2023 Volume 14 Issue 1

In-silico Prediction of Drug Target, Molecular Modeling, and Docking Study of Potential Inhibitors against Burkholderia pseudomallei


Raghunath Satpathy*

School of Biotechnology, Gangadhar Meher University, Amruta Vihar, Sambalpur Odisha, 768004, India.

*E-mail: [email protected]







The infection of the Burkholderia pseudomallei causes the disease melioidosis. for which the treatment method takes longer time, and sometimes it is difficult to completely eradicate the bacteria from the body. Moreover, its antibiotic resistance in nature created great concern in recent times. Hence, there is an urgent requirement to identify new drug molecules that can improve the current process of treatments and reduce the risk to people. This study analyzed the pyrimidine metabolic pathways of Burkholderia pseudomallei strain K96243, and UMP (Uridine monophosphate/Uridylate) kinase enzyme was selected as the drug target. After structure prediction by the AlphaFold server, the validation of the structure was performed by using Procheck, Verify3D, and Errat tool. Further, six probable inhibitor molecules were selected from the PubChem database, including the natural inhibitor of the enzyme, Uridine triphosphate (UTP). The molecular docking study predicted that the UTP (CID 6133) had the highest docking score, followed by another compound PubChem (Compound ID) CID 284262. Then, Toxicity and ADMET properties were computed and analyzed. Further, a 5 nanosecond molecular dynamics simulation of the complex of UMP-Kinase and CID 284262 was performed by using the Gromacs 5.1.1 software to analyze the stability of the best complex. It was predicted that the CID 284262 might be considered a suitable inhibitor of the enzyme.

Keywords: Metabolic pathway analysis, UMP kinase enzyme, Molecular docking, Drug target prediction, Molecular dynamics simulation, Inhibitor compounds


Burkholderia pseudomallei is a pathogenic gram-negative, bi-polar, aerobic, motile, rod-shaped soil-dwelling bacterium, and the infection in the tropical and subtropical regions causes the disease melioidosis (Wiersinga et al., 2018; Savelkoel et al., 2022). These bacteria are also known for the resistant to various environmental conditions, including deficiency of nutrients, extreme temperature, and pH (Inglis et al., 2001). It infects humans and animals, primarily cattle and livestock such as goats, pigs, and sheep (Ekakoro et al., 2022). Bacterial infection in humans is associated with different pathogenic conditions like widespread pulmonary infection, septicemic infection, diabetic patients, and renal disease (Gassiep et al., 2020). Continuous exposure to infected soils and groundwater leads to an increased risk of causing melioidosis. Pneumonia is the most common symptom of melioidosis, observed in half of all cases (Leung et al., 2023). The seriousness of the disease varies widely, such as illness with high fever, tiny cough, inflamed pain, and difficulty breathing (Khattab et al., 2022). Presently the drug doxycycline is widely used as one of the most efficient therapeutic strategies for infection (Sridharan et al., 2021). However, studies reported that the B. pseudomallei bacteria also shows resistance to doxycycline while testing against the drug with different strains (Zueter et al., 2022). This bacterium is also naturally resistant to many antibiotics, including penicillin, cephalosporins, macrolides, rifamycins, polymyxins, and aminoglycosides (Di Fiore et al., 2022). The process of antimicrobial resistance has been studied as the bacterial antibiotic efflux pump was characterized as the key cause of the resistance (Somprasong et al., 2021). Since no licensed versions of vaccines are available for melioidosis disease, new therapeutic measures and vaccination strategies are expected to come shortly as a preventive measure against the infection (Morici et al., 2019; Currie 2022). In drug design strategies against bacteria, nucleotide metabolism is frequently studied to identify the drug targets, as the pathway's enzymes are considered essential (Kumari, & Tripathi, 2021; Perveen & Sharma, 2022). The nucleoside monophosphate (NMP) kinases are a critical group of enzymes involved in the pyrimidine synthesis metabolic process (Beji et al., 2020). The de novo of the pyrimidine nucleotide biosynthetic process consists of different vital metabolic enzymes conserved among the prokaryotic and eukaryotic organisms, including humans (Uddin et al., 2020; Wyllie et al., 2022).

