Purification of Mt-ppa protein
The Mt-ppa gene was cloned into pPRO-EX-HTc using BamHI and XhoI restriction site in forward and reverse primer respectively. Mt-ppa was over expressed in the BL-21 (DE3) strain with an N terminal His-tag. The protein was induced by adding 1mM IPTG after OD600 0.8 and induction was checked by SDS PAGE analysis. The protein was purified with 80% purity and purified band appear at 18kDa. Purified Mt-ppa+His was concentrated and quantified by Bradford assay to a concentration of to 1mg/ml (Figure 1a).
3.1.1 Thermodynamic analysis of Mt-ppa and GTP interaction
Isothermal calorimetry was used to determine the type of interaction and heat involved for optimum interaction between Mt-ppa and GTP. The data was analyzed by fitting the heat burst curve in one site binding model. The stoichiometry (N) and dissociation constant (Kd) of the interaction were 10 and 37.9±7µM (Figure 1b). The heat was released in the form of enthalpy change (ΔH) which is -11±1.2kcal/mol. ΔG was -6.3kcal/mol and - TΔS was -4.96 kcal/mol (Figure 1c).
STRING and STITCH servers were used to detect the protein-protein and protein-chemical interaction. STRING showed the prominent interaction with ATP synthase family (atpA, atpB, atpC, atpD, atpE, atpF, atpG and atpH), galU, Ppk1 and ppk2. The scores for all interactive partners were 0.9 (Figure 2a). STITICH server showed the interaction with phosphate, pyrophosphate, fluoride, calcium ion, glycerol with scores as 0.991, 0.965, 0.954, 0.954 and 0.946 respectively. The scoring of all interactions showed a strong interaction between protein- protein and protein-compound (Figure 2b).
COACH server is a meta server-based approach that was used for prediction of ligand binding site in the protein. COACH server works on two mechanisms known as TM-site and S- site that recognized ligand binding template from the BioLip database. The server found the top ligand that bind to the ppa were sulphate ion, phosphate ion, potassium ion, calcium ion and Manganese ion. The topmost confidence scores (C score) were 0.39 and 0.33 for sulphate and phosphate ion respectively. The consensus residues where sulphate ion binds are 16, 30, 84, 126 and 127 and where phosphate ion binds are 16, 30, 42, 57, 84, 89, 91, 126 and 127. The TM site prediction was also cleared the binding of the protein with phosphate, sulphate and magnesium ions with C score of 0.29, 0.28 and 0.26 respectively. The S site results also found the interaction of manganese, phosphate and sulphate ions with C score 0.33, 0.24 and 0.20 respectively. In the COFACTOR outcome, the TM score were 0.970, 0.969 and 0.968 for calcium, manganese and phosphate ions respectively.
The impact of point mutations on the action and ability of Mt-ppa was assessed by utilizing sequence- based changes. The mutations were done utilizing EASE-MM, PROVEAN, I-Mutant and DynaMut servers. It is now a well-established actuality that point mutations are the significant aspect for certain diseases because of their affectability in affecting protein structure and function. Considering energy change in thermodynamics, a protein can stay stable which is in the folded state, or it is in the unfolded state that is also known as the unstable state of the protein. The distinction of energy between folded and unfolded states can be determined by Gibbs free energy ΔG=Gu−Gf, where Gu and Gf are without gibbs energy of unfolded and folded states separately. Another method used to measure change in Gibbs free energy of mutated and wild type protein is appeared by ΔΔG where, ΔΔG =ΔGm–ΔGw (ΔGm= Gibbs free energy of freak and ΔGw= Gibbs free energy of wild kind protein).
On the basis of EASE-MM result which requires protein sequence information gives possibility of effect of mutations on each residue by changing into every other residue. The server gives top 30 mutations with highest destability. W102G, V150G, F44G, I119G, L93F, F3G, F122G, I108G, L32G, M82G, Y17G, L59G, V5G, V26G, I7G, W140D, W140G, W140A, F80G, W140S, L49G, L56G, I9G, V60G, V19G, V92G, L28G, L61G, Y126E and F123G are the top 30 hits by EASE-MM server by setting a cutoff ΔΔG value of -4.0 (Table 1). In addition to the above-mentioned mutational hits, mutations were also carried out on active site residues. As Mt-ppa is a pyrophosphatase and carried out its work based on active site configuration, therefore mutations on the active side residues must be checked. There are 5 residues that are present in the active site as Y126G, Y42G, R30G, E8G and K16G (Table 2). Mutations at all active site residues showed a destabilized effect with the highest destabilizing effect of Y126G.
All mutational hits resulted from EASE-MM server were also checked by PROVEAN server that proved a mutation as deleterious or non-deleterious. The PROVEAN resulted in highest destabilized mutations of ppa i.e. W140D, W140A, W140S, W140G, Y17G, F122G, F123G and Y126E (Table 1). Mutations on active site residues Y126G, Y42G, R30G, E8G and K16G were also showed a destabilized effect with the highest destability at Y126G (Table 2).
