Open Access

PknB remains an essential and a conserved target for drug development in susceptible and MDR strains of M. Tuberculosis

  • Anamika Gupta1,
  • Sudhir K. Pal1,
  • Divya Pandey1,
  • Najneen A. Fakir1,
  • Sunita Rathod1,
  • Dhiraj Sinha6,
  • S. SivaKumar2,
  • Pallavi Sinha3,
  • Mycal Periera4,
  • Shilpa Balgam5,
  • Gomathi Sekar2,
  • K. R. UmaDevi2,
  • Shampa Anupurba3 and
  • Vijay Nema1Email authorView ORCID ID profile
Contributed equally
Annals of Clinical Microbiology and Antimicrobials201716:56

https://doi.org/10.1186/s12941-017-0234-9

Received: 28 November 2016

Accepted: 10 August 2017

Published: 18 August 2017

Abstract

Background

The Mycobacterium tuberculosis (M.tb) protein kinase B (PknB) which is now proved to be essential for the growth and survival of M.tb, is a transmembrane protein with a potential to be a good drug target. However it is not known if this target remains conserved in otherwise resistant isolates from clinical origin. The present study describes the conservation analysis of sequences covering the inhibitor binding domain of PknB to assess if it remains conserved in susceptible and resistant clinical strains of mycobacteria picked from three different geographical areas of India.

Methods

A total of 116 isolates from North, South and West India were used in the study with a variable profile of their susceptibilities towards streptomycin, isoniazid, rifampicin, ethambutol and ofloxacin. Isolates were also spoligotyped in order to find if the conservation pattern of pknB gene remain consistent or differ with different spoligotypes. The impact of variation as found in the study was analyzed using Molecular dynamics simulations.

Results

The sequencing results with 115/116 isolates revealed the conserved nature of pknB sequences irrespective of their susceptibility status and spoligotypes. The only variation found was in one strains wherein pnkB sequence had G to A mutation at 664 position translating into a change of amino acid, Valine to Isoleucine. After analyzing the impact of this sequence variation using Molecular dynamics simulations, it was observed that the variation is causing no significant change in protein structure or the inhibitor binding.

Conclusions

Hence, the study endorses that PknB is an ideal target for drug development and there is no pre-existing or induced resistance with respect to the sequences involved in inhibitor binding. Also if the mutation that we are reporting for the first time is found again in subsequent work, it should be checked with phenotypic profile before drawing the conclusion that it would affect the activity in any way. Bioinformatics analysis in our study says that it has no significant effect on the binding and hence the activity of the protein.

Keywords

PknB M. tuberculosis ConservationMultidrug resistantMutationSequencing

Background

The emergence of multi-drug and extensively drug resistant strains (MDR & XDR) of Mycobacterium tuberculosis (M.tb) has highlighted the need for new drugs to treat tuberculosis (TB). As the targets of current drugs are modified by the resistant organisms, newer targets which remain conserved in clinical isolates remain the choice for drug development. Serine/threonine protein kinases (STPK) remain one such target that plays important roles in mycobacterial cellular processes, including cell division, cell wall synthesis, cell metabolism, etc. [1]. Protein kinases A and B, encoded by pknA and pknB, respectively, are part of the operon carrying cistrons coding for protein phosphatase pstP, rodA (involved in cell shape control), and pbpA (involved in peptidoglycan synthesis). This locus is found near the origin of replication throughout the Mycobacterium genus [2]. Both these kinases have been found to be essential based on transposon-insertion experiments [3]. A role for PknB as a replication switch in response to hypoxia has been proposed with its essential role in reactivation of cells from the hypoxic state [4]. Hence, the Ser/Thr protein kinase PknB is proved to be essential for sustaining mycobacterial growth and this support the idea of the development of protein kinase inhibitors as new potential anti-tuberculosis drugs. However, to the best of our knowledge, not much work has been done for exploring the conservation of these genes in clinical isolates. In the present study, we probed the conservation pattern of the target region by sequencing this gene in clinical strains of M.tb and verified the same by deciphering the role of mutation in the drug-protein interactions in the PknB protein of M.tb using bioinformatics analysis. These isolates were either susceptible or resistant to the drugs being used currently and had different spoligotypes.

