Molecular dynamics of select missense mutations of Apolipoprotein E and their implications in Hyperlipoproteinemia type III

Abstract

Apolipoprotein E (Apo E) is involved in lipid metabolism and plays a crucial role in maintaining the balance of lipoprotein interactions within the body. Mutations in the Apo E protein have been associated with Hyperlipoproteinemia type III, which is characterized by abnormal lipid accumulation in the body. This work explores the structural and functional consequences of seven missense mutations (R154C, R154S, R160C, R163C, R163H, K164E, and K164Q) of Apo E protein associated with Hyperlipoproteinemia type III. Through computational methods such as homology modelling, pathogenicity prediction, Molecular docking and Molecular dynamics, we have investigated the impact of single-point mutations on protein structure, stability, and dynamics. Molecular dynamics simulation studies of wild type Apo E and modelled mutants provided insights into the conformational changes and flexibility of Apo E mutants, giving insights into mechanistic aspect of the influence of mutations on the receptor binding domain and protein structure. The results demonstrate that most of the studied mutations disrupt critical stabilizing interactions and alter domain flexibility thus destabilizing the protein structure and function affecting its interaction with Low-Density Lipoprotein receptor 1 (LDLR1). These molecular insights into how the mutations affect Apo E's conformation and its interaction with the LDL receptor 1 (LDLR1) will help to contribute to a deeper understanding of the pathogenesis of Hyperlipoproteinemia type III.

Highlights

• •Investigating Role of select missense mutations in Apolipoprotein E (Apo E) which leads to Hyperlipoproteinemia type III.
• •Structural and functional consequences of select missense mutations.
• •Probing protein structure and dynamics of wild type and mutant proteins using molecular dynamics and simulation studies.
• •Insights into mechanistic aspect of the impact of these mutations on the receptor binding domain of the protein.

1. Introduction

Apolipoprotein E (Apo E) is the protein involved in the metabolism of lipids and their clearance from blood and peripheral tissues. There are three distinct isoforms of Apolipoprotein E that occur on the long arm of chromosome 19 and only differ by a change in the single amino acid residue from each other. Apo E, a 317 amino acid long protein is expressed in wide variety of tissues such as liver, brain, kidney etc.[1].The protein has a N terminus region (1–191 residues), and C terminus region (216–299) are joined together by a hinge region (192–215). The N terminus region contains receptor binding domain which help in binding of Apo E with the Low-Density Lipoprotein receptors 1 (LDLR1) and C terminus contains lipid binding domain which help in interaction with the phospholipids to form lipoprotein particles [[1], [2], [3]].The interaction of Apo E with the ligand-binding domain of the LDL receptor is mediated by six to eight key arginine and lysine residues, along with a histidine residue, within the amino acid region 154–168. Arginine 176 plays a role in modulating the conformation of this 154–168 region but is only indirectly involved in receptor binding activity. (note that without the peptide signal, these positions are 136–150 and 158 respectively)[3,4]

Apo E is a major constituent of chylomicrons and very high-density lipoproteins, and some fractions of Apo E are found in high-density lipoproteins. Therefore, it participates in mediating the interaction between lipoprotein and cell surface receptors such as LDL receptors [1,5]. Apo E affects various physiological and metabolic processes such as plasma lipoprotein metabolism, blood coagulation, central nervous system physiology, inflammation, cell proliferation and cell homeostasis of macrophage, glial, and neuronal cells. Apo E is expressed in the liver and helps in the transport of lipids from the liver to other tissues and is recycled back to the liver. It also helps to transfer lipids to nervous system as it can be able to cross the blood brain barrier. [6].Thus, Apo E is a multi-functional protein which displays polymorphic effects[7].

Alleles E2, E3, and E4 are the most common polymorphisms observed between different variants of this gene[5]. In all the populations assessed, Apo E3 is the most common variation (>60 percent). This polymorphism affects lipoprotein metabolism by affecting the binding, uptake, and degradation of chylomicrons, chylomicron remnants, very low-density lipoproteins (VLDL), and high-density lipoproteins. Apo E is the major ligand for two receptors: the LDL receptor (also known as the B/E receptor) present in the liver and other organs, and an Apo E specific receptor found in the liver. The proper metabolism of cholesterol is based on the coordinated interaction of these lipoprotein complexes with their receptors[8].

