Decreased Protein Stability Research Articles

Reclassification of Two MLH1 Variants of Uncertain Significance Utilizing Clinical and Functional Data.

Pathogenic variants in the mismatch repair genes are associated with an elevated lifetime risk of colorectal cancer (CRC). We previously identified two variants of uncertain significance (VUS) in the MLH1 gene, c.696_698del, p.(Cys233del) and c.1919C > G, p.(Pro640Arg), in Danish families with numerous occurrences of CRC. To reclassify the variants we collected clinical data, initiated tumor and co-segregation analysis, and performed RNA splicing analysis, subcellular localization, and protein stability studies. The functional analysis revealed that the c.696_698del, p.(Cys233del) variant had an effect at the RNA level, on subcellular localization, and on protein stability, while the c.1919C > G, p.(Pro640Arg) variant showed decreased expression in localization studies and decreased protein stability. These results suggest both variants disrupt DNA mismatch repair. By applying all collected data and functional results we propose to reclassify the c.696_698del, p.(Cys233del) and the c.1919C > G, p.(Pro640Arg) variants as likely pathogenic (class 4) using MMR gene-specific ACMG/AMP guidelines. Consequently, the two MLH1 variants can now be used for risk assessment of variant carriers, while family members without the variants can be excluded from intensified cancer surveillance and follow population recommendations.

Linking Protein Stability to Pathogenicity: Predicting Clinical Significance of Single-Missense Mutations in Ocular Proteins Using Machine Learning.

Understanding the effect of single-missense mutations on protein stability is crucial for clinical decision-making and therapeutic development. The impact of these mutations on protein stability and 3D structure remains underexplored. Here, we developed a program to investigate the relationship between pathogenic mutations with protein unfolding and compared seven machine learning (ML) models to predict the clinical significance of single-missense mutations with unknown impacts, based on protein stability parameters. We analyzed seven proteins associated with ocular disease-causing genes. The program revealed an R-squared value of 0.846 using Decision Tree Regression between pathogenic mutations and decreased protein stability, with 96.20% of pathogenic mutations in RPE65 leading to protein instability. Among the ML models, Random Forest achieved the highest AUC (0.922) and PR AUC (0.879) in predicting the clinical significance of mutations with unknown effects. Our findings indicate that most pathogenic mutations affecting protein stability occur in alpha-helices, beta-pleated sheets, and active sites. This study suggests that protein stability can serve as a valuable parameter for interpreting the clinical significance of single-missense mutations in ocular proteins.

Insilico Identification of Association between Nicotine Dependence and Pathogenic Missense Mutations of Catechol-O-Methyltransferase Gene

Introduction: Oral cancers are known to be strongly associated with the usage of tobacco, which is majorly composed of nicotine. Genetic studies evidenced the nicotine addiction as hereditary. AIM: The aim of the present study is to analyse any genetically functional missense mutations in Catechol-O-methyl-transferase (COMT) gene and derive an association with nicotine dependence that might influence tobacco habit initiation, addiction, and cessation. Methodology: The study involved an insilico analysis about the association between COMT gene and nicotine dependence. This was done with the help of different databases available in website. Initially, database called Ensembl (https://asia.ensembl.org) was used to pool the genetic data on missense mutations of the human COMT gene. The collected data was then fed into computational tools such as SIFT, PolyPhen, PROVEAN, I-Mutant, MutPred to discover the pathogenic mutations if exists. Results: Among 78 missense mutations collected, 74 were identified as damaging variants in which 8 variants were found to cause increased protein stability and 66 were found to cause decreased protein stability. Among those 66 missense variants causing decreased protein stability, 25 variants were identified as highly pathogenic while 19 variants were identified as pathogenic. Conclusion: The in-silico analysis discovered the existence of highly pathogenic mutations in COMT gene which might have a strong association with nicotine dependence that can influence the tobacco habit initiation, addiction, and cessation.

