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Status: Unchecked ×Keyword: peptide therapeutics ×Clear all

3 claims from 1 paper

1. Computer Science › Computational Drug Discovery Methods

   Diffusion Models at the Drug Discovery Frontier: A Review on Generating Small Molecules Versus Therapeutic Peptides

   Wang, Ma, Chang et al. · Biology · 2025

   A review comparing how diffusion models are used to design small molecules and therapeutic peptides, setting out their distinct and shared challenges and arguing for closed-loop design-build-test-learn platforms.

   Unchecked3 claims
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   1. UncheckedFor therapeutic peptides, diffusion models focus on functional sequences and de novo structures, with stability, folding and immunogenicity as the main challenges.“Conversely, for therapeutic peptides, the focus shifts to generating functional sequences and designing de novo structures, where the primary challenges are achieving biological stability against proteolysis, ensuring proper folding, and minimizing immunogenicity.”
   2. UncheckedThe review says diffusion models for small molecules and for peptides share three hurdles: scarce good data, inaccurate scoring functions, and a need for lab validation.“Despite these distinct challenges, both domains face shared hurdles: the scarcity of high-quality experimental data, the reliance on inaccurate scoring functions for validation, and the crucial need for experimental validation.”
   3. UncheckedThe review says diffusion models do well at structure-based small-molecule design but struggle to ensure the molecules they generate can be synthesised.“For small molecules, these models excel at structure-based design, generating novel, pocket-fitting ligands with desired physicochemical properties, yet face the critical hurdle of ensuring chemical synthesizability.”