The QSAR-search of effective agents towards coronaviruses applying the Monte Carlo method.
SAR QSAR Environ Res
; 32(9): 689-698, 2021 Sep.
Article
in English
| MEDLINE | ID: covidwho-1322544
ABSTRACT
Perhaps there is some similarity between the coronavirus of 2017 and the COVID-19. Consequently, a predictive model for the antiviral activity for the Middle East respiratory syndrome coronavirus (MERS-CoV, 2017) could be useful for designing the strategy and tactics in the struggle with coronaviruses in general and with COVID 19 in particular. Quantitative structure-activity relationships (QSARs) of inhibitory activity to MERS-CoV were developed. The index of ideality of correlation was applied to build up these models for the antiviral activity. The statistical quality of the best model is quite good (r2 = 0.84). A mechanistic interpretation of these models based on the molecular features with strong positive (i.e. promoters for endpoint increase) and strong negative (i.e. promoters for endpoint decrease) influence on the inhibitory activity is suggested. A collection of possible biologically active compounds, constructed using data on the above molecular features which are statistically reliable promoters of increase or decrease of the activity, is presented.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Antiviral Agents
/
Monte Carlo Method
/
Quantitative Structure-Activity Relationship
/
SARS-CoV-2
/
COVID-19 Drug Treatment
Type of study:
Experimental Studies
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
SAR QSAR Environ Res
Journal subject:
Environmental Health
Year:
2021
Document Type:
Article
Affiliation country:
1062936X.2021.1952649
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