Binding Efficiency of Molecules from Medicinal Plants with Fidgetin Like Protein 2 – A Novel Target for Diabetic Foot Ulcer

 

R. Sathish Kumar1*, G. Kaavya2

1Assistant Professor, Department of Botany, PSG College of Arts and Science, Coimbatore.

2Department of Biochemistry, PSG College of Arts and Science, Coimbatore.

*Corresponding Author E-mail: sathishbioinf@gmail.com

 

ABSTRACT:

Diabetic foot ulcer (DFU) is one of the major complications for diabetes patients. DFU interrupts the normal steps involved in wound healing process and upto25% of diabetes patients develops DFU in India. At present situation, the treatment for DFU is mandatory. Perhaps bioactive compounds from medicinal plants might have an impact, therefore plants like Aloe vera, Coptis chinensis, Equisetum arvense, Paeonia suffruticosa,  Rehmannia glutinusaand Rheum palmatum has been screened for its binding efficiency with fidgetin like protein 2 (FLP2). Out of several compounds studies, α-D-glucopyranoside showed the least G.score value -7.91Kcal/mol. The compound is present in the plant Equisetum arvense, in future could be analyzed for treating DFU. The binding efficiency was studies using docking software, where the 3D of the protein was modeled using the online tool I-tasser. The protein sequence was retrieved from the UniProt database of ID: A6NMB9 and the quality of the modeled structure were determined from the Ramachandran plot generated from the SAVS (online server). In the present study the compound α-D-glucopyranoside (Equisetum arvense) had effective binding with the protein and least G.score value. Therefore further studies can be done in isolating the bioactive compounds from Equisetum arvensecould be carried out.

 

KEYWORDS: Fidgetin like protein 2, Molecular modeling, I-Tasser, Docking analysis, Equisetum arvense, α-D-glucopyranoside.

 


INTRODUCTION:

Diabetic foot ulcer is the major complication amongpatients of diabetes mellitus (DM)which leads a great impact in their life. In diabetic condition, the delay in wound healing process occurs, which further becomes more complicated for treatment and often leads to lower limb amputation. According to the study, 15% of more than 150 million cases suffer from diabetic foot ulcer1. It is estimated that more than 360 million people will have diabetes mellitus further leading to DFU, whereas in India, it is about 25% of diabetes patients are suffering from DFU2.

DFU has been increasing year by year and considered as the major cause for hospitalization of the patients with DM3, which is expected to occur due to impaired glucose control foot deformity. Blisters appear in numb area. In fact, diabetic foot ulcer can lead to infection, amputation or even death if it is left untreated. On the other hand, once DFU occurs there is a chance for ulcer progression. And it is also responsible for emotional and physical stresses. Risk factors implicated in the development of diabetic foot ulcers are diabetic neuropathy, peripheral vascular disease, cigarette smoking, poor glycemic control, previous foot ulcerations or amputations, diabetic nephropathy, and ischemia of small and large blood vessels4. The etiology and management criteria to eradicate DFU from India and all over the world have been effectively explained by Yazdanpanah et al.2 The most common pathway to develop foot problems is peripheral sensory-motor and autonomic neuropathy which leads to high foot pressure, foot deformities and gait instability, which increases the risk of developing ulcers5. The consequences of neuropathies, ischaemia, distal sensory neuropathy are explained and the antibiotic regimen are described5. The treatment measures for DFU is highly complicated, since the prolonged course of antibiotics result in resistance as well as it is unrealistic for patients to keep immobilizing the foot which might incite the risk of thrombosis, muscle wasting, depression and secondary ulceration5. The preventive measure both primary and secondary are stated, where the former includes managing diabetes, the latter includes taking good care on foot-ulcer, however, the menace of recurrence rate is high6.

 

Therefore, the need of the hour is to find an effective drug for DFU, which is appreciable, if it is from natural source. India, being known as the land of Ayurveda, is rich in medicinal plants, hence sticking to the traditional means of treatment would be more convenient due to its cost effectiveness and ready availability with less means of side effects7. The present study selected the plants like Aloe vera8, Coptis chinensis9, Equisetum arvense10, Paeonia suffruticosa11, Rehmannia glutinusa12and Rheum palmatum13on the basis of articles and literature, which are already reported for its efficiency for skin diseases. The plants chosen in the study are also reported for anti- inflammatory, anti-diabetic, anti- ulcer, anti-viral and anti- fungal properties. The chemical compounds of these selected plants are focused for its binding efficiency with fidget in like protein 2 (FLP2). FLP2 regulates the cell migration which acts microtubule (MT) severing and depolymerizing enzymes14. Charafeddineet al.15 reported the 2-fold increase in the rate of in vitro cell movement and in vivo wound closure which describes the localization of FLP2 in the region of cell cortex has suppressed the MT growth. In general, these MTs posses an important role in wound healing evidenced in controlling and coordinating the parameters involve in the cell movement16,17. The present era is technical and every steps in life includes the application of computer and even in the study of biology bioinformatics helps in a progressive way to predict the protein structure, genome sequencing, drug discovery and also helps in target identification18. Thus utilizing bioinformatics resources, the present study screen the binding efficiency of plant compounds with FLP2 proteins.

