The recent breakthrough made in the field of three-dimensional
(3D) structure prediction by artificial intelligence softwares, such
as initially AlphaFold2 (AF2) and RosettaFold (RF) and more recently
large Language Models (LLM), has revolutionized the field of structural
biology in particular and also biology as a whole. These models have
clearly generated great enthusiasm within the scientific community,
and different applications of these 3D predictions are regularly described
in scientific articles, demonstrating the impact of these high-quality
models. Despite the acknowledged high accuracy of these models in
general, it seems important to make users of these models aware of
the wealth of information they offer and to encourage them to make
the best use of them. Here, we focus on the impact of these models
in a specific application by structural biologists using X-ray crystallography.
We propose guidelines to prepare models to be used for molecular replacement
trials to solve the phase problem. We also encourage colleagues to
share as much detail as possible about how they use these models in
their research, where the models did not yield correct molecular replacement
solutions, and how these predictions fit with their experimental 3D
structure. We feel this is important to improve the pipelines using
these models and also to get feedback on their overall quality.