Identification of the mutations in BTD gene in Iranian patients with biotinidase deficiency and evaluating their genotype-phenotype correlations

BackgroundBiotinidase (BTD, encoded by the BTD gene) deficiency is an autosomal recessive neurometabolic disease caused by abnormal BTD activity in the biotin cycle. The clinical symptoms of patients, which are mainly neurocutaneous, range from mild to severe based on the enzyme activity level. This study aimed to identify BTD gene mutations in suspected BTD deficiency patients for the first time in the southwest of Iran and evaluate their genotype-phenotype correlations. Methods11 clinically and biochemically suspected patients from nine unrelated families and their available family members were subjected to Sanger sequencing. Segregation analysis was performed for novel mutation. The effect of each mutation on protein stability and hydropathicity, as well as the pathogenicity prediction of all detected mutations were assessed using various in silico analysis tools. ResultsSix mutations including a novel and five previously reported mutations were identified in patients with different ethnicities. Three out of five known mutations were reported for the first time in Iran. Various common clinical manifestations and a rarely reported coexistence of celiac disease in biotinidase deficiency patients were observed. The novel missense variant c.787G > A (p.Glu263Lys) was detected in exon 4 of the BTD gene, within the biotinidase-like domain of the BTD protein. This variation was found in two cousins of a family, both developed the same initial clinical presentation. In silico analysis revealed that this missense substitution decreased protein stability and increased protein hydrophilicity. Additionally, the known frameshift mutation c.1264delG (p.val422serfster59), was the most frequent allele in the studied population. We also predicted and visualized the effects of the novel and frameshift mutations on protein structure. ConclusionOur findings expanded the mutational spectrum of the BTD gene and provided valuable data on genotype-phenotype correlations, which helps in genetic counseling. Furthermore, the necessity of performing molecular analysis along with enzymatic analysis was highlighted by this study.

Computational Identification and Functional Analysis of Potentially Pathogenic nsSNPs in the NLRP3 Gene Linked to Alzheimer's Disease.

Single Nucleotide Polymorphisms (SNPs) are key in understanding complex diseases. Nonsynonymous single-nucleotide polymorphisms (nsSNPs) occur in protein-coding regions, potentially altering amino acid sequences, protein structure and function. Computational methods are vital for distinguishing deleterious nsSNPs from neutral ones. We investigated the role of NLRP3 gene in neuroinflammation associated with Alzheimer's disease (AD) pathogenesis. A total of 893 missense (nsSNPs) were obtained from the dbSNP database and subjected to rigorous filtering using bioinformatics tools like SIFT, Align GVGD, PolyPhen-2, and PANTHER to identify potentially damaging variants. Of these, 18 nsSNPs were consistently predicted to have deleterious effects across all tools. Notably, 16 of these variants exhibited reduced protein stability, while only 4 were predicted to be buried within the protein structure. Among the identified nsSNPs, rs180177442 (R262L and R262P), rs201875324 (T659I), and rs139814109 (T897M) were classified as high-risk variants due to their significant deleterious impact, probable damaging effects, and association with decreased protein stability. Molecular docking and simulation analyses were conducted utilizing Memantine, a standard drug utilized in AD treatment, to investigate potential interactions with the altered protein structures. Additional clinical and genetic investigations are necessary to elucidate the underlying mechanisms that link NLRP3 polymorphisms with the initiation of AD.

