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In-Silico Evaluation of Druggability Prioritization Targets of Salmonella Gallinarum viz Gallus Gallus

Bichamma Viragadindla Gopala Reddy Vijay Kumar Matham Usharani Karatlapalli Anil Kumar Rathod Laskshman Mekala
Vol 7(7) 269-279

An experimental study was conducted to evaluate the druggability prioritization targets of salmonella gallinarum in Gallus gallus. Total proteome of pathogen Vs host comparison using comparative genomics was done followed by protein docking of the target proteins of the pathogen and drug target identificationandthen calculation of drug prioritization parameters for therapeutic target. 3965 proteins of S. gallinarum were compared with 24068 proteins of Gallus gallus using BLASTP analysis. The dockingresultsshowedpositiveligandposesforproteins1L50posed with ligands 142, 152, 316 ,477,1114 and atovaquone, ethambutol, olsalazine, protein 1MDZ posed with ligands 152, 388 and ethambutol, olsalazine, protein 1R30 posed with ligands 152,157,273,477,598,701,1039,1114 and atovaquone, ethambutol,olsalazine, lenvatinib, Protein 1XVT posed with ligands 152,157,477,701,1039,1114 and 1197.protein 2KHO posed with ligands 152 and atovaquone, olsalazine, ponatinib, protein 2QVR posed with ligands 142, 152, 273, 316, 388, 477,598, 674, 1114, 1197 and 1213.protein 3E74 posed with ligands 157,477,701 and lenvatinib, Protein 3H8A posed with ligand ponatinib and protein 4ADE posed with ligands ponatinib and 157. The results of the study revealed potential drug targets for developing novel molecules against Salmonella gallinarum and resulted in identification of novel molecules.

Keywords : In-silico Durggability Salmonella gallinarum Gallus gallus


Fowl typhoid, an acute septicaemic disease of avian species caused by Salmonella gallinarum (Priyantha, 2012), affects all age groups of chickens. Morbidity is high among all age groups of the birds, whereas mortality may range widely from 10% to 90% (Latife Beyaz et al., 2010). Maintaining a disease free status is a challenging exercise due to the rapid expanding nature of the industry. This is indicated by the fact that a number of Salmonella outbreaks reported in the world are a result of injudicious introduction of infected birds (Meeusen et al., 2007). Thus, poultry industry is facing great setbacks due to frequent outbreaks of salmonellosis (Fatma et al.,2012). Since its discovery, many efforts have been made to control and prevent the occurrence in commercial poultry farming. However, outbreaks of salmonellosis still remain a serious economic problem in countries where control measures are not efficient or in those areas where the climatic conditions favour the environmental spread of these microbes (Barrow and Freitas Neto, 2011). The economic losses are chiefly due to morbidity, mortality, reduced growth rate, reduced feed conversion efficiency, drop in egg production, decreased fertility and hatchability (Mamta Mishra and Deepika Lather, 2010).

Control of fowl typhoid is difficult (Soncine and Back, 2001) due to endemicity of the disease, facultative intracellular nature of causative organism, both vertical (Paiva et al., 2009) and horizontal (Cox et al., 1996) modes of transmission, presence of carrier stage and multiple drug resistance. Fowl typhoid can be controlled by a combination of stringent management procedures and chemotherapy. The widespread and indiscriminate use of antibiotics in the treatment of poultry diseases has lead to antimicrobial resistance of resistant salmonella strains (Enabulele et al., 2010) which is of a global public health concern (Ahmed et al., 2011). However, Enabulele (2010) has reported that Salmonella gallinarum strains are becoming more resistant to antibiotics than other avian salmonellas, which meant that it is more difficult to treat infected flocks successfully. However, this view may change, as its true prevalence becomes known with improved diagnostic tests, and with the likely failure of antibacterial agents to control disease in the future and with the emphasis on curtailing the spread of disease in poultry.Thus, the present study is aimed to evaluate the druggability targets of pathogen viz Gallus gallus.

Materials and Methods

Identification of Host and Pathogen Metabolic Pathways

Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database was used as a source of metabolic pathways information (Kanehisa et al., 2006; Kanehisa et al., 2010). A list of metabolic pathways and identification numbers of the host and the pathogen Salmonella gallinarum was extracted from the KEGG database and saved locally. Proteins from pathways were identified and the respective amino acid sequences were obtained from the Swiss-Prot database (Boeckmann et al., 2003).

Screening of Non-Homologous and Essential Proteins

Two-step comparisons were performed between host and pathogen proteomes for the identification of non-homologous proteins of Salmonella gallinarum (Altschul et al., 1997). In each scenario, searching was restricted to proteins from broilers only through an option available under BLASTP parameters. Hits were filtered on the basis of expectation value (e-value) inclusion threshold being set to 0.005, and a minimum bit score of 100. Proteins, that did not have hits below the e-value inclusion threshold of 0.005, were picked as non-homologous proteins.

Druggability of Therapeutic Targets

Druggability is another important target prioritization criterion, which is defined as the likelihood of being able to modulate the activity of the protein target with a small-molecule drug (Keller et al., 2006; Cheng et al., 2007). The druggability potential of each of the identified drug targets was calculated by mining Drug Bank contents. The Drug Bank database is a unique bioinformatics and cheminformatics resource that combines detailed drug (i.e. chemical, pharmacological and pharmaceutical) data with comprehensive drug target (i.e. sequence, structure and pathway) information. The database contains 6796 drug entries including  1437  FDA approved  small  molecule drugs, 134 FDA approved biotech (protein/peptide) drugs, 83 nutraceuticals and 5174 experimental drugs. Additionally,4285 non redundant protein(i.e. drug target/enzyme/transporter/carrier) sequences are linked to these drug entries (Knox et al., 2011). BLASTP with default parameters were used to align the potential drug targets from Salmonella gallinarum against the list of protein targets of compounds found within Drug Bank. The selection criteria for filtering BLAST results were as described previously (Holman et al., 2009), that is, alignments with e-values less significant 25 than 1 x 10 were removed.

Results and Discussion

Identification of Non-Homologous Proteins

3965 proteins of Salmonella gallinarum were compared with 17,227 proteins of Gallus gallususing BLASTP analysis. 1068 non- homologous proteins of SG were found, while 2897 proteins were found homologous. These non-homologous proteins were analyzed using BLAST against PDB and all targets from Drug Bank. Number of proteins found hits against PDB (sequences of proteins with known structure): 35 (Table 1) and against Drug Bank were 29 (Table 2).

Druggability of Therapeutic Targets

Thirty five proteins found with solved PDB structures were analyzed using CLASTLW and that resulted in thirty five proteins having an average alignment of above or minimal 30% (Table 4).The thirty five proteins structures were also determined using PISA software and the structures of the proteins were determined, of which by PISA 5 monomers, 2 dimmers, 1 tetramer and 1 polymer were found (Table 3).

Table 1: List of PDB structures matching with non-homologous proteins of Salmonella gallinarum after BLAST with Gallus gallus proteome

