CHAPTER ONE
INTRODUCTION
The term in silico was coined in 1989 as allusion to the Latin Phrases in-viro, in-vitro and in-situ which are commonly used in biology.
In silico studies refers to the studies, facts, findings or experiment done in living organisms (i.e. the medicinal plant species) outside living organism (computer system) and where they are found in nature respectively.
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;
Mitochondrial and Plastid genomes show a wide array of architectures i.e. (make up) varying immensely in size, structures and content. Some organelle DNA’s have even developed elaborate eccentricities such as scrambled coding regions, non-standard genetic codes and convoluted modes of post-transcriptional modification and editing. Here we compare and contrast the breadth of genomic complexity between mitochondrial and plastid chromosomes.
However, the complexity and intensity of genomic embellishments are consistently more pronounced for mitochondria than for plastids even when they are found in both compartments. We explore the evolutionary forces responsible for these patterns and argue the organelles DNA repair processes, mutation rates and population genetic landscapes are all important factors leading to the observed consequence and divergence in organelle genome architecture.
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 genes using mathematical and statistical techniques. More broadly, Bioinformatics is applied statistics and computing to biological science.
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 novel drugs like Bridion.
In silico studies/drugs designing software plays an important roles to design innovative proteins.
With the increasing concern on the side effects caused by modern synthetic on chemical drugs, 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.
In silico studies/analysis for instance in Allium sativum (garlic) detects the novel metabolites (metabolites) and its validation (Nabarun, Roy KAU). Through In silico, the media and the properties of the selected medicinal plants e.g. garlic which is due to the presence of organosulfur compounds and several polyphenolic compounds are explored and analyzed. The major organosulfur compounds in garlic include allin, allicin, I-y—glutamyl-S-allygyl-I-Cysteine, allyl, mercaptan, diallyl disulfide, diallyltrisulfideallyl propyl disulfide, vinyldithin.
This study entitled “In silico studies of protein structure variation in PDVI and MATK genes in selected medicinal plants viz;
- Ocimum gratissimum (scent leaves)
- Zingiber Officinale (Ginger) and
- Allium Sativum (Garlic)
Is taking to analyses the medicinal effects of important compounds in the above medicinal plants inhibiting the targets involved in lifestyle diseases such as cancer, cardiovascular diseases, arthritis, and diabetic complications through in silico molecular docking analysis and validation through wet laboratory analysis.
1.1 Rationale for the Study (Justification)
Medicinal plants such as Occimum gratissimum, zingiber officinale and Allium sativum have been used as a source of medicine since historic times and several commercially important drugs are of plant-based origin. In the era of high volume, high throughput data generation across the biosciences, bioinformatics plays a crucial role. This has generally been the context of drug designing and discovery.
Availability of the functional and active components of maturase k {mat k} and plastid division 1{PDV1} genes in medicinal 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 medicinal plants will depend largely on the improvements in functional and structural traits that controls photosynthesis, nutrition and plant metabolism in general. There is the need to study maturase k and protein division1genes underlying this potential to unveil the characteristics which makes the usefulness of these genes unique to the plant breeder and biotechnologist.
Also, areas in medicinal plants research where the application of bioinformatics methodologies may result in quicker and potentially cost-effective heads toward finding plant-based remedies.
1.2 Aims and Objectives
This study is based on the use of computer simulations in analyzing MATK and PDV1 genes in Zingiber officinale (ginger).
The study was designed to;
- Compare the percent identity and similarity of MATK and PDV1 genes (Maturase K) (Plastid Division).
- To determine the physiochemicals of MATK and PDV1of selected medicinal plants.
- To determine or predict the secondary and tertiary structures of MATK and PDV1 genes of selected medicinal plants.
- Determine the G-C content of the genes.
