Chengyun M. Zhang

Zhangheng Road
Pudong, 201203, China

Last Updated: 09/26/2026

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Found 17 publications

Cyclic Peptide Therapeutic Agents Discovery: Computational and Artificial Intelligence-Driven Strategies.

Cyclic Peptide Therapeutic Agents Discovery: Computational and Artificial Intelligence-Driven Strategies.

Journal: Journal of medicinal chemistry

Published: June 04, 2025

PepExplainer: An explainable deep learning model for selection-based macrocyclic peptide bioactivity prediction and optimization.

PepExplainer: An explainable deep learning model for selection-based macrocyclic peptide bioactivity prediction and optimization.

Journal: European journal of medicinal chemistry

Published: April 17, 2024

GAPS: a geometric attention-based network for peptide binding site identification by the transfer learning approach.

GAPS: a geometric attention-based network for peptide binding site identification by the transfer learning approach.

Journal: Briefings in bioinformatics

Published: February 11, 2024

Multi_CycGT: A Deep Learning-Based Multimodal Model for Predicting the Membrane Permeability of Cyclic Peptides.

Multi_CycGT: A Deep Learning-Based Multimodal Model for Predicting the Membrane Permeability of Cyclic Peptides.

Journal: Journal of medicinal chemistry

Published: January 25, 2024

HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints.

HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints.

Journal: Briefings in bioinformatics

Published: September 29, 2023

PepScaf: Harnessing Machine Learning with In Vitro Selection toward De Novo Macrocyclic Peptides against IL-17C/IL-17RE Interaction.

PepScaf: Harnessing Machine Learning with In Vitro Selection toward De Novo Macrocyclic Peptides against IL-17C/IL-17RE Interaction.

Journal: Journal of medicinal chemistry

Published: July 22, 2023

Self-Supervised Molecular Pretraining Strategy for Low-Resource Reaction Prediction Scenarios.

Self-Supervised Molecular Pretraining Strategy for Low-Resource Reaction Prediction Scenarios.

Journal: Journal of chemical information and modeling

Published: September 21, 2022

Transformer-based multitask learning for reaction prediction under low-resource circumstances.

Transformer-based multitask learning for reaction prediction under low-resource circumstances.

Journal: RSC advances

Published: August 26, 2022

Virtual data augmentation method for reaction prediction.

Virtual data augmentation method for reaction prediction.

Journal: Scientific reports

Published: April 29, 2022

Reproducing the invention of a named reaction: zero-shot prediction of unseen chemical reactions.

Reproducing the invention of a named reaction: zero-shot prediction of unseen chemical reactions.

Journal: Physical chemistry chemical physics : PCCP

Published: April 19, 2022

From theory to experiment: transformer-based generation enables rapid discovery of novel reactions.

From theory to experiment: transformer-based generation enables rapid discovery of novel reactions.

Journal: Journal of cheminformatics

Published: December 11, 2021

A graph-convolutional neural network for addressing small-scale reaction prediction.

A graph-convolutional neural network for addressing small-scale reaction prediction.

Journal: Chemical communications (Cambridge, England)

Published: April 28, 2021

Showing 1-12 of 17

Last Updated: 09/26/2026