Sequence analysis and homology modeling of laccase from Pycnoporus cinnabarinus

Abstract

Industrial effluents of textile, paper, and leather industries contain various toxic dyes as one of the waste material. It imparts major impact on human health as well as environment. The white rot fungus Pycnoporus cinnabarinus Laccase is generally used to degrade these toxic dyes. In order to decipher the mechanism of process by which Laccase degrade dyes, it is essential to know its 3D structure. Homology modeling was performed in presented work, by satisfying Spatial restrains using Modeller Program, which is considered as standard in this field, to generate 3D structure of Laccase in unison, SWISS-MODEL web server was also utilized to generate and verify the alternative models. We observed that models created using Modeller stands better on structure evaluation tests. This study can further be used in molecular docking techniques, to understand the interaction of enzyme with its mediators like 2, 2-azinobis (3-ethylbenzthiazoline-6-sulfonate) (ABTS) and Vanillin that are known to enhance the Laccase activity. Background: In developing countries including India textile, leather and paper industries represent an important economic sector. Huge amount of capital and Human resource is engaged in these industries. These industries are one of the most important sources of Environmental pollution. Mills of these industries emancipate enormous amount of waste matter each year, that contain variety of chemicals such as formaldehyde, chlorine, heavy metals (such as lead and mercury) and toxic dyes, which lay noteworthy foundation of environmental degradation and human illnesses. Most of the dyes that are released from these industries are polymers possessing very complex structure and are very difficult to decompose biologically [1]. Many reactive dyes are not degraded in ordinary aerobic sewage treatment processes and that they can be discharged unaffected from the treatment plant [2]. An even very minute concentration of dyes in effluent is visible and is often carcinogenic [3]. Laccase belongs to group of enzyme named as large blue copper proteins or blue copper oxidases possessing polyphenol oxidase activity. It functions by generally reducing oxygen to water simultaneously oxidizing a polyphenolic substrate .Laccase has evolved with a remarkable property of non-specificity of its reducing substrates and encompass vast range of substrates oxidized [4], making it a marvelous contrivance to oxidize toxic dyes which are generally polyphenols[5]. Knowledge of 3D structure of Laccase can aid us to uncover the mystery of how Laccase has attained such huge functional diversity. To experimentally discover functionality of any protein, the information of its 3D structure remains an indispensable fact, which is achieved using techniques like X-Ray Crystallography or NMR spectroscopy. Experimental techniques are very tedious and prolonged and not always succeed in determining structure for all proteins especially membrane proteins [6]. Moreover, the rate at which protein sequence data is accumulating is far more than the structural information available, thus creating a gap between available sequences and experimentally solved structures. Computational methods like homology modeling can help reduce this gap. It is known that existing proteins are result of continuous evolution of previously existing ones, thus proteins can be grouped into families. Members in same family are similar and thus have similar folds; this fact allows predicting the structure of other members of family if structure of single member is known and the technique by which this task is achieved is termed as Homology Modeling. Modeller [7] is stand-alone package for homology modeling that accomplishes the job by method called 'Satisfaction of spatial restraints' using a set of restraints derived from the alignment and expressed as Probability Density Functions, finally the model is obtained by minimizing the violations to these restraints. Studies have proved that Modeller outperforms most of other homology modeling suits, it's fast, reliable and freely available and hence we selected it in current study [8].