3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery | Paper Citation Record

Observation cb4905a3-57a0-4074-97b9-d8ef266579a2 · outbound

This paper cites write newline.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery write newline

Reference 1

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Observation 175415be-1ed1-4328-80c9-f563359d6ff1 · outbound

This paper cites Accurate structure prediction of biomolecular interactions with alphafold 3.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Accurate structure prediction of biomolecular interactions with alphafold 3

Reference 2

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Observation edb8bbf9-5717-4625-aaf6-edf06b42b52d · outbound

This paper cites Guiding deep molecular optimization with genetic exploration.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Guiding deep molecular optimization with genetic exploration

Reference 3

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Observation 7914e2fb-fee1-4203-83bc-24e01fb905cc · outbound

This paper cites Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction

Reference 4

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Observation 291a1c23-0e6a-48cb-bfaa-f6de406f7e3c · outbound

This paper cites Fast, accurate, and reliable molecular docking with quickvina 2.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Fast, accurate, and reliable molecular docking with quickvina 2

Reference 5

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Observation 84a79ba4-4014-4fc7-b53d-230ed3dd0ee0 · outbound

This paper cites Randomized smiles strings improve the quality of molecular generative models.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Randomized smiles strings improve the quality of molecular generative models

Reference 6

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Observation de7a1e2e-1604-4a21-a09c-a73e28c13d85 · outbound

This paper cites Geometric deep learning on molecular representations.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Geometric deep learning on molecular representations

Reference 7

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Observation f99b2367-86dc-4440-83bb-cd7a9ef8b88d · outbound

This paper cites Accurate prediction of protein structures and interactions using a three-track neural network.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Accurate prediction of protein structures and interactions using a three-track neural network

Reference 8

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Observation 16f5c86c-0247-4e54-aab4-2923c667e32b · outbound

This paper cites Molgpt: molecular generation using a transformer-decoder model.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Molgpt: molecular generation using a transformer-decoder model

Reference 9

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Observation c5cfb648-aa2f-4cdf-a9d9-14e668b21a26 · outbound

This paper cites Can ai reproduce observed chemical diversity? bioRxiv, pp.\ 292177, 2018.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Can ai reproduce observed chemical diversity? bioRxiv, pp.\ 292177, 2018

Reference 10

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Observation 3a98d0e0-686d-48d9-bbc0-5a1f2ce727a2 · outbound

This paper cites Quantifying the chemical beauty of drugs.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Quantifying the chemical beauty of drugs

Reference 11

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Observation 0195aa7c-c8ea-4b7e-bb52-a4f0b401f557 · outbound

This paper cites The role of ai in drug discovery: challenges, opportunities, and strategies.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery The role of ai in drug discovery: challenges, opportunities, and strategies

Reference 12

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Observation 3c078ba4-f7c4-4f1c-8e4e-c1b301d9c225 · outbound

This paper cites Language models are few-shot learners.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Language models are few-shot learners

Reference 13

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Observation da742913-4ced-458c-b99e-165ea6c30eb0 · outbound

This paper cites Posebusters: Ai-based docking methods fail to generate physically valid poses or generalise to novel sequences.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Posebusters: Ai-based docking methods fail to generate physically valid poses or generalise to novel sequences

Reference 14

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Observation c87fed1c-8b61-4ab7-ad91-095ec8bffd93 · outbound

This paper cites Structure-aware protein self-supervised learning.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Structure-aware protein self-supervised learning

Reference 15

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Observation f1900091-ff2a-4b90-bc04-ac9866934ade · outbound

This paper cites Diffdock: Diffusion steps, twists, and turns for molecular docking.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Diffdock: Diffusion steps, twists, and turns for molecular docking

Reference 16

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Observation cd4b59d1-9e2c-4c39-8b30-7b5a6c3a7471 · outbound

This paper cites Deep confident steps to new pockets: Strategies for docking generalization.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Deep confident steps to new pockets: Strategies for docking generalization

