Applications of AlphaFold in the Medical Field

Abstract

Traditional protein structure determination techniques, including X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy, are typically time-consuming and labor-intensive. Moreover, these approaches face inherent constraints when dealing with specific protein classes, such as membrane proteins, which pose substantial technical hurdles. This severely hinders in-depth elucidation of the molecular mechanisms underlying life processes and impedes advancements in drug discovery and development. However, the advent of AlphaFold, an AI, has completely altered the landscape. AlphaFold can rapidly and accurately predict a protein’s three-dimensional architecture directly from its amino acid sequence alone, representing a paradigm shift in structural biology and broader life sciences. Therefore, through a review of the literature and representative cases, this paper systematically examines the fundamental principles and evolutionary trajectory of AlphaFold. This study highlights its key applications in target discovery, protein design, and genetic mutation analysis in medical research. In addition, it also evaluates the technological strengths of AlphaFold and explores its existing limitations as well as future development directions.