In-silico Investigation and ADMET Prediction of Potential Antifungal Phytochemicals against Lanosterol 14-Alpha Demethylase Inhibitors

 

Shalini A. Shinde¹*, Manasi J. Mhetar¹, Avantika G. Parit¹, Akash R. Thombre¹

¹Assistant Professor, Department of Pharmaceutical Chemistry,

Womens College of Pharmacy, Peth-Vadgaon, 416112, Maharashtra, India.

²UG Student, Womens College of Pharmacy, Peth-Vadgaon, 416112, Maharashtra, India.

³UG Student, Womens College of Pharmacy, Peth-Vadgaon, 416112, Maharashtra, India.

⁴Assistant Professor, Department of Pharmaceutical Chemistry,

Ashokrao Mane Institute of Pharmacy, Ambap, 416112, Maharashtra India.

 

ABSTRACT:

Mycosis is a chronic infectious disorder caused by various fungi affecting about 5% of the worldwide population. Pathogenesis involves the primary contact or inhalational roué for transmission. The infection is caused by to encoding of CYP450 enzyme Lanosterol 14-alpha demethylase. Numerous inhibitors are already used in clinical settings as therapeutic targets. A human lanosterol protein target (PDB ID: 6UEZ) and phytochemicals ligand library were used in a molecular docking simulation to perform docking simulation and ADMET studies on selected phytochemicals against human lanosterol protein receptor for drug discovery against lanosterol 14-alpha demethylase. The protein's crystal structure was retrieved and developed from the protein data repository with the aid of Biovia Discovery Studio. The phytochemicals' chemical structures were generated using Open Babel and VConf software after being downloaded from the NCBI PubChem database. PyRx was used to do molecular docking on Autodock Vina. SwissADME and pkCSM web servers were used to compute the best-performing compounds' ADMET characteristics. The findings demonstrated that taraxasterol exhibits a greater binding affinity. According to the findings, these compounds may be able to create anti-fungal activity, have decreased toxicity, and have easy absorbability at the tissue site, according to an ADME analysis. As a result, these substances can be examined in more in vitro research and could play a key role in developing a potential medicine to treat fungus infections.

 

 

 

INTRODUCTION:

Since the beginning of time, infectious diseases have plagued humankind, and the current COVID-19 (Coronavirus disease 2019) pandemic serves as a sobering reminder that this susceptibility still exists in today's society¹.

 

Healthcare practitioners have a tremendous dilemma as the prevalence of fungus infections rises significantly. Healthcare practitioners have a tremendous dilemma as the prevalence of fungus infections rises significantly².  After, infectious diseases continue to be one of the biggest causes of death in the world. Unfortunately, although endangering millions of lives annually around the world, several of these "microbial hazards" have been underappreciated and ignored by healthcare authorities¹. Over 300 million individuals are affected by fungal illness worldwide, which results in over 1.6 million fatalities each year³.

 

A fungus is a vegetative organism, yet it is also unquestionably not a plant because it does not produce chlorophyll. It is a non-motile life form, and its fundamental structural unit can be either a single cell, a chain of cylindrical cells (hyphae), or both. Everywhere on earth, the most prevalent species like Aspergillus and Candida can be found⁴. Comparative morphology, cell wall composition, ultrastructure, cellular metabolism, and the fossil record have all been used as the foundation for studies on fungal evolution. About 550 million years ago, the three major phyla of fungi—Zygomycota, Ascomycota, and Basidiomycota—are assumed to have split out from the Chytridiomycota⁵.

 

Mycosis is an infection in humans and other animals brought on by any fungus that enters the tissues and results in systemic, subcutaneous, or superficial illness. Mycosis can be brought on by a wide variety of fungi, some of which, like Cryptococcus and Histoplasma, can result in serious, life-threatening illnesses⁶.

 

A crucial enzyme in the manufacture of sterols, vital components of the fungal cell, lanosterol 14-demethylase is the target of one of the most significant and extensively researched mechanisms of resistance to azole antifungals⁷. The azole antifungals, which are widely used in medicine and agriculture as preventive or therapies for infections or disorders brought on by fungi, target the cytochrome P450 enzyme lanosterol 14-demethylase (LDM)⁸. The 14-demethylase enzyme, which is cytochrome P450 dependent, is inhibited by imidazoles. Lanosterol is demethylated to form ergosterol by the action of an important enzyme called 14- 14-demethylase. As a result of enzyme inhibition, lanosterol accumulates. This sterically bulky C-4 dimethyl and C-4 methyl sterol are unable to integrate into bio membranes like demethylated sterols like cholesterol and ergosterol. This prevents the formation of fungal cell walls, which ultimately restricts the proliferation of the fungus⁹.