Reference 17

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Observation 443602cc-6519-47ec-9936-0ff20e35dd0b · outbound

This paper cites BERT : Pre-training of deep bidirectional transformers for language understanding.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery BERT : Pre-training of deep bidirectional transformers for language understanding

Reference 18

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Observation d4e31fac-3454-4608-8304-d998ac27c3dc · outbound

This paper cites Chai-1: Decoding the molecular interactions of life.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Chai-1: Decoding the molecular interactions of life

Reference 19

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Observation 114b6848-860b-4014-9f3f-96ab0b27213d · outbound

This paper cites MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design

Reference 20

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Observation 5d0b6881-c3a5-46de-83e9-7405230c43c9 · outbound

This paper cites Machine learning-aided generative molecular design.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Machine learning-aided generative molecular design

Reference 21

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Observation 8de2f3fa-9b0c-465c-9d21-f1a5e693dbfc · outbound

This paper cites Autodock vina 1.2.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Autodock vina 1.2

Reference 22

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Observation 86b82672-5fb3-4160-bd6a-9125f66bd37f · outbound

This paper cites Limo: Latent inceptionism for targeted molecule generation.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Limo: Latent inceptionism for targeted molecule generation

Reference 23

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Observation 3d09dff8-68b6-4d4d-9cf2-16386eb4126b · outbound

This paper cites Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions

Reference 24

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Observation e45490cd-a86b-41c7-9911-c6dbdc365b16 · outbound

This paper cites Geometry-enhanced molecular representation learning for property prediction.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Geometry-enhanced molecular representation learning for property prediction

Reference 25

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Observation 5134fab5-8ca1-4602-85f3-e040d6bb4a16 · outbound

This paper cites Protein-ligand binding representation learning from fine-grained interactions.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Protein-ligand binding representation learning from fine-grained interactions

Reference 26

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Observation c9a6661d-0ef0-42b6-a6b0-d1bdbe464486 · outbound

This paper cites Generation of 3d molecules in pockets via a language model.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Generation of 3d molecules in pockets via a language model

Reference 27

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Observation 167a9a6d-3db4-4bd0-82b4-31a7a5f1f8e1 · outbound

This paper cites Language models can generate molecules, materials, and protein binding sites directly in three dimensions as XYZ, CIF, and PDB files.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Language models can generate molecules, materials, and protein binding sites directly in three dimensions as XYZ, CIF, and PDB files

Reference 28

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Observation 6f22fe68-be67-4218-b169-34709dff0ddc · outbound

This paper cites Three-dimensional convolutional neural networks and a cross-docked data set for structure-based drug design.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Three-dimensional convolutional neural networks and a cross-docked data set for structure-based drug design

Reference 29

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Observation 809debfa-a843-472c-b64f-a553d2b03b77 · outbound

This paper cites Reinforced genetic algorithm for structure-based drug design.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Reinforced genetic algorithm for structure-based drug design

Reference 30

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Observation 3defdbf6-b430-439a-bad5-cf91c4e67438 · outbound

This paper cites Drugclip: Contrasive protein-molecule representation learning for virtual screening.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Drugclip: Contrasive protein-molecule representation learning for virtual screening

Reference 31

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Observation aaa7dcaa-b49a-4f28-b0cf-fb0ba077fe92 · outbound

This paper cites Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion

Reference 32

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Observation c1b66612-293f-4725-a3a0-c623f770b23b · outbound

This paper cites xVal: A Continuous Numerical Tokenization for Scientific Language Models.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery xVal: A Continuous Numerical Tokenization for Scientific Language Models

Reference 33

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Observation df18a194-d036-48bf-ab3b-a3710b7c5a16 · outbound

This paper cites 3d equivariant diffusion for target-aware molecule generation and affinity prediction.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery 3d equivariant diffusion for target-aware molecule generation and affinity prediction

Reference 34

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Observation 97e8ce77-4deb-492e-b50c-f47ffc221689 · outbound

This paper cites Decompdiff: diffusion models with decomposed priors for structure-based drug design.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Decompdiff: diffusion models with decomposed priors for structure-based drug design

Reference 35

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Observation 8fd3328e-c2fb-4094-ba7f-36942b62330d · outbound

This paper cites Benchmarking Generated Poses: How Rational is Structure-based Drug Design with Generative Models?.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Benchmarking Generated Poses: How Rational is Structure-based Drug Design with Generative Models?

