Molecular DockingAndLigand-Protein Interaction

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Procedia Technology 00 (2012) 000–000

International Science Conference (SCICON 2014)

Molecular DockingAndLigand-Protein Interaction Study of The Expansin Protein ATEXPA23 And EXLX1 Anamika Basua, Anasua Sarkarb* a

b

Assistant Professor, Gurudas College, Kolkata, India, E-mail: [email protected]

Doctoral student, Jadavpur University, Kolkata, India;Assistant Professor, Government College of Engineering and Leather Technology, Kolkata, India, E-mail: [email protected], [email protected]

Abstract

In our present work, we analyze the peripheral membrane protein ATEXPA23 from Arabidopsis thaliana, a plant model organism, using homology modeling and molecular docking. The microarray result analysis showed ATEXPA23 (AT5G39280) protein which causes loosening and extension of plant cell walls, is differentially expressed during different stages of plant embryogenesis. It contains one expansin-like CBD domain and one expansin-like EG45 domain.ATEXPA23 belongs to the expansin family in Expansin A subfamily. The 3D model after refinement was used to explore the xylose binding characteristics of ATEXPA23 using SWISSDOCK. The docking analysis has shown that the surface exposed hydrophilic amino acid residues Arg-173 and Arg 174 interact with ligand xylose through H-bonding. The binding energy values evaluation of docking depicts a stable intermolecular conformation of the docked complex. At the same time the result of docking analysis for another expansin family protein, EXLX1 has been verified with

* Corresponding author. Tel.: +0-000-000-0000 ; fax: +0-000-000-0000 . E-mail address:[email protected] .

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Author name / Procedia Technology 00 (2012) 000–000

data obtained from NMR spectroscopy (Wang et al, 2013). The interaction of xylose, present in xyloglucan of plant cell wall, with protein ATEXPA23 will elucidate the role of expansin proteins in plant type cell modification. Keywords: Molecular modeling; molecular docking; ligand-protein binding site; ATEXPA23; EXLX1; xylose 1. Introduction Expansins are typically 250-275 amino acids long, pH-dependent wall-loosening proteins required for cell expansion in many developmental processes e.g. plant embryogenesis, leaf initiation fruit softening, xylem formation, abscission, seed germination and the penetration of pollen tubes etc .Expansins are peripheral membrane protein that has an affinity for a membrane because it binds either another membrane protein or a lipid head group. Peripheral membrane proteins do not integrate into the hydrophobic core layer of biological membrane. Expansin genes have now been identified in many plant species e.g. Arabidopsis, tomato, oat, maize, rice, tobacco etc. In the plant cell wall the cellulose microfibrils are linked via hemicellulosic tethers to form the cellulosehemicellulose network, which is embedded in the pectin matrix. Hemicellulose is a complex polysaccharide matrix composed of different residues branched in three kinds of backbones, named xylan, xyloglucan (XyG) and mannan. Xyloglucans have a main β-D-(1→4)-glucan backbone (denoted as G) generally branched with α(1→6)-linked D-xylopyranosyl (denoted as X) or β-D-galactopyranosyl (1→2)-D-xylopyranosyl residues (denoted as L). The structure and molecular distribution of these XyG side chains varies in different plant tissues and species. As stated earlier, expansions disrupt the cellulose-hemicellulose association transiently, allowing slippage or movement of cell wall polymers.But the molecular mechanism by which expansin loosens the cellulosic network within the cell wall is not yet established. In the year 2000, Cosgrove D J proposed the role of protein expansins in cell wall expansion by slippage or rearrangement of matrix polymers. At low pH, plant cell wall extends faster. This event is known as 'acid growth'. Wang et al, 2013 measured the protein-transferred 13C spectra of the polysaccharides and compared cell walls that contain wild type expansin, a WWY mutant, or an RKK mutant. The WWY mutant (W125A/ W126A/Y157A) replaces the three aromatic residues on the cellohexaose-binding D2 surface with Ala. The RKK mutant (R173Q/K180Q/K183Q) replaces three basic residues on the opposite surface of D2 with the uncharged Gln. The RKK mutant has stronger wall loosening activities than wild type expansin, an effect that was postulated to result from reduction of nonspecific interactions of the basic protein with acidic pectins. They also suggest that cellulose is the functional binding target of expansins and that the hyperactive RKK mutant binds cellulose with the shortest average distances. Molecular dynamics simulations of the expansin protein docked onto a cellulose microfibril confirms that aromatic-triplet (W125A/ W126A/Y157A) interacts with the edge of the hydrophobic surface of the cellulose microfibril. Their protein-transferred 2D 13C correlation spectrum of the RKK-expansin sample shows that the expansin-bound site has higher XyG content and lower pectin content than the average cell wall. The spin diffusion 2D spectrum confirms an interaction between the C1 of xylose and a Trp or Tyr aromatic carbon in the expansin protein and XyG-enriched regions of the cellulose microfibril. The major limitation of that study for using the bacterial expansin, EXLX1, which is less active in wall-loosening assays than are plant expansions, has been successfully overcome in our current study by using molecular docking method for ATEXPA23(AT5G39280) protein, containing 275 amino acids.ATEXPA23 expressed significantly only during globular (specifically preglobular) stage of embryogenesis, with unknown crystal structure. We use computational methods as an excellent and cost effective alternative for analyzing structure and function of protein ATEXPA23. By using computational