S. No. Query Protein ID Subject Protein ID %id Bit Score Clustalw PISA
1 sp|B5R7Q4|ACEK_SALG2 3lcb_B 92.36 1108 92.04 tetramer
2 sp|B5R646|ALLB_SALG2 3e74_D 92.72 859 92.71 tetramer
3 sp|B5R9L5|AMPA_SALG2 1gyt_L 98.01 991 98.01 polymer
4 sp|B5RGD3|ARAA_SALG2 4f2d_C 95.6 1012 95.6 Trimer
5 sp|B5RF45|ARLY_SALG2 1tj7_B 94.96 858 94.74 polymer
6 sp|B5RCC4|ARNA_SALG2 1z7e_F 79.7 1125 79.69 polymer
7 sp|B5RCC2|ARNB_SALG2 1mdz_A 99.47 739 99.47 monomer
8 sp|B5R8J5|AROA_SALG2 2pq9_A 89.7 753 89.69 monomer
9 sp|P22299|AROA_SALGL 2pq9_A 89.7 753 89.69 monomer
10 sp|B5RAZ8|ASTB_SALG2 1ynh_D 84.98 722 84.78 tetramer
11 sp|B5RB01|ASTC_SALG2 4ade_B 84.73 733 84.72 Dimer
12 sp|B5RFW1|ATPA_SALG2 3oaa_a 98.64 990 98.63 polymer
13 sp|B5RFW3|ATPB_SALG2 3oaa_d 99.13 885 99.12 polymer
14 sp|B5RHG2|BAMA_SALG2 3efc_A 97.18 777 95.94 monomer
15 sp|B5R761|BIOB_SALG2 1r30_B 94.78 656 94.5 Dimer
16 sp|B5RGA5|CAIB_SALG2 1xvt_A 94.81 788 94.81 monomer
17 sp|B5RGA7|CAIT_SALG2 3hfx_A 96.03 953 96.03 monomer
18 sp|B5RF49|CAPP_SALG2 1qb4_A 93.66 1657 93.65 monomer
19 sp|B5R991|CH60_SALG2 2eu1_N 98.5 916 98.54 polymer
20 sp|B5RHE1|CLCA_SALG2 1kpl_D 98.52 721 98.52 tetramer
21 sp|B5R6V0|CLPX_SALG2 3hte_F 97.8 711 96.96 Polmer
22 sp|B5RBK6|COBT_SALG2 1l5o_A 98.88 703 93.82 monomer
23 sp|B5R7N6|CYSG_SALG2 1pjs_B 99.34 931 99.34 Dimer
24 sp|B5RDS0|CYSI_SALG2 4g39_A 93.68 1085 93.68 monomer
25 sp|B5RFI7|DCUP_SALG2 3cyv_A 97.17 714 96.89 monomer
26 sp|B5RFZ8|DGOD_SALG2 3rra_B 82.46 647 82.46 Dimer
27 sp|B5RF08|DNAK_SALG2 2kho_A 97 1156 97.02 monomer
28 sp|B5RCP9|DNLJ_SALG2 2owo_A 92.55 1278 92.54 monomer
29 sp|B5R6S3|DXS_SALG2 2o1s_D 96.29 1203 96.29 tetramer
30 sp|B5RE31|E4PD_SALG2 2x5j_R 93.51 659 93.51 tetramer
31 sp|B5RH09|EFG_SALG2 4kjc_V 97.59 1398 96.38 NA
32 sp|B5RDS5|ENO_SALG2 3h8a_D 98.61 795 98.61 polymer
33 sp|B5R9A5|EPMA_SALG2 3g1z_B 99.08 669 99.07 Dimer
34 sp|B5R9H4|F16PA_SALG2 2qvr_A 97.29 670 97.28 monomer
35 sp|B5RFL6|FADB_SALG2 2d3t_B 56.36 748 55.52 tetramer

Molecular Docking

Thirty five proteins were loaded into Discovery studio version 4.1 for receptor ligand interaction studies with 29 ligands. The docking results showed positive ligand poses for proteins 1L50 posed with ligands DB142, 152, 316, 318, 477, 1114 and atovaquone, ethambutol, olsalazine, protein 1MDZ posed with ligands DB152, 388 and ethambutol, olsalazine, protein 1R30 posed with ligands. DB152, 157, 273, 477, 598, 701, 1039, 1114 and atovaquone, ethambutol, olsalazi ne, lenvatinib, Protein 1XVT posed with ligands DB152, 157, 477, 701, 1039, 1114 and 1197, protein 2KHO posed with ligands DB152 and atovaquone, olsalazi ne, ponatinib, protein 2QVR posed with ligands DB142, 152, 273, 316, 388, 477, 598, 674,1114,1197 and 1213, protein 3E74 posed with ligands DB157, 477, 701 and lenvatinib, protein 3H8A posed with ligand ponatinib and protein 4ADE posed with ligands DB157 and ponatinib (Fig. 1). The functional characters of the above 9 non-homologous proteins are mentioned in Table 4 proteins 1L50

