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. 2025 Jul 30;20(7):e0329126. doi: 10.1371/journal.pone.0329126

Computational prediction of the pathogenic variants of arachidonate 5-lipoxygenase activating protein using Molecular Dynamics simulation

Mohamed E Elnageeb 1, Imadeldin Elfaki 2,*, Gad Allah Modawe 3, Abdelrahman Osman Elfaki 4, Othman R Alzahrani 5, Hytham A Abuagla 1, Hayam A Alwabsi 2, Adel I Alalawy 2, Mohammad Rehan Ajmal 2, Elsiddig Idriss Mohamed 6, Hussein Eledum 6, Syed Khalid Mustafa 7, Elham M Alhathli 8
Editor: Khalid Raza9
PMCID: PMC12310011  PMID: 40737279

Abstract

The arachidonate 5-lipoxygenase activating protein (ALOX5AP) regulates leukotrienes (LTs) synthesis. LTs are involved in inflammation which is implicated in cardiovascular diseases (CVDs) and stroke. Variations in ALOX5AP gene are associated with CVDs, stroke and others because of their possible effects on ALOX5AP stability and function. In this study we investigated with molecular dynamics (MD) simulation the structural impacts of L12F, A56V, G75R, and G87R variants on ALOX5AP. We employed an array of bioinformatics techniques, including SIFT, PolyPhen-2, PANTHER, SNPs&GO, PhD-SNP, i-Mutant, MuPro, MutPred, ConSurf, and GROMACS. Results showed that the L12F variant increased structural compactness, as indicated by diminished solvent accessibility, a reduced radius of gyration, and a decrease in hydrogen bonding capacity. The A56V variant destabilized the ALOX5AP, demonstrating elevated root mean square deviation (RMSD), augmented solvent-accessible surface area, and diminished ALOX5AP compactness. The G75R and G87R variants exhibited mild effects on ALOX5AP wildtype. However, simulation trajectory snapshots results indicated G75R and G87R variants induce instability leading to structural perturbations of ALOX5AP probably due to the charge of arginine introduced by the G75R and G87R mutation. The G75R and G87R variants potentially influence ALOX5AP dynamics, stability, and function. These results require further verification in future case-control and protein functional studies.

1. Introduction

Cardiovascular diseases (CVDs) are important cause of premature death and morbidity all over the world with increasing rate of incidence [1]. Atherosclerosis is the underlying cause of pathogenesis and progression of CVDs including coronary artery disease (CAD) or ischemic heart disease, cerebrovascular disease or stroke, venous thromboembolism and, peripheral vascular disease [1]. Inflammation is one of the important pathways in the formation of atherosclerosis resulting in the atherosclerotic plaque and the subsequent pathologies such as CAD and stroke [2,3]. CVDs are developed through the interactions of genetic and environmental risk factors [4]. Environmental risk factors include unhealthy diet, physical inactivity, smoking, male gender, obesity, dyslipidemia, and air pollution [5]. The genetic risk factors were identified through the genome-wide association studies that revealed the linkage of certain loci with diseases such as diabetes mellitus (DM), CVDs, and cancers [6,7].

Arachidonate 5-Lipoxygenase Activating Protein (ALOX5AP) is encoded by ALOX5AP gene, and also known as Human 5-Lipoxygenase Activating Protein (FLAP). ALOX5AP is important for 5-lipoxygenase pathway (5-LO), this pathway is required for leukotrienes biosynthesis [8,9]. The human ALOX5AP gene is found on chromosome 13q12-13 and composed of 5 exons, 4 introns [10]. Leukotrienes are derived from arachidonic acid and function as inflammation mediators [11]. The biosynthesis of leukotrienes starts with the cleavage of arachidonic acid from the membrane phospholipids [12,13]. The 5-Lipoxygenase (5-LO), activated by FLAP, and catalyzes the conversion of arachidonic acid to 5-hydroperoxyeicosatetraenoic acid and then to leukotriene A4 (LTA4) [13]. The LTA4 is either converted to leukotriene B4 (LTB4) by LTA4 hydrolase, or conjugated to glutathione by LTC4 synthase (LTC4S) generating the cysteinyl leukotrienes such as leukotriene C4 (LTC4), leukotriene D4 (LTD4), and leukotriene E4 (LTE4) [13]. Leukotrienes are involved in autoimmune and inflammatory, CVDs, and tumors [14]. It has been reported that the 5-LO pathway is upregulated in cardiovascular diseases and that cysteinyl leukotrienes are implicated in atherosclerosis, CAD and stroke [13]. In addition the ALOX5AP gene variations are associated with CAD risk in patients with familial hypercholesterolemia [15], stroke in Iranian, Chinese [16,17], and premature CAD in European American patients [18]. However, some previous studies indicated no association of certain ALOX5AP gene polymorphisms with stroke in Chinese [19] and myocardial infarction (MI) in European population [20]. Moreover, the ALOX5AP gene polymorphisms were reported to be associated with thyroid cancer [21], myeloid leukemia [22] and Alzheimer’s disease [23]. In this research, we examined the effects of the ALOX5AP gene variations L12F, A56V, G75R, and G87R on ALOX5AP with molecular dynamic simulation [24–27] as ALOX5AP variants may be associated with CVDs, and other diseases.

2. Methods

2.1. Plan of work

The present study employed computational methodologies and various bioinformatics technologies [24,27–30] to examine the effects of non-synonymous single nucleotide polymorphisms (nsSNPs) in the ALOX5AP. Then the nsSNPs with a high-risk profile were chosen for additional examination, involving an evaluation of their conservation, stability, and structural impact using molecular dynamics (MD) simulation (Fig 1).

Fig 1. Schematic representation of the workflow.

Fig 1

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2.2. Data collection

The nucleotide and amino acid sequences of the ALOX5AP, accession numbers NG_011963.2 and NP_001620.2, were obtained from the NCBI ((accessed on 23 May 2024) in FASTA format. The SNP data for the ALOX5AP gene is accessible on the NCBI SNP database at the following URL: http://www.ncbi.nlm.nih.gov/snp/ accessed on 23 May 2024. Additionally, relevant information concerning the ALOX5AP gene and protein was obtained from the PDB ID 2Q7M, the Uniprot database (https://www.uniprot.org/uniprotkb/P20292/entry) accessed on 23 May 2024, and the Online Mendelian Inheritance in Man (OMIM) database, available at http://www.omim.org (accessed on 23 May 2024).

2.3. Prediction of functional impact of nsSNPs

This study does not include any human or animal subjects performed by any coauthors and therefore ethical approval and consent were not required. To identify deleterious nsSNPs in the ALOX5AP gene, a multi-tool computational approach was employed, utilizing predictive algorithms and structural analyses in the following steps. We examined the impact of genetic variations on protein function with numerous online tools and servers, including SIFT [31,32] which assesses the degree of conservation of amino acids and the effects of substitutions, categorizing variants as “tolerated” or “deleterious. In SIFT score, the amino acid substitution is predicted damaging if the score is <= 0.05 [32]. PolyPhen2 [33] predicts the functional consequences based on sequence and structural features, classifying variants as “benign,” “possibly damaging,” or “probably damaging.”, and PANTHER [34] that was used to classify variants based on evolutionary conservation and biological significance, identifying those with potential deleterious effects.

