Conv. Plasma
Nigella Sativa

Home COVID-19 treatment researchSelect treatment..Select..
Melatonin Meta
Metformin Meta
Azvudine Meta
Bromhexine Meta Molnupiravir Meta
Budesonide Meta
Colchicine Meta
Conv. Plasma Meta Nigella Sativa Meta
Curcumin Meta Nitazoxanide Meta
Famotidine Meta Paxlovid Meta
Favipiravir Meta Quercetin Meta
Fluvoxamine Meta Remdesivir Meta
Hydroxychlor.. Meta Thermotherapy Meta
Ivermectin Meta

Canertinib for COVID-19

Canertinib has been reported as potentially beneficial for treatment of COVID-19. We have not reviewed these studies. See all other treatments.
Taguchi et al., A New Advanced In Silico Drug Discovery Method for Novel Coronavirus (SARS-CoV-2) with Tensor Decomposition-Based Unsupervised Feature Extraction, MDPI AG, doi:10.20944/preprints202004.0524.v1
Background: COVID-19 is a critical pandemic that has affected human communities worldwide. Although it is urgent to rapidly develop effective drugs, large number of candidate drug compounds may be useful for treating COVID-19, and evaluation of these drugs is time-consuming and costly. Thus, screening to identify potentially effective drugs prior to experimental validation is necessary. Method: In this study, we applied the recently proposed method tensor decomposition (TD)-based unsupervised feature extraction (FE) to gene expression profiles of multiple lung cancer cell lines infected with severe acute respiratory syndrome coronavirus 2. We identified drug candidate compounds that significantly altered the expression of the 163 genes selected by TD-based unsupervised FE. Results: Numerous drugs were successfully screened, including many known antiviral drug compounds. Conclusions: The drugs screened using our strategy may be effective candidates for treating patients with COVID-19.
Tsuji, M., Virtual Screening and Quantum Chemistry Analysis for SARS-CoV-2 RNA-Dependent RNA Polymerase Using the ChEMBL Database: Reproduction of the Remdesivir-RTP and Favipiravir-RTP Binding Modes Obtained from Cryo-EM Experiments with High Binding Affinity, International Journal of Molecular Sciences, doi:10.3390/ijms231911009
The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified as the pathogenic cause of coronavirus disease 2019 (COVID-19). The RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 is a potential target for the treatment of COVID-19. An RdRp complex:dsRNA structure suitable for docking simulations was prepared using a cryo-electron microscopy (cryo-EM) structure (PDB ID: 7AAP; resolution, 2.60 Å) that was reported recently. Structural refinement was performed using energy calculations. Structure-based virtual screening was performed using the ChEMBL database. Through 1,838,257 screenings, 249 drugs (37 approved, 93 clinical, and 119 preclinical drugs) were predicted to exhibit a high binding affinity for the RdRp complex:dsRNA. Nine nucleoside triphosphate analogs with anti-viral activity were included among these hit drugs, and among them, remdesivir-ribonucleoside triphosphate and favipiravir-ribonucleoside triphosphate adopted a similar docking mode as that observed in the cryo-EM structure. Additional docking simulations for the predicted compounds with high binding affinity for the RdRp complex:dsRNA suggested that 184 bioactive compounds could be anti-SARS-CoV-2 drug candidates. The hit bioactive compounds mainly consisted of a typical noncovalent major groove binder for dsRNA. Three-layer ONIOM (MP2/6-31G:AM1:AMBER) geometry optimization calculations and frequency analyses (MP2/6-31G:AMBER) were performed to estimate the binding free energy of a representative bioactive compound obtained from the docking simulation, and the fragment molecular orbital calculation at the MP2/6-31G level of theory was subsequently performed for analyzing the detailed interactions. The procedure used in this study represents a possible strategy for discovering anti-SARS-CoV-2 drugs from drug libraries that could significantly shorten the clinical development period for drug repositioning.
Please send us corrections, updates, or comments. c19early involves the extraction of 100,000+ datapoints from thousands of papers. Community updates help ensure high accuracy. Treatments and other interventions are complementary. All practical, effective, and safe means should be used based on risk/benefit analysis. No treatment or intervention is 100% available and effective for all current and future variants. We do not provide medical advice. Before taking any medication, consult a qualified physician who can provide personalized advice and details of risks and benefits based on your medical history and situation. FLCCC and WCH provide treatment protocols.
  or use drag and drop   
Thanks for your feedback! Please search before submitting papers and note that studies are listed under the date they were first available, which may be the date of an earlier preprint.