TY - JOUR
T1 - The current role and evolution of X-ray crystallography in drug discovery and development
AU - Bijak, Vanessa
AU - Szczygiel, Michal
AU - Lenkiewicz, Joanna
AU - Gucwa, Michal
AU - Cooper, David R.
AU - Murzyn, Krzysztof
AU - Minor, Wladek
N1 - Publisher Copyright:
© 2023 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2023
Y1 - 2023
N2 - Introduction: Macromolecular X-ray crystallography and cryo-EM are currently the primary techniques used to determine the three-dimensional structures of proteins, nucleic acids, and viruses. Structural information has been critical to drug discovery and structural bioinformatics. The integration of artificial intelligence (AI) into X-ray crystallography has shown great promise in automating and accelerating the analysis of complex structural data, further improving the efficiency and accuracy of structure determination. Areas covered: This review explores the relationship between X-ray crystallography and other modern structural determination methods. It examines the integration of data acquired from diverse biochemical and biophysical techniques with those derived from structural biology. Additionally, the paper offers insights into the influence of AI on X-ray crystallography, emphasizing how integrating AI with experimental approaches can revolutionize our comprehension of biological processes and interactions. Expert opinion: Investing in science is crucially emphasized due to its significant role in drug discovery and advancements in healthcare. X-ray crystallography remains an essential source of structural biology data for drug discovery. Recent advances in biochemical, spectroscopic, and bioinformatic methods, along with the integration of AI techniques, hold the potential to revolutionize drug discovery when effectively combined with robust data management practices.
AB - Introduction: Macromolecular X-ray crystallography and cryo-EM are currently the primary techniques used to determine the three-dimensional structures of proteins, nucleic acids, and viruses. Structural information has been critical to drug discovery and structural bioinformatics. The integration of artificial intelligence (AI) into X-ray crystallography has shown great promise in automating and accelerating the analysis of complex structural data, further improving the efficiency and accuracy of structure determination. Areas covered: This review explores the relationship between X-ray crystallography and other modern structural determination methods. It examines the integration of data acquired from diverse biochemical and biophysical techniques with those derived from structural biology. Additionally, the paper offers insights into the influence of AI on X-ray crystallography, emphasizing how integrating AI with experimental approaches can revolutionize our comprehension of biological processes and interactions. Expert opinion: Investing in science is crucially emphasized due to its significant role in drug discovery and advancements in healthcare. X-ray crystallography remains an essential source of structural biology data for drug discovery. Recent advances in biochemical, spectroscopic, and bioinformatic methods, along with the integration of AI techniques, hold the potential to revolutionize drug discovery when effectively combined with robust data management practices.
KW - Artificial intelligence
KW - drug discovery
KW - ligand identification and refinement
KW - machine learning
KW - protein-small molecule agent complexes
KW - structure validation
UR - https://www.scopus.com/pages/publications/85168282135
U2 - 10.1080/17460441.2023.2246881
DO - 10.1080/17460441.2023.2246881
M3 - Review article
C2 - 37592849
AN - SCOPUS:85168282135
SN - 1746-0441
VL - 18
SP - 1221
EP - 1230
JO - Expert Opinion on Drug Discovery
JF - Expert Opinion on Drug Discovery
IS - 11
ER -