In Silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B

C, George Priya Doss

doi:10.1186/1423-0127-19-30

Cited by 17 publications

(4 citation statements)

References 137 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Similar to previous studies 7 – 11 , we found that mutations at positions with low solvent-accessible and low solvent-excluded surface areas, as well as in highly conserved residues are related to more severe phenotypes (Fig. 1b and Supplementary Fig.…”

Section: Resultssupporting

confidence: 90%

“…These transient and precise interactions can be disturbed by even one amino acid substitution—and the degree of disruption depends on the position and the type of amino acid replacement 27 . Similar to previous studies, we verified that the surface exposure and the conservation of a residue have a strong relation to the HA phenotype 7 – 12 . Notorious examples are mutations at residues Asp186 and Met339, buried inside FVIII and whose side-chains are involved in a complex hydrogen-bond network and contribute with major energy in copper binding 26 , 40 .…”

Section: Discussionsupporting

confidence: 90%

“…Reported mutations include deletions and inversions of large parts of its encoding gene, as well as single-nucleotide polymorphisms that do not change the reading frame, but replace an amino acid and generate a defective protein. Using gene information and protein structure properties, previous studies revealed fundamental aspects of single amino acid changes and their relation to severe or mild forms of HA 7 – 12 . However, the lack of strict data curation and the analysis of each property in isolation prevented these methods from predicting and mechanistically understanding the occurrence of mild, moderate, and severe phenotypes.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Prediction of hemophilia A severity using a small-input machine-learning framework

et al. 2021

View full text Add to dashboard Cite

Hemophilia A is a relatively rare hereditary coagulation disorder caused by a defective F8 gene resulting in a dysfunctional Factor VIII protein (FVIII). This condition impairs the coagulation cascade, and if left untreated, it causes permanent joint damage and poses a risk of fatal intracranial hemorrhage in case of traumatic events. To develop prophylactic therapies with longer half-lives and that do not trigger the development of inhibitory antibodies, it is essential to have a deep understanding of the structure of the FVIII protein. In this study, we explored alternative ways of representing the FVIII protein structure and designed a machine-learning framework to improve the understanding of the relationship between the protein structure and the disease severity. We verified a close agreement between in silico, in vitro and clinical data. Finally, we predicted the severity of all possible mutations in the FVIII structure – including those not yet reported in the medical literature. We identified several hotspots in the FVIII structure where mutations are likely to induce detrimental effects to its activity. The combination of protein structure analysis and machine learning is a powerful approach to predict and understand the effects of mutations on the disease outcome.

show abstract

Section: Resultssupporting

confidence: 90%

Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Prediction of hemophilia A severity using a small-input machine-learning framework

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Other groups used computational techniques to identify properties of the F8 gene and the FVIII protein that are related to the occurrence of mild or severe forms of HA (Refs. 8 – 13 ). However, the limited input data and the lack of generalization to all residues precluded the understanding of the effect of substitutions of each specific residue.…”

Section: Introductionmentioning

confidence: 99%

Protein residue network analysis reveals fundamental properties of the human coagulation factor VIII

Lopes

Rios

Nogueira

et al. 2021

Sci Rep

View full text Add to dashboard Cite

Hemophilia A is an X-linked inherited blood coagulation disorder caused by the production and circulation of defective coagulation factor VIII protein. People living with this condition receive either prophylaxis or on-demand treatment, and approximately 30% of patients develop inhibitor antibodies, a serious complication that limits treatment options. Although previous studies performed targeted mutations to identify important residues of FVIII, a detailed understanding of the role of each amino acid and their neighboring residues is still lacking. Here, we addressed this issue by creating a residue interaction network (RIN) where the nodes are the FVIII residues, and two nodes are connected if their corresponding residues are in close proximity in the FVIII protein structure. We studied the characteristics of all residues in this network and found important properties related to disease severity, interaction to other proteins and structural stability. Importantly, we found that the RIN-derived properties were in close agreement with in vitro and clinical reports, corroborating the observation that the patterns derived from this detailed map of the FVIII protein architecture accurately capture the biological properties of FVIII.

show abstract

In silico discrimination of nsSNPs in hTERT gene by means of local DNA sequence context and regularity

et al. 2013

View full text Add to dashboard Cite

Understanding and predicting the significance of novel genetic variants revealed by DNA sequencing is a major challenge to integrate and interpret in medical genetics with medical practice. Recent studies have afforded significant advances in characterization and predicting the association of single nucleotide polymorphisms in human TERT with various disorders, but the results remain inconclusive. In this context, a comparative study between disease causing and novel mutations in hTERT gene was performed computationally. Out of 59 missense mutations, five variants were predicted to be less stable with the most deleterious effect on hTERT gene by in silico tools, in which two mutations (L584W and M970T) were not previously reported to be involved in any of the human disorders. To get insight into the structural and functional impact due to the mutation, docking study and interaction analysis was performed followed by 6 ns molecular dynamics simulation. These results may provide new perspectives for the targeted drug discovery in the coming future.

show abstract

In Silico profiling of deleterious amino acid substitutions of potential pathological importance in haemophlia A and haemophlia B

Cited by 17 publications

References 137 publications

Prediction of hemophilia A severity using a small-input machine-learning framework

Prediction of hemophilia A severity using a small-input machine-learning framework

Protein residue network analysis reveals fundamental properties of the human coagulation factor VIII

In silico discrimination of nsSNPs in hTERT gene by means of local DNA sequence context and regularity

Contact Info

Product

Resources

About