Reference 36

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Observation ce79d82f-a64d-46c2-abb2-89b79b6272c5 · outbound

This paper cites De novo drug design using reinforcement learning with multiple gpt agents.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery De novo drug design using reinforcement learning with multiple gpt agents

Reference 37

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Observation 0dda3e0d-3089-4e27-ba80-19b0fc6892ce · outbound

This paper cites Hamiltonian diversity: effectively measuring molecular diversity by shortest hamiltonian circuits.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Hamiltonian diversity: effectively measuring molecular diversity by shortest hamiltonian circuits

Reference 38

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Observation 33866d9d-7d99-455e-a563-02d86b0f8e2d · outbound

This paper cites Chemformer: a pre-trained transformer for computational chemistry.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Chemformer: a pre-trained transformer for computational chemistry

Reference 39

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Observation 1e8e51af-ebed-4a28-b6db-d670c9c6e887 · outbound

This paper cites Structure-based drug design with geometric deep learning.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Structure-based drug design with geometric deep learning

Reference 40

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Observation a533c42a-2054-4750-b726-e7e76bf8ff21 · outbound

This paper cites Structure-based drug design with geometric deep learning.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Structure-based drug design with geometric deep learning

Reference 41

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Observation 8cde88cd-2238-4928-ab7c-30a095cafe38 · outbound

This paper cites Interactiongraphnet: A novel and efficient deep graph representation learning framework for accurate protein--ligand interaction predictions.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Interactiongraphnet: A novel and efficient deep graph representation learning framework for accurate protein--ligand interaction predictions

Reference 42

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Observation 2a893688-d5a5-470e-a489-63610d6bfc8f · outbound

This paper cites Jaakkola.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Jaakkola

Reference 43

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Observation afca2a63-f09d-4378-b6fb-86783ebcf206 · outbound

This paper cites Drugpose: benchmarking 3d generative methods for early stage drug discovery.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Drugpose: benchmarking 3d generative methods for early stage drug discovery

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:11.065188Z

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Observation 2363a87c-da66-4015-9263-667b839ba20b · outbound

This paper cites Highly accurate protein structure prediction with alphafold.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Highly accurate protein structure prediction with alphafold

Reference 45

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Observation 9796e93c-da49-4847-87e6-33ed677c9f1c · outbound

This paper cites On large-batch training for deep learning: Generalization gap and sharp minima.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery On large-batch training for deep learning: Generalization gap and sharp minima

Reference 46

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This paper cites Lessons learned in empirical scoring with smina from the csar 2011 benchmarking exercise.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Lessons learned in empirical scoring with smina from the csar 2011 benchmarking exercise

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:11.041335Z

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Observation 80a50417-4fce-486f-9303-3b0ea3364f69 · outbound

This paper cites Drug discovery with dynamic goal-aware fragments.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Drug discovery with dynamic goal-aware fragments

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:11.029473Z

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Observation f3ee613f-7cfd-4405-89dc-2818fe8e34b8 · outbound

This paper cites Evolutionary-scale prediction of atomic-level protein structure with a language model.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Evolutionary-scale prediction of atomic-level protein structure with a language model

Reference 49

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Observation 5871955d-c352-4df3-a203-3ec3ea0e425c · outbound

This paper cites Multi-objective reinforcement learning: A comprehensive overview.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Multi-objective reinforcement learning: A comprehensive overview

