The upper bound distance constraints were calculated with respect to the peak integrals.
We identified an average of 13.6 distance constraints per interaction, thereby demonstrating that the method described here, TX-MS, can model large quaternary protein structures by extracting a high-density network of distance constraints directly from complex, unfractionated, biological samples.
The experimentally derived distance constraints are further used to improve the modeling of high-resolution quaternary structures.
While the handful of classical combinatorial characterizations of rigidity focus on distance constraints between points, this is the first result simultaneously addressing coincidence, angular, and distance constraints.
The pathway is predicted using only a combination of distance constraints between contiguous residues and evolutionary data.
Obstacle avoidance is realized by considering distance constraints in the open-loop optimization process.
Tertiary interactions, in the form of distance constraints, are generated from available epitope mapping data.
Based on 41 NOE-derived distance constraints, the 3D structure of QBP1 was determined.
The final models are created through a high-resolution flexible backbone docking protocol that uses both models and all identified distance constraints as input.
Meanwhile, we randomly assign the pairwise distance constraints.
Their algorithm is based on the notion of distance constraints.
