Biology subjects

Sagar, A.

Publications and source records attributed to Sagar, A..

17 recordsLinked to original sources

bioRxiv2025

Interplay Between Intrinsically Disordered Proteins and Atomically Precise Gold Nanoclusters Modulates their Optical Properties

Understanding how structural and optical properties of metallic nanoclusters can be tuned by proteins is crucial for the use of these hybrid molecules in biomedical applications. The interaction of proteins with ultrasmall, atomically-precise gold nanoclusters (Au-NCs) has been mainly investigated in the context of structured proteins, while their behavior with intrinsically disordered proteins (IDPs) remains unexplored. This work examines the structural and optical properties of Au-NCs interacting with bioengineered IDPs containing up to three cysteines. We show that, by exploiting the conformational flexibility of cysteine-containing IDPs, we can anchor proteins to Au-NCs in a position-specific manner, leading to new bioconjugates with properties that differ from those of the individual components. We observed an up to 15-fold photoluminescence enhancement depending on the number of cysteines anchored. By combining mass spectrometry, small-angle X-ray scattering (SAXS), and computational modelling, the ensemble structures of nine bioconjugates with different stoichiometries were elucidated, indicating their overall compactness. Our results suggest that the interface between these atomically-precise species and the conformationally fluctuating protein is responsible for the optical properties of these nanobioconjugates. This research improves our understanding of Au-NC- protein interactions, paving the way to novel nano-molecular hybrid conjugates with tunable properties for bioimaging and therapeutic applications.

biochemistry↗

bioRxiv2025

New structural insights into the control of the retinoic acid receptors RAR/RXR by DNA, ligands and transcriptional coregulators

Retinoic acid receptors (RARs) are ligand-dependent transcription factors essential for various biological processes, including embryogenesis, differentiation, and apoptosis. RARs function as heterodimers with retinoid X receptors (RXRs) and regulate gene expression via retinoic acid response elements (RAREs). Their transcriptional activity is modulated by coregulators, with corepressors maintaining repression in the absence of ligand and coactivators enabling transcription upon ligand binding. Structural studies reveal that DNA binding induces conformational changes affecting coregulator interactions. However, the precise structural organization of RAR/RXR-coregulator complexes and the allosteric influence of DNA on receptor function remain incompletely understood. Our study presents an integrative analysis of the RAR/RXR heterodimer bound to four distinct and relevant RAREs (DR0, DR1, DR5, and IR0) in complex with either a corepressor (NCoR) or a coactivator (TIF-2) nuclear receptor interaction domain. By combining small-angle X-ray scattering, hydrogen/deuterium exchange mass spectrometry and molecular dynamics simulations, we revealed that the heterodimer adopts distinct conformations depending on the DNA sequence, influencing interdomain distances and receptor interactions. Additionally, we uncovered the dynamic interplay between ligand, DNA, and coregulator binding. This study provides new insights into the structural features of coregulator proteins and highlights the allosteric influence of RAREs on receptor function.

biochemistry↗

bioRxiv2024

VISUALIZING THE NUCLEATING AND CAPPED STATES OF F-ACTIN BY Ca2+-GELSOLIN: SAXS DATA BASED STRUCTURES OF BINARY AND TERNARY COMPLEXES

