Biology subjects

Kumar, A.

Publications and source records attributed to Kumar, A..

At least 343 records · Page 19Linked to original sources

bioRxiv2023

Identification of clade-specific single nucleotide polymorphisms for improved Rabies virus surveillance in Canis familiaris host

BackgroundRabies is an ancient disease that remains endemic in many countries. It causes many human deaths annually, predominantly in resource-poor countries. Over evolutionary timelines, several rabies virus (RABV) genotypes have stabilised, forming distinct clades. Extensive studies have been conducted on the origin, occurrence and spread of RABV clades. Single nucleotide polymorphisms (SNPs) distribution across the RABV genome and its clades remains largely unknown, highlighting the need for comprehensive whole-genome analyses. MethodsWe accessed whole genome sequences for RABV from public databases and identified SNPs across the whole genome sequences. Then, we annotated these SNPs using an R script, and these SNPs were categorised into different categories; universal, clade-specific, and clade-defining, based on the frequency of occurrence. ResultsIn this study, we present the SNPs occurring in the RABV based on whole genome sequences belonging to 8 clades isolated from 7 different host species likely to harbour dog-related rabies. We classified mutations into several classes based on their location within the genome and assessed the effect of SNP mutations on the viral glycoprotein. ConclusionsThe clade-defining mutations have implications for targeted surveillance and classification of clades. Additionally, we investigated the effects of these mutations on the Glycoprotein of the virus. Our findings contribute to expanding knowledge about RABV clade diversity and evolution, which has significant implications for effectively tracking and combatting RABV transmission.

microbiology↗

bioRxiv2023

Unravelling Genomic Origin of Lumpy Skin Disease Virus in Recent Outbreaks

Lumpy skin disease virus (LSDV) belongs to the genus Capripox virus and family Poxviridae. LSDV was endemic in most of Africa, Middle east and Turkey, but since 2015, several outbreaks have been reported in Asian countries. In this study we used Whole Genome Sequence (WGS) approach to investigate the origin of the outbreak and understand the genomic landscape of the virus. Our study showed that the LSDV strain of 2022 outbreak exhibited many genetic variations, compared to the Reference Neethling strain sequence and the previous field strains from India. A total of 1819 variations were found in 22 genome sequences, which includes 399 extragenic mutations, 153 insertion frameshift mutations, 234 deletion frameshift mutations, 271 Single nucleotide polymorphisms (SNPs) and 762 silent SNPs. 38 genes have more than 2 variations per gene and these genes belong to viral-core protein, viral binding proteins, replication and RNA polymerase proteins. We highlight the importance of several SNPs in various genes which may play an essential role in pathogenesis of LSDV. Phylogenetic analysis performed on all whole genome sequences of LSDV showed two types of variants in India. One group of the variant with fewer mutations was found to lie closer to the LSDV 2019 strain from Ranchi while the other group clustered with previous Russian outbreaks from 2015. Our study highlights the importance of genomic characterization of viral outbreaks to not only monitor the frequency of mutations but also address its role in pathogenesis of LSDV as the outbreak continues.

microbiology↗

bioRxiv2023

SC2Spa: a deep learning based approach to map transcriptome to spatial origins at cellular resolution

BackgroundUnderstanding cellular heterogeneity within tissues hinges on knowledge of their spatial context. However, it is still challenging to accurately map cells to their spatial coordinates. ResultsWe present SC2Spa, a deep learning-based approach that learns intricate spatial relationships from spatial transcriptomics (ST) data. Benchmarking tests show that SC2Spa outperformed other predictors and accurately detected tissue architecture from transcriptome. SC2Spa successfully mapped single cell RNA sequencing (scRNA-seq) to Visium assay, providing an approach to enhance the resolution for low resolution ST data. Our test showed that SC2Spa performs well for various ST technologies and robust to spatial resolution. In addition, SC2Spa can suggest spatially variable genes that cannot be identified from previous approaches. ConclusionsSC2Spa is a robust and accurate approach to provide single cells with their spatial location and identify spatially meaningful genes.

bioinformatics↗

bioRxiv2023

Thermodynamic Coupling of the tandem RRM domains of hnRNP A1 underlie its Pleiotropic RNA Binding Functions

