NSave Nature to Survive

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1 ISSN: : Special issue, Vol. 1; ; 2010 NSave Nature to Survive APPLICATION OF BIOINFORMATICS IN GREEN ENERGY TECHNOLOGY: JATROPHA CURCAS ACCASE ENZYME AS CASE STUDY Raghunath Satpathy et al. Biofuel Homology modelling Docking Molecular dynamics simulation Paper presented in International Conference on Environment, Energy and Development (from Stockholm to Copenhagen and beyond) December 10-12, 2010, Sambalpur University 151

2 NSave Nature to Survive RAGHUNATH SATPATHY*, SUSANT KUMAR PADHI 1 AND LOPA PATTANAIK 2 Department of Biotechnology, MIRC LAB, MITS Engineering College, Rayagada , Odisha, INDIA 1 Department of Environmental Science, Sambalpur University, Jyoti vihar, Burla 2 Department of Geology, NIT Durgapur E mail: rnsatpathy@gmail.com ABSTRACT To meet the need of oil, biofuel production is considered as an alternative energy source. So a molecular basis of understanding of the enzyme structure and function is required which are responsible for production of biofuels in the energy crops. Acetyl-CoA carboxylase (ACCase) has a very important regulatory role in controlling plant fatty acid biosynthesis and thereby affecting lipid biosynthesis. ACCase catalyzes the ATP-dependent carboxylation of acetyl-coa to produce malonyl-coa. The present work is an in-silico approach which deals with the Homology based modeling and identification of ATP binding residues of the enzyme ACCase of the biofuel producing plant Jatropha curcas. Then ATP binding pocket of the enzyme was predicted by two different analysis tools. The result indicates that the residues MET 51, ASP181, PRO 201, VAL 226 are responsible for binding to ATP and also they constitute the binding pocket. The stability of the model and complex with ATP were realised by performing molecular dynamics simulation in water by GROMACS software in a high performance computing environment. This work relates to understanding about how the metabolic pathway could be utilized for the commercial production of biofuels that would be beneficial for both environment and economics of a country. *Corresponding author 152

3 GREEN ENERGY TECHNOLOGY INTRODUCTION The development of alternative energy sources such as biofuels are one of the most exciting and challenging area. So the effort has been put to produce biodiesel from the algal species (Edward M. Rubin., 2008). In order to meet the climate change without adversely affecting global energy supply, there is growing interest in the possibility of producing transportation fuels from renewable sources by using microbial fermentation methods. In this process various biocatalysts that can efficiently used to convert cheap lignocellulosic raw materials into liquid fuels (Liu and Khosla, 2010). Jatropha, a member of the euphorbia family, originated in Central America. It has long been used around the world as a source of lamp oil and soap and also as a hedging plant in India (Eugene et al., 2010). Biochemical studies have suggested that acetyl-coa carboxylase (ACCase), a biotin-containing enzyme that catalyzes an early step in fatty acid biosynthesis, may be involved in the control of this lipid accumulation process. Therefore, it may be possible to enhance lipid production rates by increasing the activity of this enzyme via genetic engineering (Roessler et al., 1994). Since experimental structure prediction method is a time consuming process so computational study about the enzyme structure and its functional aspects for biofuel production are very much useful. As the 3D structure of the enzyme has not found out yet, so the structure is to be predicted computationally. The quality of the model structure of the enzyme is accessed by various tools and performing molecular dynamics simulation in a high performance computing environment. The valid structural model is then searched for the ATP binding pocket by automated prediction method. Docking of ATP with the structural model is performed and the binding site is to be analysed. MATERIALS AND METHODS 3D model building and model validation The sequence for the ACCase enzyme was retrieved from SWISSPROT database having ID D2D554. The model was built by homology modeling and for this Swiss model server was used (Schwede et al., 2003). The model was built by the automated mode. The model was verified for the missing side chains by SCWRL4 tool (Dunbrack et al., 2009) further verified by PROCHECK (Laskowski et al., 1993). The PROCHECK program provides the information about the stereo chemical quality of a given protein structure. The PROCHECK was used to generate Ramachandrans plot and the quality of the structure was computed in terms of % of residues in favourable regions, % of non Proline Glycine residues etc. Verify 3D is a server that calculates the interaction energy of the model so helpful to predict the model quality (Bowie et al., 1991). This is extremely useful in making decisions about reliability. Then the backbone alignment and RMSD (root mean square deviation) study was performed by using PYMOL tool ( PYMOL is useful molecular modeling software allowing the visualization of three dimensional molecular structures as well as for the backbone alignment between the model and template. For the calculation of RMSD (Root mean square deviation) and Energy value of the model enzyme GROMACS (Groningen Machine for Chemical Simulation) was used (Vander et al., 2005). GROMACS is a versatile package to perform molecular dynamics that simulates the Newtonian equations of motion for systems with hundreds to millions of particles (Hess et al., 2008). The model was subjected to molecular dynamics simulation in water at 300 K temperature and for 1500 Pico second by using Gromos 43a1 force field of GROMACS tool. The computing facility utilised is High performance cluster for Biological Applications which is based on Intel Xeon Dual Quad core as processor, Gluster HPC 1.3 X86-64 bit edition,total 16 nodes each having 4GB of memory. In-silico binding pocket analysis and docking study The verified model was then subjected to CastP (Liang et al., 1998) and ATPint ( raghava/atpint/) server to observe the possible pockets in the protein. CastP server is a automated on line tool that predicts the possible pockets for along with the residue positions and surface area. Similarly 153

