3.0 EXAMPLES OF THE BIOINFORMATICS APPLICATION

3.1 Computer Aided Drug Design

Computer-aided drug design or CADD is specialised software that uses the computational methods to stimulate the drug-receptor interactions (Casey, 2005). Basically, this software mostly depends on the bioinformatics tool, applications and database to it to function. CADD exploits the state of the art technologies to speed the drug development process. Apart from that, this CADD was established on 1900 with the information of the receptor and lock-and-key concept. Further development has been done to improve the quality and function of this CADD. The latest CADD software comes with information of the human genome, bioinformatics, combinatorial chemistry and high-throughput screening.

Basically, CADD using variety of different algorithms and approximations of the binding free energy of chemical compound to a molecular target can be generated in silico. Besides that, CADD allows user to speed up the task of developing new drugs and reduces the cost for the research. Apart from that, CADD enables user for a rapid testing of new, unsynthesised classes of the compounds.

3.2 Rational Drug Design

Rational drug designs are known as focused approach which uses information about the structure of a drug receptor or its natural ligands to identify or create candidate drugs. Basically, three-dimensional structure of a protein can be determined by using methods such as X-ray crystallography or nuclear magnetic resonance spectroscopy (Twyman, 2002). With the presence of this information, the researchers in pharmaceutical industry can use powerful computer programs to search through database containing the structure of many different chemical compounds.

 Rational drug design can be divided into two categories. Firstly, the category A is divided as the development of small molecule with desired properties for targets, biomolecules (protein or nucleic acid), whose functional roles in cellular processes and 3D structural information are known (Soma Mandal, 2009). In addition, this approach in drug design is well established and is being applied extensively by the pharmaceutical industries. The second categories B is development of small molecules with the predefined properties for targets, whose cellular functions and their structural information may be known or unknown (Soma Mandal, 2009). Besides that, knowledge of unknown target (genes and proteins) can be obtained by analysing global gene expression data of samples untreated and treated with a drug using advanced computational tools. Steps related to these two approaches and evaluations of other properties in rational drug design are presented in the following flow charts 1, 2, and 3.

Basically when the target is identified, then both approaches A and B for the development of small molecules requires some examination which stated in the flow chart 3. These aspect includes the evaluation of the binding scores such as affinity and specificity, balance between hydrophobicity and lipophilicity, absorption, distribution, metabolism and excretion (ADME), electrophilic, nucleophilic, and radical attack (biodegradation)(Soma Mandal, 2009). Besides that, evaluation of toxicity of the parent small molecules and products due biotransformation in the different phases of metabolism, quantitative structure–activity relationship (QSAR), and quantitative structure–property relationship (QSPR) respectively.

In addition, designing of the small molecule could be performed initially using computational tools. After the initial evaluation and identification of lead molecules, gene expression profiling and bioinformatics analysis would be particularly important to gain insight in gene expression patterns.  Apart from that, this knowledge can be utilized to improve drugs to accomplish desirable attributes such as disease free survival, eradication of disease, elimination or minimization of toxic side effects, reduction of undesirable biotransformation, improvement in distribution (bioavailability), overcoming of drug resistance, and improvement of immune responses(Soma Mandal, 2009). Therefore, rational drug design would be an integral approach to drug development and discovery.