Protein Stability Analysis Research Articles

Identification and analysis of drought-responsive F-box genes in upland rice and involvement of OsFBX148 in ABA response and ROS accumulation

BackgroundUpland rice varieties exhibit significant genetic diversity and broad environmental adaptability, making them ideal candidates for identifying consistently expressed stress-responsive genes. F-box proteins typically function as part of the SKP1-CUL1-F-box protein (SCF) ubiquitin ligase complexes to precisely regulate gene expression and protein level, playing essential roles in the modulation of abiotic stress responses. Therefore, utilizing upland rice varieties for screening stress-responsive F-box genes is a highly advantageous approach.ResultsThrough mRNA-seq analysis in the Brazilian upland rice (cv. IAPAR9), the research identified 29 drought-responsive F-box genes. Gene distribution and duplication analysis revealed these genes are distributed on 11 of the 12 chromosomes and 10 collinear gene pairs were identified on different chromosomes. 13 cis-elements or binding sites were identified in the promoters of the 29 drought-responsive F-box genes by analysis. Protein domain, stability and subcellular localization analysis results suggest that these F-box proteins possess F-box domain and several other domains, and they are mostly unstable proteins with subcellular localization in cytoplasm, nucleus, chloroplasts, mitochondria and endoplasmic reticulum. Most of drought-responsive F-box genes exhibited expression in various tissues such as root, stem, leaf, leaf sheath and panicle except for OsFBO10 and OsFBX283. These genes exhibited various responses to abiotic stresses such as osmotic, cold, heat, and salt stresses, along with ABA treatment. Importantly, a frame-shift mutation in OsFBX148 was created in the ZH11 variety, leading to altered ABA signal transduction and ROS accumulation. The study further elucidated the interaction of OsFBX148 with SKP1 family proteins OSK4/7/17 to form the SCF complex, dependent on the F-box domain.ConclusionsThe research identified and analyzed 29 drought-responsive F-box genes in upland rice and provides valuable insights into the role of OsFBX148 in ABA and ROS responses. It establishes a basis for future exploration of F-box genes in improving resistance to abiotic stresses, especially drought.

Phospho-regulation of ASCL1-mediated chromatin opening during cellular reprogramming.

The proneural transcription factor ASCL1 regulates neurogenesis and drives somatic cell reprogramming into neurons. However, not all cell types can be reprogrammed by ASCL1, raising the questions of what provides competence and how we can overcome barriers to enable directed differentiation. Here, we investigate how levels of ASCL1 and its phosphorylation modulate its activity over progressive lineage restriction of embryonic stem cells. We find that inhibition of ASCL1 phosphorylation enhances reprogramming of both mesodermal and neuroectodermal cells, while pluripotent cells remain refractory to ASCL1-directed neuronal differentiation. By performing RNA-seq and ATAC-seq in neuroectoderm, we find that un(der)phosphorylated ASCL1 causes increased chromatin accessibility at sites proximal to neuronal genes, accompanied by their increased expression. Combined analysis of protein stability and proneural function of phosphomutant and phosphomimetic ASCL1 reveals that protein stability plays only a marginal role in regulating activity, while changes in amino acid charge cannot fully explain enhanced activity of the serine-proline mutant variants of ASCL1. Our work provides new insights into proneural factor activity and regulation and suggests ways to optimize reprogramming protocols in cancer and regenerative medicine.

Shikonin induces ferroptosis in osteosarcomas through the mitochondrial ROS-regulated HIF-1α/HO-1 axis

