TY  - JOUR
T1  - COMPUTATIONAL INVESTIGATION OF THE EFFECT OF LICHEN METABOLITES ON THE INHIBITION OF EPIDERMAL GROWTH FACTOR RESEPTOR L858R MUTATION
AU  - Alamoody, Özlem
AU  - Al-amoody, Ahmed Ali Mohamed
AU  - Sezer Zhmurov, Çiğdem
AU  - Atalay, Vildan
PY  - 2025
DA  - September
Y2  - 2025
JF  - Turkish Computational and Theoretical Chemistry
JO  - Turkish Comp Theo Chem (TC&TC)
PB  - Koray SAYIN
WT  - DergiPark
SN  - 2587-1722
SP  - 104
EP  - 115
VL  - 10
IS  - 2
LA  - en
AB  - Epidermal growth factor reseptör (EGFR) is an important protein in the cell cycle; mutations in the protein cause many problems. The vast majority of these diseases manifest themselves as tumours. One of the most common mutations in the EGFR protein is the L858R mutation in exon 21, which is a type of missense single nucleotide polymorphism (SNP). In this mutation, the leucine in the 858th amino acid of the protein changes to arginine, and the thymine nucleotide in the leucine structure changes to guanine nucleotide. This nucleotide change leads to a high rate of cancer. Lung cancers are the leading cause of cancer caused by L858R mutations. Especially the L858R mutation is the leading cause of non-small cell lung cancer (NSCLC), and this type of mutation has been detected in most patients with this type of cancer.           In this study, a docking study was conducted to determine molecules that could be inhibitors for the mutant EGFR molecule, and lichen secondary metabolites were used for this purpose. While as known there are more than 400 lichen secondary metabolites, 155 molecules were selected as examples for this study. For this purpose, geometry optimizations were performed with the semi-empirical PM6 method on the most stable structure obtained after conformer analysis of the active molecules that have an effect from the selected lichen secondary metabolites, and a QSAR model was created to correlate the docking energies of the relevant molecules and their physicochemical properties. Optimizations and docking operations were performed in Spartan’14 and Autodock Vina programs, respectively. Calculations made for all studied molecule types, results of physicochemical parameters and linear regression analyses between binding energies were performed with the Excel program. BIOVIA Discovery Studio program was used for the docking images between protein and molecule.
KW  - EGFR
KW  - Molecular
KW  - Protein
KW  - Lichen
KW  - Metabolite.
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UR  - https://dergipark.org.tr/en/pub/tcandtc/issue//1632731
L1  - https://dergipark.org.tr/en/download/article-file/4577654
ER  -