HMG-CoA reductase (3-hydroxy-3-methyl-glutaryl-CoA reductase) is considered an important enzyme due to its catalytic activity. It catalyzes the metabolic processes that synthesize cholesterol, isoprenoids, and other lipids by converting HMG-CoA to mevalonate. Within this metabolic pathway, HMG-CoA reductase controls the rate-limiting step of cholesterol synthesis (Friesen & Rodwell, 2004). Excessive synthesis of cholesterol has a major impact on human morbidity and mortality, particularly from atherosclerosis, followed by myocardial infarction or stroke (Vance & Van den Bosch, 2000). This metabolic route, commonly known as the mevalonate or isoprenoid pathway, is highly conserved across eukaryotes, archaea, and certain bacteria (Buhaescu & Izzedine, 2007). 

Drugs that inhibit HMG-CoA reductase are referred to as HMG-CoA reductase inhibitors, or "statins." Statins primarily target this enzyme and block the conversion of HMG-CoA to mevalonate (Jiang et al., 2018). Statins inhibit the activity of 3-hydroxy-3-methyl-glutaryl-CoA reductase (HMGCR) by directly binding to its active site and inducing conformational changes (Stancu & Sima, 2001). Owing to this mechanism, statins are the most commonly prescribed drugs for the prevention of cardiovascular diseases (Wang et al., 2015). Additionally, recent research has indicated that statins have protective effects against colorectal cancer, and by inhibiting HMGCR, they can reduce the risk of colorectal cancer by 43% with at least 5 years of use (Bonovas et al., 2007; Lochhead & Chan, 2013). Currently, more than 25 million people worldwide are using statins to lower their risk of cardiovascular disorders (Lipkin et al., 2010). But statins can cause myalgia and rhabdomyolysis, which is characterized by muscular injury, weakness, and dark urine, and severe rhabdomyolysis can cause acute kidney disease (Malani et al., 2024; Petreski et al., 2021). These side effects highlight the need for alternative therapeutic strategies (Gesto et al.,  2014; Yousuf et al., 2023).

In this context, computational approaches have become indispensable in structure-based drug design, as they help in understanding the three-dimensional structure of the protein target to which the candidate drugs are intended to bind. Once the special target site of the protein is known, docking methods can be applied for designing drugs (Nishant et al., 2011). Experimental techniques like NMR and X-ray crystallography are typically used to discover the three-dimensional structure of proteins, but these methods are highly expensive, time-consuming, and quite labor-intensive. With the help of various bioinformatics tools, this study examines evolutionary relationships, conserved motifs, and physicochemical parameters of HMGR proteins, thereby providing a primary step for designing a target drug for the reduction of cholesterol synthesis in humans. 

Retrieval of target and template sequences

Twelve full-length amino acid sequences of 3-hydroxy-3-methylglutaryl CoA reductase (HMGR) from Drosophila melanogaster I (AAF56175.1), Drosophila melanogaster II (NP_732900.1), Homo sapiens (NP_001124468.1), Paris fargesii (AEL-30660.1), Catharanthus roseus (AAA33108.1), Try-panosoma grayi (XP_009313205.1), Leishmania donovani (AF054499.1), Brevibacillus leterosporus (WP_022584705.1), Vibrio alginolyticus (WP_-017820181.1), Encephalitozoon cuniculi GB-M1 (CAD25893.2), Aspergillus oryzae 100-8 (KDE-78541.1), and Haloterrigena turkmenica DSM 5511 (YP_003402108.1) were searched and retrieved from the NCBI database and saved in FASTA format. For clarity, the two Drosophila melanogaster sequences were designated as D. melanogaster I and D. melanogaster II. The sequences were organized according to species group: fruit fly, human, plants, protists, bacteria, fungi, and archaea.