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:11.009705Z

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Observation 2116e0f1-1dc4-4e7c-be56-7e2ad40b0c51 · outbound

This paper cites Generating 3d molecules for target protein binding.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Generating 3d molecules for target protein binding

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.998144Z

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Observation c2f03439-4642-47b2-a3e4-2c92c6cd4747 · outbound

This paper cites Forging the basis for developing protein--ligand interaction scoring functions.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Forging the basis for developing protein--ligand interaction scoring functions

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.985874Z

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Observation 361f66e3-370a-476d-b533-8c41f2b90f5d · outbound

This paper cites Zero-shot 3d drug design by sketching and generating.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Zero-shot 3d drug design by sketching and generating

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.973857Z

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Observation 82c39348-c42c-4a7f-8cf1-910c3e19d8f8 · outbound

This paper cites Decoupled weight decay regularization.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Decoupled weight decay regularization

Reference 54

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Observation fdfef723-b094-407e-a6b9-e8bc5a24395d · outbound

This paper cites Tankbind: Trigonometry-aware neural networks for drug-protein binding structure prediction.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Tankbind: Trigonometry-aware neural networks for drug-protein binding structure prediction

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.953705Z

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Observation 6c3db5b4-55b4-445c-9344-397370be813a · outbound

This paper cites A 3d generative model for structure-based drug design.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery A 3d generative model for structure-based drug design

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.940536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9c57cf47-f145-4284-874a-fa6356791452 · outbound

This paper cites Artificial intelligence in drug discovery and development.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Artificial intelligence in drug discovery and development

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.928459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3007bfd4-5740-42d0-b114-d49ef95813bd · outbound

This paper cites A geometric deep learning approach to predict binding conformations of bioactive molecules.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery A geometric deep learning approach to predict binding conformations of bioactive molecules

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.916486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6a5def1d-2141-46cb-bfea-6c068a843d1e · outbound

This paper cites Deep learning for protein-ligand docking: Are we there yet? arXiv preprint arXiv:2405.14108, 2024.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Deep learning for protein-ligand docking: Are we there yet? arXiv preprint arXiv:2405.14108, 2024

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-08-08T20:18:10.389782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 66863145-1fb1-4bd3-b8ed-6b7302c1e708 · outbound

This paper cites Autodock4 and autodocktools4: Automated docking with selective receptor flexibility.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Autodock4 and autodocktools4: Automated docking with selective receptor flexibility

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.904723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 76b636e5-f07a-4e9d-b209-4da6de6850b7 · outbound

This paper cites Molecular de-novo design through deep reinforcement learning.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Molecular de-novo design through deep reinforcement learning

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-08T20:18:09.930653Z

Source-reported events for the cited work

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Observation e475b478-ab33-4880-8879-9bffdcfb3ca1 · outbound

This paper cites Caught between a rock and a hard place: current challenges in structure-based drug design.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Caught between a rock and a hard place: current challenges in structure-based drug design

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.884189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 509945b7-e991-4fc6-ba56-c718568433ce · outbound

This paper cites Fabind: Fast and accurate protein-ligand binding.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Fabind: Fast and accurate protein-ligand binding

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.872277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2689b3dd-3284-482a-8f69-65a729c78977 · outbound

This paper cites Pocket2mol: Efficient molecular sampling based on 3d protein pockets.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Pocket2mol: Efficient molecular sampling based on 3d protein pockets

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.859832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6e74f67a-9406-405b-a7ab-e5b8baa79e57 · outbound

This paper cites Dive into deep learning: Tools for engagement.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Dive into deep learning: Tools for engagement

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.847934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 87829da1-a78d-4ce6-9617-9e0d1451b83c · outbound

This paper cites Vinardo: A scoring function based on autodock vina improves scoring, docking, and virtual screening.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Vinardo: A scoring function based on autodock vina improves scoring, docking, and virtual screening

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.836064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 679c2ab1-d598-46cb-b2c0-0a42de13ba4d · outbound

