Molecular Docking: A Computational Approach to Predict Protein-Ligand Interactions and Accelerating Drug Discovery

Statins are widely prescribed cholesterol-lowering medications that inhibit HMG- CoA reductase. This study employed molecular docking simulations to investigate the binding modes and energies of Atrovastatin and Fluvastatin to various protein targets. This study contributes to the understanding of statin- protein interactions and may aid in the development of novel statin-based therapeutics. The results revealed varying degrees of binding affinity, with Atrovastatin exhibiting stronger binding energies. Analysis of the docking poses and interaction energies provided valuable insights into the structure- activity relationships of these compounds..

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-05
DOI
https://doi.org/10.5281/zenodo.15340579
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Molecular Docking: A Computational Approach to Predict Protein-Ligand Interactions and Accelerating Drug Discovery

Zenodo (CERN European Organization for Nuclear Research)
Single-cell and spatial transcriptomics
article

Molecular Docking: A Computational Approach to Predict Protein-Ligand Interactions and Accelerating Drug Discovery

article en

Abstract

Statins are widely prescribed cholesterol-lowering medications that inhibit HMG- CoA reductase. This study employed molecular docking simulations to investigate the binding modes and energies of Atrovastatin and Fluvastatin to various protein targets. This study contributes to the understanding of statin- protein interactions and may aid in the development of novel statin-based therapeutics. The results revealed varying degrees of binding affinity, with Atrovastatin exhibiting stronger binding energies. Analysis of the docking poses and interaction energies provided valuable insights into the structure- activity relationships of these compounds..

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 53%
Single-cell and spatial transcriptomics
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.

Molecular Docking: A Computational Approach to Predict Protein-Ligand Interactions and Accelerating Drug Discovery · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS