfully extracts physically meaningful features from neighborhood profiles derived from coarse-grained MD simulations of ternary lipid mixture. Our results demonstrate that leveraging NMFk can (a) determine the role of different lipid molecules in phase separation, (b) characterize the formation of nano-domains of lipids, (c) determine the timescales of interest and (d) extract physically meaningful features that uniquely describe the phase separation with broad implications.

bioinformatics↗

bioRxiv2018

Molecular aspects of multivalent engagement between Syk and FcϵRIγ

Syk/Zap70 family kinases are essential for signaling via multichain immune-recognition receptors such as the tetrameric ({beta}{gamma}2) Fc{varepsilon}RI The simplest model assumes that Syk activation occurs through cis binding of its tandem SH2 domains to dual phosphotyrosines within immunoreceptor tyrosine-based activation motifs of individual {gamma} chains. In this model, Syk activity is modulated by phosphorylation occurring between adjacent Syk molecules docked on {gamma} homodimers and by Lyn molecules bound to Fc{varepsilon}RI{beta}. However, the mechanistic details of Syk docking on {gamma} homodimers are not fully resolved, particularly the possibility of trans binding orientations and the impact of Y130 autophosphorylation within Syk interdomain A. Analytical modeling shows that multivalent interactions lead to increased WT Syk cis-oriented binding by three orders of magnitude. Molecular dynamics (MD) simulations show increased inter-SH2 flexibility in a Y130E phosphomimetic form of Syk, associated with reduced overall helicity of interdomain A. Hybrid MD/worm-like chain polymer models show that the Y130E substitution reduces cis binding of Syk. We report computational models and estimates of relative binding for all possible cis and trans 2:2 Syk:Fc{varepsilon}RI{gamma} complexes. Calcium imaging experiments confirm model predictions that cis binding of WT Syk is strongly preferred for efficient signaling, while trans conformations trigger weak but measurable responses.

biophysics↗