This paper cites Language models are unsupervised multitask learners.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Language models are unsupervised multitask learners

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-08T20:18:09.950978Z

Source-reported events for the cited work

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Observation 70c3b1be-46ef-4ef3-a3c7-37c772cb17c1 · outbound

This paper cites Generating 3d molecules conditional on receptor binding sites with deep generative models.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Generating 3d molecules conditional on receptor binding sites with deep generative models

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-08T20:18:09.954278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 346c372c-bac4-46a2-83e9-800f59cf6b2e · outbound

This paper cites Structure-based Drug Design with Equivariant Diffusion Models.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Structure-based Drug Design with Equivariant Diffusion Models

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-08T20:18:09.958049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 083e76c6-cee7-43ef-a572-734c0663562f · outbound

This paper cites Molecular transformer: a model for uncertainty-calibrated chemical reaction prediction.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Molecular transformer: a model for uncertainty-calibrated chemical reaction prediction

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.807910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8fb21802-63b4-4198-be83-2c971f26bf4b · outbound

This paper cites Generating focused molecule libraries for drug discovery with recurrent neural networks.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Generating focused molecule libraries for drug discovery with recurrent neural networks

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.795986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8bf760f4-8384-4a1e-ab5f-1f729ee2e336 · outbound

This paper cites Reinforcement learning for molecular design guided by quantum mechanics.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Reinforcement learning for molecular design guided by quantum mechanics

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.784295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 264d2119-d088-46b9-bbf5-42403ee00777 · outbound

This paper cites Autogrow4: an open-source genetic algorithm for de novo drug design and lead optimization.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Autogrow4: an open-source genetic algorithm for de novo drug design and lead optimization

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.772677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bedc8dbb-5bbe-445c-8453-608ddb6f3e95 · outbound

This paper cites Equibind: Geometric deep learning for drug binding structure prediction.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Equibind: Geometric deep learning for drug binding structure prediction

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.761845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a4bec532-85d6-4ccf-9691-4faa636b3420 · outbound

This paper cites Comparative assessment of scoring functions: the casf-2016 update.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Comparative assessment of scoring functions: the casf-2016 update

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.751038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d323661d-bb53-43a3-9a4c-496702d57ffa · outbound

This paper cites Utilizing Reinforcement Learning for de novo Drug Design.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Utilizing Reinforcement Learning for de novo Drug Design

Reference 76

Resolution: verified exact; local_arxiv, observed 2026-08-08T20:18:10.174588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0575cba2-2027-4bbd-ab31-f790cb65da9f · outbound

This paper cites Autodock vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Autodock vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.630691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation aeea9409-18e7-4af4-8dbe-bae6659c9b66 · outbound

This paper cites Structure-based drug design: aiming for a perfect fit.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Structure-based drug design: aiming for a perfect fit

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.620494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8282e32b-1ac5-4642-98ba-0bd70f49ce4f · outbound

This paper cites Structure-based, deep-learning models for protein-ligand binding affinity prediction.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Structure-based, deep-learning models for protein-ligand binding affinity prediction

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.608387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a687610c-4b0e-4367-a834-54241b5d3cc6 · outbound

This paper cites Token-Mol 1.0: Tokenized drug design with large language model.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Token-Mol 1.0: Tokenized drug design with large language model

Reference 80

Resolution: verified exact; local_arxiv, observed 2026-08-08T20:18:10.159700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c6159adf-f65a-4b11-a9af-1534ddfc9508 · outbound

This paper cites Property-aware relation networks for few-shot molecular property prediction.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Property-aware relation networks for few-shot molecular property prediction

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.597186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c2f57260-5437-4b27-9d2c-a8c8a31433bc · outbound

This paper cites A compact review of molecular property prediction with graph neural networks.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery A compact review of molecular property prediction with graph neural networks

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.585914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ffb26cbd-246e-41ca-8421-eab55dda90d3 · outbound

