Pan-Cancer Analysis and Drug Formulation for GPR139 and GPR142

Abstract

GPR (G protein receptor) 139 and 142 are novel foundling GPCRs (G protein-coupled receptors) in the class "A" of the GPCRs family and are suitable targets for various biological conditions. To engage these targets, validated pharmacophores and 3D QSAR (Quantitative structure-activity relationship) models are widely used because of their direct fingerprinting capability of the target and an overall accuracy. The current work initially analyzes GPR139 and GPR142 for its genomic alteration via tumor samples. Next to that, the pharmacophore is developed to scan the 3D database for such compounds that can lead to potential agonists. As a result, several compounds have been considered, showing satisfactory performance and a strong association with the target. Additionally, it is gripping to know that the obtained compounds were observed to be responsible for triggering pan-cancer. This suggests the possible role of novel GPR139 and GPR142 as the substances for initiating a physiological response to handle the condition incurred as a result of cancer.

Keywords: 3D quantitative structure-activity relationship; 7TM; GPR142; molecular modeling; pan-cancer; pharmacophore; the cancer genome atlas.

FIGURE 1

The overall workflow of the steps taken for the successful pharmacophore’s perception, 3D QSAR model development, and 3D database screening for GPR142.

FIGURE 2

Expression of GPR139 and GPR142 in pan-cancer from analyzed TCGA data. Panel (A) GPR139 expression breakdown; Panel (B) GPR139 tumor and normal expression breakdown; Panel (C) GPR142 expression study; Panel (D) GPR142 tumor and normal expression breakdown.

FIGURE 3

GPR139 and GPR142 Global modification occurrence in pan-cancer based on the TCGA data Panel (A) GPR139 variation occurrence investigation; Panel (B) GPR142 variation frequency breakdown; Panel (C) Inclusive modification occurrence study; Panel (D) Ratio of the GPR139 mutations investigation; Panel (E): Amount of GPR142 mutations breakdown. Panel (F) Amelioration rate, portraying genomic change per patient in the given samples, showing the mediation of GPR139 and GPR142 signaling in the pan-cancer. Besides, the gene signaling can be facilitated as well upon the instigation or inactivation of cell cycle control through truncating mutations. Panel (G) This board illustrates the amount of mutations uniqueness vs co-occurrence in the Genome.

FIGURE 4

Panel (A) Depicts stage plot of GPR139; Panel (B): depicts the correlation between GPR139 and GPR142 in pan-cancer; Panel (C): depicts stage plot of GPR142 and Panel (D): depicts survival analysis of GPR139 and GPR142 in pan-cancer.

FIGURE 5

Positive coefficient represented by dark blue color and Negative coefficient represented by the red color, Hydrogen bond donor (D), Hydrophobic/nonpolar (H), Electron-withdrawing (W) shown in the red cube, where R5 has a common pharmacophoric feature, responsible for the activity. A2 are in the negative coefficient and other R7, D3P4, and R5 are in the positive coefficient shown in the supplementary information (Supplementary Figure S2).

FIGURE 6

Automatically generated regression plot of 3D QSAR EC50 value and phase predicted activity, where the X-axis signifies the EC50 score and Y-axis denotes the phase predicted activity of the chemical structure.

FIGURE 7

Represents the common pharmacophore hypotheses using screened ligand and Known Compounds, where R10 has the most important common pharmacophoric feature that inhibits cancer.

FIGURE 8

Automatically generated regression plot of 3D QSAR known EC50 value and phase predicted activity, where X-axis signifies the EC50 score activity and Y-axis signifies the phase predicted activity of chemical structure.

FIGURE 9

Represents the common pharmacophore hypotheses using the docking score of screened ligands, where R8 has the most important common pharmacophoric feature that inhibits cancer.