Human mutations often cause amino acid changes (variants) that can alter protein function or stability. Some variants fall at protein positions that experimentally exhibit "rheostatic" mutation outcomes (different amino acid substitutions lead to a range of functional outcomes). In ongoing studies of rheostat positions, we encountered the need to aggregate experimental results from multiple variants, to describe the overall roles of individual positions. Here, we present "RheoScale" which generates quantitative scores to discriminate rheostat positions from those with "toggle" (most substitutions abolish function) or "neutral" (most substitutions have wild-type function) outcomes. RheoScale scores facilitate correlations of experimental data (such as binding affinity or stability) with structural and bioinformatic analyses. The RheoScale calculator is encoded into a Microsoft Excel workbook and an R script. Example analyses are shown for three model protein systems, including one assessed via deep mutational scanning. The RheoScale calculator quickly and efficiently provided quantitative descriptions that were in good agreement with prior qualitative observations. As an example application, scores were compared to the example proteins' structures; strong rheostat positions tended to occur in dynamic locations. In the future, RheoScale scores can be easily integrated into computational studies to facilitate improved algorithms for predicting outcomes of human variants.

Understanding how each residue position contributes to protein function has been a long‐standing goal in protein science. Substitution studies have historically focused on conserved protein positions. However, substitutions of nonconserved positions can also modify function. Indeed, we recently identified nonconserved positions that have large substitution effects in human liver pyruvate kinase (hLPYK), including altered allosteric coupling. To facilitate a comparison of which characteristics determine when a nonconserved position does vs does not contribute to function, the goal of the current work was to identify neutral positions in hLPYK. However, existing hLPYK data showed that three features commonly associated with neutral positions—high sequence entropy, high surface exposure, and alanine scanning—lacked the sensitivity needed to guide experimental studies. We used multiple evolutionary patterns identified in a sequence alignment of the PYK family to identify which positions were least patterned, reasoning that these were most likely to be neutral. Nine positions were tested with a total of 117 amino acid substitutions. Although exploring all potential functions is not feasible for any protein, five parameters associated with substrate/effector affinities and allosteric coupling were measured for hLPYK variants. For each position, the aggregate functional outcomes of all variants were used to quantify a “neutrality” score. Three positions showed perfect neutral scores for all five parameters. Furthermore, the nine positions showed larger neutral scores than 17 positions located near allosteric binding sites. Thus, our strategy successfully enriched the dataset for positions with neutral and modest substitutions.

When amino acids vary during evolution, the outcome can be functionally neutral or biologically‐important. We previously found that substituting a subset of nonconserved positions, “rheostat” positions, can have surprising effects on protein function. Since changes at rheostat positions can facilitate functional evolution or cause disease, more examples are needed to understand their unique biophysical characteristics. Here, we explored whether “phylogenetic” patterns of change in multiple sequence alignments (such as positions with subfamily specific conservation) predict the locations of functional rheostat positions. To that end, we experimentally tested eight phylogenetic positions in human liver pyruvate kinase (hLPYK), using 10–15 substitutions per position and biochemical assays that yielded five functional parameters. Five positions were strongly rheostatic and three were non‐neutral. To test the corollary that positions with low phylogenetic scores were not rheostat positions, we combined these phylogenetic positions with previously‐identified hLPYK rheostat, “toggle” (most substitution abolished function), and “neutral” (all substitutions were like wild‐type) positions. Despite representing 428 variants, this set of 33 positions was poorly statistically powered. Thus, we turned to the in vivo phenotypic dataset for E. coli lactose repressor protein (LacI), which comprised 12–13 substitutions at 329 positions and could be used to identify rheostat, toggle, and neutral positions. Combined hLPYK and LacI results show that positions with strong phylogenetic patterns of change are more likely to exhibit rheostat substitution outcomes than neutral or toggle outcomes. Furthermore, phylogenetic patterns were more successful at identifying rheostat positions than were co‐evolutionary or eigenvector centrality measures of evolutionary change.

In the goal of interpreting human exomes, when predictive programs assign functional importance to some positions, they implicitly assume the existence of non-important positions -those that accommodate many side chain chemistries without altering function ("neutral"). However, very few (if any) experimental studies have demonstrated the existence of neutral positions. We sought experimental evidence for neutral positions using human liver pyruvate kinase (hLPYK) as a model system. To that end, we used multiple evolutionary criteria to identify 20 possibly neutral positions. Nine positions were further tested with a total of 117 amino acid substitutions. Although "all" potential hLPYK functions can never be explored, we measured effects on 5 parameters associated with substrate/ligand affinities and allosteric coupling. At each position, the aggregate outcomes of multiple variants were used to quantify "neutrality" scores. Three of the nine positions showed perfect neutral scores in all 5 parameters; a fourth position had high neutral scores. Although our strategy for predicting positions had low predictive power for the identification of neutral positions, all positions had neutral scores that were much higher than positions in functional sites. Given this evidence for the existence of neutral positions, similar studies should be carried out for other proteins to generate a database of well characterized neutral positions that can then be available to benchmark and validate predictions about amino acid substitutions.