The functional properties of RNA-binding proteins (RBPs) require allosteric regulation through inter-domain communication. Despite the foundational importance of allostery to biological regulation, almost no studies have been conducted to describe the biophysical nature by which inter-domain communication manifests in RBPs. Here, we show through high-pressure studies with hnRNP A1 that inter-domain communication is vital for the unique stability of its N- terminal domain containing a tandem of RNA Recognition Motifs (RRMs). Despite high sequence similarity and nearly identical tertiary structures, the two RRMs exhibit drastically different stability under pressure. RRM2 unfolds completely under high-pressure as an individual domain, but when appended to RRM1, it remains stable. Variants in which inter-domain communication is disrupted between the tandem RRMs show a large decrease in stability under pressure. Carrying these mutations over to the full-length protein for in vivo experiments revealed that the mutations affected the ability of the disordered C-terminus to engage in protein-protein interactions and more importantly, they also influenced the RNA binding capacity. Collectively, this work reveals that thermodynamic coupling between the tandem RRMs of hnRNP A1 accounts for its allosteric regulatory functions.

biochemistry↗

bioRxiv2023

BunDLe-Net: Neuronal Manifold Learning Meets Behaviour

Neuronal manifold learning techniques represent high-dimensional neuronal dynamics in low-dimensional embeddings to reveal the intrinsic structure of neuronal manifolds. A common goal of these techniques is to learn embeddings that allow a good reconstruction of the original data. We introduce a novel neuronal manifold learning technique, BunDLe-Net, that learns a low-dimensional Markovian embedding of the neuronal dynamics which pre-serves only those aspects of the neuronal dynamics that are relevant for a given behavioural context. In this way, BunDLe-Net eliminates neuronal dynamics that are irrelevant for decoding behaviour, effectively de-noising the data to reveal better the intricate relationships between neuronal dynamics and behaviour. We show that BunDLe-Net learns highly consistent manifolds across animals that reveal the building blocks of their neuronal manifolds on a variety of data sets, ranging from calcium imaging data recorded in the nematode C. elegans to spiking data from the rat hippocampus and primate somatosensory cortex.

animal behavior and cognition↗

bioRxiv2023

Discovery of a Well-Folded Protein Interaction Hub Within the Human Long Non-Coding RNA NORAD

The long non-coding RNA NORAD functions in maintaining genomic stability in humans via sequestering Pumilio proteins from the cytoplasm, and thereby modulating the gene expression of mRNA targets of Pumilio proteins. Despite its role in fundamental cellular pathways including chromosome segregation and DNA damage response, there have been limited structural and biophysical descriptions of NORAD. Here, using an integrative approach combining chemical probing coupled to high throughput sequencing, and RNA-pull downs coupled with mass spectrometry, we discovered a well-folded and structured protein interaction hub within the functional core of NORAD. Our in vitro biochemical reconstitutions using purified recombinant proteins and a NORAD repeat unit region within this hub reveal the assembly of a higher-order multimeric RNA-protein complex.

molecular biology↗

bioRxiv2023

PoxiPred: An artificial intelligence-based method for the prediction of potential antigens and epitopes to accelerate vaccine development efforts against poxviruses.

MotivationPoxviridae is a family of large, complex, enveloped, and double-stranded DNA viruses. Members of this family are ubiquitous and well known to cause contagious diseases in humans and other types of animals as well. Despite significant progress in Artificial intelligence (AI) based methods, limited methods are available to predict the epitopes. In this study, we have proposed a unique method to predict the potential antigens and T-cell epitopes for multiple poxviruses. ResultsWith PoxiPred, we developed an AI-based tool that was trained and tested with antigens and epitopes of Poxviruses. Our tool was able to locate 1,675 antigen proteins from 25 distinct poxviruses. From these antigenic proteins, PoxiPred also located 6,579 T-cell epitopes. PoxiPred is able to, on a single run, identify antigens and T-cell epitopes for poxviruses with one single input, i.e., the proteome file of any poxvirus. AvailabilityThe code that implements PoxiPred and the predicted antigens/T-cell epitopes is publicly available at https://github.com/gustavsganzerla/poxipred.

bioinformatics↗

bioRxiv2023

DNA tetrahedron as a carrier of doxorubicin for metastatic breast cancer treatment

