Based on network pharmacology and molecular docking to predict the mechanism of Huangqi in the treatment of castration-resistant prostate cancer

Abstract

Background As a kind of traditional Chinese medicine, HQ is widely mentioned in the treatment of cancerous diseases in China, which has been proven to have a therapeutic effect on cancerous diseases, such as prostate cancer. To predict the specific mechanism of HQ in the treatment of CRPC, we will conduct preliminary verification and discussion based on a comprehensive consideration of network pharmacology and molecular docking. Methods TCMSP was used to obtain the compounds and reach the effective targets of HQ. The targets of CRPC were reached based on GeneCards database and CTD database. GO and KEGG were utilized for the analysis of overlapping targets. The software of Openbabel was used to convert the formats of ligands and reporters. In addition, molecular docking studies were performed by using the software of Autodock Vina. Result It can be seen from the database results that there were 87 active compounds (20 key active compounds) in HQ, and 33 targets were screened out for CRPC treatment. GO and KEGG pathway enrichment analyses identified 81 significant GO terms and 24 significant KEGG pathways. There is a difference in terms of the expression of core protein between cancer patients and healthy people. The expression of core protein in patients also has an impact on the life cycle. The results of molecular docking showed that the docking activity of drug molecules and core proteins was better. Conclusions It is concluded from the results of this network pharmacology and molecular docking that HQ makes a multi-target and multi-biological process, and results in the multi-channel synergistic effect on the treatment of CRPC by regulating cell apoptosis, proliferation and metastasis, which still needs further verification by experimental research.

Exploring the mechanism of ellagic acid against gastric cancer based on bioinformatics analysis and network pharmacology

“…We obtained ADME parameters of EA from the TCMSP database, OB = 43.06% and DL = 0.43, where OB represents the speed and degree of drug absorption into human circulation, which is an important indicator for evaluating drug efficacy, and DL reflects the properties of drugs with specific functional groups or the same or similar physical properties, 43 according to the recommendation of TCMSP database, OB ≥ 30% and DL ≥ 0.18 are commonly used criteria for screening effective active ingredients. Based on these two powerful parameters, we infer that EA can exert effective pharmacological activity in the body, and the structure of EA was shown in Figure 2A .…”

“…The potential targets for EAWe obtained ADME parameters of EA from the TCMSP database, OB = 43.06% and DL = 0.43, where OB represents the speed and degree of drug absorption into human circulation, which is an important indicator for evaluating drug efficacy, and DL reflects the properties of drugs with specific functional groups or the same or similar physical properties,43 according to the recommendation of TCMSP database, OB ≥ 30% and DL ≥ 0.18 are commonly used criteria for screening effective active ingredients. Based on these two powerful parameters, we infer that EA can exert effective pharmacological activity in the body, and the structure of EA was shown in Figure2A.We collected candidate targets of EA from nine databases, namely TCMSP, BATMAN-TCM, Binding DB, SwissTargetPrediction, STITCH, pharmmapper, CTD, GeneCards and SEA database, as shown in Figure 2B; the acquired targets were standardized and named through the UniProt database; and after merging and deduplication, 540 EA candidate targets were finally obtained.…”

Exploring the mechanism of 6-Methoxydihydrosanguinarine in the treatment of lung adenocarcinoma based on network pharmacology, molecular docking and experimental investigation

“…In recent decades, the integration of network-based pharmacology and computer-assisted drug design technology has gained traction in uncovering the intricate workings of drugs, emerging as a potent approach in pharmaceutical investigations [51][52][53][54][55]. Among them, network pharmacology enables the anticipation of disease targets impacted by drugs, while molecular docking facilitates the examination of drug-gene interactions.…”

Using CADD tools to inhibit the overexpressed genes FAP, FN1, and MMP1 by repurposing ginsenoside C and Rg1 as a treatment for oral cancer

“…MD simulation has given many possibilities for novel drugs and drug repurposing to be used in defense of cancer ( Yalcin-Ozkat, 2021 ). As it is widely used in Chinese medicines, Lin et al examined hydroxychloroquine (HQ) to know more about its mechanism against prostate cancer using molecular docking ( Lin et al, 2022 ).…”

“…When overexpressed, they enhance the cancer cells. Fibroblast activation protein (FAP), Fibronectin 1 (FN1), and Matrix metalloproteinase-1 (MMP1) are overexpressed genes that are associated with oral cancer prognosis (Syed et al, 2020;Zhang et al, 2022;Zhou et al, 2022). The FAP, FN1, and MMP1 proteins were obtained from the Protein Data Bank (PDB) (https://www.rcsb.org/), one of the largest databases for 3D structures (Berman et al, 2000).…”