BackgroundThe most common malignant bone tumour is osteosarcoma, which has an unsatisfactory prognosis and unsatisfactory treatment. Ferroptosis shows promise as an effective OS therapy. A substance extracted from the Lithospermum erythrorhizon, Shikonin (SHK), inhibits a number of tumours, including ovarian, gastric, and lung cancers. However, whether SHK induces OS ferroptosis and its mechanisms are not clear. PurposeOur study is aimed at investigating whether SHK causes ferroptosis and elucidating its molecular mechanism. MethodsCell counting Kit-8, cell cycle and cell apoptosis assay were utilised to assess therapeutic effect of SHK against OS. Normal cells, including H9C2, AML-12 and HK-2, haematoxylin and eosin staining and mice serum biomarker tests were used to assess SHK biosafety. Malondialdehyde (MDA) levels, the glutathione (GSH)/oxidized glutathione (GSSG) ratio, reactive oxygen species (ROS), lipid peroxide (LPO), and intracellular Fe2+ detection, quantitative reverse transcription PCR (qRT-PCR), Western blotting (WB) and rescue experiments were employed to confirm whether SHK induced ferroptosis in OS cells. Molecular docking, cellular thermal shift assay (CETSA), and drug affinity responsive target stability (DARTS) assay were used to evaluate the direct binding between SHK and hypoxia-inducible factor-1α (HIF-1α). Protein stability and degradation analysis, small RNA interference, flow cytometry, qRT-PCR, and WB were used to investigate the molecular mechanism of ferroptosis. In vivo xenografts of nude mouse was used to study the anti-OS effect of SHK. ResultsSHK significantly reduced OS cell viability and induced apoptosis and G2/M arrest. SHK increased intracellular levels of MDA, ROS, LPO, and Fe2+ while simultaneously reducing the GSH/GSSG ratio and GPX4 and SLC7A11 expression. CETSA and DARTS results demonstrated that SHK did not bind targetly to HIF-1α. Instead, mitochondrial ROS (MitoROS) promoted HIF-1α expression, resulting in HO-1 overexpression, excess Fe2+ production, ROS accumulation and GPX depletion, and ferroptosis. Furthermore, inhibition of MitoROS using Mito-TEMPO downregulated HIF-1α/HO-1 axis and mitigated the SHK-induced ferroptosis. In vivo, SHK effectively suppressed OS growth with favourable biosafety, confirming the molecular mechanism underlying SHK-induced ferroptosis in OS. ConclusionWe observe that HIF-1α/HO-1 axis is the crucial factor in SHK-induced OS ferroptosis. Importantly, we demonstrate that HIF-1α is indirectly regulated by MitoROS rather than SHK bound directly to HIF-1α. Our research suggest that SHK is a potential drug candidate for OS treatment and may help in identifying novel therapeutic targets for OS.

Physicochemical and stability analysis of mung bean protein hydrolysates with lipid peroxidation inhibition

This study investigated mung bean protein hydrolysates (MBPH) produced using neutral protease, examining their physicochemical properties, stability, and lipid peroxidation inhibition capabilities. The research revealed that MBPH molecular weight ranged from 17 to 26 kDa and perform various functions, including catalytic, nutrient storage, and binding. Stability assessments showed that MBPH are stable at 45 °C and pH of 7.5 but are light-sensitive and unstable in solution or when combined with sugars. Additionally, increased concentrations of digestive enzymes reduce MBPH stability. Antioxidant tests in vitro and in Caenorhabditis elegans confirmed MBPH's ability to neutralizing radicals, enhance antioxidant enzyme activities, and reduce lipid peroxidation, thereby protecting against oxidative damage. Furthermore, in vivo experiments showed that MBPH extend the lifespan of worms and reduced their body lipid content, indicating potential benefits in mitigating cholesterol-related damage. This research demonstrates the potential of MBPH in inhibiting lipid peroxidation.

Deciphering the multidimensional impact of IGFBP1 expression on cancer prognosis, genetic alterations, and cellular functionality: A comprehensive Pan-cancer analysis

ObjectivesIGF-binding protein 1 (IGFBP1) is a key regulator of insulin-like growth factors, impacting biological processes, including cancer progression and prognosis. Materials and methodsThis study investigates genetic alterations affecting IGFBP1 expression in tumors using data from The Cancer Genome Atlas (TCGA) PanCancer Atlas via cBioPortal. We analyzed samples from 32 cancer types for mutation sites, including deep deletions, amplifications, and mutations. RNA-seq data were normalized using log2(value + 1). Statistical analyses, including survival outcomes, were conducted using R packages like ggplot2, stats, and car. Kaplan-Meier survival curves and log-rank tests assessed overall survival (OS) and progression-free survival (PFS). Univariate Cox regression was used to develop nomogram models for OS. Functional consequences of IGFBP1 mutations were explored through protein structure, stability, and IGF interaction analyses. Protein-protein interaction networks and functional enrichment were analyzed using GEPIA2, STRING, and Cytoscape. Gene Ontology (GO), KEGG, and Gene Set Enrichment Analysis (GSEA) provided insights into affected biological pathways. ResultsPan-cancer analysis revealed diverse expression patterns, including significant upregulation in cutaneous melanoma (SKCM) and downregulation in lung adenocarcinoma (LUAD) and stomach adenocarcinoma (STAD). Specifically, elevated IGFBP1 expression in SKCM patients led to a 25 % improvement in 5-year survival. In contrast, higher IGFBP1 levels in LUAD and OV patients resulted in a 30 % and 20 % decrease in survival, respectively. Elevated IGFBP1 levels are significantly linked to advanced tumor stage and grade in OV and LUAD, affecting prognostic outcomes. Nomogram models for OV, SKCM, LUAD, and STAD showed IGFBP1's predictive strength with AUC values ranging from 0.70 to 0.85, indicating its diagnostic potential. Genetic analyses revealed mutations in IGFBP1 in 12 % of STAD cases and 10 % of UCEC cases, indicating significant genetic variation. Immune analysis showed that high IGFBP1 expression significantly influenced immune cell infiltration, particularly macrophages and CD8+ T cells, thereby affecting survival in LUAD and OV. Functional enrichment and gene set enrichment analysis identified IGFBP1 involvement in crucial pathways, such as cell cycle regulation, immune response, and PD-1 signaling, highlighting its biological impact. Additionally, IGFBP1 expression delineates distinct molecular and immune subtypes, correlating with specific cancer behaviors and immune patterns. ConclusionsThese findings highlight IGFBP1's potential as a biomarker and therapeutic target, particularly for immunoregulation and cancer subtype stratification.

