Structural and functional analysis of disease-associated mutations in GOT1 gene: An in silico study

Computational screening of pathogenic missense nsSNPs in heme oxygenase 1 (HMOX1) gene and their structural and functional consequences

Heme Oxygenase 1 (HMOX1) is a cytoprotective enzyme, exhibiting the highest activity in the spleen, catalyzing the heme ring breakdown into products of biological significance- biliverdin, CO, and Fe2+. In vascular cells, HMOX1 possesses strong anti-apoptotic, antioxidant, anti-proliferative, anti-inflammatory, and immunomodulatory actions. The majority of these activities are crucial for the prevention of atherogenesis. Single amino acid substitutions in proteins generated by missense non-synonymous single nucleotide polymorphism (nsSNPs) in the protein-encoding regions of genes are potent enough to cause significant medical challenges due to the alteration of protein structure and function. The current study aimed at characterizing and analyzing high-risk nsSNPs associated with the human HMOX1 gene. Preliminary screening of the total available 288 missense SNPs was performed through the lens of deleteriousness and stability prediction tools. Finally, a total of seven nsSNPs (Y58D, A131T, Y134H, F166S, F167S, R183S and M186V) were found to be most deleterious by all tools that are present at highly conserved positions. Molecular dynamics simulations (MDS) analysis explained the mutational effects on the dynamic action of the wild-type and mutant proteins. In a nutshell, R183S (rs749644285) was identified as a highly detrimental mutation that could significantly render the enzymatic activity of HMOX1. The finding of this computational analysis might help subject the experimental confirmatory analysis to characterize the role of nsSNPs in HMOX1.Communicated by Ramaswamy H. Sarma.

Comprehensive bioinformatics analysis of structural and functional consequences of deleterious missense mutations in the human QDPR gene

Quinonoid dihydropteridine reductase (QDPR) is an enzyme that regulates tetrahydrobiopterin (BH4), a cofactor for enzymes involved in neurotransmitter synthesis and blood pressure regulation. Reduced QDPR activity can cause dihydrobiopterin (BH2) accumulation and BH4 depletion, leading to impaired neurotransmitter synthesis, oxidative stress, and increased risk of Parkinson's disease. A total of 10,236 SNPs were identified in the QDPR gene, with 217 being missense SNPs. Over 18 different sequence-based and structure-based tools were employed to assess the protein's biological activity, with several computational tools identifying deleterious SNPs. Additionally, the article provides detailed information about the QDPR gene and protein structure and conservation analysis. The results showed that 10 mutations were harmful and linked to brain and central nervous system disorders, and were predicted to be oncogenic by Dr. Cancer and CScape. Following conservation analysis, the HOPE server was used to analyse the effect of six selected mutations (L14P, V15G, G23S, V54G, M107K, G151S) on the protein structure. Overall, the study provides insights into the biological and functional impact of nsSNPs on QDPR activity and the potential induced pathogenicity and oncogenicity. In the future, research can be conducted to systematically evaluate QDPR gene variation through clinical studies, investigate mutation prevalence across different geographical regions, and validate computational results with conclusive experiments.Communicated by Ramaswamy H. Sarma.

A computational study on structural and functional consequences of nsSNPs in human dopa decarboxylase

The Dopa Decarboxylase (DDC) gene plays an important role in the synthesis of biogenic amines such as dopamine, serotonin, and histamine. Non-synonymous single nucleotide polymorphisms (nsSNPs) in the DDC gene have been linked with various neurodegenerative disorders. In this study, a comprehensive in silico analysis of nsSNPs in the DDC gene was conducted to assess their potential functional consequences and associations with disease outcomes. Using publicly available databases, a complete list of nsSNPs in the DDC gene was obtained. 29 computational tools and algorithms were used to characterise the effects of these nsSNPs on protein structure, function, and stability. In addition, the population-based association studies were performed to investigate possible associations between specific nsSNPs and arthritis. Our research identified four novel DDC gene nsSNPs that have a major impact on the structure and function of proteins. Through molecular dynamics simulations (MDS), we observed changes in the stability of the DDC protein induced by specific nsSNPs. Furthermore, population-based association studies have revealed potential associations between certain DDC nsSNPs and various neurological disorders, including Parkinson's disease and dementia. The in silico approach used in this study offers insightful information about the functional effects of nsSNPs in the DDC gene. These discoveries provide insight into the cellular processes that underlie cognitive disorders. Furthermore, the detection of disease-associated nsSNPs in the DDC gene may facilitate the development of tailored and targeted therapy approaches.Communicated by Ramaswamy H. Sarma.

