An overview of molecular hybrids in drug discovery
G Bérubé - Expert opinion on drug discovery, 2016 - Taylor & Francis
Introduction: The hybridization of biologically active molecules is a powerful tool for drug
discovery used to target a variety of diseases. It offers the prospect of better drugs for the …
discovery used to target a variety of diseases. It offers the prospect of better drugs for the …
iANP-EC: identifying anticancer natural products using ensemble learning incorporated with evolutionary computation
L Nguyen, TH Nguyen Vo, QH Trinh… - Journal of Chemical …, 2022 - ACS Publications
Cancer is one of the most deadly diseases that annually kills millions of people worldwide.
The investigation on anticancer medicines has never ceased to seek better and more …
The investigation on anticancer medicines has never ceased to seek better and more …
Multiparametric MRI‐based radiomics approaches for preoperative prediction of EGFR mutation status in spinal bone metastases in patients with lung …
X Jiang, M Ren, X Shuang, H Yang… - Journal of Magnetic …, 2021 - Wiley Online Library
Background Preoperative prediction of epidermal growth factor receptor (EGFR) mutation
status in patients with spinal bone metastases (SBM) from primary lung adenocarcinoma is …
status in patients with spinal bone metastases (SBM) from primary lung adenocarcinoma is …
QSAR based model for discriminating EGFR inhibitors and non-inhibitors using Random forest
Abstract Background Epidermal Growth Factor Receptor (EGFR) is a well-characterized
cancer drug target. In the past, several QSAR models have been developed for predicting …
cancer drug target. In the past, several QSAR models have been developed for predicting …
Speeding up early drug discovery in antiviral research: a fragment-based in silico approach for the design of virtual anti-hepatitis C leads
A Speck-Planche… - ACS Combinatorial …, 2017 - ACS Publications
Hepatitis C constitutes an unresolved global health problem. This infectious disease is
caused by the hepatotropic hepatitis C virus (HCV), and it can lead to the occurrence of life …
caused by the hepatotropic hepatitis C virus (HCV), and it can lead to the occurrence of life …
AVC pred: an integrated web server for prediction and design of antiviral compounds
Viral infections constantly jeopardize the global public health due to lack of effective antiviral
therapeutics. Therefore, there is an imperative need to speed up the drug discovery process …
therapeutics. Therefore, there is an imperative need to speed up the drug discovery process …
GraphEGFR: Multi‐task and transfer learning based on molecular graph attention mechanism and fingerprints improving inhibitor bioactivity prediction for EGFR family …
B Boonyarit, N Yamprasert… - Journal of …, 2024 - Wiley Online Library
The proteins within the human epidermal growth factor receptor (EGFR) family, members of
the tyrosine kinase receptor family, play a pivotal role in the molecular mechanisms driving …
the tyrosine kinase receptor family, play a pivotal role in the molecular mechanisms driving …
Structure guided design and binding analysis of EGFR inhibiting analogues of erlotinib and AEE788 using ensemble docking, molecular dynamics and MM-GBSA
VK Sharma, PP Nandekar, A Sangamwar… - RSC …, 2016 - pubs.rsc.org
Epidermal growth factor receptor (EGFR) is an important validated drug target for cancer
therapy. Some therapeutic agents targeting EGFR have been developed, however these are …
therapy. Some therapeutic agents targeting EGFR have been developed, however these are …
Computer-aided prediction of inhibitors against STAT3 for managing COVID-19 associated cytokine storm
Background Proinflammatory cytokines are correlated with the severity of disease in patients
with COVID-19. IL6-mediated activation of STAT3 proliferates proinflammatory responses …
with COVID-19. IL6-mediated activation of STAT3 proliferates proinflammatory responses …
Prediction of anticancer molecules using hybrid model developed on molecules screened against NCI-60 cancer cell lines
Background In past, numerous quantitative structure-activity relationship (QSAR) based
models have been developed for predicting anticancer activity for a specific class of …
models have been developed for predicting anticancer activity for a specific class of …