Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText.
Kick-your-searchterm to multiple Engines kick-your-query now !>
A dictionary by aggregated review articles of nephrology, medicine and the life sciences
Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

suck abstract from ncbi


suck pdf from google scholar
unlimited free pdf from europmc32643529    free
PDF from PMC    free
html from PMC    free
PDF vom PMID32643529  :  Publisher

suck abstract from ncbi

Nephropedia Template TP Text

Twit Text FOAVip

Twit Text #

English Wikipedia

  • Natural-like products as potential SARS-CoV-2 M(pro) inhibitors: in-silico drug discovery #MMPMID32643529
  • Ibrahim MAA; Abdeljawaad KAA; Abdelrahman AHM; Hegazy MF
  • J Biomol Struct Dyn 2021[Sep]; 39 (15): 5722-5734 PMID32643529show ga
  • In December 2019, a COVID-19 epidemic was discovered in Wuhan, China, and since has disseminated around the world impacting human health for millions. Herein, in-silico drug discovery approaches have been utilized to identify potential natural products (NPs) as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) main protease (M(pro)) inhibitors. The MolPort database that contains over 100,000 NPs was screened and filtered using molecular docking techniques. Based on calculated docking scores, the top 5,000 NPs/natural-like products (NLPs) were selected and subjected to molecular dynamics (MD) simulations followed by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations. Combined 50 ns MD simulations and MM-GBSA calculations revealed nine potent NLPs with binding affinities (DeltaGbinding) > -48.0 kcal/mol. Interestingly, among the identified NLPs, four bis([1,3]dioxolo)pyran-5-carboxamide derivatives showed DeltaGbinding > -56.0 kcal/mol, forming essential short hydrogen bonds with HIS163 and GLY143 amino acids via dioxolane oxygen atoms. Structural and energetic analyses over 50 ns MD simulation demonstrated NLP-M(pro) complex stability. Drug-likeness predictions revealed the prospects of the identified NLPs as potential drug candidates. The findings are expected to provide a novel contribution to the field of COVID-19 drug discovery.Communicated by Ramaswamy H. Sarma.
  • |*COVID-19[MESH]
  • |*SARS-CoV-2[MESH]
  • |Drug Discovery[MESH]
  • |Humans[MESH]
  • |Molecular Docking Simulation[MESH]
  • |Molecular Dynamics Simulation[MESH]
  • |Protease Inhibitors[MESH]

  • DeepDyve
  • Pubget Overpricing
  • suck abstract from ncbi

    5722 15.39 2021