Biology subjects

Mandal, N.

Publications and source records attributed to Mandal, N..

11 recordsLinked to original sources

bioRxiv2026

The hearing-essential intracellular domain of PCDH15 reveals a new layer of auditory mechanotransduction

Current models of mechanotransduction in inner-ear hair cells explain how force is transmitted through the extracellular tip link but provide little insight into how force is propagated beneath the plasma membrane. Although the CD2 isoform of PCDH15 has been shown to be essential for hearing in mature mammalian hair cells, its structural and mechanical properties have remained largely unknown. Here, we combine computational sequence analysis, orthogonal biophysical characterization and small-angle X-ray scattering (SAXS) to show that the hearing-essential CD2 intracellular domain is an intrinsically disordered region (IDR) that behaves as a highly expanded acidic polyampholyte. CD2 remains predominantly monomeric in solution and occupies a larger conformational space at physiological-like ionic strength, whereas inclusion of the isoform-shared common region increases self-association. CD2 also contains a conserved regulatory interaction platform, providing a potential link between its polymer properties and cellular regulation. Together, these findings identify the CD2 intracellular domain as a polymer with biophysical properties consistent with a mechanically responsive structural element. Furthermore, they provide a framework for investigating how intracellular polymer mechanics may contribute to force transmission and adaptation in auditory mechanotransduction.

biophysics↗

bioRxiv2025

Muscle Energy Crisis is the Initial Driver of Locomotor Dysfunction in β-glucuronidase-Deficient Drosophila

Mucopolysaccharidosis type VII (MPS VII) is characterised by progressive locomotor decline, attributed to musculoskeletal and neurological defects. However, the severity varies according to the extent of {beta}-glucuronidase ({beta}-GUS) deficiency, with musculoskeletal deformities typically preceding neurological manifestations. To investigate the underlying cause of neuromuscular pathology, we employed {beta}-GUS-deficient Drosophila models. In Drosophila, {beta}-GUS is encoded by two genes, CG2135 and CG15117. Previously generated CG2135-/- flies recapitulated several hallmark features of MPS VII, despite retaining approximately 30% residual {beta}-GUS activity contributed by CG15117. To assess the consequences of complete loss of {beta}-GUS, we now generated CG15117-/- flies using CRISPR/Cas9 and subsequently established CG15117-/-;CG2135-/- double knockout (DKO) flies. Phenotypic assessment revealed differences in susceptibility to starvation, lifespan, and locomotor function, with DKO flies exhibiting more severe impairments than either single knockout flies. Notably, CG15117-/- did not show any significant defect in lifespan or locomotion, except under starvation conditions. Consistent with our earlier finding in CG2135-/- fly brains, ATP depletion in DKO fly brains became evident only after 45 days of age, failing to explain the locomotory defects observed in earlier ages. Interestingly, analysis of muscles of 30-day-old CG2135-/- and DKO flies revealed abnormal mitochondrial accumulation with autophagy defect and severe ATP depletion. Consequently, these defects led to locomotor impairment driven by apoptotic muscle degeneration. Collectively, this work provides the first evidence of tissue-specific vulnerability in MPS VII models, identifying muscle as an early pathological target and offering new insights into disease progression.

cell biology↗

bioRxiv2024

Benchmarking coarse-grained simulation methods for investigation of transport tunnels in enzymes

