163 citations · 317 across the 9 of their papers we have counts for
9 papers
AUTODIFF: Autoregressive Diffusion Modeling for Structure-based Drug Design
Xinze Li, Penglei Wang, Tianfan Fu +4
Structure-based drug design (SBDD), which aims to generate molecules that can bind tightly to the target protein, is an essential problem in drug discovery, and previous approaches…
Revealing the Relationship Between Publication Bias and Chemical Reactivity with Contrastive Learning
Wenhao Gao, Priyanka Raghavan, Ron Shprints +1
A synthetic method's substrate tolerance and generality are often showcased in a "substrate scope" table. However, substrate selection exhibits a frequently discussed publication b…
Reinforced Genetic Algorithm for Structure-based Drug Design
Tianfan Fu, Wenhao Gao, Connor W. Coley +1
Structure-based drug design (SBDD) aims to discover drug candidates by finding molecules (ligands) that bind tightly to a disease-related protein (targets), which is the primary ap…
Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization
Wenhao Gao, Tianfan Fu, Jimeng Sun +1
Molecular optimization is a fundamental goal in the chemical sciences and is of central interest to drug and material design. In recent years, significant progress has been made in…
Amortized Tree Generation for Bottom-up Synthesis Planning and Synthesizable Molecular Design
Wenhao Gao, Rocío Mercado, Connor W. Coley
Molecular design and synthesis planning are two critical steps in the process of molecular discovery that we propose to formulate as a single shared task of conditional synthetic p…
Differentiable Scaffolding Tree for Molecular Optimization
Tianfan Fu, Wenhao Gao, Cao Xiao +3
The structural design of functional molecules, also called molecular optimization, is an essential chemical science and engineering task with important applications, such as drug d…
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development
Kexin Huang, Tianfan Fu, Wenhao Gao +7
Therapeutics machine learning is an emerging field with incredible opportunities for innovatiaon and impact. However, advancement in this field requires formulation of meaningful l…
Deep Learning in Protein Structural Modeling and Design
Wenhao Gao, Sai Pooja Mahajan, Jeremias Sulam +1
Deep learning is catalyzing a scientific revolution fueled by big data, accessible toolkits, and powerful computational resources, impacting many fields including protein structura…
The Synthesizability of Molecules Proposed by Generative Models
Wenhao Gao, Connor W. Coley
The discovery of functional molecules is an expensive and time-consuming process, exemplified by the rising costs of small molecule therapeutic discovery. One class of techniques o…