107 citations · 138 across the 8 of their papers we have counts for
8 papers
Training Large Language Models for Small-Molecule Design with Synthetic Task Scaling
Frank Hu, Shriram Chennakesavalu, Zichen Wang +5
Designing viable drug candidates requires searching a combinatorially large and rugged chemical space for molecules that satisfy multiple, often competing, objectives. Large langua…
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…
Evaluating the Progression of Large Language Model Capabilities for Small-Molecule Drug Design
Shriram Chennakesavalu, Kirill Shmilovich, Hayley Weir +5
Large Language Models (LLMs) have the potential to accelerate small molecule drug design due to their ability to reason about information from diverse sources and formats. However,…
DiAMoNDBack: Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein Traces
Michael S. Jones, Kirill Shmilovich, Andrew L. Ferguson
Coarse-grained molecular models of proteins permit access to length and time scales unattainable by all-atom models and the simulation of processes that occur on long-time scales s…
DEL-Dock: Molecular Docking-Enabled Modeling of DNA-Encoded Libraries
Kirill Shmilovich, Benson Chen, Theofanis Karaletsos +1
DNA-Encoded Library (DEL) technology has enabled significant advances in hit identification by enabling efficient testing of combinatorially-generated molecular libraries. DEL scre…
Orbital Mixer: Using Atomic Orbital Features for Basis Dependent Prediction of Molecular Wavefunctions
Kirill Shmilovich, Devin Willmott, Ivan Batalov +3
Leveraging ab initio data at scale has enabled the development of machine learning models capable of extremely accurate and fast molecular property prediction. A central paradigm o…
Temporally coherent backmapping of molecular trajectories from coarse-grained to atomistic resolution
Kirill Shmilovich, Marc Stieffenhofer, Nicholas E. Charron +1
Coarse-graining offers a means to extend the achievable time and length scales of molecular dynamics simulations beyond what is practically possible in the atomistic regime. Sampli…
Discovery of Self-Assembling -Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation
Kirill Shmilovich, Rachael A. Mansbach, Hythem Sidky +4
Electronically-active organic molecules have demonstrated great promise as novel soft materials for energy harvesting and transport. Self-assembled nanoaggregates formed from -c…