In silico bioprospecting of receptors for Oligoventin: an antimicrobial peptide isolated from spider eggs of Phoneutria nigriventer

doi:10.21203/rs.3.rs-4013832/v1

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Research Article

In silico bioprospecting of receptors for Oligoventin: an antimicrobial peptide isolated from spider eggs of Phoneutria nigriventer

https://doi.org/10.21203/rs.3.rs-4013832/v1

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Background

Irresponsible and wholesale use of antimicrobial agents is the principal cause of the emergence of strains of resistant microorganisms to traditional drugs. Oligoventin is a neutral peptide isolated from spider eggs of Phoneutria nigriventer, with antimicrobial activity against Gram-positive, Gram-negative, and yeast organisms. However, the molecular target and pathways of antimicrobial activity are still unknown. Thus, the aim of the present study is to prospect receptors associated with the antimicrobial activity of Oligoventin using in silico tools.

Methods

The PharmMapper server was used to prospect targets originating from microorganisms. Additionally, the PatchDock server was utilized to perform molecular docking between Oligoventin and the targets. Subsequently, the I-TASSER server was adopted to predict the ligand site. Finally, the docking results and predicted sites were compared with literature sites of each target.

Results

Twenty-two potential receptors for Oligoventin were identified. Among these, Enoyl-ACP reductase (Id_pdb1lxc) and Thymidylate synthase ThyX (Id_pdb 1O28) demonstrated superior interaction with the peptide, exhibiting co-localization between docked residues and literature sites. These enzymes play a crucial role in fatty acid and DNA biosynthesis in prokaryotes

Conclusion

Therefore, in silico results suggest that Oligoventin can impair fatty acid and DNA synthesis, thereby reducing microbial proliferation and causing microorganism death.

Bioinformatics

Applied Biochemistry

Computational Biology

Molecular Docking Simulation

Protein Domains

DNA Metabolism Enzymes

Bacteria are unicellular organisms with an unstructured nucleus, known as prokaryotes. They are closely associated with human activities. In general, this association is beneficial to humanity (1). However, it can also be a disharmonious relationship, with parasitism being the main cause of disease (2–4). Thus, microorganisms are also associated with impairments in agriculture, the food industry, and public health as: Salmonella typhi (5), Streptococcus pyogenes (6) and Mycobacterium tuberculosis (7).

The emergence of microorganisms resistant to traditional drugs is increasing each year, primarily due to the irresponsible and widespread use of antimicrobial agents, coupled with the high mutational capacity of certain bacterial strains. Studies indicate that multidrug-resistant organisms may lead to the deaths of 10 million people per year by 2050, making it the leading cause of mortality in humans and resulting in an estimated expenditure of over $100 trillion on public health systems worldwide (8, 9).

The development of new antimicrobial drugs is crucial in mitigating the impact caused by resistant organisms. Peptides or peptidic-derived biomolecules, which are amino acid polymers, offer an alternative to combating resistant organisms. Once these molecules are associated with antimicrobial activity, they exhibit a high capacity for analog production (10, 11).

Oligoventin (COOH-QPFSLERW-NH₂) is a neutral and amphiphilic peptide isolated from spider eggs of Phoneutria nigriventer. This molecule exhibits antimicrobial activity against Gram-positive bacteria (Micococcus luteus, Staphylococcus aureus, and Staphylococcus epidermidis) with minimal inhibitory concentrations (MIC) ranging from 47.2 to 188.9 µM (12). Additionally, it demonstrates activity against Gram-negative strains (Serratia marcescens) with MIC ranging from 25.7 to 47.2 µM (12, 13). Furthermore, it displays antifungal activity against Candida albicans and Candida auris, with MIC lower than 1 mM. However, the molecular target and mechanism of action of this peptide remain unknown.

Computational tools are currently utilized for simulating biological and physicochemical phenomena. These tools are commonly used in protein chemistry, enabling the evaluation of molecular three-dimensional structure, folding, interactions, docking, and dynamics (14–17). In silico methods offer the principal advantage of reducing the time and cost associated with screening assays.