Table 2: List of Drug Targets matching with non-homologous proteins of Salmonella gallinarum after BLAST with Gallus gallus proteome

SL.No Query protein ID Subject protein ID %id Bit Score
1 sp|B5R646|ALLB_SALG2 drugbank_target|3230 34.85 231
2 sp|B5R9L5|AMPA_SALG2 drugbank_target|6384 34.90 244
3 sp|B5RF45|ARLY_SALG2 drugbank_target|577 44.93 357
4 sp|B5RCC4|ARNA_SALG2 drugbank_target|3257 79.70 1125
5 sp|B5RCC2|ARNB_SALG2 drugbank_target|2749 99.47 739
6 sp|B5R8J5|AROA_SALG2 drugbank_target|2525 89.70 753
7 sp|P22299|AROA_SALGL drugbank_target|2525 89.70 753
8 sp|B5RAZ8|ASTB_SALG2 drugbank_target|3406 85.01 724
9 sp|B5RB01|ASTC_SALG2 drugbank_target|472 34.66 221
10 sp|B5RFW1|ATPA_SALG2 drugbank_target|6342 56.14 527
11 sp|B5RFW3|ATPB_SALG2 drugbank_target|6343 71.24 621
12 sp|B5R761|BIOB_SALG2 drugbank_target|3164 94.80 659
13 sp|B5RGA5|CAIB_SALG2 drugbank_target|3024 94.81 788
14 sp|B5RF49|CAPP_SALG2 drugbank_target|3339 93.66 1657
15 sp|B5RHE1|CLCA_SALG2 drugbank_target|3428 98.94 725
16 sp|B5R6V0|CLPX_SALG2 drugbank_target|5270 51.14 417
17 sp|B5RBK6|COBT_SALG2 drugbank_target|2264 99.16 705
18 sp|B5R7N6|CYSG_SALG2 drugbank_target|4318 99.34 931
19 sp|B5RDS0|CYSI_SALG2 drugbank_target|2421 93.52 613
20 sp|B5RFZ8|DGOD_SALG2 drugbank_target|2726 26.05 71.2
21 sp|B5RF08|DNAK_SALG2 drugbank_target|1847 50.73 561
22 sp|B5RCP9|DNLJ_SALG2 drugbank_target|6275 62.97 870
23 sp|B5R6S3|DXS_SALG2 drugbank_target|110 22.01 58.9
24 sp|B5RE31|E4PD_SALG2 drugbank_target|4336 49.40 355
25 sp|B5RH09|EFG_SALG2 drugbank_target|3270 59.68 800
26 sp|B5RDS5|ENO_SALG2 drugbank_target|3173 65.42 514
27 sp|B5R9A5|EPMA_SALG2 drugbank_target|221 28.06 121
28 sp|B5R9H4|F16PA_SALG2 drugbank_target|4198 44.98 270
29 sp|B5RFL6|FADB_SALG2 drugbank_target|6764 56.36 748

posed with ligands 142(L glutamic acid), 152(Thiamine), 316(Acetaminophen) ,477(Chlorepromazine),1114(Chlorephenamine)  and atovaquone, ethambutol, olsalazine, protein 1MDZ posed with ligands 152(Thiamine), 388(Phenyleprine) and   ethambutol,   olsalazine,   protein  1R30  posed  with   ligands 152(Thiamine),157(NADH),273(Topiramate),477(Chlorepromazine),598(Labetolol),701(Amprenavir),1039(Fenofibrate),1114 (Chlorephenamine)and atovaquone, ethambutol,olsalazine, lenvatinib, Protein 1XVT posed with ligands 152(Thiamine),157(NADH),477(Chlorepromazine),701(Amprenavir),1039(Fenofibrate),1114(Chlorephenamine) and 1197(Captopril).protein 2KHO posed with ligands 152(Thiamine)   and  atovaquone,   olsalazine,   ponatinib,  protein  2QVR  posed  with   ligands 142(L glutamic acid), 152(Thiamine), 273(Topiramate), 316(Acetaminophen), 388(Phenyleprine), 477(Chlorepromazine),598(Labetolol), 674(Galantamine), 1114(Chlorephenamine), 1197(Captopril) and 1213(Fomepizole), protein 3E74 posed with ligands 157(NADH),477(Chlorepromazine),701(Amprenavir) and lenvatinib, Protein 3H8A posed with ligand ponatinib and protein 4ADE posed with ligands ponatinib and 157(NADH). The functional characters of the above 9 non-homologous proteins are mentioned in Table 4.