Hyperlipoproteinemia type III occurs due to defects in the receptor binding domain of Apo E protein. As a result of this Apo E is not able to bind with LDL receptors and this results in cholesterol deposition in the various cells and organs in the body [9]. There are different variants in Apo E, that are reported to be associated with Hyperlipoproteinemia type III [8,[10], [11], [12], [13]].

In this work we have studied selected missense variants which are known to be associated with Hyperlipoproteinemia type III. We have used computational methods along with bioinformatic tools to understand how these single point mutations could impact protein structure/function to gain insight about correlation between genotype and phenotype at the molecular level. Our study demonstrated that these selected variants have significant effect in terms of structure and function.

2. Materials and methods

2.1. Retrieval of sequence of Apo E protein and along with its variants

The sequence of Apo E and its variants was retrieved from UniProt along with its selected variants in FASTA format. Natural variants of Apo E protein were selected from the UniProt under pathology and biotech section for Hyperlipoproteinemia Type III[14]. These mutations are single amino acid substitutions which are further assessed for their pathogenic effect on the protein structure and function.

2.2. Prediction of similarity and conservation of the mutated residues

BLASTp (Basic Local Alignment Search Tool) was performed to discover homologous protein sequence of Apo E3 from mammals. Ten sequences from different mammalian species were selected and multiple sequence alignment was performed using Clustal omega [15].

2.3. Pathogenicity and protein stability prediction of the selected variants

Different web-based servers (PolyPhen-2, Panther PSEP, and SIFT) were used to predict the pathogenic effect of the selected variants. The variants which were predicted to be damaging were selected for further analysis. Protein stability and flexibility of selected variants was predicted using Dynamut server [[16], [17], [18], [19]].

2.4. Prediction of tertiary structure of the selected mutants/variants

Homology modelling was performed using the SWISS model to predict the tertiary structure of different variants[20]. The quality and accuracy of predicted structures was carried out and all predicted structures were found to be accurate and reliable.

2.5. Molecular dynamics and simulations

Molecular dynamics (MD) simulations were performed to assess the stability and conformational changes of the wildtype and mutant protein with a total simulation time of 50 ns.PDB structure was cleaned and prepared using APBS software [21]. Topology and parameter files were prepared for each structure using AmberTools 2023. The ff14SB forcefield was applied for the protein and water.opc model was used for solvation (Izadi et al., 2014). Each system was solvated in a TIP3P cubic box of size 15 Å to ensure adequate solvation and minimize edge effects (Jorgensen et al., 1983). Further 1Na⁺ ion was added to neutralize the charge on wildtype protein and 2 Na⁺ were added to neutralize charge on each mutant protein and 50 Na⁺ and 50 Cl^- were added to maintain 0.15 M standard ion concentration for each system.[22]. (Note that after cleaning the pdb file, modelling the missing residues and creating topology file, mutant positions are 113 (154), 119 (160), 122 (163) and 123 (164)). Structure relaxation was done with initial step involves minimizing the added water and ions while restraining the solute with a force constant of 100 kcal/mol•Å². The system is minimized for 1000 steps using both steepest descent and conjugate gradient algorithms. Next, the system is heated from 100 K to 298 K over 1 ns under constant volume, with restraints still applied to the solute. Once heated, the system undergoes relaxation at constant pressure for 1 ns to adjust the box density, with the same restraints. Afterward, the restraints are gradually reduced in stages: first, lowering to 10 kcal/mol•Å², then performing further relaxations with 1 kcal/mol•Å², and eventually 0.1 kcal/mol•Å² restraints for 1ns each. Lastly, a final relaxation without restraints is conducted for 1 ns at constant pressure. Throughout the process, a time step of 1 fs is maintained, and key settings include the use of the Langevin thermostat, Monte Carlo barostat, and removal of the centre of mass motion every 1000 steps. Then production dynamics was performed for 50 ns and a time step of 2fs is maintained throughout the simulation. Analysis was done using PyMOL[23] and VMD[24].

2.6. Protein-protein docking using cluspro 2.0 server

Protein –Protein docking was carried out using Cluspro 2.0 [25] The 3D structure of Apo E (PDB id: 1NFN) [26]and LDLR (PDB id: 1N7D) [27] was obtained from PDB. The LDL receptor was also docked N-terminal domain crystal structure of Apo E and mutant homology models generated using Swiss Model. The docked complexes were visualized and analysed using PyMol, LigPlot+ was used to tabulate domain-domain interactions [28].

