Synthesis, structural characterization, and DFT studies of anti-cancer drug
S N Chandana1, Fares Hezam Al-Ostoot2,3, Yasser Hussein Eissa Mohammed2,4
1Department of Engineering Physics, Adichunchanagiri Institute of Technology, Jyothinagara, Chikkamamagaluru 577102, Karnataka, India.
Researchers synthesized and characterized a novel compound, N-(2-aminophenyl)-2-(4-bromophenoxy) acetamide, using X-ray diffraction. Intermolecular interactions were analyzed to understand crystal structure stabilization, aiding future drug design.
Area of Science:
- Medicinal Chemistry
- Crystallography
- Computational Chemistry
Background:
- Drug design aims to create novel, safe, and tailored therapeutics.
- Understanding molecular interactions and physicochemical properties is crucial for effective drug development.
Purpose of the Study:
- To synthesize and characterize the compound N-(2-aminophenyl)-2-(4-bromophenoxy) acetamide.
- To elucidate the crystal structure and analyze intermolecular interactions.
- To computationally investigate molecular properties and interactions.
Main Methods:
- Synthesis and characterization using spectroscopic techniques (1H, 13C NMR, LC-MS).
- X-ray diffraction (XRD) for crystal structure determination.
- Hirshfeld surface analysis, 2D fingerprint plots, and Energy framework analysis using CrystalExplorer17.
- Density Functional Theory (DFT) calculations for HOMO/LUMO energies.
Main Results:
- The compound N-(2-aminophenyl)-2-(4-bromophenoxy) acetamide was synthesized in good yield.
- The crystal structure was confirmed as orthorhombic with space group Pca2(1).
- Intermolecular interactions (N-H … O, N-H … Cg) were identified and quantified, stabilizing the crystal structure.
- Computational analyses provided insights into interaction energies and electronic properties.
Conclusions:
- The study successfully synthesized and structurally characterized a novel compound.
- Analysis of intermolecular interactions provides a foundation for understanding structure-activity relationships.
- Computational methods complement experimental data, aiding in the rational design of new drug candidates.
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