2.4. Structural stability and functional impact assessment

The tools employed for evaluating the correlation between the filtered SNPs and disease were PhD-SNP [35,36] to provide support vector machines and evolutionary information and SNPS&GO [37] to evaluate the functional impact using neural networks. The I-Mutant algorithm receives the amino acid sequence of the ALOX5AP, together with data on the individual mutated residues and their corresponding locations [38]. The MUpro tool was utilized to assess protein stability and changes in mutations [39]. While the MutPred2 web service was used for classifying mutations as either neutral or disease-associated [40], and the assessment of amino acid conservation was performed using the ConSurf web server [41].

2.5. Molecular Dynamics (MD) simulations using GROMACS

The simulation workflow involved multiple steps, including system preparation, energy minimization, equilibration, production simulation, and subsequent post-simulation analysis to evaluate structural and dynamic properties were performed using GROMACS [42]. The initial structures were prepared using CHARMM-GUI, specifically its Solution Builder module, which facilitates system setup with CHARMM36m forcefield. This process ensured accurate representation of the molecular system through solvation, ion addition, and parameterization. To refine the system further, energy minimization was carried out to eliminate steric clashes and stabilize the structure. Equilibration was performed in two phases to enable the system to adapt to the desired simulation conditions while maintaining structural integrity. Beginning with the previously minimized structure, equilibration established a well-stabilized environment for the production run. Following this, production simulations were conducted over a time scale of 100 nanoseconds (ns), encompassing 50 million steps. These simulations leveraged GPU acceleration to enhance computational efficiency, with specific commands such as `-bonded gpu` and `-pme gpu` employed to optimize the handling of bonded and non-bonded interactions. The production phase generated detailed atomistic trajectories, providing insight into the dynamic evolution of the protein structures. Post-simulation analysis was undertaken using GROMACS [42] to examine the structural stability and flexibility of ALOX5AP key metrics such as the root-mean-square deviation (RMSD) [29,43], which assesses the ALOX5AP overall structural stability, and root-mean-square fluctuation (RMSF) [29,43], which evaluated the flexibility of individual amino acid residue. We also examined the radius of gyration (Rg) which gives an understanding of the overall dimensions of ALOX5AP, and solvent accessible surface area (SASA) that is a bio-molecular surface area accessible to solvent molecules [29,44]. To enhance the data interpretation, custom Python scripts were developed [45] to generate visualizations of these parameters, enabling a comprehensive understanding of the simulation results. Hydrogen bonds (HB) formation analysis was also examined, HB analysis is an important factor in protein stability, structural integrity, and interactions [46]. Furthermore, trajectory snapshots per 100th frame of the entire simulation period were taken as protein data bank (PDB) files which were then superimposed to compare the structural changes of the variants structure overtime.

3. Results

3.1. Prediction of deleterious nsSNPs in ALOX5AP

A thorough computational investigation was conducted to discover harmful nsSNPs in the ALOX5AP gene utilizing SIFT, PolyPhen-2, and PANTHER tools. The findings indicated several variations with a significant likelihood of being harmful, corroborated by uniform predictions from all three methods. SIFT classified all examined nsSNPs as harmful, with scores between 0 and 0.03. The scores demonstrate significant evolutionary conservation at the impacted residues, implying that alterations at these locations are likely to impair protein function. Significant variations with a score of 0 encompass L12F, G46R, and G75R, underscoring their potential influence on protein stability and functionality. PolyPhen-2 categorized all variations as “probably damaging,” with scores approaching or equal to 1, signifying a substantial probability of functional impairment. Variants including I18N, G46R, and P65R received a maximum score of 1, thereby reinforcing their anticipated deleterious impacts. These elevated scores indicate substantial modifications in protein structure or interactions resulting from these mutations. PANTHER categorized the majority of the variations as “probably damaging,” with Pdel values between 0.57 and 0.95. Variants including (F50L), (N59K), G87R, and G100S had the highest Pdel values of 0.95, signifying a substantial probability of adverse impacts grounded in evolutionary conservation and functional significance. A number of nsSNPs were consistently predicted as harmful by all techniques. Notable variants, such as L12F, G46R, G75R, and G87R, exhibited elevated scores in SIFT, PolyPhen-2, and PANTHER (Table 1), suggesting their considerable capacity to influence the structure and function of the ALOX5AP. These findings establish a solid foundation for additional structural and functional investigations to elucidate the significance of these mutations in the etiology of CVDs.

Table 1. SIFT, PolyPhen, and PANTHER predictions for the impact of amino acid substitution on the ALOX5AP gene.

SIFT Polyphen PANTHER
Variant ID Alleles AA Predication Score Predication Score Message Pdel
rs764814001 G/T D2Y Deleterious 0.03 probably damaging 0.999 probably damaging 0.57
rs199916092 G/T L12F Deleterious 0 probably damaging 0.997 probably damaging 0.78
rs775787793 T/A I18N Deleterious 0.01 probably damaging 1 probably damaging 0.57
rs775787793 T/G I18S Deleterious 0.01 probably damaging 1 probably damaging 0.57
rs1278903858 C/A A27D Deleterious 0.02 probably damaging 0.999 probably damaging 0.57
rs1278903858 C/T A27V Deleterious 0.03 probably damaging 0.998 probably damaging 0.57
rs41351946 C/G S41R. Deleterious 0.02 probably damaging 0.994 probably damaging 0.57
rs1438548272 G/A G46R Deleterious 0 probably damaging 1 probably damaging 0.85
rs1302091419 T/G F50L Deleterious 0 probably damaging 0.992 probably damaging 0.95
rs748246562 A/G Y54C Deleterious 0.01 probably damaging 1 probably damaging 0.57
rs781044231 C/T A56V Deleterious 0 probably damaging 0.998 probably damaging 0.86
rs777940375 C/A N59K Deleterious 0 probably damaging 0.998 probably damaging 0.95
rs563599872 G/T C60F Deleterious 0 probably damaging 0.997 probably damaging 0.78
rs1245911587 A/T D62V Deleterious 0.01 probably damaging 0.998 probably damaging 0.57
rs768483394 C/G P65R Deleterious 0 probably damaging 1 probably damaging 0.95
rs1338792287 C/G L71V Deleterious 0 probably damaging 0.997 probably damaging 0.57
rs1338792287 C/T L71F Deleterious 0 probably damaging 0.962 probably damaging 0.57
rs148308449 C/A A74E Deleterious 0 probably damaging 0.999 probably damaging 0.78
rs148308449 C/T A74V Deleterious 0 probably damaging 1 probably damaging 0.78
rs376956587 G/A G75R Deleterious 0 probably damaging 1 probably damaging 0.78
rs1951856934 T/C L76P Deleterious 0.03 probably damaging 1 probably damaging 0.57
rs1951890039 C/T A83V Deleterious 0 probably damaging 0.999 probably damaging 0.78
rs1951890190 G/A G87R Deleterious 0 probably damaging 1 probably damaging 0.95
rs1489183133 G/T R94S Deleterious 0 probably damaging 1 probably damaging 0.95
rs1383209302 G/A G100S Deleterious 0 probably damaging 1 probably damaging 0.95
rs1383209302 G/C G100R Deleterious 0 probably damaging 1 probably damaging 0.95
rs1345574893 T/G I119R Deleterious 0.01 probably damaging 0.998 probably damaging 0.57
rs200791383 C/A L122M Deleterious 0 probably damaging 1 probably damaging 0.57
rs984005136 T/G L122R Deleterious 0 probably damaging 0.999 probably damaging 0.57
rs750529523 T/C M125T Deleterious 0.01 probably damaging 0.997 probably damaging 0.57
rs750529523 T/G M125R Deleterious 0.01 probably damaging 0.967 probably damaging 0.57
rs751354742 T/A Y134N Deleterious 0 probably damaging 0.997 probably damaging 0.57
rs751354742 T/C Y134H Deleterious 0.01 probably damaging 0.991 probably damaging 0.57
rs1951969673 C/A S155Y Deleterious 0 probably damaging 0.999 probably damaging 0.57
rs774719216 C/T P161S Deleterious 0 probably damaging 1 probably damaging 0.57
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3.2. Prediction of pathogenic nsSNPs in ALOX5AP using SNPs&GO and PhD-SNP