Unraveling the function and structure impact of deleterious missense SNPs in the human OX1R receptor by computational analysis

The orexin/hypocretin receptor type 1 (OX1R) plays a crucial role in regulating various physiological functions, especially feeding behavior, addiction, and reward. Genetic variations in the OX1R have been associated with several neurological disorders. In this study, we utilized a combination of sequence and structure-based computational tools to identify the most deleterious missense single nucleotide polymorphisms (SNPs) in the OX1R gene. Our findings revealed four highly conserved and structurally destabilizing missense SNPs, namely R144C, I148N, S172W, and A297D, located in the GTP-binding domain. Molecular dynamics simulations analysis demonstrated that all four most detrimental mutant proteins altered the overall structural flexibility and dynamics of OX1R protein, resulting in significant changes in the structural organization and motion of the protein. These findings provide valuable insights into the impact of missense SNPs on OX1R function loss and their potential contribution to the development of neurological disorders, thereby guiding future research in this field.

Comprehensive analysis of non-synonymous missense SNPs of human galactose mutarotase (GALM) gene: an integrated computational approach

Missense Non-synonymous single nucleotide polymorphisms (nsSNPs) of Galactose Mutarotase (GALM) are associated with the Novel type of Galactosemia (Galactosemia type 4) together with symptoms such as high blood galactose levels and eye cataracts. The objective of the present study was to identify deleterious nsSNPs of GALM recorded on the dbSNP database through comprehensive insilico analysis. Among the 319 missense nsSNPs reported, various insilco tools predicted R78S, R82G, A163E, P210S, Y281C, E307G and F339C as the most deleterious mutations. Structural analysis, PTM analysis and molecular dynamics simulations (MDS) were carried out to understand the effect of these mutations on the structural and physicochemical properties of the GALM protein. The residues R82G and E307G were found to be part of the binding site that resulted in decreased surface accessibility. Replacing the charged wild-type residue with a neutral mutant type affected its substrate binding. All 7 mutations were found to increase the rigidity of the protein structure, which is unfavorable during ligand binding. The mutation F339E made the protein structure more rigid than all the other mutations. Y281 is a phosphorylated site, and therefore, less significant structural changes were observed when compared to other mutations; however, it may have significant differences in the usual functioning of the protein. In summary, the structural and functional analysis of missense SNPs of GALM is important to reduce the number of potential mutations to be evaluated in vitro to understand the association with some genetic diseases.Communicated by Ramaswamy H. Sarma.

Field measures of strengthen plant-microbial remediation of PAHs-FQs compound pollution

In this study, five PAHs (benzo [b] fluoranthene (BbF), phenanthrene (Phe), fluoranthene (Flu), fluorene (Fl), benzo [A] pyrene (Bap)), and five FQs (ofloxacin (OFL), enrofloxacin (ENR), ciprofloxacin (CIP), norfloxacin (NOR), lomefloxacin (LOM)) were selected as ligands; peroxidase (1NML) was selected as receptor degrading protein. In the plant-microbial degradation, the factors with significant inhibitory effects are NOR, Bap, CIP, ENR, OFL, Flu, LOM, Phe, Fl, and BbF by the fractional factorial design experiment and molecular docking-assisted molecular dynamics methods. Using Taguchi experiment and molecular dynamics simulation methods, the main external field measures were designed and screened to effectively promote the degradation of PAHs-FQs under the combined pollution scenarios of Bap-CIP and BbF-NOR, respectively. The peroxidase mutation design plans with enhanced substrate affinity were then designed and screened using the DS software by predicting the virtual key amino acid of peroxidase. The novel biodegradable enzymes 2YCD-1, 2YCD-4, 2YCD-5, 2YCD-7, and 2YCD-9 had better structures and showed excellent degradability for PAHs and FQs. This study explored the degradation rules of the composite pollutants in the coexistence systems of multiple PAHs and FQs, providing the best external field measures for the control and treatment of the combined pollution effects of different PAHs and FQs. Overall, the current study has important practical significance for promoting the plant-microbial joint remediation of PAHs-FQs pollution and for reducing the combined pollution of PAHs and FQs in farmland systems.

Dynamics of TUBB protein with five majorly occurring natural variants: a risk of cortical dysplasia

Beta-tubulin (TUBB) protein is one of the components of the microtubule cytoskeleton that plays a critical role in the central nervous system. Genetic variants of TUBB cause cortical dysplasia, a developmental brain defect implicated in axonal guidance and the neuron migration. In this study, we assess pathogenic variants (Q15K, Y222F, M299V, V353I, and E401K) of TUBB protein and compared with non-pathogenic variant G235S to determine their impact on protein dynamic to cause cortical dysplasia. Among the analyzed variants, Q15K, Y222F, M299V, and E401K were noticed to have deleterious effect. Then, variant structures were modeled and their affinity with their known cofactor Guanosine-5'-triphosphate (GTP) was assessed which showed diverse binding energies ranged between (-7.436 to -6.950 kcal/mol) for the variants compared to wild-type (-7.428 kcal/mol). Finally, the molecular dynamics simulation of each variant was investigated which showed difference in trajectory between the pathogenic and non-pathogenic variant. Our analysis suggests change in amino acid residue of TUBB structure has notably affects the protein flexibility and their interactions with known cofactor. Overall, our findings provide insight on the relationship between TUBB variants and their structural dynamics that may cause diverse effects leading to cortical dysplasia.

