Changing parameters (especially the # of residues per site) in the scheme for identifying surface-critical residues

Q:

I would like to ask for advice on your recently published STRESS tool. I would like to use it to identify residues that might be involved in allostery, however in the case of surface critical residues, it currently reports only up to ten residues per binding pocket. Is there a way to "hack" the identify_high_confidence_BL_sites.py script (which writes this file) to write all such residues, according to some probability cutoff? (I’m a Perl programmer, with relatively limited python experience.) Thank you in advance.

A:
In order to change the number of residues reported for each site, you may download and modify 2 of the C scripts (available on the stress github page)

For example, to modify the scripts such that the new limit is set to 15 residues (you can change this cutoff number to be any arbitrary value that you wish), do the following:

1) In the script bindingSiteMeasures.c, replace instances of "10" with "15" in lines 77, 79, 217, 219, 240, 242.

2) In the script surfaceProbe.c, I replace instances of "10" with "15" in lines 1227, 1229, 1235, 1237.

3) Recompile the source code and re-run the calculations.

However, with respect to the parameters in general, we should note that the parameters of the surface-site identification scheme were established using a known set of allosteric residues. That is, our parameters were established empirically to best capture known allosteric sites. The details of all this can be found in the Supplementary Materials of the paper, specifically in the Supp section 3.1-a-iii "Defining & Applying Thresholds to Select High-Confidence Surface-Critical Sites". Thus, we would advise against changing them, since again, they were empirically optimized.

Batch submissions to the STRESS server

Q:
I have a large number of structures that I would like to submit to the STRESS server. Does the server offer an option for batch submissions?

A:
The STRESS server itself does not currently provide an option for batch submissions. However, we encourage users to try implementing such jobs by running the source code available on our GitHub page. This may be accessed through github.com/gersteinlab/STRESS

Distinction Between Surface- and Interior-Critical Residues

Q:
What is the main difference between surface- and interior-critical residues?

A:
Allosteric surface residues play regulatory roles that are fundamentally distinct from those of allosteric residues within the interior. While surface residues may often constitute the sources or sinks of allosteric signals, interior residues act to transmit such signals. Thus, different approaches are needed for identifying these two classes of residues. Surface-critical residues are identified by finding pockets such that the occlusion of such pockets is likely to interfere with large-scale protein motions (see Documentation for details; see also Ming and Wall, 2005; Mitternacht and Berezovsky, 2011). Interior-critical residues are identified by finding information-flow bottlenecks within the protein structure (see Documentation and main paper for details; see also del Sol et al, 2006; Ghosh et al, 2008; Rousseau et al, 2005).

del Sol, A., Fujihashi, H., Amoros, D., and Nussinov, R. (2006). Residues crucial for maintaining short paths in network communication mediate signaling in proteins. Mol. Syst. Biol. 2(1).

Ghosh, A., and Vishveshwara, S. (2008). Variations in Clique and Community Patterns in Protein Structures during Allosteric Communication: Investigation of Dynamically Equilibrated Structures of Methionyl tRNA Synthetase Complexes. Biochemistry. 47, 11398-11407.

Ming, Dengming, and Michael E. Wall. “Quantifying allosteric effects in proteins.” Proteins: Structure, Function, and Bioinformatics 59.4 (2005): 697-707.

Mitternacht, S. and Berezovsky, I.N. (2011). Binding leverage as a molecular basis for allosteric regulation. PLoS Comput. Biol. 7, e1002148.

Rousseau, F. and Schymkowitz, J. (2005). A systems biology perspective on protein structural dynamics and signal transduction. Curr. Opin. Struct. Biol. 15, 23–30.