Enhanced molecular stability of ApxII antigen during secretion in Corynebacterium glutamicum by rational design

ApxII is a vaccine antigen used to protect against porcine contagious pleuropneumonia, which is a significant threat to the pig industry. Here, we aimed to improve the proteolytic degradation stability of ApxII during its secretion by establishing a complete screening process of stable variants through bioinformatics and site-directed mutagenesis. We employed a combination of semi-rational and rational design strategies to create 34 single-point variants of ApxII. Among them, R114E and T115D variants exhibited better stability without compromising antigen activity. Furthermore, we constructed a multi-site variant, R114E/T115D, which demonstrated the best stability, activity, and yield. Protein stability and molecular dynamic analysis indicated that the greater solubility and lower structural expansion coefficient might explain the increased stability of R114E/T115D. Additionally, site T115 was identified as a key point of truncated ApxII stability. The R114E/T115D variant, with its proven stability and intact antigenic activity, holds promising prospects for industrial-scale applications in the prevention of porcine contagious pleuropneumonia.

Substitutions in the nonactive site of the passenger domain on the activity of Haemophilus influenzae immunoglobulin A1 protease.

Immunoglobulin A1 (IgA1) protease is a critical virulence factor of Haemophilus influenzae that facilitates bacterial mucosal infection. This study investigates the effect of iga gene polymorphism on the enzymatic activity of H. influenzae IgA1 protease. The IgA1 protease activity was examined in the H. influenzae Rd KW20 strain and 51 isolates. Genetic variations in iga and deduced amino acid substitutions affecting IgA1 protease activity were assessed. Machine learning tools and functional complementation assays were used to analyze the effects of identified substitutions on the stability and activity of IgA1 protease, respectively. All 51 isolates exhibited similar iga expression levels. No igaB expression was detected. According to comparisons with the reference Rd KW20 strain, four substitutions in the protease domain, 26 in the nonprotease passenger domain, and two in the β-barrel domain were associated with the change in IgA1 protease activity. No substitutions in the catalytic site of IgA1 protease were observed. Logistic regression, receiver operating characteristic curves, Venn diagrams, and protein stability analyses revealed that the substitutions Asn352Lys, Pro353Ala, Lys356Asn, Gln916Lys, and Gly917Ser, which were located in the nonactive site of the passenger domain, were associated with decreases in IgA1 protease activity and stability, whereas Asn914Lys was associated with an increase in these events. Functional complementation assays revealed that the Asn914Lys substitution increased IgA1 protease activity in the Rd KW20 strain. This study identified substitutions in the nonactive site of the passenger domain that affect both the activity and stability of H. influenzae IgA1 protease.

Preparation of Calcium-Binding Peptides Derived from Mackerel (Scomber japonicus) Protein and Structural Characterization and Stability Analysis of Its Calcium Complexes.

The purpose of this study was to prepare mackerel peptides (MPs) with calcium-binding capacity through an enzyme method and to investigate the potential role they play in improving the bioavailability of calcium in vitro. The calcium-binding capacity, degree of hydrolysis (DH), molecular weight (MW), and charge distribution changes with the enzymolysis time of MPs were measured. The structural characterization of mackerel peptide-calcium (MP-calcium) complexes was performed using spectroscopy and morphology analysis. The results showed that the maximum calcium-binding capacity of the obtained MPs was 120.95 mg/g when alcalase was used for 3 h, with a DH of 15.45%. Moreover, with an increase in hydrolysis time, the MW of the MPs decreased, and the negative charge increased. The carboxyl and amino groups in aspartic (Asp) and glutamate (Glu) of the MPs may act as calcium-binding sites, which are further assembled into compact nanoscale spherical complexes with calcium ions through intermolecular interactions. Furthermore, even under the influence of oxalic acid, MP-calcium complexes maintained a certain solubility. This study provides a basis for developing new calcium supplements and efficiently utilizing the mackerel protein resource.

Differentiating stable and unstable protein using convolution neural network and molecular dynamics simulations

Protein stability is a critical aspect of molecular biology and biochemistry, hinges on an intricate balance of thermodynamic and structural factors. Determining protein stability is crucial for understanding and manipulating biological machineries, as it directly correlated with the protein function. Thus, this study delves into the intricacies of protein stability, highlighting its dependence on various factors, including thermodynamics, thermal conditions, and structural properties. Moreover, a notable focus is placed on the free energy change of unfolding (ΔGunfolding), change in heat capacity (ΔCp) with protein structural transition, melting temperature (Tm) and number of disulfide bonds, which are critical parameters in understanding protein stability. In this study, a machine learning (ML) predictive model was developed to estimate these four parameters using the primary sequence of the protein. The shortfall of available tools for protein stability prediction based on multiple parameters propelled the completion of this study. Convolutional Neural Network (CNN) with multiple layers was adopted to develop a more reliable ML model. Individual predictive models were prepared for each property, and all the prepared models showed results with high accuracy. The R2 (coefficient of determination) of these models were 0.79, 0.78, 0.92 and 0.92, respectively, for ΔG, ΔCp, Tm and disulfide bonds. A case study on stability analysis of two homologous proteins was presented to validate the results predicted through the developed model. The case study included in silico analysis of protein stability using molecular docking and molecular dynamic simulations. This validation study assured the accuracy of each model in predicting the stability associated properties. The alignment of physics-based principles with ML models has provided an opportunity to develop a fast machine learning solution to replace the computationally demanding physics-based calculations used to determine protein stability. Furthermore, this work provided valuable insights into the impact of mutation on protein stability, which has implications for the field of protein engineering. The source codes are available at https://github.com/Growdeatechnology.

Identification of a Novel Variant c.163delG in HBB Gene Resulting in a Beta Null Phenotype in a Proband with Thalassemia Intermedia

A 21-year-old patient presented with a previous medical history of pallor, mild icterus, increased fatigue, low hemoglobin, and abnormal hemoglobin variant analysis with more than 70 transfusions. He was referred for genetic analysis to identify the pathogenic variations in the β-globin gene. Sanger’s sequencing of the proband and his family revealed the presence of a novel frame shift variant HBB:c.163delG in a compound heterozygous state with hemoglobin E (HbE) (HBB:c.79G > A) variant. The father and the sibling of the patient were found to be normal for the HBB gene. Mother was found to be heterozygous for HbE (HBB:c.79G > A) variant. In silico analysis by Mutalyzer predicted that c.163delG variant generated a premature stop codon after seven codons, leading to a truncated protein. FoldX protein stability analysis showed a positive ΔΔG value of 45.27 kcal/mol suggesting a decrease in protein stability. HBB:c.79G > A is a known variant coding for HbE variant, which results in the reduced synthesis of β-globin chain and shows mild thalassemia. Combined effect of HBB:c.163delG and HBB:c.79G > A variants in the proband might have led to the reduced synthesis of β-globin chains resulting in a thalassemia intermedia type of clinical manifestation.

YTHDF3 modulates the progression of breast cancer cells by regulating FGF2 through m6A methylation.