To assess the possible pathogenicity of nsSNPs in the ALOX5AP gene, the SNPs&GO and PhD-SNP tools were utilized. Both techniques reliably identified significant variations as disease-associated with high confidence. SNPs&GO categorized all four examined nsSNPs as “pathogenic,” with pathogenicity probability (Path_Prop) between 0.584 and 0.953 [37]. The variations G75R and G87R had the greatest pathogenicity probability of 0.953 each, signifying a robust correlation with functional impairment. The mutation L12F exhibited a significant likelihood of pathogenicity (0.860), hence reinforcing its harmful characteristics. The mutation A56V, despite a comparatively lower Path_Prop of 0.584, was nonetheless categorized as harmful, indicating possible functional implications. PhD-SNP classified all four variations as “disease-associated,” with reliability indices (RI) between 2 and 9, indicating the confidence in the predictions [36]. Variants G75R and G87R received the highest RI values of 9, suggesting a significant probability of becoming pathogenic variants. The variant L12F was firmly identified as disease-associated, whereas A56V obtained a risk index score of 2, indicating a moderate probability of disease association. The uniform designation of these nsSNPs as harmful by both SNPs&GO and PhD-SNP underscores their potential influence on the structure and function of the ALOX5AP. Significant variants, such as G75R and G87R were identified as the most detrimental alterations, corroborated by elevated pathogenicity probability and reliability scores (Table 2).

Table 2. Analysis of disease-associated nsSNPs on ALOX5AP gene.

SNPs&GO PhD-SNP
Variant ID Alleles Mutation Pred_class Path_Prop RI Prediction Score
rs199916092 G/T L12F Pathogenic 0.85970382 7 Disease 0
rs781044231 C/T A56V Pathogenic 0.5844504 2 Disease 1
rs376956587 G/A G75R Pathogenic 0.95299451 9 Disease 4
rs1951890190 G/A G87R Pathogenic 0.95299451 9 Disease 3
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3.3. Prediction of ALOX5AP stability changes using i-Mutant and MuPro

The impact of specific non-synonymous single nucleotide polymorphisms (nsSNPs) in the ALOX5AP on structural stability was assessed utilizing i-Mutant and MuPro (Table 3). Both instruments yielded uniform forecasts on the destabilizing effects of particular variants.

Table 3. Investigation of the molecular mechanisms underlying pathogenicity.

i-mutant MuPro
Variant ID Alleles AA Prediction score prediction
rs199916092 G/T L12F decrease 3 decrease
rs781044231 C/T A56V increase 6 decrease
rs376956587 G/A G75R decrease 6 decrease
rs1951890190 G/A G87R decrease 1 decrease
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i-Mutant forecasted a reduction in protein stability for three of the examined variations, namely L12F, G75R, and G87R. The destabilizing effects were corroborated by stability scores of 3, 6, and 1, respectively. The variant A56V was predicted to enhance stability, with a score of 6, suggesting a possible stabilizing influence on the protein structure. MuPro forecasted that all four variations will diminish ALOX5AP stability, specifically L12F, A56V, G75R, and G87R. The predictions aligned with i-Mutant for the destabilizing variants and offered a different viewpoint for the stabilizing prediction of A56V. i-Mutant and MuPro consistently recognized L12F, G75R, and G87R as destabilizing mutations, indicating their potential effect on the structural integrity and functionality of the ALOX5AP. The variant A56V displayed inconsistent predictions, necessitating more examination via MD simulations.

3.4. Prediction of functional impacts of nsSNPs using MutPred

All four examined nsSNPs received elevated pathogenicity scores, varying from 0.766 to 0.933 (Table 4). The anticipated functional effects are as follows: The L12F variant had a pathogenicity score of 0.766 and was linked to several functional modifications, such as the loss of helix and loop structures, absence of GPI-anchor amidation at N8, and disturbances in the transmembrane protein domain and signal peptide. The A56V scored 0.809 and may in the loss of a helical shape, potentially compromising local protein folding and stability. While the G75R variant received a score of 0.859 and is linked to the loss of pyrrolidone carboxylic acid at Q80, an alteration that could influence protein stability or interactions. The G87R variant demonstrated the greatest pathogenicity score of 0.933 and was anticipated to modify an ordered interface, perhaps disrupting protein-protein interactions or binding affinity. The elevated pathogenicity scores and anticipated functional effects underscore the substantial influence of these nsSNPs on the structural and functional characteristics of the ALOX5AP. The variations G75R and G87R are significant due to their elevated scores and the anticipated disruption of essential functional characteristics, including post-translational modifications and protein interfaces.

Table 4. Investigation of the molecular mechanisms underlying pathogenicity.

