Skip to main content

De novo design of peptide binders to conformationally diverse targets with contrastive language modeling.

Publication ,  Journal Article
Bhat, S; Palepu, K; Hong, L; Mao, J; Ye, T; Iyer, R; Zhao, L; Chen, T; Vincoff, S; Watson, R; Wang, TZ; Srijay, D; Kavirayuni, VS; Goel, S ...
Published in: Sci Adv
January 24, 2025

Designing binders to target undruggable proteins presents a formidable challenge in drug discovery. In this work, we provide an algorithmic framework to design short, target-binding linear peptides, requiring only the amino acid sequence of the target protein. To do this, we propose a process to generate naturalistic peptide candidates through Gaussian perturbation of the peptidic latent space of the ESM-2 protein language model and subsequently screen these novel sequences for target-selective interaction activity via a contrastive language-image pretraining (CLIP)-based contrastive learning architecture. By integrating these generative and discriminative steps, we create a Peptide Prioritization via CLIP (PepPrCLIP) pipeline and validate highly ranked, target-specific peptides experimentally, both as inhibitory peptides and as fusions to E3 ubiquitin ligase domains. PepPrCLIP-derived constructs demonstrate functionally potent binding and degradation of conformationally diverse, disease-driving targets in vitro. In total, PepPrCLIP empowers the modulation of previously inaccessible proteins without reliance on stable and ordered tertiary structures.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Sci Adv

DOI

EISSN

2375-2548

Publication Date

January 24, 2025

Volume

11

Issue

4

Start / End Page

eadr8638

Location

United States

Related Subject Headings

  • Protein Conformation
  • Protein Binding
  • Peptides
  • Models, Molecular
  • Humans
  • Drug Discovery
  • Drug Design
  • Amino Acid Sequence
  • Algorithms
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Bhat, S., Palepu, K., Hong, L., Mao, J., Ye, T., Iyer, R., … Chatterjee, P. (2025). De novo design of peptide binders to conformationally diverse targets with contrastive language modeling. Sci Adv, 11(4), eadr8638. https://doi.org/10.1126/sciadv.adr8638
Bhat, Suhaas, Kalyan Palepu, Lauren Hong, Joey Mao, Tianzheng Ye, Rema Iyer, Lin Zhao, et al. “De novo design of peptide binders to conformationally diverse targets with contrastive language modeling.Sci Adv 11, no. 4 (January 24, 2025): eadr8638. https://doi.org/10.1126/sciadv.adr8638.
Bhat S, Palepu K, Hong L, Mao J, Ye T, Iyer R, et al. De novo design of peptide binders to conformationally diverse targets with contrastive language modeling. Sci Adv. 2025 Jan 24;11(4):eadr8638.
Bhat, Suhaas, et al. “De novo design of peptide binders to conformationally diverse targets with contrastive language modeling.Sci Adv, vol. 11, no. 4, Jan. 2025, p. eadr8638. Pubmed, doi:10.1126/sciadv.adr8638.
Bhat S, Palepu K, Hong L, Mao J, Ye T, Iyer R, Zhao L, Chen T, Vincoff S, Watson R, Wang TZ, Srijay D, Kavirayuni VS, Kholina K, Goel S, Vure P, Deshpande AJ, Soderling SH, DeLisa MP, Chatterjee P. De novo design of peptide binders to conformationally diverse targets with contrastive language modeling. Sci Adv. 2025 Jan 24;11(4):eadr8638.

Published In

Sci Adv

DOI

EISSN

2375-2548

Publication Date

January 24, 2025

Volume

11

Issue

4

Start / End Page

eadr8638

Location

United States

Related Subject Headings

  • Protein Conformation
  • Protein Binding
  • Peptides
  • Models, Molecular
  • Humans
  • Drug Discovery
  • Drug Design
  • Amino Acid Sequence
  • Algorithms