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

Lopes, Tiago J. S.; Rios, Ricardo; Nogueira, Tatiane; Mello, Rodrigo Fernandes de

doi:10.1038/s41598-021-92201-3

Cited by 9 publications

(12 citation statements)

References 65 publications

(77 reference statements)

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“…We observed that the centrality characteristics of the AT residues are similar to those of other proteins ( Lopes et al , 2021b , 2022 ), with a few residues interacting with several others, and numerous residues taking part in only a few interactions. In particular, when we consider the degree and the betweenness together, we immediately identify an emerging pattern in the AT structure, namely, the existence of residues with high-degree and high-betweenness (HDHB), residues with low-degree and high-betweenness (LDHB) and finally, residues displaying low-degree and low-betweenness (LDLB) ( Fig.…”

Section: Resultssupporting

confidence: 56%

Computational analyses reveal fundamental properties of the AT structure related to thrombosis

Lopes

Rios

et al. 2022

Bioinformatics Advances

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Blood coagulation is a vital process for humans and other species. Following an injury to a blood vessel, a cascade of molecular signals is transmitted, inhibiting and activating more than a dozen coagulation factors and resulting in the formation of a fibrin clot that ceases the bleeding. In this process, Antithrombin (AT), encoded by the SERPINC1 gene is a key player regulating the clotting activity and ensuring that it stops at the right time. In this sense, mutations to this factor often result in thrombosis - the excessive coagulation that leads to the potentially fatal formation of blood clots that obstruct veins. Although this process is well known, it is still unclear why even single residue substitutions to AT lead to drastically different phenotypes. In this study, to understand the effect of mutations throughout the AT structure, we created a detailed network map of this protein, where each node is an amino acid, and two amino acids are connected if they are in close proximity in the three-dimensional structure. With this simple and intuitive representation and a machine learning framework trained using genetic information from more than 130 patients, we found that different types of thrombosis have emerging patterns that are readily identifiable. Together, these results demonstrate how clinical features, genetic data and in silico analysis are converging to enhance the diagnosis and treatment of coagulation disorders.

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Section: Resultssupporting

confidence: 56%

Computational analyses reveal fundamental properties of the AT structure related to thrombosis

Lopes

Rios

et al. 2022

Bioinformatics Advances

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“…To address this issue, we created an in silico network representation of the FIXa structure—a residue interaction network (RIN)—where each of its residues is a node, and two nodes are connected by an edge if they are in close proximity to each other in the FIXa 3D structure. As we reported previously for FVIII ( Lopes et al, 2021a ; Lopes et al, 2021b ), this novel representation allowed us to calculate several centrality measures of each amino acid, effectively quantifying their importance in the FIXa structure and indicating which amino acids are more or less tolerant to substitutions. To ensure the robustness of this approach, we carefully validated our in silico findings against hundreds of clinical reports associating mutations to the severity of the HB symptoms.…”

Section: Introductionmentioning

confidence: 99%

A Machine Learning Framework Predicts the Clinical Severity of Hemophilia B Caused by Point-Mutations

2022

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Blood coagulation is a vital physiological mechanism to stop blood loss following an injury to a blood vessel. This process starts immediately upon damage to the endothelium lining a blood vessel, and results in the formation of a platelet plug that closes the site of injury. In this repair operation, an essential component is the coagulation factor IX (FIX), a serine protease encoded by the F9 gene and whose deficiency causes hemophilia B. If not treated by prophylaxis or gene therapy, patients with this condition are at risk of life-threatening bleeding episodes. In this sense, a deep understanding of the FIX protein and its activated form (FIXa) is essential to develop efficient therapeutics. In this study, we used well-studied structural analysis techniques to create a residue interaction network of the FIXa protein. Here, the nodes are the amino acids of FIXa, and two nodes are connected by an edge if the two residues are in close proximity in the FIXa 3D structure. This representation accurately captured fundamental properties of each amino acid of the FIXa structure, as we found by validating our findings against hundreds of clinical reports about the severity of HB. Finally, we established a machine learning framework named HemB-Class to predict the effect of mutations of all FIXa residues to all other amino acids and used it to disambiguate several conflicting medical reports. Together, these methods provide a comprehensive map of the FIXa protein architecture and establish a robust platform for the rational design of FIX therapeutics.

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“…This network topology can be analyzed with help of various centrality measures and helps identify structurally and functionally important nodes and edges 58 . It has been used in studying protein stability and folding, effects of mutations on protein structure, protein dynamics, allosteric regulations, identification of functionally and biologically important residues, identification of ligand binding sites, and so forth 59‐63 . Here, we make use of RIN to study the functionally important residues.…”

Section: Resultsmentioning

confidence: 99%

“…58 It has been used in studying protein stability and folding, effects of mutations on protein structure, protein dynamics, allosteric regulations, identification of functionally and biologically important residues, identification of ligand binding sites, and so forth. [59][60][61][62][63] Here, we make use of RIN to study the functionally important residues. In order to make interaction networks, we made use of the lowest energy conformations of Tau_plane and Tau_glyc obtained from the FEL analysis.…”

Section: Rin Analysismentioning

confidence: 99%

N‐glycosylation induced changes in tau protein dynamics reveal its role in tau misfolding and aggregation: A microsecond long molecular dynamics study

et al. 2022

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Various posttranslational modifications like hyperphosphorylation, O-GlcNAcylation, and acetylation have been attributed to induce the abnormal folding in tau protein.Recent in vitro studies revealed the possible involvement of N-glycosylation of tau protein in the abnormal folding and tau aggregation. Hence, in this study, we performed a microsecond long all atom molecular dynamics simulation to gain insights into the effects of N-glycosylation on Asn-359 residue which forms part of the microtubule binding region. Trajectory analysis of the stimulations coupled with essential dynamics and free energy landscape analysis suggested that tau, in its Nglycosylated form tends to exist in a largely folded conformation having high beta sheet propensity as compared to unmodified tau which exists in a large extended form with very less beta sheet propensity. Residue interaction network analysis of the lowest energy conformations further revealed that Phe378 and Lys353 are the functionally important residues in the peptide which helped in initiating the folding process and Phe378, Lys347, and Lys370 helped to maintain the stability of the protein in the folded state.

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

Cited by 9 publications

References 65 publications

Computational analyses reveal fundamental properties of the AT structure related to thrombosis

Computational analyses reveal fundamental properties of the AT structure related to thrombosis

A Machine Learning Framework Predicts the Clinical Severity of Hemophilia B Caused by Point-Mutations

N‐glycosylation induced changes in tau protein dynamics reveal its role in tau misfolding and aggregation: A microsecond long molecular dynamics study

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