Rational design of novel potential EGFR inhibitors: molecular docking, molecular descriptor and pharmacokinetics studies of piperidin-4-one derivatives
Bibliographic record
Abstract
The epidermal growth factor receptor (EGFR) is one of the most attractive drug targets against the human pancreas cancer cell line (Panc-1). In this research, Piperidin-4-one derivative is identified as novel potential EGFR inhibitors were subjected to molecular docking, molecular descriptor and pharmacokinetics studies in order to design new compound with high predicted activity. Using the 6-311G (d, p) basis set, the density functional theory (DFT) B3LYP method was utilised to calculate the optimal structure of the compound 1-(cyclopropanecarbonyl)−2,6-di(1H-indol-3-yl)−3-methylpiperidin-4-one (CIMP). The experimental bond length and bond angles were then compared with the data obtained from the reference compound. The electron densities of the donor (i) and acceptor (j) bonds and the hyper conjugative interaction energy E(2) were found using natural bonding orbital (NBO) analysis. The band gap energy value was found in calculations of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO). Analysis has been done on molecular electrostatic potential. At the same theoretical level, the Mulliken atomic charges of the carbon, nitrogen and oxygen atoms were computed. The good nonlinear optical (NLO) property of the title molecule is demonstrated by the dipole moment, polarizability and first-order hyperpolarizability. The properties of partial density of states (PDOS), total density of states (TDOS) and thermodynamics were computed and discussed separately. Furthermore, statistical analyses were performed to elucidate the relationships between ADMET (Absorption, distribution, Metabolism, Elimination and Toxicity) properties of CIMP and molecular descriptors, including degree, neighborhood degree, degree entropy, and neighborhood degree entropy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".