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Title: GitHub - TCoulth/dynamicMPNN: LigandMPNN but with dynamic constraints. This allows the biases applied during inference to adjust to a desired goal during the generation process. Current implementations are for pI targeting and surface patch generation · GitHub

Open Graph Title: GitHub - TCoulth/dynamicMPNN: LigandMPNN but with dynamic constraints. This allows the biases applied during inference to adjust to a desired goal during the generation process. Current implementations are for pI targeting and surface patch generation

X Title: GitHub - TCoulth/dynamicMPNN: LigandMPNN but with dynamic constraints. This allows the biases applied during inference to adjust to a desired goal during the generation process. Current implementations are for pI targeting and surface patch generation

Description: LigandMPNN but with dynamic constraints. This allows the biases applied during inference to adjust to a desired goal during the generation process. Current implementations are for pI targeting and surface patch generation - TCoulth/dynamicMPNN

Open Graph Description: LigandMPNN but with dynamic constraints. This allows the biases applied during inference to adjust to a desired goal during the generation process. Current implementations are for pI targeting and ...

X Description: LigandMPNN but with dynamic constraints. This allows the biases applied during inference to adjust to a desired goal during the generation process. Current implementations are for pI targeting and ...

Opengraph URL: https://github.com/TCoulth/dynamicMPNN

X: @github

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Domain: github.com

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README.mdhttps://github.com/TCoulth/dynamicMPNN/blob/main/README.md
data_utils.pyhttps://github.com/TCoulth/dynamicMPNN/blob/main/data_utils.py
data_utils.pyhttps://github.com/TCoulth/dynamicMPNN/blob/main/data_utils.py
get_model_params.shhttps://github.com/TCoulth/dynamicMPNN/blob/main/get_model_params.sh
get_model_params.shhttps://github.com/TCoulth/dynamicMPNN/blob/main/get_model_params.sh
model_utils.pyhttps://github.com/TCoulth/dynamicMPNN/blob/main/model_utils.py
model_utils.pyhttps://github.com/TCoulth/dynamicMPNN/blob/main/model_utils.py
requirements.txthttps://github.com/TCoulth/dynamicMPNN/blob/main/requirements.txt
requirements.txthttps://github.com/TCoulth/dynamicMPNN/blob/main/requirements.txt
run.pyhttps://github.com/TCoulth/dynamicMPNN/blob/main/run.py
run.pyhttps://github.com/TCoulth/dynamicMPNN/blob/main/run.py
run_examples.shhttps://github.com/TCoulth/dynamicMPNN/blob/main/run_examples.sh
run_examples.shhttps://github.com/TCoulth/dynamicMPNN/blob/main/run_examples.sh
sc_examples.shhttps://github.com/TCoulth/dynamicMPNN/blob/main/sc_examples.sh
sc_examples.shhttps://github.com/TCoulth/dynamicMPNN/blob/main/sc_examples.sh
sc_utils.pyhttps://github.com/TCoulth/dynamicMPNN/blob/main/sc_utils.py
sc_utils.pyhttps://github.com/TCoulth/dynamicMPNN/blob/main/sc_utils.py
score.pyhttps://github.com/TCoulth/dynamicMPNN/blob/main/score.py
score.pyhttps://github.com/TCoulth/dynamicMPNN/blob/main/score.py
READMEhttps://github.com/TCoulth/dynamicMPNN
MIT licensehttps://github.com/TCoulth/dynamicMPNN
https://github.com/TCoulth/dynamicMPNN#dynamicmpnn
LigandMPNNhttps://www.biorxiv.org/content/10.1101/2023.12.22.573103v1
ProteinMPNNhttps://www.science.org/doi/10.1126/science.add2187
https://github.com/dauparas/LigandMPNNhttps://github.com/dauparas/LigandMPNN
herehttps://github.com/dauparas/LigandMPNN
Instructions for runninghttps://github.com/TCoulth/dynamicMPNN#how-to-use-dynamic-constraints
Target pIhttps://github.com/TCoulth/dynamicMPNN#target-pi
Benchmark resultshttps://github.com/TCoulth/dynamicMPNN#pi-results
Surface patcheshttps://github.com/TCoulth/dynamicMPNN#surface-patches
Benchmark resultshttps://github.com/TCoulth/dynamicMPNN#patches-results
Sequence motifshttps://github.com/TCoulth/dynamicMPNN#sequence-motifs
https://github.com/TCoulth/dynamicMPNN#how-to-use-dynamic-constraints
https://github.com/TCoulth/dynamicMPNN#targeting-pi
https://github.com/TCoulth/dynamicMPNN#surface-patches
https://github.com/TCoulth/dynamicMPNN#dynamic-constraint-sets
Target pIhttps://github.com/TCoulth/dynamicMPNN#target-pi
Surface charge patcheshttps://github.com/TCoulth/dynamicMPNN#surface-patches
Target sequence motifshttps://github.com/TCoulth/dynamicMPNN#sequence-motifs
https://github.com/TCoulth/dynamicMPNN#target-pi
https://github.com/TCoulth/dynamicMPNN#pi-benchmark-setup
https://github.com/TCoulth/dynamicMPNN#pi-results
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https://github.com/TCoulth/dynamicMPNN#surface-patches-1
https://github.com/TCoulth/dynamicMPNN#patches-benchmark-setup
PEP-patchhttps://github.com/liedllab/surface_analyses
https://github.com/TCoulth/dynamicMPNN#patches-results
https://github.com/TCoulth/dynamicMPNN#negative-patches
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https://github.com/TCoulth/dynamicMPNN#positive-patches
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https://github.com/TCoulth/dynamicMPNN#hydrophobic-patches
https://private-user-images.githubusercontent.com/21342963/581619221-eb070b47-5c3b-41e7-8d72-4d466955a5e3.PNG?jwt=eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.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.bdjOESN_yhw8Ri3zCD4V4141Zr2cdG1uidMJHJ6NZ2w
https://github.com/TCoulth/dynamicMPNN#selected-af2-patch-comparisons
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https://github.com/TCoulth/dynamicMPNN#sequence-motifs
https://github.com/TCoulth/dynamicMPNN#citing-this-work
https://github.com/TCoulth/dynamicMPNN#claude-code-disclosure
protein-structure https://github.com/topics/protein-structure
protein https://github.com/topics/protein
protein-design https://github.com/topics/protein-design
inverse-folding https://github.com/topics/inverse-folding
protein-engineering https://github.com/topics/protein-engineering
proteinmpnn https://github.com/topics/proteinmpnn
protein-electrostatics https://github.com/topics/protein-electrostatics
Readme https://github.com/TCoulth/dynamicMPNN#readme-ov-file
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