Biology subjects

Shen, X.

Publications and source records attributed to Shen, X..

At least 145 records · Page 8Linked to original sources

bioRxiv2023

Pan-genome and Haplotype Map of Cultivars and Their Wild Ancestors Provides Insights into Adaptive Evolution of Cassava (Manihot esculenta Crantz)

Cassava is the most important starch sources, a tropical model crop. We constructed nearly T2T genomes of cultivar AM560, wild ancestors FLA4047 and W14, pan-genome of 24 representatives and a clarified evolutionary tree with 486 accessions. Comparison of SVs and SNVs between the ancestors and cultivated cassavas revealed predominant expansion, contraction of genes and gene families. Significantly selective sweeping occurred in the cassava genomes in 122 footprints with 1,519 candidate domestication genes. We identified selective mutations in MeCSK and MeFNR3 promoting photoreaction associated with MeNADP-ME of C4 assimilation in modern cassava. Co-evolved retardation of floral primordia and initiation of storage roots arose from MeCOL5 mutants with altered bindings to MeFT1, MeFT2 and MeTFL2. MebHLHs evolved to regulate the biosynthesis, transport and endogenous remobilization of cyanogenic glucosides, with new functionalities of MeMATE1, MeGTR in selected sweet cassava. These findings enhanced comprehensive knowledge and database on the evolution and breeding of cassava. HIGHLIGHTSO_LIThree nearly T2T cassava genomes of cultivar AM560 and its wild ancestors FLA4047 and W14. C_LIO_LIA species-level cassava panSV haplotype map across 346,322 structural variations over 31,362 gene families and 96,032,008 SNPs and InDels variations globally and a clarified evolutionary tree with 486 accessions. C_LIO_LISelective mutations in MeCSK and MeFNR3 promoted photoreaction associated with MeNADP-ME of C4 assimilation shaped the C3-C4 intermediate photosynthesis of modern cassava. C_LIO_LICoevolution of floral primordia contrary to initiated storage root is pivotal for the domestication of cassava, and arose from MeCOL5 mutants altered the binding with MeFT1, MeFT2 (SP6A), and MeTFL2. C_LI

systems biology↗

bioRxiv2023

Human Immune Cell Epigenomic Signatures in Response to Infectious Diseases and Chemical Exposures

The epigenomic landscape of human immune cells is dynamically shaped by both genetic factors and environmental exposures. However, the relative contributions of these elements are still not fully understood. In this study, we employed single-nucleus methylation sequencing and ATAC-seq to systematically explore how pathogen and chemical exposures, along with genetic variation, influence the immune cell epigenome. We identified distinct exposure-associated differentially methylated regions (eDMRs) corresponding to each exposure, revealing how environmental factors remodel the methylome, alter immune cell states, and affect transcription factor binding. Furthermore, we observed a significant correlation between changes in DNA methylation and chromatin accessibility, underscoring the coordinated response of the epigenome. We also uncovered genotype-associated DMRs (gDMRs), demonstrating that while eDMRs are enriched in regulatory regions, gDMRs are preferentially located in gene body marks, suggesting that exposures and genetic factors exert differential regulatory control. Notably, disease-associated SNPs were frequently colocalized with meQTLs, providing new cell-type-specific insights into the genetic basis of disease. Our findings underscore the intricate interplay between genetic and environmental factors in sculpting the immune cell epigenome, offering a deeper understanding of how immune cell function is regulated in health and disease.

genomics↗

bioRxiv2023

YAP/TAZ enhance P-body formation to promote tumorigenesis

The role of Processing bodies (P-bodies) in tumorigenesis and tumor progression is not well understood. Here, we showed that the oncogenes YAP/TAZ promote P-body formation in a series of cancer cell lines. Mechanistically, both transcriptional activation of the P- body-related genes SAMD4A, AJUBA, and WTIP and transcriptional suppression of the tumor suppressor gene PNRC1 are involved in enhancing the effects of YAP/TAZ on P- body formation in CRC cells. By reexpression of PNRC1 or knockdown of P-body core genes (DDX6, DCP1A, and LSM14A), we determined that disruption of P-bodies attenuates cell proliferation, cell migration and tumor growth induced by overexpression of YAP5SA in CRC. Analysis of a pancancer CRISPR screen database (DepMap) revealed codependencies between YAP/TEAD and the P-body core genes and correlations between the mRNA levels of SAMD4A, AJUBA, WTIP, PNRC1 and YAP target genes. Our study suggests that the P-body is a new downstream effector of YAP/TAZ, which implies that reexpression of PNRC1 or disruption of P-bodies is a potential therapeutic strategy for tumors with active YAP.