Mut-pred
Variant ID Alleles AA score Prediction Functions affected
rs199916092 G/T L12F 0.766 -ve Loss of Helix; Loss of Loop; Loss of GPI-anchor amidation at N8; Altered Transmembrane protein; Altered Signal peptide
rs781044231 C/T A56V 0.809 -ve Loss of Helix
rs376956587 G/A G75R 0.859 -ve Loss of Pyrrolidone carboxylic acid at Q80
rs1951890190 G/A G87R 0.933 -ve Altered Ordered interface
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3.5. Conservation analysis of ALOX5AP using ConSurf

The evolutionary conservation of amino acid residues in the ALOX5AP was assessed using ConSurf. The research indicated differing degrees of conservation throughout the protein sequence, with certain residues recognized as highly conserved and possibly essential for protein function. The results of the conservation study for the four mutants L12, A56, G75, and G87, derived from the ConSurf service, is illustrated in Fig 2. The findings indicate that these mutants had a high conservation score of 8 or 9, signifying that these residues are highly conserved and situated inside essential structural domains of the ALOX5AP. These findings indicate that mutations at these loci may exert considerable functional or structural effects. Conversely, residues with lower conservation scores, predominantly situated in more changeable and exposed areas of the protein, were less probable to be crucial for preserving the protein’s basic function. The significant conservation of L12, A50, G75, and G87 underscores their probable significance in the stability and functionality of the protein.

Fig 2. ConSurf analysis for critical residues in ALOX5AP.

Fig 2

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(A). ConSurf analysis results in terms of residue conservation and the 3D of the protein structure. A. The amount of confidence in the sequence conservation is shown by a range of colors in the ConSurf results. The sky-blue color in this color scheme stands for variable residues, while the dark purple color stands in for highly conserved residues. (B) 3D ALOX5AP indicated the position of the mutants within PDB ID 2Q7M, this figure is prepared using PyMOL [47].

3.6. Molecular dynamics (MD) simulation of ALOX5AP wildtype and its variants

3.6.1. Temperature, pressure, and density analyses of ALOX5AP wildtype and its variants.

The temperature, pressure, and density characteristics of the wildtype ALOX5AP and its variants (L12F, A56V, G75R, and G87R) were examined throughout a 100 ps simulation period to evaluate the structural and dynamic impacts of the mutations.

The temperature profiles of the wildtype protein and its mutations displayed slight variations around an average of 303 K, signifying stable thermal conditions during the simulation (S1 Fig). The majority of systems exhibited stable temperature trends, but G75R and G87R demonstrated marginally greater variability over specific intervals. The results indicate that the mutations exerted negligible influence on the overall thermal stability of the ALOX5AP.

The pressure analysis indicated an initial stabilizing period for all systems, succeeded by oscillations around a mean pressure of approximately 0 bar (S2 Fig). Both the wild-type and mutant proteins exhibited comparable patterns, while G75R had marginally more oscillations during equilibration. The data suggest that the mutations exerted little impact on the pressure stability of the ALOX5AP under the simulated conditions. The density analysis indicated that equilibrium was attained at roughly 25 ps for all systems (S3 Fig). The wildtype ALOX5AP and the majority of mutants (A56V, G75R, and G87R) had similar density values (~1010 kg/m³), indicating little structural variations. Nevertheless, the L12F mutant had a somewhat elevated density (~1023 kg/m³) (S3 Fig).

3.6.2. RMSD and RMSF analyses of ALOX5AP wildtype and its variants.

RMSD profiles of the wildtype ALOX5AP and its mutations (L12F, A56V, G75R, and G87R) during a duration of 100 ns (Fig 3A). The wild-type protein exhibited a persistent RMSD plateau of around 1.2 nm following an initial equilibration phase, signifying consistent conformational dynamics. Among the mutations, L12F demonstrated the lowest RMSD (~0.5 nm). While A56V exhibited greater variability, stabilizing at approximately 1.4 nm. The G75R and G87R mutants exhibited intermediate RMSD values (~1.0–1.2 nm), similar to the wild-type, although displayed periodic variations, signifying moderate departures in structural stability.

Fig 3. RMSD (A) and RMSF (B) analyses of ALOX5AP and its Variant proteins.

Fig 3

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Comparative MD analyses of wildtype ALOX5AP and selected variants, showing (A) RMSD trajectories indicating overall protein stability, and (B) RMSF profiles highlighting residue-level flexibility differences (ALOX5AP wildtype in black, L12F in orange, A56V in green, G75R in blue, G87R in purple). The duration of MD simulation was 100 ns.

RMSF profiles of the wildtype ALOX5AP and its mutations, emphasizing residue-specific flexibility throughout the simulation duration. The wild-type protein displayed regular changes, with peaks noted around the terminal sections, suggesting inherent flexibility in these places. Comparable tendencies were noted for the mutants, with the terminal areas (residues approaching 160) exhibiting the highest RMSF values (>2.5 nm). The L12F mutant demonstrated the least fluctuations overall, but A56V exhibited heightened variations across the protein, especially in flexible loop regions. G75R and G87R exhibited minor variations, with marginally increased RMSF values near the termini in comparison to the wild-type (Fig 3B).

3.6.3. Radius of gyration (Rg) Analysis of ALOX5AP Wildtype and its variants.

The Rg patterns for the wildtype ALOX5AP and its mutations (L12F, A56V, G75R, and G87R) during a 100 ns simulation period are shown in Fig 4. The Rg denotes the compactness of the protein structure, with diminished values indicating a more tightly folded conformation. The wildtype ALOX5AP exhibited an average Rg of approximately 2.2 nm during the simulation, with slight variations, signifying a stable and somewhat compact conformation. The L12F mutant had the lowest Rg value (~1.8 nm) with minor variations, signifying a highly compact and stable structure in comparison to the wild-type protein and other mutants. The A56V mutant had the largest Rg (~2.6 nm) among the systems, with considerable oscillations over the simulation duration. The A56V mutation results in a more expansive and flexible structure. The G75R and G87R mutants displayed intermediate Rg values (~2.1–2.3 nm) similar to those of the wildtype protein, with minor variations. The G75R and G87R mutations demonstrate behavior akin to the wildtype protein (Fig 4).

Fig 4. Radius of gyration (Rg) Analyses of ALOX5AP wildtype and its Variants.

Fig 4

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Comparative analysis of Rg trajectories for Cα atoms, depicting structural compactness and stability differences among wildtype ALOX5AP and mutant variants (ALOX5AP wildtype in black, L12F in orange, A56V in green, G75R in blue, G87R in purple) during MD simulations for 100 ns.

3.6.4. SASA analysis of ALOX5AP wildtype and its variants.

SASA patterns of the wildtype ALOX5AP and its mutations (L12F, A56V, G75R, and G87R) during a 100 ns simulation period. SASA quantifies the surface area of a protein accessible to the solvent, offering information regarding structural compactness and conformational alterations. The wild-type protein exhibited an average SASA of roughly 115 nm², with slight variations during the simulation, signifying a highly stable structure with uniform solvent exposure. The L12F mutant demonstrated the lowest solvent-accessible surface area (SASA) of around 95 nm², with negligible variability. The A56V mutant had the greatest SASA of around 125 nm² among the systems, indicating enhanced solvent exposure. The G75R and G87R mutants demonstrated SASA values akin to the wild-type (~115 nm²), with minor variations during the simulation. The results demonstrate that these alterations do not substantially influence the solvent exposure or compactness of the protein. The SASA analysis demonstrates specific impacts of the mutations on the structural characteristics of the ALOX5AP (Fig 5).

