Have you heard about AlphaFold?

AlphaFold is a deep learning-based protein structure prediction algorithm developed by Google's DeepMind and was first introduced in 2018 and has since become one of the most accurate and widely used methods for predicting protein structures.

One of the main challenges in biology is to understand the structure of proteins, as the structure determines the function of a protein. Understanding the structure of a protein can be used to study its biological role, its interactions with other molecules, and in drug discovery. The most common experimental methods to determine the structure of a protein are X-ray crystallography and Nuclear Magnetic Resonance (NMR) spectroscopy, but they have limitations, they are time-consuming, and costly, and not all proteins can be studied using these methods.

AlphaFold is a computational method that uses deep learning to predict the structure of a protein based on its amino acid sequence. The algorithm is trained on a large dataset of known protein structures and uses this information to predict the structure of a new protein. The algorithm is divided into two parts: a deep neural network that predicts the distance between pairs of residues in a protein, and a refinement algorithm that uses this information to generate an accurate 3D structure.

One of the most remarkable features of AlphaFold is its accuracy. In 2018, AlphaFold was tested against a dataset of proteins whose structures were unknown, and it was able to predict the structure of 25% of the proteins with near-atomic accuracy. In the next years, the algorithm was improved and in 2020, AlphaFold 2 was released and it was able to predict the structure of nearly 40% of the proteins with near-atomic accuracy.

AlphaFold has many potential applications in the field of biology. For example, it can be used to predict the structure of proteins that are difficult to study experimentally, such as transmembrane proteins, and it can be used to study the structure of proteins that have not yet been discovered. Additionally, it can be used to aid in the development of new drugs and therapies by helping scientists to identify specific sites on a protein that can be targeted by a drug molecule.

In conclusion, AlphaFold is a deep learning-based algorithm that is able to predict the structure of proteins with near-atomic accuracy. Its high accuracy has the potential to revolutionize the field of biology by enabling the study of proteins that are difficult to study experimentally and providing new insights into the structure and function of proteins. Understand AlphaFold Metrics for Structural Evaluation

In case you are new to the field, Protein Structural Modeling will help in the foundation.