4 RAGHUNATH SATPATHY et al., ATPint is a server to predict the ATP binding pockets. Further Docking was performed between the validated structure of ACCase enzyme and the energy minimized ligand by using HEX 5.0 tool (Ritchie, 2003). HEX is an interactive molecular graphics program for protein-ligand docking, assuming the ligand is rigid and it can superpose pairs of molecules using only knowledge of their 3D shapes. It is still the only docking and superposition program to use spherical polar Fourier (SPF) correlations to accelerate the calculations (Mavridis and Ritchie, 2008).The binding energy was computed and the ligand binding pattern was observed. RESULTS AND DISCUSSIONS 3D model of ACCase enzyme and molecular dynamics study The sequence of 232 amino acid protein Acetyl Co-enzyme carboxyl transferase subunit alpha was obtained from SWISSPROT database. The model was obtained from Swiss model server and by the available template structure A chain of 2DN8 ( Fig. 1 shows the model obtained and then the structural features of the model were studied (Table 1). The missing side Figure 1: Structural model of ACCase enzyme of Jatropha Curcas Table 1: Structural features of the model enzyme Structural features Information No. of residues 232 No. of atoms 1394 No. of hydrogen bonds 64 No. of helices 0 No. of strands 16 No. of turns 20 Table 2: Ramachandran plot statistics computed with PROCHECK program % residues in favourable regions 70.3 % residues in additional residue regions 28.1 % residues in generously regions 0.0 % residues in disallowed regions 1.6 % of non Proline and non Glycine residues 100 chains of the model was checked and managed by SCWRL4 software. To verify further the predicted structures, the model was fed into the verify 3D structure and reliable result was obtained as shown in Fig. 2. The stereo chemical quality of the structure was checked by PROCHECK tool. The Φ and Ψ distributions of the Ramachandran plots of non-glycine, non-proline residues are summarized in Fig. 3. Altogether 92.3% of the residues were in favoured regions (Table 2) so it can consider as a good model for further analysis. The overall G-factor of dihedrals used was computed as The molecular dynamics simulation was performed. Both energy, root mean square deviation plots were 154

5 GREEN ENERGY TECHNOLOGY Verify 3D PROCHECK Psi (degrees) 3D-10 Average score Figure 2: Showing Verify 3D plot of the model Residue Ramachandran Plot model_out Figure 3: Ramachandran plot of the model Psi (degrees) B (kj mol-1) Time (ps) Figure 4: Energy profile of the model after molecular dynamics simulation 155