Computational analysis of non-synonymous SNPs in the human LCN2 gene

BackgroundLipocalin-2 (LCN2), a neutrophil gelatinase-associated protein, plays an important role in iron homeostasis, infection, and inflammation. Polymorphism in the LCN2 gene is linked to various diseases such as cardiovascular disease, renal damage, and colorectal and pancreatic cancer. Identifying deleterious functional non-synonymous SNPs in the LCN2 gene is crucial in understanding how these genetic variations affect its structure and function.MethodsSeveral in silico tools such as SIFT, Polyphen-2, PROVEAN, PREDICT SNP, MAPP, and SNAP2 followed by I-MUTANT 2.0, MUpro, ConSurf, and NetsurfP-2.0, secondary structure of the protein by SOPMA and PSIPRED, while its interaction with other genes and proteins was analyzed using GeneMANIA and STRING, respectively, and AlphaFold for protein's 3D structure prediction.ResultsThe study identified 6 potentially harmful nsSNPs (rs11556770, rs139418967, rs142623708, rs200107414, rs201365744, rs368926734) and their structure and function were analyzed using prediction tools. I-MUTANT 2.0 predicted an increase in stability with the nsSNPs rs139418967, while the other shows decrease in protein stability with the 6 nsSNPs (rs11556770, rs139418967, rs142623708, rs200107414, rs201365744, rs368926734) which was validated using MUpro. ConSurf identified the 6 high-risk nsSNPs to be in the conserved regions of the protein. The result showed that rs11556770, rs139418967, rs142623708, rs200107414, rs201365744, and rs368926734 were found to be highly conserved and the variant amino acids. According to NetsurfP-2.0 server, the result showed that rs11556770 (Q39H), rs139418967 (L6P), rs368926734 (Y135H) were predicted to be exposed and rs142623708 (M71I), rs200107414 (Y52C), rs368926734 (Y135) were buried. The PSIPRED server analysis indicated that the predominant secondary structure was a strand, with lesser occurrences of coil and helix.ConclusionOverall, the study identified detrimental nsSNPs of LCN2 using computational analysis which could be used for large population-based investigations and diagnosis.

An extensive in silico analysis of missense mutations of the human AIMP2 gene

HLD17 (Hypomyelinating Leukodystrophy 17) is an inherited white matter disorder characterized by insufficient myelin production due to biallelic loss of function mutations in the aminoacyl-tRNA synthetase complex-interacting multifunctional protein 2 (AIMP2) gene. In silico analysis of SNVs (single nucleotide variants) in the AIMP2 gene is an efficient and cost-effective method for analyzing and predicting the impact of mutations on protein function and disease pathophysiology.The study used dbSNP and Ensembl databases to obtain data on 343 nonsynonymous single nucleotide variants (nsSNVs) in the human AIMP2 gene. Six prediction algorithm tools were used to assess the effects of these nsSNVs on AIMP2's functions and structures. Results showed that 18 nsSNVs were located within functional domains, while 10 nsSNVs led to decreased protein stability. The structural and functional properties of the AIMP2 protein were investigated using databases such as Predict Protein, Mutpred2, and HOPE. ConSurf analysis provided information about conserved nsSNVs. GeneMANIA and STRING software tools were used to predict interactions between gene-gene and protein-protein, respectively. Phyre2 and I-TASSER web servers were used to predict the 3D structures of wild-type and mutant proteins.In addition, having the challenge of probable post-translational modification sites in the AIMP2, we made predictions using various bioinformatics tools. Consecuently, three minor mutations (L138Q, V161E, and I188N) and five major mutations (C23S, D121G, I122S, P128S, and W268S) were found to affect the AIMP2 protein's structure or function. Anyway, These mutations need to be further studied and confirmed through experimental investigation and GWAS studies.

Mitochondrial Pathogenic Mutations and Expression Pattern of Oxidative Phosphorylation Genes in COVID-19 Patients.

Mitochondrial missense mutations and pathogenic variants have been implicated in the pathogenesis of COVID-19. This study evaluated the role of mitochondrial DNA (mtDNA) mutations and changes in gene expression in the progression of COVID-19 and their correlation with clinical characteristics. Next-generation sequencing with high throughput was used to identify mtDNA mutations in 30 COVID-19 patients compared to 20 healthy controls. The potential impact of identified mutations on protein structure and stability was predicted using bioinformatic tools. Quantitative real-time polymerase chain reaction was employed to assess the expression levels of mtDNA-encoded genes involved in oxidative phosphorylation in COVID-19 patients and healthy controls. Correlations between gene expression levels, clinical parameters, including leukocyte, lymphocyte, neutrophil, and platelet count, as well as creatinine, alanine transaminase (ALT), aspartate transaminase (AST), and blood urea nitrogen (BUN) levels, and disease severity were analyzed. We found 8 different mtDNA mutations in ND1, ND5, CO3, ATP6, and CYB genes, which were predicted to alter amino acids and decrease protein stability. Two missense unique mutations, C9555T in CO3 and A12418T in ND5 were identified and correlated with Complexes I and IV, respectively. This downregulation was correlated with age, elevated levels of leukocytes, lymphocytes, neutrophils, platelets, creatinine, ALT, AST, and BUN, as well as disease severity. These findings suggest that mtDNA mutations and altered expression of oxidative phosphorylation genes contribute to mitochondrial dysfunction in COVID-19. Targeting mitochondrial dysfunction may represent a promising therapeutic strategy for COVID-19 treatment.