Methods

Ethics permission

The study was approved by the institutional ethics committee and all the experiments were undertaken by the trained staff at BSL3 facility.

Isolates used

A total of 116 Mycobacterium tuberculosis isolates were obtained from three different geographical regions of India, viz., Pune (Western India), Varanasi (Northern India) and Chennai (Southern India). Also, two sets of isolates were obtained from Pune wherein set 1 was an older collection of the isolates (2006–2007) and set 2 was a recent collection (2012–2013). Isolates from Chennai and Varanasi were collected during 2013–2014 (Table 1).
Table 1

Demographic and laboratory profile of the isolates used

Sr. no.

Study no.

HIV

Age

Sex

Collection date

Drug susceptibility profile (MGIT)

Spoligotype

Mutations in pknB gene

1

N1

N

35

F

6/3/2006

Susceptible

T1-53

Nil

2

N2

N

50

F

17/03/2006

Susceptible

Orphan

Nil

3

N3

N

30

M

24/03/2006

Susceptible

EAI5-355

Nil

4

N4

N

50

M

27/03/2006

Susceptible

EAI3_IND-11

Nil

5

N5

N

22

F

29/03/2006

Susceptible

CAS1_DELHI-26

Nil

6

N6

N

38

M

28/04/2006

Susceptible

CAS1_DELHI-26

Nil

7

N7

N

55

F

8/5/2006

Susceptible

CAS-486

Nil

8

N8

N

29

F

15/06/2006

Susceptible

CAS-357

Nil

9

N9

N

23

M

16/06/2006

Susceptible

MANU2-1634

Nil

10

N10

N

23

M

19/06/2006

Susceptible

EAI5-126

Nil

11

N11

N

40

F

27/06/2006

Susceptible

CAS1_DELHI-427

Nil

12

N12

N

28

M

29/06/2006

Susceptible

T3-37

Nil

13

N13

N

40

M

29/06/2006

Susceptible

CAS1_DELHI-25

Nil

14

N14

N

24

M

10/10/2006

Susceptible

CAS1_DELHI-26

Nil

15

N15

N

22

M

20/10/2006

Susceptible

EAI1_SOM-48

Nil

16

N16

N

25

F

11/5/2006

S,H

T2-52

664 (GTC-ATC)

