Feiying Chen

AI-driven and Phenotype-based Drug Design

Sun, 07 Jun 2026 00:00:00 +0000

My earlier work focused on molecular generation, allosteric regulation, CRISPR-Cas9 conformational dynamics, and computational-experimental workflows for drug discovery. I am especially interested in phenotype-based drug design, where cellular response, molecular mechanism, and perturbation design are linked into one therapeutic discovery loop.

Computational Chemistry and CRISPR Allostery

Sun, 07 Jun 2026 00:00:00 +0000

I use molecular dynamics, docking, Markov state modeling, pathway analysis, and allosteric network analysis to study how molecular perturbations reshape protein conformational states. This direction grew from work on SauCas9 inhibition by AcrIIA14, SpCas9 catalytic activation, and allosteric knowledgebase construction.

Experience

Sun, 07 Jun 2026 00:00:00 +0000

Perturbation Biology and AI Virtual Cells

Sun, 07 Jun 2026 00:00:00 +0000

I am interested in models that connect perturbations, cellular state transitions, and phenotype-level responses. Current directions include single-cell foundation model pretraining, post-training for perturbation response prediction, model deployment for biological workflows, and AI virtual cell frameworks for tumor microenvironment analysis.

BiEvo: From autoregression to bidirectional genomic representations with MNTP and architectural symmetrization

Thu, 01 Jan 2026 00:00:00 +0000

Citation. Feiying Chen et al. BiEvo: From autoregression to bidirectional genomic representations with MNTP and architectural symmetrization. Ongoing manuscript.

This project studies bidirectional genomic representation learning, using objective and architecture changes to improve how sequence models encode biological context. It is listed as ongoing rather than under review.

TCM-Navigator: A deep learning workflow for TCM-like compound generation and evaluation

Fri, 26 Sep 2025 00:00:00 +0000

Citation. Feiying Chen, Victor Jun Yu Lim, Mingyu Li, and Hao Fan. TCM-Navigator: a deep learning-based workflow for generation and evaluation of traditional Chinese medicine-like compounds for drug development. Briefings in Bioinformatics, 2025.

This work connects molecular generation with practical drug-development filters: a TCM-like chemical language model generates large focused libraries, an AttentiveFP-based identifier scores TCM-like characteristics, and physics-based evaluation helps prioritize target-ligand pairs.

In silico Identification and Experimental Validation of Long-range Allosteric Inhibition of Staphylococcus aureus Cas9 by Anti-CRISPR Protein AcrIIA14

Thu, 01 May 2025 00:00:00 +0000

Citation. Feiying Chen et al. In silico Identification and Experimental Validation of Long-range Allosteric Inhibition of Staphylococcus aureus Cas9 by Anti-CRISPR Protein AcrIIA14. International Journal of Biological Macromolecules, 2025.

The work uses molecular simulation and wet-lab validation to explain how AcrIIA14 can remotely regulate SauCas9 catalytic activity, supporting the design of controllable CRISPR systems and Cas9 allosteric inhibitors.

Untangling the molecular mechanism of SpCas9 catalytic activation

Tue, 04 Mar 2025 00:00:00 +0000

Citation. Shaoyong Lu, Xinyi Li, Jiacheng Wei, Feiying Chen, Mingyu Li, Ning Liu, and Jian Zhang. Untangling the molecular mechanism of SpCas9 catalytic activation: A gear-and-wedge fitting model. Under review.

This manuscript links atomistic simulation to biochemical and cellular validation, showing how linker remodeling and REC2-domain motion coordinate the large HNH-domain displacement required for SpCas9 activation.

ASD2023: Toward an integrated allosteric knowledgebase

Fri, 05 Jan 2024 00:00:00 +0000

Citation. Jixiao He, Xinyi Liu, Chunhao Zhu, Jinyin Zha, Qian Li, Mingzhu Zhao, Jiacheng Wei, Feiying Chen, et al. ASD2023: towards the integrating landscapes of allosteric knowledgebase. Nucleic Acids Research, 2024.

ASD2023 extends the Allosteric Database from curated entries toward an integrated research platform for allosteric target discovery, mechanistic analysis, and drug development.