Therefore, the aim of this study was to prospect receptors associated with the antimicrobial activity of the Oligoventin peptide using bioinformatics tools (in silico).

Peptide Characterization and Folding

To determine the physicochemical parameters of the peptide (net charge, hydrophobicity, hydrophobic moment, and molecular weight), the amino acid sequence of Oligoventin (COOH-QPFSLERW-NH₂) was submitted to the Heliquest server (18). The three-dimensional structure and free energy minimization were performed using UCSF Chimera software (19) with the following settings: 1000 steps of steepest descent, steepest descent step size of 0.02 Å, 10 steps of conjugate gradient, conjugate gradient step size of 0.02 Å, update interval of 10, and no fixed atoms after hydrogen addition, hydrogen bond addition, charges, and side-chain torsion (using the amber force field ff14SB).

Targets Prospection

The PharmMapper server was utilized to identify potential receptors for Oligoventin (20). The Oligoventin structure was submitted to the server with the following parameters: Generate Conformers (YES), Maximum Generated Conformations (300), and full/complete pharmacophore mapping with all Targets selected (v2010, 7302), and a number of Reserved Matched Targets (300). The top 50 best-ranked targets based on normalized fit score were chosen, and further filtered by microbial origin (Gram-positive or Gram-negative). Consequently, 22 targets were selected for this study, and the structure of each target was downloaded from the Protein Data Bank (PDB) server.

Molecular Docking

The PatchDock server was employed to conduct molecular docking between Oligoventin (ligand) and all 22 targets identified in PharmMapper (receptors) (21). PatchDock server parameters were set to Clustering RMSD (4.0) and Complex Type (Default). For each receptor, the best solution (conformation) was determined by collecting Score, Area, ACE (effective atomic contact energies), and transformation value. Ultimately, the highest score value was used to assess the optimal binding of Oligoventin.

Ligand and Receptor interaction

The software UCSF Chimera was utilized to analyze the interaction between Oligoventin and the receptors (22). The FindHBond tool was configured with relaxed constraints (2 Å and 20 degrees) to identify hydrogen bonds. Only hydrogen atoms with a distance of less than 4 Å between their heavy atoms were considered in this study. Additionally, information regarding electron donor/acceptor and residue interactions between the ligand and receptor was collected.

Ligand binding site prediction

The I-TASSER (protein function & function prediction) server was employed to identify binding sites for receptors (23). In this study, only the top 6 receptors (based on major docking scores) were selected for analysis. For polymeric proteins, only one chain was used for this analysis. Subsequently, the predicted binding sites were compared with those found by docking analysis to assess the accuracy of receptor selection.

Peptide characterization

Oligoventin (COOH-QPFSLERW-NH2) is a neutral peptide with a net charge of 0, comprising 8 amino acids with a molecular weight of 1062.18 g/mol and an isoelectric point of pH 6.58. This peptide consists of half hydrophilic and half hydrophobic residues, with two of them being aromatic, resulting in an extinction coefficient of 5690 M^− 1 cm^− 1, indicating good water solubility. Additionally, in silico energy minimization of the peptide structure yielded − 852.55 kJ/mol. This molecule was utilized to perform simulations in this study.

Targets Prospection

After performing the initial search on the PharmMapper server, 300 potential receptors were identified (Table S1). These were filtered by their origin from microorganisms (Gram-positive or Gram-negative), resulting in 22 targets with normalized fit scores ranging from 0.9912 to 0.9313 (Table 1).

The top three receptors based on their score are Urocanate hydratase (1W1U), Aspartate aminotransferase (1TOI), and Copper-containing nitrite reductase (1RZP), ranked as 3, 4, and 9, respectively, in the general rank. Conversely, the receptors with the lowest fit scores are A/G-specific adenine glycosylase (1WEI), 2-C-methyl-D-erythritol 2,4-cyclodiphosphate synthase (1U3L), and DNA protection during starvation protein 2 (1JI5), ranked as 50, 47, and 42, respectively, in the general rank (Table 1).

