The rs61742690 (S783N) single nucleotide polymorphism is a suitable target for disrupting BCL11A-mediated foetal-to-adult globin switching

Base editing of key residues in the BCL11A-XL-specific zinc finger domains derepresses fetal globin expression

BCL11A-XL directly binds and represses the fetal globin (HBG1/2) gene promoters, using 3 zinc-finger domains (ZnF4, ZnF5, and ZnF6), and is a potential target for β-hemoglobinopathy treatments. Disrupting BCL11A-XL results in derepression of fetal globin and high HbF, but also affects hematopoietic stem and progenitor cell (HSPC) engraftment and erythroid maturation. Intriguingly, neurodevelopmental patients with ZnF domain mutations have elevated HbF with normal hematological parameters. Inspired by this natural phenomenon, we used both CRISPR-Cas9 and base editing at specific ZnF domains and assessed the impacts on HbF production and hematopoietic differentiation. Generating indels in the various ZnF domains by CRISPR-Cas9 prevented the binding of BCL11A-XL to its site in the HBG1/2 promoters and elevated the HbF levels but affected normal hematopoiesis. Far fewer side effects were observed with base editing- for instance, erythroid maturation in vitro was near normal. However, we observed a modest reduction in HSPC engraftment and a complete loss of B cell development in vivo, presumably because current base editing is not capable of precisely recapitulating the mutations found in patients with BCL11A-XL-associated neurodevelopment disorders. Overall, our results reveal that disrupting different ZnF domains has different effects. Disrupting ZnF4 elevated HbF levels significantly while leaving many other erythroid target genes unaffected, and interestingly, disrupting ZnF6 also elevated HbF levels, which was unexpected because this region does not directly interact with the HBG1/2 promoters. This first structure/function analysis of ZnF4-6 provides important insights into the domains of BCL11A-XL that are required to repress fetal globin expression and provide framework for exploring the introduction of natural mutations that may enable the derepression of single gene while leaving other functions unaffected.

In-silico assessment of high-risk non-synonymous SNPs in ADAMTS3 gene associated with Hennekam syndrome and their impact on protein stability and function

Hennekam Lymphangiectasia-Lymphedema Syndrome 3 (HKLLS3) is a rare genetical disorder caused by mutations in a few genes including ADAMTS3. It is characterized by lymphatic dysplasia, intestinal lymphangiectasia, severe lymphedema and distinctive facial appearance. Up till now, no extensive studies have been conducted to elucidate the mechanism of the disease caused by various mutations. As a preliminary investigation of HKLLS3, we sorted out the most deleterious nonsynonymous single nucleotide polymorphisms (nsSNPs) that might affect the structure and function of ADAMTS3 protein by using a variety of in silico tools. A total of 919 nsSNPs in the ADAMTS3 gene were identified. 50 nsSNPs were predicted to be deleterious by multiple computational tools. 5 nsSNPs (G298R, C567Y, A370T, C567R and G374S) were found to be the most dangerous and can be associated with the disease as predicted by different bioinformatics tools. Modelling of the protein shows it can be divided into segments 1, 2 and 3, which are connected by short loops. Segment 3 mainly consists of loops without substantial secondary structures. With prediction tools and molecular dynamics simulation, some SNPs were found to significantly destabilize the protein structure and disrupt the secondary structures, especially in segment 2. The deleterious effects of mutations in segment 1 are possibly not from destabilization but from other factors such as the change in phosphorylation as suggested by post-translational modification (PTM) studies. This is the first-ever study of ADAMTS3 gene polymorphism, and the predicted nsSNPs in ADAMST3, some of which have not been reported yet in patients, will serve for diagnostic purposes and further therapeutic implications in Hennekam syndrome, contributing to better diagnosis and treatment.

Computational screening and analysis of deleterious nsSNPs in human p14ARF (CDKN2A gene) protein using molecular dynamic simulation approach

