**1. Introduction**

Ethnomedicine is the study of traditional medicine based on the bioactive compounds of plants and animals, the mother of all other systems of medicines-Ayurveda, Siddha, Unani, Naturopathy, and even modern medicine. These ethnomedicine have played a major role throughout the world in treating and preventing diseases. The various sources of natural medicinal products could be terrestrial plants, terrestrial microbes, marine microbes, and even vertebrates and invertebrates [1].

During the 'golden era' of antibiotic discovery, the generation time of pathogens varies from minutes to weeks, leading to the inevitability of resistance selection. This reinforced the need for new chemical entities. The two novel antibiotics that are approved by FDA for human use are linezolid and daptomycin. There is a need for the discovery of an alternative drug using natural medicinal products.

Microorganisms are ubiquitous interact with all other organisms and inhabit every environment on Earth. These are the leading producers of the useful natural products, indicating their excellency in drug formulation. Various portions of microbial genomes are devoted to production of secondary metabolites. Recently, scientists have begun to realize and discover their role in the medical community. These are an ample source of structurally diverse bioactive substances which have led to the discovery of drugs mainly penicillin, cephalosporins, polyketides, and tetracyclines [2]. A single microbe can produce several the secondary metabolites. They include antibiotics, anticancer agents, immunosuppressants, anthelmintics, and many more. With the development of Computer technology, in silico approaches have been widely used to elucidate the pharmacological use of plants and microbes in drug discovery [3]. Therefore the 'new era' of drug discovery is believed to prevent and control the consequence of disease and illness in a more rational way [4]. Generally, microorganisms are differentiated on the basis of their cellular organization as shown in **Figure 1**.

According to National Organization for Rare Diseases (NORD), Gaucher Disease (GD) is an orphan disease, an inherited metabolic disorder in which deficiency of the enzyme β- glucosidase results in the accumulation of harmful quantities of lipids/fats. Especially the glycolipid glucocerebroside, throughout the body especially within the bone marrow, spleen, and liver. Researchers have identified three distinct forms of GD: Type 1 - Non-neuronopathic GD, Type 2 - Acute neuronopathic GD, Type 3- Chronic neuronopathic GD [5]. The gene mutations lead to the replacement of amino acids in the enzyme β- glucosidase which reduces the protein stability and the catalytic activity. Personalized treatment is required depending on the type of GD.

The drug therapy options approved by FDA include (ERT) Enzyme Replacement Therapy and (SRT) Substrate Reduction Therapy [6, 7]. The cost of ERT and SRT are very high as for most orphan drugs. These kinds of treatment measures are not available for rural people as they are unaware due to the lack of facilities in hospitals. The ultimate aim of the study is the application of virtual screening and network pharmacology which enriches the active compounds among the candidates, thereby indicating the action mechanism of beneficial microbes, reducing the cost, and increasing the efficiency of the whole procedure, seeking an alternative solution for GD.

#### **Figure 1.**

*Microbial classification based on cellular organization.*

*A Scientific Ethnomedical Study Using Microbes on Gaucher Disease: An* In-Silico *Analysis DOI: http://dx.doi.org/10.5772/intechopen.107545*

In our study, we construct the network of relationships among the medicinal microbes, their natural compounds, and the biological targets of the diseases. We hereby performed a deep virtual screening process through the molecular docking studies to test the binding efficiency of selected bioactive compounds from the microbes as a drug candidate. This is first in-silico work using the microbes as the core elements for the therapeutic studies against the GD, which brings out the novelty of the work carried out, attempting to find an alternative solution for GD.

## **2. Methodology**

The structure-based drug designing was performed, which serves as a powerful tool in identifying new lead compounds in the process of drug discovery [8]. The sources of the chemicals from the microbes are purely based on the literature work done intensively during the whole work.

#### **2.1 Databases**

The 3D protein structure was retrieved from Protein Data Bank. All the corresponding ligand molecules were retrieved after intensive literature review from various online sources and the 2D structure of these bioactive compounds were retrieved from PubChem (https://pubchem.ncbi.nlm.nih.gov/).