Table 1

PharmMapper search results using Oligoventin as a ligand
PM Rank	PDB ID	Target Name	Normalized Fit Score	Origin	Gram
3	1W1U	Urocanate hydratase	0.9912	Pseudomonas putida	-
4	1TOI	Aspartate aminotransferase	0.9903	Escherichia coli	-
9	1RZP	Copper-containing nitrite reductase	0.9817	Achromobacter cycloclastes	-
10	1SFJ	3-dehydroquinate dehydratase	0.9811	Staphylococcus aureus subsp. aureus MRSA252	+
14	1UDX	Hypothetical protein	0.9732	Thermus thermophilus HB8	-
15	1KSS	Fumarate reductase flavoprotein subunit	0.9723	Shewanella frigidimarina	-
16	1O28	Thymidylate synthase thyX	0.9698	Thermotoga maritima	-
17	1LXC	Enoyl-ACP Reductase	0.9697	Escherichia coli	-
18	1M5W	Pyridoxine 5-phosphate synthase	0.9673	Escherichia coli	-
22	1B6G	Haloalkane dehalogenase	0.9617	Xanthobacter autotrophicus	-
24	1UFY	Chorismate mutase	0.9582	Thermus thermophilus HB8	-
27	1UXG	Malate dehydrogenase	0.9554	Chloroflexus aurantiacus	-
33	1VMA	Cell division protein FtsY	0.9463	Thermotoga maritima	-
34	1Y54	Beta-lactamase	0.946	Enterobacter cloacae	-
35	1BO5	Glycerol kinase	0.9446	Escherichia coli	-
37	1VMK	Purine nucleoside phosphorylase	0.9418	Thermotoga maritima MSB8	-
38	1UKQ	Cyclomaltodextrin glucanotransferase	0.9404	Bacillus sp. 1011	+
39	1TDJ	Threonine dehydratase biosynthetic	0.9403	Escherichia coli	-
40	2PIL	Fimbrial protein	0.9402	Neisseria gonorrhoeae	-
42	1JI5	DNA protection during starvation protein 2	0.9386	Bacillus anthracis	+
47	1U3L	2-C-methyl-D-erythritol 2,4-cyclodiphosphate synthase	0.9339	Escherichia coli	-
50	1WEI	A/G-specific adenine glycosylase	0.9313	Escherichia coli	-

PM Rank (General PharmMapper rank search), PDB ID (Identification code in protein data bank), Normalized Fit Score (value obtained by ratio of fit score and number of features), Origin (Specie form the target was isolated), + (Gram-positive), - (Gram-Negative).

Molecular docking results

Docking results showed a range of scores (10982 to 5308), areas (1493.9 to 679.9), and ACE values (289.21 to -290.26). The rankings obtained from the PatchDock server differed from those presented by PharmMapper. The complete results are provided in Table S2.

In the molecular docking analysis, Thymidylate synthase ThyX (Id_pdb 1O28), Pyridoxine 5-phosphate synthase (Id_pdb 1M5W), Threonine dehydratase biosynthetic (Id_pdb 1TDJ), Enoyl-ACP reductase (Id_pdb 1LXC), Fumarate reductase flavoprotein subunit (1KSS), and Cyclomaltodextrin glucanotransferase (Id_pdb 1UKQ) exhibited top dock scores. Additionally, these targets showed similar interaction areas, ranging from 1492.9 to 881.2. However, targets 1TDJ (-2.33), 1LXC (-290.26), and 1KSS (-218.38) presented negative values for ACE (Table 2).

In contrast, targets with lower dock scores included Fimbrial protein (Id_pdb 2PIL), Haloalkane dehalogenase (Id_pdb 1B6G), Chorismate mutase (Id_pdb 1UFY), and 2-C-methyl-D-erythritol 2,4-cyclodiphosphate synthase (Id_pdb 1U3L). All of these targets exhibited interaction areas less than 800 and positive values of ACE (Table 2).

