  Transition state (TS) search is key in chemistry for elucidating reaction
mechanisms and exploring reaction networks. The search for accurate 3D TS
structures, however, requires numerous computationally intensive quantum
chemistry calculations due to the complexity of potential energy surfaces.
Here, we developed an object-aware SE(3) equivariant diffusion model that
satisfies all physical symmetries and constraints for generating sets of
structures - reactant, TS, and product - in an elementary reaction. Provided
reactant and product, this model generates a TS structure in seconds instead of
hours required when performing quantum chemistry-based optimizations. The
generated TS structures achieve a median of 0.08 {\AA} root mean square
deviation compared to the true TS. With a confidence scoring model for
uncertainty quantification, we approach an accuracy required for reaction rate
estimation (2.6 kcal/mol) by only performing quantum chemistry-based
optimizations on 14\% of the most challenging reactions. We envision the
proposed approach useful in constructing large reaction networks with unknown
mechanisms.