The current work aims to discover some inhibitor molecules from the database and investigate the inhibition potential against the UMP kinase of Burkholderia pseudomallei (strain K96243) bacteria.

Materials and Methods

Computational Resources Used for Molecular Docking and MD Simulation Study

Processor: AMD Ryzen 3900*4.6GHz, Mother Board: Gigabyte B550 Acurs pro AC, RAM: Corsair 16*2 vengeance 3200NH 32GB, GPU: Asus dual GT 165004G, Operating system: Ubuntu Version 2021

Analysis of Nucleotide Synthesis Metabolic Pathway of Burkholderia Pseudomallei (strain K96243) and Target Prediction

The nucleotide synthetic pathway of the Burkholderia pseudomallei was searched in the KEGG pathway database (https://www.genome.jp/kegg/) with the organism keyword. The active genes involved in the pyrimidine metabolism were retrieved along with the sequence and functional information. Further, the sequence similarity was searched against the Homo sapiens using the protein Basic Local Alignment Search Tool (BLAST) available at https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE=Proteins by using the default parameter. The essential enzymes of the bacteria having no significant similarity were selected as the target in the present study. Further, the essential nature of the selected target protein was searched in the DEG (Database of Essential gene) database (http://origin.tubic.org/deg/public/index.php) to confirm the result.

Retrieval of the Three-Dimensional (3D) Structure of the Target Enzyme of Burkholderia Pseudomallei (strain K96243) and Validation

The 3D structure of the enzymes was obtained from the AlphaFold server (https://alphafold.ebi.ac.uk/). Further, the structural validation was performed by analyzing the output of several tools like PROCHECK (Ramachandran plot), ERRAT, and Verify 3D (https://saves.mbi.ucla.edu/).

Retrieval of Ligand Information

In the present work, the UTP and five similar types of compounds were considered inhibitor molecules by searching the literature (Arvind et al., 2013). The compound structures were retrieved from the PubChem database, and several molecular features were computed.

Molecular Docking, ADMET Property, and Molecular Dynamics Simulation Study

This selected target protein (receptor) and the ligand were subjected to the molecular docking study. Molecular docking uses searching and scoring algorithms to calculate the binding affinity and conformation of the ligand on the receptor molecule (Satpathy, 2020). Followed by molecular docking, the toxicity level and ADMET (Absorption, distribution, metabolism, excretion, and toxicity) properties were evaluated for the ProTox-II server (https://tox-new.charite.de/protox_II/) and Swiss ADME server (http://www.swissadme.ch/) respectively. Protox II server takes the input molecule in the canonical SMILES (Simplified Molecular-Input Line-Entry System) format. It predicts the compound's toxicity in six classes (Class I fatal to Class VI non-toxic). Further, GROMACS 5.1.1 (Groningen Machine for Advanced Chemical Simulations) software was employed for MD simulation at 5 nanoseconds (ns) time scale. It is an open-source, free molecular dynamics modeling program that is primarily made for simulating biological molecules, including proteins, lipids, and nucleic acids (www.gromacs.org). The 5 nanosecond molecular dynamics simulation was conducted for the receptor only and the selected ligand-receptor complex in the water environment by choosing the GROMOS 43A1 force field with SPCE as the water molecule topology. For the complex simulation, the topology file of the ligand molecule was obtained from the Prodrg server (http://prodrg1.dyndns.org/submit.html). The MD simulation result generated the parameters such as Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), Radius of gyration (Rg), Hydrogen bond, and Solvent accessible surface area (SASA) were considered for further analysis (Ghahremanian et al., 2022).

