SAGE: A Segment-Anchor-Guided Exploration Framework for the Optimization of CDK7 Inhibitors as Promising Cancer Therapy

Cyclin-dependent kinase 7 (CDK7) plays a crucial role in cell cycle regulation and transcription, establishing it as a promising target for cancer therapy. Although the covalent inhibitor THZ1 effectively targets CDK7, it presents risks such as a short half-life and potential off-target side effects. To address these limitations, we employed a computational workflow integrating virtual screening, molecular dynamics (MD) simulations, and the free energy perturbation (FEP) method to design noncovalent CDK7 inhibitors with enhanced selectivity and safety profiles. MD simulations elucidated THZ1's inhibitory mechanism and identified key molecular fragments within its structure. By incorporating fragments from known inhibitors, we introduced extensive noncovalent interactions within the binding pocket, leading to the identification of three novel noncovalent inhibitors with binding affinities comparable to or higher than that of THZ1. Our findings not only introduce promising CDK7 inhibitors but also present a robust computational framework that could accelerate the discovery of kinase-targeted therapeutics.

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Publication Details

Journal
The Journal of Physical Chemistry B
Published
2025-08-19
DOI
https://doi.org/10.1021/acs.jpcb.5c02076
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

SAGE: A Segment-Anchor-Guided Exploration Framework for the Optimization of CDK7 Inhibitors as Promising Cancer Therapy

Damiano Buratto, Zhaoqi Shi, Ruhong Zhou, Xufan Gao
The Journal of Physical Chemistry B
Computational Drug Discovery Methods
article

SAGE: A Segment-Anchor-Guided Exploration Framework for the Optimization of CDK7 Inhibitors as Promising Cancer Therapy

Damiano Buratto, Zhaoqi Shi, Ruhong Zhou, Xufan Gao
article en

Abstract

Cyclin-dependent kinase 7 (CDK7) plays a crucial role in cell cycle regulation and transcription, establishing it as a promising target for cancer therapy. Although the covalent inhibitor THZ1 effectively targets CDK7, it presents risks such as a short half-life and potential off-target side effects. To address these limitations, we employed a computational workflow integrating virtual screening, molecular dynamics (MD) simulations, and the free energy perturbation (FEP) method to design noncovalent CDK7 inhibitors with enhanced selectivity and safety profiles. MD simulations elucidated THZ1's inhibitory mechanism and identified key molecular fragments within its structure. By incorporating fragments from known inhibitors, we introduced extensive noncovalent interactions within the binding pocket, leading to the identification of three novel noncovalent inhibitors with binding affinities comparable to or higher than that of THZ1. Our findings not only introduce promising CDK7 inhibitors but also present a robust computational framework that could accelerate the discovery of kinase-targeted therapeutics.

The Journal of Physical Chemistry BVol. 129(34)
Quantitative BioSciences (US), Shanghai Advanced Research Institute (CN), Zhejiang University (CN), Columbia University (US)
National Natural Science Foundation of China, Zhejiang University, National Key Research and Development Program of China
Openalex Percentile: Top 77%
Computational Drug Discovery Methods
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SAGE: A Segment-Anchor-Guided Exploration Framework for the Optimization of CDK7 Inhibitors as Promising Cancer Therapy — Damiano Buratto, Zhaoqi Shi, et al. · The Journal of Physical Chemistry B (2025) | TGRS Research Map | TGRS