Physicochemical characterization

Physicochemical properties of the protein, which include the theoretical isoelectric point (PI value) (Bjellqvist et al., 1993), total number of negatively (Asp+Glu) and positively (Arg+Lys) charged residues, and extinction coefficients (Gill & von Hippel, 1989), instability index (Guruprasad et al.,  1990), aliphatic index (Ikai, 1980; Saikat et al., 2020), and grand average of hydropathicity (GRAVY) (Kyte and Doolittle, 1982), were computed using Expasy's Protparam server (Wilkins et al., 1999). The molecular weight and amino acid composition (essential and non-essential residues) were also calculated using the same server.

Secondary structure prediction

Secondary structural features of amino acid sequences were predicted by the Self-Optimized Prediction Method Alignment (SOPMA) server (Geourjon & Deleage, 1995) and PHD server (Rost et al., 1994). These tools classified regions of the proteins into alpha helices, beta strands, and random coils. The secondary structures from amino acid sequences were predicted by setting default parameters in the web server (number of states: 3, similarity threshold: 8, and window width: 17).

Subcellular localization prediction

Subcellular localization was predicted to provide insights into the biological functions of the proteins (Gillani & Pollastri, 2024). For fruit fly, plant, and fungal sequences, localization was predicted using WoLF PSORT (Horton et al., 2007). Subcellular localization of human, protists, and bacteria was determined by CELLO (Yu et al., 2004), while archaeal sequences were analyzed by PSORT-b (Gardy et al., 2003).

Multiple sequence alignment and construction of a phylogenetic tree

A multiple sequence alignment was conducted using ClustalW (Thompson, Higgins, & Gibson, 1994) software to compare sequences of HMG-CoA reductase from human and other species. A phylogenetic tree was constructed using the UPGMA method (Schlee, 1975) and were aligned with each other by using ClustalW software (Thompson et al., 1994).

Motif analysis

Protein sequence motifs were predicted using Multiple EM for Motif Elicitation (MEME) version 4.10.0 (Bailey et al., 2006) and Motif Alignment and Search Tool (MAST) version 4.10.0 (Bailey & Gribskov, 1998). The parameters were set as follows: the minimum and maximum motif widths were 6 and 50, respectively; the maximum number of motifs was limited to 10; and each sequence was allowed zero or one occurrence of a motif.

Homology modeling and visualization

Three-dimensional structures of the HMGR proteins were generated using the SWISS-MODEL workspace (https://swissmodel.expasy.org) (Arnold et al., 2006). The predicted models were visualized and analyzed using PyMOL version 1.3 (DeLano, 2002).

Protein 3D model quality assessment

The stereochemical quality of the predicted protein models was assessed using PROCHECK (Laskowski et al.,  1996) by Ramachandran plot analysis (Spencer et al., 2019), through PDBsum (Laskowski et al., 2005). Additionally, ERRAT (Colovos & Yeates, 1993), and VERIFY 3D (Bowie et al., 1991; Eisenberg et al., 1997) scores by using the Structure Analysis and Verification (SAVES) Server version 4 (https://saves.mbi.ucla.edu/) were employed for further evaluation of the HMG-CoA reductase protein models. 

Physico-chemical characterization

The physicochemical properties of each of the proteins were determined by the ProtParam server (Wilkins et al., 1999). These characteristics include the molecular weight, theoretical pI, and extinction coefficient (Gill & von Hippel, 1989), instability index (Guruprasad et al., 1990), aliphatic index (Ikai, 1980), grand average of hydropathicity (GRAVY) (Kyte & Doolittle, 1982) and the absolute number of negatively and positively charged residues, which are shown in Table 1, and the essential amino acid compositions are shown in Fig. 1.

Table 1: Parameters computed using Expasy's ProtParam tools.

*Extinction coefficient (EC), *Isoelectric Point (PI), *Grand average of hydropathicity (GRAVY) 

 Understanding the theoretical pI, which is the pH at which a specific molecule or surface has no net electrical charge, helps understand the charge stability of proteins (Enany, 2014). The calculated isoelectric points (pI) of HMG-CoA reductase proteins ranged from 4.43 to 9.01. Determination of the Instability index results in an understanding of the stability of the protein. An Instability index value exceeding the value of 40 indicates an unstable nature of the protein, while the protein whose Instability index value is less than 40, predicted as stable (Guruprasad et al., 1990). The instability index value indicated that HMG-CoA reductase proteins from H. sapiens (51.39) and C. roseus (52.25), P. fargesii (44.59), D. melanogaster I and II (41.89) are unstable; on the other hand, proteins of the rest of the species were stable (instability index < 40), indicating better robustness. 