Fig 5. SASA analyses of ALOX5AP wildtype and its variants.

Fig 5

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SASA analyses of ALOX5AP wildtype and its variants for 100 ns. (ALOX5AP wildtype in black, L12F in orange, A56V in green, G75R in blue and G87R in purple).

3.6.5. Hydrogen bond (HB) formation analyses of ALOX5AP wildtype and its variants.

HB is a vital factor in protein stability, structural integrity, and interactions.

The ALOX5AP wildtype exhibited an average of approximately 125 HB during the simulation, with consistent variations, signifying stable internal bonding and structural integrity.

The L12F mutant displayed the fewest HBs (about 100), with diminished variations relative to the wild-type and other mutants. The A56V mutant exhibited a moderately decreased hydrogen bond count (~110) relative to the wild-type, accompanied by somewhat increased fluctuations. The G75R and G87R mutants exhibited HB counts (~115–120) akin to the wildtype, with analogous oscillations. This indicates that these mutations exert negligible influence on the overall hydrogen bonding network and structural integrity of ALOX5AP. The study of HBs elucidates the structural implications of the mutations in ALOX5AP (Fig 6).

Fig 6. Hydrogen bond (HB) formation analyses of ALOX5AP wildtype and its variants.

Fig 6

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HB formation analyses of ALOX5AP wildtype and its variant proteins for 100 ns (ALOX5AP wildtype in black, L12F in orange, A56V in green, G75R in blue and G87R in purple).

3.6.6. Simulation trajectory snapshot.

The MD simulation trajectory of the wildtype ALOX5AP and its variants (L12F, A56V, G75R, and G87R) reveals that most of the protein remains stable, with well-aligned helices and minimal deviations in the core structure (Fig 7). However, the loops are inherently more flexible, which is biologically relevant since loops naturally exhibit greater flexibility. Interestingly, some mutations, such as L12F and A56V, induce notable flexibility in specific loop regions, but this instability is relatively mild compared to the more pronounced effects seen in the G75R and G87R mutants. These latter mutations cause widespread structural perturbations, including disrupted helical packing and increased loop flexibility, likely due to steric or electrostatic changes introduced by the mutations.

Fig 7. Simulation trajectory snapshots of ALOX5AP wildtype and its variants.

Fig 7

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Structural comparison of ALOX5AP wildtype and its Variant proteins based on simulation trajectory snapshots.

Discussion

Cardiovascular diseases (CVDs) and cerebrovascular diseases are one of the main causes of deaths and disabilities worldwide with 20.5 million deaths in the year 2021 [48,49]. Certain genetic loci were reported to be associated with CVDs with exome and genome-wide sequencing methods [50,51]. Genetic testing is used to identify the individuals and populations at risk for CVDs and other diseases [52,53]. Maintaining a healthy lifestyle such as sound nutrition, regular physical activity, no alcohol, no smoking and weight loss will reduce the risk of CVDs [54].

The ALOX5AP is important for the synthesis of leukotrienes, which is involved in inflammatory reactions and dysregulation of leukotrienes production results in atherosclerosis [55,56]. Atherosclerosis is main pathogenic cause of CAD, cerebral stroke, peripheral arterial disease [57]. Jin et al reported that the SNPs (rs17216473, rs10507391, rs4769874, rs9551963, rs17222814, and rs7222842) of ALOX5AP gene were associated with peripheral arterial disease in elderly Korean population [58]. While, Lee et al., reported that ALOX5AP rs4293222, rs10507391, rs12429692 SNPs were associated with risk of atherothrombotic stroke in Taiwanese population [59]. Furthermore, it has been demonstrated that the ALOX5AP 17216473 SNP is linked to CAD in Ukrainian Chinese populations [60,61]. In addition, rs4073259, rs9579646, rs9551963, rs9315050, rs9551963 and the rs4073259 SNPs of ALOX5AP were linked with ischemic stroke in Chinese Han population [62]. Moreover, the ALOX5AP rs38022789 SNP was reported to be associated with diabetic nephropathy in Slovenian population [63]. Whereas, the ALOX5AP rs10507391 SNP was reported to increase susceptibility to myeloid leukemia in Chinese population [22].

The protein structure affects its protein-protein interaction and function [64]. SNPs may influence protein structure and function and therefore bioinformatics, protein structural and function studies are required to gain insight on the impact of SNPs on protein [65–68]. In the present study we investigated the effects of nsSNPs the structure of ALOX5AP using bioinformatics tools. We employed MD simulation to examined effect of nsSNPs L12F, A56V, G75R, and G87R on ALOX5AP structural stability since ALOX5AP gene variations are associated with CVDs and other diseases [17,63,69,70].

Our results indicated L12F results in exchange of leu 12 to Phe (Tables 1–3, and Fig 3). This variant results in structural changes of ALOX5AP leading to loss of helix, loop, loss of GPI-anchor amidation at N8, transmembrane protein change and alteration of signal peptide (Table 4). Furthermore, results showed that L12F variant exhibited a slightly elevated density (~1023 kg/m³), indicated possible modifications of ALOX5AP in packing and compactness (S3 Fig). Result also showed that the L12F variant may affect the structural integrity of ALOX5AP more profoundly than the other variants. The L12F variant demonstrated the lowest RMSD (~0.5 nm), (Fig 3A), and highest RMSF values (>2.5 nm) (Fig 3B) indicating a more compact and stable structure. The L12F variant showed the least fluctuations overall aligning with its compact structure. RMSD and RMSF analyses demonstrate that the L12F mutation enhances ALOX5AP stability, leading to a more ALOX5AP compact conformation. Moreover, our Rg results indicated that the L12F mutation appears to improve protein folding and stability (Fig 4). Whereas the SASA analysis (Fig 5) showed that L12F variant had diminished solvent exposure providing a more compact structure relative to the ALOX5AP wildtype and other variants, implying that L12F variant augments structural compactness of ALOX5AP. HB data (Fig 6) indicated that the L12F variant diminishes the total hydrogen bonding capability, potentially leading to a more compact and stiff structure as observed in prior assessments. The L12F variant results in an increased ALOX5AP compact conformation (Fig 7) leading to structural changes which can significantly influence the functional properties of the ALOX5AP. This may be consistent with a study reported that a mutation leading to more compact protein can alter protein structure dynamics and significantly affect the function of the protein [71].