Metastatic breast cancer is a significant clinical challenge calling for novel and efficient therapeutic approaches. DNA tetrahedron, a highly programmable nanocage, offers some promising attributes including biocompatibility, stability, and functionalization making it an attractive candidate for drug delivery. In this study, we have explored the potential of DNA tetrahedron as a carrier of doxorubicin, a DNA and RNA synthesis-inhibiting chemotherapy drug. We have encapsulated doxorubicin in DNA tetrahedron (TD: Dox) and subsequently focused on metastatic breast cancer cells for the effect of the same. We showed that TD: Dox has the potential to inhibit the migration of cancerous cells in the 2D model and inhibit the invasion of tumor cells in the 3D model as well. This system also can be uptaken in in vivo zebrafish model as well. Overall, this study promises the TD: Dox system as an ideal drug delivery model and a viable approach for metastatic breast cancer treatment.

bioengineering↗

bioRxiv2023

DeepMap: A deep learning-based model with four-line code for prediction-based breeding in crops

Prediction of phenotype through genotyping data using the emerging machine or deep learning technology has been proven successful in genomic prediction. We present here a graphical processing unit (GPU) enabled DeepMap configurable deep learning-based python package for the genomic prediction of quantitative phenotype traits. We found that deep learning captures non-linear patterns more efficiently than conventional statistical methods. Furthermore, we suggest an additional module inclusion of epistasis interactions and training of the model on Graphical Processing Units (GPUs) in addition to Central Processing Unit (CPU) to enhance efficiency and increase the models performance. We developed and demonstrated the application of DeepMap using a 3K rice genome panel and 1K-Rice Custom Amplicon (1kRiCA) data for several phenotypic traits including days to 50% flowering (DTF), number of productive tillers (NPT), panicle length (PL), plant height (PH), and plot yield (PY). We have found that DeepMap outperformed the best existing state-of-the-art models by giving higher predictive correlation and low mean squared error for the datasets studied. This prediction performance was higher than other compared models in the range of 13-31%. Similarly for Dataset-2, significantly higher predictions were observed than the compared models (16-20% higher prediction ability). On Dataset-3, we have also shown the better and versatile performance of our model across crops (wheat, maize, and soybean) for yield and yield-related traits. This demonstrates the potentiality of the framework and ease of use for future research in crop improvement. The DeepMap is accessible at https://test.pypi.org/project/DeepMap-1.0/. Short SummaryDeepMap is a deep learning-based breeder-friendly python package to perform genomic prediction. It utilizes epistatic interactions for data augmentation and outperforms the existing state-of-the-art machine/deep learning models such as Bayesian LASSO, GBLUP, DeepGS, and dualCNN. DeepMap developed for rice and tested across crops such as maize, wheat, soybean etc.

genomics↗

bioRxiv2023

In-silico identification, characterization, and expression analysis of RNA recognition motif (RRM) containing RNA binding proteins in Aedes aegypti

BackgroundRNA binding proteins (RBPs) are the proteins that bind RNAs and regulate their functioning. RBPs in mosquitoes are gaining attention due to their ability to bind flaviviruses and regulate their replication and transmission. Despite their relevance, RBPs in mosquitoes have not been explored much. In this study, we screened the whole genome of Aedes aegypti, the primary vector of several pathogenic viruses, and identified the proteins containing RNA recognition motif (RRM), the most abundant protein domain in eukaryotes. ResultsUsing several in-silico strategies, a total of 135 RRM containing RBPs were identified in Ae. aegypti. The proteins were characterized based on their available annotations and the sequence similarity with the Drosophila melanogaster. Ae. aegypti RRM containing RBPs included serine/arginine-rich (SR) proteins, polyadenylate binding proteins (PABP), heteronuclear ribonucleoproteins (hnRNP), small nuclear ribonucleoproteins (snRNP), splicing factors, eukaryotic initiation factors, transformers, nucleolysins, etc. Phylogenetic analysis revealed that the proteins and the domain organisation is conserved among Ae. aegypti, Bombyx mori and Drosophila melanogaster. However, the gene length and the intron-exon organisation varied across the insect species. Expression analysis of the genes encoding RBPs using publicly available RNA sequencing data for different developmental time points of the mosquito life cycle starting from the ovary and eggs up to the adults revealed stage-specific expression with several genes preferentially expressed in early embryonic stages and blood-fed female ovary. ConclusionsThis is the first database for the Ae. aegypti RBPs that can serve as the reference base for future investigations. The stage-specific genes can be further explored to determine their role in mosquito growth and development with a focus to develop novel mosquito control strategies.

bioinformatics↗

bioRxiv2023

Pharmacological Evaluations of Select Herbal Extracts on TLR7/8-induced Cytokine and Chemokine Production in Macrophage-like Cells