Table 2

Docking results by PatchDock server. Oligoventin was used as ligand, and target obtained by PharmMapper was used as receptor.
PM Rank	PDB ID	Receptor Name	Score	Area (Å²)	ACE (Kcal/mol)
16	1O28	Thymidylate synthase thyX	10982	1493.9	289.21
18	1M5W	Pyridoxine 5-phosphate synthase	8982	999.2	255.89
39	1TDJ	Threonine dehydratase biosynthetic	8046	1072.1	-2.33
17	1LXC	Enoyl-ACP reductase	7904	1105.1	-290.26
15	1KSS	Fumarate reductase flavoprotein subunit	7776	1238.1	-218.38
38	1UKQ	Cyclomaltodextrin glucanotransferase	7698	881.2	114.28
35	1BO5	Glycerol kinase	7640	1067	139.05
37	1VMK	Purine nucleoside phosphorylase	7438	882.5	276.17
9	1RZP	Copper-containing nitrite reductase	7286	837.6	5.66
27	1UXG	Malate dehydrogenase	7258	921.8	-126.08
14	1UDX	Hypothetical protein	7128	930.3	-195.07
4	1TOI	Aspartate aminotransferase	6996	886.1	-136.05
34	1Y54	Beta-lactamase	6982	928.4	43.77
3	1W1U	Urocanate hydratase	6824	1033.1	210.99
50	1WEI	A/G-specific adenine glycosylase	6782	858.6	-24.09
33	1VMA	Cell division protein FtsY	6614	792.9	184.82
42	1JI5	DNA protection during starvation protein 2	6398	798.2	248.52
10	1SFJ	3-dehydroquinate dehydratase	6374	765.8	-73.11
47	1U3L	2-C-methyl-D-erythritol 2,4-cyclodiphosphate synthase	6068	661.8	99.21
24	1UFY	Chorismate mutase	5696	721.1	108.96
22	1B6G	Haloalkane dehalogenase	5566	770.8	102.31
40	2PIL	Fimbrial protein	5308	697.9	28.03

PM Rank (General PharmMapper rank search), PDB ID (Identification code in protein data bank), ACE (Atomic efective contact energy - Kcal/mol)

Receptor and ligand binding analysis

To simplify the analysis, only hydrogen bonds (≤ 4Å) were considered in the docking results, and the entire binding interactions are summarized in Table S3. In all interactions observed, Oligoventin acted as the electron donor, while the receptor served as the acceptor. No association was found between the number of hydrogen bonds and the dock score.

Thymidylate synthase ThyX (4 bonds) exhibited interactions among HIS5.L -> Thr_101.RB, Gln1.L -> Glu_58RA / Thr_161.RB, and Arg_7.L -> Glu_54.RA. Pyridoxine 5-phosphate synthase and Threonine dehydratase biosynthetic showed 1 bond each, with receptor Gln_1.L -> Glu_240.RD and Gln_1.L -> Glu_324.R, respectively. Finally, Enoyl-ACP reductase (3 bonds) demonstrated interactions among Gln_1.L -> Gly_13.RB / Ser_19.RB and Arg_7.L -> ILE_192.RB (Table 3)