Results and Discussion 

Metabolic Pathway Analysis and Identification of the Target

The metabolic pathway related to pyrimidine metabolism resulted in 7 active enzymes involved in the pathways (Figure 1). The enzyme details with the E.C. numbers and functions were retrieved. Further, the protein sequences were obtained from the Uniport database. Further the


Figure 1. Screenshot of the active enzymes (highlighted in red) involved in the pyrimidine metabolism of Burkholderia pseudomallei


Position-specific iterated Blast (PSI-BLAST) program was used to obtain the homologous nature of the proteins concerning the human genome. The output of the seven selected enzymes is shown in Table 1. The enzyme uridylate kinase (uridine monophosphate kinase) did not show any homology as no significant similarity obtained with the human genome was selected as the target for the present study. The DEG database search also confirms the essential nature of the enzyme as it is available in the database with the DEG ID DEG10350258.


Table 1.  Enzyme details involved in the pyrimidine metabolism and selection of targets

S. N

Name of the Enzyme


E.C No


BLAST Matching with human, E-value, and % similarity


nucleoside diphosphate kinase



Synthesis of nucleoside triphosphates other than ATP.

Similar to NDP kinase,

9e-34, 43.94%


Uridylate kinase



Catalyzes the reversible phosphorylation of UMP to UDP

No Significant Similarity


CTP synthase



Catalyzes the ATP-dependent amination of UTP to CTP

CTP synthase 2,

1e-166, 45.08%


ribonucleoside-diphosphate reductase

beta chain



Provides the precursor molecules, essential for DNA synthesis.

ribonucleoside-diphosphate reductase subunit M2 B isoform 1

1e-38, 26.88%


dUTP Pyrophosphatase



Generates the immediate precursor, dUMP, of thymidine nucleotides

dUTP Pyrophosphatase complex with dUDP



putative thymidylate synthase



Catalyzes the reductive methylation of 2'-deoxyuridine-5'-monophosphate (dUMP) to 2'-deoxythymidine-5'-monophosphate (dTMP)

thymidylate synthase,

1e-54, 35.51%


putative thymidylate kinase



Phosphorylation of dTMP to form dTDP in both de novo and salvage pathways of dTTP synthesis

thymidylate kinase,

7e-08, 28.92%



Structure Prediction of the Uridylate Kinase

The 3D structure of uridylate kinase of Burkholderia pseudomallei strain K96243 is not available in the PDB. Hence, the alpha fold server was used to obtain the 3D structure and visualized it. The key binding sites were obtained from the UniProt server                (https://www.uniprot.org/uniprotkb/Q63T14/entry) and are shown in Figure 2.





Figure 2. a) Predicted 3D structure of UMP kinase enzyme and b) binding residues ATP binding residues are 11-14, 54,58, 161,167,170 (Red color highlights), UMP binding sites are 53, 73, 134-141 (Blue color highlights). The lower section describes validation features of the UMP kinase 3D model.

Table 2. Ligand details selected for docking studies

S. N

Compound (CID)





N-benzyl-2-[(2S,3R,4S,5R)-3,4-dihydroxy-5-(methanesulfonamidomethyl)oxolan-2-yl]-N methylacetamide








4-(2-Amino-4-(4-chlorophenyl)-7-oxo-5H-pyrrolo[3,4-d]pyrimidin-6(7H)-yl)butanoic acid




4-[2-amino-4-(4-methoxyphenyl)-7-oxo-5H-pyrrolo[3,4-d]pyrimidin-6-yl]butanoic acid




[[(2R,3S,4R,5R)-5-(2,4-dioxopyrimidin-1-yl)-3,4-dihydroxyoxolan-2-yl] methoxy-hydroxyphosphoryl] phosphono hydrogen phosphate (UTP)








The 3D structure of the molecule was predicted, and the ATP and UMP binding residues were highlighted (Figure 2). The model was further subjected to validation by using different parameters. The Ramachandran plot of the model shows 96.5% of residues are in favorable regions. The analysis of the model by the Errat tool generated a quality factor of 99.561, and a satisfactory level of the plot was obtained by Verify 3D tool (Figure 2). The overall result indicates that the model quality is good and can be considered for further study. Molecular docking by AutodockVina tool predicted the UTP, the enzyme's natural inhibitor having the highest binding affinity (docking score = -8.7 Kcal/mole). However, another molecule, CID 284262, also showed a comparatively good docking score (-8.1 Kcal/mole) (Table 2).