In Silico Study to Estimate the Impact of Pollutants Resulted from Generators Emissions on ACE2 Receptor in the Respiratory System

ABSTRACT Pollution by greenhouse gases is a serious problem nowadays, especially those who are emitted by diesel generators. The angiotensin-converting enzyme-2 (ACE2) is a common enzyme with active receptor included on the alveoli surface in mammalians. This study used the software of molecular docking tools for turning out the interaction between ACE-2 receptor and generators emission gases and particulate matter, which are other important trace components in air. Molecular docking has been performed for many gases which might bind to chain (A) in ACE-2 receptor. Tools included the version 0.8 of the docking program (PyRx 2021) followed by analysing the binding by the program (discovery studio visualizer 2021) to show the amino acids and chemical bonds among gases and ACE-2 respecter. Results showed that the highest affinity of binding was the highest (- 9.9 kcal/ mol) of PM 2.5 to ACE-2 receptor, while the lowest was (- 0.7 kcal/ mol) of H2S to the same target. For the other gaseous pollutants the affinity to be docked with ACE-2 receptors fluctuated around (- 9 kcal/ mol) till less than (-2 kcal/ mol) with different bond types. In unexpected way, neither CO2 and CO nor CH4 recorded affinity or binding degrees towards ACE-2 receptor. In short, the most dangerous gaseous emissions of generators to human alveoli were PM molecules among the emissions of diesel generators.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-17
DOI
https://doi.org/10.5281/zenodo.13936049
Primary Topic
Hormonal and reproductive studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

In Silico Study to Estimate the Impact of Pollutants Resulted from Generators Emissions on ACE2 Receptor in the Respiratory System

Zenodo (CERN European Organization for Nuclear Research)
Hormonal and reproductive studies
article

In Silico Study to Estimate the Impact of Pollutants Resulted from Generators Emissions on ACE2 Receptor in the Respiratory System

article en

Abstract

ABSTRACT Pollution by greenhouse gases is a serious problem nowadays, especially those who are emitted by diesel generators. The angiotensin-converting enzyme-2 (ACE2) is a common enzyme with active receptor included on the alveoli surface in mammalians. This study used the software of molecular docking tools for turning out the interaction between ACE-2 receptor and generators emission gases and particulate matter, which are other important trace components in air. Molecular docking has been performed for many gases which might bind to chain (A) in ACE-2 receptor. Tools included the version 0.8 of the docking program (PyRx 2021) followed by analysing the binding by the program (discovery studio visualizer 2021) to show the amino acids and chemical bonds among gases and ACE-2 respecter. Results showed that the highest affinity of binding was the highest (- 9.9 kcal/ mol) of PM 2.5 to ACE-2 receptor, while the lowest was (- 0.7 kcal/ mol) of H2S to the same target. For the other gaseous pollutants the affinity to be docked with ACE-2 receptors fluctuated around (- 9 kcal/ mol) till less than (-2 kcal/ mol) with different bond types. In unexpected way, neither CO2 and CO nor CH4 recorded affinity or binding degrees towards ACE-2 receptor. In short, the most dangerous gaseous emissions of generators to human alveoli were PM molecules among the emissions of diesel generators.

Zenodo (CERN European Organization for Nuclear Research)
Ministry of Higher Education and Scientific Research (IQ), Ministry of Higher Education and Scientific Research (AE)
Openalex Percentile: Top 51%
Hormonal and reproductive studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.