This workflow uses RFdiffusion for generating protein backbones, which can be done in two main ways: conditioned on a target structure or by scaffolding a known binding motif. It can also be applied to design miniproteins. The sequence is then designed using either ProteinMPNN or its solubility-optimized variant, SolubleMPNN, which can also be used for round-based optimization. The final designs are validated and filtered using AlphaFold2 and other optional metrics, including those derived from molecular dynamics (MD) simulations.
id: shy-tiger-pine

IL-7Ra
None
--
True
9.8 kDa
84
id: scarlet-ant-granite

IL-7Ra
Medium
7.7e-8 M
True
9.8 kDa
85
id: lunar-jaguar-thorn

IL-7Ra
Medium
1.8e-7 M
True
7.3 kDa
65
id: dark-falcon-cedar

IL-7Ra
Medium
3.6e-7 M
True
7.9 kDa
68
id: quick-panther-snow

IL-7Ra
Strong
4.0e-8 M
True
7.2 kDa
65
id: jade-jaguar-plume

IL-7Ra
Weak
--
True
6.8 kDa
58
id: lunar-toad-cypress

IL-7Ra
Medium
1.2e-7 M
True
10.2 kDa
83
id: rough-cobra-thorn

IL-7Ra
Weak
--
True
10.0 kDa
88
id: wild-crane-rose

IL-7Ra
Weak
--
True
11.0 kDa
97
id: shy-orca-sand

IL-7Ra
Weak
--
True
10.0 kDa
91
id: azure-eagle-maple

IL-7Ra
Medium
1.4e-7 M
True
7.1 kDa
64
id: solid-raven-onyx

IL-7Ra
Weak
--
True
8.9 kDa
81
id: steady-swan-onyx

IL-7Ra
Medium
9.4e-8 M
True
10.9 kDa
97
id: gentle-deer-jade

IL-7Ra
Weak
--
True
7.3 kDa
65
id: crimson-hawk-moss

IL-7Ra
Weak
--
True
10.9 kDa
89
id: soft-zebra-jade

IL-7Ra
None
--
True
7.5 kDa
65
id: shy-raven-ember

IL-7Ra
Weak
--
True
6.9 kDa
62
id: calm-vole-fern

IL-7Ra
Medium
2.7e-7 M
True
7.5 kDa
67
id: scarlet-bear-lotus

IL-7Ra
Medium
6.4e-8 M
True
10.4 kDa
88
id: jade-bear-opal

IL-7Ra
Weak
--
True
7.5 kDa
65
id: mellow-ox-jade

IL-7Ra
None
--
True
8.4 kDa
71