In silico designing of some Benzimidazole derivatives for Anti-fungal activity

 

Amrita Muralikrishnan, Radhika R Nair, Jifitha Banu, Dr Leena K Pappachen

Department of Pharmaceutical Chemistry and Analysis, Amrita School of Pharmacy,

Amrita Vishwa Vidyapeetham, AIMS Health Sciences Campus, Kochi, Kerala, India.

*Corresponding Author E-mail: leenakpappachen@aims.amrita.edu

 

ABSTRACT:

Fungus is a kind of living organism and yeast mould and mushrooms are types of fungi. The fungal infections are caused by the fungus. A fungus that invades the tissue can cause a disease that confined to the skin, spread into tissue, bone and organs or affect the whole body. Benzimidazole is a class of heterocyclic aromatic organic compound which posses pharmacological activities including antifungal, antitumor, antiparasitic, analgesic etc. Insilico methods can be used to identify target molecules using bioinformatics tool. The aim of our study was to conduct the insilico drug designing of some benzimidazole derivatives having antifungal activities.  In our study the insilico drug design was performed using Biovia discovery studio.

 

KEYWORDS: Fungal diseases, Ketoconazole, Biovia Discovery studio, Benzimidazole, Molecular docking studies.

 

 


INTRODUCTION:

More than 1.5 million people are killed due to fungal infections and over a billion people get affected. Nevertheless, they remain a neglected concern for public health officials, although the majority of deaths from fungal diseases can be prevented.1 When compared to treatment options available for bacterial infections, the therapeutic options for fungal infections is limited. Currently, only three drug classes are used in clinical practice for fungal infections. Also, in the last 30 years only one new category of drug has been invented.2

 

One may group fungal infections into two classes. The first category of fungal infection is mycoses of external surfaces such as the skin, skin structures and mucosa. The second main class of invasive fungal infections includes sterile body locations such as the bloodstream, CNS or organs like the lungs, liver and kidneys. Polyenes is the earliest group of antifungal medicines, the only example used for treating systemic fungal infections in this group being Amphotericin B.

 

Their severe toxicity has been one of the major drawbacks of polyenes, even though the production of Amphotericin B lipid preparations has greatly reduced this issue, these preparations are very costly and not accessible in some areas. Azole derivatives are the most commonly used class of antifungal drugs. The newest addition to the antifungal pharmacopeia is echinocandins with the first example, Capsofungin, launched a decade ago in clinical usage.3,4

 

Ketoconazole is an imidazole antifungal agent used in the prevention and treatment of a variety of fungal infections.14-α-sterol demethylase is a cytochrome P-450 enzyme essential for the transformation of lanosterol into ergosterol. Ketoconazole interacts with the enzyme and leads to ergosterol synthesis inhibition and increased fungal cellular permeability due to decreased levels of ergosterol present in the fungal cell membrane. This metabolic inhibition also leads to the build up of 14α-methyl-3,6-diol, a toxic metabolite.

 

MATERIALS AND METHODS:

Target identification:

Ketoconazole was selected as the standard drug for the study. The physical properties, chemical properties and mechanism of action of the drug was identified using the drug bank.

 

Protein selection and characterization:

The proteins were accessed from the protein data bank. The primary and secondary characterisation of the PDB ID’s obtained from the protein data bank were tested by using online tools such as PROTPARAM and SOPMA. The proteins must satisfy screening parameters including theoretical pH, half-life, instability index, aliphatic index, GRAVY, alpha helix, beta turn and random coil.5


 

Fig 1. Proteins selected for docking studies

 

Ligand modelling:

Ligand molecules were created with the help of ChemDraw.

SL NO

STRUCTURE

SL NO

STRUCTURE

B  1

 

B  5

 

B  2

 

B  6

 

B  3

 

B  7

B  4

 

B  8

 

 


Ligand characterisation:

Using Biovia Discovery Studio molecular pharmacophoric properties of ligand molecules including Alogp, molecular weight, HBD, HBA were calculated and compared with that of Ketoconazole.(6) Studies for the efficiency of absorption, distribution, metabolism and excretion in the body were conducted on the chosen ligands using prediction software Biovia ADMET.

 

Docking:

The docking studies of benzimidazole derivatives and standard drug Ketoconazole with known anti-fungal target proteins were carried out using Biovia discovery studio. The Cdocker energy and Cdocker interaction energy of benzimidazole derivatives were compared with that of  Ketoconazole. (7,8)

 

RESULTS:

Protein characterisation

Table 1 PROTPARAM

Protein

T1/2

Instability index

Aliphatic index

Gravy

pH

5 ESI

30

38.89

85.90

-0.262

8.76

5 ESG

30

38.50

85.90

-0.267

8.66

5 ESM

30

38.50

85.90

-0.267

8.66

 

Table 2 SOPMA

Protein

Α helix

Β turn

Random coil

5 ESI

250 is 4.38%

19 is 9.53%

21 is 40.07%

5 ESG

254 is 47.12%

18 is 3.34%

209 is 38.78%

5 ESM

253 is 46.94%

21 is 3.90%

205 is 38.03%

 


Ligand characterisation:

