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Drug Design

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/exalearn/covid-drug-design

공식 코드

Evening the Score: Targeting SARS-CoV-2 Protease Inhibition in Graph Generative Models for Therapeutic Candidates

https://github.com/fairydance/deeprli

공식 코드

DeepRLI: A Multi-objective Framework for Universal Protein--Ligand Interaction Prediction

https://github.com/foralan/equiboost

공식 코드

EquiBoost: An Equivariant Boosting Approach to Molecular Conformation Generation

https://github.com/futianfan/reinforced-genetic-algorithm

공식 코드

Reinforced Genetic Algorithm for Structure-based Drug Design

https://github.com/garywei944/chemflow

공식 코드

Navigating Chemical Space with Latent Flows

https://github.com/gcorso/diffdock

공식 코드

DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

https://github.com/genentech/voxbind

공식 코드

Structure-based drug design by denoising voxel grids

https://github.com/gersteinlab/genai4drug

공식 코드

A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generation

https://github.com/gitter-lab/Assay2Mol

공식 코드

Assay2Mol: large language model-based drug design using BioAssay context

https://github.com/gnina/gnina

공식 코드

Protein-Ligand Scoring with Convolutional Neural Networks

https://github.com/goldzzmj/M2oE

공식 코드

M2oE: Multimodal Collaborative Expert Peptide Model

https://github.com/grimmlab/graphxform

공식 코드

GraphXForm: Graph transformer for computer-aided molecular design

https://github.com/guanjq/targetdiff

공식 코드

3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction

https://github.com/guanlueli/AMDiff

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Molecule Generation for Target Protein Binding with Hierarchical Consistency Diffusion Model

https://github.com/haddocking/deeprank-gnn-esm

공식 코드

Ranking protein-protein models with large language models and graph neural networks

https://github.com/hampusgs/smiles-rnn-rl

공식 코드

Utilizing Reinforcement Learning for de novo Drug Design

https://github.com/hankerwu/tamgent

공식 코드

Tailoring Molecules for Protein Pockets: a Transformer-based Generative Solution for Structured-based Drug Design

https://github.com/hanrthu/copra

공식 코드

CoPRA: Bridging Cross-domain Pretrained Sequence Models with Complex Structures for Protein-RNA Binding Affinity Prediction

https://github.com/hoonose/sever

공식 코드

Sever: A Robust Meta-Algorithm for Stochastic Optimization

https://github.com/hxyfighter/3dmolformer

공식 코드

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

https://github.com/hxyfighter/llmsunderstandmol

공식 코드

Empirical Evidence for the Fragment level Understanding on Drug Molecular Structure of LLMs

https://github.com/hxyfighter/molrl-mgpt

공식 코드

De novo Drug Design using Reinforcement Learning with Multiple GPT Agents

https://github.com/iambic-therapeutics/np-bench

공식 코드

NeuralPLexer3: Accurate Biomolecular Complex Structure Prediction with Flow Models

https://github.com/idrori/cu-tsp

공식 코드

Accurate Protein Structure Prediction by Embeddings and Deep Learning Representations

https://github.com/idruglab/hignn

공식 코드

HiGNN: Hierarchical Informative Graph Neural Networks for Molecular Property Prediction Equipped with Feature-Wise Attention

https://github.com/isayev/ReLeaSE

공식 코드

Deep Reinforcement Learning for De-Novo Drug Design

https://github.com/ishirraov/novomol

공식 코드

NovoMol: Recurrent Neural Network for Orally Bioavailable Drug Design and Validation on PDGFRα Receptor

https://github.com/jiaqinglv2000/diff4vs

공식 코드

Diff4VS: HIV-inhibiting Molecules Generation with Classifier Guidance Diffusion for Virtual Screening

https://github.com/jiaxianyan/DeltaDock

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DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking

https://github.com/jostorge/diffusion-hopping

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DiffHopp: A Graph Diffusion Model for Novel Drug Design via Scaffold Hopping

https://github.com/junxia97/awesome-pretrain-on-molecules

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A Systematic Survey of Chemical Pre-trained Models

https://github.com/junxia97/mole-bert

공식 코드

A Systematic Survey of Chemical Pre-trained Models

https://github.com/karma211225/karmaloop

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Highly accurate and efficient deep learning paradigm for full-atom protein loop modeling with KarmaLoop

https://github.com/keiradams/squid

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Equivariant Shape-Conditioned Generation of 3D Molecules for Ligand-Based Drug Design

https://github.com/kevinid/molecule_generator

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Multi-Objective De Novo Drug Design with Conditional Graph Generative Model

https://github.com/kexinhuang12345/CASTER

공식 코드

CASTER: Predicting Drug Interactions with Chemical Substructure Representation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.