Moderators
Enrique Espinosa
Arie van der Lee
Summary
Since a couple of years new methodology is changing rapidly the way how we have traditionally solved and refined crystal structures. Using machine/deep learning and artificial intelligence we are now capable to solve the molecular structures of proteins even without experimental data (Alphafold), and small molecule or inorganic crystal structures with incomplete and/or limited-resolution data (PhAI). These crystal structures can now also be refined using non-spherical form factors obtained by quantum-mechanical calculations giving access to a wealth of chemical properties not accessible before. This session intends to give an overview of the possibilities and applications of artificial intelligence, machine/deep learning and quantum-mechanical methods in all fields of crystallography: structural biology, molecular and inorganic chemistry, dispersed systems (saxs/sans).