TRPV Ion channels are sophisticated molecular sensors designed to respond to distinct temperature thresholds. The recent surge in cryo-EM structures has provided numerous insights into the structural rearrangements accompanying their opening and closing; however, the molecular mechanisms by which TRPV channels establish precise and robust temperature sensing remain elusive. In this work we employ molecular simulations, multi-ensemble contact analysis, graph theory, and machine learning techniques to reveal the temperature-sensitive residue-residue interactions driving allostery in TRPV3. We find that groups of residues exhibiting similar temperature-dependent contact frequency profiles cluster at specific regions of the channel. The dominant mode clusters on the ankyrin repeat domain and displays a linear melting trend while others display non-linear trends. These modes describe the residue-level temperature response patterns that underlie the channel's functional dynamics. With network analysis, we find that the community structure of the channel changes with temperature. And that a network of high centrality contacts connects distant regions of the protomer to the gate, serving as a means for the temperature-sensitive contact modes to allosterically regulate channel gating. Using a random forest model, we show that the contact states of specific temperature-sensitive modes are indeed predictive of the channel gate's state. Supporting the physical validity of these modes and networks are several residues identified with our analyses that are reported in literature to be functionally critical. Our results offer high resolution insight into thermo-TRP channel function and demonstrate the utility of temperature-sensitive contact analysis.

MOTIVATION: For a complex molecular system the delineation of atom-atom contacts, exposed surface and binding sites represents a fundamental step to predict its interaction with solvent, ligands and other molecules. Recently, atom depth has been also considered as an additional structural descriptor to correlate protein structure with folding and functional properties. The distance between an atom and the nearest water molecule or the closest surface dot has been proposed as a measure of the atom depth, but, in both cases, the 3D character of depth is largely lost. In the present study, a new approach is proposed to calculate atom depths in a way that the molecular shape can be taken into account. RESULTS: An algorithm has been developed to calculate intersections between the molecular volume and spheres centered on the atoms whose depth has to be quantified. Many proteins with different size and shape have been chosen to compare the results obtained from distance-based and volume-based depth calculations. From the wealth of experimental data available for hen egg white lysozyme, H/D exchange rates and TEMPOL induced paramagnetic perturbations have been analyzed both in terms of depth indexes and of atom distances to the solvent accessible surface. The algorithm here proposed yields better correlations between experimental data and atom depth, particularly for those atoms which are located near to the protein surface. AVAILABILITY: Instructions to obtain source code and the executable program are available either from http://sienabiografix.com or http://sadic.sourceforge.net CONTACT: [email protected] SUPPLEMENTARY INFORMATION: http://www.Sienabiogzefix.com/publication.