PeptiVerse: A Unified Platform for Therapeutic Peptide Property Prediction

Therapeutic peptides combine the advantages of small molecules and antibodies, offering target flexibility and low immunogenicity, yet their successful translation requires careful evaluation of multiple developability properties beyond binding alone. As chemically modified peptides become increasingly common in drug design, no unified platform currently supports systematic property assessment across both canonical sequences and SMILES-based representations. Leveraging the generalizability of large foundational models trained on protein and chemical data, we introduce <b>PeptiVerse</b>, a universal therapeutic peptide property prediction platform. PeptiVerse accepts either amino acid sequences or chemically modified peptide SMILES, delivers state-of-the-art performance across diverse property prediction tasks, and provides both a web interface and open-source implementation for rapid, accessible, and scalable peptide developability analysis. By unifying property prediction across representations, PeptiVerse directly supports early-stage peptide therapeutic development campaigns and property-aware generative design workflows.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-01-03
DOI
https://doi.org/10.64898/2025.12.31.697180
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
0.00

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article

PeptiVerse: A Unified Platform for Therapeutic Peptide Property Prediction

Sophia Vincoff, Pranam Chatterjee, Yong Zhang, Tong Chen et al.
bioRxiv (Cold Spring Harbor Laboratory)
vaccines and immunoinformatics approaches
article

PeptiVerse: A Unified Platform for Therapeutic Peptide Property Prediction

Sophia Vincoff, Pranam Chatterjee, Yong Zhang, Tong Chen, Sophia Tang, Elizabeth Mahood
article en

Abstract

Therapeutic peptides combine the advantages of small molecules and antibodies, offering target flexibility and low immunogenicity, yet their successful translation requires careful evaluation of multiple developability properties beyond binding alone. As chemically modified peptides become increasingly common in drug design, no unified platform currently supports systematic property assessment across both canonical sequences and SMILES-based representations. Leveraging the generalizability of large foundational models trained on protein and chemical data, we introduce <b>PeptiVerse</b>, a universal therapeutic peptide property prediction platform. PeptiVerse accepts either amino acid sequences or chemically modified peptide SMILES, delivers state-of-the-art performance across diverse property prediction tasks, and provides both a web interface and open-source implementation for rapid, accessible, and scalable peptide developability analysis. By unifying property prediction across representations, PeptiVerse directly supports early-stage peptide therapeutic development campaigns and property-aware generative design workflows.

bioRxiv (Cold Spring Harbor Laboratory)
Duke-NUS Medical School (SG), University of Pennsylvania (US)
University of Pennsylvania, National Institutes of Health
Partnerships for the goals
Openalex Percentile: Top 98%
vaccines and immunoinformatics approaches
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PeptiVerse: A Unified Platform for Therapeutic Peptide Property Prediction — Sophia Vincoff, Pranam Chatterjee, et al. · bioRxiv (Cold Spring Harbor Laboratory) (2026) | TGRS Research Map | TGRS