Enzymes are pivotal to numerous biological processes, often featuring buried active sites linked to the surrounding solvent through intricate and dynamic tunnels. These tunnels are vital for facilitating substrate access, enabling product release, and regulating solvent exchange, which collectively influence enzymatic function and efficiency. Consequently, knowledge of tunnels is key for a holistic understanding of the effect of mutations as well as predicting drug residence times. Unfortunately, most transport tunnels are transient, i.e., equipped by molecular gates, rendering their opening a rare event that is often notoriously hard to study with conventional molecular dynamics simulations. To overcome the sampling limitation of such simulations, this study investigated the efficacy of three different coarse-grained (CG) molecular dynamics simulation methods for inferring enzyme tunnel structure and dynamics. Here, we covered the Martini and SIRAH models with different restraint protocols providing stability to CG proteins while to some extent biasing the sampling towards a reference structure. By contrasting CG results with all-atom simulations, we benchmarked the ability of CG methods to replicate ensemble characteristics of complex tunnel networks in haloalkane dehalogenase LinB and two of its mutants with engineered tunnel networks. The assessed tunnel parameters are essential for prioritizing functionally relevant tunnels and delineating the effect of mutations on transport tunnels. Our findings reveal that while CG methods significantly enhance the efficiency of tunnel analyses, some of them, like Martini with Elastic network restraints, were limited in recapitulating all-atom tunnel dynamics due to the structural bias applied. In contrast, the Martini G[o] model even captured the intricate details of mutation perturbing tunnel dynamics. All studied CG methods performed well in capturing the geometry of tunnel ensembles in line with all-atom simulations. Additionally, the wider applicability of CG methods was verified by analyzing tunnel networks of nine enzymes from different combinations of structural and functional classes, demonstrating their potential to uncover new tunnel phenomena and validate their utility in broader biological and functional contexts. This comprehensive evaluation underscores the strengths and constraints of CG simulations in capturing enzyme tunnels and benefiting from their computational speed for studying huge datasets of enzymes. These insights are valuable for enzyme engineering, drug design, and understanding enzyme function while benefitting from the efficiency of coarse-grained models.

bioinformatics↗

bioRxiv2024

Crowder induced conformational fluctuations modulate the phase separation of yeast SUP35 NM domain

Intrinsically disordered proteins (IDPs) like Sup35NM can undergo liquid-liquid phase separation (LLPS) to form biomolecular condensates, a process influenced by their conformational flexibility and the crowded intracellular environment. This study investigates how molecular crowding, specifically the size and shape of crowders like Dextran and Ficoll, modulates the conformational states and phase separation behavior of Sup35NM. Using fluorescence correlation spectroscopy (FCS) and molecular dynamics simulations, we observed that Dextran, depending on its molecular weight, induces both compaction and expansion of Sup35NM, driving phase separation at certain thresholds. Notably, rod-like Dextran crowders promote phase separation, while spherical Ficoll does not, highlighting the impact of crowder geometry on IDP behavior. Computational modelling further revealed that the crowder shape influences Sup35NMs conformational ensemble by modulating intra- and inter-domain interactions. These findings elucidate the role of crowding agents in IDP phase behavior, suggesting that cellular crowding may regulate IDP functionality through conformational control.

biophysics↗

bioRxiv2024

Unravelling a mechanistic link between mitophagy defect, mitochondrial malfunction, and apoptotic neurodegeneration in MPS VII

Progressive neurodegeneration and cognitive disability are prominent symptoms of MPS VII, a lysosomal storage disorder caused by {beta}-glucuronidase enzyme deficiency. Yet, the mechanism of neurodegeneration in MPS VII remains elusive thereby limiting the scope of targeted intervention. To address this, we recently developed a {beta}-glucuronidase-deficient (CG2135-/-) Drosophila model of MPS VII. The CG2135-/- flies exhibited signs of neuromuscular degeneration, including loss of dopaminergic neurons, and accumulated engorged lysosomes, ubiquitinated proteins and mitochondria in their brains. These observations, coupled with our current finding that the CG2135-/- flies were highly susceptible to starvation, prompted us to investigate potential defects in the autophagy-lysosomal clearance machinery in the brain. We found that both autophagy induction and lysosome-mediated autophagosomal turnover were impaired in the CG2135-/- fly brain. This was evidenced by lower Atg8a-II levels, reduced Atg1 and Ref(2)P expression along with accumulation of lipofuscin-like inclusions and multilamellar bodies. Interestingly, mitophagy was also found to be defective in their brain, causing buildup of enlarged mitochondria with distorted cristae and reduced membrane potential. This, in turn, affected mitochondrial function as reflected by drastically reduced brain ATP levels. Energy depletion triggered apoptosis in neuronal as well as non-neuronal cells of the CG2135-/- fly brain, where we also detected apoptotic dopaminergic neurons. Resveratrol treatment, previously found to protect against loss of dopaminergic neurons in the CG2135-/- flies, has now been shown act by correcting the mitophagy defect and preventing ATP depletion. Collectively, our study establishes a causal link between mitophagy defect, mitochondrial malfunction, and apoptotic neurodegeneration in MPS VII.