Report of a novel recurrent homozygous variant c.620A>T in three unrelated families with thiamine metabolism dysfunction syndrome 5 and review of literature.

Biallelic variants in thiamine pyrophosphokinase 1 ( TPK1 ) are known to cause thiamine metabolism dysfunction syndrome 5 (THMD5). This disorder is characterized by neuroregression, ataxia and dystonia with basal ganglia abnormalities on neuroimaging. To date, 27 families have been reported with THMD5 due to variants in TPK1 . We ascertained three individuals from three unrelated families. Singleton exome sequencing was performed on all three individuals, followed by in silico mutagenesis of the mutant TPK protein. Additionally, we reviewed the genotypic and phenotypic information of 27 previously reported individuals with THMD5. Singleton exome sequencing revealed a novel homozygous variant c.620A>T p.(Asp207Val) in TPK1 (NM_022445.4) in all three individuals. In silico mutagenesis of the mutant protein revealed a decrease in protein stability and altered interactions with its neighboring residues compared to the wild-type protein. Thus, based on strikingly similar clinical and radiological findings compared to the previously reported individuals and with the support of in silico mutagenesis findings, the above-mentioned variant appears to be the probable cause for the condition observed in the affected individuals in this study. We report a novel homozygous variant in TPK1 , which appears to be recurrent among the Indian population.

Revisiting the Roles of Catalytic Residues in Human Ornithine Transcarbamylase.

Human ornithine transcarbamylase (hOTC) is a mitochondrial transferase protein involved in the urea cycle and is crucial for the conversion of toxic ammonia to urea. Structural analysis coupled with kinetic studies of Escherichia coli, rat, bovine, and other transferase proteins has identified residues that play key roles in substrate recognition and conformational changes but has not provided direct evidence for all of the active residues involved in OTC function. Here, computational methods were used to predict the likely active residues of hOTC; the function of these residues was then probed with site-directed mutagenesis and biochemical characterization. This process identified previously reported active residues, as well as distal residues that contribute to activity. Mutation of active site residue D263 resulted in a substantial loss of activity without a decrease in protein stability, suggesting a key catalytic role for this residue. Mutation of predicted second-layer residues H302, K307, and E310 resulted in significant decreases in enzymatic activity relative to that of wild-type (WT) hOTC with respect to l-ornithine. The mutation of fourth-layer residue H107 to produce the hOTC H107N variant resulted in a 66-fold decrease in catalytic efficiency relative to that of WT hOTC with respect to carbamoyl phosphate and a substantial loss of thermal stability. Further investigation identified H107 and to a lesser extent E98Q as key residues involved in maintaining the hOTC quaternary structure. This work biochemically demonstrates the importance of D263 in hOTC catalytic activity and shows that residues remote from the active site also play key roles in activity.

The Temperature Dependence of Hydrogen Bonds Is More Uniform in Stable Proteins: An Analysis of NMR h3JNC' Couplings in Four Different Protein Structures.

