1
Siqueira-Neto, J. L. et al. Antimalarial drug discovery: progress and approaches. (2023). Nature Reviews Drug Discovery 22, 807–826
2
[2] Asiamah, I., Obiri, S. A., Tamekloe, W., Armah, F. A. & Borquaye, L. S. (2023). Applications of molecular docking in natural products-based drug discovery. Scientific African 20, 1–8
3
[3] Imieje, V. & Amafili, L. (2025) GC-MS Profiling, In Vitro Antimalarial, and Antimicrobial activity of Ricinodendron heudelotii Seed Extracts.Sciences of Phytochemistry 4, 1–8
4
[4] Sarma, M. et al. (2023).Multi-target molecular dynamic simulations reveal glutathione-S-transferase as the most favorable drug target of knipholone in Plasmodium falciparum. Journal of Biomolecular Structure and Dynamics 41, 12808–12824
5
[5] Al-Malki, E. S. (2024). Exploring the Infectious Drug Target Glutathione S‐Transferase in Plasmodium falciparum with the Inhibitory Potential of Azadirachta indica Phytocompounds. Advances in Public Health, 2024(1), 8486021.
6
[6] Dulsat, J., López-Nieto, B., Estrada-Tejedor, R., & Borrell, J. I. (2023). Evaluation of free online ADMET tools for academic or small biotech environments. Molecules, 28(2), 776.
7
[7] Wu, F., Zhou, Y., Li, L., Shen, X., Chen, G., Wang, X., ... & Huang, Z. (2020). Computational approaches in preclinical studies on drug discovery and development. Frontiers in chemistry, 8, 726.
8
[8] Pinzi, L., & Rastelli, G. (2019). Molecular docking: shifting paradigms in drug discovery. International journal of molecular sciences, 20(18), 4331.
9
[9] Forli, S. et al. (2019).Computational protein-ligand docking and virtual drug screening with the AutoDock suite. Nature Protocols 11, 905–919
10
[10] Pantsar, T. & Poso, A. (2018). Binding affinity via docking: Fact and fiction. Molecules 23, 1–11
11
[11] Khanum, A. et al. (2024).Molecular docking of bioactive compounds extracted and purified from selected medicinal plant species against covid-19 proteins and in vitro evaluation. Scientific Reports 14, 1–18
12
[12] Chaudhary, M., Tyagi, K. & Nagar, P. (2024). A Review On Molecular Docking And It’s Application M. International Journal Of advanced Research 12, 1141–1153
13
[13] Gurung, A. B., Ali, M. A., Lee, J., Farah, M. A., & Al-Anazi, K. M. (2021). An updated review of computer‐aided drug design and its application to COVID‐19. BioMed research international, 2021(1), 8853056.
14
[14] Sriramulu, D. K. & Lee, S. G. (2020). Combinatorial Effect of Ligand and Ligand-Binding Site Hydrophobicities on Binding Affinity. Journal of Chemical Information and Modeling 60, 1678–1684
15
[15] Muhammed, M. T. & Aki-Yalcin, E. (2022). Molecular Docking: Principles, Advances, and Its Applications in Drug Discovery. Letters in Drug Design & Discovery 21, 480–495
16
[16] Torres, P. H. M., Sodero, A. C. R., Jofily, P. & Silva-Jr, F. P. (2019). Key topics in molecular docking for drug design. International Journal of Molecular Sciences 20, 1–29
17
[17] Olatunde, A., Sulaiman, U., Muhammad, B. B., Tijjani, H., Muktar, M. A., Ibiyemi, B. F., ... & Aremu, A. O. (2025). Deciphering the inhibitory activity of flavonoids against Plasmodium falciparum proteases through molecular docking, drug-likeness and pharmacokinetic studies. Discover Chemistry, 2(1), 294.
18
[18] Huang, Y., Hu, B., Liu, H., Wang, J. & Duan, N. (2025). Stable H-bond networks are crucial for selective CLK1 inhibition: a computational perspective. Frontiers in Chemistry 13, 1–19.
19
[19] Oluwole, S. A., Weldu, W. D. & Agatemor, C. (2025). Hydrophobicity-Driven Enhancement of Hydrogen Bonding in Ionic Liquid Hybrid Solvents. Journal of Physical Chemistry 129, 7228–7237.