Table 3 Lipinski rule of five

Structure

A log p

Number of HBA

Number of HBD

Molecular weight

PROTEIN – 5ESG

B  1

2.625

1

1

180.634

B  2

2.887

1

1

245.504

B  3

3.11

1

1

194.661

B  4

2.625

1

1

180.634

B  5

2.887

1

1

245.504

B  6

2.344

1

1

184.598

B  7

2.112

2

1

211.623

B  8

2.128

3

1

231.611

KETOCONAZOLE

3.610

5

0

531.431

PROTEIN – 5 ESM

B  1

2.625

1

1

180.634

B  2

3.378

1

1

326.416

B  3

3.602

1

1

275.573

B  4

3.116

1

1

261.546

B  5

3.378

1

1

326.416

B  6

2.835

1

1

265.51

B  7

2.508

1

1

272.529

B  8

2.524

1

1

292.517

KETOCONAZOLE

3.610

5

0

531.431

PROTEIN – 5 ESI

B  1

2.625

1

1

180.634

B  2

3.378

1

1

326.416

B  3

3.662

1

1

275.573

B  4

3.116

1

1

261.546

B  5

3.378

1

1

326.416

B  6

2.835

1

1

265.51

B  7

2.508

2

1

272.529

B  8

2.524

3

1

292.517

KETOCONAZOLE

3.610

5

0

531.431

 

Table 4 ADMET properties

Structure

BBB

Absoprtion

Solubility

Hepatotoxicity

PROTEIN – 5 ESG

B  1

1

0

3

True

B  2

1

0

3

True

B  3

1

0

3

True

B  4

1

0

3

True

B  5

1

0

3

True

B  6

1

0

3

True

B  7

2

0

3

True

B  8

3

0

3

True

KETOCOAZOLE

2

0

2

False

PROTEIN – 5 ESM

B  1

1

0

3

True

B  2

1

0

3

True

B  3

1

0

2

True

B  4

1

0

3

True

B  5

1

0

3

True

B  6

1

0

3

True

B  7

2

0

3

True

B  8

3

0

3

True

KETOCONAZOLE

2

0

2

False

PROTEIN – 5 ESI

B  1

1

0

3

True

B  2

1

0

3

True

B  3

1

0

2

True

B  4

1

0

3

True

B  5

1

0

3

True

B  6

2

0

3

True

B  7

1

0

3

True

B  8

2

0

3

True

KETOCONAZOLE

2

0

2

False


 

Table 5 Docking

Structure

Cdocker energy

Cdocker interaction energy

PROTEIN – 5 ESG

B  1

19.5458

22.8988

B  2

18.4672

22.3552

B  3

18.9818

23.3467

B  4

17.3000

21.6862

B  5

17.6675

22.6273

B  6

11.4323

16.2301

B  7

17.5794

21.4091

B  8

14.9868

22.8106

KETOCOAZOLE

30.1681

54.7465

PROTEIN – 5 ESM

B  1

17.1007

20.4637

B  2

20.3209

23.992

B  3

20.7660

24.9263

B  4

17.5272

20.9952

B  5

18.1239

22.3651

B  6

11.5253

16.1806

B  7

18.6310

22.8956

B  8

8.8416

16.7218

KETOCOAZOLE

31.2463

56.7017

PROTEINN – 5 ESI

B  1

14.0416

17.5002

B  2

20.0818

23.9603

B  3

21.4308

25.5113

B  4

17.4488

20.7679

B  5

19.5579

23.8939

B  6

16.0872

20.8733

B  7

17.3514

21.8616

B  8

15.5148

22.9859

KETOCONAZOLE

32.7041

57.9578

 


DISCUSSION:

All the generated benzimidazole derivatives satisfied the Lipinski’s rule of five. Comparison of benzimidazole derivatives docking scores with the standard drug Ketoconazole revealed that the derivatives exhibited a greater binding strength to the chosen proteins. Therefore, they offer exciting prospects for their antifungal activity to be investigated. The suggested benzimidazole derivatives are useful for further in vitro and in vivo studies against fungal infections.

 

REFERENCES:

1.      Felix Bongomin, Sara Gago , Rita O. Oladele and David W. Denning.Global and Multi-National Prevalence of Fungal Diseases—Estimate Precision. Journal of Fungi. 2017; 3(4): 57.

2.      WeijieSi, Tao Zhang, Yaofa Li, Dongmei She, Wenliang Pan, Zhanlin Gao, Jun Ning and Xiangdong Mei.. Synthesis and biological activity of novel benzimidazole derivatives as potential antifungal agents. Journal of Pesticide Science.2016; 41(1): 15–19.

 

3.      Terry Roemer and Damian J. Krysan. Antifungal Drug Development: Challenges, Unmet Clinical Needs, and New Approaches. Cold Spring Harbor Perspectives in Medicine. 2014; 4.

4.      Denning, D. W., and Hope, W. W. (2010). Therapy for fungal diseases: opportunities and priorities. Trends in Microbiology. 2010; 18(5): 195-204.

5.      Dr Leena K Pappachen, Dr Subin Mary Zachariah and Chandran D. Insilico design, synthesis and characterization of some novel benzothiazole derivatives as anti-cancer agents. Asian Journal of Pharmaceutical and Clinical Research.2017; 10: 150-155.

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Received on 09.05.2020           Modified on 12.07.2020

Accepted on 16.08.2020         © RJPT All right reserved

Research J. Pharm. and Tech. 2021; 14(9):4983-4986.

DOI: 10.52711/0974-360X.2021.00867