Computational Studies on Antibody Drug Conjugates (ADCs) for Precision Oncology

抗体-药物偶联物 对接(动物) 细胞毒性T细胞 抗体 抗原 药品 自动停靠 药理学 计算生物学 癌症研究 单克隆抗体 化学 医学 生物 免疫学 生物化学 体外 生物信息学 基因 护理部
作者
Ruby Srivastava
出处
期刊:ChemistrySelect [Wiley]
卷期号:7 (34) 被引量:3
标识
DOI:10.1002/slct.202202259
摘要

Abstract After decades of technological research, the basic understanding of Antibody‐drug conjugates (ADCs) has resulted in the development of therapeutic agents for cancer patients. In this work, we have studied the mechanism of only nine FDA‐approved ADCs (Nat Rev Clin Oncol. 2021;18(6):327‐344) by computational methods, while many more ADCs are in preclinical and clinical development. The biological and Absorption, distribution, metabolism, excretion, and toxicity (ADMET) risk prediction for cytotoxic payloads is estimated to predict their bioavailability as drugs for the treatment of cancer patients. Other potential targets for the cytotoxic payloads are accessed by SwissTargetPrediction. Docking for the optimized structures of drugs and linkers are carried out by AutoDock tools. CABS‐flex 2.0 web server is used for Molecular Dynamics (MD) simulations of antigens and antibodies (IgG1, IgG4) and potential binding pockets for antibodies are searched by the PrankWeb server. HDOCK web server is used to find the docking of (Antigens‐ Antibodies‐ (linker‐payloads)) complexes. Protein‐ligand interaction profiler (PLIP) web server is used to find the noncovalent interactions in ADCs. Results indicated higher toxicity for the studied payloads, yet drug likeliness is observed for all studied cytotoxic payloads. The predicted targets for the payloads are mostly phosphodiesterase and protease electrochemical transporter. Strong Hydrogen bond Interactions have been observed for the ADCs. The cytotoxic payloads showed a specific binding location for the target antigens. Hopefully, these studies will help to improve the design patterns and facilitate the optimal allocation of ADCs for precision oncology in the future.
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
1秒前
阔达的无剑完成签到,获得积分10
2秒前
桐桐应助sszxlijin采纳,获得10
2秒前
4秒前
Ran发布了新的文献求助10
4秒前
隐形曼青应助Della采纳,获得10
5秒前
yitai完成签到,获得积分10
5秒前
jjjjj发布了新的文献求助30
6秒前
杜兰特发布了新的文献求助20
7秒前
9秒前
木心应助负责小蜜蜂采纳,获得10
9秒前
Rondab应助负责小蜜蜂采纳,获得30
9秒前
shenzhou9发布了新的文献求助10
10秒前
10秒前
11秒前
11秒前
13秒前
rrgogo发布了新的文献求助10
13秒前
13秒前
酷波er应助展希希采纳,获得10
14秒前
慕青应助xn201120采纳,获得10
15秒前
七七完成签到,获得积分10
15秒前
Della发布了新的文献求助10
16秒前
gogoyoco发布了新的文献求助10
16秒前
符小俊完成签到,获得积分10
18秒前
旷野发布了新的文献求助10
18秒前
mammer完成签到,获得积分10
19秒前
左肩微笑完成签到,获得积分10
19秒前
来来完成签到,获得积分10
21秒前
Cochrane完成签到,获得积分0
21秒前
Hey关闭了Hey文献求助
22秒前
jjjjj完成签到,获得积分20
23秒前
23秒前
8R60d8应助yitai采纳,获得10
24秒前
科研助手6应助yitai采纳,获得10
24秒前
脑洞疼应助man采纳,获得10
24秒前
来来发布了新的文献求助10
24秒前
yizhiGao应助科研通管家采纳,获得10
26秒前
思源应助科研通管家采纳,获得10
26秒前
Akim应助科研通管家采纳,获得10
26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
‘Unruly’ Children: Historical Fieldnotes and Learning Morality in a Taiwan Village (New Departures in Anthropology) 400
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
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 3989550
求助须知:如何正确求助?哪些是违规求助? 3531774
关于积分的说明 11254747
捐赠科研通 3270278
什么是DOI,文献DOI怎么找? 1804966
邀请新用户注册赠送积分活动 882125
科研通“疑难数据库(出版商)”最低求助积分说明 809176