 

MATERIALS AND METHODS:

The 3D structure of FLP2 was not crystallized and deposited in the PDB; hence the structure was modeled using I-TASSER online tool (zhanglab.ccmb.med. umich.edu/I-TASSAR/)19. At first, the sequence of fidget in like protein 2 was retrieved in fasta format from SwissProt database of Accession number A6NMB920 (http//www.uniprot.org/uniprot/ A6NMB9) (Fig. 1). The BLAST search for finding homology structure was carried out, since the sequence has no similarity with the proteins in PDB databank, the sequence was subjected for ab-initio modeling. The modeled structure was energy minimized and validated in SAVS online (http://nihserver.mbi.ucla.edu/SAVES/) 21 to predict the Ramachandran plot. Further, the active site pocket was found using Ligsite online tool (Table 1). The structure of the modeled protein was given in (Fig. 2).

 

The compound structures of the plants were downloaded from PubChem database. Finally, the docking analysis was carried out in Glide molecule of Schrödinger. The interactions of each ligand molecule with the target protein were observed in the PyMol viewer.

 

>sp|A6NMB9|FIGL2_HUMAN Putative fidgetin-like protein 2 OS=Homo sapiens GN=FIGNL2 PE=5 SV=2

MHWTPEHAQPLNQWPEQHLDVSSTTPSPAHKLELPPGGRQRCHYAWAHDDISALTASNLLKRYAEKYSGVLDSPYERPALGGYSDASFLNGAKGDPEPWPGPEPPYPLASLHEGLPGTKSGGGGGSGALGGSPVLAGNLPEPLYAGNACGGPSAAPEYAAGYGGGYLAPGYCAQTGAALPPPPPAALLQPPPPPGYGPSAPLYNYPAGGYAAQPGYGALPPPPGPPPAPYLTPGLPAPTPLPAPAPPTAYGFPTAAPGAESGLSLKRKAADEGPEGRYRKYAYEPAKAPVADGASYPAADNGECRGNGFRAKPPGAAEEASGKYGGGVPLKVLGSPVYGPQLEPFEKFPERAPAPRGGFAVPSGETPKGVDPGALELVTSKMVDCGPPVQWADVAGQGALKAALEEELVWPLLRPPAYPGSLRPPRTVLLFGPRGAGKALLGRCLATQLGATLLRLRGATLAAPGAAEGARLLQAAFAAA

RCRPPSVLLISELEALLPARDDGAAAGGALQVPLLACLDGGCGAGADGVLVVGTTSRPAALDEATRRRFSLRFYVALPDSPARGQILQRALAQQGCALSERELAALVQGTQGFSGGELGQLCQQAAAGAGLPGLQRPLSYKDLEAALAKVGPRASAKELDSFVEWDKMYGSGH

Fig.1: Sequence of fidgetin like protein 2

 

RESULT AND DISCUSSION:

The FLP2 protein was modeled using online tool I-tasser, which generated five models among first had C-score of -0.11, estimated TM score of 0.70±0.12 and estimated RMSD of 8.2±4.4Å. The C-score is said to be a confidence score calculated for estimating the quality of predicted models based on the significance of threading template alignments and the convergence parameters of the structure assembly simulations19.For FLP2, the templates are 4L15, 5FTJ, 3CF1, 3D8B and 5G4F. TM-score and RMSD are used for measuring structural similarity between two structures19. Further, the quality of the modeled structure was determined by the presence of amino acid residues in the Ramachandran Plot (Fig. 3). The binding site was analyzed using Ligsite which is shown in table 1. From the docking study, the G.score was observed for all the phytoconstituents of selected plants and the table 2 showed the number of hydrogen bonds formed, interacting residues and also its bond length. α-D-Glucopyranoside, a compound from E. arvense scored least Glide value of -7.91 Kcal/mol. The interactions were observed with the predicted active sites GLY386, ALA136 and ASN138 of bond length 2.3, 1.6 and 2.6 Å, respectively. Moreover, the compound was observed for its ADME-tox properties which indicated its drug like property. Followed by Gallic acid, a compound from P.suffruticosa scored least Glide value of -4.1 Kcal/mol. The compounds catechin and rehin had G.score of -3.41 and -3.6 Kcal/mol, respectively. Each had the number of hydrogen bonds as 4 and 6 with their respective bond length which are represented in the table 2. While the rest of the compounds protopine, fumariline, sanguinarine, anthocyanin and ethyl parabene had G.score in the range of -2 Kcal/mol and the interactions were observed as 1 or 2. The interactions involve active site residues like ALA136, ARG277, GLU275 and GLY386, where the residues ALA136 and GLU275 were often to form bonds with the plant compounds. The compounds α D-glucopyranoside, gallic acid and rehin had interactions with both ALA136 and GLU275. Though rehin has less G.score value compared to α D-glucopyranoside and gallic acid, it has interactions all with active site residues. So far none of the studies have concentrated on docking analysis of FLP2. The in vitro experimental analysis has indicated that inhibition of FLP2 resulted in the hair follicle formation and collagen deposition15. Moreover, treating FLP2 as therapeutic target would enhance the broader signaling milieu within the wound instead of providing the injured site with regenerative and proliferative agents15. The present study would serve as a basis for future perspective in developing drugs from plant based therapy especially in targeting FLP2 protein.