Long-range HNCO NMR spectra for proteins show crosspeaks due to 1JNC', 2JNC', 3JNCγ, and h3JNC' couplings. The h3JNC' couplings are transmitted through hydrogen bonds and their sizes are correlated to hydrogen bond lengths. We collected long-range HNCO data at a series of temperatures for four protein structures. P22i and CUS-3i are six-stranded beta-barrel I-domains from phages P22 and CUS-3 that share less than 40% sequence identity. The cis and trans states of the C-terminal domain from pore-forming toxin hemolysin ΙΙ (HlyIIC) arise from the isomerization of a single G404-P405 peptide bond. For P22i and CUS-3i, hydrogen bonds detected by NMR agree with those observed in the corresponding domains from cryoEM structures of the two phages. Hydrogen bond lengths derived from the h3JNC' couplings, however, are poorly conserved between the distantly related CUS-3i and P22i domains and show differences even between the closely related cis and trans state structures of HlyIIC. This is consistent with hydrogen bond lengths being determined by local differences in structure rather than the overall folding topology. With increasing temperature, hydrogen bonds typically show an apparent increase in length that has been attributed to protein thermal expansion. Some hydrogen bonds are invariant with temperature, however, while others show apparent decreases in length, suggesting they become stabilized with increasing temperature. Considering the data for the three proteins in this study and previously published data for ubiquitin and GB3, lowered protein folding stability and cooperativity corresponds with a larger range of temperature responses for hydrogen bonds. This suggests a partial uncoupling of hydrogen bond energetics from global unfolding cooperativity as protein stability decreases.

Identification of high-risk non-synonymous SNPs (nsSNPs) in DNAH1 and DNAH17 genes associated with male infertility: a bioinformatics analysis.

Male infertility is a significant reproductive issue affecting a considerable number of couples worldwide. While there are various causes of male infertility, genetic factors play a crucial role in its development. We focused on identifying and analyzing the high-risk nsSNPs in DNAH1 and DNAH17 genes, which encode proteins involved in sperm motility. A total of 20 nsSNPs for DNAH1 and 10 nsSNPs for DNAH17 were analyzed using various bioinformatics tools including SIFT, PolyPhen-2, CADD, PhD-SNPg, VEST-4, and MutPred2. As a result, V1287G, L2071R, R2356W, R3169C, R3229C, E3284K, R4096L, R4133C, and A4174T in DNAH1 gene and C1803Y, C1829Y, R1903C, and L3595P in DNAH17 gene were identified as high-risk nsSNPs. These nsSNPs were predicted to decrease protein stability, and almost all were found in highly conserved amino acid positions. Additionally, 4 nsSNPs were observed to alter post-translational modification status. Furthermore, the interaction network analysis revealed that DNAH1 and DNAH17 interact with DNAH2, DNAH3, DNAH5, DNAH7, DNAH8, DNAI2, DNAL1, CFAP70, DNAI3, DNAI4, ODAD1, and DNAI7, demonstrating the importance of DNAH1 and DNAH17 proteins in the overall functioning of the sperm motility machinery. Taken together, these findings revealed the detrimental effects of identified high-risk nsSNPs on protein structure and function and highlighted their potential relevance to male infertility. Further studies are warranted to validate these findings and to elucidate the underlying mechanisms.

Caffeic acid phenethyl ester suppresses the expression of androgen receptor variant 7 via inhibition of CDK1 and AKT.

Androgen receptor (AR) splice variant 7 (AR-V7) is capable to enter nucleus and activate downstream signaling without ligand. AR-V7 assists the tumor growth, cancer metastasis, cancer stemness, and the evolvement of therapy-resistant prostate cancer (PCa). We discovered that caffeic acid phenethyl ester (CAPE) can repress the expression and downstream signaling of AR-V7 in PCa cells. CAPE blocked the gene transcription, nuclear localization, and protein abundance of AR-V7. CAPE inhibited the expression of U2AF65, SF2 and hnRNPF, which were splicing factors for AR-V7 intron. Additionally, CAPE decreased protein stability of AR-V7 and enhanced the proteosome-degradation of AR-V7. We observed that CDK1 and AKT regulated the expression and stability of AR-V7 via phosphorylation of Ser81 and Ser213, respectively. CAPE decreased the expression of CDK1 and AKT. Overexpression of CDK1 restored the abundance of AR-V7 in CAPE-treated PCa cells. Overexpression of AR-V7, AKT or CDK1 rescued the proliferation of PCa cells under CAPE treatment. Intraperitoneal injection of 10 mg/kg CAPE retarded the growth of 22Rv1 xenografts in nude mice and suppressed the protein levels of AR-V7, CDK1 and AKT in 22Rv1 xenografts. Our study provided the rationale of applying CAPE for inhibition of AR-V7 in prostate tumors.