3. Results and discussion

Apo E gene codes for Apolipoprotein E protein which consists of two domains, a N terminal domain and a C terminal domain. Single nucleotide polymorphisms are one of the most frequently occurring changes in DNA. Among them, some of the variations lead to missense mutations which leads to replacement of an amino acid with another at a given position in protein chain. To understand the effect of such substitutions, these changes need to be studied in context of three-dimensional structure of the given protein. We shortlisted missense mutations in the gene for Apo E which were found to be associated with Hyperlipoproteinemia Type III. In order to fully comprehend and understand the effect of these mutations we conducted comprehensive analysis of these mutations on the structural and functional aspects of the Apo E protein.

3.1. Sequence similarity analysis and multiple sequence alignment

Homologues of the protein were searched in mammals with BlastP which led to identification of highly similar sequences in other mammalian species[Fig. 1].

Fig. 1.

BLAST results for query Apo E shows homologues in other organisms.

In order to look into evolutionary aspects of the selected missense mutations, we conducted multiple sequence alignment (MSA) of these homologues. Result of MSA showed that the selected missense mutations are highly conserved among different organisms. This indicate strong selection pressure on these residues which might be due to important functional/structural role of these amino acids. All these missense mutations are located near to receptor binding domain of Apo E.

Multiple sequence alignment shows that the position of the selected variants is highly conserved among different organisms therefore these residues may be critical for the proper functioning of the protein [Fig. 2].

Fig. 2.

Multiple sequence alignment results of Apo E (position marked for mutations).

3.2. Pathogenicity prediction of the selected variants

Pathogenicity of the variants of Apo E protein was predicted as described in methods. Based on prediction scores and consensus among all prediction, all the seven mutations were predicted to be pathogenic in nature[Table 1].

Table 1.

List of selected variants and their Pathogenicity predictions.

Residue	Panther prediction	Sift prediction	Polyphen 2.0 prediction	ΔΔG prediction	ΔΔSVib ENCoM: (mOLECULE FLEXIBILITY)
R154C	0.5 Possibly damaging	0.01 Damaging	1 Probably damaging	−0.755 kcal/mol (Destabilizing)	0.254 kcal mol−1 K−1 (Increase)
R154S	0.5 Possibly damaging	0.04 Damaging	1 Probably damaging	−0.942 kcal/mol (Destabilizing)	0.224 kcal mol−1 K−1 (Increase)
R160C	0.5 Possibly damaging	0.01 Damaging	1 Probably damaging	0.012 kcal/mol (Stabilizing)	−0.027 kcal mol−1 K−1 (Decrease)
R163C	0.5 Possibly damaging	0.00 Damaging	1 Probably damaging	−0.125 kcal/mol (Destabilizing)	0.173 kcal mol−1 K−1 (Increase)
R163H	0.5 Possibly damaging	0.03 Damaging	0.697 Probably damaging	−0.386 kcal/mol (Destabilizing)	0.178 kcal mol−1 K−1 (Increase)
K164E	0.5 Possibly damaging	0.06 Tolerated	1 Probably damaging	0.159 kcal/mol (Stabilizing)	0.103 kcal mol−1 K−1 (Increase)
K164Q	0.5 Possibly damaging	0.09 Tolerated	1 Probably damaging	−0.224 kcal/mol (Destabilizing)	0.080 kcal mol−1 K−1 (Increase)

3.3. Tertiary structure predictions of variants

Homology models of the mutants were generated using Swiss Model. The template used for modelling was 1NFN(PDB id). It has a resolution of 1.80 Å and represents N -terminal domain of Apo E[26].

3.3.1. Validation of predicted models

The homology models of the mutants which were generated using the Swiss Model were evaluated by the QMEAN and GMQE score of the models along with structural quality assessment. Table 2 lists the quality of these homology models(Fig. S7).

Table 2.

Structural quality scores of homology models of mutant protein structures.

SR.No.	Mutation	Sequence identity	QMEAN-DisCO	GMQE	Ramachandran Favored
1.	R154C	97.66 %	0.74	0.46	99.28 %
2.	R154S	97.66 %	0.74	0.47	99.28 %
3.	R160C	97.66 %	0.75	0.47	99.28 %
4.	R163H	97.66 %	0.74	0.46	99.28 %
5.	R163C	97.66 %	0.73	0.46	99.28 %
6.	K164E	97.66 %	0.72	0.46	99.28 %
7.	K164Q	97.66 %	0.74	0.47	99.28 %

PyMOL was used for visualization and analysis [23]. Crystal structure of Wild type Apo E protein with marked area as the residues which undergo missense mutations (Fig. 3, Fig. 4).

