scholarly journals Identification of a disruptor of the MDM2-p53 protein–protein interaction facilitated by high-throughput in silico docking

2009 ◽  
Vol 19 (14) ◽  
pp. 3756-3759 ◽  
Author(s):  
Harshani R. Lawrence ◽  
Zhenyu Li ◽  
M.L. Richard Yip ◽  
Shen-Shu Sung ◽  
Nicholas J. Lawrence ◽  
...  
Keyword(s):  
High Throughput ◽  
Protein Interaction ◽  
In Silico ◽  
P53 Protein ◽  
In Silico Docking ◽  
Protein Protein Interaction

scholarly journals Design and In Silico Study of the Novel Small Molecular MDM2 Inhibitors

2020 ◽  
Vol 11 (1) ◽  
pp. 8052-8064
Keyword(s):  
Protein Interaction ◽  
In Silico ◽  
P53 Protein ◽  
Docking Study ◽  
Rational Approach ◽  
The Novel ◽  
Molecular Docking Study ◽  
Protein Protein Interaction ◽  
In Silico Study ◽  
Cancer Agent

Protein-protein Interaction (PPIs) plays a central role in many diseased conditions. Therefore to target and to modulate PPIs is an efficient approach for the disease treatment. Cancer is also arising because of Protein-protein interaction. In cancer, the tumor suppressor p53 protein got inhibited by the MDM2 protein. p53 protein regulates the cell cycle and apoptosis. Interaction between the p53-MDM2 proteins is responsible for the inhibition of the p53 function. By this interaction, MDM2 degrades and inhibits the p53 protein. Hence, to target and inhibit the p53-MDM2 interaction for the treatment of cancer is the rational approach. By targeting this interaction with the drugs, we can selectively kill the cancer cells over the normal cells. Recently, p53-MDM2 interaction inhibitor drugs have been reported by many researchers and pharmaceutical companies. And several drugs entered into the clinical trials. In this study, a novel 1,2,4-triazole based molecules were designed as MDM2 inhibitors and performed their in-silico study. We designed the novel compound 01 and Lead 1a. In this work, In silico study of the Lead 1a and reference compounds (Nutlin 3a, RG7112) was carried out. The molecular docking study of the Novel 1,2,4-triazole based lead 1a and reference compounds was carried out. The docking score of the Lead 1a found to be better than Nutlin 3a and close to RG7112. The various possible conformations and binding affinity values were also determined by the docking study. These results indicate the Lead 1a as a potential MDM2 inhibitor and anti-cancer agent.

scholarly journals Development of a Novel High-Throughput Screen and Identification of Small-Molecule Inhibitors of the Gα–RGS17 Protein–Protein Interaction Using AlphaScreen

2011 ◽  
Vol 16 (8) ◽  
pp. 869-877 ◽  
Author(s):  
Duncan I. Mackie ◽  
David L. Roman
Keyword(s):  
Small Molecule ◽  
High Throughput ◽  
Protein Interaction ◽  
High Throughput Screening ◽  
Drug Targets ◽  
Screening Method ◽  
Fold Increase ◽  
Rgs Proteins ◽  
High Throughput Screen ◽  
Protein Protein Interaction

In this study, the authors used AlphaScreen technology to develop a high-throughput screening method for interrogating small-molecule libraries for inhibitors of the Gαo–RGS17 interaction. RGS17 is implicated in the growth, proliferation, metastasis, and the migration of prostate and lung cancers. RGS17 is upregulated in lung and prostate tumors up to a 13-fold increase over patient-matched normal tissues. Studies show RGS17 knockdown inhibits colony formation and decreases tumorigenesis in nude mice. The screen in this study uses a measurement of the Gαo–RGS17 protein–protein interaction, with an excellent Z score exceeding 0.73, a signal-to-noise ratio >70, and a screening time of 1100 compounds per hour. The authors screened the NCI Diversity Set II and determined 35 initial hits, of which 16 were confirmed after screening against controls. The 16 compounds exhibited IC50 <10 µM in dose–response experiments. Four exhibited IC50 values <6 µM while inhibiting the Gαo–RGS17 interaction >50% when compared to a biotinylated glutathione-S-transferase control. This report describes the first high-throughput screen for RGS17 inhibitors, as well as a novel paradigm adaptable to many other RGS proteins, which are emerging as attractive drug targets for modulating G-protein-coupled receptor signaling.

Structure-Based Design of Potent and Orally Active Isoindolinone Inhibitors of MDM2-p53 Protein–Protein Interaction

2021 ◽  
Author(s):  
Gianni Chessari ◽  
Ian R. Hardcastle ◽  
Jong Sook Ahn ◽  
Burcu Anil ◽  
Elizabeth Anscombe ◽  
...  
Keyword(s):  
Protein Interaction ◽  
P53 Protein ◽  
Protein Protein Interaction ◽  
Orally Active

MDM2-p53 protein–protein interaction inhibitors: A-ring substituted isoindolinones

2011 ◽  
Author(s):  
Anna F. Watson ◽  
Junfeng Liu ◽  
Karim Bennaceur ◽  
Catherine J. Drummond ◽  
Jane A. Endicott ◽  
...  
Keyword(s):  
Protein Interaction ◽  
P53 Protein ◽  
Protein Protein Interaction

scholarly journals An Application of Fit Quality to Screen MDM2/p53 Protein-Protein Interaction Inhibitors

Molecules ◽  
2018 ◽  
Vol 23 (12) ◽  
pp. 3174 ◽  
Author(s):  
Xin Xue ◽  
Gang Bao ◽  
Hai-Qing Zhang ◽  
Ning-Yi Zhao ◽  
Yuan Sun ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Drug Target ◽  
P53 Protein ◽  
Pharmacophore Model ◽  
Cellular Level ◽  
Complex Structures ◽  
Ligand Complex ◽  
Null Cell ◽  
Protein Protein Interaction ◽  
First Time

: The judicious application of ligand or binding efficiency (LE) metrics, which quantify the molecular properties required to obtain binding affinity for a drug target, is gaining traction in the selection and optimization of fragments, hits and leads. Here we report for the first time the use of LE based metric, fit quality (FQ), in virtual screening (VS) of MDM2/p53 protein-protein interaction inhibitors (PPIIs). Firstly, a Receptor-Ligand pharmacophore model was constructed on multiple MDM2/ligand complex structures to screen the library. The enrichment factor (EF) for screening was calculated based on a decoy set to define the screening threshold. Finally, 1% of the library, 335 compounds, were screened and re-filtered with the FQ metric. According to the statistical results of FQ vs activity of 156 MDM2/p53 PPIIs extracted from literatures, the cut-off was defined as FQ = 0.8. After the second round of VS, six compounds with the FQ > 0.8 were picked out for assessing their antitumor activity. At the cellular level, the six hits exhibited a good selectivity (larger than 3) against HepG2 (wt-p53) vs Hep3B (p53 null) cell lines. On the further study, the six hits exhibited an acceptable affinity (range of Ki from 102 to 103 nM) to MDM2 when comparing to Nutlin-3a. Based on our work, FQ based VS strategy could be applied to discover other PPIIs.

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