Table 3 Results from ten-temperature melting analysis of \(\hbox {hPTH}_{1}\hbox {R}\) variants.

From: IMPROvER: the Integral Membrane Protein Stability Selector

Module

Variant

\(T_m\) (\(^{\circ }\)C)\(^{\mathrm{a}}\)

\(T_m\) error (\(\pm ^{\circ }\)C)\(^{\mathrm{b}}\)

\(\Delta T_m\) (\(^{\circ }\)C)

\(\Delta T_m\) error (\(\pm ^{\circ }\)C)\(^{\mathrm{c}}\)

Repeats (n)

Status

n/a

Wild-type

38.7

0.8

0

1.1

3

n/a

Deep-sequence

G188Y

41.2

0.7

2.5

0.7

3

Stabilising

Deep-sequence

M189L

39.1

0.9

0.4

0.9

3

Neutral

Deep-sequence

G188K

40.3

1.2

1.6

1.2

3

Stabilising

Deep-sequence

A274D

39.1

0.1

0.4

0.1

3

Neutral

Model-based

S198M

42.1

0.8

3.4

1.1

3

Stabilising

Model-based

F291T

40.9

0.9

2.2

1.2

3

Stabilising

Model-based

D251R

41.7

1.5

3.0

1.6

3

Stabilising

Model-based

E260R

39.7

1.5

1.0

1.7

3

Neutral

Data-driven

Q401A

40.7

0.2

2.0

0.2

3

Stabilising

Data-driven

F288A

41.5

0.7

2.8

0.7

3

Stabilising

Data-driven

E391A

39.4

0.2

0.7

0.2

3

Neutral

Data-driven

G323A

41.5

0.6

2.8

0.6

2

Stabilising

  1. \(^{\mathrm{a}}\)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.
  2. \(^{\mathrm{b}}\)For n > 1: standard error of the mean (SEM) shown.
  3. \(^{\mathrm{c}}\)For n > 1: error calculated and propagated as detailed in “Methods and materials” section.