The 3.2 Å structure of a bioengineered variant of blood coagulation factor VIII indicates two conformations of the C2 domain

Smith, Ian W. M.; d’Aquino, Anne E.; Coyle, Christopher W.; Fedanov, Andrew; Parker, Ernest T.; Denning, Gabriela; Spencer, H. Trent; Lollar, Pete; Doering, Christopher B.; Spiegel, P. Clint

doi:10.1111/jth.14621

Cited by 17 publications

(37 citation statements)

References 79 publications

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“…Therefore, we collected several properties of all amino acids of the FVIII structure 13 (Protein Data Bank (PDB) accession 2R7E), including the surface exposure area, hydrophobicity and torsion angles of the amino acids, and searched for clinical reports that described HA cases caused by mutations at each of those residues. In addition, we verified that the properties of the structure we used in this study strongly correlated to the properties of another structure published recently 14 (PDB accession 6MF2—Supplementary Fig. 1 ), thus, we did not use the 6MF2 structure for the analyses.…”

Section: Resultssupporting

confidence: 69%

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

et al. 2021

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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.

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Section: Resultssupporting

confidence: 69%

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

et al. 2021

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“…Previous studies determined the structure of FVIII (Refs. 3 – 5 ), performed massive alanine mutagenesis experiments 6 , 7 , and made point mutations that increased the half-life of FVIII in circulation 5 . However, determining which residue substitutions are beneficial or detrimental to the FVIII activity remains a laborious and costly trial-and-error approach.…”

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

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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.

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“…Data collection and processing were performed with Adxv, XDS and CCP4 ( 29 ). Phasing of the ET3i:G99 crystals was determined with PHASER-MR using a fragment-based molecular replacement approach with the previously determined 3.2 Å structure of ET3i (PDB ID: 6MF0) and the 2.47 Å structure of human factor VIII C2 domain in complex with murine inhibitory antibodies 3E6 and G99 (PDB ID: 4KI5) ( 20 , 27 , 30 ). Model building and refinement were performed with WinCoot and PHENIX, respectively ( 31 ).…”

Section: Methodsmentioning

confidence: 99%

“…where B is the raw atomic B-factor from the crystal dataset, B average is an average of the atomic B-factors of the ET3i molecule in the crystal asymmetric unit, and Resolution is the reported atomic resolution for the respective structure. Model A of the free ET3i crystal structure, which has two ET3i molecules in the ASU (27), was used to compare with the antibodybound structures. Atomic B' values encompassing the peptide backbone and residues were averaged at known C1 and C2 domain epitopes (Figure 3C) from three ET3i crystal structures were averaged and tabulated for comparison (Table 1).…”

Section: Analysis Of B-factor Values From Multiple Et3i Crystal Structuresmentioning

confidence: 99%

“…The crystal structure of the isolated C2 domain bound to G99 identified a conformational epitope composed of multiple loops and revealed K2227 forms multiple electrostatic contacts with the G99 light chain ( 20 ). Here, we present the crystal structure of ET3i ( 25 – 27 ), a bioengineered human/porcine chimera of B domain-deleted fVIII, bound to the G99 antigen binding fragment (F AB ). Our structure represents the first crystal structure of a fVIII replacement therapeutic bound to an anti-C2 inhibitor, providing insight into how non-classical inhibitors alter the C2 domain conformation of mature fVIII and allosterically influence the thermal motion of nearby epitopes.…”

Section: Introductionmentioning

confidence: 99%

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Structure of Blood Coagulation Factor VIII in Complex With an Anti-C2 Domain Non-Classical, Pathogenic Antibody Inhibitor

et al. 2021

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Factor VIII (fVIII) is a procoagulant protein that binds to activated factor IX (fIXa) on platelet surfaces to form the intrinsic tenase complex. Due to the high immunogenicity of fVIII, generation of antibody inhibitors is a common occurrence in patients during hemophilia A treatment and spontaneously occurs in acquired hemophilia A patients. Non-classical antibody inhibitors, which block fVIII activation by thrombin and formation of the tenase complex, are the most common anti-C2 domain pathogenic inhibitors in hemophilia A murine models and have been identified in patient plasmas. In this study, we report on the X-ray crystal structure of a B domain-deleted bioengineered fVIII bound to the non-classical antibody inhibitor, G99. While binding to G99 does not disrupt the overall domain architecture of fVIII, the C2 domain undergoes an ~8 Å translocation that is concomitant with breaking multiple domain-domain interactions. Analysis of normalized B-factor values revealed several solvent-exposed loops in the C1 and C2 domains which experience a decrease in thermal motion in the presence of inhibitory antibodies. These results enhance our understanding on the structural nature of binding non-classical inhibitors and provide a structural dynamics-based rationale for cooperativity between anti-C1 and anti-C2 domain inhibitors.

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The 3.2 Å structure of a bioengineered variant of blood coagulation factor VIII indicates two conformations of the C2 domain

Cited by 17 publications

References 79 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

Structure of Blood Coagulation Factor VIII in Complex With an Anti-C2 Domain Non-Classical, Pathogenic Antibody Inhibitor

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