Results showed that the A56V variant leads to ALOX5AP loss of helix and pathogenic (Tables 1–4). Result of density experiment of the A56V variant (~1010 kg/m³) was comparable to that of the ALOX5AP wild type, implying little structural change (S3 Fig). In RMSD experiment, the A56V showed greater variability, stabilizing at about 1.4 nm, indicating enhanced structural flexibility. In the RMSF experiment, the A56V showed the greatest variations across the ALOX5AP, especially in flexible loop regions. In summary, the RMSD and RMSF analyses showed that the A56V mutation promotes the flexibility and protein structural variability, and weakens the stability of the ALOX5AP (Fig 3). Whereas our SASA analysis showed that the A56V variant had the greatest Rg (~2.6 nm) than the ALOX5AP wildtype and its variants (Fig 4). with considerable oscillations over the simulation duration. The A56V mutation leads to a more expansive and flexible structure of ALOX5AP, indicating reduced compactness and possible instability of ALOX5AP. In addition, the SASA run showed that the A56V mutant had the biggest SASA (~125 nm²) than the ALOX5AP wildtype and its variants, indicating enhanced solvent exposure (Fig 5). This indicates that the A56V variant induces a more extended and less compact structure, potentially signifying destabilization or modified folding of ALOX5AP. The HB experiment indicated that A56V mutant exhibited a slightly reduced HB (~110) relative to the ALOX5AP wildtype, agreeing with its increased fluctuations (Fig 6). This suggests that the A56V mutation may interfere with hydrogen bonding interactions, resulting in diminished stability and structural integrity. The results of the simulation trajectory snapshots indicated that the A56V results in notable flexibility in specific ALOX5AP loop regions (Fig 7).

Result also showed that the G75R and G87R variants influence the ALOX5AP structure (Tables 1–4). These variants result in substitution of glycine 75, 87, respectively (un uncharged amino acid) to arginine (a positively charged) amino acid. Result indicated that G75R and G87R variants result in loss of pyrrolidone carboxylic acid at Q80 of ALOX5AP and altered ordered interface, respectively, of ALOX5AP. Our RMSD and RMSF data showed that the G75R and G87R exhibited minor variations, with marginally increased RMSF values near the termini in comparison to the wild-type (Fig 3). The G75R and G87R variants displayed intermediate Rg values (~2.1–2.3 nm) similar to those of the wildtype protein (Fig 4). These findings indicate that G75R and G87R variant exert a mild influence on the compactness of ALOX5AP structure without causing substantial instability. Result of SASA analysis showed that the G75R and G87R variants exert no influence on the ALOX5AP solvent exposure, preserving characteristics similar to the wildtype (Fig 5). Moreover, G75R and G87R variants preserved HB formation patterns comparable to ALOX5AP wildtype, suggesting negligible effects on the protein’s internal bonding and stability (Fig 6). In addition, simulation trajectory snapshots results indicated G75R and G87R variants induce instability causing widespread structural perturbations of ALOX5AP, including disrupted helical packing and increased loop flexibility, likely due to steric or electrostatic changes introduced by Arginine (Fig 7). The G75R and G87R variants potentially impact ALOX5AP dynamics, stability, and function.

The impaired ALOX5AP function due to the mutations would affects the leukotrienes biosynthesis. Leukotrienes are crucial pro-inflammatory lipid mediators, play important roles in the pathogenesis of acute or chronic inflammatory diseases, and implicated in immune-mediated disorders such as bronchial asthma, rhinitis, atherosclerotic CVD and stroke [55,56,72]. Limitations of the present study include that this in silico analysis was performed on certain genetic variants, and other variants of ALOX5AP, potentially critical to clinical outcomes, were not analyzed. Furthermore, the MD simulations do not fully represent the complexity of cellular environments, including intricate interactions with arachidonic acid and 5-lipoxygenase, cell membrane and other physiological conditions which may affect ALOX5AP function.

Conclusion

To sum up, in this MD simulation study we investigated the effects of certain nsSNPs on the structure of the ALOX5AP. The L12F, A56V, G75R, and G87R using bioinformatics tools. Results showed that variants influence the ALOX5AP differently. L12F variant caused noticeable structural changes, making ALOX5AP more compact and stable. These changes included improved structural integrity, reduced flexibility, and decreased solvent exposure. While A56V variant has a destabilizing effect, increasing ALOX5AP flexibility and reducing its compactness and stability. The G75R and G87R variants, while causing some localized structural disruptions, had relatively minor effects overall and retained much of the stability seen in ALOX5AP wild-type. Our study highlights how these variations in the ALOX5AP gene can differently affect the protein’s structure, stability, and function leading to defective leukotrienes biosynthesis, shedding light on their potential contributions to the development of atherosclerotic CVDs and other diseases reported to be associated with ALOX5AP variants. Future MD simulations (to more nsSNPs) in which the complexity of cellular environment is presented, large scale case-control and protein functional studies are required to validate these findings.

Supporting information

S1 Fig. Simulation of the temperature changes over time for the ALOX5AP wildtype and its variant proteins.

(TIF)

pone.0329126.s001.tif (350.5KB, tif)
S2 Fig. Simulation of the pressure changes over time for the ALOX5AP wildtype and its variant proteins.

(TIF)

pone.0329126.s002.tif (186.4KB, tif)
S3 Fig. Simulation of the density changes over time for the ALOX5AP wildtype and its variant proteins.

(TIF)

pone.0329126.s003.tif (123.5KB, tif)

Abbreviations

ALOX5AP

Arachidonate 5-Lipoxygenase Activating Protein

FLAP

5-Lipoxygenase Activating Protein

5-LO

5-Lipoxygenase

LT

Leukotrienes

LTA4

Leukotriene A4

LTB4

Leukotriene B4

LTC4

Leukotriene C4

LTD4

Leukotriene D4

LTE4

Leukotriene E4

LTC4S

Leukotriene C4 Synthase

CVDs

Cardiovascular Diseases

CAD

Coronary Artery Disease

MI

Myocardial Infarction

SNP

Single Nucleotide Polymorphism

nsSNP

Non-Synonymous Single Nucleotide Polymorphism

MD

Molecular Dynamics

RMSD

Root Mean Square Deviation

RMSF

Root Mean Square Fluctuation

Rg

Radius of Gyration

SASA

Solvent Accessible Surface Area

HB

Hydrogen Bond

PDB

Protein Data Bank

NCBI

National Center for Biotechnology Information

OMIM

Online Mendelian Inheritance in Man

Data Availability

All relevant data are within the manuscript and its Supporting information files.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Khalid Raza

Dear Dr. Elfaki,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

After carefully considering the reviews and assessing your manuscript, I am pleased to inform you that we would like to invite you to revise and resubmit your manuscript for further consideration. The reviewers have provided constructive comments that will help strengthen your work. Please address each of these points thoroughly in your revised manuscript. Additionally, ensure that you provide a detailed response letter outlining how you have addressed each comment raised by the reviewers. This will help the reviewers and myself to evaluate the changes made to the manuscript.  Please note that additional references suggested during the peer-review process should only be included if the authors agree that they are relevant and useful. Good luck

==============================

Please submit your revised manuscript by Jul 02 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

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Khalid Raza, PhD (Computational Biology)

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Partly

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: No

Reviewer #2: N/A

**********

3. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: No

Reviewer #2: Yes

**********

Reviewer #1: The manuscript contains numerous grammatical errors and typographical mistakes throughout. A thorough revision is necessary before resubmission. Editing by a native English speaker or professional language editing service is strongly recommended.