cell biology↗

bioRxiv2023

Electrophysiological Representations of Multivariate Human Emotion Experience

Despite the fact that human daily emotions are co-occurring by nature, most neuroscience studies have primarily adopted a univariate approach to identify the neural representation of emotion (emotion experience within a single emotion category) without adequate consideration to the co-occurrence of different emotions (emotion experience across different emotion categories simultaneously). To investigate the neural representations of multivariate emotion experience, this study employed the inter-situation representational similarity analysis (RSA) method. Researchers used an EEG dataset of 78 participants who watched 28 video clips and rated their experience on eight emotion categories. The EEG-based electrophysiological representation was extracted as the power spectral density (PSD) feature per channel in the five frequency bands. The inter-situation RSA method revealed significant correlations between the multivariate emotion experience ratings and PSD features in the Alpha and Beta bands, primarily over the frontal and parietal-occipital brain regions. The study found the identified EEG representations to be reliable with sufficient situations and participants. Moreover, through a series of ablation analyses, the inter-situation RSA further demonstrated the stability and specificity of the EEG representations for multivariate emotion experience. These findings highlight the importance of adopting a multivariate perspective for a comprehensive understanding of neural representation of human emotion experience.

neuroscience↗

bioRxiv2023

Lipid-anchored Proteasomes Control Membrane Protein Homeostasis

Protein degradation in eukaryotic cells is mainly carried out by the 26S proteasome, a macromolecular complex not only present in the cytosol and nucleus but also associated with various membranes. How proteasomes are anchored to the membrane and the biological meaning thereof have been largely unknown in higher organisms. Here we show that N-myristoylation of the Rpt2 subunit is a general mechanism for proteasome-membrane interaction. Loss of this modification in the Rpt2-G2A mutant cells leads to profound changes in the membrane-associated proteome, perturbs the endomembrane system and undermines critical cellular processes such as cell adhesion, endoplasmic reticulum-associated degradation (ERAD) and membrane protein trafficking. Rpt2G2A/G2A homozygous mutation is embryonic lethal in mice and is sufficient to abolish tumor growth in a nude mice xenograft model. These findings have defined an evolutionarily conserved mechanism for maintaining membrane protein homeostasis and underscored the significance of compartmentalized protein degradation by myristoyl-anchored proteasomes (MAPs) in health and disease.

biochemistry↗

bioRxiv2023

Asparagine synthetase and G-protein coupled estrogen receptor are critical responders to nutrient supply in KRAS mutant colorectal cancer

The nutrient status of the tumor microenvironment has major impacts on cell growth. Under nutrient depletion, asparagine synthetase (ASNS)-mediated asparagine production increases to sustain cell survival. G protein-coupled estrogen receptor-1 (GPER1) signaling converges via cAMP/PI3K/AKT with KRAS signaling to regulate ASNS expression. However, the role of GPER1 in CRC progression is still debated, and the effect of nutrient supply on both ASNS and GPER1 relative to KRAS genotype is not well understood. Here, we modeled a restricted nutrient supply by eliminating glutamine from growing cancer cells in a 3D spheroid model of human female SW48 KRAS wild-type (WT) and KRAS G12A mutant (MT) CRC cells, to examine effects on ASNS and GPER1 expression. Glutamine depletion significantly inhibited cell growth in both KRAS MT and WT cells; however, ASNS and GPER1 were upregulated in KRAS MT compared to WT cells. When nutrient supply was adequate, ASNS and GPER1 were not altered between cell lines. The impact of estradiol, a ligand for GPER1, was examined for any additional effects on cell growth. Under glutamine deplete conditions, estradiol decreased the growth of KRAS WT cells but had no effect on KRAS MT cells; estradiol had no additive or diminutive effect on the upregulation of ASNS or GPER1 between the cell lines. We further examined the association of GPER1 and ASNS levels with overall survival in a clinical colon cancer cohort of The Cancer Genome Atlas. Both high GPER1 and ASNS expression associated with poorer overall survival for females only in advanced stage tumors. These findings suggest that KRAS MT cells have mechanisms in place that respond to decreased nutrient supply, typically observed in advanced tumors, by increasing the expression of ASNS and GPER1 to drive cell growth. Furthermore, KRAS MT cells are resistant to the protective effects of estradiol under nutrient deplete conditions. ASNS and GPER1 may therefore be potential therapeutic targets that can be exploited to manage and control KRAS MT CRC.