Cyclin-dependent kinase inhibitor 2 A (CDKN2A) gene belongs to the cyclin-dependent kinase family that code for two transcripts (p16INK4A and p14ARF), both work as tumor suppressors proteins. The mutation that occurs in the p14ARF protein can lead to different types of cancers. Single nucleotide polymorphisms (SNPs) are an important type of genetic alteration that can lead to different types of diseases. In this study, we applied the computational strategy on human p14ARF protein to identify the potential deleterious nsSNPs and check their impact on the structure, function, and protein stability. We applied more than ten prediction tools to screen the retrieved 288 nsSNPs, consequently extracting four deleterious nsSNPs i.e., rs139725688 (R10G), rs139725688 (R21W), rs374360796 (F23L) and rs747717236 (L124R). Homology modeling, conservation and conformational analysis of mutant models were performed to examine the divergence of these variants from the native p14ARF structure. All-atom molecular dynamics simulation revealed a significant impact of these mutations on protein stability, compactness, globularity, solvent accessibility and secondary structure elements. Protein-protein interactions indicated that p14ARF operates as a hub linking clusters of different proteins and that changes in p14ARF may result in the disassociation of numerous signal cascades. Our current study is the first survey of computational analysis on p14ARF protein that determines the association of these nsSNPs with the altered function of p14ARF protein and leads to the development of various types of cancers. This research proposes the described functional SNPs as possible targets for proteomic investigations, diagnostic procedures, and treatments.Communicated by Ramaswamy H. Sarma.

In Silico Analysis of nsSNPs of Human KRAS Gene and Protein Modeling Using Bioinformatic Tools

The KRAS gene belongs to the RAS family and codes for 188 amino acid residues of KRAS protein, with a molecular mass of 21.6 kD. Non-synonymous single-nucleotide polymorphisms (nsSNPs) have been identified within the coding region in which some are associated with different diseases. However, structural changes are not well defined yet. In this study, we first categorized SNPs in the KRAS coding area and then used computational methods to determine their impact on the protein structure and stability. In addition, the three-dimensional model of KRAS was taken from the Protein Data Bank for structural modeling. Furthermore, genomic data were extracted from a variety of sources, including the 1000 Genome Project, dbSNPs, and ENSEMBLE, and assessed through in silico methods. Based on various tools used in this study, 10 out of 48 missense SNPs with rsIDs were found deleterious. The substitution of alanine for proline at position 146 pushed several residues toward the center of the protein. Arginine instead of leucine has a minor effect on protein structure and stability. In addition, the substitution of proline for leucine at the 34th position disrupted the structure and led to a bigger size than the wild-type protein, hence interrupting the protein interaction. Using the well-intended computational approach and applying several bioinformatic tools, we characterized and identified most damaging nsSNPs and further explored the structural dynamics and stability of KRAS protein.

Emerging of composition variations of SARS-CoV-2 spike protein and human ACE2 contribute to the level of infection: in silico approaches

SARS-CoV-2 is causative of pandemic COVID-19. There is a sequence similarity between SARS-CoV-2 and SARS-CoV; however, SARS-CoV-2 RBDs (receptor-binding domain) binds 20-fold strongly with human angiotensin-converting enzyme 2 (hACE2) than SARS-CoV. The study aims to investigate protein-protein interactions (PPI) of hACE2 with SARS-CoV-2 RBD between wild and variants to detect the most influential interaction. Variants of hACE2 were retrieved from NCBI and subjected to determine the most pathogenic nsSNPs. Probability of PPIs determines the binding affinity of hACE2 genetic variants with RBD was investigated. Composition variations at the hACE2 and RBD were processed for PatchDock and refined by FireDock for the PPIs. Twelve nsSNPs were identified as the top pathogenic from SNPs (n = 7489) in hACE2 using eight bioinformatics tools. Eight RBD variants were complexed with 12 nSNPS of hACE2, and the global energy scores (Kcal/mol) were calculated and classified as very weak (-3.93 to -18.43), weak (-18.42 to -32.94), moderate (-32.94 to -47.44), strong (-47.44 to -61.95) and very strong (-61.95 to -76.46) zones. Seven composition variants in the very strong zone [G726R-G476S; R768W-V367F; Y252N-V483A; Y252N-V367F; G726R-V367F; N720D-V367F and N720D-F486L], and three in very weak [P263S-S383C; RBD-H378R; G726R-A348T] are significantly (p < 0.00001) varied for global energy score. Zonation of the five zones was established based on the scores to differentiate the effect of hACE2 and RBD variants on the binding affinity. Moreover, our findings support that the combination of hACE2 and RBD is key players for the risk of infection that should be done by further laboratory studies.Communicated by Ramaswamy H. Sarma.

In-silico analysis of nonsynonymous genomic variants within CCM2 gene reaffirm the existence of dual cores within typical PTB domain

Purpose

The objective of this study is to validate the existence of dual cores within the typical phosphotyrosine binding (PTB) domain and to identify potentially damaging and pathogenic nonsynonymous coding single nuclear polymorphisms (nsSNPs) in the canonical PTB domain of the CCM2 gene that causes cerebral cavernous malformations (CCMs).