Section 2.2: Data Collection

References are missing. Please provide appropriate citations to support the methodology described.

Section 2.5: Molecular Dynamics (MD) Simulations Using GROMACS

The section lacks sufficient citations. Key methodological steps and tools used in the simulations should be properly referenced.

Section 3.1: Prediction of Deleterious nsSNPs in ALOX5AP

The classification of mutations is not adequately referenced. For example, the manuscript states that SIFT classified all examined nsSNPs as harmful, with scores between 0 and 0.03. However, the rationale for selecting this threshold is not provided or supported with references.

Throughout this section, several predictive tool results (e.g., SNPs&GO, PROVEAN, PhD-SNPg) are reported without proper citation or explanation of the basis of score ranges used for classification. This reduces the credibility of the findings and should be addressed.

Discussion

The discussion lacks scientific depth and critical comparison with findings from other published studies.

The opening part of the discussion reads more like an introduction and should be revised to focus on interpreting results.

The impact of the identified mutations, particularly in relation to cardiovascular diseases, needs to be discussed in more detail. For example, although the figures suggest that the L12F variant causes significant structural compaction of ALOX5AP, the manuscript fails to explain how this structural change could affect protein function or contribute to cardiovascular disease mechanisms.

The sentence: “Our result in inconsistent with a study reported that the p.L12F variant has no detrimental effect on the pancreatic secretory trypsin inhibitor protein(47), this inconsistency may because of the different protein examined in that study(47).” is problematic both in grammar and logic. If the compared study involves an entirely different protein, then drawing a direct comparison based on the same amino acid substitution (L12F) is inappropriate due to differences in tertiary structure and protein context. This kind of comparison is premature and scientifically unsound.

Conclusion

The conclusion section would benefit from a brief discussion of the study’s limitations. Additionally, future research directions should be clearly outlined to enhance the manuscript’s overall impact.

Reviewer #2: Dear authors,

Your manuscript is somehow interesting. However, the major issue which comes in my mind, plot the simulation results in in Angstrom, not in nm to make it clear how much the results has deviated. Also, compare it with standard results.

**********

what does this mean? ). If published, this will include your full peer review and any attached files.

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Reviewer #1: Yes:  Dr Ayan Saha

Assistant Professor

Bioinformatics and Biotechnology

Asian University for Women

Chattogram-4000, Bangladesh.

Reviewer #2: No

**********

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Attachment

Submitted filename: PONE-D-25-17796.docx

pone.0329126.s004.docx (13.9KB, docx)
PLoS One. 2025 Jul 30;20(7):e0329126. doi: 10.1371/journal.pone.0329126.r002

Author response to Decision Letter 1

11 Jun 2025

Dear Editor, Dear reviewers

Thank you very much for your consideration. We also thank you and the reviewers for the questions and the comments that significantly improved our manuscript. Please find below step-by-step response to all questions and comments.

Best regards,

Imadeldin Elfaki, PhD

The manuscript contains numerous grammatical errors and typographical mistakes throughout. A thorough revision is necessary before resubmission. Editing by a native English speaker or professional language editing service is strongly recommended.

Authors

Thank you very much. We are very sorry that manuscript contains numerous grammatical errors and typographical mistakes. English is revised carefully.

Section 2.2: Data Collection

● References are missing. Please provide appropriate citations to support the methodology described.

Authors

● Thank you very much. Appropriate citations to support the methodology described are provided. Please see ref 24 to 45.

Section 2.5: Molecular Dynamics (MD) Simulations Using GROMACS

● The section lacks sufficient citations. Key methodological steps and tools used in the simulations should be properly referenced.

● Authors

● Thank you very much. In molecular dynamics (MD) simulation the temperature, pressure, and density [1, 2] characteristics of the wild-type ALOX5AP protein and its mutants (L12F, A56V, G75R, and G87R) were examined throughout a 100 ps simulation period to evaluate the structural and dynamic impacts of these variants. to examine the structural stability and flexibility of ALOX5AP key metrics such as the root-mean-square deviation (RMSD) [1, 2], which assesses the ALOX5AP overall structural stability, and root-mean-square fluctuation (RMSF) [1, 2], which evaluated the flexibility of individual amino acid residue. We also examine the radius of gyration (Rg) which gives an understanding of the overall dimensions of ALOX5AP, and solvent- accessible surface area (SASA) that is a bio-molecular surface area accessibility to solvent molecules [1, 3]. Hydrogen bonds analysis was also examined, HB is an important factor in protein stability, structural integrity, and interactions[4]. To enhance the data interpretation, custom Python scripts were developed [5] to generate visualizations of these parameters, enabling a comprehensive understanding of the simulation results.

●

Section 3.1: Prediction of Deleterious nsSNPs in ALOX5AP

● The classification of mutations is not adequately referenced. For example, the manuscript states that SIFT classified all examined nsSNPs as harmful, with scores between 0 and 0.03. However, the rationale for selecting this threshold is not provided or supported with references.

● Authors

● Thank you very much. In SIFT Score, the amino acid substitution is predicted damaging if the score is <= 0.05[6], please also see website https://sift.bii.a-star.edu.sg/www/SIFT_help.html. The SIFT Score of the selected variants L12F, A56V, G75R and G87R variants was 0 (Table1). This score is predicted damaging or deleterious to the protein.

● Throughout this section, several predictive tool results (e.g., SNPs&GO, PROVEAN, PhD-SNPg) are reported without proper citation or explanation of the basis of score ranges used for classification. This reduces the credibility of the findings and should be addressed.

● Authors

● -Thank you very much. In the SNPs&Go, score of 0.5 is selected to distinguish between benign (t≤0.5) and pathogenic (t>0.5) SNP[7]. SNPs&GO categorized all four examined nsSNPs as "pathogenic," with pathogenicity probability (Path_Prop) between 0.584 and 0.953[7] (Table2).

● -We did not employ PROVEAN in this study.

● - The PhD-SNP classified all four variations as "disease-associated," with reliability indices (RI) between 2 and 9, indicating the confidence in the predictions[8].

Discussion

● The discussion lacks scientific depth and critical comparison with findings from other published studies.

● Authors

● Thank you very much. A comparison with findings from other published studies was added in a separated paragraph. Changes are highlighted.

● The opening part of the discussion reads more like an introduction and should be revised to focus on interpreting results.

Authors

opening part of the is revised and focused on interpreting results

● The impact of the identified mutations, particularly in relation to cardiovascular diseases, needs to be discussed in more detail. For example, although the figures suggest that the L12F variant causes significant structural compaction of ALOX5AP, the manuscript fails to explain how this structural change could affect protein function or contribute to cardiovascular disease mechanisms.