Inflammation is an innate immune response triggered by harmful stimuli, such as pathogens, tissue injury, or toxins. The purpose is to eliminate the source of infection and initiate the healing process. However, an excessive acute inflammatory response can lead to severe and life-threatening complications, as seen during recent pandemics. In the context of viral infections, the activation of the TLR7/8 signaling pathway has been implicated in excessive cytokine secretion. In this study, we aimed to replicate the perturbed inflammatory environment resulting from the activation of the TLR7/8 specific agonists, imiquimod, and resiquimod. We utilized macrophage-like cells, as macrophages are the first responders during infections and secrete key pro-inflammatory cytokines (TNF-, IL-6, and IL-1{beta}) to recruit immune cells to the site of infection. Herbal medicines have been traditionally used for centuries to enhance respiratory immune function. In the present study, we employed a prophylactic approach, where macrophage-like THP1 cells, differentiated with PMA, were pre-treated with select herbal extracts/formulations prior to TLR7/8 activation in the presence of agonists. Several medicinal plants and formulations known for their therapeutic potential in respiratory ailments were investigated, including Withania somnifera, Tinospora cordifolia, Glycyrrhiza glabra, and AYUSH-64, an herbal formulation. The gene expression and corresponding secreted levels of various inflammatory mediators were measured using RT-PCR and ELISA methods, respectively, in treated and untreated differentiated THP1 cells induced with TLR7/8 agonists. Comparatively, the gene expression of inflammatory markers was significantly higher in resiquimod-induced cells than in imiquimod-treated cells. Notably, Withania somnifera demonstrated pronounced prophylactic efficacy compared to other herbs/formulations, as evidenced by reduction in expression of majority of investigated inflammatory marker genes.

pharmacology and toxicology↗

bioRxiv2023

Peripheral linker mediates ACP's recognition of DH and stabilizes Mycobacterium tuberculosis FAS-I

1Incomplete structural details of Mycobacterium tuberculosis (Mtb) fatty acid synthase-I (FAS-I) at near-atomic resolution have limited our understanding of the shuttling mechanism of its mobile acyl carrier protein (ACP). Here, we have performed atomistic molecular dynamics simulation of Mtb FAS- I with a homology-modelled structure of ACP stalled at dehydratase (DH), and identified key residues that mediate anchoring of the recognition helix of ACP near DH. The observed distance between catalytic residues of ACP and DH agrees with that reported for fungal FAS-I. Further, the conformation of the peripheral linker is found to be crucial in stabilizing ACP near DH. Correlated inter-domain motion is observed between DH, enoyl reductase (ER) and malonyl/palmitoyl transferase (MPT); consistent with prior experimental reports of fungal and Mtb FAS-I.

biophysics↗

bioRxiv2023

Prolonged Kaposi's Sarcoma-associated Herpesvirus vIL-6 Exposure Enhances Inflammatory Responses by Epigenetic Reprogramming

Kaposi sarcoma-associated herpesvirus (KSHV) inflammatory cytokine syndrome (KICS) is a newly described chronic inflammatory disease condition caused by KSHV infection and is characterized by high KSHV viral load and sustained elevations of serum KSHV-encoded IL-6 (vIL-6) and human IL-6 (hIL-6). KICS has significant immortality and possesses greater risks of having other complications, which include malignancies. Although prolonged inflammatory vIL-6 exposure by persistent KSHV infection is expected to have key roles in subsequent disease development, the biological effects of prolonged vIL-6 exposure remain elusive. Using thiol-Linked Alkylation for the Metabolic Sequencing and Cleavage Under Target & Release Using Nuclease analysis, we studied the effect of prolonged vIL-6 exposure in chromatin landscape and resulting cytokine production. The studies showed that prolonged vIL-6 exposure increased Bromodomain containing 4 (BRD4) and histone H3 lysine 27 acetylation co-occupancies on chromatin, and the recruitment sites were frequently co-localized with poised RNAPII with associated enzymes. Increased BRD4 recruitment on promoters was associated with increased and prolonged NF-KB p65 binding after the lipopolysaccharide stimulation. The p65 binding resulted in quicker and sustained transcription bursts from the promoters; this mechanism increased total amounts of hIL-6 and IL-10 in tissue culture. Pretreatment with the BRD4 inhibitor, OTX015, eliminated the enhanced inflammatory cytokine production. These findings suggest that persistent vIL-6 exposure may establish a chromatin landscape favorable for the reactivation of inflammatory responses in monocytes. This epigenetic memory may explain the greater risk of chronic inflammatory disease development in KSHV-infected individuals. Author summaryCombined and continuous cytokine stimulation triggers transcription reprogramming and is often used for specific tissue development. Continuous vIL-6 exposure occurs in KSHV-infected patients and leads to inflammatory cytokine storm with high mortality. However, possible epigenetic reprogramming by the vIL-6 and its association with pathogenesis remain unclear. Here we demonstrate the establishment of a new chromatin landscape mediated by BRD4 through prolonged vIL-6 exposure which contributes to more robust and rapid transcription and increased cytokines production. Inhibition of BRD4 suppressed this inflammatory response. Our results indicate that targeting the epigenetic effect of viral cytokines may lead to novel therapies for KSHV-induced inflammatory cytokine storms.

