MP2D is a framework that guides discrete diffusion denoising with constrained MCTS and Pareto rewards to optimize protein sequences for four to five simultaneous objectives, outperforming baselines on antimicrobial peptide and binder design tasks.
A graph-based genetic algo- rithm and generative model/monte carlo tree search for the exploration of chemical space.Chemical science, 10(12):3567–3572
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
q-bio.BM 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
MP2D: Constrained Monte Carlo Tree-Guided Diffusion for Multi-Objective Protein Sequence Design
MP2D is a framework that guides discrete diffusion denoising with constrained MCTS and Pareto rewards to optimize protein sequences for four to five simultaneous objectives, outperforming baselines on antimicrobial peptide and binder design tasks.