● Authors

● Thank you very much. We explained how this structural change due to the mutation could affect ALOX5AP function or contribute to cardiovascular disease mechanisms.

● The sentence: “Our result in inconsistent with a study reported that the p.L12F variant has no detrimental effect on the pancreatic secretory trypsin inhibitor protein(47), this inconsistency may because of the different protein examined in that study(47).” is problematic both in grammar and logic. If the compared study involves an entirely different protein, then drawing a direct comparison based on the same amino acid substitution (L12F) is inappropriate due to differences in tertiary structure and protein context. This kind of comparison is premature and scientifically unsound.

● authors

● Thank you very much. We remove the sentence “Our result in inconsistent with a study reported that the p.L12F variant has no detrimental effect on the pancreatic secretory trypsin inhibitor protein.

Conclusion

● The conclusion section would benefit from a brief discussion of the study’s limitations. Additionally, future research directions should be clearly outlined to enhance the manuscript’s overall impact.

● Authors

● Thank you very much. Some study limitations and suggested future research direction are added to the conclusion.

REFERENCES

1. Hasnain MJU, Shoaib M, Qadri S, Afzal B, Anwar T, Abbas SH, Sarwar A, Talha Malik HM, Tariq Pervez M: Computational analysis of functional single nucleotide polymorphisms associated with SLC26A4 gene. PLoS One 2020, 15(1):e0225368.

2. Alomair L, Mustafa S, Jafri MS, Alharbi W, Aljouie A, Almsned F, Alawad M, Bokhari YA, Rashid M: Molecular Dynamics Simulations to Decipher the Role of Phosphorylation of SARS-CoV-2 Nonstructural Proteins (nsps) in Viral Replication. Viruses 2022, 14(11).

3. Rani N, Boora N, Rani R, Kumar V, Ahalawat N: Molecular dynamics simulation of RAC1 protein and its de novo variants related to developmental disorders. J Biomol Struct Dyn 2024, 42(24):13437-13446.

4. Zhang D, Lazim R: Application of conventional molecular dynamics simulation in evaluating the stability of apomyoglobin in urea solution. Sci Rep 2017, 7:44651.

5. Irrgang ME, Davis C, Kasson PM: gmxapi: A GROMACS-native Python interface for molecular dynamics with ensemble and plugin support. PLoS Comput Biol 2022, 18(2):e1009835.

6. Ng PC, Henikoff S: Predicting deleterious amino acid substitutions. Genome Res 2001, 11(5):863-874.

7. Capriotti E, Martelli PL, Fariselli P, Casadio R: Blind prediction of deleterious amino acid variations with SNPs&GO. Hum Mutat 2017, 38(9):1064-1071.

8. Capriotti E, Calabrese R, Casadio R: Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information. Bioinformatics 2006, 22(22):2729-2734.

Attachment

Submitted filename: Response to Reviewers.docx

pone.0329126.s005.docx (34.4KB, docx)

Decision Letter 1

Khalid Raza

Dear Dr. Elfaki,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

==============================

Before manuscript may be accepted, authors are required to address the following concerns: 1) Drop the word "(MD)" from the title. 2) Section 2.1 heading, check the spelling of "Plane".  3) A large number of abbreviations have been used. Compile a list of abbreviations used and place it before the References section 4) There spacing issues and other typos throughout the manuscript. For instance, there is no space between Figure and figure numbers. Get your manuscript thoroughly proofread.

==============================

Please submit your revised manuscript by Aug 15 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols .

We look forward to receiving your revised manuscript.

Kind regards,

Dr. Khalid Raza, PhD (Computational Biology)

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions??>

Reviewer #1: Partly

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: N/A

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #1: No

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #2: Yes

**********

Reviewer #1:  The manuscript is in good form for acceptance, but kindly review the grammar and typos once again. Improve the quality of figures also.

Reviewer #2:  The manuscript is now well improved as the authors has addressed all of my comments and can be accepted for publication.

**********

what does this mean? ). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy

Reviewer #1: Yes:  Dr Ayan Saha

Reviewer #2: Yes:  Shaban Ahamd

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org

PLoS One. 2025 Jul 30;20(7):e0329126. doi: 10.1371/journal.pone.0329126.r004

Author response to Decision Letter 2

7 Jul 2025

Dear Editor

Thank you very much for the considering our paper. We also thank you and the reviewers the comments that significantly improved our manuscript. Please find below responses to questions and comments.

Best regards,

Imadeldin Elfaki, PhD

1) Drop the word "(MD)" from the title.

Authors

Thank you very much. MD is dropped from the title.

2) Section 2.1 heading, check the spelling of "Plane".

Authors

Thank you very much: The spelling of ‘’plane’’ is checked.

3) A large number of abbreviations have been used. Compile a list of abbreviations used and placed it before the References section

Authors

Thank you very much. A list of abbreviations used is prepared and placed before the References section

4) There spacing issues and other typos throughout the manuscript. For instance, there is no space between Figure and figure numbers. Get your manuscript thoroughly proofread.

Authors

Thank you very much. Types errors are revised; the manuscript is thoroughly proofread.

Attachment

Submitted filename: response to reviewers 7 7 25 afternoon.docx

pone.0329126.s006.docx (15.6KB, docx)

Decision Letter 2

Khalid Raza

Computational Prediction of the Pathogenic Variants of Arachidonate 5-Lipoxygenase Activating Protein Using Molecular Dynamics Simulation

PONE-D-25-17796R2

Dear Dr. Elfaki,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Khalid Raza, PhD (Computational Biology)

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Khalid Raza

PONE-D-25-17796R2

PLOS ONE

Dear Dr. Elfaki,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team.

At this stage, our production department will prepare your paper for publication. This includes ensuring the following:

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Academic Editor

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    Supplementary Materials

    S1 Fig. Simulation of the temperature changes over time for the ALOX5AP wildtype and its variant proteins.

    (TIF)

    pone.0329126.s001.tif (350.5KB, tif)
    S2 Fig. Simulation of the pressure changes over time for the ALOX5AP wildtype and its variant proteins.

    (TIF)

    pone.0329126.s002.tif (186.4KB, tif)
    S3 Fig. Simulation of the density changes over time for the ALOX5AP wildtype and its variant proteins.

    (TIF)

    pone.0329126.s003.tif (123.5KB, tif)
    Attachment

    Submitted filename: PONE-D-25-17796.docx

    pone.0329126.s004.docx (13.9KB, docx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    pone.0329126.s005.docx (34.4KB, docx)
    Attachment

    Submitted filename: response to reviewers 7 7 25 afternoon.docx

    pone.0329126.s006.docx (15.6KB, docx)

    Data Availability Statement

    All relevant data are within the manuscript and its Supporting information files.

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