A protein that has a high aliphatic index is thermostable over a broad temperature range (Ikai, 1980). Value of AI, an indicator of thermostability, was highest in H. sapiens (97.27), closely followed by C. roseus (96.74), D. melanogaster (96.58), and P. fargesii (95.48), while the lowest was in E. cuniculi (87.66), indicating reduced thermal stability. Proteins with positive or negative grand average hydropathy (GRAVY) values are considered hydrophobic or hydrophilic, respectively (Kyte & Doolittle, 1982). GRAVY (Grand Average of Hydropathicity) analysis suggested that most HMG-CoA reductase proteins, including H. sapiens, were hydrophobic. Exceptions included B. laterosporus (-0.013), E. cuniculi (-0.108), and H. turkmenica (-0.084), indicating hydrophilicity. 

The percentages of essential amino acids show that all species contain higher amounts of leucine and valine compared to other essential amino acids.

Fig. 1: Percentages of essential amino acids of HMG-CoA reductase of human and 11 other species.

Protein secondary structure prediction

There remains a close relationship between protein structure and function, so secondary structure analysis is a necessity for understanding protein function (Mamun et al., 2024). Predicting the secondary structure of proteins can also help predict the tertiary structure by minimizing the gap between the primary sequence and the tertiary structure (Zhang et al., 2018). The secondary structure implies whether the given amino acids lie in a helix, strand, or coil. Secondary structural features analyzed by SOPMA (Geourjon & Deleage, 1995) and PHD server (Rost et al., 1994) are shown in Table 2. 

Motif analysis

Motifs are a set of conserved amino acid sequences that provide information about function. Motifs also provide information and help to identify the binding sites (Bailey et al., 2006). Motifs predicted using MEME (Bailey et al., 2006) and MAST (Bailey & Gribskov, 1998) showed the distribution of 10 conserved motifs among these HMG-CoA reductase protein sequences. The widths of those predicted 10 motifs range from 21 to 50 amino acids. Pfam (Mistry et al., 2021) analysis ensures that most of the predicted motifs are associated with the HMG-CoA reductase family (Table 3). 

Fig. 3: Phylogenetic tree of the HMG-CoA reductase sequence of human and 11 other species.

Predicting the subcellular location of proteins 

Understanding the subcellular location of proteins is essential for genome analysis and determining protein function. The position of a protein within a cell is known as subcellular location, which may be the cytoplasm, periplasm, extracellular space, outer membrane, or inner membrane (Mamun et al., 2024). Depicting the protein as a target for a drug or vaccine is the significance of the localization study. Proteins found in the cytoplasm and surface membranes can be utilized as drug targets and vaccine targets, respectively (Barh et al., 2011). Subcellular locali-zation analysis suggested that HMGRs are mostly found in the cytoplasm and endoplasmic reticulum across a variety of species. In addition to intracellular localizations, B. leterosporus and V. alginolyticus showed minor localization of these proteins to the extracellular space, determined by CELLO (Yu et al., 2004). These results suggest that cytoplasmic and extracellular HMG-CoA reductase proteins could serve as promising targets for drug and vaccine development. 

Fig. 4: Predicted motif of HMG-CoA reductase sequences by MAST.

Tertiary structure prediction 

In this study, the three-dimensional (3D) structures of HMG-CoA reductase (HMGR) proteins from various species were predicted using SWISS-MODEL (Arnold et al., 2006), an automated server for comparative protein modeling. SWISS-MODEL demonstrates reliable performance when the sequence identity between the target and template exceeds 30% (Arnold et al., 2006). High-confidence models were generated for Drosophila melanogaster II (NP_732900.1) and Homo sapiens (NP_001124468.1), supported by template identities greater than 60% (see Table 4). 

Table 3: Showing protein family of conserved motifs determined by Pfam analysis.

