12 citations · 35 across the 11 of their papers we have counts for
11 papers
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…
Ion-atom-atom three-body recombination in cold hydrogen and deuterium plasmas
Miruna T. Cretu, Marjan Mirahmadi, Jesús Pérez-Ríos
We present a detailed study about ion-atom-atom three-body recombination in hydrogen and deuterium plasmas based on classical trajectory calculations in hyperspherical coordinates.…
Dynamics of translational and rotational thermalization of AlF molecules via collisions with cryogenic helium
Mallikarjun Karra, Miruna T. Cretu, Bretislav Friedrich +3
We investigated helium-mediated translational and rotational thermalization of the aluminum monofluoride (AlF) molecule at cryogenic temperatures via a new potential…
Predicting second virial coefficients of organic and inorganic compounds using Gaussian Process Regression
Miruna T. Cretu, Jesús Pérez-Ríos
We show that by using intuitive and accessible molecular features it is possible to predict the temperature-dependent second virial coefficient of organic and inorganic compounds u…