Methods

The nsSNPs within the coding sequence for PTB domain of human CCM2 gene, retrieved from exclusive database searches, were analyzed for their functional and structural impact using a series of bioinformatic tools. The effects of mutations on the tertiary structure of the PTB domain in human CCM2 protein were predicted to examine the effect of nsSNPs on the tertiary structure of PTB Cores.

Results

Our mutation analysis, through alignment of protein structures between wildtype CCM2 and mutant, predicted that the structural impacts of pathogenic nsSNPs is biophysically limited to only the spatially adjacent substituted amino acid site with minimal structural influence on the adjacent core of the PTB domain, suggesting both cores are independently functional and essential for proper CCM2 PTB function.

Conclusion

Utilizing a combination of protein conservation and structure-based analysis, we analyzed the structural effects of inherited pathogenic mutations within the CCM2 PTB domain. Our results predicted that the pathogenic amino acid substitutions lead to only subtle changes locally, confined to the surrounding tertiary structure of the PTB core within which it resides, while no structural disturbance to the neighboring PTB core was observed, reaffirming the presence of independently functional dual cores in the CCM2 typical PTB domain.

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The pathogenic amino acid mutants lead to subtle structural changes in the PTB core.

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No structural disturbance to the neighboring PTB core was observed.

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Data reaffirm the presence of dual functional cores in the CCM2 PTB domain.

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More new genetic variants leading to CCM pathogenesis were suggested.

Predicting the Most Deleterious Missense Nonsynonymous Single-Nucleotide Polymorphisms of Hennekam Syndrome-Causing CCBE1 Gene, In Silico Analysis

Hennekam lymphangiectasia-lymphedema syndrome has been linked to single-nucleotide polymorphisms in the CCBE1 (collagen and calcium-binding EGF domains 1) gene. Several bioinformatics methods were used to find the most dangerous nsSNPs that could affect CCBE1 structure and function. Using state-of-the-art in silico tools, this study examined the most pathogenic nonsynonymous single-nucleotide polymorphisms (nsSNPs) that disrupt the CCBE1 protein and extracellular matrix remodeling and migration. Our results indicate that seven nsSNPs, rs115982879, rs149792489, rs374941368, rs121908254, rs149531418, rs121908251, and rs372499913, are deleterious in the CCBE1 gene, four (G330E, C102S, C174R, and G107D) of which are the highly deleterious, two of them (G330E and G107D) have never been seen reported in the context of Hennekam syndrome. Twelve missense SNPs, rs199902030, rs267605221, rs37517418, rs80008675, rs116596858, rs116675104, rs121908252, rs147974432, rs147681552, rs192224843, rs139059968, and rs148498685, are found to revert into stop codons. Structural homology-based methods and sequence homology-based tools revealed that 8.8% of the nsSNPs are pathogenic. SIFT, PolyPhen2, M-CAP, CADD, FATHMM-MKL, DANN, PANTHER, Mutation Taster, LRT, and SNAP2 had a significant score for identifying deleterious nsSNPs. The importance of rs374941368 and rs200149541 in the prediction of post-translation changes was highlighted because it impacts a possible phosphorylation site. Gene-gene interactions revealed CCBE1's association with other genes, showing its role in a number of pathways and coexpressions. The top 16 deleterious nsSNPs found in this research should be investigated further in the future while researching diseases caused CCBE1 gene specifically HS. The FT web server predicted amino acid residues involved in the ligand-binding site of the CCBE1 protein, and two of the substitutions (R167W and T153N) were found to be involved. These highly deleterious nsSNPs can be used as marker pathogenic variants in the mutational diagnosis of the HS syndrome, and this research also offers potential insights that will aid in the development of precision medicines. CCBE1 proteins from Hennekam syndrome patients should be tested in animal models for this purpose.

In Silico Analysis of High-Risk Missense Variants in Human ACE2 Gene and Susceptibility to SARS-CoV-2 Infection

SARS-CoV-2 coronavirus uses for entry to human host cells a SARS-CoV receptor of the angiotensin-converting enzyme (ACE2) that catalyzes the conversion of angiotensin II into angiotensin (1-7). To understand the effect of ACE2 missense variants on protein structure, stability, and function, various bioinformatics tools were used including SIFT, PANTHER, PROVEAN, PolyPhen2.0, I. Mutant Suite, MUpro, SWISS-MODEL, Project HOPE, ModPred, QMEAN, ConSurf, and STRING. All twelve ACE2 nsSNPs were analyzed. Six ACE2 high-risk pathogenic nsSNPs (D427Y, R514G, R708W, R710C, R716C, and R768W) were found to be the most damaging by at least six software tools (cumulative score between 6 and 7) and exert deleterious effect on the ACE2 protein structure and likely function. Additionally, they revealed high conservation, less stability, and having a role in posttranslation modifications such a proteolytic cleavage or ADP-ribosylation. This in silico analysis provides information about functional nucleotide variants that have an impact on the ACE2 protein structure and function and therefore susceptibility to SARS-CoV-2.