cancer biology↗

bioRxiv2023

Dynamics of the epigenetic landscape during development and in response to drought stress in sorghum

Sorghum bicolor is a C4 plant with the characteristics of high stress tolerance, which may be conferred partly by the underlying epigenetic mechanism unique to sorghum. In this study, we revealed some epigenomic features in sorghum that have never been reported before. The long H3K27me3 regions clustered in four areas, which we defined as H3K27me3 islands, were identified in sorghum. H3K36me3 plays some role in inhibiting the deposition of both H3K27me3 and H2A.Z, which may serve as partial motivation for the removal of H3K27me3 and H2A.Z in leaf and root. All the 7 histone marks are involved in the regulation of tissue-specific genes, especially the specific expression of C4 genes in leaf and peroxidase (POD) encoding genes in root, which are involved in the photosynthesis in leaf and lignin synthesis in root, respectively. These marks except H3K36me3 and H3K27me3 also engage in the regulation of stress genes in response to PEG treatment. However, we found that differential enrichment of histone marks on many tissue-specific genes was observed only between leaf and root but hardly in response to PEG treatment, although expression of these genes changed after PEG treatment.

plant biology↗

bioRxiv2023

General and specific patterns of cortical gene expression as substrates of complex cognitive functioning

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given genes expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components : gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 41 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|{beta}| range = 0.15 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.

neuroscience↗

bioRxiv2023

Discovery of decreased ferroptosis in male colorectal cancer patients with KRAS mutations

Aberrant tumor metabolism is a hallmark of cancer in which metabolic rewiring can support tumor growth under nutrient deficient conditions. KRAS mutations occur in 35-45% of all colorectal cancer (CRC) cases and are difficult to treat. The relationship between mutant KRAS and aberrant metabolism in CRCs has not been fully explored and could be a target for intervention. We previously acquired non-targeted metabolomics data from 161 tumor tissues and 39 normal colon tissues from stage I-III chemotherapy naive CRC patients. In this study, we revealed that tumors from male patients with KRAS mutations only, had several altered pathways that suppress ferroptosis, including glutathione biosynthesis, transsulfuration activity, and methionine metabolism. To validate this phenotype, MC38 CRC cells (KRASG13R) were treated with a ferroptosis inducer; RAS-selected lethal (RSL3). RSL3 altered metabolic pathways in the opposite direction to that seen in KRAS mutant tumors from male patients confirming a suppressed ferroptosis metabolic phenotype in these patients. We further validated gene expression data from an additional CRC patient cohort (Gene Expression Omnibus (GEO), and similarly observed differences in ferroptosis-related genes by sex and KRAS status. Further examination of the relationship between these genes and overall survival (OS) in the GEO cohort showed that KRAS mutant tumors are associated with poorer 5-year OS compared to KRAS wild type tumors, and only in male patients. Additionally, high compared to low expression of GPX4, FTH1, FTL, which suppressed ferroptosis, were associated with poorer 5-year OS only in KRAS mutant tumors from male CRC patients. Low compared to high expression of ACSL4 was associated with poorer OS for this group. Our results show that KRAS mutant tumors from male CRC patients have suppressed ferroptosis, and gene expression changes that suppress ferroptosis associate with adverse outcomes for these patients, revealing a novel potential avenue for therapeutic approaches.

cancer biology↗

bioRxiv2023

Inferring a directed acyclic graph of phenotypes from GWAS summary statistics

SO_SCPLOWUMMARYC_SCPLOWEstimating phenotype networks is a growing field in computational biology. It deepens the understanding of disease etiology and is useful in many applications. In this study, we present a method that constructs a phenotype network by assuming a Gaussian linear structure model embedding a directed acyclic graph (DAG). We utilize genetic variants as instrumental variables and show how our method only requires access to summary statistics from a genome-wide association study (GWAS) and a reference panel of genotype data. Besides estimation, a distinct feature of the method is its summary statistics-based likelihood ratio test on directed edges. We applied our method to estimate a causal network of 29 cardiovascular-related proteins and linked the estimated network to Alzheimers disease (AD). A simulation study was conducted to demonstrate the effectiveness of this method. An R package sumdag implementing the proposed method, all relevant code, and a Shiny application are available at https://github.com/chunlinli/sumdag.

molecular biology↗

bioRxiv2023

Development of a Robust Consensus Modeling Approach for Identifying Cellular and Media Metabolites Predictive of Mesenchymal Stromal Cell Potency

Mesenchymal stromal cells (MSCs) have shown promise in regenerative medicine applications due in part to their ability to modulate immune cells. However, MSCs demonstrate significant functional heterogeneity in terms of their immunomodulatory function because of differences in MSC donor/tissue source, as well as non-standardized manufacturing approaches. As MSC metabolism plays a critical role in their ability to expand to therapeutic numbers ex vivo, we comprehensively profiled intracellular and extracellular metabolites throughout the expansion process to identify predictors of immunomodulatory function (T cell modulation and indoleamine-2,3-dehydrogenase (IDO) activity). Here, we profiled media metabolites in a non-destructive manner through daily sampling and nuclear magnetic resonance (NMR), as well as MSC intracellular metabolites at the end of expansion using mass spectrometry (MS). Using a robust consensus machine learning approach, we were able to identify panels of metabolites predictive of MSC immunomodulatory function for 10 independent MSC lines. This approach consisted of identifying metabolites in 2 or more machine learning models and then building consensus models based on these consensus metabolite panels. Consensus intracellular metabolites with high predictive value included multiple lipid classes (such as phosphatidylcholines, phosphatidylethanolamines, and sphingomyelins) while consensus media metabolites included proline, phenylalanine, and pyruvate. Pathway enrichment identified metabolic pathways significantly associated with MSC function such as sphingolipid signaling and metabolism, arginine and proline metabolism, and autophagy. Overall, this work establishes a generalizable framework for identifying consensus predictive metabolites that predict MSC function, as well as guiding future MSC manufacturing efforts through identification of high potency MSC lines and metabolic engineering.

bioengineering↗

bioRxiv2023

Phenome-wide analysis identifies parent-of-origin effects on the human methylome associated with changes in the rate of aging

Variation in the rate at which humans age may be rooted in early life events acting through genomic regions that are influenced by such events and subsequently are related to health phenotypes in later life. The parent-of-origin-effect (POE)-regulated methylome includes regions either enriched for genetically controlled imprinting effects (the typical type of POE) or atypical POE introduced by environmental effects associated with parents. This part of the methylome is heavily influenced by early life events, making it a potential route connecting early environmental exposures, the epigenome and the rate of aging. Here, we aim to test the association of POE-influenced methylation of CpG dinucleotides (POE-CpG sites) with early and later environmental exposures and subsequently with health-related phenotypes and adult aging phenotypes. We do this by performing phenome-wide association analyses of the POE-influenced methylome using a large family-based population cohort (GS:SFHS, Ndiscovery=5,087, Nreplication=4,450). At the single CpG level, 92 associations of POE-CpGs with phenotypic variation were identified and replicated. Most of the associations were contributed by POE-CpGs belonging to the atypical class and the most strongly enriched associations were with aging (DNAmTL acceleration), intelligence and parental (maternal) smoking exposure phenotypes. We further found that a proportion of the atypical-POE-CpGs formed co-methylation networks (modules) which are associated with these phenotypes, with one of the aging-associated modules displaying increased internal module connectivity (strength of methylation correlation across constituent CpGs) with age. Atypical POE-CpGs also displayed high levels of methylation heterogeneity and epigenetic drift (i.e. information loss with age) and a strong correlation with CpGs contained within epigenetic clocks. These results identified associations between the atypical-POE-influenced methylome and aging and provided new evidence for the "early development of origin" hypothesis for aging in humans.

