Functional and structural prediction analysis
Five tools have been utilized to identify the functional effect of the CYP4F2*3 (V433M) variant on the CYP4F2 protein (Table 1). PolyPhen-2, FATHMM-MKl, PANTHER-PSEP, CADD, and PhD-SNP tools have identified the CYP4F2*3 (V433M) as a deleterious variant.
Table 1
Pathogenicity evaluation of V433M variant on CYP4F2 protein by using bioinformatics tools.
dbSNP ID | Amino acid change | PolyPhen-2 | FATHMM-MKl | PANTHER-PSEP | CADD | PhD-SNP |
| Prediction | Score | Prediction | Scoree | Predictionn | Score | Prediction | Score | Prediction | Score |
CYP4F2*3 (rs2108622) | V433M | Possibly damaging | 2.657 | AEFBHCI | 0.754 | Probably damaging | 0.74 | Deleterious | 22.3 | Pathogenic | 0.865 |
I-mutant2, MUpro, DUET, mCSM, and SDM tools predict protein stability changes upon the CYP4F2*3 (V433M) variant based on the DDG value (change in Gibbs free energy). The DDG value is a metric of calculation of how a single nucleotide variant can impact protein stability. A DDG score of less than zero shows lower stability. From the results illustrated in Table 2, the CYP4F2*3 (V433M) variant showed reduced protein stability. Destabilization of a protein structure can change its biological function and disrupt the signal cascades and the normal pathways of the protein [50].
Table 2
Stability prediction of V433M variant on CYP4F2 protein by using five prediction tools.
dbSNP ID | Amino acid change | I-mutant2 | MUpro | DUET | mCSM | SDM |
| Stability | DDG (kcal/mol) | Stability | DDG (kcal/mol) | Stability | DDG (kcal/mol) | Prediction | Score | Prediction | Score |
CYP4F2*3 (rs2108622) | V433M | Decrease | -2.18 | Decrease | -1.129 | Decrease | -0.74 | Decrease | -22.3 | Decrease | -0.865 |
Project HOPE server investigated the effect of the V433M variant on physio-chemical characteristics, intermolecular interaction, and functional and structural properties. It was predicted that the mutant amino acid (methionine) is bigger than the wild-type amino acid (valine) and possibly will not fit into the protein structure, causing structural alterations. Furthermore, the wild-type amino acid is positioned in a region essential for interacting with other molecules, which is crucial in the protein's activity. The mutation might alter this interaction and disturb the signal cascade from the binding domain to the activity domain.
Structural Modeling Validation And Quality Estimation
Due to the lack of tertiary structure of the CYP4F2, homology modeling was applied by the I-TASSER webserver (Fig. 1A). The quality of the predicted structure was analyzed by the different webservers (Table 3). Checking the quality of a model by Ramachandran plot with Procheck webserver illustrated that more than 80% of protein structures were located in the core and allowed regions which means the high physicochemical quality of protein structure. The Verify3D value of more than 80% showed high compatibility between the primary and tertiary structure of CYP4F2. The ERRAT rate of 91.01 is interpreted good overall quality of protein structure. The Z-score − 8.66 was located in regions of proteins that were identified experimentally that figured out the high quality of the predicted model of CYP4F2 (Fig. 1B). The position of V433M mutation on CYP4F2 structure was shown in Fig. 1C.
Table 3
Physicochemical quality assessment of CYP4F2 protein structure.
Model | Procheck | Verify3D | ERRAT | ProsA Z-score |
| Core | Allowed | Generally allowed | Disallowed |
CYP4F2 | 76.9% | 18.1% | 2.6% | 2.4% | 87.12% | 91.01 | -8.66 |
Md Simulation Findings
MD simulations were conducted to analyze the deviation of native and CYP4F2*3 (V433M) variant proteins in physiological environments over time (Fig. 2).
The RMSD deviations produced during MD simulation were determined to estimate the stability of the protein [51]. As presented in the RMSD plot (Fig. 2A), the native protein attained a relatively stable conformation after 10 ns. In comparison, the V433M variant was stable after about 40 ns of simulations, suggesting that the V433M variant had experienced more significant structural rearrangement before reaching a stable structure. In addition, the RMSD average values verified that the mutant structure had a bit higher RMSD value (0.617 nm) compared to the native (0.586 nm), which means that the mutant form caused instability in the protein structure of CYP4F2 (Table 4).
