Development of LRRK2 inhibitors through computational strategies: a promising avenue for Parkinson's disease

Xiaoqing Gong; Shuoyan Tan; Yuwei Yang; Yang Yu; Xiaojun Yao; Huanxiang Liu

doi:10.1016/j.drudis.2025.104446

Development of LRRK2 inhibitors through computational strategies: a promising avenue for Parkinson's disease

Xiaoqing Gong, Shuoyan Tan, Yuwei Yang, Yang Yu, Xiaojun Yao, Huanxiang Liu

Faculty of Applied Sciences

Research output: Contribution to journal › Review article › peer-review

Abstract

Parkinson's disease (PD) is a prevalent neurodegenerative disorder that remains incurable. Leucine-rich repeat kinase 2 (LRRK2) has a pivotal role in PD pathogenesis, making it a promising therapeutic target. Thus, there is an urgent need to develop structurally diverse, highly selective, blood–brain barrier (BBB)-permeable LRRK2 inhibitors. Computer-aided and artificial intelligence (AI)-driven drug design methods have shown significant advantages in the discovery of LRRK2 inhibitors. Building upon a systematic review of structural characteristics, biological functions, and molecular mechanisms of LRRK2, in this review, we summarize recent advances in LRRK2 inhibitor development, highlighting the pivotal role of computational approaches in accelerating inhibitor discovery.

Original language	English
Article number	104446
Journal	Drug Discovery Today
Volume	30
Issue number	9
DOIs	https://doi.org/10.1016/j.drudis.2025.104446
Publication status	Published - Sept 2025

Keywords

AI-driven drug design
LRRK2 inhibitors
Parkinson's disease
computer-aided drug design

Access to Document

10.1016/j.drudis.2025.104446

Cite this

@article{9d6ae935c5d44a3d8915cfc85c891b7a,

title = "Development of LRRK2 inhibitors through computational strategies: a promising avenue for Parkinson's disease",

abstract = "Parkinson's disease (PD) is a prevalent neurodegenerative disorder that remains incurable. Leucine-rich repeat kinase 2 (LRRK2) has a pivotal role in PD pathogenesis, making it a promising therapeutic target. Thus, there is an urgent need to develop structurally diverse, highly selective, blood–brain barrier (BBB)-permeable LRRK2 inhibitors. Computer-aided and artificial intelligence (AI)-driven drug design methods have shown significant advantages in the discovery of LRRK2 inhibitors. Building upon a systematic review of structural characteristics, biological functions, and molecular mechanisms of LRRK2, in this review, we summarize recent advances in LRRK2 inhibitor development, highlighting the pivotal role of computational approaches in accelerating inhibitor discovery.",

keywords = "AI-driven drug design, LRRK2 inhibitors, Parkinson's disease, computer-aided drug design",

author = "Xiaoqing Gong and Shuoyan Tan and Yuwei Yang and Yang Yu and Xiaojun Yao and Huanxiang Liu",

note = "Publisher Copyright: {\textcopyright} 2025 Elsevier Ltd",

year = "2025",

month = sep,

doi = "10.1016/j.drudis.2025.104446",

language = "English",

volume = "30",

journal = "Drug Discovery Today",

issn = "1359-6446",

publisher = "Elsevier Ltd.",

number = "9",

}

TY - JOUR

T1 - Development of LRRK2 inhibitors through computational strategies

T2 - a promising avenue for Parkinson's disease

AU - Gong, Xiaoqing

AU - Tan, Shuoyan

AU - Yang, Yuwei

AU - Yu, Yang

AU - Yao, Xiaojun

AU - Liu, Huanxiang

PY - 2025/9

Y1 - 2025/9

N2 - Parkinson's disease (PD) is a prevalent neurodegenerative disorder that remains incurable. Leucine-rich repeat kinase 2 (LRRK2) has a pivotal role in PD pathogenesis, making it a promising therapeutic target. Thus, there is an urgent need to develop structurally diverse, highly selective, blood–brain barrier (BBB)-permeable LRRK2 inhibitors. Computer-aided and artificial intelligence (AI)-driven drug design methods have shown significant advantages in the discovery of LRRK2 inhibitors. Building upon a systematic review of structural characteristics, biological functions, and molecular mechanisms of LRRK2, in this review, we summarize recent advances in LRRK2 inhibitor development, highlighting the pivotal role of computational approaches in accelerating inhibitor discovery.

AB - Parkinson's disease (PD) is a prevalent neurodegenerative disorder that remains incurable. Leucine-rich repeat kinase 2 (LRRK2) has a pivotal role in PD pathogenesis, making it a promising therapeutic target. Thus, there is an urgent need to develop structurally diverse, highly selective, blood–brain barrier (BBB)-permeable LRRK2 inhibitors. Computer-aided and artificial intelligence (AI)-driven drug design methods have shown significant advantages in the discovery of LRRK2 inhibitors. Building upon a systematic review of structural characteristics, biological functions, and molecular mechanisms of LRRK2, in this review, we summarize recent advances in LRRK2 inhibitor development, highlighting the pivotal role of computational approaches in accelerating inhibitor discovery.

KW - AI-driven drug design

KW - LRRK2 inhibitors

KW - Parkinson's disease

KW - computer-aided drug design

UR - https://www.scopus.com/pages/publications/105013092662

U2 - 10.1016/j.drudis.2025.104446

DO - 10.1016/j.drudis.2025.104446

M3 - Review article

C2 - 40769274

AN - SCOPUS:105013092662

SN - 1359-6446

VL - 30

JO - Drug Discovery Today

JF - Drug Discovery Today

IS - 9

M1 - 104446

ER -

Development of LRRK2 inhibitors through computational strategies: a promising avenue for Parkinson's disease

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this