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To illuminate the complexities of this relationship, high\u2010throughput (HTP) assays are increasingly used to assess site\u2010saturating mutagenesis libraries. A common downstream analysis is to average the set of 20 outcomes at each amino acid position for comparison with structural and evolutionary features. Average values clearly identify positions that tolerate most substitutions (neutral positions) and positions where most substitutions abolish activity (toggle positions). However, average values conceal the existence of rheostat positions, where different amino acid substitutions sample a wide range of outcomes. To quantitatively identify rheostat positions, we previously developed a histogram\u2010based analysis that we here expand by: (i) incorporating new position classes observed in experimental studies of rheostat positions; (ii) formalizing a hierarchy of class assignments; (iii) refining error\u2010based identification of neutral positions; and (iv) statistically assessing the robustness of class assignments to changes in experimental and computational parameters. RheoScale 2.0 is implemented in Excel and newly implemented in Python for facile integration with existing HTP pipelines; all parameters are customizable. Example analyses are shown for three HTP datasets of the SARS\u2010CoV\u20102 papain\u2010like protease. Results illustrate two aspects that influence interpretation of HTP data: First, position assignments (and substitution outcomes) depend highly on the measured feature. Second, many protein positions play multiple roles in the sequence\u2010structure\u2013function relationship. The recognition of varied position roles will advance understanding of pathogen evolution, protein engineering, and variant interpretation for personalized medicine.<\/jats:p>","DOI":"10.1002\/pro.70804","type":"journal-article","created":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T13:23:11Z","timestamp":1789996991000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["<scp>RheoScale<\/scp>\n                    2.0: Revealing the hidden roles of protein positions via substitution patterns"],"prefix":"10.1002","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-9162-5172","authenticated-orcid":false,"given":"David H.","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Biochemistry and Molecular Biology University of Kansas Medical Center  Kansas City Kansas 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Kansas Medical Center  Kansas City Kansas USA"},{"name":"Department of Electrical Engineering and Computer Science University of Kansas\u2010Lawrence  Lawrence Kansas USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5925-9741","authenticated-orcid":false,"given":"Liskin","family":"Swint\u2010Kruse","sequence":"additional","affiliation":[{"name":"Department of Biochemistry and Molecular Biology University of Kansas Medical Center  Kansas City Kansas 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