Other HMGR proteins - D. melanogaster I (AAF-56175.1), P. fargesii (AEL30660.1), Catharanthus roseus (AAA33108.1), Trypanosoma grayi (XP_-009313205), Leishmania donovani (AF054499.1), and Aspergillus oryzae 100-8 (KDE78541.1) - showed template identities near 50%, enabling the construction of reliable models. Additionally, acceptable structures were obtained for Brevibacillus laterosporus (WP_-022584705.1), Haloterrigena turkmenica DSM 5511 (YP_003402108.1), Encephalitozoon cuniculi GB-M1 (CAD25893.2), and Vibrio alginolyticus (WP_-017820181.1), with template identities exceeding the 30% threshold.

Table 4: Percentages of sequence identity, resolution, and E-value of HMG CoA-reductase protein sequences.

The predicted 3D models were visualized using PyMOL software (DeLano, 2002). Structural comparison revealed that while the overall 3D architectures were not identical, they exhibited notable similarities in general shape and domain organization. Fig. 5 presents the modeled structures, where helices, sheets, and loops are highlighted in blue, red, and violet, respectively.

Quality assessment of the model

Quality assessment and validation of proteins were done by several quality assessment steps. Accuracy and quality of the 3D model were assessed with PROCHECK (Laskowski et al., 1996) by Rama-chandran plot analysis. It was found from the analysis that most of the residues of the three-dimensional models belonged to the most favored regions, ranging from 83-89% (shown in Table 5, Fig. 6). 

Fig. 5: Predicted 3D structures of HMG-CoA reductase proteins. A= D. melanogaster-I, B= D. melanogaster-II, C= H. sapiens, D= P. fargesii, E= C. roseus, F= T. grayi, G= L. donovani, H= B. leterosporus, I= V. alginolyticus, J= E. cuniculi, K= A. oryzae 100-8, L= H. turkmenica DSM 5511.

Fig. 6: Ramachandran plot of HMG-CoA reductase protein of D. melanogaster generated by PROCHECK.

Table 6: Percentages of Verify 3D and ERRAT overall quality factor of HMG-CoA reductase protein models.

In this study, the amino acid sequences were retrieved and saved in FASTA format from the NCBI database. Sequence analysis showed that the HMG-CoA reductase of D. melanogaster I, D. Melanogaster II, H. sapiens, P. fargesii, C. roseus, T. grayi, L. donovani, B. leterosporus, V. alginolyticus, E. cuniculi GB-M1, A. oryzae 100-8, and H. turkmenica DSM 5511 consisted of amino acids 920, 920, 835, 575, 601, 435, 434, 432, 420, 398, 1044, and 408 amino acids, respectively. Analysis of the instability index (Guruprasad et al., 1990) indicated that most of the evaluated proteins were unstable, except proteins from humans, fruit flies, and plants, which showed values below the threshold of 40. In this in silico analysis, aliphatic indices were calculated to assess the structural stability of the selected enzyme. The results showed that the aliphatic index (Ikai, 1980) of the protein sequences ranged from 87.66 to 97.27, suggesting the stability of these enzymes across a wide range of temperatures. Positive GRAVY (Kyte & Doolittle, 1982) values indicated the hydrophobic nature of the protein from different species, with an exception in B. leterosporus (−0.013), E. cuniculi (−0.108), and H. turkmenica DSM 5511 (−0.084). Overall, the computational analysis suggested that HMG-CoA reductase proteins from D. melanogaster, P. fargesii, and C. roseus share strong structural and physicochemical similarities with the human enzyme.

Essential amino acids, particularly leucine and valine, are known to play a crucial role in reducing the synthesis of cholesterol (Adhikari et al., 2013). By lowering serum cholesterol, the essential amino acids leucine and valine may help in reducing the risk of atherosclerosis (Cojocaru et al., 2010). In this study, the high level of leucine and valine in every species suggested that these enzymes could serve as potential sources of HMG-CoA reductase for reducing the human blood cholesterol levels. In the case of secondary structure analysis, joint prediction with SOPMA and a neural network method (PHD) correctly predicts secondary structure with 82.2% accuracy (Rost et al., 1994). Both prediction servers indicated that α-helices were the predominant structural elements, followed by random coils and extended strands. 