Table 3: List of Drug Receptor Ligand Interactions with Positive Poses

Sl.No Salmonella protein PDB ID Ligand Name Docking Score
1 sp|B5R646|ALLB_SALG2 3e74_D 701- Amprenavir 38.193
157- NADH 56.251
477- chlorpromazine 25.812
Lenvatinib(mol) 33.819
2 sp|B5RCC2|ARNB_SALG2 1mdz_A 152-thiamine 1.934
388-phenyleprine 12.757
Ethambutol (mol) 26.477
Olsalazine (mol) 40.355
3 sp|B5RB01|ASTC_SALG2 4ade_B 157-NADH 45.038
Ponatinib (mol) 59.724
4 sp|B5R761|BIOB_SALG2 1r30_B 152-thiamine 185.605
157-NADH 110.807
273-Topiramate 768.927
477-chlorpromazine 265.73
598-labetalol 235.958
701-amprenavir 553.537
1039-fenofibrate 267.718
1114chlorephenamine 104.889
Atovaquone (mol) 70.008
Ethambutol (mol) 389.607
Lenvatinib (mol) 145.741
Olsalazine (mol) 304.101
5 sp|B5RGA5|CAIB_SALG2 1xvt_A 152-thiamine 57.255
157-NADH 45.732
273-topiramate 31.33
477-chlorpromazine 41.912
701-amprenavir 36.938
1039-fenofibrate 10.995
1114chlorephenamine 7.628
1197-captopril 2.652
Atovaquone (mol) 40.575
Ethambutol (mol) 34.949
Lenvatinib (mol)
Olsalazine (mol 57.587
6 sp|B5RBK6|COBT_SALG2 1l5o_A 142-Lglutamic acid 49.6
152-thiamine 15.793
316-acetaminophen 23.99
388-phenyleprine 31.67
477-chlorpromazine 25.525
1114chlorephenamine 7.73
Atovaquone (mol) 0.006
Ethambutol (mol) 25.79
Olsalazine (mol)

Table 4: List of non-homologous proteins of Salmonella gallinarum after BLASTP with Gallus gallus with their functional characters