17

N17

N

32

M

5/7/2006

S,H,R

Orphan

Nil

18

N18

N

30

M

12/9/2006

S,H,R

CAS2-288

Nil

19

N19

N

21

M

22/09/2006

S,H

T3-37

Nil

20

N20

N

27

M

27/09/2006

S

Orphan

Nil

21

N21

N

42

M

31/10/2006

S

EAI5-126

Nil

22

N22

N

26

M

15/01/2007

S,H

Orphan

Nil

23

N23

N

21

M

18/01/2007

H

H3-99

Nil

24

N24

N

38

M

22/01/2007

S,H,E

CAS1_DELHI-26

Nil

25

N25

N

45

F

31/01/2007

H

CAS1_DELHI-26

Nil

26

N26

P

32

M

7/2/2007

S,H,R

T2-1077

Nil

27

N27

P

40

M

7/3/2007

S,H

CAS2-288

Nil

28

N28

N

50

M

8/3/2007

S

H3-99

Nil

29

N29

P

35

M

8/3/2007

H

Orphan

Nil

30

S1

NT

35

M

27/03/2013

Susceptible

CAS1_DELHI-26

Nil

31

S2

NT

27

M

3/4/2013

Susceptible

T1-53

Nil

32

S3

NT

50

M

3/4/2013

Susceptible

Orphan

Nil

33

S4

NT

24

M

3/4/2013

H,R,E,OFX

Orphan

Nil

34

S5

NT

38

M

4/4/2013

S,H,R,E

BEIJING-1

Nil

35

S6

NT

45

M

5/4/2013

R,H

T1-53

Nil

36

S7

NT

31

M

8/4/2013

Susceptible

T1-53

Nil

37

S8

NT

50

M

3/4/2013

R,H

CAS1_DELHI-1789

Nil

38

S9

NT

35

M

8/4/2013

Susceptible

Orphan

Nil

39

S10

NA

55

M

8/4/2013

OFX

MANU1-100

Nil

40

S11

NA

NA

NA

NA

S,H,E,OFX

BEIJING-1

Nil

41

S12

P

40

F

2012–2013

Susceptible

EAI3_IND-11

Nil

42

S13

P

NA

NA

2012–2013

Susceptible

CAS1_DELHI-26

Nil

43

S14

P

35

M

2012–2013

Susceptible

CAS1_DELHI-26

Nil

44

S15

P

48

F

2012–2013

H

CAS1_DELHI-26

Nil

45

S16

P

26

M

2012–2013

H,R

CAS1_DELHI-26

Nil

46

S17

P

30

F

2012–2013

H

CAS1_DELHI-26

Nil

47

S18

P

31

M

2012–2013

H,R,OFX

Orphan

Nil

48

S19

P

36

M

2012–2013

H

Orphan

Nil

49

S20

P

23

M

2012–2013

H

Orphan

Nil

50

C1

NT

NA

NA

2013

R,H, OFX

T5-1268

Nil

51

C2

NT

NA

NA

2013

R,H

EAI3_IND-11

Nil

52

C3

NT

NA

NA

2013

R,H

BEIJING-1

Nil

53

C4

NT

NA

NA

2013

R,H,OFX

Orphan

Nil

54

C5

NT

NA

NA

2013

R,H

Orphan

Nil

55

C6

NT

NA

NA

2013

R,H,OFX

CAS1_DELHI-381

Nil

56

C7

NT

NA

NA

2013

R,H

T1–T2-78

Nil

57

C8

NT

NA

NA

2013

R,H,OFX

T2-52

Nil

58

C9

NT

NA

NA

2013

R,H,OFX

Orphan

Nil

59

C10

NT

NA

NA

2013

R,H,OFX

Orphan

Nil

60

C11

NT

NA

NA

2013

R,H

T1-53

Nil

61

C12

NT

NA

NA

2013

R,H

Orphan

Nil

62

C13

NT

NA

NA

2013

S,H,R,E,OFX

Orphan

Nil

63

C14

NT

NA

NA

2013

Susceptible

CAS1_DELHI-26

Nil

64

C15

NT

NA

NA

2013

S,H,E

T2-52

Nil

65

C16

NT

NA

NA

2013

S,H,R,E

Bejing-1

Nil

66

C17

NT

NA

NA

2013

S,E

CAS1_DELHI-26

Nil

67

C18

NT

NA

NA

2013

S,E

Orphan

Nil

68

C19

NT

NA

NA

2013

S

Orphan

Nil

69

C20

NT

NA

NA

2013

S

Orphan

Nil

70

C21

NT

NA

NA

2013

Susceptible

EA15-934

Nil

71

C22

NT

NA

NA

2013

S,H,R,E

EA15-934

Nil

72

C23

NT

NA

NA

2013

Susceptible

EAI3_IND-11

Nil

73

C24

NT

NA

NA

2013

Susceptible

Orphan

Nil

74

C25

NT

NA

NA

2013

Susceptible

Bejing-1

Nil

75

C26

NT

NA

NA

2013

S,H,R,E

 

