Sürdürülebilir Kalkınma Amaçları

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• MakaleYalnız künye2026/r/kostu/10974
  Suppressing Liver Cancer via the VEGFR1 Receptor using De novo Ellagic Acid Derivatives and Co-drugs: Comprehensive In silico Biochemistry Research with ADMET, RMSD, Molecular Docking, and Molecular Dynamics Simulations

  Agar, S; Acar, E; Aldemir, O; Gokoluk, E; Issa, G; Bogdanov, J

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• MakaleAçık Erişim2026/r/kostu/10860
  In silico biochemical de novo drug design of valproic acid derivatives to suppress cancerous dna: comprehensive molecular docking, molecular dynamics, 1 h nmr, adme

  Acar, Esra; Issa, Ghassan; Agar, Soykan; Gökoluk, Erkan; Giglou, Erfan Akhavan; Şimşek, Dilruba

  Objective: This comprehensive in silico computational and theoretical biochemistry/organic chemistry research study covers the inhibition methodologies of 1-BNA, which is an essential template for cancer- suppressing research. By disrupting the minor groove domain binding site of the DNA template 1-BNA dodecamer, three de novo drug candidate molecules via derivatization of anti-epileptic valproic acid (VPA) drug were designed. Methods: Calf thymus DNA (ct-DNA) sequence d(CGCGAATTCGCG)2 dodecamer (PDB ID: 1BNA) was obtained from the Protein Data Bank to study. Molecular docking simulations, the most updated docking programs of AutoDock Vina and PyRx were utilized. Molecular dynamics (MD) simulations and Absorption, distribution, metabolism and excretion (ADME) analyses were employed by Schrödinger’s Desmond software. Results: Thorough in silico results of three new derivatized analogues of VPA showed that chloro-derivatized analogue with its -9.6 kcal/mol docking score and 297.2 µM inhibition constant (IC) has a much better indication in the suppression where isopropyl and fluoro derivatized analogues possess -9.1 kcal/mol docking score with 483.8 µM IC and - 8.3 kcal/mol docking score with 896.2 µM IC respectively compared to the results of pristine VPA’s -8.2 kcal/mol docking score with 863.6 µM IC. Along with the detailed ADME results, isopropyl and chloro- derivatized ligands prove their worth of being a new drug candidate. Conclusion: All results proved that the de novo derivatives of VPA illustrate better docking scores (better suppression) along with better ICs and oral absorption percentage values, meaning that the analogues possess better indications compared to pristine VPA toward the suppression of cancerous cell template DNA.

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• MakaleAçık Erişim2024Scopus SJRQ4/r/kostu/10222
  AI Integrated Theoretical/Organic Chemistry is Set to Revolutionize the Future of Education and De Novo Drug Discovery

  Agar, Soykan; Tokay, Ilgaz; Akkurt, Barbaros; Gokoluk, Erkan; Akbulut, M. Berk; Ozler, Berin Damla; Elmas, Muzaffer

  This article discusses the rapidly expanding artificial intelligence (AI) tools combined with theoretical and organic chemistry software to point out the fact that near future is being reborn with a new education system and research system in drug discovery. The integration of AI into the field of chemistry and pharmacy has expanded rapidly in recent years. There has been a significant surge in both journal articles and patents, particularly from 2015 onward. Analyzing the distribution of these publications across various pharmaceutical and chemical research domains reveal that theoretical chemistry, organic chemistry and biochemistry have embraced AI most extensively, showing the highest growth rates. Utilizing such new software tools in educational research centers and academia, students and scholars can learn and apply much more long-durational and larger techniques in shorter times to yield massive results for the sake of humankind’s future with no diseases. This new type of educational and research-oriented technique integrating the control and check mechanism of AI is being used today for the design of new drugs which are essential for the longevity. The utilization of AI with in-silico studies and education increases the ability to stop diseases with a logarithmic increase while the old-fashioned ways of chemistry will be no more in the near future. Overall, this research paper offers a comprehensive overview of AI's advancement in pharmaceutical and chemical area and sheds light on its potential future trajectories.

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