#### **2.2 Protein preparation**

The proteins were assembled by removing the native auto inducer all water molecules. Hydrogen was re-added using the protein residue template in Maestro v10.2. This is a vital stage in the preparation of protein as any modification can be re-addressed like missing side chains, and updating the missing residues. To enhance the structure the water molecules were removed, increasing the entropy of the target molecule.

#### **2.3 Ligand preparation**

Initially the ligands were converted into 3D structure using the Ligprep tool in maestro Schrödinger v10.2. The ligand was geometrically optimized.

#### **2.4 ADMET activity**

An account of druggability is very essential while performing a docking study, the ligands were checked for Absorption, distribution, metabolism, excretion, and toxicity (ADMET) test. It is a preliminary step in drug preparation. The knowledge on drugs for Gaucher disease is very scanty, and it is very reasonable to make out more and reduce the cost of treatment as a lot of developing countries can rely on it. 12 compounds successfully scored well in all the ADMET parameters analyzed using Qikprop version 4.4. in the Schrodinger suite [9]. Some important parameters like CNS, Blood-barrier coefficient, human blood absorption, Lipinski's rule of three and five were analyzed. The bioactive phyto-compounds which displayed pragmatic result were chosen for the ADME and preferable docking poses has been tabbed for the rationale of docking [10].

#### **2.5 Molecular docking**

Molecular docking outlays the ligand's preferred orientation with the target molecule while interacting with each other in forming a highly stable complex. For this purpose, we have employed Maestro v10.2 to conduct the extra precision (XP) docking for speculating the binding affinity, analyzing the efficacy of the ligand, and inhibitory constant of ligand against the target. In this study, the entire ligand was docked with the target molecule flexibly using the Glide Xtra precision (XP) tool. As a result of successful docking, we have obtained better docking scores, poses with accurate hydrophobic contacts between target residues to ligand [11].

#### **2.6 PyMOL**

PyMOL is an open-source molecular visualization tool commercialized by Schrödinger, which can produce high-quality 3D images of small molecules, biological macromolecules like proteins. It is one of the most trusted tools for visualization in structural biology and it operates on Python language.

#### **2.7 LigPlot**

A computer program able to generate 2D schematic representation of proteinligand interaction from the standard PDB input file. The interactions shown are basically of hydrogen bonds and hydrophobic contacts. In this hydrogen bonds are indicated by dashed lines between the atoms involved whereas hydrophobic interactions are represented by an arc with spokes facing towards the ligand atoms they come in contact with. The interacted atoms are represented by the spokes facing them back [12].

## **3. Result and discussion**

#### **3.1 ADMET analysis**

The ADMET (Adsorption, Distribution, Metabolism, Excretion, and Toxicity) analysis was performed for evaluating the drug-likeness of 50 compounds from microorganisms. The prediction was performed using the Quikprop version 4.4 in the Schrodinger suite [8]. Drug likeness properties of the selected compounds were determined by Lipinski's rule of five, Jorgensen's rule of three, molecular weight, CNS activity, dipole movement, Volume, Total solvent accessible surface area (SASA), Brain/blood partition coefficient, metabolic reactions, Human oral absorption and Percent Human Oral Absorption. It is believed that ADME shows the toxicity of small molecules [13]. The drug-like property's prediction was then evaluated and the results were portrayed in **Table 1**.

ADME is an essential tool for analyzing the proposed molecule's oral bioavailability as possible drugs. Statistics estimate that almost half of the candidate drugs do not undergo clinical trials because they fail to meet the suitable levels of efficacy, toxic effect on the body, making it unsafe for human use [14]. According to the literature study, 50 compounds were selected for ADME Analysis, from which the prediction results were shown by the 10 compounds from different microorganisms, especially bacteria, fungi, and algae (**Figure 2**).

*A Scientific Ethnomedical Study Using Microbes on Gaucher Disease: An* In-Silico *Analysis DOI: http://dx.doi.org/10.5772/intechopen.107545*


**Table 1.**

*Analysis of ADMET properties for the microbial compounds.*

**Figure 2.**

*Bioavailability of microbial compounds before and after ADMET analysis.*