 

The process of finding chemical entities with the potential to be medicinal agents is known as drug discovery. Identifying novel molecular entities that may be useful in treating diseases that meet the criteria for unmet medical needs is one of the main objectives of drug development programmes¹⁰. Drug discovery was previously only possible through traditional drug design methods, which involved laborious screening procedures for thousands of synthetic and natural chemicals. Medicinal chemists would then develop compounds that had been discovered through the laborious screening procedure by synthesizing hundreds of related compounds in an effort to create a molecule that was both safe and efficient for use as a medicine in people¹¹. It can take up to 14 years to complete a traditional drug development cycle from target identification to an FDA-approved medicine, at an estimated cost of 800 million dollars. However, due to failure in various stages of clinical trials, there has recently been a decline in the number of new drugs available. Therefore, it's critical to replace the drawbacks of traditional drug discovery approaches with effective, affordable, and versatile computational alternatives¹². In-silico methods have had a significant impact on the global biological system in the current period. Today, in-silico methods are frequently employed to forecast a variety of biological phenomena, including drug sensitivity and resistance, protein-protein interactions, and DNA-protein interactions. One of the key factors in C. albicans' azole resistance is the amino acid changes in the Erg11 protein¹³.

 

MATERIALS AND METHODS:

Ligand curation and preparation:

Literature searches were carried out to identify phytochemicals previously reported to possess anti-cancer properties. Some of the sources consulted are Phytochemistry: Phytochemical Analysis and molecular docking by  Simhadri VSDNA Nagesh, et al., (2018), and Phytochemical against antifungal activity edited by S. Gupta et al. (2012). The ligand library was prepared in 2D SDF format against lanosterol 14-alpha demethylase, retrieved from the NCBI PubChem database (pubchem.ncbi.nlm.nih.gov). To facilitate simple insertion into PyRx software, all the various ligands created were compressed into a single SDF file using the Open Babel program (openbabel.org).

 

Protein Preparation:

The protein data bank (https://www.rcsb.org/) provided the Human sterol 14-alpha demethylase in complex with the substrate lanosterol (PDB ID: 6UEZ, 1.98 resolution), which was downloaded in pdb format and analyzed using BIOVIA Discovery Studio Visualizer 2021 v21.1.0.20298. Polar hydrogens were added while water molecules and hetero atoms were removed during the procedure.

 

Active Site Preparation:

It was projected that 6UEZ's active site would be found in literature, Discovery Studio, and the PDB. The correct predicted amino acid residue must be chosen to guarantee that the target protein binding site is covered by the grid box configuration in the PyRx software. After that, it was discovered that the study's resolved center point was X: -22.8087, Y: -55.7715, Z: 0.1212 with dimensions (Angstrom) of X: 25, Y: 25, Z: 25.

 

Molecular Docking Studies:

PyRx software version 0.8 was used to run molecular docking simulations. PyRx is a program for high-throughput virtual screening of compounds against protein targets using molecular docking simulations. By analyzing the binding energy of compounds in kcal/mol, it is possible to determine which substances have the best chances of forming a strong bond with a protein. In this work, the 3D SDF-formatted ligands that had been generated and compressed were loaded into PyRx using the built-in OpenBabel graphical user interface. The conjugate gradient approach was used to minimize energy using the Universal Force Field (UFF), with a total number of steps set at 200. If the energy difference exceeds the threshold, the update process will cease after 1 step/mol. Thereafter all ligands were changed into AutoDock ligands to reduce energy use (pdbqt). The produced protein was loaded into PyRx and later changed to pdbqt in order to be ready for docking.  The docking simulation was run with an exhaustiveness level of 8. The ligand with the greatest propensity for binding was identified as having the highest binding energy (most negative). Using BIOVIA Discovery Studio, specific interactions of the optimum docking poses were shown.

 

Theoretical Prediction of ADMET Parameters:

The top-ranked compounds were exported in SMILES format from the docking simulation to SwissADME and the pkCSM web server for toxicity and bioavailability prediction techniques like Lipinski's rule of 5. SwissADME and pkCSM are free online tools for predicting the pharmacokinetics, drug-likeness, and medicinal chemistry friendliness of small compounds (http://biosig.unimelb.edu.au/pkcsm/prediction) (Daina et al., 2017; Pires et al., 2015). The importance and typical range of the ADMET parameters were chosen for this investigation.

 

RESULT AND DISCUSSION:

Molecular Docking Simulations:

In order to find novel Lanosterol 14-alpha demethylase inhibitors from natural sources, molecular docking experiments were conducted. The outcome suggests that some naturally occurring substances have higher binding energies than common medications The chemicals of plant sources were found in IMPPAT, Wikipedia, and other documentary evidence. The findings indicate that the optimal binding energy for taraxasterol, which is found in Mangifera indica (aerial portion) and Catharanthus roseus (seed oil), is -13 kcal/mol. The investigation demonstrated the 3D and 2D structures of taraxasterol in association with the Lanosterol protein (PDB ID: 6UEZ). The picture also depicts the interaction between taraxasterol and the ATP-binding site of 6UEZ. The binding activity and ligand-protein interaction of beta-amyrin, stepacidinA, sclerotamide, and isopomiferin are -12.5, -12.2, -12.2 and -10.9. The interactions of the first five phytochemicals having higher binding affinity are shown in Figures 1 to 5 respectively.