microbiology↗

bioRxiv2023

Tomosyns attenuate SNARE assembly and synaptic depression by binding to VAMP2-containing template complexes

Tomosyns are soluble SNARE proteins proposed to attenuate membrane fusion by competing with synaptobrevin-2/VAMP2 for SNARE-complex assembly. Here, we present evidence against this scenario using a novel mouse model, energy barrier recordings, and single-molecule force measurements. Tomosyn-1/2 deficiency drastically enhanced the probability that synaptic vesicles fuse at synapses, resulting in stronger synapses with faster depression and slower recovery. While wildtype tomosyn-1m rescued these phenotypes, substitution of its SNARE motif with that of synaptobrevin-2/VAMP2 did not. Force measurements revealed that tomosyns SNARE motif cannot substitute synaptobrevin-2/VAMP2 to form template complexes with Munc18-1 and syntaxin-1, an essential intermediate for SNARE assembly. Instead, tomosyns bind synaptobrevin-2/VAMP2-containing template complexes and prevent SNAP-25 association. Structure-function analyses indicate that regions outside the SNARE motif contribute to tomosyns inhibitory function. These results reveal that tomosyns regulate synaptic transmission by preventing SNAP-25 binding to template complexes, increasing the energy barrier for synaptic vesicle fusion, and limiting synaptic depression.

neuroscience↗

bioRxiv2023

Dopamine functionalized, red carbon quantum dots for in vivo bioimaging, cancer therapeutics, and neuronal differentiation

One of the crucial requirements of quantum dots for biological applications is their surface modifications for very specific and enhanced biological recognition and uptake. Toward this, we present the green synthesis of bright, red-emitting carbon quantum dots derived from mango leaf extract (mQDs). These mQDs are conjugated electrostatically with dopamine to form mQDs-dopamine (mQDs: DOPA) bioconjugates. Bright red fluorescence of mQDs was used for bioimaging and uptake in multiple cell lines, tissues, and in vivo models like zebrafish. mQDs exhibited the highest uptake in brain tissue as compared to others. mQD:DOPA conjugate induced cellular toxicity only in cancer cells while showing increased uptake in epithelial cells and zebrafish. Additionally, the mQDs: DOPA promoted neuronal differentiation of SH-SY5Y cells to complete neurons. Both mQDs and mQDs: DOPA exhibited potential for higher collective cell migrations implicating their future potential as next-generation tools for advanced biological and biomedical applications. TOCmQDs were electrostatically conjugated with dopamine (DOPA) to form the mQDs: DOPA bioconjugate. mQDs are used to image cells, tissues, and zebrafish embryos. mQDs: DOPA kills cancer cells, differentiates neuronal cells, and increases the uptake of mQDs in zebrafish embryos. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=116 SRC="FIGDIR/small/545347v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@f521a4org.highwire.dtl.DTLVardef@173a8f0org.highwire.dtl.DTLVardef@585271org.highwire.dtl.DTLVardef@8c959d_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2023

Antibodies against Elapidae and Viperidae snake venoms: in vivo neutralization and mechanistic insights

Snake envenomation results in a range of clinical sequelae, and effective therapy is yet to be discovered. Anti-snake venom antibodies are being considered as a potent strategy. We developed venom-neutralizing humanized antibody scFvs and elucidated biochemical and structural mechanisms associated with the inhibition of toxicity. Tomlinson I and J human antibody scFv libraries were screened against Naja naja and Echis carinatus venoms, and seven unique antibody scFvs were obtained. Further, specific toxins of snake venom interacting with each of these scFvs were identified, and phospholipase A2 (PLA2) was found to be prominently captured by the phage-anchored antibody scFvs. Proteomic analysis of whole venom also revealed PLA2 to be the most abundant toxin in both venom samples. The scFvs binding to PLA2 were used to perform in vivo survival assay using the mouse model and in vitro toxin inhibition assays. scFv N194, which binds to acidic PLA2, showed considerable survival in Naja naja venom-challenged mice and conferred up to 50% protection. A combination of two scFvs, E113 and E10, both interacting with basic PLA2, exhibited synergistically enhanced survival of 33% in Echis carinatus venom-challenged mice, compared to 16% survival conferred by an equal amount of individual scFvs. Furthermore, these scFvs demonstrated inhibition of venom-induced myotoxicity and hemolysis which corroborate the survival data. Structural studies highlighted possible modes of PLA2 neutralization by scFv through the engagement of CDRs with C-terminal myotoxic loop and interfacial region, which are crucial for PLA2 toxicity.

biochemistry↗

bioRxiv2023

Deep-learning Based Pathological Assessment of Frozen Procurement Kidney Biopsies Predicts Graft Loss and Guides Organ Utilization: A Large-scale Retrospective Study

BackgroundLesion scores on procurement donor biopsies are commonly used to guide organ utilization. However, frozen sections present challenges for histological scoring, leading to inter- and intra-observer variability and inappropriate discard. MethodsWe constructed deep-learning based models to recognize kidney tissue compartments in H&E stained sections from procurement biopsies performed at 583 hospitals nationwide in year 2011-2020. The models were trained and tested respectively on 11473 and 3986 images sliced from 100 slides. We then extracted whole-slide abnormality features from 2431 kidneys, and correlated with pathologists scores and transplant outcomes. Finally, a Kidney Donor Quality Score (KDQS) incorporating digital features and the Kidney Donor Profile Index (KDPI) was derived and used in combination with recipient demographic and peri-transplant characteristics to predict graft loss or assist organ utilization. ResultsOur model accurately identified 96% and 91% of normal/sclerotic glomeruli respectively; 94% of arteries/arterial intimal fibrosis regions; 90% of tubules. Three whole-slide features (Sclerotic Glomeruli%, Arterial Intimal Fibrosis%, and Interstitial Fibrosis%) demonstrated strong correlations with corresponding pathologists scores (n=2431), but had superior associations with post-transplant eGFR (n=2033) and graft loss (n=1560). The combination of KDQS and other factors predicted 1- and 4-year graft loss (discovery: n=520, validation: n=1040). Finally, by matching 398 discarded kidneys due to "biopsy findings" to transplanted population, the matched transplants from discarded KDQS<4 group (110/398, 27.6%) showed similar graft survival rate to unmatched transplanted kidneys (2-, 5-year survival rate: 97%, 86%). KDQS [≥] 7 (37/398, 9.3%) and 1-year survival model score [≥] 0.55 were determined to identify possible discards (PPV=0.92). ConclusionThis deep-learning based approach provides automatic and reliable pathological assessment of procurement kidney biopsies, which could facilitate graft loss risk stratification and organ utilization. Translational StatementThis deep-learning based approach provides rapid but more objective, sensitive and reliable assessment of deceased-donor kidneys before transplantation, and improves the prognostic value of procurement biopsies, thus could potentially reduce inappropriate discard and stratify patients needing monitoring or preventative measures after transplantation. The pipeline can be integrated into various types of scanners and conveniently generates report after slide scanning. Such report can be used in conjunction with pathologists report or independently for centers lacking renal pathologists.

bioinformatics↗

bioRxiv2023

Recalibration of protein interactions in Martini 3

Multidomain proteins with flexible linkers and disordered regions play important roles in many cellular processes, but characterizing their conformational ensembles is diffcult. We have previously shown that the coarse-grained model, Martini 3, produces too compact ensembles in solution, that may in part be remedied by strengthening protein-water interactions. Here, we show that decreasing the strength of protein-protein interactions leads to improved agreement with experimental data on a wide set of systems. We show that the symmetry between rescaling protein-water and protein-protein interactions breaks down when studying interactions with or within membranes; rescaling protein-protein interactions better preserves the binding specificity of proteins with lipid membranes, whereas rescaling protein-water interactions preserves oligomerization of transmembrane helices. We conclude that decreasing the strength of protein-protein interactions improves the accuracy of Martini 3 for IDPs and multidomain proteins, both in solution and in the presence of a lipid membrane.

biophysics↗