Table 4
The conformational dynamics of native CYP4F2 protein and V433M variant through RMSD, Rg, SASA, and RMSF analysis. In each parameter, the average mean value is represented by the standard deviation.
dbSNP ID | RMSD (nm) | Rg (nm) | SASA (nm2) | RMSF (nm) |
Native | 0.586 ± 0.068 | 2.459 ± 0.016 | 249.571 ± 4.640 | 0.077 ± 0.028 |
V433M | 0.617 ± 0.099 | 2.493 ± 0.021 | 264.501 ± 4.626 | 0.084 ± 0.032 |
Rg is an essential parameter for evaluating the dynamic adaptability of proteins and other biopolymers [52]. The Rg plot showed that the V433M mutant fluctuated more than the native form (Fig. 2B). Also, the average Rg value analysis presented that the V433M mutation had a higher average Rg value (2.493 nm) compared to the native protein (2.459 nm) over the simulation time. This result indicates that the V433M mutation is less compact and more flexible than native CYP4F2. This data is compatible with the structural alignment of native and mutate forms after molecular dynamics simulation, representing that mutate form had a more open structure form than the native (Fig. 3).
SASA denotes the portion of the protein surface accessible to the water solvent [53]. As shown in Fig. 2C, SASA analysis revealed that the V433M mutation had a higher average SASA value (264.501 nm) than the native CYP4F2 (249.571 nm), suggesting the structural rearrangements in the V433M mutation resulted in increased protein expansion.
The RMSF based on residue displacement explains thermal stability, local flexibility, and heterogeneity of macromolecules over the MD simulations time [54]. The RMSF plot indicated that the V433M variant exhibited a higher fluctuation region in the residues 263–285 of the G helix, followed by increased flexibility in the residues 239–241 of the Fˊ helix when compared to the native CYP4F2 structure (Fig. 4). Also, the result of average RMSF value suggested that V433M mutation alters structural flexibility (Table 4). These fluctuation changes were further studied by DSSP and PCA analysis.
The changes in the secondary structure give more insight into understanding a protein's folding mechanism and conformational behavior. It is identified from the DSSP plot (Fig. 5) that the native protein (Fig. 5A) and V433M variant (Fig. 5B) have almost the same secondary structure arrangement. Data illustrated that the native CYP4F2 contains an overall 60% secondary structure including, β-bridges, β-sheets, α-helices, and turns (Table 5). However, the V433M variant showed a slight decrease in the secondary structure profile compared to the native. Significant changes in the secondary structure content of the V433M variant can be seen due to bend and turn formation and loss of A-Helix and 3-Helix without any change in β-sheets and coils.
Table 5
Secondary structure percentage of native CYP4F2 and V433M variant. * Structure = β-sheet + β-bridge + Turn + A-helix
Structure | Structure* | Coil | B-Sheet | B-Bridge | Bend | Turn | A-Helix | 5-Helix | 3-Helix |
Native | 60% | 17% | 8% | 0% | 16% | 15% | 37% | 0% | 7% |
V433M | 59% | 17% | 8% | 0% | 18% | 16% | 35% | 0% | 6% |
PCA uses covariance matrices of the Cα atoms to calculate significant motions of atom pairs associated with vital biological functions. The first two principal components (named PC1 and PC2) of the native and V433M variant proteins were generated by projecting the trajectories on the respective eigenvectors. As seen in Fig. 6, the V433M variant covered the higher subspace spanned along the two eigenvectors (PC1: -10.29 nm to + 4.18 nm and PC2: − 6.42 nm to + 3.90 nm) compared to the native (PC1: -9.75 nm to + 5.06 nm, and PC2: -6.4 to + 2.67 nm). It was also noticed that the trace of the diagonalized covariance matrix of the native form and V433M variant was calculated to be 19.95 nm and 30.73 nm, respectively, confirming an increase in the overall flexibility of the V433M variant, which agreed with the RMSD, Rg, and RMSF values, as well as SASA and DSSP analysis.
Molecular Docking
The enzyme activity of the CYP4F2 protein depends on its interaction with VK1. For this reason, molecular docking by the HADDOCK webserver was performed to figure out the effect of the V433M variant on the interaction of CYP4F2 protein with VK1 (Fig. 7). The binding site of VK1 on CYP4F2 protein was characterized according to a previous work of Li et al., that predicted binding site of VK1 in this protein. Based on this research, amino acids Trp59, Trp61, Met92 Phe124, His236, Phe327, Glu328, Val397, and Leu504 are responsible for interacting with VK1 [55]. The docking result (Table 6) showed that although mutate form could still interact with VK1 while with a lower binding affinity (-8.5 kcal/mol) than the native form (-10.1 kcal/mol), which caused less activity of the mutating state compared to the native.
Table 6
the docking result of CYP4F2 in both native and mutant form by HADDOCK webserver. Amino acids in bold are amino acids of CYP4F2 which are identified as important in interaction with VK1.
Complex structure | Amino acids in interaction with Vitamin K | ∆G (Kcal/mol) |
Native | Val397, Phe327, Glu328, Leu128, Leu504, Ser399, Tyr125, His236, Phe127, Phe124, Ile398 | -10.1 |
V433M | His236, Val397, Pro396, Ser323, Met66, Leu504, Pro502, Phe60, His327, Val67, Trp59 | -8.5 |