 

 

Fig 2: Modeled Structure of FLP2 protein

 

Table 1: Active Site Prediction for FLP2

Fidgetin like protein 2

VAL 134, LEU 135,  ALA 136,  LEU 167,  TYR 228,  GLU 275,  ARG 277,  PRO 340,  LYS 347, PHE 348, ASP 384, GLY 386.

 

Fig.2: Ramachandran Plot for the modeled FLP2 protein

 

Table 2: Interactions of Phytoconstituents with FLP2 Protein

S.

No.

Ligand

Name

Pub

Chem ID)

Residues

Interaction

Bond Length (Å)

No.

of Hydrogen

Bonds

G.score (Kcal/mol)

EQUISETUM ARVENSE

1

α-D-Glucopyranoside(165580)

GLY-276 (H-O)

2.8

2

-7.91

GLY-276 (H-O)

2

GLY-386 (0-H)

2.3

1

ASN-138(H-O)

2.6

1

ALA-506(H-O)

2.6

1

ALA-451(H-O)

2.6

2

ALA-136(H-O)

1.6

PAEONIA SUFFRUTICOSA

2

Gallic acid (370)

ALA-136 (H-O)

2.3

2

-4.1

ALA-136 (H-O)

2.1

LYS-312 (O-H)

2.3

1

GLU-275 (H-O)

2.4

1

3

Catechin (9064)

GLU-275 (H-O)

1.6

2

-3.41

GLU-275 (H-O)

2.3

ARG-277 (O-H)

2.5

1

LYS-312 (O-H)

2.3

1

GLY-386 (O-H)

1.9

2

GLY-386 (H-O)

2.7

REHMANNIA GLUTINUSA

4

Rehin (156112)

ALA-136 (H-O)

2.4

2

-3.6

ALA-136 (O-O)

3.1

ARG-277 (O-H)

2

1

GLU-275 (O-O)

2.5

1

CORYDALIS TURTSCHONINOVII

5

Protopine(4970)

LYS-312 (O-H)

2.2

1

-2.87

 

GLY-386 (O-H)

2.7

1

6

Fumariline (159888)

GLY-386 (O-H)

2

1

-2.32

7

Sanguinarine (97679)

ARG-483 (N-H)

1.8

1

-2.27

RHEUM PALMATUM

8

Anthocyanins (5318979)

ARG-483 (O-H)

1.9

1

-2.84

ALA-136 (H-O)

2

1

ALOE BARBADENSIS

9

Ethylparabene (8434)

ALA-282 (O-H)

2.1

1

-2.54

 

 

Fig. 3: Interaction of α-D-Glucopyranoside with modeled FLP2 Protein

 

Note: Pink color represents the amino acids and the green color represents Ligand; blue dotted lines represents interactions between amino acid residue and ligand.

 

CONCLUSION:

Among several compounds from the selected plants, α-D-Glucopyranoside was found to show the good G.score and interactions than other compounds. In future, the studies could be focused on the stability of the bond formations and QSAR studies to understand the pharmacophore of the compound.

 

 

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20.   http://www.uniprot.org/uniprot/A6NMB9

21.   http://nihserver.mbi.ucla.edu/SAVES/

 

 

 

 

Received on 08.03.2017          Modified on 22.05.2017

Accepted on 18.09.2017        © RJPT All right reserved

Research J. Pharm. and Tech 2017; 10(11): 3757-3760.

DOI: 10.5958/0974-360X.2017.00682.5