Fig. 3.

Crystal structure of N-terminal Domain of Apo E protein.

Fig. 4.

Superimposed structure of mutant models with wild type (green)protein crystal structure.

3.4. Molecular dynamics simulation

We carried out all atoms molecular dynamics simulations to assess the stability and conformational changes of the wildtype and mutant proteins with a total simulation time of 50 ns. The following analysis was conducted.

3.4.1. RMSD analysis

The RMSD analysis of the backbone atoms of the various mutants (R154C, R154S, R160C, R163C, R163H, K164Q, and K164E) provides a comprehensive understanding of the impact of each mutation on the protein's structural stability[Fig. 5]. The wild type serves as a reference, consistently demonstrating low RMSD values ranging from 1.2 to 1.6 Å, indicative of stable structural behaviour throughout the entire simulation with no significant deviations. Conversely, the R160C shows the most pronounced disruption, with RMSD values sometimes exceeding 4 Å, indicative of major conformational changes and a markedly unstable structure. The R154C mutation also exhibits considerable destabilization, with peak RMSD values around 3.5 Å, signifying substantial structural disorder, albeit slightly less severe than R160C. In contrast, the R154S mutation results in moderate instability, with RMSD fluctuations reaching up to 3 Å, indicative of noticeable yet less severe deviations compared to R154C, thereby indicating that serine substitution is less disruptive than cysteine at position 154.

Fig. 5.

RMSD (Å) of backbone of wild type and mutant proteins.

Mutations such as R163C and R163H induce moderate structural perturbations, with RMSD values spanning from 1.5 to 2.5 Å. This indicates that although these mutations result in deviations from the wildtype, they do not destabilize the protein to the same extent as mutations R160C or R154C. The impact of R163C and R163H appears to be subtler, affecting the protein's flexibility without inducing large-scale conformational shifts. Mutation K164Q demonstrates more significant instability, with RMSD values reaching up to 3.5 Å, positioning it closer to R154C in terms of its disruptive effects. In contrast, K164E manifests a more complex RMSD profile. During the early phase (0–10 ns), RMSD fluctuates between 1.2 and 2.4 Å, indicating moderate instability, a pattern that persists through the middle phase (10–35 ns) with fluctuations ranging from 1.5 to 2.4 Å. In the final phase (35–50 ns), RMSD values stabilize somewhat to between 1.4 and 2.3 Å. This suggests that while K164E introduces moderate structural perturbations, it does not lead to severe destabilization, allowing the protein to maintain a degree of structural integrity over time. Further, average ± Standard deviation and p-values of RMSD analysis revealed that all mutants displayed higher structural fluctuations compared to the wild type (WT, 1.44 ± 0.18 Å). Notably, R160C (2.52 ± 0.57 Å, p < 0.0001) and R154S (2.09 ± 0.31 Å, p < 0.0001) exhibited the greatest deviations, suggesting significant destabilization. Other mutants, including R154C (1.88 ± 0.40 Å), R163C (1.94 ± 0.24 Å), and K164Q (1.97 ± 0.30 Å), also showed statistically significant increases in RMSD (all p < 0.0001). Interestingly, R163H showed only a moderate increase (1.53 ± 0.22 Å) compared to WT (Table S1 and Fig. S2) These statistically significant differences (p < 0.0001 for all mutants) indicate mutation-induced alterations in structural stability of Apo E. Collectively, these findings illustrate a spectrum of effects, from severe destabilization with R160C and R154C to moderate structural changes with R154S and K164Q, and milder disturbances with R163C and R163H. Overall, the comparison emphasizes that the nature and position of the mutation are crucial determinants in the extent to which they affect the protein's structural stability[Fig. 6 and S1].

Fig. 6.

RMSF (Å) plot of residues of wildtype and mutant protein.