biology methods almost exact structure of protein along with its structure-function relationship and ligandprotein interaction of that protein has been determined. At the same time the same computational methods are used for for Bacillus subtilis YoaJ (EXLX1), a bacterial expansin to verify results of expansin binding with cell wall (Wang et al, 2013).Since the structure reflects function, so the 3D structure of the proteinATEXPA23 was established using homology modelling approach. The predicted structure was subjected to dock using xylose as a ligand to study the ligand-protein interaction sites. The study will lead us to better understanding of the role of protein expansin ATEXPA23 in cell wall expansion in theXyG-enriched regions of the cellulose microfibril.

2.Methodology The in-silico analysis of ATEXPA23 involves various desktop based applications for homology modelling and protein- ligand binding including SWISS-MODEL Version 8.05 (Arnold et al, 2006) and GalaxyWEB( Shin et al, 2014 ).Our study involves various online applications for docking includes, SwissDock, a web service to predict the molecular interactions that may occur between a target protein and a small molecule, based on the docking software EADock DSS, (Grosdidier et al , 2011) with CHARMM force field method for calculation ( Vanommeslaeghe et al. 2010) . The most favourable clusters can be visualized using UCSF Chimera ( Pettersen et al , 2004) .The presence of particular motifs that reflects the specific functions of the proteins was searched by Motif Search Library (http://www.genome.jp/tools/motif/). From PROCHECK server residue- by- residue analysis for Ramachandran plot ispredicted for our query proein. 2.1 Homology modeling SWISS-MODEL, a fully automated protein structure homology-modelling server, accessible via the ExPASy web server was adopted to predict the three dimensional structure of the protein encoded by the selected gene retrieved from Uniprot (The UniProt Consortium,2014) (Accession number Q9FL79) in FASTA format. The protein data bank (PDB) was checked for the 3D structure of the selected protein, and it was confirmed that no 3D structure had been predicted to date. Homology modeling was implemented to generate the 3D structure of the encoded protein. Dali program was run to identify template (Holm et al., 2010). The PDB ids of selected templates were 2hcz-X and 3d30A. . PDB ‘2hcz-X’ is the crystal structure of EXPB1 (Zea m 1), a beta-expansin and group-1 pollen allergen from maize, induces extension and stress relaxation of grass cell walls. PDB ‘3d30A’ is the crystal structure of an expansin like protein from Bacillus Subtilis at 1.9A resolution YoaJ (EXLX1), a bacterial expansin that promotes root colonization. Table 1 lists the two templates 2hcz-X and 3d30A with Z-score and % identity with our protein ATEXPA23. Table 1. List of templates with Z-score and % identity for protein ATEXPA23 PDB ID

Z-score

% ID

2hcz-X

33.6

28

3d30A

19.7

22

2.2 Molecular docking

3

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Prior to the docking procedure, ligand was identified by using the GalaxySite (Heo et al, 2014), is a ligand binding site prediction from a given protein structure from web server GalaxyWEB (Shin et al, 2014) for both the three-dimensional structures of the compounds ATEXPA23 and EXLX1 , considering PDB ID 2hczX as template for protein – ligand binding. The ATEXPA23 and EXLX1 are both have a carbohydrate binding domain. For both ATEXPA23 and EXLX1 proteins GALAXYWeb shows that xylose is the predicted ligand structure shown in Figure 1.

