Proteins are large molecules that play a vital role in many biological processes. They can act as enzymes, which catalyze chemical reactions; receptors, which bind to specific molecules and trigger a cellular response; and transporters, which move molecules across cell membranes. Drugs often work by binding to proteins and interfering with their function.
However, it can be difficult to predict how a drug will interact with a protein. This is because proteins are complex molecules with many different binding sites. The strength of a drug's binding to a protein depends on the chemical structure of the drug, the structure of the protein, and the environment in which the interaction takes place.
The AFE method developed by the UCSD researchers addresses this challenge by using a combination of computational and experimental techniques. The computational component of the method uses a molecular dynamics simulation to calculate the free energy of binding between a drug and a protein. The experimental component of the method uses a technique called "fluorescence anisotropy" to measure the binding affinity between a drug and a protein.
The AFE method is able to accurately calculate the binding affinity of a drug for a protein even when the protein is flexible and has multiple binding sites. This makes the method a valuable tool for drug discovery.
"Our method could help scientists design new drugs that are more effective and have fewer side effects," said Rommie Amaro, a professor of chemistry and biochemistry at UCSD and the senior author of the study. "We are excited to see how our method will be used to develop new therapies for diseases such as cancer, Alzheimer's, and HIV."
The study was published in the journal Nature Methods.