3.4.2. RMSF analysis

The analysis of RMSF data for both wild-type and mutant proteins indicates notable alterations in flexibility, especially in the loop regions [Fig. 6]. Peaks in the RMSF plot are detected around residues 59–62, 99–104 and 144–148 which correspond to loop regions that possess inherent flexibility (note that without the peptide signal, and starting missing residues mutant positions are 113, 119, 122 and 123, respectively in RMSF graph). Nevertheless, mutants R160C and K164E, result in an increase of this flexibility. The R160C mutation exhibits the most pronounced fluctuation within the 59–62 loop, denoting significant destabilization. This alteration could have impact upon structural integrity, as these loop regions help in connecting and maintaining the alpha helical structure of N terminal domain of Apo E which is crucial for its receptor binding activity. Likewise, the K164E mutation augments flexibility in the 144–148 loop.

Other mutations, such as R154C, R154S, R163C, and R163H, exhibit moderate increases in loop flexibility but have less pronounced effects relative to R160C and K164E. Conversely, the wildtype protein displays lower RMSF values [Fig. 7 and S3], signifying a more stable and rigid structure, particularly within the loop regions. Average ± Standard deviation and p-values of Residue-level flexibility (RMSF) analysis showed that most mutants had increased fluctuations compared to wild-type Apo E (0.83 ± 0.29 Å). The most pronounced increases were observed in R160C (1.17 ± 0.71 Å, p < 0.0001) and R154S (1.13 ± 0.53 Å, p < 0.0001), suggesting enhanced flexibility and potential loss of structural rigidity. Although R163H showed only a mild increase (0.88 ± 0.31 Å) compared to WT, the difference was not statistically significant (p = 0.1211), implying a less disruptive effect. The other mutants (R154C, R163C, K164Q, and K164E) also displayed significantly higher flexibility, supporting the hypothesis that these mutations destabilize local structural regions critical for function (Table S2 and Fig. S4). This implies that the mutations induce significant destabilization in regions that are vital for preserving the protein's structural and functional integrity. Increased flexibility in these loop regions, especially in areas, near to receptor binding domain of protein can disrupt interactions essential for protein function, such as molecular binding or the regulation of conformational changes as seen in Fig. 7, Fig. 8. In summary, mutations like R160C and K164E are likely to exert a destabilizing impact on the protein, with potentially detrimental implications for its functional and structural stability.

Fig. 7.

Superimposed structures of Wildtype and mutant.

Fig. 8.

Solvent accessible surface area (Ų) of wildtype and mutant proteins.

3.4.3. Solvent accessible surface area

In order to explore the effect of these mutations on the overall protein structure, we conducted analysis of solvent accessible surface area of wild type and mutant protein structures using VMD plugin [29]. Fig. 8 and S3 display the solvent-accessible surface area (SASA) over a 50-ns span of molecular dynamics simulations for both the wild-type protein and several mutants, including R154C, R154S, R160C, R163C, R163H, K164Q, and K164E. SASA is crucial for assessing how much of the protein surface is open to the solvent, providing insight into the protein's folding and stability. Both the wild-type and R160C mutant show similar fluctuations in SASA over time, with R160C consistently similar SASA values as compared to the wild-type, particularly between 20 and 40 ns, indicating least change in structure. Surprisingly, other mutants show significant decrease in SASA during the time course of dynamics in comparison to the wildtype protein and R160C mutant. The wild-type SASA ranges between ∼8000 Å² to 13,000 Å², illustrating greater conformational flexibility and dynamic behaviour. Average ± SD and p-values of Solvent accessible surface area (SASA) analysis revealed a marked reduction in solvent exposure in most Apo E mutants relative to wild type (10709.51 ± 1166.91 Å²). Notably, R163H (8874.73 ± 159.85 Å²) and K164E (8754.89 ± 168.69 Å²) showed significantly reduced SASA values (p < 0.0001), indicating more compact or collapsed conformations. An exception was R160C, which exhibited an increase (11045.20 ± 1048.59 Å²), suggesting potential structural loosening. These statistically significant differences suggest that mutations can alter solvent exposure patterns, possibly affecting binding or interaction interfaces(Table S3 and Fig. S5.). The overall decrease in SASA in R154C, R154S, R163C, R163H, K164Q, and K164E mutants suggests that these mutations, involving the replacement of large, charged residues like arginine or lysine with smaller, more neutral, or less polar residues like cysteine or glutamine, and may create more compact or rigid structures, reducing solvent exposure. Fig. 9 represents the surface representation of wildtype and mutant proteins at 50 ns; we can clearly see that there is change in the surface of wildtype and mutant proteins which may arise due to these mutations. Furthermore, all these mutations are near the region of receptor binding domain and thus might reduce the interaction energy with receptor.