Table 3

Hydrogens H-Bond (≤ 4Å) between receptor and Oligoventin obtained by a docking result of Patchdock Server
PM Rank	PDB ID	Receptor Name	Donor	Acceptor	D-A distance (Å)
16	1O28	Thymidylate synthase thyX	HIS 5.L NE2 GLN 1.L NE2 GLN 1.L NE2 ARG 7.L NH2	THR 101.R_B O GLU 58.R_A O THR 161.R_B O GLU 54.R_A OE2	3.717 3.850 3.875 3.426
18	1M5W	Pyridoxine 5-phosphate synthase	GLN 1.L N	GLU 240.R_D OE2	2.394
39	1TDJ	Threonine dehydratase biosynthetic	GLN 1.L N	GLU 324.R OE2	2.669
17	1LXC	Enoyl-ACP Reductase	GLN 1.L N GLN 1.L N ARG 7.L NE	GLY 13.R_B O SER 19.R_B OG ILE 192.R_B O	3.964 2.872 3.705
15	1KSS	Fumarate reductase flavoprotein subunit	N/B	N/B	N/B
38	1UKQ	Cyclomaltodextrin glucanotransferase	GLN 1.L NE2 GLN 1.L NE2 ARG 7.L NE ARG 7.L NH2	TYR 406.R_B O GLY 502.R_B O THR 409.R_B O THR 409.R_B O	3.764 2.401 3.795 3.574
35	1BO5	Glycerol kinase	PHE 3.L N	THR 14.R_A OG1	3.528
37	1VMK	Purine nucleoside phosphorylase	GLN 1.L NE2	ARG 140.R_C O	3.195
9	1RZP	Copper-containing nitrite reductase	N/B	N/B	N/B
27	1UXG	Malate dehydrogenase	GLN 1.L N	GLY 79.R_B O	3.810
14	1UDX	Hypothetical protein	ARG 7.L NH1	ALA 368.R O	3.872
4	1TOI	Aspartate aminotransferase	GLN 1.L N ARG 7.L NH2	THR 59.R O TYR 288.R O	2.486 3.441
34	1Y54	Beta-lactamase	GLN 1.L N SER 4.L OG ARG 7.L NH2	SER 310.R OG SER 281.R OG ASP 280.R OD1	2.763 3.649 3.244
3	1W1U	Urocanate hydratase	SER 4.L OG ARG 7.L NH2	ASN 6.R_A OD1 ASN 6.R_A OD1	2.263 3.908
50	1WEI	A/G-specific adenine glycosylase	ARG 7.L NH2	GLN 33.R OE1	3.238
33	1VMA	Cell division protein FtsY	SER 4.L N ARG 7.L NH1 ARG 7.L NH2	GLN 1.L O ASN 80.R_B O ASN 80.R_B O	2.847 3.423 3.93
42	1JI5	DNA protection during starvation protein 2	GLN 1.L N	PHE 36.RA O	3.504
10	1SFJ	3-dehydroquinate dehydratase	ARG 7.L NH2	TYR 15.R_B OH	2.327
47	1U3L	2-C-methyl-D-erythritol 2,4-cyclodiphosphate synthase	GLN 1.L N ARG 7.L NH2	ASP 55.R OD2 ASP 38.R OD1	3.453 3.435
24	1UFY	Chorismate mutase	N/B	N/B	N/B
22	1B6G	Haloalkane dehalogenase	ARG 7.L NH2	GLN 181.R O	3.858
40	2PIL	Fimbrial protein	GLN 1.L N ARG 7.L NE	TRP 111.R O ASP 145.R OD1	1.641 3.806

Donor (Electron donor residue), Acceptor (Electron acceptor residue), D-A distance (distance between heavy atoms of electron acceptor and donor), GLY 1.L N (Residue name/ Number/ Chain ID/ Shared electron atom), L (Ligand ID), Rx (ReceptorSubunit ID)

Receptor and ligand binding analysis

Ligand binding site predictions were conducted for the six receptors with the highest dock scores. The major C-Scores are presented in Table 4, while all ligand site predictions can be found in Table S4.

Receptors 1O28 (Score = 0.42; Size = 45), 1M5W (Score = 0.93; Size = 141), 1TDJ (Score = 0.97; Size = 200), 1KSS (Score = 0.88; Size = 128), and 1UKQ (Score = 0.86; Size = 108) did not exhibit co-location between predicted and docked residues. Only receptor 1LXC (Score = 0.86; Size = 702) shared residues between both models. The co-localized residues were 13, 19, 91, 192, and 194 (Table 4 and Figs. 1–2).

