Inferred edges come from two machine sources: sweeps of open repository
metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is
labelled with the one it came from. Neither is a complete citation index — absence here is not
evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
Free energy calculation methods: A theoretical and empirical comparison of numerical errors and a new method qualitative estimates of free energy changes
Accurate and Reliable Prediction of Relative Ligand Binding Potency in Prospective Drug Discovery by Way of a Modern Free-Energy Calculation Protocol and Force Field
Theoretical Efficacy of Possible Inhibitors of SARS-CoV-2 Cell Recognition and Their Effect on Viral Dynamics in Different Cell Types: Computational Biology and Prediction from in Vitro Experimental Data
Computational screening of FDA approved drugs of fungal origin that may interfere with SARS-CoV-2 spike protein activation, viral RNA replication, and post‐translational modification: a multiple target approach
Identification of lead compounds from large natural product library targeting 3C-like protease of SARS-CoV-2 using E-pharmacophore modelling, QSAR and molecular dynamics simulation
Combining virtual screening with cis-/trans-cleavage enzymatic assays effectively reveals broad-spectrum inhibitors that target the main proteases of SARS-CoV-2 and MERS-CoV
D3CARP: a comprehensive platform with multiple-conformation based docking, ligand similarity search and deep learning approaches for target prediction and virtual screening
Fast Prediction of Binding Affinities of SARS-CoV-2 Spike Protein and Its Mutants with Antibodies through Intermolecular Interaction Modeling-Based Machine Learning
Biophysical Analysis of Potential Inhibitors of SARS-CoV-2 Cell Recognition and Their Effect on Viral Dynamics in Different Cell Types: A Computational Prediction from In Vitro Experimental Data
The dolabellane diterpenes as potential inhibitors of the SARS-CoV-2 main protease: molecular insight of the inhibitory mechanism through computational studies
Reckoning γ-Glutamyl-S-allylcysteine as a potential main protease (mpro) inhibitor of novel SARS-CoV-2 virus identified using docking and molecular dynamics simulation
Enantiomers of Chloroquine and Hydroxychloroquine Exhibit Different Activities Against SARS-CoV-2 in vitro , Evidencing S -Hydroxychloroquine as a Potentially Superior Drug for COVID-19
Neutrophil elastase inhibitor (sivelestat) may be a promising therapeutic option for management of acute lung injury/acute respiratory distress syndrome or disseminated intravascular coagulation in COVID‐19
Characterisation of Recombinant 3CL Protease from SARS-CoV-2 Produced in E. coli BL21 (DE3) for Screening Anti-Covid Drug Candidates using Rhodamine 110-Synthetic Peptide Conjugate as A Substrate
Unlocking Therapeutic Potential: Identifying Small Molecule Inhibitors for Sars-Cov-2 Variants' Main Protease (MPRO) Through Molecular Docking Analysis
A Molecular Modeling and Molecular Dynamics Simulations Investigation of the Potential Therapeutic Applications of Main Protease Inhibitors for SARS-CoV-2
Exploring structurally diverse plant secondary metabolites as a potential source of drug targeting different molecular mechanisms of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pathogenesis: An in silico approach
Microsecond molecular dynamics suggest that a non-synonymous mutation, frequently observed in patients with mild symptoms in Tokyo, alters dynamics of the SARS-CoV-2 main protease
Hydroxychloroquine (HCQ) Exhibits Better Binding to the Main Protease (Mpro) Compared to Spike Protein (S protein) of SARS-CoV-2: An In-silico Analysis
A Benchmark of Popular Free Energy Approaches Revealing the Inhibitors Binding to SARS-CoV2 Mpro
showing the first 200 of 252
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.