23 citations · 42 across the 7 of their papers we have counts for
8 papers
DrugPlayGround: Benchmarking Large Language Models and Embeddings for Drug Discovery
Tianyu Liu, Sihan Jiang, Fan Zhang +3
Large language models (LLMs) are in the ascendancy for research in drug discovery, offering unprecedented opportunities to reshape drug research by accelerating hypothesis generati…
SynLlama: Generating Synthesizable Molecules and Their Analogs with Large Language Models
Kunyang Sun, Dorian Bagni, Joseph M. Cavanagh +6
Generative machine learning models for exploring chemical space have shown immense promise, but many molecules they generate are too difficult to synthesize, making them impractica…
A Workflow to Create a High-Quality Protein-Ligand Binding Dataset for Training, Validation, and Prediction Tasks
Yingze Wang, Kunyang Sun, Jie Li +4
Development of scoring functions (SFs) used to predict protein-ligand binding energies requires high-quality 3D structures and binding assay data for training and testing their par…
SmileyLlama: Modifying Large Language Models for Directed Chemical Space Exploration
Joseph M. Cavanagh, Kunyang Sun, Andrew Gritsevskiy +4
We show that large language model (LLMs) can be transformed via supervised fine-tuning (SFT) of engineered prompts into SmileyLlama for exploring the chemical space of drug molecul…
Leak Proof PDBBind: A Reorganized Dataset of Protein-Ligand Complexes for More Generalizable Binding Affinity Prediction
Jie Li, Xingyi Guan, Oufan Zhang +4
The majority of machine learning scoring functions used in drug discovery for predicting protein-ligand binding poses and affinities have been trained on the PDBBind dataset. Howev…
Chiral edge waves in a dance-based human topological insulator
Matthew Du, Juan B. Pérez-Sánchez, Jorge A. Campos-Gonzalez-Angulo +10
Topological insulators are insulators in the bulk but feature chiral energy propagation along the boundary. This property is topological in nature and therefore robust to disorder.…
LIMO: Latent Inceptionism for Targeted Molecule Generation
Peter Eckmann, Kunyang Sun, Bo Zhao +3
Generation of drug-like molecules with high binding affinity to target proteins remains a difficult and resource-intensive task in drug discovery. Existing approaches primarily emp…
Mining for Potent Inhibitors through Artificial Intelligence and Physics: A Unified Methodology for Ligand Based and Structure Based Drug Design
Jie Li, Oufan Zhang, Yingze Wang +8
The viability of a new drug molecule is a time and resource intensive task that makes computer-aided assessments a vital approach to rapid drug discovery. Here we develop a machine…