Drug design, also known as rational drug design, is the inventive process of finding new medications based on the knowledge of a biological target. Drug design defines the design of molecules that are complementary in shape and charge to the bimolecular target with which they interact and therefore will bind to it.
Pharmacokinetics of drug design:
Drugs must be polar, to be soluble in aqueous conditions
to interact with molecular targets
Drugs must be ‘fatty’ to cross cell membranes
Drugs must have both hydrophilic and lipophilic characteristics
Many drugs are weak bases with pKa ’s 6-8
COMPUTER-AIDED DRUG DESIGN (CADD)
It is a specialized discipline that uses computational methods to simulate drug-receptor interactions. CADD methods are heavily dependent on bioinformatics tools, applications and databases. In CADD research, one often knows the genetic sequence of multiple organisms or the amino acid sequence of proteins from many species. It is very useful to determine how similar or dissimilar the organisms are based on gene or protein sequences. With this information one can infer the evolutionary relationships of the organisms, search for similar sequences in Bioinformatics databases and find related species to those under investigation. There are many Bioinformatics sequence analysis tools that can be used to determine the level of sequence similarity.
Structure-Based Drug Design (SBDD)
Structure-based drug design is one of many methods in the rational drug design toolbox. Drug targets are typically key molecules involved in a specific metabolic or cell signaling pathway that is known, or believed, to be related to a particular disease state. Drug targets are most often proteins and enzymes in these pathways. Drug compounds are designed to inhibit, restore or otherwise modify the structure and behavior of disease-related proteins and enzymes. SBDD uses the known 3D geometrical shape or structure of proteins to help in the development of new drug compounds. The 3D structure of protein targets is most often derived from x-ray crystallography or nuclear magnetic resonance (NMR) techniques. X-ray and NMR methods can resolve the structure of proteins to a resolution of a few angstroms (about 500,000 times smaller than the diameter of a human hair). At this level of resolution, researchers can precisely examine the interactions between atoms in protein targets and atoms in potential drug compounds that bind to the proteins. This ability to work at high resolution with both proteins and drug compounds makes SBDD one of the most powerful methods in drug design.
With high-resolution x-ray and NMR structures for proteins and ligands, researchers can show precisely how ligands orient themselves in protein active sites. Furthermore, it is well known that proteins are often flexible molecules that adjust their shape to accommodate bound ligands. In a process called molecular dynamics, SBDD allows researchers to dock ligands into protein active sites and then visualize how much movement occurs in amino acid side chains during the docking process. In some cases, there is almost no movement at all (i.e., rigid-body docking); in other cases, such as with the HIV-1 protease enzyme, there is substantial movement.
Virtual High-Throughput Screening (vHTS) Pharmaceutical companies are always searching for new leads to develop into drug compounds. One search method is virtual high-throughput screening. In vHTS, protein targets are screened against databases of small-molecule compounds to see which molecules bind strongly to the target. If there is a hit with a particular compound, it can be extracted from the database for further testing. With today's computational resources, several million compounds can be screened in a few days on sufficiently large clustered computers.
Ligand-based drug design
It relies on knowledge of other molecules that bind to the biological target of interest. These other molecules may be used to derive a pharmacophore model that defines the minimum necessary structural characteristics a molecule must possess in order to bind to the target. In other words, a model of the biological target may be built based on the knowledge of what binds to it, and this model in turn may be used to design new molecular entities that interact with the target.