Fig. 9.

Surface representation of Wildtype and mutant protein at 50 ns.

The N terminal domain of Apo E contains five alpha helices and four helices among five are arranged in an antiparallel four helix bundle [30]. Previous studies have suggested that the Arginine (154, 160 and 163) and lysine (164) (without signal sequence these positions are 136, 142, 145 and 146) residues in N terminal domain of Apo E play important role in maintaining the interdomain H bond and salt bridges which plays crucial role to stabilize the C terminal domain in Lipid unbound form of Apo E as a result major LDL binding region in the N terminal Domain of Apo E remains shielded and unavailable for receptor binding [[30], [31]]. Further in one of the studies it has been shown that when lipid molecules bind to the Apo E, Apo E undergoes conformational changes in the receptor binding domain (130–149) of the protein. As a result of this induced conformational change, the receptor binding domain gets exposed, and the helices reorient to form high affinity receptor binding sites for LDLR. It has been shown earlier that modification of these Arginine and lysine residues results in the loss of receptor binding ability of Apo E [[32], [33], [34]]. In a recent study it has been proposed that patients with rare Apo E variants R154S and R163C play vital role in developing Hyperlipoproteinemia Type III [35].

Our work clearly demonstrates that mutation in the Arginine (154, 160 and 163) and Lysine (164) residues do impact the overall protein structure and its stability. Mutation-induced changes in local flexibility, interactions, or binding properties shall overall contribute to manifestation of pathogenicity of these mutations.

In order to investigate to what extent these mutations will hamper binding of Apo E with its receptor, LDLR, we conducted protein-protein docking studies with crystal structure of LDLR. We also conducted docking of homology models of mutants with crystal structure of the receptor. Visualization and analysis of the docked complexes revealed that all the mutations studied in this study are part of interaction interface between Apo E and LDLR (Fig. S6). Upon interaction interface surface analysis revealed these mutations shall lead to destabilization of complex formation between Apo E and LDLR (Table 3) with increase in free energy of the complexes. Therefore, mutations in Apo E result in decreased binding affinity with LDLR hence can be pathogenic, potentially altering protein function and contributing to disease pathology.

Table 3.

List of interactions between Apo E and LDLR1.

Interactions with LDLR	H-bonds Ligand (Apo E) – Receptor (LDLR)	Hydrophobic interactions	Energy
1. Wildtype	Gln174 – Cys227	Ligand: Val179, Asp171, Leu167, Arg 168, Arg 165 and Asp169.	−989
	Ala178 – Ala213	Receptor: Ala211, Val212, Cys210, Lys241, Cys240, Arg194, Ser191and Phe179.
	Lys175 - Asp224 & Asn226
	Arg176 - Cys195 & Glu579
	Lys164 - Tyr238 & Asp239
	Arg163 - Asp239 & Glu237
	Asp172 - Ser192
	Total = 11
2. R154C	Asp172 – Ser192	Ligand: Leu167, Val179, Arg165, Arg 168, Asp169 and Arg176	−958
	Asp171 – Lys 241	Receptor: Cys240, Cys210, Ala211, Val212, Phe179, Ser191 and Arg194
	Lys161 – Glu 579
	Lys 175 – Asn226 and Asp224
	Gln174 – Cys227
	Ala178 – Ala213
	Lys164 - Tyr238 & Asp239
	Arg163 – Glu237 & Asp 239
	Total = 11
3. R154S	Asp172 – Ser192	Ligand: Leu167, Asp171, Val179, Arg 168, Arg 176 Asp 169 and Arg 165	−964
	Lys 175 – Asn226	Receptor: Cys240, Lys241, Val212, Cys210, Ala211, Ser191, Arg194, Cys195 and Phe179Total = 9
	Ala178 – Ala213
	Gln174 – Cys227
	Lys164 - Tyr238 & Asp239
	Arg163 – Glu237 & Asp 239
	Arg160 – Glu237
	Total = 9
4. R160C	Arg168 – Asp239	Ligand: Asp171, Leu177, Tyr180, Cys160, Ser157, Ala170, Gln174, Leu167, Leu155 and Val179.	−944
	Arg165 – Asp239	Receptor: Ser191, Lys241, Ile228, Arg232, Gln540, Leu143, Val212, His229, Phe179, Ser192 and Leu561.
	Ala178 – Trp144
	Lys161 – Gly225, Ala213 and Cys227
	His158 – Glu219
	Lys164 – Asn226, Asp224
	Leu151 – Arg216
	Arg154 – Arg216
	Lys175 – Glu581
	Total = 12
5. R163C	Ala178 – Asn667	Ligand: Leu177, Val179	−980
	Tyr180 – Gln 665	Receptor: Ile666, Pro668 and His507.
	Arg168 – Asp335
	Arg165 – Glu351
	Lys161 – Glu332
	Total = 5
6. R163H	Lys175- Asp224, Asn226	Ligand: Val179, Arg176 Leu167, Arg165 and Asp169.	−970
	Asp171- Lys241	Receptor: Ala213, Val212, Cys240, His229, Phe179, Ser192, Ser191 and Trp193.
	Lys161 – Glu579
	Lys164 – Asp239, Tyr238, Glu237
	Arg160 – Glu237
	Gln 174 – Cys227
	Arg168 – Asp196, Glu581
	Total = 11
7. K164Q	Lys175 – Asp224, Asn226	Ligand: Arg165, Asp169, Leu167, Arg176 and Val179.	−955
	Gln174 – Arg232, Cys227	Receptor: Phe179, Ser192. Ser191, Cys240, His229, Val212 and Ala213
	Asp171 – Lys241
	Lys161 – Glu579
	Arg168 – Asp196, Glu581
	Arg163 – Asp239, Tyr238, Glu237
	Arg160 – Glu237
	Total = 12
8. K164E	Tyr180 – Gln665	Ligand: Leu177, Val179	−983
	Ala178 – Asn667	Receptor: Ile666, Pro668 and His507
	Arg168 – Asp335
	Arg165 – Glu332
	Total = 4