Nil

76

C27

NT

NA

NA

2013

Susceptible

T1-804

Nil

77

C28

NT

NA

NA

2013

H

EAI3_IND

Nil

78

C29

NT

NA

NA

2013

Susceptible

EAI3_IND

Nil

79

C30

NT

NA

NA

2013

S,H,R,E,OFX

Orphan

Nil

80

C31

NT

NA

NA

2013

Susceptible

Orphan

Nil

81

C32

NT

NA

NA

2013

Susceptible

CAS1_DELHI

Nil

82

C33

NT

NA

NA

2013

S,H, OFX

Bejing-1

Nil

83

C34

NT

NA

NA

2014

Susceptible

EAI3_IND-11

Nil

84

C35

NT

NA

NA

2014

S,H,OFX

Orphan

Nil

85

C36

NT

NA

NA

2014

OF

U-1391

Nil

86

C37

NT

NA

NA

2014

Susceptible

EAI3_IND-11

Nil

87

C38

NT

NA

NA

2014

Susceptible

EAI3_IND-11

Nil

88

C39

NT

NA

NA

2014

R

EAI3_IND-11

Nil

89

C40

NT

NA

NA

2014

Susceptible

Orphan

Nil

90

C41

NT

NA

NA

2014

Susceptible

EAI3_IND-11

Nil

91

B1

N

18

F

2013–2014

S,H,R,E,OFX

BEIJING-1

Nil

92

B2

N

20

M

2013–2014

S,H,R,E,OFX

H1-47

Nil

93

B3

P

25

F

2013–2014

S

LAM2–LAM4-194

Nil

94

B4

N

25

M

2013–2014

S,H,R,E, OFX

LAM-9

Nil

95

B5

N

40

M

2013–2014

S,H

CAS2-288

Nil

96

B6

N

25

M

2013–2014

Susceptible

Orphan

Nil

97

B7

N

47

M

2013–2014

S,H,R,E

Orphan

Nil

98

B8

N

30

M

2013–2014

S,H,R,E

BEIJING-1

Nil

99

B9

N

20

M

2013–2014

S,H,R,E,OFX

T1-53

Nil

100

B10

N

21

M

2013–2014

H,R

Orphan

Nil

101

B11

N

45

M

2013–2014

H,R,OFX

BEIJING-1

Nil

102

B12

N

23

M

2013–2014

S,H

T1-53

Nil

103

B13

N

23

M

2013–2014

Susceptible

EAI1_SOM-235

Nil

104

B14

N

22

F

2013–2014

S,H,R,OFX

CAS1_DELHI

Nil

105

B15

N

22

F

2013–2014

S,H,R,E,OFX

CAS1_DELHI

Nil

106

B16

N

70

M

2013–2014

H,R,OFX

Orphan

Nil

107

B17

N

9

F

2013–2014

H,R,E,OFX

BEIJING-1

Nil

108

B18

N

19

M

2013–2014

H,R,E

Orphan

Nil

109

B19

N

25

F

2013–2014

H

T1-53

Nil

110

B20

P

45

F

2013–2014

Susceptible

BEIJING-1

Nil

111

B21

N

30

F

2013–2014

S,H,R,E,OFX

BEIJING-1

Nil

112

B22

N

18

F

2013–2014

S,H,R,E,OFX

BEIJING-1

Nil

113

B23

N

46

F

2013–2014

S

Orphan

Nil

114

B24

N

50

M

2013–2014

H,R,OFX

BEIJING-1

Nil

115

B25

N

NA

NA

2013–2014

OFX

T1-1567

Nil

116

B26

N

NA

NA

2013–2014

H,S

U-172

Nil

N1–N29 isolates obtained from NARI, Pune; S1–S20 isolates obtained from STDC, Pune, Maharashtra; C1–C40 isolates obtained from NIRT, Chennai, Tamil Nadu; B1–B26 isolates obtained from BHU, Varanasi, Uttar Pradesh

NIRT National Institute for Research in Tuberculosis, BHU Banaras Hindu University, STDC State TB Training and Demonstration Centre, S resistant to streptomycin, H resistant to isoniazid, R resistant to rifampicin, E resistant to ethambutol, OFX resistant to ofloxacin, N negative, NT not tested, NA information not available

Sub-culturing

Upon arrival to our laboratory, the isolates were sub-cultured on Löwenstein-Jensen (LJ) medium and incubated till sufficient growth was indicated by typical non-pigmented, rough, dry colonies.