Structural insight eludes on how full-length gelsolin depolymerizes and caps F-actin, while the same entity can nucleate polymerization of G-actins. Employing small angle X-ray scattering (SAXS) data analysis, we deciphered these two contrasting assemblies. Mixing Ca2+-gelsolin with F-actin in high salt F-buffer resulted in depolymerization of ordered F-actin rods to smaller sized species which became monodisperse upon dialysis with low salt G-buffer. These entities were the ternary (GA2) and binary (GA) complexes of gelsolin and actin with radius of gyration and maximum linear dimension of 4.55 and 4.68 nm, and 15 and 16 nm, respectively. In contrast, upon mixing G-actin with Ca2+-gelsolin in G-buffer, rapid association of higher order species started. Using size exclusion chromatography in-line with SAXS, we confirmed that initially GA and GA2 species are formed as seen upon depolymerization of F-actin, followed by dialysis. Interestingly, while GA2 could seed formation of native-like F-actin in both G- and F-buffer, GA failed in G-buffer. Thus, GA2 and GA are the central species formed via depolymerization or towards nucleation. SAXS profile referenced modeling revealed that: 1) in GA, actin is bound to the C-terminal half of gelsolin, and 2) in GA2, second actin binds to the open N-terminal half accompanied by dramatic rearrangements across gelsolins g1-g2 and g3-g4 linkers. Importantly, first structural insight is provided into the two probable models for GA2 with two actins in parallel, but differentially stacked: one in polymerization competent, and other in incompetent manner, suggesting latter to represent capped state along with the inert GA. TOC Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=129 SRC="FIGDIR/small/584204v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@9b7ab4org.highwire.dtl.DTLVardef@194d85aorg.highwire.dtl.DTLVardef@108151dorg.highwire.dtl.DTLVardef@1a24e88_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIOrderly decrement in the length of F-actin by Ca2+-gelsolin was tracked by SAXS. C_LIO_LIResidual re-association in 1:2 ratio in F-buffer was quenched by dialysis in G-buffer. C_LIO_LIIdentical GA and GA2 entities formed upon mixing F- or G-actin with Ca2+-gelsolin. C_LIO_LIModels of nucleation competent, GA2 showed differential stacking of two G-actins. C_LIO_LIN-terminal half of gelsolin reposition as GA2 changes to or from GA, the capped state. C_LI

biophysics↗

bioRxiv2023

Phosphorylation motif dictates GPCR C-terminal domain conformation and arrestin interaction

Arrestin dependent G protein-coupled receptor (GPCR) signaling pathway is regulated by the phosphorylation state of GPCRs C-terminal domain, but the molecular bases of arrestin:receptor interaction are to be further illuminated. Here we investigated the impact of phosphorylation on the conformational features of the C-terminal region from three Rhodopsin-like GPCRs, the vasopressin V2 Receptor (V2R), the Growth Hormone Secretagogue or ghrelin Receptor type 1a (GHSR) and the {beta}2-Adernergic Receptor ({beta}2AR). Using phosphomimetic variants, we identified pre-formed secondary structure elements, or short linear motif (SLiMs), that undergo specific conformational transitions upon phosphorylation. Of importance, such conformational transition favors arrestin-2 binding. Hence, our results suggest a model in which the cellular signaling specificity of GPCRs is encoded in the phosphorylation-dependent structuration of the C-terminal regions, which will subsequently modulate arrestin conformation and therefore GPCR:arrestin signaling outcomes.

biophysics↗

bioRxiv2022

WASCO: A Wasserstein-based statistical tool to compare conformational ensembles of intrinsically disordered proteins

The structural investigation of intrinsically disordered proteins (IDPs) requires ensemble models describing the diversity of the conformational states of the molecule. Due to their probabilistic nature, there is a need for new paradigms that understand and treat IDPs from a purely statistical point of view, considering their conformational ensembles as well-defined probability distributions. In this work, we define a conformational ensemble as an ordered set of probability distributions and provide a suitable metric to detect differences between two given ensembles at the residue level, both locally and globally. The underlying geometry of the conformational space is properly integrated, being one ensemble characterized by a set of probability distributions supported on the three-dimensional Euclidean space (for global-scale comparisons) and on the two-dimensional flat torus (for local-scale comparisons). The inherent uncertainty of the data is also taken into account to provide finer estimations of the differences between ensembles. Additionally, an overall distance between ensembles is defined from the differences at the residue level. We illustrate the interest of the approach with several examples of applications for the comparison of conformational ensembles: (i) produced from molecular dynamics (MD) simulations using different force fields, and (ii) before and after refinement with experimental data. We also show the usefulness of the method to assess the convergence of MD simulations. The numerical tool has been implemented in Python through easy-to-use Jupyter Notebooks available at https://gitlab.laas.fr/moma/WASCO.

bioinformatics↗

bioRxiv2022

The structure of pathogenic huntingtin exon-1 defines the bases of its aggregation propensity