6 RAGHUNATH SATPATHY et al., C-alpha after Isq fit to C-alpha RMSD (nm) Time (ps) Figure 5: RMSD analysis of the model after molecular dynamics simulation Figure 6: Binding of ATP (Red colour) in the ACCase enzyme pocket (Blue colour) derived from the respective trajectory file by Gromacs software output. The potential energy for the protein was initially high but during course of simulation it has came down. Similarly the high kinetic energy shows the constant value however the total energy is low as in Fig. 4. The RMSD fluctuation plot shows the C- alpha backbone deviation during the simulation process is within the range 0.7 nm (Fig. 5). Since it is a tolerable fluctuation in the backbone hence it confirms the model is stable. Docking study and ATP binding pocket prediction Docking of the ATP with the modeled enzyme was performed using HEX tool. The grid was fixed at 0.6 and the default FFT (Fast Fourier Transformation) mode was chosen. The algorithm exhaustively searches the entire rotational and translational space of the ligand with respect to the receptors. The ATP binding with the enzyme was obtained as energy value Further the result of CastP server, ATPint server and ATP docking site was analysed to be same i.e. the amino acid residues MET 51, ASP181, PRO 201, VAL 226 are responsible for binding to ATP (Fig. 6). CONCLUSION Acetyl Co-enzyme carboxyl transferase (ACCase) is the main enzyme which catalyses the first step of the 156

7 lipid synthesis in plant Jatropha curcas. The storage lipids in the algae correspond to the biofuel producing capability. In the present work a homology based modeling for the above enzyme has been constructed using Swiss model. After use of various types of model validation software the result suggest that the model is reliable. The stable structure is further subjected to Docking with ATP the key ligand of the enzyme action. The docking result shows that almost similar part of the enzyme is responsible for binding with both the ligand and the residue. The predicted pocket result of the enzyme obtained from CastP server was found to be consistent with the predicted result by ATPint server and also docking result. The work basically relates to the in-silico analysis of the fatty acid synthetic pathway leading to accumulation of oils and fats and an understanding about how the pathway could be utilized for the commercial production of algal biofuels. REFERENCES GREEN ENERGY TECHNOLOGY Bowie, J. U., Lüthy, R. and Eisenberg, D A method to identify protein sequences that fold into a known three-dimensional structure. Sci. 253: Dunbrack, R. L., Krivov, G. G. and Shapovalov, M. V Improved prediction of protein side-chain conformations with SCWRL4. Proteins. 77: Edward, M. R Genomics of cellulosic biofuels. Nature. 454: Eugene P. Wagner, Maura A. Koehle, Todd M. Moyle and Patrick D. Lambert How Green Is your Fuel? Creation and Comparison of Automotive Biofuels. J. Chem. Educ. 87: Hess, B., Kutzner, C., Van Der Spoel, D. and Lindahl, E GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. J. Chem. Theory Comput. 4: Liang, J., Herbert, E. and Clare, W Anatomy of Protein Pockets and Cavities: Measurement of Binding Site Geometry and Implications for Ligand Design. Protein Sci. 7: Laskowski, R. A., Mac Arthur, M. W., Moss, D. S. and Thornton, J. M PROCHECK aprogram to check the streochemical quality of protein structure. J. Appl. crystallogr. 26: Liu, T. and Khosla, C Genetic Engineering of Escherichia coli for Biofuel Production. Annu. Rev. Genet: in press. Mavridis, L. and Ritchie, D. W J. Chem. Inf. Model. 47: Ritchie, D. W PROTEINS. Structure, Function and Genetics. 52: Roessler, P. G., Bleibaum, J. L., Thompson, G. A. and Ohlrogge, J. B Characteristics of the gene that encodes acetyl-coa carboxylase in the diatom Cyclotella cryptic. Ann. N Y Acad. Sci. 721: Schwede, T., Kopp, J., Guex, N. and Peitsch, M. C SWISS-MODEL: An automated protein homologymodeling server. Nucleic Acids Res. 31: Vander, S. D., Lindahl, E., Hess, B., Groenhof, G. and Mark, A. E GROMACS: Fast, Flexible and Free. J. comp. chem. 26:

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