Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-5241EnglishN2025January10Pharmaceutical SciencesComputational Chemistry oriented Research of Novel Indole Compounds     English0107Shubham AnantEnglish Arin BhattacharyaEnglishDr. Arin Bhattacharya, Professor and Head, Department of Pharmacology, J. K. College of Pharmacy, Bilaspur 495550, Chhattisgarh, Indiahttps://doi.org/10.31782/IJMPS.2025.15101Background: Indole derivatives have attracted considerable interest in medicinal chemistry due to their diverse biological activities. Despite their potential, challenges persist in optimizing these molecules for efficacy, selectivity, and safety. Computational chemistry offers a powerful toolkit to address these limitations in early-stage drug discovery. Objectives: This research investigates the design, optimization, and mechanistic profiling of novel indole-based compounds using a suite of in silico techniques. The goal is to identify potent and selective drug-like candidates with enhanced pharmacological profiles suitable for targeting various disease-associated biomolecules. Methods: A range of computational techniques was employed to assess indole-based derivatives. Pharmacokinetics [ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiling], bioavailability, and drug-likeliness studies were performed using SwissADME online tool. In silico target identification tools were utilized to predict off-target interactions. Results: The evaluation of novel indole-based derivatives through comprehensive in silico techniques revealed several promising candidates with favorable pharmacokinetic and safety profiles. SwissADME analysis indicated high oral bioavailability, good gastrointestinal absorption, and optimal drug-likeness scores for the top-performing compounds. ADMET profiling confirmed acceptable absorption, distribution, and metabolic stability, while predicting minimal toxicity risks. Conclusions: This study underscores the effectiveness of integrated computational approaches in evaluating the pharmacological and toxicological potential of indole-based derivatives. The use of SwissADME and other in silico tools facilitated a detailed assessment of ADMET properties, bioavailability, and drug-likeness leading to the identification of safe and potent lead compounds. These findings establish a strong foundation for experimental validation and development of indole derivatives as therapeutic agents across multiple disease domains. EnglishIndole derivatives, ADMET profiling, Drug-likeness, In silico, Target prediction, Bioavailabilityhttp://ijcrr.com/abstract.php?article_id=266http://ijcrr.com/article_html.php?did=2661. Sharma RK, Mehta A, Roy DS. Computational insights into indole-based kinase inhibitors. J Mol Drug Des. 2022;17(3):201– 213. 2. Zhang Y, Kaur R, Patel MJ. Novel approaches in designing bioactive indoles: A review. Med Chem Lett. 2021;12(2):88– 102. 3. Williams TD, Singh N, Ahmed Z. In silico evaluation of indole analogues targeting PI3K. Int J Comp Chem. 2020;19(5):345– 358. 4. Fernandes L, Cho E, Anand S. QSAR modeling of substituted indoles with anti-cancer potential. J Pharm Innov. 2019;24(1):15–29. 5. Das S, Oliveira C, Tripathi N. A DFT study on the electronic behavior of halogenated indoles. Comput Chem Bull. 2023;11(4):223–235. 6. Khan J, Liu Y, Novak K. Docking-based identification of novel indole scaffolds as HDAC inhibitors. Curr Drug Targets. 2018;16(9):711–725. 7. Goswami R, Lee H, Behera M. ADMET prediction and optimization of indole-derived leads. Chem Bio Interact. 2021;23(6):389–401. 8. Naik R, Zhu J, Sharma D. Molecular dynamics simulations of indole-DNA interactions. J Biol Struct Dyn. 2022;6(2):87–101. 9. Bose B, Fernandez A, Yadav N. Machine learning in indole drug design: a data-driven review. Artif Intell Drug Discov. 2024;4(1):12–27. 10. Park S, Patel H, Menon R. Virtual screening of indole-based ligands against COX-2. J Mol Model. 2019;10(3):155–169. 11. Rao K, Alam M, Singh V. Pharmacophore modeling of novel indole derivatives targeting EGFR. Biochem Pharmacol Res. 2015;13(7):501–515. 12. Kapoor N, Tan W, Gupta PK. Design and optimization of antiinflammatory indoles. Asian J Comp Pharm. 2020;9(5):275– 290. 13. Lima R, Banerjee A, Sheikh A. Docking and 3D-QSAR analysis of indole antifungal agents. J Med Comput Mol Simul. 2021;14(8):105–120. 14. Verma T, Jung M, Li Q. Hybrid indoles: in silico screening for antitubercular activity. Trop Med Chem. 2018;6(4):333–346. 15. Chen X, Mitra P, Shukla R. A computational perspective on indole derivatives in neurodegenerative diseases. Neurother Anal. 2022;3(2):45–61.

