HOMOLOGY MODELING AND INSILICO APPROACH OF CLEOME GYNANDRA-AN INDIGENOUS MEDICINAL PLANT

Cleome gynandra is a widespread medicinal plant belonging to the family Capparaceae. In Ayurvedic medicine C. gynandra is a main component in Narayana Churna. It has numerous properties like Anthelmintic, in ear diseases, pruritis and several other diseases like gastro intestinal disorders and gastrointestinal infections etc. This is an effort to gather and document evidence on different features of C. gynnadra and highlight the need for survey and development. In this current study, nine proteins of C. gynandra were identify by using of bioinformatics tools. The bioinformatic study of the characterization of proteins of C. gynandra were using Expasy Protparam server, 3D structure was done using SWISS MODEL. Plants of different family show uniqueness 98% and above were particular and its sequences retrieved, aligned using Clustal Omega. Secondary Structure prediction exhibited that α – helix, random coil, β – turn and long strand leads. Phylogenetic analysis of Glyceraldehyde 3 PO4 of C. gynandra exposes that the Capparaceae families are closely related. Insilco sequence analysis of C. gynandra showed that these proteins taken from different organisms linked organized evolutionarily as they possess conserved regions in their protein sequences. These results will be helpful to further study on C. gynandra protein functions at molecular or structural levels and also valuable in homology modelling and insilico approach.


INTRODUCTION
Cleome gynandra is a common, plant and its native of Africa and now largely distributed in tropical and subtropical regions throughout the world [1]. C. gynandra is a richly current species and produces as a weed in common barren land and in crop fields throughout India. In all over the world in diverse countries it is used to treat many ailments in their traditional system and it is also used in many traditional food systems for its notable nutritional and antioxidant properties. In India alone it is used by the traditional therapists for many diseases e.g... epilepsy, irritable bowel syndrome and in protozoal and worm infections [2].
In the process of novel drug discovery, the application of virtual screening and network pharmacology can improve active compounds among the applicants and effectively indicate the mechanism of action of medicinal plants, reducing the cost and increasing the efficiency of the whole procedure [3]. We also review common databases, software programs and website tools that can be used for virtual screening and pharmacological network construction. Furthermore, we accomplish with a simple example that illustrates the whole methodology, and we present outlooks on the development and application of this in silico methodology to reveal the pharmacological basis of the effects of traditional medicinal plants [4].
The lot of protein sequences that can be modelled, as well as the exactness of the prediction, is growing gradually because of the growth and number of known protein sequences and structures as well as advances in the modelling software. It is now possible to model, with useful exactness. Significant parts of approximately one half of all known protein sequences [5]. Despite progress in an initio protein structure prediction, qualified modelling remains the only process that can constantly predict the 3-D structure of a protein with accuracy comparable to a low-resolution experimentally determined structure. Even models with mistakes may be useful, because some features of function can be predictable from only coarse structural features [6].
However there remains still a huge scope for use of current scientific methods -genomics, proteomics and bioinformatics in the C. gynandra. Bioinformatics shall enable study and integration of information from these linked fields to enable the identification of genes and gene products and explain the useful relationships between genotype and observed phenotype [7]. This study report affords a state-of-the-art overview of bioinformatics study of C. gynandra with importance on the new development and future plans, which shall provide tools and properties essential to know and help advances in this vital field [8].

Sequence Retrieval
The FASTA sequence of the proteins was retrieved by using of Genbank database hosted by the NCBI [9].

Primary Structure Prediction
For Physio-chemical description, theoretical Isoelectric Point (pI), molecular weight, total number of positive and negative residues, extinction coefficient, instability index, aliphatic index and grand average of hydropathy (GRAVY) were computed using the Expasy Protparm server [10]

Secondary Structure Prediction
SOPMA (Self Optimized Prediction Method with Alignment) was used for the secondary structure prediction.

