Sesamum indicum is an annual herb of the family Pedaliaceae. The plant is commonly known as beniseed, benneseed in English and it is found in tropical and subtropical areas of Asia, Africa and South America. Compared to similar crops, such as peanuts, soybean, and rapeseed, the seeds of sesame are believed to have the most oil. Sesame seed is one of the oldest oilseed crops known, domesticated well over 3000 years ago. S. indicum has many other species, most being wild and native to sub-Saharan Africa. S. indicum, the cultivated type, originated in India (Ogasawara, et al., 1988) and is tolerant to drought-like conditions, growing where other crops fail (Raghav et al., 1990). Sesame has been widely known for its oil seeds production which has also finds wide applications in the food and pharmaceutical industries due to their significance. The genes responsible for this oil production trait is the lipid transfer protein 1 gene whose properties, functions and structures, this research tries to analyze using in silico approach.
The expression in silico was first used in public in 1989 in the workshop “Cellular Automata”: Theory and Application in Los Alamos New Mexico by Pedro Miramontes a Mathematician from National Autonomous University of Mexico (UNAM) who presented the report “DNA and RNA physiochemical constraints, Cellular Automata and Molecular Evolution;
Plants genome shows a wide array of architectures i.e. (genetic make-up) varying immensely in size, structures and content. Some organelle DNA’s have even developed elaborate peculiarities such as scrambled coding regions, non-standard genetic codes and convoluted modes of post-transcriptional modification and editing all of which has been deciphered using bioinformatics tools.
Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data. As an interdisciplinary field of science, bioinformatics combines Computer Science, Biology, Mathematics and Engineering to analyze and interpret biological data.
Bioinformatics has been used for in silico analyses of biological data and genes using mathematical and statistical techniques. Bioinformatics has become an important part of many areas of biology. In experimental molecular biology, Bioinformatics techniques such as image and signal processing allow extraction of useful results from large amount of raw data. In the field of genetics and genomics, it aids in sequencing and annotating genomes and their observed mutations. It plays a role in the text miming of biological literature and the development of biological and gene ontologies to organize and query biological data. It also plays a role in the analysis of gene and protein expression and regulation. Bioinformatics tools aid in the comparison of genetic and genomic data and more generally in the understanding of evolutionary aspects of molecular biology. At a more integrative level, it helps to analyze and catalogue the biological pathways and networks that are an important part of systems biology. In structural biology, it aids in the simulation and modeling of DNA, RNA, proteins as well as bimolecular interactions.
In Genetics and Biochemistry, in silico studies can be used to examine the molecular modeling of gene, gene expression, gene sequence analysis and 3D structure of proteins, identification of diseases and prediction of lipid metabolic pathways. In silico studies/drugs designing software plays an important role to design innovative proteins.
With the increasing concern on the side effects caused by modern synthetic on chemical drugs, oil seeds and medicinal plants remain the main source of a large range of basic healthcare and pharmaceutical products. Successful attempts, to produce some of the valuable in relatively large quantities by cell cultures have been reported.
Oil rich plants such as Sesame indicum have been used as a source of food and medicine since historic times. In the era of high volume, high throughput data generation across the biosciences, bioinformatics plays a crucial role in food, drug design, drug discovery and metabolism.
Availability of the functional and active components of lipid transfer protein genes in plant species is an indication of increase yield and high output for medicinal relevance and therapeutic security. The yield and potency of active ingredients in the oil rich plants will depend largely on the expressions in functional and structural of the LTP gene that controls photosynthesis, nutrition and lipid metabolism in general. There is therefore, need to study lipid transfer protein genes underlying this potential to unveil the physiochemical characteristics and other parameters which makes the usefulness of these genes unique to the plant breeders and biotechnologists.
The study is aimed at using in silico approach to evaluate lipid transfer protein (LTP) gene variations in sesame and other plants.
The objectives of the study are to identify the percentage identity and similarity in the Lipid Transfer Protein (LTP) gene in sesame and other plants, to determine the variations in the physiochemical properties of the Lipid transfer protein (LTP) gene in sesame and other plants, to determine the Lipid transfer protein (LTP) gene stability in terms of their Guanine – cytosine contents.