Papers › Generative Modeling of Full-Atom Protein Conformations using Latent Diffusion on Graph...

Generative Modeling of Full-Atom Protein Conformations using Latent Diffusion on Graph Embeddings

20 Jun 2025arXiv:2506.17064archive 2025-07-28

Aditya Sengar, Ali Hariri, Daniel Probst, Patrick Barth, Pierre Vandergheynst

Generating diverse, all-atom conformational ensembles of dynamic proteins such as G-protein-coupled receptors (GPCRs) is critical for understanding their function, yet most generative models simplify atomic detail or ignore conformational diversity altogether. We present latent diffusion for full protein generation (LD-FPG), a framework that constructs complete all-atom protein structures, including every side-chain heavy atom, directly from molecular dynamics (MD) trajectories. LD-FPG employs a Chebyshev graph neural network (ChebNet) to obtain low-dimensional latent embeddings of protein conformations, which are processed using three pooling strategies: blind, sequential and residue-based. A diffusion model trained on these latent representations generates new samples that a decoder, optionally regularized by dihedral-angle losses, maps back to Cartesian coordinates. Using D2R-MD, a 2-microsecond MD trajectory (12 000 frames) of the human dopamine D2 receptor in a membrane environment, the sequential and residue-based pooling strategy reproduces the reference ensemble with high structural fidelity (all-atom lDDT of approximately 0.7; C-alpha-lDDT of approximately 0.8) and recovers backbone and side-chain dihedral-angle distributions with a Jensen-Shannon divergence of less than 0.03 compared to the MD data. LD-FPG thereby offers a practical route to system-specific, all-atom ensemble generation for large proteins, providing a promising tool for structure-based therapeutic design on complex, dynamic targets. The D2R-MD dataset and our implementation are freely available to facilitate further research.

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load_config adityasengar/ld-fpg/residue/chebnet_res.py official repository ran · our draft was wrong no licence file found · pointer only · 8a430032884e2b85 · report
compute_centroid adityasengar/ld-fpg/residue/chebnet_res.py official repository ran · our draft was wrong fingerprinted no licence file found · pointer only · fc5abdbbf38af52d · report
get_global_indices adityasengar/ld-fpg/blind/chebnet_blind.py official repository ran · our draft was wrong no licence file found · pointer only · b004087130a22c7e · report
load_checkpoint adityasengar/ld-fpg/residue/chebnet_res.py official repository ran · our draft was wrong no licence file found · pointer only · 292eae31f01f62ee · report
parse_pdb adityasengar/ld-fpg/blind/chebnet_blind.py official repository ran · our draft was wrong no licence file found · pointer only · 0c4b4f93db8bf2de · report
renumber_atoms_and_residues adityasengar/ld-fpg/blind/chebnet_blind.py official repository ran · our draft was wrong no licence file found · pointer only · eb9a96ca416d95d9 · report
build_decoder_mlp adityasengar/LD-FPG/blind/chebnet_diff.py official repository unverified no licence file found · pointer only · 91fdcf166a6dc639 · report
get_global_indices adityasengar/LD-FPG/chebnet_multi.py official repository unverified no licence file found · pointer only · bef3518c709e63c0 · report
load_checkpoint adityasengar/LD-FPG/multi_receptor_ddp/chebnet_blind_cueq.py official repository unverified no licence file found · pointer only · 21f47ed10353c713 · report
load_heavy_atom_coords_from_json adityasengar/LD-FPG/multi_receptor_ddp/chebnet_blind_cueq.py official repository unverified no licence file found · pointer only · b0916fcbacde20d8 · report
parse_pdb adityasengar/LD-FPG/chebnet_multi.py official repository unverified no licence file found · pointer only · 54c81b3f5cdb84a1 · report
parse_pdb adityasengar/LD-FPG/conditional_generation/chebnet_conditional_setup.py official repository unverified no licence file found · pointer only · 48db614e67bcffab · report
renumber_atoms_and_residues adityasengar/LD-FPG/chebnet_multi.py official repository unverified no licence file found · pointer only · 45eb58749dc3b0ee · report
renumber_atoms_and_residues adityasengar/LD-FPG/conditional_generation/chebnet_conditional_setup.py official repository unverified no licence file found · pointer only · df015852241191a2 · report

Tasks

Graph Neural Network

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Methods

DiffusionGraph Neural Network

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