Drug susceptibility testing

Isolates were subjected to drug susceptibility testing on BACTEC™ MGIT™ 960 Mycobacterial Detection System (BD, NJ, USA) using SIRE kit for the susceptibility testing against streptomycin (S), isoniazid (I), rifampin (R) and ethambutol (E). For susceptibility testing against ofloxacin, blank tubes of medium were used wherein the final concentration of ofloxacin was kept to 2 μg/ml as per the CLSI standards using filtered stock solution of the drug. The inoculum was prepared from fresh LJ medium by following the methods used by Devasia and co-workers [5]. A growth control containing no antibiotic and a sterile control without inoculation were also used with every set of experiment.

DNA isolation and amplification of pknB gene

Genomic DNA isolation was done from freshly sub-cultured isolates using a cetyltrimethyl ammonium bromide (CTAB) based modified method as reported by earlier workers [6, 7]. The DNA so obtained was quantitated using NanoDrop 1000 spectrophotometer (Thermo, USA) and purity and integrity were checked on 0.8% agarose gel after electrophoresis. A length of 876 bp covering the cytosolic portion of the protein was amplified using forward primer as AATGACCACCCCTTCCCA and reverse primer as TCGGCA TCGGTGAGCACTTT designed with Mycobacterium tuberculosis H37Rv (NC_000962;16594-17469) as a template. The amplification reaction was done using KAPA HiFi DNA Polymerase (KAPA Biosystems, USA) using manufacturer’s instructions and annealing at 65 °C.

Spoligotyping

Spoligotyping was performed using the standard method at National Institute for Research in Tuberculosis, Chennai [8]. In brief, the spacers between the direct repeats in the target region were amplified by using a primer set, primer Dra 5′-CC AAG AGG GGA CGG AAA C-3′ and biotinylated primer Drb 5′-GGT TTT GGG TCT GAC GAC-3′. The polymerase chain reaction (PCR) products were then hybridized to a Biodyne C membrane (Isogen Bioscience). This membrane contains immobilized synthetic oligomeric spacer sequences derived from the direct-repeat region of M. tuberculosis H37Rv and Mycobacterium bovis BCG. Hybridized DNA was detected using an enhanced chemiluminescence kit (Amersham International), with exposure to X-ray film producing a pattern or profile reminiscent of a bar code. These were matched with the SITVIT web database to get spoligotypes matched with available profiles (http://www.pasteur-guadeloupe.fr:8081/SITVIT_ONLINE/).

Sequencing and sequence analysis

For sequencing of the amplified gene of pknB, same primers which were used for amplification were employed. The sequencing of plasmid DNA was carried out using Big Dye Terminator v. 3.1 cycle sequencing kit and an ABI 3730xl DNA analyzer, according to the manufacturer’s protocol. Nucleotide sequence analysis and curing were done using Applied Biosystem SeqScape v.2.5. The cured sequences were compared for sequence similarities using Rv0014c from NC_000962 as a template in SeqScape software.

Bioinformatics analysis

Based on sequencing of the pknB gene, the sequence that showed mutation was taken for bioinformatics analysis to access the impact of the change. Molecular dynamics simulations (MD) tool have potential to provide detailed information on the fluctuations and conformational changes of proteins and hence was used here. MD-simulations were performed to the docked complex to evaluate the stability, conformational changes and getting insights into the natural dynamic in solutions. MD-simulations were performed using GROMACS version-4.6.4 [911], with the AMBER99SB force field [12]. The ligand was parameterized by applying the standard RESP procedure using Antechamber [13], where charges for free ligand were derived from HF/6-31G* calculation in Gaussian03 [14]. Histidine residues were assumed to be charged, with the ND and NE atoms protonated; Arginine and Lysine residues were assumed to be protonated. All systems were solvated using explicit TIP3P water model [15], in a cubic box with a margin of 10 Å and neutralized by adding Sodium counter-ions. The Particle-Mesh Ewald method was applied to calculate long-range electrostatic interactions with a cutoff distance range of 10 Å, [16] and a Lennard-Jones 6–12 potential was used to evaluate van-der-Waals interactions within the cut-off range of 10 Å. The LINCS algorithm of fourth order expansion was used to constrain bond lengths [17]. After solvation and neutralization, each system was energy minimized for 10,000 steps using steepest-descent optimization method to remove poor van-der-Waals contacts in the initial geometry. After minimization, two stages of equilibration were conducted. First, the system was equilibrated for 100 ps with position restraints of 10,000 kJ/mol on all heavy atoms. A constant temperature of 300 K was maintained using the V-rescale algorithm [18], with a coupling time of 0.1 ps and separate baths for the solute and the solvent. Second, the pressure was kept constant at 1 bar using the Parrinello–Rahman pressure coupling scheme with a time constant of 2 ps [19]. Initial velocities were generated randomly using a Maxwell–Boltzmann distribution corresponding to 300 K. Neighbor lists were updated every 10 fs using a group cut-off scheme. Finally, the production run was performed for 100 ns without restraints at 300 K in the isothermal-isobaric ensemble.