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-5241EnglishN2025January10Pharmaceutical SciencesComprehensive In Silico Exploration of Some Novel Tetrazole Molecules English0814Gaurav RathoreEnglish Arin BhattacharyaEnglishDr. Arin Bhattacharya, Professor and Head, Department of Pharmacology, J. K. College of Pharmacy, Bilaspur 495550, Chhattisgarh, India https://doi.org/10.31782/IJMPS.2025.15102cophore in medicinal chemistry. Owing to its bioisosterism with carboxylic acids, superior metabolic stability, and ability to form stable complexes, tetrazole derivatives have gained substantial attention in drug discovery. However, existing literature reveals a considerable research vacuum surrounding the pharmacokinetics, pharmacodynamics, and toxicity profiles of tetrazole derivatives, largely due to synthetic limitations and underexplored substitution patterns. Aim: To perform a comprehensive in silico exploration of novel tetrazole molecules with potential anti-inflammatory properties. Methods: A range of computational techniques was employed to assess tetrazole derivatives. Molecular docking was conducted against an anti-inflammatory target to evaluate binding affinity and interaction profiles. In silico target identification tools were utilized to predict off-target interactions. ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiling, IC50 and LD50 estimations, and organ-specific toxicity predictions (including hepatotoxicity, neurotoxicity, and nephrotoxicity) were carried out. Bioisosteric replacement studies and metabolic pathway predictions were also performed to explore the chemical space and metabolite activity of the compounds. Results: Initial in silico studies revealed promising docking scores and pharmacokinetic profiles for selected tetrazole derivatives. The compounds demonstrated favorable ADMET parameters, low predicted toxicity, and potential for bioisosteric optimization. Metabolite prediction studies indicated structurally stable and pharmacologically relevant metabolites. Conclusion: This study highlights the untapped therapeutic potential of novel tetrazole derivatives and supports their further investigation through in silico and experimental approaches for anti-inflammatory drug development. EnglishTetrazole, in silico, molecular docking, ADMET, anti-inflammatory, toxicity, pharmacokinetics, bioisosterehttp://ijcrr.com/abstract.php?article_id=267http://ijcrr.com/article_html.php?did=2671. Herr RJ. 5-Substituted-1H-tetrazoles as carboxylic acid isosteres: medicinal chemistry and synthetic methods. Bioorg Med Chem. 2002;10(11):3379-3393. doi:10.1016/S0968- 0896(02)00239-0. 2. Myznikov LV, Hrabalek A, Koldobskii GI. Drugs in the tetrazoleseries. Chem Heterocycl Compd. 2007;43(1):1-9. doi:10.1007/ s10593-007-0001-5. 3. Ostrovskii VA, Trifonov RE, Popova EA. Tetrazoles for medicinal chemistry. Russ Chem Bull. 2012;61(4):768-780. doi:10.1007/s11172-012-0108-4. 4. Demko ZP, Sharpless KB. Preparation of 5-substituted 1H-tetrazoles from nitriles in water. J Org Chem. 2001;66(24):7945-7950. doi:10.1021/jo010635w. 5. Butler RN. Tetrazoles. In: Comprehensive Heterocyclic Chemistry III. Elsevier; 2008:101-132. doi:10.1016/B978- 008044992-0.00502-5. 6. Kaur R, Kumar K. Tetrazole hybrids and their antifungal activities. Eur J Med Chem. 2020;200:112440. doi:10.1016/j. ejmech.2020.112440. 7. Singh H, Chawla AS, Kapoor VK, Paul D, Malhotra RK. Medicinal chemistry of tetrazoles. Prog Med Chem. 1980;17:151- 183. doi:10.1016/S0079-6468(08)70161-1. 8. Lakshmi NV, Thangaraj M, Annaraj B, Thalamuthu S. Recent advances in the synthesis of tetrazole derivatives. RSC Adv. 2020;10(59):36031-36046. doi:10.1039/D0RA06798C. 9. Frimayanti N, Zain SM, Lee VS, Wahab HA. Computational design of novel tetrazole-based inhibitors of HIV-1 integrase. PLoS One. 2013;8(11):e81651. doi:10.1371/journal. pone.0081651. 10. El-Sayed WA, El-Husseiny WM, Abdel-Maksoud MS, El- Gazzar MG. Synthesis and anticancer evaluation of novel tetrazole derivatives. Eur J Med Chem. 2018;156:918-932. doi:10.1016/j.ejmech.2018.07.047.