cell biology↗

bioRxiv2024

Reinforcing Tunnel Network Exploration in Proteins using Gaussian Accelerated Molecular Dynamics

Tunnels are structural conduits in biomolecules responsible for transporting chemical compounds and solvent molecules to and from the active site. They have been shown to be present in a wide variety of enzymes across all functional and structural classes. However, the study of such pathways is experimentally challenging because they are typically transient. Computational methods such as molecular dynamics (MD) simulations have been successfully proposed to explore tunnels. Conventional MD (cMD) provides structural details to characterize tunnels but suffers from sampling limitations to capture rare tunnel openings on longer timescales. Therefore, in this study, we explored the potential of Gaussian accelerated MD (GaMD) simulations to improve the exploration of complex tunnel networks in enzymes. We used the haloalkane dehalogenase LinB and its two variants with engineered transport pathways, which are not only well-known for their application potential but have also been extensively studied experimentally and computationally regarding their tunnel networks and their importance in multi-step catalytic reactions. Our study demonstrates that GaMD efficiently improves tunnel sampling and allows the identification of all known tunnels for LinB and its two mutants. Furthermore, the improved sampling provided insight into a previously unknown transient side tunnel (ST). The extensive conformational landscape explored by GaMD simulations allowed us to investigate in detail the mechanism of ST opening. We determined variant-specific dynamic properties of ST opening, which were previously inaccessible due to limited sampling of cMD. Our comprehensive analysis supports multiple indicators of the functional relevance of the ST, emphasizing its potential significance beyond structural considerations. In conclusion, our research proves that the GaMD method can overcome the sampling limitations of cMD for the effective study of tunnels in enzymes, providing further means for identifying rare tunnels in enzymes with potential for drug development, precision medicine, and rational protein engineering.

bioinformatics↗

bioRxiv2023

The role of sphingosine-1-phosphate receptor 2 in mouse retina light responses

The bioactive sphingolipid sphingosine-1-phosphate (S1P) acts as a ligand for a family of G protein-coupled S1P receptors (S1PR1-5) to participate in a variety of signaling pathways. However, their specific roles in the neural retina remain unclear. We previously showed that S1P receptor subtype 2 (S1PR2) is expressed in murine retinas, primarily in photoreceptors and bipolar cells, and its expression is altered by retinal stress. This study aims to elucidate the role of S1PR2 in the mouse retina. We examined light responses by electroretinography (ERG), structural differences by optical coherence tomography (OCT), and protein levels by immunohistochemistry (IHC) in wild-type (WT) and S1PR2 knockout (KO) mice at various ages between 3 and 6 months. We found that a- and b-wave responses significantly increased at flash intensities between 400[~]2000 and 4[~]2,000 cd.s/m2 respectively, in S1PR2 KO mice relative to those of WT controls at baseline. S1PR2 KO mice also exhibited significantly increased retinal nerve fiber layer (RNFL) and outer plexiform layer (OPL) thickness by OCT relative to the WT. Finally, in S1PR2 KO mice, we observed differential labeling of synaptic markers by immunohistochemistry (IHC) and quantitative reverse transcription polymerase chain reaction (RT-qPCR). These results suggest a specific involvement of S1PR2 in the structure and synaptic organization of the retina and a potential role in light-mediated functioning of the retina.