Similarly, all 30 mutational hits were also checked by I-MUTANT 3.0 server and the result outcome showed that L28G, L32G, I7G, V26G, L93F, I119G, F122G, I108G, L59G, F80G, I9G and V19G (Table 1). Active site residue mutation showed destability at all point changes with the highest destability at K16G (Table 2).
Stress based mutation analysis was done by changing the pH and temperature from the optimum range to see if protein would attain stability or destability in different conditions. Increasing temperature from 40C to 600C (Table 3) showed a decrease in destability and increasing pH from 3 to 13 (Table 4) also showed a decrease in stability till pH 7 and slightly increase in stability after pH 7 to 13.
Phosphorylation site prediction
Protein phosphorylation controls an enormous assortment of biological processes in every living cell. In pathogenic microorganisms, the investigation of serine, threonine, and tyrosine (Ser/Thr/Tyr) phosphorylation has revealed insight into the course of infectious diseases, from adherence to have cells to microbial pathogenesis, replication, and ingenuity. Mass spectrometry (MS)-based phosphoproteomics has given worldwide guides of Ser/Thr/Tyr phosphor sites in bacterial microorganisms. The NetPhos3.1 server predicts serine, threonine or tyrosine phosphorylation positions in eukaryotic proteins utilizing outfits of neural organizations. Both conventional and kinase explicit predictions are performed. The initial region shows the name and length of the sequence followed by the amino acid sequence. At that point follows a task field depicting the anticipated class for every residue. If the residue is predicted NOT to be phosphorylated, either because the score is below the threshold or because the residue is not Ser/Thr/Tyr, that position is marked by a dot ('.'). Residues having a prediction score above the threshold are indicated by 'S', 'T' or 'Y', respectively (Table 5).
The Epitopic recognition
B cell epitope prediction was done by BCpred server which detects the amino acid chain of length 7-10 amino acids that are indulged in epitope like function. In BCpred there were 4 epitopes were found of length 20 amino acids at different positions. The epitopes were as AADWVDRAEAEAEVQRSVER at position 137 with score 0.996, EHGGDDKVLCVPAGDPRWDH at position 85 with score 0.99, DVTIEIPKGQRNKYEVDHET at position 4 with score 0.921 and TPMAYPTDTGFIEDTLGDDG at position 34 with score 0.891. Another tool known as ABCpred was also used to the same information. The predicted B cell epitopes are ranked according to their score obtained by trained recurrent neural network.
Higher score of the peptide means the higher probability to be as epitope. The threshold value was set at 0.51 and epitope length of 16 amino acids. The top four epitopes were FRMVDEHGGDDKVLCV, GVLVAARPVGMFRMVD, DVTIEIPKGQRNKYEV and FFVHYKDLEPGKFVKA at position 80, 69, 4 and 122 and with score 0.93, 0.90, 0.88 and 0.88 respectively. HLA pred was used determine T cell epitope in combination with MHC-II molecule. The top ten epitopic regions were DLEPGKFVK, FELDAIKHF, FRMVDEHGG, GKFVKAADW, IKHFFVHYK, LLPQPVFPG, LPQPVFPGV, LVAARPVGM, LVLLPQPVF and LVLLPQPVF. A list os top epitopes were given in Table 6.
Screening of compounds against Mt-ppa (1wcf)
Screening of ZINC herbal compound database
Mt-ppa is an essential gene for in vitro and in vivo survival of Mycobacterium tuberculosis. Mt-ppa also provides advanced endurance mechanisms to the bacterium. Virtual screening was performed using docking to select the potent natural and synthetic inhibitor. We had used subset of Zinc database library known as Herbal ingredients targets (HITs) to select the herbal ingredient compound. Screening was performed by targeting the residues of active site and the results were generated. Among the 750 compounds from Zinc database of herbal ingredients, all compounds were successfully and Compound ZINC000003780340 showed the highest binding energy, which is followed by compound ZINC000003979028, ZINC000003870413, ZINC000003870412, ZINC000150338758, ZINC0000070450948, ZINC000150338754, ZINC000095098891, ZINC000000119985, ZINC000005085286 (Table 7).
Screening of GTPase inhibitor
GTPase inhibitors inhibit the GTPase activity of a protein and thus may hinders the metabolism of the bacterium. Total 16 inhibitors were used in the study were Mac0182344, NAV_2729, Br_GTP, ML141, Rhosin_HCl, NSC_23766, CID_1067700, ITX3, EHT1864, Berberine, Salirasib, Mac0174809, Mac0182099, CCG_50014, Nexinhib20, Mac0080023. The highest binding affinity was seen in Mac0182344 and NAV_2729. Mac0174809 and Mac0080023 are the synthetic molecules and structural analogues whereas the other two compounds namely Mac0182099 and Mac0182344 are the natural product (Table 7).
Docking of NTPs with Mt-ppa
Molecular docking was performed to check the binding of Mt-ppa with nucleotide tri and diphosphates. In the docking experiment, we found that Mt-ppa has the maximum binding affinity for Guanosine Di Phosphate (GDP) which is followed by UDP, GTP, ATP, ADP, CDP, CTP and UTP. The outcome of docking analysis showed that Mt-ppa having higher affinity for diphosphates in comparison to tri phosphates (Table 7).