Interaction analysis was performed using g_dist tool in the GROMACS package to measure the inter-atomic distances. The g_rms tool of the GROMACS package was used to calculate the root mean square deviations (RMSD) during the trajectories taking the minimized crystal structure as a reference. Root mean square fluctuations (RMSF) of the backbone of each residue were calculated by g_rmsf while g_mmpbsa tool is used to calculate the binding energy.

Results

DST and spoligotypes

The isolates had a variety of characteristics in terms of drug resistance to the drugs (SIRE/SHRE) with ofloxacin and spoligotypes as elaborated in Table 1. As obtained in Table 1, isolates used in the study ranged from pan-susceptible to complete resistance towards the tested drugs. The same stands true for their spoligotypes, reflecting different dominances in different geographical locations with more of Beijing strains in recent isolates.

Sequencing results

No mutation, except in one, could be observed in the region sequenced. A single mutation that was found was G to A resulting in the change of amino acid from Valine (GTC) to Isoleucine (ATC) in isolate N16. The isolate showed a change in one nucleotide as compared with wild-type sequence at the 664th position from the start of the codon i.e. A (TG….); this corresponds to the position 16,807 of the template. The sequence was submitted to NCBI and have Genbank accession number as KX029321. This change is reported as Non-synonymous SNP in Polytb (http://pathogenseq.lshtm.ac.uk/polytb) and GMTV (http://mtb.dobzhanskycenter.org/) SNP databases. However, the isolation sites were other than India, spoligotypes were different and no comment on its impact on protein structure or function could be found.

MD simulations results

The conformation achieved from 100 ns of simulation is more stable and credible than docked conformations. This can be justified by the fact that docking methods have some inherent pitfalls and approximations. However, MD-simulations represent more realistic conditions with the physiological environment. Therefore, the binding orientation of Mitoxantrone (ligand) predicted through MD-simulations shows better correlation to their biologically active state. The structural and dynamical property of the complex has been analyzed through the trajectories obtained from the MD-simulations. The trajectory data of complex were plotted for energy, RMSD, and RMSF and the interaction analysis of the ligand have been done within the binding pocket.

The potential energy of the system is quite stable throughout the simulations as shown in Fig. 1. The trajectories reveal that secondary structure of the protein is maintained throughout the simulation. RMSD plot in Fig. 2 shows that after an initial equilibration period of about 25 ns the system reached a plateau and the RMSD value never crossed the mark of 3.5 Å from the initial structure in the entire simulation of 100 ns. The flexibility of the structure is measured in terms of RMSF. Figure 3 demonstrates the flexibility of backbone with respect to an average structure which is below 2 Å. Only for loops it is a little bit higher and reaches a maximum of 3 Å. The interactions which are responsible for keeping the ligand inside the pocket are analyzed by a number of H-bond interactions. Figure 4 reveals that average 3 H-bonds between 2FUM protein and the ligand, Mitoxantrone, is quite persistent and sometimes 4 H-bonds were also seen which reached a maximum of 6–8. Further, we analyzed the particular residue responsible for these interactions as well.
Fig. 1

Energy plot of MD simulations for protein–ligand (Mitoxantrone) complex as a function of time