Congenital dyserythropoietic anemia and drug-induced liver injury present as bland cholestasis: A case report

Anemias and drug-induced liver injury(DILI) are separate disorders, which are difficult to diagnose. The clinical effects of DILI vary among individuals. However, the outcome determinants remain to be fully established. To the best of our knowledge, the role of anemia in DILI has yet to be reported. The present study reported on the case of one Chinese patient (male; age, 21 years) who experienced obvious drug-induced cholestasis. Of note, the hepatocyte injury was minimal compared with that in previously reported cases treated with the same drug. In addition, the patient suffered from mild hemolytic anemia with no obvious cause. A genetic pedigree analysis revealed compound heterozygous mutations in the congenital anemia-associated gene codanin 1, including the novel rare p.R1067H mutation. Treatment with ursodeoxycholic acid alone sufficed and the outcome was good. Therefore, whilst chronic hemolysis predisposed the liver to cholestasis, it could have shielded the liver from further injuries, since bilirubin, a by-product of hemolysis, is a known antioxidant. The results of the present study indicated that genetic screening may be used for the diagnosis of liver injury concurring with undiagnosed anemia.

Association of polymorphisms in the HBG1-HBD intergenic region with HbF levels

BACKGROUND

Increased levels of fetal hemoglobin (HbF) can improve the clinical course of the patients with sickle cell anemia (SCA) or β-thalassemia. The HBG1-HBD intergenic region plays an important role in this process. However, very few studies investigated whether the variations in this region have an effect on HbF expression.

METHODS

We retrieved all the SNP data in the HBG1-HBD intergenic region and defined the haplotype blocks, then performed cluster analysis and selected a tagSNP. A total of 500 normal individuals and 300 β-thalassemia carriers were enrolled. After routine blood and hemoglobin capillary electrophoresis testing, β-thalassemia mutations were detected using PCR-reverse dot blot. The genotypes of the rs4910736 (A > C) and rs10128556 (C > T) were determined using Sanger sequencing; the relationship between the two SNPs and the levels of HbF was analyzed.

RESULTS

Two haplotype blocks were constructed. Block 1 included seven haplotypes divided into two groups M and N by 11 tagSNPs, among which rs4910736 was selected as a tagSNP, while block 2 included three haplotypes. We found that the haplotypes of block 1 were statistically associated with HbF levels, but the non-tagSNP rs10128556 was shown to be more strongly associated with HbF levels than rs4910736.

CONCLUSION

This work proved that the haplotypes in the HBG1-HBD intergenic region and SNP rs10128556 are both statistically associated with HbF levels, revealing the association of polymorphisms in the HBG1-HBD intergenic region with HbF levels.

State-of-the-art tools to identify druggable protein ligand of SARS-CoV-2

INTRODUCTION

The SARS-CoV-2 (previously 2019-nCoV) outbreak in Wuhan, China and other parts of the world affects people and spreads coronavirus disease 2019 (COVID-19) through human-to-human contact, with a mortality rate of > 2%. There are no approved drugs or vaccines yet available against SARS-CoV-2.

MATERIAL AND METHODS

State-of-the-art tools based on in-silico methods are a cost-effective initial approach for identifying appropriate ligands against SARS-CoV-2. The present study developed the 3D structure of the envelope and nucleocapsid phosphoprotein of SARS-CoV-2, and molecular docking analysis was done against various ligands.

RESULTS

The highest log octanol/water partition coefficient, high number of hydrogen bond donors and acceptors, lowest non-bonded interaction energy between the receptor and the ligand, and high binding affinity were considered for the best ligand for the envelope (mycophenolic acid: log P = 3.00; DG = -10.2567 kcal/mol; pKi = 7.713 µM) and nucleocapsid phosphoprotein (1-[(2,4-dichlorophenyl)methyl]pyrazole-3,5-dicarboxylic acid: log P = 2.901; DG = -12.2112 kcal/mol; pKi = 7.885 µM) of SARS-CoV-2.

CONCLUSIONS

The study identifies the most potent compounds against the SARS-CoV-2 envelope and nucleocapsid phosphoprotein through state-of-the-art tools based on an in-silico approach. A combination of these two ligands could be the best option to consider for further detailed studies to develop a drug for treating patients infected with SARS-CoV-2, COVID-19.