Relative energies of the docked structures were calculated as follows: E = 0.40Erep+−0.40Eatt+600Eelec+1.00EDARS.

To enhance the clinical relevance of the studied Apo E mutations, future work should incorporate population-level data from resources such as gnomAD, etc. to assess allele frequencies across diverse populations, enabling the distinction between rare pathogenic variants and benign polymorphisms. Additionally, linking these mutations to reported clinical phenotypes using databases like ClinVar or the Human Gene Mutation Database (HGMD) would strengthen the interpretation of their disease relevance and improve the translational value of the findings.

While our in-silico approach, including molecular dynamics simulations, provides detailed atomistic insights into the structural and functional consequences of Apo E mutations, the lack of experimental validation remains a limitation. Future studies should involve site-directed mutagenesis and biochemical assays to evaluate the stability, folding, and receptor-binding capabilities of mutant proteins. Techniques such as Surface Plasmon Resonance (SPR) and Isothermal Titration Calorimetry (ITC) could be used to assess binding affinities with the LDL receptor (LDLR), while in vitro LDLR-binding or lipoprotein uptake assays would help to the confirm functional impacts of these mutations. Together, these integrative approaches would strengthen the translational significance of the study and support the broader application of this computational framework in personalized medicine and genetic screening.

4. Conclusion

Apolipoprotein E (Apo E) is crucial in lipid and triglyceride metabolism and plays a role in the receptor-mediated uptake of lipoprotein particles. This study, provides molecular insights of seven missense mutations of Apo E associated with Hyperlipoproteinemia type III, revealing their impact on structural stability, flexibility and how loss of critical interactions near the receptor binding domain of Apo E affects its binding with LDLR1. Molecular dynamics simulation of wildtype and mutant protein highlights the importance of Residues 154, 160, 163 and 164 in maintain the structural integrity of Apo E protein. These results enhance our understanding of Apo E's structural dynamics and its potential links to Hyperlipoproteinemia type III at a molecular mechanistic level. By integrating structural modelling with population and clinical data, this approach can support the prioritization of potentially pathogenic variants and underscores the utility of such pipelines in personalized medicine and structure-based drug design. Future experimental studies—including site-directed mutagenesis, binding affinity assays, and in vitro validation—will be essential to validate these computational insights and translate them into translational medical treatments.

CRediT authorship contribution statement

Sumit Thakur: Writing – original draft, Visualization, Formal analysis, Data curation. Balvinder Singh: Software, Resources. Ranvir Singh: Writing – review & editing, Writing – original draft, Supervision, Project administration, Methodology, Data curation, Conceptualization.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

The following is the Supplementary data to this article.