We use geometrical considerations to provide a different perspective on the fact that a few selected amino acids, the so-called “key residues,” act as nucleation centers for protein folding. By constructing graphs corresponding to protein structures we show that they have the “small-world” feature of having a limited set of vertices with large connectivity. These vertices correspond to the key residues that play the role of “hubs” in the network of interactions that stabilize the structure of the transition state.

We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises.