12 citations · 35 across the 11 of their papers we have counts for
8 papers · 1 filter
DBMol: Design of High-Affinity, Target-Specific Small Molecules through Structure Prediction Models
Yiming Qin, Kai Yi, Miruna Cretu +3
Designing small molecule ligands that bind with high affinity to specific protein pockets is a fundamental goal in drug discovery, as small molecules constitute a major fraction of…
SynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore Profiles
Miruna Cretu, John Bradshaw, Patricia Suriana +6
We present SynLaD, a latent diffusion framework for small-molecule generation that unifies ligand-based drug design objectives (what to make) with synthetic accessibility (how to m…
General Multimodal Protein Design Enables DNA-Encoding of Chemistry
Jarrid Rector-Brooks, Théophile Lambert, Marta Skreta +15
Evolution is an extraordinary engine for enzymatic diversity, yet the chemistry it has explored remains a narrow slice of what DNA can encode. Deep generative models can design new…
Zatom-1: Towards a Multimodal Foundation Model for 3D Molecules and Materials
Alex Morehead, Miruna Cretu, Antonia Panescu +14
General-purpose 3D modeling in chemistry encompasses molecules and materials, requiring both generative and predictive capabilities. However, most existing AI approaches are optimi…
SynCoGen: Synthesizable 3D Molecule Generation via Joint Reaction and Coordinate Modeling
Andrei Rekesh, Miruna Cretu, Dmytro Shevchuk +6
Synthesizability remains a critical bottleneck in generative molecular design. While recent advances have addressed synthesizability in 2D graphs, extending these constraints to 3D…
TABASCO: A Fast, Simplified Model for Molecular Generation with Improved Physical Quality
Carlos Vonessen, Charles Harris, Miruna Cretu +1
State-of-the-art models for 3D molecular generation are based on significant inductive biases, SE(3), permutation equivariance to respect symmetry and graph message-passing network…
Diffusion-Free Graph Generation with Next-Scale Prediction
Samuel Belkadi, Steve Hong, Marian Chen +3
Autoregressive models excel in efficiency and plug directly into the transformer ecosystem, delivering robust generalization, predictable scalability, and seamless workflows such a…
SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints
Miruna Cretu, Charles Harris, Ilia Igashov +6
Generative models see increasing use in computer-aided drug design. However, while performing well at capturing distributions of molecular motifs, they often produce synthetically…