Machine Learning‐Enabled Virtual Screening with Multiple Protein Structures toward the Discovery of Novel JAK3 Inhibitors: Integration of Molecular Docking, Pharmacophore, and Naïve Bayesian Classification

药效团 虚拟筛选 对接(动物) 计算生物学 Janus激酶3 计算机科学 药物发现 仿形(计算机编程) 分子动力学 机器学习 化学 人工智能 生物信息学 生物 立体化学 计算化学 生物化学 医学 抗原提呈细胞 细胞毒性T细胞 护理部 体外 操作系统
作者
Jingyu Zhu,Jingyu Sun,Lei Jia,Lei Xu,Yanfei Cai,Yun Chen,Jian Jin
出处
期刊:Advanced theory and simulations [Wiley]
卷期号:6 (7) 被引量:2
标识
DOI:10.1002/adts.202200835
摘要

Abstract Extensive research has accumulated suggesting that Janus kinase 3 (JAK3) is closely related to the occurrence and development of various human diseases, making JAK3 a highly potential drug target. However, JAK3 has high homology with other members of the JAK family, making the development of JAK3 inhibitors full of challenges. Thus, here, a naïve Bayesian classification (NBC) model based on multiple JAK3 protein conformations, which integrates molecular docking, pharmacophore, and molecular descriptors, is developed to find novel JAK3 inhibitors. First, the validation set is used to prove whether molecular docking or pharmacophore, integrating multiple JAK3 conformations always has higher prediction accuracy than that of any single conformation. Second, external prediction reveals that the NBC model combining molecular docking, pharmacophore, and important molecular features could significantly improve the enrichment of active JAK3 inhibitors. Finally, the optimal NBC model is utilized for virtual screening against a large chemical database and some compounds with high Bayesian scores are identified. Altogether, the machine learning‐based virtual screening protocol not only has strong efficiency but also has high screening accuracy. It is hoped that the developed virtual screening strategy could provide valuable guidance for the discovery of novel JAK3 inhibitors.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
安静雅阳发布了新的文献求助10
刚刚
蝈蝈完成签到,获得积分10
刚刚
崔裕敬完成签到,获得积分20
刚刚
楼山柳发布了新的文献求助10
刚刚
1秒前
生椰拿铁不加生椰完成签到 ,获得积分10
1秒前
1秒前
1秒前
wzj完成签到,获得积分10
2秒前
仿生人发布了新的文献求助10
2秒前
万信心完成签到,获得积分10
3秒前
3秒前
4秒前
苏醒的记忆完成签到,获得积分10
4秒前
ZP完成签到 ,获得积分10
4秒前
可爱完成签到,获得积分10
4秒前
www完成签到,获得积分10
4秒前
4秒前
Dritsw应助clocksoar采纳,获得10
4秒前
6秒前
李健的小迷弟应助Loooong采纳,获得10
6秒前
。。发布了新的文献求助10
6秒前
Q华完成签到,获得积分10
6秒前
烟花应助激昂的渊思采纳,获得10
6秒前
铁铁发布了新的文献求助10
6秒前
7秒前
小麻薯发布了新的文献求助10
7秒前
夏之发布了新的文献求助10
8秒前
8秒前
joker完成签到,获得积分10
8秒前
山东及时雨完成签到,获得积分20
9秒前
9秒前
11秒前
Gemini完成签到,获得积分10
11秒前
vividkingking完成签到 ,获得积分10
11秒前
不想学习发布了新的文献求助10
11秒前
12秒前
大个应助biubiu采纳,获得30
12秒前
12秒前
12秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Picture Books with Same-sex Parented Families: Unintentional Censorship 500
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
不知道标题是什么 500
A Preliminary Study on Correlation Between Independent Components of Facial Thermal Images and Subjective Assessment of Chronic Stress 500
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 360
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3970724
求助须知:如何正确求助?哪些是违规求助? 3515419
关于积分的说明 11178342
捐赠科研通 3250592
什么是DOI,文献DOI怎么找? 1795372
邀请新用户注册赠送积分活动 875802
科研通“疑难数据库(出版商)”最低求助积分说明 805181