Huntingtons Disease is a neurodegenerative disorder caused by a CAG expansion of the first exon of the HTT gene, resulting in an extended poly-glutamine (poly-Q) tract in the N-terminus of the protein huntingtin (httex1). The structural changes occurring to the poly-Q when increasing its length remain poorly understood mainly due to its intrinsic flexibility and the strong compositional bias of the protein. The systematic application of site-specific isotopic labeling has enabled residue-specific NMR investigations of the poly-Q tract of pathogenic httex1 variants with 46 and 66 consecutive glutamines. The integrative analysis of the data reveals that the poly-Q tract adopts long -helical conformations stabilized by glutamine side-chain to backbone hydrogen bonds. 19F-NMR of site-specifically incorporated fluoro-glutamines and molecular dynamics simulations demonstrate that the mechanism propagating -helical conformations towards the poly-Q from the upstream N17 domain is independent of the poly-Q track length. Aggregation and atomic force microscopy experiments show that the presence of long and persistent -helices in the poly-Q tract is a stronger signature in defining the aggregation kinetics and the structure of the resulting fibrils than the number of glutamines. The ensemble of our observations provides a structural perspective of the pathogenicity of expanded httex1 and paves the way to a deeper understanding of poly-Q related diseases.

biophysics↗

bioRxiv2022

Tip-links serve as force-pass filter to fulfil the role of gating-springs

Tip-links as gating-spring in the mechanotransduction in hearing is still a debate. While the molecular elasticity of individual tip-link proteins warrants its candidature, the apparent rigidity from the heterotetrameric tip-links assembly refutes the claim. Using force-clamp experiments and simulations, we report that the heterotetrameric assembly is the natural selection for the gating-springs. Tip-links follow slip-ideal-slip bonds with increasing force. While in slip, the complex dissociates monotonously, ideal-bond interface responds indifferently to various auditory inputs. Insensitivity to forces renders tip-links as low-force pass filter, characteristic of gating-spring. Individual tip-links, however, forms slip-catch-slip bonds under tension. While catch bonds turn stronger with force from loud sound, our Langevin dynamics indicated the transition from slip-catch to slip-ideal bonds as cooperative effect of the dimers of individual protein complexes in tip-links. From molecular dynamics, we deciphered the molecular mechanism of catch bonds and its importance in deafness.

biophysics↗

bioRxiv2022

Cis-clustering of cadherin-23 controls the kinetics of cell-cell adhesion

Cis and trans-interactions among cadherins secure multicellularity. While the molecular structure of trans-interactions of cadherins is well understood, identifying the molecular cues that spread the cis-interactions two-dimensionally is still ongoing. Here, we report that transient, weak, multivalent, and spatially distributed hydrophobic interactions, requisite for liquid-liquid phase separations of biomolecules in solution, alone can drive the lateral-clustering of cadherin-23 on a membrane. No specific cis-dimer interactions are required for the lateral clustering. In cellulo, the cis-clustering accelerates the cell-cell adhesion and, thus, contributes in cell-adhesion kinetics along with strengthening the junction. Although the physiological connection of cis-clustering with rapid adhesion is yet to be explored, M2-macrophages that predominantly express cadherin-23 undergo fast attachments to circulatory tumor cells during metastasis.

cell biology↗

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

Molecular and cellular insight into Escherichia coli SslE and its role during biofilm maturation

Escherichia coli is a Gram-negative bacterium that colonizes the human intestine and virulent strains can cause severe diarrhoeal and extraintestinal diseases. The protein SslE is secreted by a range of pathogenic and some commensal E. coli strains. It can degrade mucins in the intestine, promotes biofilm maturation and it is a major determinant of infection in virulent strains, although how it carries out these functions is not well understood. Here we examine SslE from the E. coli Waksman and H10407 strains and reveal that it has a novel and dynamic structure. In response to acidification within mature biofilms we show how SslE forms a unique functional aggregate that interacts with cellulose and regulates the distribution of exopolysaccharides in macrocolony biofilms. Our data indicates that the spatial organization of SslE polymers and local pH are critical for biofilm maturation and SslE is a key factor that drives persistence of SslE-secreting bacteria during acidic stress.