Electrostatics introduce a trade-off between mesophilic stability and adaptation in halophilic proteins.

Extremophile organisms have adapted to extreme physicochemical conditions. Halophilic organisms, in particular, survive at very high salt concentrations. To achieve this, they have engineered the surface of their proteins to increase the number of short, polar and acidic amino acids, while decreasing large, hydrophobic and basic residues. While these adaptations initially decrease protein stability in the absence of salt, they grant halophilic proteins remarkable stability in environments with extremely high salt concentrations, where non-adapted proteins unfold and aggregate. The molecular mechanisms by which halophilic proteins achieve this, however, are not yet clear. Here, we test the hypothesis that the halophilic amino acid composition destabilizes the surface of the protein, but in exchange improves the stability in the presence of salts. To do that, we have measured the folding thermodynamics of various protein variants with different degrees of halophilicity in the absence and presence of different salts, and at different pH values to tune the ionization state of the acidic amino acids. Our results show that halophilic amino acids decrease the stability of halophilic proteins under mesophilic conditions, but in exchange improve salt-induced stabilization and solubility. We also find that, in contrast to traditional assumptions, contributions arising from hydrophobic effect and preferential ion exclusion are more relevant for haloadaptation than electrostatics. Overall, our findings suggest a trade-off between folding thermodynamics and halophilic adaptation to optimize proteins for hypersaline environments.

Insights into the structure–function relationship of missense mutations in the human TOP2A protein in ovarian cancer

Topoisomerase 2-alpha (TOP2A) is a nuclear protein that is responsible for the maintenance of the topological state of DNA. TOP2A is highly upregulated in ovarian cancer, and its copy number is an important prognosis factor. A large number of single-nucleotide polymorphism (SNP), insertion, and deletion mutations have been reported in TOP2A. Thus, a structural and functional study of missense SNPs was carried out to screen potentially damaging mutations. The 193 non-synonymous SNPs in the coding region of TOP2A in the dbSNP database were selected for in silico analysis. The deleterious SNPs were screened using sorting intolerant from tolerant (SIFT), PolyPhen-2, SNAP2, and SNPs&Go, and we obtained four possibly damaging SNPs at the end (Y481C, N7741, E922K, and R1514W). Mutants Y481C and E922K were predicted to be highly deleterious and showed decreased protein stability compared with native proteins, as predicted by I-Mutant 3. We used the SWISS-MODEL to model the structure of these two mutants, and the structural attributes of modeled mutants were studied using Hope Project, solvent accessibility-based protein–protein interface identification and recognition (SPPIDER), SRide, and HBAT, which predicted small variations from the native protein. Molecular dynamics simulation demonstrated a decrease in root mean square deviation (RMSD) and the radius of gyration of two mutants, which is relative to the native protein. The molecular docking of TOP2A with etoposide suggests that mutations may lead to resistance to TOP2A-targeted chemotherapy. In addition, the relative expression analysis performed by qRT-PCR also reveals that there is a three-fold increase in the expression levels of the TOP2A protein in ovarian adenoma cancer cell lines. Our analysis reveals that Y481C and E922K are highly damaging variants of TOP2A, which alter the protein dynamics and may be implicated in causing ovarian cancer.

Abstract 3336: Regulation of liver X receptor protein stability by novel ligands in pancreatic cancer cells