Figure 1: 2D and 3D of xylose from GALAXYWeb The 3D structure of the ligand molecule was obtained from The GlycoBioChem PRODRG2 Server (Schüttelkopf et al, 2004). Docking of ATEXPA23 and EXLX1 with ligand xylose was carried with SWISSDOCK web server based on EADock DSS (Grosdidier et al , 2011) and many binding modes are generated in the vicinity of all target cavities (blind docking). , and simultaneously, their CHARMM energies are estimated on a grid with CHARMM force field( Vanommeslaeghe et al. 2010) on external computers from the Swiss Institute of Bioinformatics. The binding modes with the most favourable energies are evaluated with FACTS, (Brooks, et al 2009) and clustered. Molecular complexes are ranked by the most favourable binding energies, and we selected among those one structure representing the best binding mode, based on an energy average value corresponding to the first five ranked structures. The most favourable clusters were visualized by the USCF Chimera software (Pettersen et al, 2004)). 3.Results & Discussion The present study comprises structural and docking analysis of the Expansin A 23 from in Arabidopsis thaliana and EXLX1from Bacillus Subtilis.

The structure predicted by SWISS-MODEL Version 8.05 with the alpha helices and beta pleated sheets visualized by Jmol 11.6.1 is illustrated in Figure 2(A). Figure 2(B) demonstrates a superimposition of structure and template.


Figure 2 (A) Predicted structure of ATEXPA23 using template2hcz-X with Seq Identity 30.09% and GMQE 0.56. (B) Structural superimposition of predicted structure and template 2hcz-X showing high structural similarity. Cartoon structure represents the predicted structure and ball and stick structure represents the template used. Docking of ATEXPA23 and EXLX1 with ligand xylose was carried with SWISSDOCK web server based on EADock DSS (Grosdidier et al , 2011) and many binding modes are generated in the vicinity of all target cavities (blind docking).From several clusters for EXLX1 third cluster was selected with the vales for FullFitness is -2074.39 (kcal/mol) and Estimated ΔG is -6.12 (kcal/mol) using UCSF Chimera ( Pettersen et al , 2004) as shown in Figure3.

Figure 3: Predicted xylose binding with EXLX1 This depicts a stable intermolecular conformation of the docked complex. For EXLX1 protein TRP125, TRP126 and TYR 157 are red circled and ligand xylose is shown in sticks in the above figure. This result confirms the xylose binding site of EXLX1 as shown in mutation analysis result of WWY mutant (W125A/ W126A/Y157A) of EXLX1 (Wang et al, 2013).

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Above mentioned molecular docking methods were applied for binding site prediction of ATEXPA23 for ligand xylose Docking of ATEXPA23 with ligand xylose was carried with SWISSDOCK web server based on EADock DSS (Grosdidier et al , 2011) and 42 binding clusters are generated in the vicinity of all target cavities (blind docking).From those clusters for ATEXPA23 cluster 0 was selected with the values for FullFitness is -10008.32 (kcal/mol) and Estimated ΔG is -6.76 (kcal/mol).Protein –ligand binding for this cluster was visualized by using UCSF Chimera ( Pettersen et al , 2004) as shown in Figure 4:

Figure 4:Predicted binding of xylose with ATEXPA23 For ATEXPA23 protein Arg 173 and Arg 174 are red circled and ligand xylose is shown in sticks in the above figure.H bonding between O atom of Gly 49 with H8 atom of xylose and H atom of Arg 174 with O1 atom of xylose, with their bond lengths were shown in the above 2nd figure.The functional motif search result for the query protein in PROSITE PROFILE shown in Table 2. Table 2. The functional motif search result for the query protein in PROSITE PROFILE Found Motif

Position

PROSITE

EXPANSIN_EG45

72..182

PS50842

EXPANSIN_CBD

192..271

PS50843

Description Expansin, family-45 endoglucanase-like domain profile. Expansin, Cellulosebinding-like domain profile.

Score 2790

1523

From PROCHECK server (Laskoswki et al, 1993) residue- by- residue analysis for Ramachandran plot shows that Arg 173 and Arg 174 are present in Core beta region with extended strand, participates in beta-ladder as Secondary structure. These two amino acid residues are present in EXPANSIN_EG45 motif as shown in Table 2. So, it can be concluded that endoglucanase-like domain of expansin protein plays an important role in interaction with the XyG-enriched regions of the cellulose microfibril.