Breast cancer (BC) is a prevailing malignancy among women, and its inconspicuous development contributes significantly to mortality. The RNA N6-methyladenosine (m6A) modification represents an emerging mechanism for gene expression regulation, with the active involvement of the YTH N6-methyladenosine RNA binding protein 3 (YTHDF3) in tumor progression across multiple cancer types. Nonetheless, its precise function in breast cancer necessitates further investigation. The expression of YTHDF3 in both cell lines and patient tissues was examined using Western blotting, reverse transcription quantitative PCR (RT-qPCR), and immunohistochemistry (IHC) techniques. Bioinformatics analysis of methylated RNA immunoprecipitation sequencing (MeRIP-seq) and transcriptome RNA sequencing (RNA-seq) data was employed to screen for the target genes of YTHDF3. The main focus of this study was to investigate the in vitro biological functions of YTHDF3. The specific binding of YTHDF3 to its target genes and its correlation with m6A methylation were studied through RNA pull-down, RNA immunoprecipitation, and co-immunoprecipitation experiments. The protein regulatory mechanisms of downstream genes of YTHDF3 were assessed using protein stability analysis. Furthermore, the biological functions of YTHDF3 and its target genes in breast cancer cells were validated through CRISPR-Cas9 technology and rescue experiments. By constructing a risk model using the TCGA database, YTHDF3 was identified as a high-risk factor among m6A methylation factors. Subsequent investigations revealed its elevated expression in various subtypes of breast cancer, accompanied by poor prognosis. MeRIP-seq analysis further revealed fibroblast growth factor 2 (FGF2) as a downstream gene of YTHDF3. Knockdown of YTHDF3 in breast cancer cells led to significant inhibition of cell self-renewal, migration, and invasion abilities in vitro. Mechanistically, YTHDF3 specifically recognized the methylated transcript of FGF2 within its coding sequence (CDS) region, leading to the inhibition of FGF2 protein degradation. Moreover, depletion of FGF2 markedly suppressed the biological functions of breast cancer cells, while reducing FGF2 expression in YTHDF3-overexpressing breast cancer cell lines substantially alleviated the malignant progression. In summary, our study elucidates the role of YTHDF3 as an oncogene in maintaining FGF2 expression in BC cells through an m6A-dependent mechanism. Additionally, we provide a potential biomarker panel for prognostic prediction in BC.

Anti-biofilm potential of human senescence marker protein 30 against Mycobacterium smegmatis.

Human senescence marker protein 30 (huSMP30) has been characterized as a multifaceted protein consisting of various enzymatic and cellular functions. It catalyzes the interconversion of L-gulonate and L-gulono-γ-lactone in the ascorbate biosynthesis pathway. Therefore, we hypothesized that it could be a potential anti-biofilm agent against pathogenic bacteria due to its lactonase activity. In order to corroborate this, the huSMP30 was recombinantly expressed, purified, and analyzed for its ability to inhibit Mycobacterium smegmatis biofilm formation, which showed a concentration-dependent inhibition as compared to the untreated control group. Further, in silico analysis was performed to redesign the huSMP30 with enhanced lactonase activity. Molecular docking analysis of the huSMP30 and lactone substrates facilitated the selection of three single amino acid substitutions (E18H, N154Q, and D204V), which were created using a PCR-based site-directed mutagenesis reaction. These mutant proteins and the wild-type huSMP30 were purified, and the effects on the enzymatic activity and biofilm formation were studied. The mutants E18H and D204V showed non-significant effects on specific lactonase activity, catalytic efficiency, and anti-biofilm property; however, the mutant N154Q showed significant improvement in the specific lactonase activity, catalytic efficiency, and inhibition in the biofilm formation. The protein stability analysis revealed that the wild-type huSMP30 and its designed mutants were stable at 37°C for up to 4 days. In conclusion, the anti-biofilm property of the huSMP30 has been established, and an engineered version, N154Q, inhibits biofilm formation with greater efficiency. Human SMP30 is a versatile protein with multiple cellular and enzymatic functions, however, its anti-biofilm potential has not been explored. Our work presents the method to produce soluble and active huSMP30 in the E. coli expression system and establishes its role as an anti-biofilm agent against Mycobacterium smegmatis owing to its lactonase activity. Our results provide support for the future advancement of huSMP30 as a potential anti-biofilm agent targeting pathogenic Mycobacterium species.

Mechanism of RhoA regulating benign prostatic hyperplasia: RhoA-ROCK-β-catenin signaling axis and static & dynamic dual roles