S. No. Name of the POSSITIVE Salmonella Proteins POSSITIVE PDB id Function of Salmonella Protein
1 sp|B5R646|ALLB_SALG2 3e74_D Allantoinase; Catalyzes the conversion of allantoi (5- ureidohydantoin) to allantoic acid by hydrolytic cleavage of the five-member hydantoin ring
2 sp|B5RCC2|ARNB_SALG2 1mdz_A UDP-4-amino-4-deoxy-L-arabinose–oxoglutarate aminotransferase; Catalyzes the conversion of UDP-4-keto-arabinose(UDP-Ara4O) to UDP-4-amino-4-deoxy-L-arabinose (UDP-L-Ara4N)
3 sp|B5RB01|ASTC_SALG2 4ade_B Succinylornithine transaminase;Catalyzes the transamination of N(2)-succinylornithineand alpha-ketoglutarate into N(2)-succinylglutamate semialdehyde and glutamate. Can also act as an acetylornithine aminotransferase.
4 sp|B5R761|BIOB_SALG2 1r30_B Biotin synthase; Catalyzes the conversion of dethiobiotin (DTB) to biotin by the insertion of a sulphur atom into dethiobiotin via a radical-based mechanism.
5 sp|B5RGA5|CAIB_SALG2 1xvt_A L-carnitine CoA-transferase; Catalyzes the reversible transfer of the CoA moiety from gamma-butyrobetainyl-CoA to L-carnitine to generate L-carnitinyl-CoA and gamma-butyrobetaine.
6 sp|B5RBK6|COBT_SALG2 1l5o_A Nicotinate-nucleotide—dimethylbenzimidazole phosphoribosyltransferase; Catalyzes the synthesis of alpha-ribazole-5′- phosphate from nicotinate mononucleotide (NAMN) and 5,6-dimethylbenzimidazole(DMB).
7 sp|B5RF08|DNAK_SALG2 2kho_A Chaperone protein; Heat shock protein 70 ,Acts as a chaperone.
8 sp|B5RDS5|ENO_SALG2 3h8a_D Enolase; Catalyzes the reversible conversion of 2-phosphoglycerate into phosphoenolpyruvate. It is essential for the degradation of carbohydrates via glycolysis.
9 sp|B5R9H4|F16PA_SALG2 2qvr_A Fructose-1,6-bisphosphatase class 1

Fig. 1: Receptor Ligand Interactions

Sl.NO Receptor Receptor Ligand Interaction
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A variety of compounds which are involved in the management of diseases of non-infectious etiology have shown some antimicrobial activity in vitro, against bacteria and other microorganisms (Tyski, 2003). Such compounds are called “non-antibiotics”. By the end of the nineteenth century, the dyes were known to possess antimicrobial activity, methylene blue (one of phenothiazines compounds) as an antimicrobial agent (Gutman and Ehrlich, 1891). So far, a lot of attention has been focused on thioxanthenes, phenothiazines and other agents with affinities to cellular transport systems which influence the structure of cellular membrane or ions transport etc. (Hendrics et al., 2003). In one study (Kruszewska et al., 2008), it was indicated that some of preparations inhibited growth of at least one of the four examined standard microbial strains. The drugs with the following active substances showed significant antimicrobial activity- amlodipine, acepromazine, butorphanole, cisapride, cisplatine, clomipramine, diltiazem, emadastine, fluvastatine, ketamine, levocabastine, matipranalol. methotrexate, nicergoline, perphenazine, proxymetacaine, sertraline, tegaserole, tetrahydrozoline, ticlopidine and tropicamide. In the present study in silico antimicrobial activity was positive for paracetamol, chlorephenaramine, chlorpromazine, thiamine, labetalol, finofibrate, topiramate, glucosamine, galantamine, L-glutamic acid, ethambutol, phenyleprine. Chen et al., 2002, confirmed that non- antibiotic compounds enhance the in vitro activity of certain antibiotics against specific bacteria. Moreover, the antimicrobial activity of such non antibiotic drugs emphasizes a necessity of the neutralization of their activity during the microbial purity tests of pharmaceutical products (Clonts,1998) This is the reason why any product should be validated towards its possible inhibition against microorganisms. In this study, we examined ligands with pure molecules which gave good scoring in virtual screening and the MIC values of these compounds were ranging from 0.2 to 14.5µg/ml. The less sensitivity of the compounds could be due to variation in the dosages and further dosage studies are required in this study.


Fowl typhoid is prevalent in commercial broiler flocks and is responsible for considerably high morbidity and mortality in affected flocks.In this study, Salmonella gallinarum isolates were found resistant to enrofloxacin, moxifloxacin, azithromycin, erythromycin, chloramphenicol and clindamycin, whereas cefpodoxime showed moderate sensitivity to Salmonella gallinarum. Surveillance, identification and antibiotic sensitivity of the prevalent Salmonella serotypes in the country would help devise suitable prevention and control program for this important poultry pathogen. Since the consumption of poultry products is often associated with salmonellosis, therefore, it becomes necessary to update information about Salmonella resistance to antibiotics used in poultry production.


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