Cover Image

Conditional Chemical Language Models are Versatile Tools in Drug Discovery

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhu, Lu, Noutahi, Emmanuel
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Biomolecules
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SAFE setup for generative molecular design
by: Mesbahi, Yassir El, et al.
Published: (2024)

A Foundation Chemical Language Model for Comprehensive Fragment-Based Drug Discovery
by: Ho, Alexander, et al.
Published: (2025)

InstructMol: Multi-Modal Integration for Building a Versatile and Reliable Molecular Assistant in Drug Discovery
by: Cao, He, et al.
Published: (2023)

Diffusion Language Models Are Versatile Protein Learners
by: Wang, Xinyou, et al.
Published: (2024)

Morphology-Aware Peptide Discovery via Masked Conditional Generative Modeling
by: Costa, Nuno, et al.
Published: (2025)

Large Language Model Agent for Modular Task Execution in Drug Discovery
by: Ock, Janghoon, et al.
Published: (2025)

Graph Neural Networks in Modern AI-aided Drug Discovery
by: Zhang, Odin, et al.
Published: (2025)

How Evaluation Choices Distort the Outcome of Generative Drug Discovery
by: Özçelik, Rıza, et al.
Published: (2024)

Rethinking Drug-Drug Interaction Modeling as Generalizable Relation Learning
by: Xu, Dong, et al.
Published: (2026)

DrugCLIP: Contrastive Drug-Disease Interaction For Drug Repurposing
by: Lu, Yingzhou, et al.
Published: (2024)

Graph-structured Small Molecule Drug Discovery Through Deep Learning: Progress, Challenges, and Opportunities
by: Li, Kun, et al.
Published: (2025)

Integrating Chemical Language and Molecular Graph in Multimodal Fused Deep Learning for Drug Property Prediction
by: Lu, Xiaohua, et al.
Published: (2023)

Bridging the Gap between Chemical Reaction Pretraining and Conditional Molecule Generation with a Unified Model
by: Qiang, Bo, et al.
Published: (2023)

DrugPlayGround: Benchmarking Large Language Models and Embeddings for Drug Discovery
by: Liu, Tianyu, et al.
Published: (2026)

Quantum-machine-assisted Drug Discovery
by: Zhou, Yidong, et al.
Published: (2024)

Function-Guided Conditional Generation Using Protein Language Models with Adapters
by: Yang, Jason, et al.
Published: (2024)

Quantum Long Short-Term Memory for Drug Discovery
by: Zhang, Liang, et al.
Published: (2024)

KITE-DDI: A Knowledge graph Integrated Transformer Model for accurately predicting Drug-Drug Interaction Events from Drug SMILES and Biomedical Knowledge Graph
by: Tamir, Azwad, et al.
Published: (2024)

Structure-based Drug Design with Equivariant Diffusion Models
by: Schneuing, Arne, et al.
Published: (2022)

A Generalist Cross-Domain Molecular Learning Framework for Structure-Based Drug Discovery
by: Zhu, Yiheng, et al.
Published: (2025)

Structure Language Models for Protein Conformation Generation
by: Lu, Jiarui, et al.
Published: (2024)

Steering Protein Language Models
by: Huang, Long-Kai, et al.
Published: (2025)

Quantum-inspired Reinforcement Learning for Synthesizable Drug Design
by: Wang, Dannong, et al.
Published: (2024)

Binding-Adaptive Diffusion Models for Structure-Based Drug Design
by: Huang, Zhilin, et al.
Published: (2024)

A Collaborative Framework Integrating Large Language Model and Chemical Fragment Space: Mutual Inspiration for Lead Design
by: Tuo, Hao, et al.
Published: (2025)

Structure-Informed Protein Language Model
by: Zhang, Zuobai, et al.
Published: (2024)

Site4Drug: Predicting Drug-Binding Target Sites with an AI Agent
by: Kim, Taehan, et al.
Published: (2026)

Contrastive Multi-Task Learning with Solvent-Aware Augmentation for Drug Discovery
by: Lan, Jing, et al.
Published: (2025)

Hybrid Quantum Generative Adversarial Networks for Molecular Simulation and Drug Discovery
by: Jain, Prateek, et al.
Published: (2022)

A Hitchhiker's Guide to Deep Chemical Language Processing for Bioactivity Prediction
by: Özçelik, Rıza, et al.
Published: (2024)

RNACG: A Universal RNA Sequence Conditional Generation model based on Flow-Matching
by: Gao, Letian, et al.
Published: (2024)

Reprogramming Pretrained Target-Specific Diffusion Models for Dual-Target Drug Design
by: Zhou, Xiangxin, et al.
Published: (2024)

DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design
by: Guan, Jiaqi, et al.
Published: (2024)

Assessing Reusability of Deep Learning-Based Monotherapy Drug Response Prediction Models Trained with Omics Data
by: Overbeek, Jamie C., et al.
Published: (2024)

Thin Bridges for Drug Text Alignment: Lightweight Contrastive Learning for Target Specific Drug Retrieval
by: Tupakula, Mallikarjuna
Published: (2025)

Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
by: Wu, Luhuan, et al.
Published: (2023)

A Geometric Graph-Based Deep Learning Model for Drug-Target Affinity Prediction
by: Rana, Md Masud, et al.
Published: (2025)

MFBind: a Multi-Fidelity Approach for Evaluating Drug Compounds in Practical Generative Modeling
by: Eckmann, Peter, et al.
Published: (2024)

Interpreting GFlowNets for Drug Discovery: Extracting Actionable Insights for Medicinal Chemistry
by: S, Amirtha Varshini A, et al.
Published: (2025)

Structure-Aware Contrastive Learning with Fine-Grained Binding Representations for Drug Discovery
by: Lan, Jing, et al.
Published: (2025)