LncRNA-disease association identification using graph auto-encoder and learning to rank

Discovering the relationships between long non-coding RNAs (lncRNAs) and diseases is significant in the treatment, diagnosis and prevention of diseases. However, current identified lncRNA-disease associations are not enough because of the expensive and heavy workload of wet laboratory experiments. Therefore, it is greatly important to develop an efficient computational method for predicting potential lncRNA-disease associations. Previous methods showed that combining the prediction results of the lncRNA-disease associations predicted by different classification methods via Learning to Rank (LTR) algorithm can be effective for predicting potential lncRNA-disease associations. However, when the classification results are incorrect, the ranking results will inevitably be affected. We propose the GraLTR-LDA predictor based on biological knowledge graphs and ranking framework for predicting potential lncRNA-disease associations. Firstly, homogeneous graph and heterogeneous graph are constructed by integrating multi-source biological information. Then, GraLTR-LDA integrates graph auto-encoder and attention mechanism to extract embedded features from the constructed graphs. Finally, GraLTR-LDA incorporates the embedded features into the LTR via feature crossing statistical strategies to predict priority order of diseases associated with query lncRNAs. Experimental results demonstrate that GraLTR-LDA outperforms the other state-of-the-art predictors and can effectively detect potential lncRNA-disease associations. Availability and implementation: Datasets and source codes are available at http://bliulab.net/GraLTR-LDA.

A bioinformatics approach to the identification of novel deleterious mutations of human TPMT through validated screening and molecular dynamics

Polymorphisms of Thiopurine S-methyltransferase (TPMT) are known to be associated with leukemia, inflammatory bowel diseases, and more. The objective of the present study was to identify novel deleterious missense SNPs of TPMT through a comprehensive in silico protocol. The initial SNP screening protocol used to identify deleterious SNPs from the pool of all TPMT SNPs in the dbSNP database yielded an accuracy of 83.33% in identifying extremely dangerous variants. Five novel deleterious missense SNPs (W33G, W78R, V89E, W150G, and L182P) of TPMT were identified through the aforementioned screening protocol. These 5 SNPs were then subjected to conservation analysis, interaction analysis, oncogenic and phenotypic analysis, structural analysis, PTM analysis, and molecular dynamics simulations (MDS) analysis to further assess and analyze their deleterious nature. Oncogenic analysis revealed that all five SNPs are oncogenic. MDS analysis revealed that all SNPs are deleterious due to the alterations they cause in the binding energy of the wild-type protein. Plasticity-induced instability caused by most of the mutations as indicated by the MDS results has been hypothesized to be the reason for this alteration. While in vivo or in vitro protocols are more conclusive, they are often more challenging and expensive. Hence, future research endeavors targeted at TPMT polymorphisms and/or their consequences in relevant disease progressions or treatments, through in vitro or in vivo means can give a higher priority to these SNPs rather than considering the massive pool of all SNPs of TPMT.

A single nucleotide polymorphism of the thyrotropin releasing hormone degrading ectoenzyme (TRHDE) gene is associated with post-partum anestrus in Murrah buffalo

Thyrotropin releasing hormone degrading enzyme (TRHDE) gene is implicated in Thyrotropin releasing hormone (TRH) mediated prolactin secretion. It has been shown that the prolactin secretion alters the Gonadotropin-releasinghormone(GnRH) mediated estrous cycle. Therefore, TRHDE may also regulate postpartum anestrus. Earlier studies reported the role of non-synonymous single nucleotide polymorphism (SNPs) in various pathophysiological conditions by altering the structure and function of the proteins. Hence, in the present study, we identified SNPs in the putative promoter, first exon, middle exon and 3'-UTR containing the last exon of TRHDE gene and determined their association with postpartum anestrus (PPA) in Murrah buffaloes. We found one non synonymous SNP (G > C at 118095875 bp on chromosome 4) in the first exon of TRHDE and performed its association analysis in a population sample of 50 extreme PPA (residual PPAI: 123.06 ± 12.98 days) and 50 normal (residual PPAI: -80.46 ± 3.19 days) buffaloes. The residual PPAI value was the observed PPAI adjusted for the effect of 38 non-genetic factors. The analysis showed a significant (P < 0.004167) association of this SNP with PPA in buffaloes. Molecular dynamics simulations (MDS) also supported that the C allele altering Glutamine to Histidine at the amino acid 148 of TRHDE could enhance the stability and rigidity of TRHDE protein, which may lower its activity, increase TRH and prolactin, and reduce GnRH in PPA buffaloes. The MDS analysis further strengthens the association of the SNP (G > C) in the TRHDE gene with PPA condition in Murrah buffaloes. However, further investigation is needed to prove the MDS observations.