microbiology↗

bioRxiv2020

On Using Transfer Learning For Plant Disease Detection

Deep neural networks has been highly successful in image classification problems. In this paper, we show how neural networks can be used for plant disease recognition in the context of image classification. We have used publicly available Plant Village dataset which has 38 classes of diseases. Hence, the problem that we have addressed is a multi class classification problem. We compared five different architectures including VGG16, ResNet50, InceptionV3, InceptionResNet and DenseNet169 as the backbones for our work. We found that ResNet50 achieves the best result on the test set. For evaluation, we used metrics: accuracy, precision, recall, F1 score and class wise confusion metric. Our model achieves the best of results using ResNet50 with accuracy of 0.982, precision of 0.94, recall of 0.94 and F1 score of 0.94.

plant biology↗

bioRxiv2020

Convolutional Neural Networks for ClassifyingMelanoma Images

In this work, we address the problem of skin cancer classification using convolutional neural networks. A lot of cancer cases early on are misdiagnosed leading to severe consequences including the death of patient. Also there are cases in which patients have other problems and doctors interpret it as skin cancer. This leads to unnecessary time and money spent for further diagnosis. In this work, we address both of the above problems using deep neural networks and transfer learning architecture. We have used publicly available ISIC databases for both training and testing our network. Our model achieves an accuracy of 0.935, precision 0.94, recall 0.77, F1 score 0.85 and ROC-AUC 0.861 which is better than the previous state of the art approaches.

cancer biology↗

bioRxiv2019

Broken force dispersal network in tip-links by the mutations induces hearing-loss

Tip-link as force-sensor in the hearing conveys the mechanical force originating from sound to ion-channels while maintaining the integrity of the entire sensory assembly in inner-ear. This delicate balance between structure and function of tip-links is regulated by Ca2+-ions present in endolymph. Mutations at the Ca2+-binding sites of tip-links often lead to congenital deafness, sometimes syndromic defects impairing vision along with hearing. Although such mutations are already identified, it is still not clear how the mutants alter the structure-function properties of the force-sensors associated with diseases. With an aim to decipher the differences in force-conveying properties of the force-sensors in molecular details, we identified the conformational variability of mutant and wild-type tip-links at the single-molecule level using FRET at the endolymphatic Ca2+ concentrations and subsequently measured the force-responsive behavior using single-molecule force spectroscopy with an AFM. AFM allowed us to mimic the high and wide range of force ramps (103 - 106 pN.s-1) as experienced in the inner ear. We performed in silico network analyses to learn that alterations in the conformations of the mutants interrupt the natural force-propagation paths through the sensors and make the mutant tip-links vulnerable to input forces from sound stimuli. We also demonstrated that a Ca2+ rich environment can restore the force-response of the mutant tip-links which may eventually facilitate the designing of better therapeutic strategies to the hearing loss.\n\nSignificance StatementForce-sensors in inner ear are the key components in the hearing. Mutations in force-sensors often lead to congenital hearing loss. Loss of hearing has become a threat to humanity, with over 5% of world population suffering from deafness and 40% of which is congenital, primarily due to mutations in the sensory machinery in inner-ear. A better understanding of the molecular mechanism of the underlined hearing loss due to mutations is, therefore, necessary for better therapeutics to deaf. Here with a zoomed region of the force-sensors, we pointed out the differences in the force-propagation properties of the mutant and wild-type force-sensors. Our observation on restoring of functions of mutants in Ca2+-rich buffer indicates methods of developing low-cost therapeutic strategies against deafness.

biophysics↗

bioRxiv2017

Dynamic Optimization with Particle Swarms (DOPS): A meta-heuristic for parameter estimation in biochemical models

BackgroundMathematical modeling is a powerful tool to analyze, and ultimately design biochemical networks. However, the estimation of the parameters that appear in biochemical models is a significant challenge. Parameter estimation typically involves expensive function evaluations and noisy data, making it difficult to quickly obtain optimal solutions. Further, biochemical models often have many local extrema which further complicates parameter estimation. Toward these challenges, we developed Dynamic Optimization with Particle Swarms (DOPS), a novel hybrid meta-heuristic that combined multi-swarm particle swarm optimization with dynamically dimensioned search (DDS). DOPS uses a multi-swarm particle swarm optimization technique to generate candidate solution vectors, the best of which is then greedily updated using dynamically dimensioned search.\n\nResultsWe tested DOPS using classic optimization test functions, biochemical benchmark problems and real-world biochemical models. We performed [Formula] trials with [Formula] function evaluations per trial, and compared the performance of DOPS with other commonly used meta-heuristics such as differential evolution (DE), simulated annealing (SA) and dynamically dimensioned search (DDS). On average, DOPS outperformed other common meta-heuristics on the optimization test functions, benchmark problems and a real-world model of the human coagulation cascade.\n\nConclusionsDOPS is a promising meta-heuristic approach for the estimation of biochemical model parameters in relatively few function evaluations. DOPS source code is available for download under a MIT license at http://www.varnerlab.org.

