3.1 Sequence Retrieval and structure prediction:
The Mycobacterial Tap protein sequence (Locus tag: Rv1258, Uniprot ID: P9WJX9) was downloaded from Uniprot (https://www.uniprot.org/uniprot/P9WJX9) and used to perform structure prediction and for other purposes. This sequence was retrieved in FASTA format [22] for further studies. This protein comprised of 419 residues having the size of 43.287 kDa. TAP protein sequence in FASTA format is shown below;
>sp|P9WJX9|TAP_MYCTU Multidrug efflux pump Tap OS=Mycobacterium tuberculosis (strain ATCC 25618 / H37Rv) OX=83332 GN=tap PE=1 SV=1
MRNSNRGPAFLILFATLMAAAGDGVSIVAFPWLVLQREGSAGQASIVASATMLPLLFATLVA
GTAVDYFGRRRVSMVADALSGAAVAGVPLVAWGYGGDAVNVLVLAVLAALAAAFGPAG
MTARDSMLPEAAARAGWSLDRINGAYEAILNLAFIVGPAIGGLMIATVGGITTMWITATAFG
LSILAIAALQLEGAGKPHHTSRPQGLVSGIAEGLRFVWNLRVLRTLGMIDLTVTALYLPMES
VLFPKYFTDHQQPVQLGWALMAIAGGGLVGALGYAVLAIRVPRRVTMSTAVLTLGLASMV
IAFLPPLPVIMVLCAVVGLVYGPIQPIYNYVIQTRAAQHLRGRVVGVMTSLAYAAGPLGLLL
AGPLTDAAGLHATFLALALPIVCTGLVAIRLPALRELDLAPQADIDRPVGSAQ
In the final structure predicted by Phyre2, 100% residues were modelled at >90% confidence [Fig. 1 and 2]. 82% of the sequence acquires alpha-helical structure and 12% are disordered whereas 59% of the sequence is a part of TM helix. Surprisingly, the predicted model did not show any β-strand. According to Phyre2, six templates were selected to model TAP protein based on heuristics to maximise confidence, percentage identity and alignment coverage; only two residues were modelled by ab initio. Transmembrane helices have also been predicted by Phyre2 in our sequence to adopt the best topology as shown in figure 3 [21]. Eventually, based on these parameters, a suitable model of TAP protein was utilized to conduct the further In silico analyses and validation.
3.2 MD Simulations and selection of the best model:
The dynamics of biological systems are crucial for their structure and functions, but using the experimental setup, deciphering the dynamics is difficult or even sometimes impossible; so computational tools are the saviour here. Molecular dynamics simulation was implemented for analysing the dynamics of the modelled TAP protein. As all-atom simulations are computationally expensive, the route of coarse-grained simulation is preferred sometimes. CABS-Flex is a web-server for fast simulations of proteins. Using CABS-Flex server, 10 ns MD simulation was performed and the best model was selected after clustering [Fig. 4]. The contact map of the residues [Fig. 6] and Root Mean Square Fluctuation (RMSF) plot [Fig. 5] were also generated using this server. RMSF plot is the residue-wise fluctuations recorded throughout the MD simulation while the Contact map provides a detailed view of the protein's residue-residue interaction pattern. Based on the generated trajectory, the residue fluctuation profile is calculated as,
where <> denotes the average over a whole trajectory, and x is the position of particle i in the frame j [23, 32].
3.3 Validation of the TAP protein model:
The quality of the structure of the predicted model of TAP protein was verified by Ramachandran Plot (in PROCHECK server) [24]. This experiment suggested that 79.3% of residues were in the favoured regions, 14.1% in the additional allowed regions,4.3% in the generously allowed regions and 2.3% in disallowed regions [Fig. 7].
3.4 Binding Site Prediction:
The active site can be represented as a part of the protein surface to which a specific substrate (ligand) or set of substrates (ligands) binds. We predicted the active sites in the modelled protein by CASTp 3.0 server. CASTp server facilitates the identification and measurements of surface accessible pockets for proteins with the active site residues. In Fig. 8, top two pockets are shown in accordance with their Area (SA) and Volume (SA). In the Table 2, the red coloured pocket has the highest Area (SA) and Volume (SA), 3132.679 and 2572.874 respectively. Whereas, the second-best pocket (green coloured) has a much lesser Area and Volume compared to the first one. Table 2 is representing the values and colour ID of the pockets. The best two active site residues with pocket volume are shown in Fig. 8 in red and green color.
3.5 Molecular Docking:
Docking is a powerful computational tool for estimating binding affinities of the ligands with the target protein.
From the molecular docking studies with Tap protein in PyRx software, the ligands are ranked in terms of binding affinity. Greater the negative value of score indicates better binding. Top three (3) drugs have been selected for further investigation, 1) Glibenclimide, 2) Lubiprostone, 3) Flecainde demonstrating the significant negative change in free energy (ΔG) -9.8, -8.4 and -8.1 respectively. Docking score of the all-tested ligands are mentioned in table 3. Other details of these compounds such as 2D structure, H-Bond donor and acceptor, molecular weight etc. are provided in table 1. Docking poses are visualized using Discovery Studio [ Fig. 9] [33-35].