References [1] Wang T, Park YB, Caporini MA, Rosay M, Zhong L, "Sensitivity-enhanced solid-state NMR detection of expansin’s target in plant cell walls". Proc Natl Acad Sci USA110: 16444–16449, 2013 [2] Cosgrove DJ"Loosening of plant cell walls by expansins" Nature 407 (6802), 321-326 ,2000 [3] Arnold K.,.Bordoli L,.Kopp J,.Schwede T ,“The SWISS-MODEL Workspace: A web-based environment for protein structure homology modelling”, Bioinformatics, vol. 22, pp. 195-201, 2006. [4] Shin W. H., Lee G. R., Heo L., Lee H., Seok C., “Prediction of Protein Structure and Interaction by GALAXY protein modeling programs”, Bio Design, vol. 2, no. 1, pp. 1-11, 2014. [5] Grosdidier A., Zoete V., Michielin O., “SwissDock, a protein-small molecule docking web service based on EADock DSS”, Nucleic Acids Res, vol. 39, pp. 270–277, 2011. [6] Vanommeslaeghe K., Hatcher E., Acharya C., Kundu S., Zhong S. “CHARMM General Force Field (CGenFF): A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields”, J Comput Chem, vol. 31, pp. 671–690, 2010. [7] Pettersen E.F., Goddard T.D., Huang C.C., Couch G.S., Greenblatt D.M., Meng E.C., Ferrin T.E.,“UCSF Chimera--a visualization system for exploratory research and analysis”, J Comput Chem, vol.25, no. 13, pp. 1605-12, 2004. [8] The UniProt Consortium "Activities at the Universal Protein Resource (UniProt)" Nucleic Acids Res. 42: D191-D198 , 2014 [9] Holm L., Rosenström P., “Dali server: conservation mapping in 3D”, Nucl. Acids Res, vol. 38, pp. W545-549, 2010. [10] Heo L., Shin W. H.,. Lee M. S, Seok C., “GalaxySite: Ligand-binding site prediction by using molecular docking”, Nucleic Acids Res, accepted, 2014. [11] Schüttelkopf A. W. and van Aalten D. M. F. ,"PRODRG: a tool for high-throughput crystallography of protein-ligand complexes", Acta Crystallogr D60, 1355–1363,2004. [12] Brooks B. R., Brooks III C. L., Mackerell A. D., Nilsson L., Petrella R. J., Roux B., Won Y., Archontis G., Bartels C., Boresch S. ,Caflisch A., Caves L., Cui Q., Dinner A. R. , Feig M., Fischer S., Gao J., Hodoscek M., Im W., Kuczera K., Lazaridis T.s, Ma J., Ovchinnikov V., Paci E., Pastor R. W., Post C. B., Pu J. Z., Schaefer M., Tidor B., Venable R. M., Woodcock H. L., Wu X., Yang W., York D. M., and Karplus M. , “CHARMM: The Biomolecular simulation Program”, J. Comp. Chem, vol. 30, pp. 15451615, 2009. [13] Laskoswki RA, MacArthur MW, Moss DS & Thorton JM.. PROCHECK: a program to check the stereochemical quality of protein structures. J. Appl. Cryst. 26, 283-291, 1993.

[14] http://www.genome.jp/tools/motif/

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References Clark, T., Woodley, R., De Halas, D., 1962.Gas-Graphite Systems, in “Nuclear Graphite” R. Nightingale, Editor. Academic Press, New York, p. 387. Deal, B., Grove, A., 1965. General Relationship for the Thermal Oxidation of Silicon, Journal of Applied Physics 36, p. 3770. Deep-Burn Project: Annual Report for 2009, Idaho National Laboratory, Sept. 2009. Fachinger, J., den Exter, M., Grambow, B., Holgerson, S., Landesmann, C., Titov, M., Podruhzina, T., 2004. “Behavior of spent HTR fuel elements in aquatic phases of repository host rock formations,” 2 nd International Topical Meeting on High Temperature Reactor Technology. Beijing, China, paper #B08. Fachinger, J., 2006. Behavior of HTR Fuel Elements in Aquatic Phases of Repository Host Rock Formations. Nuclear Engineering & Design 236, p. 54.

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