Microsecond Molecular Dynamics Simulation to Gain Insight Into the Binding of MRTX1133 and Trametinib With KRASG12D Mutant Protein for Drug Repurposing

曲美替尼 克拉斯 达布拉芬尼 分子动力学 癌症研究 化学 突变 计算生物学 生物 信号转导 威罗菲尼 生物化学 MAPK/ERK通路 黑色素瘤 计算化学 基因 转移性黑色素瘤
作者
Ancy Iruthayaraj,Penislusshiyan Sakayanathan,Fuád Ameén,Chitra Loganathan
出处
期刊:Journal of Molecular Recognition [Wiley]
被引量:3
标识
DOI:10.1002/jmr.3103
摘要

ABSTRACT The Kirsten Rat Sarcoma (KRAS) G12D mutant protein is a primary driver of pancreatic ductal adenocarcinoma, necessitating the identification of targeted drug molecules. Repurposing of drugs quickly finds new uses, speeding treatment development. This study employs microsecond molecular dynamics simulations to unveil the binding mechanisms of the FDA‐approved MEK inhibitor trametinib with KRAS G12D , providing insights for potential drug repurposing. The binding of trametinib was compared with clinical trial drug MRTX1133, which demonstrates exceptional activity against KRAS G12D , for better understanding of interaction mechanism of trametinib with KRAS G12D . The resulting stable MRTX1133‐KRAS G12D complex reduces root mean square deviation (RMSD) values, in Switch I and II domains, highlighting its potential for inhibiting KRAS G12D . MRTX1133's robust interaction with Tyr64 and disruption of Tyr96‐Tyr71‐Arg68 network showcase its ability to mitigate the effects of the G12D mutation. In contrast, trametinib employs a distinctive binding mechanism involving P‐loop, Switch I and II residues. Extended simulations to 1 μs reveal sustained network interactions with Tyr32, Thr58, and GDP, suggesting a role of trametinib in maintaining KRAS G12D in an inactive state and impede the further cell signaling. The decomposition binding free energy values illustrate amino acids' contributions to binding energy, elucidating ligand–protein interactions and molecular stability. The machine learning approach reveals that van der Waals interactions among the residues play vital role in complex stability and the potential amino acids involved in drug–receptor interactions of each complex. These details provide a molecular‐level understanding of drug binding mechanisms, offering essential knowledge for further drug repurposing and potential drug discovery.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
希望天下0贩的0应助hyl采纳,获得10
1秒前
1秒前
user001完成签到,获得积分10
1秒前
2秒前
2秒前
2秒前
2秒前
张张张完成签到,获得积分10
3秒前
SciGPT应助欣慰梦易采纳,获得10
3秒前
勤恳的金鱼完成签到,获得积分10
3秒前
superchen发布了新的文献求助10
3秒前
科研通AI6.2应助嗯嗯采纳,获得10
4秒前
4秒前
杜天豪完成签到,获得积分20
5秒前
5秒前
英姑应助孤独的晓山采纳,获得10
5秒前
CipherSage应助顺心的匪采纳,获得10
6秒前
6秒前
0101完成签到,获得积分10
6秒前
newstrong发布了新的文献求助10
6秒前
7秒前
科研通AI6.4应助尤野采纳,获得10
7秒前
笨小孩发布了新的文献求助10
7秒前
郭优优发布了新的文献求助10
7秒前
郭优优发布了新的文献求助10
7秒前
郭优优发布了新的文献求助10
7秒前
郭优优发布了新的文献求助10
7秒前
酷波er应助神勇饼干采纳,获得10
8秒前
rrr应助堡主采纳,获得10
9秒前
理想三旬发布了新的文献求助10
9秒前
豌豆苗完成签到 ,获得积分10
10秒前
杜天豪发布了新的文献求助10
11秒前
土豪的洋葱完成签到,获得积分10
11秒前
11秒前
fighter完成签到,获得积分10
11秒前
12秒前
12秒前
14秒前
15秒前
Yukki发布了新的文献求助10
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Navigating Normative Orders. Interdisciplinary Perspectives 800
1 Peter and Christ's Descent to the Dead in Its Early Christian Reception 700
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7740693
求助须知:如何正确求助?哪些是违规求助? 9289281
关于积分的说明 20195025
捐赠科研通 7318891
什么是DOI,文献DOI怎么找? 3306508
关于科研通互助平台的介绍 2458788
邀请新用户注册赠送积分活动 2316746