Table 1.

Results from ten-temperature melting analysis of ClPPase variants.

Module	Variant	$T_m$ (${}^{\circ }$C)${}^{\mathrm{a}}$	$T_m$ error (${\pm }^{\circ }$C)${}^{\mathrm{b}}$	$\mathrm{\Delta }{T}_m$ (${}^{\circ }$C)	$\mathrm{\Delta }{T}_m$ error (${\pm }^{\circ }$C)${}^{\mathrm{c}}$	Repeats (n)	Status
n/a	Wild-type	49.3	0.9	0.0	1.2	8	n/a
Deep-sequence	S113A	53.6	2.8	4.3	3.0	3	Stabilising
Deep-sequence	S273V	48.8	–	− 0.5	–	1	Neutral
Deep-sequence	G130S	57.4	–	8.1	–	1	Stabilising
Deep-sequence	S371K	50.6	–	1.3	–	1	Neutral
Deep-sequence	F20Y	58.4	1.2	9.1	1.5	3	Stabilising
Model-based	V81W	50.5	–	1.2	–	1	Stabilising
Model-based	R463W	51.1	1.3	1.8	1.6	3	Neutral
Model-based	L142P	44.0	0.5	− 5.3	1.0	3	Destabilising
Model-based	L151I	49.7	1.2	0.4	1.5	2	Neutral
Model-based	V693Y	51.4	–	2.1	–	1	Stabilising
Model-based	R109W	52.7	1.7	3.4	1.9	3	Stabilising
Model-based	R290F	50.5	–	1.2	–	3	Stabilising
Model-based	D468F	52.0	0.6	2.7	1.1	1	Stabilising
Model-based	I501L	50.6	–	1.3	–	1	Neutral
Model-based	G179A	52.9	1.5	3.6	1.7	3	Stabilising
Data-driven	A492L	47.7	–	− 1.6	–	1	Destabilising
Data-driven	A14L	48.4	–	− 0.9	–	1	Neutral
Data-driven	G31A	51.0	–	1.7	–	1	Stabilising
Data-driven	A319L	51.5	–	2.2	–	1	Stabilising
Data-driven	G130A	62.3	1.1	13.0	1.4	3	Stabilising
Data-driven	A114L	50.2	–	0.9	–	1	Neutral
Combined	G130A+F20Y	59.6	1.8	10.3	2.0	3	Stabilising

${}^{\mathrm{a}}$Average $T_m$ was calculated from individual $T_m$ estimated for each individual repeat by fitting with a four-parameter dose-response curve (variable slope) by non-linear least-squares fitting in the python package scipy.stats.

${}^{\mathrm{b}}$For n > 1: standard error of the mean (SEM) shown.

${}^{\mathrm{c}}$For n > 1: error calculated and propagated as detailed in “Methods and materials” section.