BackgroundThe pathogenesis of benign prostatic hyperplasia (BPH) has not been fully elucidated. Ras homology family member A (RhoA) plays an important role in regulating cell cytoskeleton, growth and fibrosis. The role of RhoA in BPH remains unclear.MethodsThis study aimed to clarify the expression, functional activity and mechanism of RhoA in BPH. Human prostate tissues, human prostate cell lines, BPH rat model were used. Cell models of RhoA knockdown and overexpression were generated. Immunofluorescence staining, quantitative real time PCR (qRT-PCR), Western blotting, cell counting kit-8 (CCK-8), flow cytometry, phalloidine staining, organ bath study, gel contraction assay, protein stability analysis, isolation and extraction of nuclear protein and cytoplasmic protein were performed.ResultsIn this study we found that RhoA was localized in prostate stroma and epithelial compartments and was up-regulated in both BPH patients and BPH rats. Functionally, RhoA knockdown induced cell apoptosis and inhibited cell proliferation, fibrosis, epithelial-mesenchymal transformation (EMT) and contraction. Consistently, overexpression of RhoA reversed all aforementioned processes. More importantly, we found that β-catenin and the downstream of Wnt/β-catenin signaling, including C-MYC, Survivin and Snail were up-regulated in BPH rats. Downregulation of RhoA significantly reduced the expression of these proteins. Rho kinase inhibitor Y-27632 also down-regulated β-catenin protein in a concentration-dependent manner. However, overexpression of β-catenin did not affect RhoA-ROCK levels, suggesting that β-catenin was the downstream of RhoA-ROCK regulation. Further data suggested that RhoA increased nuclear translocation of β-catenin and up-regulated β-catenin expression by inhibiting its proteasomal degradation, thereby activating Wnt/β-catenin signaling. Overexpression of β-catenin partially reversed the changes in cell growth, fibrosis and EMT except cell contraction caused by RhoA downregulation. Finally, Y-27632 partially reversed prostatic hyperplasia in vivo, further suggesting the potential of RhoA-ROCK signaling in BPH treatment.ConclusionOur novel data demonstrated that RhoA regulated both static and dynamic factors of BPH, RhoA-ROCK-β-catenin signaling axis played an important role in the development of BPH and might provide more possibilities for the formulation of subsequent clinical treatment strategies.

An in-silico analysis predicting the impact of coding single nucleotide polymorphisms (SNPs) in the human multidrug pump ABCG2

ATP-Binding Cassette transporter G2 (ABCG2) is a multidrug resistance pump involved in pathophysiology and pharmacoresistance in various neurological, and neurogenerative disorders. Single nucleotide polymorphisms (SNPs) of ABCG2 affecting expression or function may be involved in the pharmacokinetics of its substrate drugs, influencing the bioavailability leading to disease progression. Thus, pathophysiology and pharmacogenetics linked to ABCG2 can be comprehended by understanding the functions of its SNPs. Identification of these SNPs predictive of pharmacoresistance and disease progression is still a major challenge. Here, we have prioritized ABCG2 SNPs for the identification and validation of deleterious/damaging coding SNPs (cSNPs) using an in-silico approach. Out of 965 cSNPs, only 6 were considered to be highly deleterious by five in-silico computational tools. These cSNPs were submitted to MutPred and PMut for further validation followed by subjected to I-Mutant 2.0 for protein stability analysis. We found 5 cSNPs with a DDG score less than −0.5, suggesting a damaging effect. Based on the conservation of amino acid residues, post-translational modification sites, and structural superimposition, rs3116448 (S248A) and rs41282401 (D296H) were predicted as high-risk cSNPs. Molecular dynamics (MD) simulations revealed that the substitution of the residues S248A in the ABCG2 model altered the structural conformation of the protein and may influence the functional activity as per previously reported in vitro studies. Thus, findings from our study, for the first time, identified clinically important ABCG2 variations utilizing a substantial bioinformatics pipeline that not only provides important potential targets in the field of pharmacogenomics but also curtails study costs.

Computational Exploration of Functional and Structural Impact of Single Nucleotide Changes in DNMT3A Gene among Acute Myeloid Leukemia Patients