systems biology↗

bioRxiv2017

Atypical domain communication and domain functions of a Hsp110 chaperone

Hsp110s are well recognized nucleotide exchange factors (NEFs) of Hsp70s, in addition they are implicated in various aspects of cellular proteostasis as discrete chaperones with yet enigmatic molecular mechanism. Stark similarity in domain organization and structure between Hsp110s and Hsp70s, is easily discernible although the nature of domain communication and domain functions of Hsp110s are still puzzling. Here, we report atypical domain communication of yeast Hsp110, Sse1 using single molecule FRET, small angle X-ray scattering measurements (SAXS) and Molecular Dynamic simulations. Our data show that Sse1 lacks typical domain movements as exhibited by Hsp70s, albeit it undergoes unique structural alteration upon nucleotide and substrate binding. Hsp70-like domain-movements can be artificially salvaged in chimeric constructs of Hsp110-Hsp70 although such salvaging proves detrimental for the NEF activity of the protein. Furthermore, we show that substrate binding domain (SBD) of Hsp110, chaperones self, as well as foreign nucleotide binding domains (NBD). Interestingly, the substrate binding specificity of Hsp110 is largely determined by its NBD rather than SBD, the latter being the foremost substrate binding region for Hsp70s.

biochemistry↗

bioRxiv2017

Molecular mechanism of cell-cell adhesion mediated by cadherin-23

Adherin-junctions are traditionally described by the homophilic-interactions of classical cadherin-proteins at the extracellular region. However, the role of long-chain non-classical cadherins like cadherin-23(Cdh23) is not explored as yet even though it is implicated in tissue-morphogenesis, cancer, and force-sensing in neuronal tissues. Here, we identified a novel antiparallel-binding interface of Cdh23 homodimer in solution by combining biophysical and computational methods, in-vitro cell-binding, and mutational modifications. The dimer consists of two electrostatic-based interfaces extended up to two terminal domains, atypical to classical-cadherins known so far, and forms the strongest interactions in cadherin-family as measured using single-molecule force-spectroscopy. We further identified single point-mutation, E78K, that completely disrupts this binding. Interestingly, the mutation, S77L, found in skin cancers falls within the binding interface of the antiparallel-dimer. Overall, we provide the molecular architecture of Cdh23 at the cell-cell junctions which are likely to have far-reaching applications in the fields of mechanobiology and cancer.

biophysics↗

bioRxiv2017

An Effective Model Of The Retinoic Acid Induced HL-60 Differentiation Program

In this study, we present an effective model All-Trans Retinoic Acid (ATRA)-induced differentiation of HL-60 cells. The model describes reinforcing feedback between an ATRA-inducible signalsome complex involving many proteins including Vav1, a guanine nucleotide exchange factor, and the activation of the mitogen activated protein kinase (MAPK) cascade. We decomposed the effective model into three modules; a signal initiation module that sensed and transformed an ATRA signal into program activation signals; a signal integration module that controlled the expression of upstream transcription factors; and a phenotype module which encoded the expression of functional differentiation markers from the ATRA-inducible transcription factors. We identified an ensemble of effective model parameters using measurements taken from ATRA-induced HL-60 cells. Using these parameters, model analysis predicted that MAPK activation was bistable as a function of ATRA exposure. Conformational experiments supported ATRA-induced bistability. Additionally, the model captured intermediate and phenotypic gene expression data. Knockout analysis suggested Gfi-1 and PPAR$[gamma] were critical to the ATRA-induced differentiation program. These findings, combined with other literature evidence, suggested that reinforcing feedback is central to hyperactive signaling in a diversity of cell fate programs.

systems biology↗