genetics↗

bioRxiv2023

An efficient context-aware approach for whole slide image classification

Computational pathology for gigapixel whole slide images (WSIs) at slide-level is helpful in disease diagnosis and remains challenging. We propose a context-aware approach termed WSI Inspection via Transformer (WIT) for slide-level classification via holistically modeling dependencies among patches on the WSI. WIT automatically learns feature representation of WSI by aggregating features of all image patches. We evaluate classification performance of WIT along with state-of-the-art baseline method. WIT achieved an accuracy of 82.1% (95% CI, 80.7% - 83.3%) in the detection of 32 cancer types on the TCGA dataset, 0.918 (0.910 - 0.925) in diagnosis of cancer on the CPTAC dataset and 0.882 (0.87 - 0.890) in the diagnosis of prostate cancer from needle biopsy slide, outperforming the baseline by 31.6%, 5.4% and 9.3%, respectively. WIT can pinpoint the WSI regions that are most influential for its decision. WIT represents a new paradigm for computational pathology, facilitating the development of effective tools for digital pathology.

pathology↗

bioRxiv2022

Connectome-based predictive modeling shows sex differences in brain-based predictors of memory performance

Alzheimers disease (AD) takes a more aggressive course in women than men, with higher prevalence and faster progression. Amnestic AD specifically targets the default mode network (DMN), which subserves short-term memory; past research shows relative hyperconnectivity in the posterior DMN in aging women. Higher reliance on this network during memory tasks may contribute to womens elevated AD risk. Here, we applied connectome-based predictive modeling (CPM), a robust linear machine-learning approach, to the Lifespan Human Connectome Project-Aging (HCP-A) dataset (n=579). We sought to characterize sex-based predictors of memory performance in aging, with particular attention to the DMN. Models were evaluated using cross-validation both across the whole group and for each sex separately. Whole-group models predicted short-term memory performance with accuracies ranging from {rho}=0.21-0.45. The best-performing models were derived from an associative memory task-based scan. Sex-specific models revealed significant differences in connectome-based predictors for men and women. DMN activity contributed more to predicted memory scores in women, while within- and between-visual network activity contributed more to predicted memory scores in men. While men showed more segregation of visual networks, women showed more segregation of the DMN. We demonstrate that women and men recruit different circuitry when performing memory tasks, with women relying more on intra-DMN activity and men relying more on visual circuitry. These findings are consistent with the hypothesis that women draw more heavily upon the DMN for recollective memory, potentially contributing to womens elevated risk of AD.

neuroscience↗

bioRxiv2022

Functional network organization of the mouse cortex determined by wide-field fluorescence imaging shares some --but not all-- properties revealed with simultaneous fMRI-BOLD

Work in humans and animals shows that the brain can be decomposed into large-scale functional networks. Whereas most studies, especially in humans, use the blood-oxygenation-level-dependent (BOLD) signal, the relationship between BOLD and neuronal activity is complex and incompletely understood. This limits our ability to interpret and apply measures derived from fMRI-BOLD. Here, we employ wide-field Ca2+ imaging simultaneously recorded with fMRI-BOLD in highly-sampled mice expressing GCaMP6f in excitatory neurons. These unique data enabled us to characterize the similarities and differences between networks discoverable by each modality. Importantly, we applied a network partitioning approach that uses a mixed-membership algorithm, which allows brain regions to participate in multiple networks with varying strengths. This contrasts with assuming regions belong to only one network. Our findings demonstrate that (1) most BOLD networks are detected via Ca2+ signals. (2) There is considerable overlapping--as opposed to disjoint--network organization that is evident from both modalities. (3) Large-scale networks determined by Ca2+ signals at low temporal frequencies (0.01 - 0.5 Hz)--as opposed to higher frequencies (0.5 - 5 Hz)--are more similar to those determined by BOLD. (4) Despite many similarities, differences emerge across modes including the spatial distribution of membership diversity (the extent to which regions affiliate with multiple networks). In sum, Ca2+ imaging of excitatory neurons confirms that the mouse cortex is functionally organized into overlapping large-scale networks in a manner that reflects many, but not all, properties observable with simultaneous fMRI-BOLD; affirming the neural origins of patterns of brain organization that are evident in a clinically accessible neuroimaging modality.

