Despite phenomenal rise in R&D spending, pharmaceutical industries are facing a formidable problem in terms of drying pipelines, lack of research productivity and late stage attrition of drug candidates. Increasing the speed and efficiency of drug discovery is a major challenge facing the pharmaceutical industry. Although technologies such as combinatorial chemistry and high throughput screening have increased the speed of synthesis and screening of compounds, industry has failed to achieve the level of desired productivity. This in turn has generated considerable interest in new approaches to drug discovery process. Advances in molecular biology, high throughput crystallography, computational methods and NMR techniques have made structure based drug design (SBDD) a powerful tool in drug discovery.

The pharmacologically relevant information derived from the three dimensional structure of a target protein drives the SBDD process. The advantage of the three dimensional structure of a protein is, you can exactly see how a small molecule ligand interacts with the target protein. X-ray crystallography and NMR have been the methods of choice for obtaining the structural information. Automation and parallelization in the process of protein expression, purification, crystallization and structure determination have led to high throughput crystallography, dispelling the earlier notion that it is a slow process to be effectively employed in drug discovery. Currently more than 35000 structures deposited in the PDB, which is more than ten times the number a decade ago. This wealth of structural information is influencing several aspects of drug discovery process including target selection and prioritization, lead generation and optimization.

The post genomic era has seen a rapid explosion in the number of available targets for treatment of human diseases. However, identification, selection and prioritization of druggable targets remain a challenge. Structure based approaches can provide valuable information in determining the suitability of a target using the pharmacogenetic and mutation profile of the target.

The wealth of structural information has dramatically influenced the lead discovery process. The traditional method of random combinatorial synthesis and HTS has evolved to generate more focused libraries guided by structural information. Availability of a large number of co-crystal structures has led to the development of newer approaches such as virtual target screening. Screening of binding site of a target against a database of co-crystal binding sites can provide critical information about the classes of molecular scaffolds that have the potential to bind to the target of interest. High throughput crystallography and NMR based screening techniques have led to the development of fragment-based approaches for identification of novel scaffolds for specific drug targets.

Lead optimization is one of the driving forces behind the structure based drug design. Critical elements of protein ligand interaction can be directly visualized using the structural information, which in turn can guide modification of the compound to achieve desired properties.

SBDD techniques have been used with great advantage in improving the potency, selectivity and pharmacokinetic profile of the lead molecules. Structural informatics studies within a family of proteins can provide very useful inputs for improving the selectivity profile of the lead molecule. Development of protein kinase inhibitors provides a good example for this. Protein kinases comprise a large family of proteins involved in a variety of biological functions including cell signal transduction. There are more than 500 kinases in the human body and the active site where the ATP molecule binds is highly conserved among them. Achieving selectivity is a key challenge as most kinase inhibitors compete with ATP for binding. However, minor differences in the active site derived from the structural comparisons have led to the successful development of selective kinase inhibitors. The quality of lead compounds is thought to have a major impact on late stage attrition rates. Availability of structures of proteins such as CYPs and various ion channels have led to the development of improved in silico ADME filters which help in selection of quality lead molecules.

Structure-based approaches to discovery process have become an integral part of most pharmaceutical companies. The importance of SBDD is set to broaden through out the discovery process with increases in the numbers and classes of available protein structures. Using this structural information appropriately in the decision making process is key to the success of this approach.

(The authors, Dr Subrahmanya Hosahalli is vice-president, Lead Generation & Structural Biology, Dr Murali Ramachandra, vice-president, Pre-clinical Biology and Dr. Ramesh Sistla , scientist, Computational Chemistry, Aurigene Discovery Technologies Ltd. Bangalore)