Affiliations 

  • 1 Computational Intelligence and Bioinformatics Lab, Department of Computer Science, Jamia Millia Islamia, New Delhi 110025, India. Electronic address: Shaban184343@st.jmi.ac.in
  • 2 Computational Intelligence and Bioinformatics Lab, Department of Computer Science, Jamia Millia Islamia, New Delhi 110025, India; Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi 110067, India. Electronic address: Kushagra@ucsiuniversity.edu.my
  • 3 Faculty of Pharmaceutical Sciences, UCSI University, Kuala Lumpur 56000, Malaysia. Electronic address: Nagmi2300973@st.jmi.ac.in
  • 4 Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi 110067, India. Electronic address: Dinesh@icgeb.res.in
  • 5 Computational Intelligence and Bioinformatics Lab, Department of Computer Science, Jamia Millia Islamia, New Delhi 110025, India. Electronic address: Kraza@jmi.ac.in
Int J Biol Macromol, 2024 Sep;276(Pt 1):133872.
PMID: 39019378 DOI: 10.1016/j.ijbiomac.2024.133872

Abstract

Lung Cancer (LC) is among the most death-causing cancers, has caused the most destruction and is a gender-neutral cancer, and WHO has kept this cancer on its priority list to find the cure. We have used high-throughput virtual screening, standard precision docking, and extra precise docking for extensive screening of Drug Bank compounds, and the uniqueness of this study is that it considers multiple protein targets of prognosis and metastasis of LC. The docking and MM\GBSA calculation scores for the Tiaprofenic acid (DB01600) against all ten proteins range from -8.422 to -5.727 kcal/mol and - 47.43 to -25.72 kcal/mol, respectively. Also, molecular fingerprinting helped us to understand the interaction pattern of Tiaprofenic acid among all the proteins. Further, we extended our analysis to the molecular dynamic simulation in a neutralised SPC water medium for 100 ns. We analysed the root mean square deviation, fluctuations, and simulative interactions among the protein, ligand, water molecules, and protein-ligand complexes. Most complexes have shown a deviation of <2 Å as cumulative understanding. Also, the fluctuations were lesser, and only a few residues showed the fluctuation with a huge web of interaction between the protein and ligand, providing an edge that supports that the protein and ligand complexes were stable. In the MTT-based Cell Viability Assay, Tiaprofenic Acid exhibited concentration-dependent anti-cancer efficacy against A549 lung cancer cells, significantly reducing viability at 100 μg/mL. These findings highlight its potential as a therapeutic candidate, urging further exploration into the underlying molecular mechanisms for lung cancer treatment.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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