 

 

Fig1: 2D and 3D interactions of Taraxasterol

 

Fig2: 2D and 3D interactions of Beta-Amyrin

 

 

Fig 3: 2D and 3D interactions of Stephacidin A

 

 

Fig 4: 2D and 3D interactions of Sclerotamide

 

 

Fig 5: 2D and 3D interactions of Isopomiferin

 

Drug like-ness and ADMET Prediction:

Absorption, distribution, metabolism, excretion, and toxicity are all abbreviated as ADMET in the fields of pharmacokinetics, pharmacology, and toxicology. It focuses specifically on a compound's physicochemical, drug-likeness, and physiochemical characteristics. The idea behind ADMET is that a substance must be bioavailable, distributed to specific target areas, metabolized appropriately, excreted after performing its function, and have no adverse implications on the body cells, tissues, or organs it came into contact with in order to be effective when taken orally. Forecasting the ADMET qualities of a natural chemical from the beginning of a drug's development process is a crucial step in raising the likelihood that clinical trials will be successful in general. The ADMET properties of the top-performing drugs and common inhibitors were predicted in this study using the SwissADME and pkCSM web servers. Tables were used to present the results of the ADMET test. According to the findings, several compounds contradicted Veber's Rule, Ghose's Rule, Egan's Rule, and Muegge's Rule as well as Lipinski's Rule of Five (RO5). In addition to the drug-likeness characteristics, we also looked at the physiochemical characteristics as retrieved from the pkCSM web server and displayed in Tables 1 and 2.

Table 1: Drug-Likeness properties of phytochemicals by Swiss ADME

Sr no.	PubChem ID	MW (g/mol)	mLogP	HBA	HBD	MR	TPSA	nRot	Lipinski's Rule (Ro5)	Veber's Rule	Ghose's Rule	Egan's Rule	Muegge's Rule
1	115250	426.72	6.92	1	1	135.14	20.23 Ų	0	Yes	Yes	No	No	No
2	73145	426.72	6.93	1	1	134.88	20.23 Ų	0	Yes	Yes	No	No	No
3	10274385	431.53	2.56	3	2	130.66	74.43 Ų	0	Yes	Yes	No	Yes	Yes
4	132472696	477.55	1.66	5	2	139.58	99.18 Ų	0	Yes	Yes	No	Yes	Yes
5	20055152	420.45	2.17	6	2	119.89	89.13 Ų	1	Yes	Yes	Yes	Yes	Yes

 

Table 2: ADMET properties of phytochemicals by PkCSM

Sr. No	PubChem Id	Absorption				Distribution
		Intestinal Absorption (Human)	P-Glyco protein Substrate	P-Glyco protein Substrate I	P-Glyco protein Substrate II	VDss (Human)	BBB Permeability	CNS Permeability
		Numeric (% absorbed)	Categorial (Yes/No)	Categorial (Yes/No)	Categorial (Yes/No)	Numeric (log Lkg-1)	Numeric (log BB)	Numeric (log PS)
1	115250	96.351	No	Yes	Yes	-0.048	0.705	-1.668
2	73145	93.733	No	Yes	Yes	0.268	0.667	-1.773
3	10274385	93.885	Yes	No	Yes	1.167	-0.417	-1.983
4	132472696	89.888	Yes	Yes	No	0.74	-0.528	-3.115
5	20055152	93.297	Yes	Yes	Yes	0.494	-0.428	-1.659

 

Table 2: Cont……

Sr. No	PubChem Id	Metabolism							Excretion	Toxicity
		Substrate		Inhibitors					Total Clearance	AMES Toxicity
		CYP
		2D6	3A4	1A2	2C19	2C9	2D6	3A4
		Categorial (Yes/No)							Numeric (log mL min-1kg-1)	Categorial (Yes/No)
1	115250	No	Yes	No	No	No	No	No	0.151	No
2	73145	No	Yes	No	No	No	No	No	-0.044	No
3	10274385	Yes	Yes	No	Yes	No	No	No	-0.363	No
4	132472696	No	Yes	No	No	No	No	No	-0.3	No
5	20055152	No	Yes	Yes	Yes	Yes	No	No	-0.317	No

 

 

CONCLUSION:

Fungal infection is in the association between polyene susceptibility and the presence of sterols in the plasma membrane of the cells. The results of the molecular docking tests done in this study showed that the best-performing compounds were taraxasterol, beta-amyrin, stepacidin A, sclerotamide and Isopomiferin. Some of these compounds are, however, desirable for further evaluation due to their ADMET features. They are considered safe for usage because they do not have high BBB and CNS values, which indicate that they cannot easily access the nervous system.

 

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Received on 28.04.2023         Modified on 16.10.2023

Accepted on 13.01.2024   ©Asian Pharma Press All Right Reserved

Asian J. Pharm. Res. 2024; 14(1):33-38.