neuroscience↗

bioRxiv2022

Organism-wide secretome mapping uncovers pathways of tissue crosstalk in exercise

There has been growing interest in identifying blood-borne factors that mediate tissue crosstalk and function as molecular effectors of physical activity. Although past studies have focused on an individual molecule or cell type, the organism-wide secretome response to physical activity has not been evaluated. Here, we use a cell type-specific proteomic approach to generate a 21-cell type, 10-tissue map of exercise-regulated secretomes in mice. Our dataset identifies >200 exercise-regulated cell type-secreted protein pairs, the majority of which have not been previously reported. Pdgfra-cre-labeled secretomes were the most responsive to exercise training. Elevated lactate levels can directly regulate protein secretion. Lastly, we establish an anti-obesity and anti-diabetic role for a proteoform of an intracellular carboxylesterase whose secretion from the liver is induced by exercise training. Together, our data uncover the dynamic remodeling of cell and tissue crosstalk by physical activity.

systems biology↗

bioRxiv2022

Deep Learning-based Feature Extraction with MRI Data in Neuroimaging Genetics for Alzheimer's Disease

The prognosis and treatment of the patients suffering from Alzheimers disease (AD) have been one of the most important and challenging problems over the last few decades. To better understand the mechanism of AD, it is of great interest to identify genetic variants associated with brain atrophy. Commonly in these analyses, neuroimaging features are extracted based on one of many possible brain atlases with FreeSurf and other popular softwares, which however may lose important information due to our incomplete knowledge about brain function embedded in these suboptimal atlases. To address the issue, we propose convolutional neural network (CNN) models applied to three-dimensional MRI data for the whole brain or multiple divided brain regions to perform completely data-driven and automatic feature extraction. These image-derived features are then used as endophenotypes in Genome-Wide Association Studies (GWAS) to identify associated genetic variants. When applied to the ADNI data, we identified several associated SNPs which have been previously shown to be related to several neurodegenerative/mental disorders such as AD, depression and schizophrenia. Code and supplementary materials are available at https://github.com/Dipnil07. The codes have been implemented using Python, R and Plink softwares.

bioinformatics↗

bioRxiv2022

Gating interactions steer loop conformational changes in the active site of the L1 metallo-β-lactamase

{beta}-lactam antibiotics are the most important and widely used antibacterial agents across the world. However, the widespread dissemination of {beta}-lactamases among pathogenic bacteria limits the efficacy of {beta}-lactam antibiotics. This has created a major public health crisis. The use of {beta}-lactamase inhibitors has proven useful in restoring the activity of {beta}-lactam antibiotics, yet, effective clinically approved inhibitors against class B metallo-{beta}-lactamases (MBLs) are not available. L1, a class B3 enzyme expressed by Stenotrophomonas maltophilia, is a significant contributor to the {beta}-lactam resistance displayed by this opportunistic pathogen. Structurally, L1 is a tetramer with two elongated loops, 3-{beta}7 and {beta}12-5, present around the active site of each monomer. Residues in these two loops influence substrate/inhibitor binding. To study how the conformational changes of the elongated loops affect the active site in each monomer, enhanced sampling molecular dynamics (MD) simulations were performed, Markov State Models (MSM) were built, and convolutional variational autoencoder (CVAE)-based deep learning was applied. The key identified residues (D150a, H151, P225, Y227, R236) were mutated and the activity of the generated L1 variants was evaluated in cell-based experiments. The results demonstrate that there are extremely significant gating interactions between 3-{beta}7 and {beta}12-5 loops. Taken together, the gating interactions with the conformational changes of the key residues play an important role in the structural remodeling of the active site. These observations offer insights into the potential for novel drug development exploiting these gating interactions.

biophysics↗