Functional Characterization
SOSUI tool used to describe whether the protein is soluble or transmembrane in nature. InterPro is a combined resource for protein families, domains and functional sites. Inter Pro incorporates the major protein signature databases into a single resource. Superfamily and molecular function were predicted by Inter pro protein sequencing and classification.
Sequence alignment of was performed using pair wise sequence alignment tool (NCBI-BLAST) (http://blast.ncbi.nlm.nih.gov/Blast.cgi) and multiple sequence alignment was done using the EBI-CLUSTAL OMEGA (http://www.ebi.ac.uk/Tools/msa/clustalo/) tool. Clustal Omega also has powerful features for adding sequences to and exploiting information in existing alignments, making use of the vast amount of precomputed information in public databases like Pfam [11].The importance of this work was to novelty the regions of sequence comparison, which in other words allows us to yield functional and evolutionary relationships among the proteins considered in this study.
The phylogenetic analysis of ten proteins was completed to determine the number of proteins that part common structural and functional features. As an input to Clustal Omega all sequences in FASTA formats were supplied with default options. The output was analysed for sequences that are aligned for the complete length, scores, alignment, conserved residues, substitutes and semi conserved substituted residue patterns. The phylogenetic tree was constructed based on the bootstrap Neighbour Joining (NJ) method [12]. The steadiness of the internal nodes was assessed by bootstrap analysis with 1000 replicates.

RESULTS AND DISCUSSION
The plant is an herb Caparaceae family. It is commonly known as African spider. The plant is natural to tropical forest Tropical and subtropical dry broadleaf forests habitats C. gynandra contains vast number of bioactive constituents.
In addition, it has extensive variety of pharmacological activities. Hence the plant can be used to treat numerous diseases, and can be used in numerous pharmaceutical inventions and drug development studies [13].
The primary structure prediction was complete with the help of protparam tool (  AC4). The pI of five protein was less than 2 which specified that they are acidic and one protein was greater than 7 which exhibited that it is basic in character. The proteins are created to be compact and stable at their pI. Among the nine five proteins are presented instability index lesser than 40, signifying that the protein is stable. Aliphatic index of the proteins extended between 56.03 -94.82. The computed extinction coefficients help in the quantifiable study of proteinprotein and protein-ligand relations in solution. The range of GRAVY (Grand Average of Hydropathicity) of C. gynandra proteins was found to be -0.023 to -0.655. The lowest value of GRAVY shows the possibility of better interaction with water.
The secondary structure prediction of C. gynandra proteins (Table-3) was exhibit by SOPMA which revealed that alpha helix, extended strand, beta turn and random coil, were more main. In all the three proteins alpha helix dominates which is tracked by random coil, extended strand and beta turn. The secondary structure was using default parameters (Window width: 17, similarity Secondary structure of proteins by SOPMA revealed that α -helix, random coil, β -turn and extended strand were more predominant. In rbcL , maturase K, capid protein α -helix predominates, whereas V2 protein L32, C4 protein random coil region was frequent (Table: 2). In Replication enhancer, A4 protein Beta subunit, Ribosomal protein II, Replication enhancer extended strand controls followed by random coil and α -helix. Domains are evolutionary units, frequently known as repeated sequence or 3D structure [14].   (Fig 2.). Merging and separation are two vital phylogenetic properties, which can be valuable to novelty and closely as well as distantly related group containing C. gynandra protein sequences [15]. The minimum degree of divergence was found between Capisicum annumn, while the maximum degree of divergence was found between Ulmus alata unicolor. This outcome suggests that C. gynandra protein sequences are conserved and they are developed from a common ancestor [16].

CONCLUSION
Now-a-days designing and developing Medicinal plants built on ethanobotanical and traditional systems of medicine is fast extra importance. The use of in silico methods for drug discovery in natural products has enhanced during the past decade. However, even the application of currently existing chemo-and bioinformatics capitals and approaches provide valuable data for finding of new applications of conservational and industrial wastes beyond their traditional use. The bioinformatics studies, which overwhelmingly and broadly confirms its therapeutic potential. Hence, the vital to exploit the abilities of these plants particularly in areas of traditional medicine and therapeutic industries growths.