Bioinformatics in Structure-Based Drug Design

Bioinformatics played a major role in Drug designing and discovery.

What is drug designing?

This is the way of finding new drugs with the help of its design based on their biological target. This target is usually a key molecule that causes a disease condition, or infection, or maybe survival of pathogen and plays a role in biological pathways, such as the metabolic pathway, signaling pathway, etc.
So the drug is synthesized in such a way that when it binds to the target, it inhibits the molecule from causing the above as well as it doesn’t affect any other part of the body by binding the targets which are similar in design to the target molecule. This kind of confusion is usually avoided by performing a sequence homology, where sequences (DNA/Protein) are compared to find any similarities along its length which can prove to show that the molecules may have shared an ancestor.
These drugs can be designed structurally by using computational tools, where the drug molecules are designed inside the target molecule knowing its active site and structure. The drug molecule can be designed inside-out or outside-in by deciding to start from the core group or the R-chain(side chain).

Ways of Drug Designing

Rational Drug Design (RDD).
Rational drug design is a process used in the biopharmaceutical industry to discover and develop new drug compounds. RDD uses a variety of computational methods to identify novel compounds, design compounds for selectivity, efficacy and safety, and develop compounds into clinical trial candidates. These methods fall into several natural categories – structure-based drug design, ligand-based drug design, de novo design and homology modeling – depending on how much information is available about drug targets and potential drug compounds.

Structure-based Drug Design (SBDD)
SBDD uses the known 3D geometrical shape or structure of proteins to assist 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 and change its activity. This ability to work at high resolution with both proteins and drug compounds makes SBDD one of the most powerful methods in drug design.
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 sidechains during the docking process. In some cases, there is almost no movement at all (i.e., rigid-body docking); in other cases, there is substantial movement. Flexible docking can have profound implications for designing small-molecule ligands so this is an important feature in SBDD methods.

Ligand-based Drug Design

This approach is most effective when the structure of the binding site/receptor side is not known, but when a series of compounds have been identified that exert the activity of interest. In this case, structurally similar compounds with no activity, high activity and a range of intermediate activity are taken. From these molecules, the template (called the pharmacophore) is identified. It is represented as a collection of functional groups in three-dimensional space that is complementary to the geometry of the receptor site.

De Novo Design

In the de novo design, the entire ligand is designed from the scratch and bind it with the receptor site. But this method does not prove to be an efficient one. The difficulty lies in predicting how this structure will behave in real life. Since ligands are flexible and can take up any conformation and orientation, the question lies in whether the predicted structure will mirror the calculated structure. The second disadvantage is the large range of undesired structures, which are rejected sue to their instability, toxicity, and difficulty in their synthesis.

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Lead Optimization

After a number of lead compounds have been found, SBDD techniques are especially effective in refining their 3D structures to improve binding to protein active sites, a process known as lead optimization. In lead optimization researchers systematically modify the structure of the lead compound, docking each specific configuration of a drug compound in a protein’s active site, and then testing how well each configuration binds to the site. In a common lead optimization method known as bioisosteric replacement, specific functional groups in a ligand are substituted for other groups to improve the binding characteristics of the ligand. With SBDD researchers can examine the various bioisosteres and their docking configurations, choosing only those that bind well in the active site.