Acute myeloid leukemia (AML) is a blood cell malignancy of the myeloid line, characterized by fast proliferation of aberrant cells that build up in the bone marrow and blood, interfering with normal blood cell synthesis. DNMT3A is a DNA methyltransferase that plays a role in DNA methylation, an epigenetic modification associated with gene expression regulation. DNMT3A mutations are frequently found in AML and are associated with poor prognosis. Objective: To evaluate the impact of DNMT3A mutations on protein structure and function, specifically in the context of AML. Methods: SNPs of DNMT3A gene reported in AML (R882P, R882L, R882S, R882G, and R882C) were retrieved from National Centre for Biotechnology Information (NCBI) database and different in silico approaches were used to investigate how these mutations affect protein structure and function. Results: Prediction tools indicated that mutations are pathogenic affecting DNMT3A function and were found in evolutionarily conserved regions. Protein stability analysis showed that mutations reduce DNMT3A's structural stability, alter secondary structure of the protein, particularly helices, interacts with other proteins and reduce protein-protein affinity. RNA folding analysis revealed abnormal folding patterns caused by mutant, affecting protein translation. DNMT3A expression was reported to be considerably greater in AML compared to normal tissues, and mutations were associated with poor overall survival in AML patients. Methylation levels and post-translational modification sites of DNMT3A were also investigated. Conclusions: Overall, this research highlighted the negative impact of DNMT3A mutations on protein structure and function, emphasizing their importance in the development and prognosis of AML. Acute myeloid leukemia (AML) is a blood cell malignancy of the myeloid line, characterized by fast proliferation of aberrant cells that build up in the bone marrow and blood, interfering with normal blood cell synthesis. DNMT3A is a DNA methyltransferase that plays a role in DNA methylation, an epigenetic modification associated with gene expression regulation. DNMT3A mutations are frequently found in AML and are associated with poor prognosis. Objective: To evaluate the impact of DNMT3A mutations on protein structure and function, specifically in the context of AML. Methods: SNPs of DNMT3A gene reported in AML (R882P, R882L, R882S, R882G, and R882C) were retrieved from National Centre for Biotechnology Information (NCBI) database and different in silico approaches were used to investigate how these mutations affect protein structure and function. Results: Prediction tools indicated that mutations are pathogenic affecting DNMT3A function and were found in evolutionarily conserved regions. Protein stability analysis showed that mutations reduce DNMT3A's structural stability, alter secondary structure of the protein, particularly helices, interacts with other proteins and reduce protein-protein affinity. RNA folding analysis revealed abnormal folding patterns caused by mutant, affecting protein translation. DNMT3A expression was reported to be considerably greater in AML compared to normal tissues, and mutations were associated with poor overall survival in AML patients. Methylation levels and post-translational modification sites of DNMT3A were also investigated. Conclusions: Overall, this research highlighted the negative impact of DNMT3A mutations on protein structure and function, emphasizing their importance in the development and prognosis of AML.

Laser-Based Mid-Infrared Spectroscopy for Monitoring Temperature-Induced Denaturation of Bovine Serum Albumin and De-/Stabilization Effects of Sugars.

Stability of high-concentration protein formulations is considered a major challenge in current biopharmaceutical development. In this work, we introduce laser-based mid-infrared (IR) spectroscopy as a versatile technique to study the effect of protein concentration and presence of sugars on the thermal denaturation of the model protein bovine serum albumin (BSA). Many analytical techniques struggle to characterize the complex structural transition that occurs during protein denaturation. To this end, a commercially available laser-based mid-IR spectrometer equipped with a customized flow cell was employed to record IR spectra of BSA in the temperature range of 25-85 °C. The temperature perturbation induces a conformational change from a native α-helical to an intermolecular β-sheet secondary structure in BSA. Systematic investigation of the concentration dependence of the α-β transition temperature between 30 and 90 mg mL-1 shows a trend of decreasing denaturation temperatures at higher BSA concentrations. In-depth chemometric analysis by a multivariate curve resolution-alternating least squares (MCR-ALS) analysis of the spectra, suggested the formation of not one but two intermediates in the denaturation of BSA. Subsequently, the impact of sugars on denaturation temperatures was investigated, revealing both stabilizing (trehalose, sucrose, and mannose) and destabilizing (sucralose) effects, illustrating the applicability of this method as an investigative tool for stabilizers. These results highlight the potential and versatility of laser-based IR spectroscopy for analysis of protein stability at high concentrations and varying conditions.

High risk genetic variants of human insulin receptor substrate 1(IRS1) infer structural instability and functional interference

Insulin receptor substrate 1(IRS1) is a signaling adapter protein encoded by the IRS1 gene. This protein delivers signals from insulin and insulin-like growth factor-1(IGF-1) receptors to the phosphatidylinositol 3-kinases (P13K)/protein kinase B (Akt) and Extracellular signal-regulated kinases (Erk) - Mitogen-activated protein (MAP) kinase pathways, which regulate particular cellular processes. Mutations in this gene have been linked to type 2 diabetes mellitus, a heightened risk of insulin resistance, and an increased likelihood of developing a number of different malignancies. The structure and function of IRS1 could be severely compromised as a result of single nucleotide polymorphism (SNP) type genetic variants. In this study, we focused on identification of the most harmful non-synonymous SNPs (nsSNPs) of the IRS1 gene as well as prediction of their structural and functional consequences. Six different algorithms made the initial prediction that 59 of the 1142 IRS1 nsSNPs would have a negative impact on the protein structure. In-depth evaluations detected 26 nsSNPs located inside the functional domains of IRS1. Following that, 16 nsSNPs were identified as more harmful based on conservation profile, hydrophobic interaction, surface accessibility, homology modelling, and inter-atomic interactions. Following an in-depth analysis of protein stability, M249T (rs373826433), I223T (rs1939785175) and V204G (rs1574667052) were identified as three most deleterious SNPs and were subjected to molecular dynamics simulation for further insights. These findings will help us understand the implications for disease susceptibility, cancer progression, and the efficacy of therapeutic development against IRS1 gene mutants. Communicated by Ramaswamy H. Sarma

