Structure-based assessment and druggability classification of protein–protein interaction sites

作者
Lara Alzyoud,Richard A. Bryce,Mohammad Al Sorkhy,Noor Atatreh,Mohammad A. Ghattas
出处
期刊:Scientific Reports [Nature Portfolio]
卷期号:12 (1): 7975-7975 被引量:48
标识
DOI:10.1038/s41598-022-12105-8
摘要

The featureless interface formed by protein-protein interactions (PPIs) is notorious for being considered a difficult and poorly druggable target. However, recent advances have shown PPIs to be druggable, with the discovery of potent inhibitors and stabilizers, some of which are currently being clinically tested and approved for medical use. In this study, we assess the druggability of 12 commonly targeted PPIs using the computational tool, SiteMap. After evaluating 320 crystal structures, we find that the PPI binding sites have a wide range of druggability scores. This can be attributed to the unique structural and physiochemical features that influence their ligand binding and concomitantly, their druggability predictions. We then use these features to propose a specific classification system suitable for assessing PPI targets based on their druggability scores and measured binding-affinity. Interestingly, this system was able to distinguish between different PPIs and correctly categorize them into four classes (i.e. very druggable, druggable, moderately druggable, and difficult). We also studied the effects of protein flexibility on the computed druggability scores and found that protein conformational changes accompanying ligand binding in ligand-bound structures result in higher protein druggability scores due to more favorable structural features. Finally, the drug-likeness of many published PPI inhibitors was studied where it was found that the vast majority of the 221 ligands considered here, including orally tested/marketed drugs, violate the currently acceptable limits of compound size and hydrophobicity parameters. This outcome, combined with the lack of correlation observed between druggability and drug-likeness, reinforces the need to redefine drug-likeness for PPI drugs. This work proposes a PPI-specific classification scheme that will assist researchers in assessing the druggability and identifying inhibitors of the PPI interface.

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
zoey发布了新的文献求助10
刚刚
白夜发布了新的文献求助10
刚刚
1秒前
1秒前
童梦发布了新的文献求助10
1秒前
15发布了新的文献求助30
1秒前
Ava应助拖鞋采纳,获得10
2秒前
脑洞疼应助PGtwo采纳,获得10
2秒前
2秒前
2秒前
3秒前
liming应助Mikami采纳,获得30
3秒前
可靠的友桃关注了科研通微信公众号
3秒前
3秒前
3秒前
顾顾发布了新的文献求助10
4秒前
无辜澜发布了新的文献求助10
4秒前
4秒前
852应助雪季语采纳,获得10
4秒前
浅夏发布了新的文献求助10
4秒前
claud发布了新的文献求助10
4秒前
ffyz完成签到,获得积分10
4秒前
5秒前
今后应助周周采纳,获得10
5秒前
Yelanjiao发布了新的文献求助10
5秒前
CipherSage应助ff采纳,获得10
5秒前
6秒前
Answer0928发布了新的文献求助10
6秒前
6秒前
汉堡包应助carbon采纳,获得10
6秒前
tiana发布了新的文献求助30
6秒前
6秒前
大模型应助梦想里采纳,获得20
7秒前
7秒前
7秒前
9秒前
失眠翠芙应助Eujay采纳,获得10
9秒前
尼仲星完成签到 ,获得积分10
9秒前
jiabaoyu发布了新的文献求助10
9秒前
9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
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Governing Growth: Us Industrial Policy from Hamilton to Trump 500
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
Synthesis of P-Chiral Phosphine Ligands and Their Applications in Asymmetric Catalysis 400
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 7623830
求助须知:如何正确求助?哪些是违规求助? 9198995
关于积分的说明 19721338
捐赠科研通 7195091
什么是DOI,文献DOI怎么找? 3273410
关于科研通互助平台的介绍 2435560
邀请新用户注册赠送积分活动 2269029