Fig. 2

Root mean square deviation (RMSD) of Protein of C-alpha atoms with respect to the time over the course of 100 ns of MD simulation

Fig. 3

Root mean square fluctuation (RMSF) of residue backbone with respect to the average structure during the course of 100 ns of MD simulations

Fig. 4

Average number of Hydrogen bond between ligand and protein during the entire 100 ns of simulations

Interaction analysis

The persistence of interaction is quantified by distance analysis between particular residues in the binding pocket with the specific atoms of Mitoxantrone. Figure 5 reveals the most persistent interaction found in simulations of 100 ns. Figure 5a shows the interaction of MET-155 with the ligand in which after initial equilibration period of 40 ns the interaction is quite stable and distance is below 3 Å while with VAL-25 it is quite persistent (about 3.75 Å) from the beginning of the simulation. The most surprising interaction found with ALA-142 with the ligand. Figure 5c shows that initially residue was distant (~7 Å apart) but after equilibration time the conformation of protein switched in a manner that ALA-142 started interacting with the ligand. Similarly, Fig. 5d also shows that initially the residue MET-92 was distant from the ligand but after equilibration time the conformation of protein switched in a manner that MET-92 started interacting with the ligand. These interactions were the major binding source for the ligand in the binding cavity.
Fig. 5

Interaction of residues with the ligand. a Interaction of Methionine-155 with the ligand. b Interaction of Valine-25 with the ligand. c Interaction of Alanine-142 with the ligand d Interaction of Methionine-142 with the ligand

MMPBSA results

The binding energy of the ligand is calculated by MMPBSA method which is allowing the calculation of non-bonded interactions i.e., Van-der-Waal and the electrostatic terms between two sets of atoms along the length of trajectory. Each snapshot from every nanosecond was taken for our calculations. The method also allowed the calculation of polar solvation energy and SASA energy as well. In our calculation, the overall binding energy of ligand with the protein is −71.564 kJ/mol, where negative term confirms substantial affinity of the receptor for the ligand. It also confirms our molecular dynamics simulation results. In residue-wise contribution in the binding, MET-155 plays a key role and shows maximum contribution. Our interaction analysis shows persistent interaction with the ligand (Table 2). This critical residue may provide guidance for the rational design to discover a more potent drug (Fig. 6).
Table 2

MMPBSA calculation results

Energetic contributions

KJ/mol

Van-der-Waal energy

−225.117 ± 11.889

Electrostatic energy

−93.523 ± 15.703

Polar solvation energy

268.278 ± 23.834

SASA energy

−21.201 ± 0.721

Binding energy

−71.564 ± 19.084

Fig. 6

The orientation of Mitoxantrone before simulation in blue while after a simulation in red. Interaction of residue shown with side chains. Protein is represented in tube (grey colour) in both the figures (a, b)

Discussion

The M.tb genome encodes 11 serine/threonine protein kinases (STPK) which offer attractive targets for inhibitor development [20]. PknB is part of the 11 eukaryotic-like serine–threonine protein kinases listed as an essential protein in the M.tb TraSH and NGS datasets [21]. The necessity of pknB was verified by gene knockdown experiments, which showed a remarkable decrease in bacterial viability in liquid culture upon depletion of the kinase [22]. According to Ortega and co-workers, pknB provides a highly potential drug target against Mtb as it controls both the active replicating and latent nonreplicating forms of Mtb [4]. They tested the role of serine/threonine protein kinases—signaling molecules and found that kinase depletion led to decrease in bacterial viability and they specifically identified the PknB kinase as a critical regulator of the oxygen-dependent replication switch. These data show that signaling through PknB modulates the growth and replication state of Mtb in response to oxygen. Therefore, it can also be a valuable drug target for latent TB infection.

