清晨好,您是今天最早来到科研通的研友!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您科研之路漫漫前行!

Molecular modelling studies and identification of novel phytochemical inhibitor of DLL3

前列腺癌 虚拟筛选 药效团 植物化学 化学 计算生物学 药物发现 癌症 医学 立体化学 生物化学 内科学 生物
作者
Bhrugesh Joshi,Vishwambhar Vishnu Bhandare,Prittesh Patel,Abhishek Sharma,Rajesh Patel,Ramar Krishnamurthy
出处
期刊:Journal of Biomolecular Structure & Dynamics [Taylor & Francis]
卷期号:41 (7): 3089-3109 被引量:2
标识
DOI:10.1080/07391102.2022.2045224
摘要

Prostate cancer has been recently considered the most diagnosed cancer in male. DLL3 is overexpressed in CRPC-NE but not in localised prostate cancer or BPH. There are no effective treatments for neuroendocrine differentiated prostate cancer due to a lack of understanding of DLL3 structure and function. The structure of DLL3 is not yet determined using any experimental techniques. Hence, the structure-based drug discovery approach against prostate cancer has not shown great success. In present study, molecular modelling techniques were employed to generate three-dimensional structure of DLL3 and performed its thorough structural analysis. Further, all-atom molecular dynamics simulation was performed to obtain energetically favourable conformation. Further, we used a virtual screening using a library of >13800 phytochemicals from the IMPPAT database and other literature to select the best possible phytochemical inhibitor for DLL3 and identified the top five compounds. Relative binding affinity was calculated using the MM-PBSA approach. ADMET properties of the screened compounds reveal the toxic effect of Gnemonol C. We believe these studied physicochemical properties, functional domain identification, and binding site identification would be very useful to gain more structural and functional insights of DLL3; also, it can be used to infer their pharmacodynamics properties of DLL3 which was recently reported as an important prostate cancer target. The current study also proposes that Ergosterol Peroxide, Dioslupecin A, Mulberrofuran K, and Caracurine V have strong affinities and could serve as plausible inhibitors against DLL3. We believe this study would further help develop better drug candidates against neuroendocrine prostate cancer.Communicated by Ramaswamy H. Sarma.
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
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
李霞客完成签到,获得积分10
3秒前
LGH完成签到 ,获得积分10
6秒前
6秒前
神一样的鸟完成签到 ,获得积分10
6秒前
hyl-tcm完成签到 ,获得积分10
17秒前
先锋老刘001完成签到,获得积分10
20秒前
点点完成签到 ,获得积分10
21秒前
槑槑完成签到 ,获得积分10
43秒前
古炮完成签到 ,获得积分10
49秒前
科研通AI6.3应助Lijunjie采纳,获得10
51秒前
共享精神应助科研通管家采纳,获得10
52秒前
凌泉完成签到 ,获得积分10
53秒前
Lijunjie完成签到,获得积分10
1分钟前
save完成签到,获得积分10
1分钟前
1分钟前
1分钟前
拂晓发布了新的文献求助10
1分钟前
冷傲的凡雁完成签到 ,获得积分10
1分钟前
1分钟前
拂晓完成签到,获得积分10
1分钟前
1分钟前
1分钟前
偏偏完成签到 ,获得积分10
1分钟前
甜叶菊发布了新的文献求助10
1分钟前
Qing完成签到 ,获得积分10
1分钟前
图喵喵完成签到,获得积分10
1分钟前
空儒完成签到 ,获得积分10
1分钟前
记上没文献了完成签到 ,获得积分10
1分钟前
妩媚的羽毛完成签到,获得积分10
1分钟前
华仔应助苏素肃采纳,获得10
2分钟前
su完成签到 ,获得积分10
2分钟前
任性铅笔完成签到 ,获得积分10
2分钟前
甜叶菊发布了新的文献求助10
2分钟前
wanghao完成签到 ,获得积分10
2分钟前
漂亮板栗完成签到 ,获得积分10
2分钟前
2分钟前
kkscanl完成签到 ,获得积分10
2分钟前
leapper完成签到 ,获得积分10
2分钟前
2分钟前
Hello应助科研通管家采纳,获得10
2分钟前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(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
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
ズームレンズの光学設計に関する研究 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
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 7298107
求助须知:如何正确求助?哪些是违规求助? 8916567
关于积分的说明 18879421
捐赠科研通 6963240
什么是DOI,文献DOI怎么找? 3210641
关于科研通互助平台的介绍 2379958
邀请新用户注册赠送积分活动 2187125