Abstract Liver X Receptors (LXRs) are nuclear receptors that act as ligand-modulated transcription factors. LXRs are overexpressed in various cancers, including pancreatic cancer, and targeting LXR with small molecule ligands has emerged as a promising therapeutic strategy in cancer. Current small molecule LXR ligands were originally developed for the treatment of atherosclerosis and other metabolic diseases. To identify ligands specifically targeting cancer cells, we screened a focused library of drug-like molecules predicted to bind to LXR using molecular docking. In the screen, novel LXR ligand GAC0001E5 (1E5) exhibited significant anti-proliferative effects in human pancreatic ductal adenocarcinoma (PDAC) cell lines. Functionally, 1E5 is an LXR inverse agonist which decreases LXR target gene expression and a “degrader” of LXR proteins following prolonged treatment. We posit that this novel ligand inhibits PDAC cells by downregulating the expression of LXR target genes. To test this hypothesis, we treated cancer cells with the previously described LXR inverse agonist SR9238 and examined its effect on cancer cell proliferation. Interestingly, treatments with SR9238 had no effect on pancreatic cancer cell proliferation as compared to the novel ligand 1E5 and the 1E5 derivative KD-95, suggesting that LXR inverse agonism was insufficient to inhibit cell proliferation. To determine whether SR9238 has similar effects on LXR protein levels as novel ligands, we performed western analysis of protein expression following ligand treatment. In contrast to the novel ligands 1E5 and KD-95, treatments with SR9238 increased LXR protein levels. Furthermore, time-course studies in cycloheximide treated cells indicated that novel ligands decreased protein stability whereas SR9238 had the opposite effect. Inhibition of proteasomal degradation and autophagy abolished the effects of 1E5 and KD-95 in a cell line-dependent manner. Related to these observations, previously published data revealed that knockdown of LXR expression greatly diminished PDAC cell proliferation. Taken together, these findings indicate that LXR expression is essential in pancreatic cancer cells and suggest that the novel ligands may disrupt its involvement in protein-protein interactions and non-genomic mechanisms. Citation Format: Abhinav Bagchi, Kasuni T. Gamage, Scott R. Gilbertson, Chin-Yo Lin. Regulation of liver X receptor protein stability by novel ligands in pancreatic cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3336.

BRCA2 Polymorphisms and Breast Cancer Susceptibility: a Multi-Tools Bioinformatics Approach.

The main focus of this investigation is to identify deleterious single nucleotide polymorphisms (SNPs) located in the BRCA2 gene through in silico approach, thereby,providing an understanding of potential consequences regarding the susceptibility to breast cancer. The GenomAD database was used to identify SNPs. To determine the potential adverse consequences, our study employed various prediction tools, including SIFT, PolyPhen, PredictSNP, SNAP2, PhD-SNP, and ClinVar. The pathogenicity associated with the deleterious snSNPs was evaluated bu MutPred and Fathmm. Additionally, I-Mutant and MuPro were used to assess the stability, followed by conservation and protein-protein interaction analysis using robust computational tools. The 3D structure of BRCA2 protein was generated by SwissModel, followed by validation using PROCHECK and Errat. The GenomAD database was used to identify a total of 7, 921 SNPs, including 1940 missense SNPs. A set of 69 SNPs predicted by consensus to be damaging across all platforms was identified. Mutpred and Fathmm identified 48 and 38 SNPs, respectively to be associated with cancer. While I- Mutant and MuPro assays suggested 22 SNPs to decrease protein stability. Additionally, these 22 SNPs reside within highly conserved regions of the BRCA2 protein. Domain analysis, utilizing InterPro, pinpointed 18 deleterious mutations within crucial DNA binding domains and one in the BRC repeat region. This study establishes a foundation for future experimental validations and the creation of breast cancer-targeted treatment approaches.

MISSENSE MUTATIONS IN THE IRAK1 GENE ARE ASSOCIATED WITH AN INCREASED RISK OF SYSTEMIC LUPUS ERYTHEMATOSUS

Single nucleotide polymorphisms (SNPs) are the most common form of genetic variation in humans. Missense SNPs can change protein structure and function. This study aimed to determine missense SNPs of the IRAK1 gene that can affect the amino acid sequence and lead to changes in protein structure and function, as well as their relationship as a risk factor for SLE. In this in silico method, several bioinformatics tools have been used to identify missense SNPs, including their properties and impacts, as well as their interaction networks with proteins. The tools used were PolyPhenv2, SIFT, PhD-SNP, PROVEAN, SNAP, Panthers, I-Mutant 3.0, and GeneMania. Four missense SNPs, rs11465830, rs1059702, rs1059703, and 10127175, were obtained from the NCBI SNP database. The SIFT test results showed that all the SNPs were tolerant. In the test results obtained using PolyPhen, the four SNPs were benign. The results of the probe test indicated that the four SNPs were neutral. When tested with SNAP, one SNP was neutral, and three others had an impact. In the PhD-SNP test, all SNPs were neutral. In the panther test, all SNPs were benign. The I-mutant assay showed that the four SNPs could decrease protein stability. Tests with GeneMania have reported that most interactions between genes were between IRAK1 and MYD88, and physical interactions were the most dominant form of interaction. Conclusion. rs10127175, rs11465830, rs1059702, and rs1059703 are missense SNPs in IRAK1, which can disrupt protein stability and be a risk factor for SLE. Keywords: IRAK1, SNP, Missense, Systemic Lupus Erythematosus