Table 4

Bind site co-location among predicted (I-TASSER), found in study (PatchDock) and literature descripted. Only one protein chain was used in this analysis. In **bold** residue shared for bind site models.
PM Rank	PDB ID	Cluster Score	Cluster size	Ligand bind site residues (Prediction)	Ligand bind site residues (Found)
16	1O28	0.42	45	42, 65, 67, 70, 93, 175, 177	39,40, 54ra,54ra, 163ra, 163rc, 165ra, 165rc, 169rc, 172rc 211ra, 211rc, 211rc
18	1M5W	0.93	141	72, 94, 133, 153, 192, 193, 194, 213, 214, 215, 216	228ra, 228ra, 235rf, 236rf, 236rg, 236rg, 240rd,
39	1TDJ	0.97	200	60, 61, 62, 87, 88, 89, 90, 157, 186, 188, 189, 190, 191, 192, 241, 242, 286, 288, 315, 316	320r, 320r, 321r, 323r, 324r, 458r, 461r
17	1LXC	0.86	704	13, 15, 16, 19, 20, 39, 40, 41, 63, 64, 65, 91, 92, 93, 94, 119, 144, 145, 146, 159, 163, 189, 190, 191, 192, 194, 195, 196, 197	13rb, 19rb, 91rb(2), 97rb, 192rb, 194rb(3)
15	1KSS	0.88	128	132, 133, 134, 135, 136, 137, 156, 157, 158, 162, 163, 164, 165, 167, 168, 169, 170, 171, 276, 277, 278, 312, 313, 314, 336, 337, 338, 344, 375, 504, 505, 533, 534, 544, 547, 548, 549, 550, 553	44r, 52r, 53r(2), 74r, 423r, 426r
38	1UKQ	0.68	108	100, 140, 194, 197, 227, 229, 230, 257, 327, 328	311rb(2), 406rb(2), 409rb(2), 424rb, 502rb, 576rb,

Cluster Score (confidence score of the prediction, ranges [0–1]), Cluster size (total number of templates in a cluster).

The principal molecular pathways of antimicrobial molecules involve the impairment of protein, lipid, cell wall, genetic material synthesis, and membrane injury (24). Cationic amphiphilic peptides primarily exert their action mechanism through membrane interaction and disruption (25, 26). This occurs due to their physicochemical properties; the positively charged peptide is attracted to the negatively charged bacterial plasma membrane (27). Subsequently, its amphiphilic characteristics enable the peptide to embed into the bacterial membrane, forming toroidal pores, barrel-stave pores, or carpet-like structures, leading to electrolytic imbalance and ultimately cell death (28–30). However, this mechanism is not specific, and cationic peptides are potentially cytotoxic (31).

However, some peptides interact with intracellular targets, inhibiting protein (e.g., Pleurocidin, Apidaecin Hb1a), lipid (e.g., Mersacidin, MBI-28), and DNA (e.g., Buforin II, Ostricacin-1) biosynthesis, thereby harming microbial development (24). The Heliquest results showed that Oligoventin is a neutral and hydrophilic peptide. Furthermore, experimental assays demonstrated that this peptide does not exhibit cytotoxicity against fresh human blood cells at a concentration of 500µM (32). Both results suggest that the antimicrobial activity of Oligoventin is associated with intracellular pathways, interfering with bacterial homeostasis.

PharmMapper is an online reverse docking tool that identifies targets using a mapping approach. After conducting the necessary methodology, 22 potential receptors for Oligoventin originating from both Gram-positive and Gram-negative microorganisms were identified. Subsequently, molecular docking was performed using PatchDock, revealing the best targets as thymidylate synthase ThyX (Id_pdb 1O28), pyridoxine 5-phosphate synthase (Id_pdb 1M5W), threonine dehydratase biosynthetic (Id_pdb 1TDJ), enoyl-ACP reductase (Id_pdb 1LXC), fumarate reductase flavoprotein subunit (Id_pdb 1KSS), and cyclomaltodextrin glucanotransferase (Id_pdb 1UKQ).

