Alanine scanning mutagenesis is used to analyze the function of specific amino acid residues on protein surface. Charged residues on the surface of proteins are usually not necessary for the overall structure of proteins, but they are generally involved in ligand binding, oligomerization or catalysis. Replacing charged amino acid residues with alanine residues can eliminate the side chains outside the beta-carbon structure and destroy the functional roles of amino acids, but does not change the conformation of the main chain of proteins. Therefore, alanine scanning is a very useful method to study the function of specific areas on protein surface.
So far, it has not been very reliable to use computer simulations to predict which drug candidates provide the greatest potential, because the chemical properties of small drug-like molecules and protein amino acids vary greatly. At present, researchers at Uppsala University in Sweden have skillfully developed a method and proved that this method is accurate, reliable and versatile.
G-protein coupled receptors (GPCRs) are the largest class of human drug target proteins, and approximately 40% of all drugs on the market can target them. GPCR is an important protein in cell signaling and is a membrane protein that is signally linked to G protein. Professor Johan Åqvist, the head of the study, explained that these receptors recognize and transmit a variety of different signals from outside the cell, regulating most of the cellular responses to hormones, neurotransmitters, as well as vision, smell and taste. The 2012 Nobel Prize in Chemistry was awarded to two American scientists who have made outstanding contributions to the field of "G-protein coupled receptors".
The key to the research and development of modern new drugs is to find, determine and prepare drug screening targets - molecular drug targets. The drug target refers to the binding site of the drug in the body, including biological macromolecules such as gene loci, receptors, enzymes, ion channels, and nucleic acids. Identifying new effective drug targets is a top priority for new drug development. A total of about 500 have been identified as therapeutic drug targets to date, and G-protein coupled receptor (GPCR) targets account for the vast majority of receptors. Today we only know about the three-dimensional molecular structure of 20 of these receptors. Understanding these molecular structures is very important for drug development. The increasing crystal structure of G-protein coupled receptors paves the way for the detailed description of receptor ligand interactions and energetics using advanced computer models.
The methods used today to understand receptor function are complex and time consuming, and traditional methods combine site-directed mutagenesis, biochemical experiments, and computational three-dimensional structural models. First, the binding strength of a series of molecules (so-called binding of agonists and antagonists) is determined. Mutations are then induced in the receptor to ascertain how the binding properties are affected.
This is very time consuming and often difficult because genetically engineered receptors must be expressed in living cells. Johan Åqvist said that using their calculations, mutations can be created in the computer and the effects of receptor binding can be calculated very accurately.
Previously, the problem with this type of computational simulation approach has been that protein amino acids are very different, depending on size, charge, etc., which is an existing problem in computation. But when the researchers divided the program into a series of smaller calculations, they suddenly got accurate and stable results.
Researchers have now tested this method on a neuropeptide receptor and demonstrated that it can predict the effects of mutations and the ability of receptors to bind to a range of different molecules with great reliability. This method also allows us to judge whether the three-dimensional structural model of the molecules combined with each other is correct.
Johan Åqvist believes that these results can be extremely useful for drug research. It allows us to find new drug candidates faster and easier. This method of calculation is also very versatile, so it can also be used to study various other proteins that bind various functional molecules.