This paper cites A systematic survey of chemical pre-trained models.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery A systematic survey of chemical pre-trained models

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.573497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4c70bd3f-93b0-4375-a015-94504c190966 · outbound

This paper cites Protein--ligand docking in the machine-learning era.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Protein--ligand docking in the machine-learning era

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.562494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 04b8d631-320f-4842-af32-b6cbd7e112d6 · outbound

This paper cites Deep molecular representation learning via fusing physical and chemical information.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Deep molecular representation learning via fusing physical and chemical information

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.552259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 946711d7-4f20-48e8-8f32-50cb6888ed0a · outbound

This paper cites Hit and lead discovery with explorative rl and fragment-based molecule generation.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Hit and lead discovery with explorative rl and fragment-based molecule generation

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.542025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation abbb046f-71c2-487e-92ed-cc2607b874df · outbound

This paper cites Graph convolutional policy network for goal-directed molecular graph generation.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Graph convolutional policy network for goal-directed molecular graph generation

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.531423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f8a7be81-e268-4b2f-9f01-068283e9c104 · outbound

This paper cites E3bind: An end-to-end equivariant network for protein-ligand docking.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery E3bind: An end-to-end equivariant network for protein-ligand docking

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.519706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 38aed36c-c43d-47be-b181-4362b8ea15c9 · outbound

This paper cites Motif-based graph self-supervised learning for molecular property prediction.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Motif-based graph self-supervised learning for molecular property prediction

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.508510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3fbfe4f9-2f6c-4fea-a03e-c731182e6481 · outbound

This paper cites Geometric Deep Learning for Structure-Based Drug Design: A Survey.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Geometric Deep Learning for Structure-Based Drug Design: A Survey

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-08T20:18:10.033108Z

Source-reported events for the cited work

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Observation a153ff62-f977-41ae-8177-a77c7469c97f · outbound

This paper cites A brief review of protein--ligand interaction prediction.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery A brief review of protein--ligand interaction prediction

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.497904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2743eae0-ad14-4ccf-9056-e858260bc2a7 · outbound

This paper cites Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate?.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate?

Reference 92

Resolution: verified exact; local_arxiv, observed 2026-08-08T20:18:10.134374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5312db31-4ac8-4ba0-ace7-8ff9963bfc64 · outbound

This paper cites Uni-mol: A universal 3d molecular representation learning framework.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Uni-mol: A universal 3d molecular representation learning framework

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.486834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bf3fe4c2-9dd4-4934-bc0c-de25d23ec97e · outbound

This paper cites Do Deep Learning Methods Really Perform Better in Molecular Conformation Generation?.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Do Deep Learning Methods Really Perform Better in Molecular Conformation Generation?

Reference 95

Resolution: verified exact; local_arxiv, observed 2026-08-08T20:18:10.107568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ba3de2d3-1021-47b8-bbe8-9ea6c81fadb7 · outbound

This paper cites Unified 2d and 3d pre-training of molecular representations.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Unified 2d and 3d pre-training of molecular representations

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T20:18:10.475868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation addbffc9-7b7e-440d-9048-d8ba6c465dbd · outbound

This paper cites @esa (Ref.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery @esa (Ref

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-08T20:18:10.059028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be63a7fa-2cf3-4ab9-891c-85ba162f80ec · outbound

This paper cites an unresolved cited work.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery Unresolved cited work

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-08T20:18:10.063098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bb5577f-c904-41b3-9254-4f8905188f85 · outbound

This paper cites BindGPT: A Scalable Framework for 3D Molecular Design via Language Modeling and Reinforcement Learning.

3DMolFormer: A Dual-channel Framework for Structure-based Drug Discovery BindGPT: A Scalable Framework for 3D Molecular Design via Language Modeling and Reinforcement Learning

Reference 99

Resolution: malformed identifier; no resolver link, observed 2026-08-08T20:18:10.067022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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