physiology↗

bioRxiv2021

Scanning the RBD-ACE2 molecular interactions in Omicron variant

The emergence of new SARS-CoV-2 variants poses a threat to the human population where it is difficult to assess the severity of a particular variant of the virus. Spike protein and specifically its receptor binding domain (RBD) which makes direct interaction with the ACE2 receptor of the human has shown prominent amino acid substitutions in most of the Variants of Concern. Here, by using all-atom molecular dynamics simulations we compare the interaction of Wild-type RBD/ACE2 receptor complex with that of the latest Omicron variant of the virus. We observed a very interesting diversification of the charge, dynamics and energetics of the protein complex formed upon mutations. These results would help us in understanding the molecular basis of binding of the Omicron variant with that of SARS-CoV-2 Wild-type. TOC Graphics O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/472253v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@1e35dceorg.highwire.dtl.DTLVardef@23a441org.highwire.dtl.DTLVardef@1f4b7e3org.highwire.dtl.DTLVardef@1549a1c_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2021

Molecular Insights into the Differential Dynamics of SARS-CoV-2 Variants of Concern (VOCs)

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has affected the lives and livelihood of millions of individuals around the world. It has mutated several times after its first inception, with an estimated two mutations occurring every month. Although we have been successful in developing vaccines against the virus, emergence of variants has enabled it to escape therapy. Few of the generated variants are also reported to be more infectious than the wild-type (WT). In this study, we analyze the attributes of all RBD/ACE2 complexes for the reported VOCs, namely, Alpha, Beta, Gamma, and Delta through computer simulations. Results indicate differences in orientation and binding energies of the VOCs from the WT. Overall, it was observed that electrostatic interactions play a major role in the binding of the complexes. Detailed residue level energetics revealed that the most prominent changes in interaction energies were seen particularly at the mutated residues which were present at RBD/ACE2 interface. We found that the Delta variant is one of the most tightly bound variants of SARS-CoV-2 with dynamics similar to WT. High binding affinity of RBD towards ACE2 is indicative of an increase in the viral transmission and infectivity. The details presented in our study would prove extremely useful for the design and development of effective therapeutic strategies for the emerging variants of the virus.

biophysics↗

bioRxiv2021

How does temperature affect the dynamics of SARS-CoV-2 M proteins? Insights from Molecular Dynamics Simulations

Enveloped viruses, in general, have several transmembrane proteins and glycoproteins, which assist the virus in entry and attachment onto the host cells. These proteins also play a significant role in determining the shape and size of the newly formed virus particles. The lipid membrane and the embedded proteins affect each other in non-trivial ways during the course of the viral life cycle. Unravelling the nature of the protein-protein and protein-lipid interactions, under various environmental and physiological conditions, could therefore prove to be crucial in development of therapeutics. Here, we study the M protein of SARS-CoV-2 to understand the effect of temperature on the properties of the protein-membrane system. The membrane embedded dimeric M proteins were studied using atomistic and coarse-grained molecular dynamics simulations at temperatures ranging between 10 and 50 {degrees}C. While temperature induced fluctuations should be monotonic, we observe a steady rise in the protein dynamics up to 40 {degrees}C, beyond which it surprisingly reverts back to the low temperature behaviour. Detailed investigation reveals disordering of the membrane lipids in the presence of the protein, which induces additional curvature around the transmembrane region. Coarse-grained simulations indicate temperature dependent aggregation of M protein dimers. Our study clearly indicates that the dynamics of membrane lipids and integral M protein of SARS-CoV-2 enables it to better associate and aggregate only at a certain temperature range (i.e., ~30 to 40 {degrees}C). This can have important implications in the protein aggregation and subsequent viral budding/fission processes.

biophysics↗

bioRxiv2021

TransportTools: a library for high-throughput analyses of internal voids in biomolecules and ligand transport through them

Information regarding pathways through voids in biomolecules and their roles in ligand transport is critical to our understanding of the function of many biomolecules. Recently, the advent of high-throughput molecular dynamics simulations has enabled the study of these pathways, and of rare transport events. However, the scale and intricacy of the data produced requires dedicated tools in order to conduct analyses efficiently and without excessive demand on users. To fill this gap, we developed the TransportTools, which allows the investigation of pathways and their utilization across large, simulated datasets. TransportTools also facilitates the development of custom-made analyses. TransportTools is implemented in Python3 and distributed as pip and conda packages. The source code is available at https://github.com/labbit-eu/transport_tools.

bioinformatics↗