  Intrinsically disordered proteins (IDPs) constitute a broad set of proteins
with few uniting and many diverging properties. IDPs-and intrinsically
disordered regions (IDRs) interspersed between folded domains-are generally
characterized as having no persistent tertiary structure; instead they
interconvert between a large number of different and often expanded structures.
IDPs and IDRs are involved in an enormously wide range of biological functions
and reveal novel mechanisms of interactions, and while they defy the common
structure-function paradigm of folded proteins, their structural preferences
and dynamics are important for their function. We here discuss open questions
in the field of IDPs and IDRs, focusing on areas where machine learning and
other computational methods play a role. We discuss computational methods aimed
to predict transiently formed local and long-range structure, including methods
for integrative structural biology. We discuss the many different ways in which
IDPs and IDRs can bind to other molecules, both via short linear motifs, as
well as in the formation of larger dynamic complexes such as biomolecular
condensates. We discuss how experiments are providing insight into such
complexes and may enable more accurate predictions. Finally, we discuss the
role of IDPs in disease and how new methods are needed to interpret the
mechanistic effects of genomic variants in IDPs.
