DOCKING OF POLYKETIDE SYNTHASE FROM PGPR2 AGAINST SELECTED TARGETS FROM PHYTOPATHOGENS

* Illakkiam D 1 and Usha Raja Nanthini A 2 . 1. Assistant Professor, Department of Biotechnology, Mother Teresa Women’s University, Kodaikanal. 2. Head, Department of Biotechnology, Mother Teresa Women’s University, Kodaikanal. ...................................................................................................................... Manuscript Info Abstract ......................... ........................................................................ Manuscript History

Among the various groups of antibiotics produced by the PGPR, the polyketides such as 2, 4 Diacetyl phloroglucinol, Pyoluteorin and Mupirocin are highly effective in suppression of plant pathogens. Naturally occurring polyketides are produced by the successive condensation of small carboxylic acids in a process that resembles fatty acid synthesis. The genes encoding polyketide synthases (PKSs) show similarities to one other as well as to genes for fatty acid synthases (Hopwood et al., 1990;Hutchinson et al., 1995).

Alignment process:-
Polyketide synthase amino acid sequences were aligned using the multiple sequence alignment program ClustalW2. (Thompson et al., 1997) Default gap opening and extension penalty were used. A careful manual examination was done to avoid misalignment. Gaps in the alignment were treated as missing data. Proteins were named using an abbreviation followed by the family name in the alignment.
Sequence and structural analysis:-Amino acid composition of selected Polyketide synthase proteins were analyzed by ProtParam, an online tool available on ExPASy proteomics server (Gasteiger et al., 2005). Secondary structures were predicted by SOPMA on EMBOSS server. InterProScan was used to identify conserved domains in selected sequences. PSIPRED, a highly accurate secondary structure prediction method available at http://globin.bio.warwick.ac.uk/psipred. SWISS-MODEL (http://swissmodel.expasy.org) is a server for automated comparative modeling of three-dimensional (3D) protein structures. It pioneered the field of automated modeling starting in 1993 and is the most widely-used free web-based automated modeling facility today. LOMETS (Local Meta-Threading-Server) (http://zhanglab.ccmb.med.umich.edu/LOMETS/) is an on-line web service for protein structure prediction. It generates 3D models by collecting high-scoring target-to-template alignments from 9 locally-installed threading programs (FFAS-3D, HHsearch, MUSTER, pGenTHREADER, PPAS, PRC, PROSPECT2, SP3, and SPARKS-X). ClusPro: an automated docking and discrimination method for the prediction of protein complexes. ClusPro (http://nrc.bu.edu/cluster) represents the first fully automated, web-based program for the computational docking of protein structures.

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Characterization of secondary metabolites using Preparative HPLC:-Extraction of secondary metabolites was carried out following the method described earlier (Raajimakers et al., 2001) with modifications. Briefly, overnight culture of Pseudomonas sp. PGPR2 was inoculated with resorcinol and phloroglucinol to confirm the production of bioactive compounds. One liter of the culture supernatant was acidified to pH 2.0 with HCl and then extracted with equal volumes of ethyl acetate. The ethyl acetate extracts were dried in vacuum and dissolved in methanol. Aliquots were filtered (0.2 µm, Millipore Corp. USA) and the antifungal compound was purified by HPLC method (Keel et al., 1992). Briefly, extracts were resuspended in 1 ml of acetonirile and fractionated using Shimadzu HPLC system with C18 (250 x 10000 mm) reverse-phase column (Phenomenex Luna, Torrance, CA, USA) with 40% Acetonitrile containing 0.1% TFA in water as solvent system with a flow rate of 4.5 ml min -1 . HPLC profiles were monitored at 254 nm using PDA. Appropriate solvent was used as negative controls. PGPR2 has been generated in automated mode.
1383 Fig 8:-Threading modeling Image of the predicted model using Lomets. The confidence score for estimating the model quality is reported as C-score.   (Fig.1). This suggested a high conservation among Polyketide synthase sequence from bacterial species (Fig.2). Domain disribution and organization of PKS protein was analyzed by InterProScan.  (Fig.3). Neil et al., (2011) stated that disulfide bridges play a major role in the stabilization of the folding process also regulate redox-dependent functions. In Polyketide synthase sequence showed presence of 4 cysteines and two bonds were predicted. The position of first cysteines is 367 th and 388 amino acid and second position on 35th and 228 th amino acid (Fig.4). To study the structural and functional properties of specific proteins, prediction of disulphide bridges from the sequence is an important tool. In addition, knowledge about the disulfide bonding state of cysteines may help the experimental structure determination process and may be useful in other genomic annotation tasks.