D76V, L161R, and C117S are the most pathogenic amino acid substitutions with several dangerous consequences on leptin structure, function, and stability

Background

Leptin is a versatile hormone with a variety of functions, including regulation of food intake by inhibiting hunger. Any deleterious mutation in this protein can lead to serious consequences for the body. This study was conducted to identify the most deleterious non-synonymous single-nucleotide polymorphisms (nsSNPs) of human LEP gene and their impact on its encoded protein.

Methods

To predict the possible impact of nsSNPs on leptin, a total of 90 nsSNPs were retrieved from dbSNP and investigated using many in silico tools which specially designed to analyze nsSNPs’ consequences on the protein structure, function, and stability.

Results

Three nsSNPs, namely D76V, L161R, and C117S, were found to be completely deleterious by all utilized nsSNPs prediction tools, thus affecting leptin protein structure, biological activity, and stability. Evolutionary information indicated L161R and C117S mutations to be located in extremely high conserved positions. Furthermore, several deleterious mechanisms controlled by both L161R and C117S mutations which alter several motifs in the secondary structure of leptin were detected. However, all D76V, L161R, and C117S mutations exhibited alteration in polar interactions in their representative positions. Further in-depth analyses proved several harmful structural effects of the three nsSNPs on leptin, which may lead to multiple intrinsic disorders in the altered protein forms.

Conclusions

This study provides the first comprehensive computation of the effect of the most damaging nsSNPs on leptin. The exploration of these missense mutations may present novel perspectives for various deleterious consequences originated from such amino acids substitutions. The dynamics of leptin performance, therefore, in many biological pathways, may be changed to create a variety of disorders, such as obesity and diabetes. These findings will help in detecting the most harmful variations needed to be screened for clinically diagnosed patients with leptin disorders.

Trial registration

ISRCTN73824458

In silico analysis of nonsynonymous single-nucleotide polymorphisms (nsSNPs) of the SMPX gene

Mutations in the SMPX gene can disrupt the regular activity of the SMPX protein, which is involved in the hearing process. Recent reports showing a link between nonsynonymous single-nucleotide polymorphisms (nsSNPs) in SMPX and hearing loss, thus classifying deleterious SNPs in SMPX will be an uphill task before designing a more extensive population study. In this study, damaging nsSNPs of SMPX from the dbSNP database were identified by using 13 bioinformatics tools. Initially, the impact of nsSNPs in the SMPX gene were evaluated through different in silico predictors; and the deleterious convergent changes were analyzed by energy-minimization-guided residual network analysis. In addition, the pathogenic effects of mutations in SMPX-mediated protein-protein interactions were also characterized by structural modeling and binding energy calculations. A total of four mutations (N19D, A29T, K54N, and S71L) were found to be highly deleterious by all the tools, which are located at highly conserved regions. Furthermore, all four mutants showed structural alterations, and the communities of amino acids for mutant proteins were readily changed, compared to the wild-type. Among them, A29T (rs772775896) was revealed as the most damaging nsSNP, which caused significant structural deviation of the SMPX protein, as a result reducing the binding affinity to other functional partners. These findings reflect the computational insights into the deleterious role of nsSNPs in SMPX, which might be helpful for subjecting wet-lab confirmatory analysis.

Molecular simulation studies on B-cell lymphoma/leukaemia 11A (BCL11A)

B-cell lymphoma/leukaemia 11A (BCL11A) is a modulator of foetal-to-adult globin switching and is involved in brain development and normal lymphopoiesis. The three-dimensional structure of BCL11A and its structural domains had not yet been completely determined; hence, this study aimed to elucidate the structural domains of BCL11A. Molecular modelling and dynamics simulation studies were conducted using in silico tools with the templates selected based on Basic Local Alignment Search Tool (BLAST) searches of the Protein Data Bank (PDB). Ten protein models were generated using the MODELLER software, and the best model was selected according to the Discrete Optimised Protein Energy (DOPE) score and validated using the RAMPAGE server by evaluation of the Ramachandran plot. More than 93% of the amino acid residues of the best model of BCL11A were found to be in the favoured and allowed regions. The best model was validated using a 100-ns time span molecular dynamics simulation. The root-mean-square deviation, root-mean-square fluctuation, and radius of gyration values were found to explain the stability of the best BCL11A protein molecular model generated in the study. The validated best model of the BCL11A protein may be useful for effective modulator studies on foetal-to-adult globin switching and related research.