Greetings and Happy New Year to All! My question is about broadly protein-protein interactions (PPIs. Last year several manuscripts came out proposing new metrics for assessing PPIs. This was in logical response to the growing understanding that ipTM (alone) is a fairly flawed metric, particularly for detecting interactions that involve a small number/fraction of the total residues. For those interested, I’ve pasted links to three such papers below (Coincidentally one is from a former roommate's lab, which I didn’t notice until recently!). Some may be easier to use than others (have GUIs). Tom Goddard and I emailed back and forth a bit about the relative merits of some of these metrics - nothing is perfect obviously (thank you again Tom). With respect to ChimeraX, I was wondering if there was a way to extract average PAE values after employing a cutoff. For example, "alphafold contacts /A distance 5 maxPae 5” will tell me that are "54 residue or atom pairs within distance 5 with pae <= 5”. But what if I want to know the average of those 54? Along those lines, for some PPIs there may be several spatially separated interfaces, with each one contributing to the total number. Is there an easy way to obtain the average and other metrics for each one? Some of this information I could probably find in my clunky (borderline boomer) way, by filtering, adding, and averaging values from the pairwise data (perhaps made easier by Predictome). Lastly, drawing rectangles on the PAE plot does a great job of giving coordinates and the average PAE, but it doesn’t give the range or other potentially useful data, such as the number of PAE<5 values etc. I guess I’m thinking that it could be very useful to be able to get metrics for a prescribed region of the PAE plot simply by drawing the rectangle. (And maybe there is but I missed it.) Those are my questions and thoughts. But I also wanted to express my gratitude for the ChimeraX software, and even more, the people working at ChimeraX who are always exceptionally responsive and helpful. David https://www.biorxiv.org/content/10.1101/2024.02.19.580970v1 https://www.biorxiv.org/content/10.1101/2024.10.23.619601v1 https://www.biorxiv.org/content/10.1101/2024.04.09.588596v1 David S. Fay Ph.D. Professor, Department of Molecular Biology Associate Director, National Institutes of Health Wyoming INBRE University of Wyoming email: davidfay@uwyo.edu