PknB has autophosphorylation properties [23], with a cross-phosphorylation potential of other STPKs such as PknA, and PknG [24]. Moreover, PknB seems to control major metabolic pathways directly via phosphorylation of multiple protein substrates, such as the protein regulator GarA that halts the TCA cycle [25], the KasA/B proteins involved in the biosynthesis of the essential mycolic acid [26], and the Wag31 proteins involved in cell division and morphology [27]. Likewise, virulence factors SigH and RshA [28], and cell wall biosynthetic enzymes GlmU or PBPA are also influenced [29, 30]. Thus, PknB is established as an important participant and a regulator of cell division and growth in M. tuberculosis proving its essentiality. However, there are no studies, to the best of our knowledge to say about the conservation status of this gene in clinical isolates with existing pressure of drugs being used for other targets.

This study tried to survey the same by sequencing the most important region of the cytoplasmic domain that participates in ligand/inhibitor binding. The crystal structure studies demonstrated that mitoxantrone is an ATP-competitive inhibitor of PknB and Leu17, Gly18, Val25, Ala38, Met 92, Glu93, Tyr94 and Val95 in the N-terminal lobe, Met145 and Met155 in the C-terminal lobe are the important residues taking part in the complex formation [31]. Moreover, we used high fidelity enzyme for amplification of pknB gene from genomic DNA to ensure error-free amplification before sequencing.

Conclusions

In our study, pknB was confirmed to be conserved, even in clinical isolates with different drug resistance and spoligotype profile. This was observed in sequencing experiments with 116 clinical isolates having susceptibility profiles ranging from multidrug resistant isolates with resistance to individual drugs including fluoroquinolones to the ones with complete susceptibility towards tested drugs. The choice of clinical strains of M.tb to probe the conservation pattern of the target region is the best strategy because of different drug exposures to them along with host’s immune pressure. Such isolates are under pressure to acquire drug resistance by the modification of the drug targets. Bioinformatics studies using hypothetical mutations in binding sites were also done to access the mutations which may disturb the drug binding and induce resistance. The absence of mutations in overall sequence including putative drug binding domains proved that pknB remain a good target for drug development. Even the highly resistant isolates did not have any mutations in this region. This also reveals that sequences in pknB are not influenced by the change in other genomic regions. However, a study is required to see if constant usage of inhibitors of this particular protein exerts a selection pressure and how susceptible is the target for mutations under specific drug pressure.

Notes

Declarations

Authors’ contributions

AG: Execution of the work in the laboratory, manuscript review. SKP: Bioinformatics work, manuscript review. DP: Execution of the work in the laboratory. NAF: Execution of the work in the laboratory. SR: Execution of the work in the laboratory. DS: Bioinformatics work. SS: Spoligotyping of the isolates. PS: Collection and identification of isolates from BHU. MP: Collection and identification of isolates and their details from NARI. SB: Collection and identification of isolates and their details from STDC. GS: Collection and identification of isolates and their details from NIRT. KRU: Manuscript review; isolates and their details from NIRT. SA: Manuscript review; isolates and their details from BHU. VN: Principle Investigator of the project, conception of the work, manuscript writing and review. All authors read and approved the final manuscript.

Acknowledgements

Authors are thankful to Director, NARI, Director, NIRT, Joint Director of Health Services (Leprosy and TB), Pune and CMO, STDC, Pune for their kind support in obtaining isolates and related information for this study.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

The datasets generated and/or analysed during the current study are available with the PI of the study and segregated data about the isolates is available with the authors from different institutes as listed in the author’s list. A detailed report with data has been submitted to funding agency (ICMR) also.

Consent for publication

Not applicable.

Ethics approval and consent to participate

The study was approved by institutional ethics committee.

Source of funding

This work was supported by Indian Council of Medical Research (extramural Grant No. AMR/45/2011-ECD-I).

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Authors’ Affiliations

(1)
Department of Molecular Biology, National AIDS Research Institute
(2)
National Institute for Research in Tuberculosis
(3)
Department of Microbiology, Institute of Medical Sciences, Banaras Hindu University
(4)
Department of Microbiology and Clinical Pathology, National AIDS Research Institute
(5)
Intermediate Reference Laboratory State TB Training and Demonstration Centre (STDC) Pune
(6)
Department of Bioinformatics, IIDS, Nehru Science Center, University of Allahabad

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