Computer-aided drug discovery strategies for novel therapeutics for prostate cancer leveraging next-generating sequencing data DOI
Weijie Zhang, R. Stephanie Huang

Expert Opinion on Drug Discovery, Journal Year: 2024, Volume and Issue: 19(7), P. 841 - 853

Published: June 11, 2024

Introduction Prostate cancer (PC) is the most common malignancy and accounts for a significant proportion of deaths among men. Although initial therapy success can often be observed in patients diagnosed with localized PC, many eventually develop disease recurrence metastasis. Without effective treatments, aggressive PC display very poor survival. To curb current high mortality rate, investigations have been carried out to identify efficacious therapeutics. Compared de novo drug designs, computational methods widely employed offer actionable predictions fast cost-efficient way. Particularly, powered by an increasing availability next-generation sequencing molecular profiles from patients, computer-aided approaches tailored screen candidate drugs.

Language: Английский

Exploring the interaction between immune cells in the prostate cancer microenvironment combining weighted correlation gene network analysis and single-cell sequencing: An integrated bioinformatics analysis DOI Creative Commons
Danial Hashemi Karoii,

Sobhan Bavandi,

Melika Djamali

et al.

Discover Oncology, Journal Year: 2024, Volume and Issue: 15(1)

Published: Sept. 30, 2024

Language: Английский

Citations

3
Oxidative stress as a catalyst in prostate cancer progression: unraveling molecular mechanisms and exploring therapeutic interventions DOI Creative Commons
Yawen Song,

Zheng Hou,

Lingqun Zhu

et al.

Discover Oncology, Journal Year: 2025, Volume and Issue: 16(1)

Published: April 3, 2025

Language: Английский

Citations

0
Computer-aided drug discovery strategies for novel therapeutics for prostate cancer leveraging next-generating sequencing data DOI
Weijie Zhang, R. Stephanie Huang

Expert Opinion on Drug Discovery, Journal Year: 2024, Volume and Issue: 19(7), P. 841 - 853

Published: June 11, 2024

Introduction Prostate cancer (PC) is the most common malignancy and accounts for a significant proportion of deaths among men. Although initial therapy success can often be observed in patients diagnosed with localized PC, many eventually develop disease recurrence metastasis. Without effective treatments, aggressive PC display very poor survival. To curb current high mortality rate, investigations have been carried out to identify efficacious therapeutics. Compared de novo drug designs, computational methods widely employed offer actionable predictions fast cost-efficient way. Particularly, powered by an increasing availability next-generation sequencing molecular profiles from patients, computer-aided approaches tailored screen candidate drugs.

Language: Английский

Citations

2