Reprint of: Recessive APC2 missense variants associated with epilepsies without neurodevelopmental disorders

ObjectivesThe APC2 gene, encoding adenomatous polyposis coli protein-2, is involved in cytoskeletal regulation in neurons responding to endogenous extracellular signals and plays an important role in brain development. Previously, the APC2 variants have been reported to be associated with cortical dysplasia and intellectual disability. This study aims to explore the association between APC2 variants and epilepsy. MethodsWhole-exome sequencing (WES) was performed in cases (trios) with epilepsies of unknown causes. The damaging effects of variants were predicted by protein modeling and in silico tools. Previously reported APC2 variants were reviewed to analyze the genotype-phenotype correlations. ResultsFour pairs of compound heterozygous missense variants were identified in four unrelated patients with epilepsy without brain malformation/intellectual disability. All variants presented no or low allele frequencies in the controls. The missense variants were predicted to be damaging by silico tools, and affect hydrogen bonding with surrounding amino acids or decreased protein stability. Patients with variants that resulted in significant changes in protein stability exhibited more severe and intractable epilepsy, whereas patients with variants that had minor effect on protein stability exhibited relatively mild phenotypes. The previously reported APC2 variants in patients with complex cortical dysplasia with other brain malformations-10 (CDCBM10; MIM: 618677) were all truncating variants; in contrast, the variants identified in epilepsy in this study were all missense variants, suggesting a potential genotype-phenotype correlation. SignificanceThis study suggests that APC2 is potentially associated with epilepsy without brain malformation/intellectual disability. The genotype-phenotype correlation helps to understand the underlying mechanisms of phenotypic heterogeneity.

Most Monogenic Disorders Are Caused by Mutations Altering Protein Folding Free Energy.

Revealing the molecular effect that pathogenic missense mutations have on the corresponding protein is crucial for developing therapeutic solutions. This is especially important for monogenic diseases since, for most of them, there is no treatment available, while typically, the treatment should be provided in the early development stages. This requires fast targeted drug development at a low cost. Here, we report an updated database of monogenic disorders (MOGEDO), which includes 768 proteins and the corresponding 2559 pathogenic and 1763 benign mutations, along with the functional classification of the corresponding proteins. Using the database and various computational tools that predict folding free energy change (ΔΔG), we demonstrate that, on average, 70% of pathogenic cases result in decreased protein stability. Such a large fraction indicates that one should aim at in silico screening for small molecules stabilizing the structure of the mutant protein. We emphasize that knowledge of ΔΔG is essential because one wants to develop stabilizers that compensate for ΔΔG, but do not make protein over-stable, since over-stable protein may be dysfunctional. We demonstrate that, by using ΔΔG and predicted solvent exposure of the mutation site, one can develop a predictive method that distinguishes pathogenic from benign mutations with a success rate even better than some of the leading pathogenicity predictors. Furthermore, hydrophobic-hydrophobic mutations have stronger correlations between folding free energy change and pathogenicity compared with others. Also, mutations involving Cys, Gly, Arg, Trp, and Tyr amino acids being replaced by any other amino acid are more likely to be pathogenic. To facilitate further detection of pathogenic mutations, the wild type of amino acids in the 768 proteins mentioned above was mutated to other 19 residues (14,847,817 mutations), the ΔΔG was calculated with SAAFEC-SEQ, and 5,506,051 mutations were predicted to be pathogenic.