Moreover, only receptors 1LXC and 1TDJ exhibited negative ACE values, suggesting thermodynamically favorable interactions between Oligoventin and these receptors (33, 34). Notably, only enoyl-ACP reductase (Id_pdb 1LXC) showed co-localization between the docked and ligand site predicted by I-TASSER (Fig. 1–2).

Thymidylate synthase ThyX is an enzyme implicated in prokaryotic cell DNA synthesis, with two principal sites: the FAD⁺ cofactor site (Asn₁₆, Ser₃₀, Thr₅₅, His₇₉, Glu₈₆, and Arg₁₆₅) and the dUMP substrate site (Arg₇₈, Glu₈₆, Ser_88, Arg₉₀, Arg₁₄₇ and Arg₁₇₄,) (34–36). The dock simulation revealed co-localization with Arg₁₆₅, present in the FAD⁺ cofactor site. However, no residues were co-localized with the predicted site from the I-TASSER server (Table 4 and Fig. 2a – 2b). Despite this, this receptor was discarded as a potential molecular target for Oligoventin due to the positive ACE value, indicating that the interaction is thermodynamically unfavorable in vitro assays.

Pyridoxine 5-phosphate synthase is an enzyme associated with B6 vitamin synthesis, serving as an important cofactor in amino acid metabolism and glycogenolysis. This enzyme forms a complex with 1-deoxy-D-xylulose phosphate (dXP), involving residues such as Asp₁₁, His₁₂, Arg_20, His₅₂, Glu₇₂, Thr₁₀₃, Glu₁₅₃, and His₁₉₃ (37, 38). While the dock simulation did not reveal shared residues with the dXP site, the predicted model exhibited co-localization with Glu₁₅₃, Glu₇₂ and His₁₉₃ (Table 4 and Fig. 1a).

Threonine dehydratase biosynthetic is an important enzyme in the biosynthesis of the amino acid threonine in E. coli. This structure contains a Pyridoxal 5-phosphate (PLP) binding site composed of Phe₆₁, Lys₆₂, Asn₈₉, Gly₂₄₁ and Ser₃₁₅ (39, 40). Although the dock simulation did not reveal shared residues with PLP, all residues were shared with the predicted binding site (Table 4 and Fig. 1b).

Enoyl-ACP reductase is a key enzyme in the final step of type II fatty acid synthesis, specifically in the elongation phase. This molecule contains a cofactor binding site, with one binding site for NAD + comprising residues Ala₁₆, Ala₄₁, Leu₄₅, Asp₆₇, Val₆₈, Ile₉₅, and Ile₁₂₁ and another for the nicotinamide ring comprising Thr₁₄₇, Tyr₁₄₈, Ala₁₉₁, Gly₁₉₂, and Ile₁₉₄ (40–42). Both the dock simulation and predicted site revealed co-location with the residues Gly₁₉₂ and Ile₁₉₄, which are present in the nicotinamide ring binding site (Table 4 and Fig. 2c – 2d).

Fumarate reductase flavoprotein subunit is enzyme associated with bacteria respiration in oxygen absence, which are closely related to succinate dehydrogenase. This molecule has FAD⁺ cofactor site (Glu₅₃₄) and subtracts (His₅₀₄) (43, 44). Both residues not associated with Oligoventin in dock simulation results. In contrast, they are present in predicted binding site (Table 4 and Fig. 1c).

Cyclomaltodextrin glucanotransferase is enzyme associated to carbohydrates metabolism, important in cyclization of D-glucose. The substrate site is formed by Tyr₁₀₀, Phe₁₈₃, Tyr₁₉₅, Asp₂₂₉, Phe₂₅₉ and Asp₃₂₈ (45). Dock simulation not shows shared residues with substrate site, however Asp229 residues was shared with predicted bind site (Table 4 and Fig. 1d).