Analysis and prediction of protein stability based on interaction network, gene ontology, and KEGG pathway enrichment scores

Metabolic stability of proteins plays a vital role in various dedicated cellular processes. Traditional methods of measuring the metabolic stability are time-consuming and expensive. Therefore, we developed a more efficient computational approach to understand the protein dynamic action mechanisms in biological process networks. In this study, we collected 341 short-lived proteins and 824 non-short-lived proteins from U2OS; 342 short-lived proteins and 821 non-short-lived proteins from HEK293T; 424 short-lived proteins and 1153 non-short-lived proteins from HCT116; and 384 short-lived proteins and 992 non-short-lived proteins from RPE1. The proteins were encoded by GO and KEGG enrichment scores based on the genes and their neighbors in STRING, resulting in 20,681 GO term features and 297 KEGG pathway features. We also incorporated the protein interaction information from STRING into the features and obtained 19,247 node features. Boruta and mRMR methods were used for feature filtering, and IFS method was used to obtain the best feature subsets and create the models with the highest performance. The present study identified 42 features that did not appear in previous studies and classified them into eight groups according to their functional annotation. By reviewing the literature, we found that the following three functional groups were critical in determining the stability of proteins: synaptic transmission, post-translational modifications, and cell fate determination. These findings may serve as a valuable reference for developing drugs that target protein stability.

Identification of deleterious nsSNPs in human HGF gene: in silico approach

HGF is a protein that binds to the hepatocyte growth factor receptor to regulate cell growth, cell motility and morphogenesis in different cells and tissues. Several bioinformatics tools and in silico methods were used to identify most deleterious nsSNPs that might change the structure and function of HGF protein. The in silico tools such as SIFT, SNP&GO and PolyPhen2 were used to distinguish deleterious nsSNPs from neutral ones. Protein stability is analysed by I‐Mutant, MUpro and iStable. The functional and structural effects are predicted by other tools like MutPred2, Maestro, DUET etc. Analysis of structure was performed by HOPE and Mutation3D. SWISS-MODEL. server, was used for wild type and mutant proteins 3‐D Modelling. Gene–gene and protein–protein interaction were predicted by GeneMANIA and STRING, respectively. The wildtype HGF protein and these three variants were independently docked with their close interactor protein MET by the use of ClusPro. Our study suggested that out of 392 missense nsSNPs of the HGF gene, five nsSNPs (D358G, G648R, I550N, N175S and R220Q), are the most deleterious in HGF gene. Gene–gene interactions showed relation of HGF with other genes depicting its importance in several pathways and co‐expressions. The protein–protein interacting network is composed of 11 nodes. Analysis of protein stability by different tools indicated that the five nsSNPS decreased the stability of the protein. Anyway these nsSNPs need a confirmation analysis by experimental investigation and GWAS studies Communicated by Ramaswamy H. Sarma

Thermal analysis of protein stability and ligand binding in complex media

Screening of ligands that can bind to biologic products of in vitro expression systems typically requires some purification of the expressed biologic target. Such purification is often laborious and time consuming as well as a limiting challenge. What is required, representing an enormous advantage, is the ability to screen expressed proteins in the crude lysate stage without purification. For that purpose, we explore here, the utility of differential scanning calorimetry (DSC) measurements for detecting the presence of specific proteins and their interactions with ligands in the complex media where they were prepared, i.e. crude lysates. Model systems were designed to mimic analogous conditions comparable to those that may be encountered in actual in vitro expression systems. Results are reported for several examples where DSC measurements distinctly showed differences in the thermal denaturation behaviors of the crude lysate alone, proteins and proteins plus binding ligands added to the crude lysate. Results were obtained for Streptavidin/Biotin binding in E. coli lysate, and binding of Angiotensin Converting Enzyme 2 (ACE2) by captopril or lisinopril in the lysate supernatant derived from cultured Human Kidney cells (HEK293). ACE2 binding by the receptor binding domain (RBD) of SARS-CoV-2 was also examined. Binding of ACE2 by RBD and lisinopril were similar and consistent with the reported ACE2 inhibitory activity of lisinopril.