HPLC analysis of Pseudomonas PGPR2 extracts with Phloroglucinol and Resorcinol:-
Ethyl acetate extract of Pseudomonas sp. PGPR2 culture supernatant was co-inoculated with 250ng of phloroglucinol and resorcinol was analyzed by Shimadzu HPLC system with a C18 reverse-phase column. This ethyl extract of Pseudomonas sp. PGPR2 showed six fractions with different retention time. Earlier we reported that the partially purified fraction with 10.1min retention time exhibited antifungal activity was identified as chromanone compound (Illakkiam b et al. 2013). In this, we examined the addition of phloroglucinol and resorcinol to the 1385 Pseudomonas sp. PGPR2 culture, showed to enhance the production of chromanone compound about 35% with 10.1min retention time (Fig.5).

Structural Analysis on Polyketide synthase:-
Evaluating the structure of unknown protein is a key factor for identification of protein function. Koswatta et al. 2011 reported a comparative evaluation of five widely used protein secondary structure prediction programs available in World Wide Web was carried out. Secondary structure prediction tools such as GOR, PSIPRED, HNN, PROF, and YASPIN were used to evaluate the amino acid sequences of the proteins. Among the most frequently used software in the World Wide Web, PSIPRED is the best program for secondary structure prediction.
In present study, secondary structure of a protein was analyzed using PSIPRED and predicts the percentage of alpha helix, beta sheet and coil structure. The purple colour indicates the presence of helix region and magenta colour indicates the sheet region. In this, we set 70 as output width, so it shows 70 amino acids and corresponding predicted structures in each line. The sequence length is also displayed in the output (515 amino acids in this case). The percentage of each structure is also listed as Alpha helix is 56.31%, extended strand as 10.29%, Beta turn is 9.90% and random coil is 23.50% (Fig.6). Homology modeling aims to build three-dimensional protein structure models using experimentally determined structures of related family members as templates. SWISS-MODEL workspace is an integrated Web-based modeling expert system (Lorenza et al. 2009). For a given target protein, a library of experimental protein structures is searched to identify suitable templates. On the basis of a sequence alignment between the target protein and the template structure, a three-dimensional model for the target protein is generated. Based on template 3onqB, a model for Polyketide synthase of Pseudomonas sp. PGPR2 has been generated in automated mode and the identity was 18.5% with E value 6.2E-31 (Fig.7). Since the homology between template and target sequence is very low, threading modeling was generated using LOMETS. LOMETS (Local Meta-Threading-Server) is an on-line web service for protein structure prediction. 3D models were generated by collecting highscoring target-to-template alignments from Eight (8) locally-installed threading programs (FUGUE, HHsearch, MUSTER, PPA, PROSPECT2, SAM-T02, SPARKS, and SP3). For a given target, 160 models are generated by the eight (8) component servers where each server generates 20 models, as sorted by their Z-scores in each algorithm. The best model was selected from the 160 models based on a scoring function (Fig.8). From the generated model, the PDB file was downloaded for the docking analysis. Simultaneously the target enzymes such as Ergosterol (2AIB), β-(1,3)-D-Glucanase (4M80) , DNA gyrase (1BGW), RNA polymerase (3M3Y)and Chitinase (1O6I) were retrieved from PDB database in PDB format. ClusPro represents the first fully automated, web-based program for the computational docking of protein structures. The coordinate files of two protein structures were uploaded through ClusPro's web interface (Comeau et al. 2004). The docking algorithms evaluate billions of putative complexes, retaining a preset number with favorable surface complementarities. A set of structures were selected by a filtering method, then those structures with good electrostatic values were selected and de-solvation free energies for further clustering. The program output is a short list of putative complexes ranked according to their clustering properties (Fig. 9). Docking results revealed the weighted score for the putative complexes of PGPR2-RNA Polymerase, PGPR2-DNA Topoisomerase, PGPR2-Ergosterol, PGPR2-Beta glucanase and PGPR2-Chitinase (Table 1). Pseudomonas sp. PGPR2 template protein Polyketide synthase might be target the fungus by inhibiting the DNA synthesis. This was proved by weighted score of PGPR2-RNA Polymerase complex which has low score compared to other complexes and this might be due to the presence of conserved domains responsible for transcription in Pseudomonas sp. PGPR2.

Summary:-
In silico sequence and structural analysis of Polyketide synthase protein showed structurally related regions in a compilation of amino acid sequences. Structural analysis showed that the protein's secondary structures were mainly composed of alpha helices and random coils. Presence of conserved cysteine residues plays a major role in the stabilization of the folding process of protein. The docking and discrimination method also provides good results for a number of complexes that were used as targets in the Critical Assessment of Predictions of Interactions experiment. Hence in future, in silico analyses of bacterial genomes associated with fungal viability and virulence has led to the identification of many putative targets for novel antifungal agents.