Therefore, molecular docking simulations suggest that Oligoventin interacts more strongly with Enoyl-ACP reductase (Id_pdb 1LXC) and with less avidity with Thymidylate synthase ThyX (Id_pdb 1O28), potentially disrupting the normal functions of these enzymes. This interaction could lead to a decrease in fatty acid and DNA biosynthesis, ultimately reducing microbial proliferation and impacting bacterial homeostasis.

The in silico bioprospecting of receptors for the antimicrobial activity of Oligoventin proved to be highly efficient, identifying only two targets from a database containing over seven thousand enzymes. The integration of software tools, including PharmMapper for target search, PatchDock for molecular docking, I-TASSER for ligand site prediction, and literature validation, was instrumental in validating each step of the analysis.

In this study, Enoyl-ACP reductase and Thymidylate synthase ThyX emerged as the most promising targets, showing consistent results across docking, prediction, and literature binding sites. These enzymes are associated with fatty acid and DNA synthesis in prokaryotic organisms. Thus, Oligoventin's interaction with these targets may disrupt their normal function by competing for cofactor or substrate binding sites, ultimately reducing microbial proliferation and leading to bacterial death, consistent with previous antibacterial in vitro assays.

This study paves the way for further research into the interaction between receptors and ligands using molecular dynamics (in silico) or enzymology assays (in vitro). Furthermore, it suggests the potential for designing new Oligoventin analogs to enhance antimicrobial efficacy and explore other biological potentials, such as antitumoral and anti-inflammatory properties.

Data and software availability

The physicochemical proprieties were determined via Heliquest server https://heliquest.ipmc.cnrs.fr/. Potential receptors were search using PharmMapper available in http://www.lilab-ecust.cn/pharmmapper/. Receptor sequence file was obtained from website protein data bank https://www.rcsb.org/. Molecular docking method was performed by PatchDock https://bioinfo3d.cs.tau.ac.il/PatchDock/. Ligand and receptor interaction, molecular presentation was building by free software UCSF chimera (version 1.16) https://www.cgl.ucsf.edu/chimera/. For prediction of ligand site, it was used I-TASSER (protein function & function prediction) server https://zhanggroup.org/I-TASSER/. All file used in this study are available in https://github.com/eliasseif/Oligoventin_prospecting.git.

Acknowledgments

We thank all the team of the Protein Chemistry Laboratory at the Laboratory for Applied Toxinology (LETA - Butantan Institute, Brazil) for the constant support and encouragement. Additionally, we thank the technicians Rosa Maria Carmo and Priscila do Nascimento Nanni.

Author Contributions:

Conceptualization, E.J.M.S. and P.I.S.J. ; methodology E.J.M.S. and P.I.S.J.; software, E.J.M.S. and P.I.S.J. ; validation, E.J.M.S. and P.I.S.J. ; formal analysis, E.J.M.S. and P.I.S.J. ; investigation, E.J.M.S. and P.I.S.J. ; resources, P.I.S.J. ; data curation, E.J.M.S. and P.I.S.J. ; writing-original draft preparation, E.J.M.S. ; writing, review and editing, E.J.M.S. and P.I.S.J. ; supervision, P.I.S.J. ; project administration, P.I.S.J.; funding acquisition, P.I.S.J. All authors have read and agreed to the published version of the manuscript.

Funding:

This research received financial support from the Research Support Foundation of the State of São Paulo (FAPESP/CeTICS), grant number 2013/07467-1, and from the Brazilian National Council for Scientific and Technological Development (CNPq), grant numbers 472744/2012-7 and 161722/2021-0.

Conflicts of Interest:

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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The authors declare no competing interests.

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In silico bioprospecting of receptors for Oligoventin: an antimicrobial peptide isolated from spider eggs of Phoneutria nigriventer

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Abstract

Background

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Introduction

Methods

Targets Prospection

Molecular Docking

Ligand and Receptor interaction

Ligand binding site prediction

Results

Targets Prospection

Molecular docking results

Receptor and ligand binding analysis

Receptor and ligand binding analysis

Discussion

Conclusion

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References

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