Drug Molecule

Drug molecule research centers on designing and optimizing molecules for therapeutic applications, focusing on predicting properties like binding affinity, efficacy, and side effects. Current research heavily utilizes machine learning, particularly graph neural networks and transformer models, to analyze molecular structures (2D and 3D) and predict properties from various data sources, including large datasets of molecular structures and associated biological activity. These advancements aim to accelerate drug discovery, reduce development costs, and improve the precision and safety of new therapeutics by enabling more efficient virtual screening and property prediction.

Papers

July 15, 2024

Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design
Nataša Tagasovska, Ji Won Park, Matthieu Kirchmeyer, Nathan C. Frey, Andrew Martin Watkins, Aya Abdelsalam Ismail, Arian Rokkum Jamasb, Edith Lee, Tyler Bryson, Stephen Ra, Kyunghyun Cho
Distribution Generalization Protein Design Understanding Out of Distribution Drug Design Antibody Design Drug Molecule Antibody Sequence

February 27, 2024

Exploring Gene Regulatory Interaction Networks and predicting therapeutic molecules for Hypopharyngeal Cancer and EGFR-mutated lung adenocarcinoma
Abanti Bhattacharjya, Md Manowarul Islam, Md Ashraf Uddin, Md. Alamin Talukder, AKM Azad, Sunil Aryal, Bikash Kumar Paul, Wahia Tasnim, Muhammad Ali Abdulllah Almoyad, Mohammad Ali Moni
Computational Biology Regulatory Network Genome Understanding Drug Molecule Nasopharyngeal Carcinoma Genetic Network Lung Adenocarcinoma

February 14, 2024

Emerging Opportunities of Using Large Language Models for Translation Between Drug Molecules and Indications
David Oniani, Jordan Hilsman, Chengxi Zang, Junmei Wang, Lianjin Cai, Jan Zawala, Yanshan Wang
Emerging Opportunity Drug Discovery View Translation Known Molecule Drug Discovery Process Drug Molecule

January 15, 2024

Empirical Evidence for the Fragment level Understanding on Drug Molecular Structure of LLMs
Xiuyuan Hu, Guoqing Liu, Yang Zhao, Hao Zhang
Language Model Medical LLM Molecular Design Chemical Space Empirical Evidence Drug Molecule Fuzzy String Matching Aware Fragment

October 16, 2023

Pareto Optimization to Accelerate Multi-Objective Virtual Screening
Jenna C. Fromer, David E. Graff, Connor W. Coley
Pareto Optimal Molecular Design Virtual Screening Multi Objective Bayesian Optimization Drug Molecule

October 11, 2023

ADMEOOD: Out-of-Distribution Benchmark for Drug Property Prediction
Shuoying Wei, Xinlong Wen, Lida Zhu, Songquan Li, Rongbo Zhu
Distribution Data Property Prediction Novel Benchmark Drug Feature Drug Molecule Distribution Benchmark

August 27, 2023

Building explainable graph neural network by sparse learning for the drug-protein binding prediction
Yang Wang, Zanyu Shi, Timothy Richardson, Kun Huang, Pathum Weerawarna, Yijie Wang
Neural Network Graph Neural Network Chemical Structure Explainable Graph Drug Molecule Chemical Graph

May 17, 2023

Predicting Side Effect of Drug Molecules using Recurrent Neural Networks
Collin Beaudoin, Koustubh Phalak, Swaroop Ghosh
Recurrent Neural Network Side Effect Complex Model Drug Molecule

October 23, 2022

TransEDRP: Dual Transformer model with Edge Emdedded for Drug Respond Prediction
Li Kun, Hu Wenbin
Transformer Architecture Graph Transformer Drug Response Prediction Drug Molecule

August 24, 2022

Molecular Substructure-Aware Network for Drug-Drug Interaction Prediction
Xinyu Zhu, Yongliang Shen, Weiming Lu
Drug Drug Interaction Drug Combination Drug Molecule

May 31, 2022

3D Graph Contrastive Learning for Molecular Property Prediction
Kisung Moon, Sunyoung Kwon
Self Supervised Molecular Representation Molecular Property Prediction Drug Molecule 3D Contrastive Learning

Drug Molecule

Papers

Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design

Exploring Gene Regulatory Interaction Networks and predicting therapeutic molecules for Hypopharyngeal Cancer and EGFR-mutated lung adenocarcinoma

Emerging Opportunities of Using Large Language Models for Translation Between Drug Molecules and Indications

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

Pareto Optimization to Accelerate Multi-Objective Virtual Screening

ADMEOOD: Out-of-Distribution Benchmark for Drug Property Prediction

Building explainable graph neural network by sparse learning for the drug-protein binding prediction

Predicting Side Effect of Drug Molecules using Recurrent Neural Networks

TransEDRP: Dual Transformer model with Edge Emdedded for Drug Respond Prediction

Molecular Substructure-Aware Network for Drug-Drug Interaction Prediction

3D Graph Contrastive Learning for Molecular Property Prediction