Multiple sequence alignment of HMG-CoA reductases from different species indicated that they likely originated from a common ancestral gene. A motif is a sequence pattern that occurs repeatedly in a group of related protein or DNA sequences. It may also have a role in the development of the protein's binding sites (Sanchita et al., A motif analysis by MEME (Bailey et al., 2006) and the MAST server (Bailey & Gribskov, 1998) indicated the uniformity in the conserved sequences of all the species. Proteins found in the cytoplasm and surface membranes can act as potential drug or vaccine targets (Barh et al., 2011). Subcellular localization analysis using PSORT-b (Gardy et al., 2003), WoLF PSORT (Horton et al., 2007), and CELLO (Yu et al., 2004) suggested that most of the proteins were cytoplasmic and could serve as promising drug target candidates. To predict the three-dimensional structure of HMG-CoA reductase protein for fruit flies, humans, plants, protists, bacteria, archaea, and fungi by homology modelling, appro-priate templates were selected by subjecting the sequences of proteins to BLASTp against the PDB database, considering several parameters like query coverage, lower resolution, lowest E-value, and above 30% sequence identity. SWISS-MODEL server (Arnold et al., 2006) provided suitable templates, and all sequences were found to have identity values above 30%, suggesting their suitability for reliable 3D modeling. 

Model validation using PROCHECK (Laskowski et al., 1996) demonstrated that most species had 85% to 89.9% of residues in the most favored regions of the Ramachandran plot (Spencer et al., 2019). These findings displayed a higher percentage of residues occupying the favorable regions within the plot, signifying good stereochemical quality and structural reliability. No species in the experimental sequences exceeds the value of most favored regions above 90%. For the quality of the protein model to be considered satisfactory, it is expected to have a Verify3D score greater than 80% (Khor et al., 2014). In this study, for most species, a value of more than 80% indicates that at least 80% of the amino acids have scored > 0.2 in the 3D/1D profile, which is considered passed, suggesting that most protein model quality in this analysis is satisfactory. ERRAT (Colovos & Yeates, 1993) predicted an overall quality factor value above 80 for most of the protein, which indicates the high reliability of the predicted protein model (Colovos & Yeates, 1993). But according to Messaoudi (Messaoudi et al., 2011), a generally acceptable model range is >50 for a high-quality model. It is found from analysis by ERRAT that, overall quality factor value for all the species is >60, with a value of H. sapiens, along with D. melanogaster I, D. melanogaster II, P. forgesii, C. roseus, T. grayi, L. donovani, and H. turkmenica DSM 5511 (Table 5), above 80. The overall quality factor obtained through ERRAT indicated a high-quality protein model. 

This study successfully performed a comprehensive in silico characterization and comparative analysis of HMG-CoA reductase (HMGR) enzymes from twelve diverse species to investigate their properties, subcellular localization, functional motifs, and phy-logenetic relationships using various bioinformatics tools and servers. Additionally, this study aimed to construct a 3D model of the HMG-CoA reductase enzyme, as understanding its three-dimensional structure is crucial for gaining insights into its functional characteristics. The findings provide com-prehensive information on the molecular properties, architecture, and functional roles of the HMG-CoA reductase enzyme. The results suggest that HMG-CoA reductase enzymes from all the studied species may serve as potential sources for developing targeted cholesterol-lowering drugs in humans. 

R: Conducted data collection, performed bioinfor-matics analyses, and prepared the initial draft of the manuscript. M.M.R.: Supervised methodological design, guided phylogenetic and motif analyses, and critically reviewed and revised the manuscript for important intellectual content. S.M.: Conceived and designed the research, interpreted the results, and finalized the manuscript for submission and publication. All authors read and approved the final version of the manuscript. 

The authors gratefully acknowledge Mr. Utpal Kumar Adhikari of the School of Medicine, Western Sydney University, Australia, for his kind cooperation during this research.

The authors declare that there is no conflict of interest.