An online repository of solvation thermodynamic and structural maps of SARS-CoV-2 targets.
J Comput Aided Mol Des
; 34(12): 1219-1228, 2020 12.
Article
in English
| MEDLINE | ID: covidwho-754411
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
ABSTRACT
SARS-CoV-2 recently jumped species and rapidly spread via human-to-human transmission to cause a global outbreak of COVID-19. The lack of effective vaccine combined with the severity of the disease necessitates attempts to develop small molecule drugs to combat the virus. COVID19_GIST_HSA is a freely available online repository to provide solvation thermodynamic maps of COVID-19-related protein small molecule drug targets. Grid inhomogeneous solvation theory maps were generated using AmberTools cpptraj-GIST, 3D reference interaction site model maps were created with AmberTools rism3d.snglpnt and hydration site analysis maps were created using SSTMap code. The resultant data can be applied to drug design efforts scoring solvent displacement for docking, rational lead modification, prioritization of ligand- and protein- based pharmacophore elements, and creation of water-based pharmacophores. Herein, we demonstrate the use of the solvation thermodynamic mapping data. It is hoped that this freely provided data will aid in small molecule drug discovery efforts to defeat SARS-CoV-2.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Antiviral Agents
/
Pneumonia, Viral
/
Thermodynamics
/
Drug Design
/
Viral Nonstructural Proteins
/
Coronavirus Infections
/
Drug Evaluation, Preclinical
/
Molecular Dynamics Simulation
/
Molecular Targeted Therapy
/
Pandemics
Type of study:
Prognostic study
Topics:
Traditional medicine
/
Vaccines
Limits:
Humans
Language:
English
Journal:
J Comput Aided Mol Des
Journal subject:
Molecular Biology
/
Biomedical Engineering
Year:
2020
Document Type:
Article
Affiliation country:
S10822-020-00341-x
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