20
[20] Aaftaab Sethi. (2020).Molecular Docking in Modern Drug Discovery : Principles and Recent Applications. Drug Discovery and Development .
21
[21] Payandeh, J. & Volgraf, M. (2021). Ligand binding at the protein–lipid interface: strategic considerations for drug design. Nature Reviews Drug Discovery 20, 710–722
22
[22] Caminero Gomes Soares, A., Marques Sousa, G. H., Calil, R. L., & Goulart Trossini, G. H. (2023). Absorption matters: A closer look at popular oral bioavailability rules for drug approvals. Molecular informatics, 42(11), e202300115.
23
[23] Bocci, G., Oprea, T. I., & Benet, L. Z. (2022). State of the Art and Uses for the Biopharmaceutics Drug Disposition Classification System (BDDCS): New Additions, Revisions, and Citation References: State of the Art and Uses for the BDDCS. The AAPS journal, 24(2), 37.
24
[24] Shou. (2020). Current status and future directions of high-throughput ADME screening in drug discovery. Journal of Pharmaceutical Analysis 10, 201–208
25
[25] Karami, T. K., Hailu, S., Feng, S., Graham, R. & Gukasyan, H. J. (2022). Eyes on Lipinski’s Rule of Five: A New “Rule of Thumb” for Physicochemical Design Space of Ophthalmic Drugs. Journal of Ocular Pharmacology and Therapeutics 38, 43–55
26
[26] Kadela-Tomanek, M., Jastrzębska, M., Chrobak, E. & Bębenek, E. 2023). Lipophilicity and ADMET Analysis of Quinoline-1,4-quinone Hybrids. Pharmaceutics 15.
27
[27] Pirie, R. et al. (2024).An analysis of the physicochemical properties of oral drugs from 2000 to 2022. RSC Medicinal Chemistry 15, 3125–3132
28
[28] Garcia Jimenez, D. et al. Chamelogk: (2023).A Chromatographic Chameleonicity Quantifier to Design Orally Bioavailable Beyond-Rule-of-5 Drugs. Journal of Medicinal Chemistry 66, 10681–10693
29
[29] Gu, Y. et al. (2024).DBPP-Predictor: a novel strategy for prediction of chemical drug-likeness based on property profiles. Journal of Cheminformatics 16, 1–15
30
[30] Poongavanam, V. et al. (2021).Predicting the Permeability of Macrocycles from Conformational Sampling – Limitations of Molecular Flexibility. Journal of Pharmaceutical Sciences 110, 301–313.
31
[31] Aqeel, I., Bilal, M., Majid, A., & Majid, T. (2022). Hybrid approach to identifying druglikeness leading compounds against COVID-19 3CL protease. Pharmaceuticals, 15(11), 1333.
32
[32] Lobo, S. (2020). Is there enough focus on lipophilicity in drug discovery?. Expert Opinion on Drug Discovery 15, 261–263
33
[33] Liebeschuetz, J. W. (2021). The Good, the Bad, and the Twisted Revisited: An Analysis of Ligand Geometry in Highly Resolved Protein-Ligand X-ray Structures. Journal of Medicinal Chemistry 64, 7533–7543
34
[34] Zhou, S., Liu, Y., Wang, S. & Wang, L. (2023).Chemical features and machine learning assisted predictions of protein-ligand short hydrogen bonds. Scientific Reports 13, 1–9
35
[35] Venkataraman, M., Rao, G. C., Madavareddi, J. K., & Maddi, S. R. (2025). Leveraging machine learning models in evaluating ADMET properties for drug discovery and development. ADMET and DMPK, 13(3).
36
[36] Venkatraman, V. (2021). FP-ADMET: a compendium of fingerprint-based ADMET prediction models. Journal of cheminformatics, 13(1), 75.
37
[37] Avdeef, A. (2022).Thickness of the aqueous boundary layer in stirred microtitre plate permeability assays (PAMPA and Caco-2), based on the Levich equationǂ. ADMET and DMPK 10, 249–252
38
[38] Grumetto, L., & Russo, G. (2021). cΔlog kwIAM: can we afford estimation of small molecules’ blood-brain barrier passage based upon in silico phospholipophilicity?. ADMET and DMPK, 9(4), 267-281.
39
[39] Deodhar, M., Al Rihani, S. B., Arwood, M. J., Darakjian, L., Dow, P., Turgeon, J., & Michaud, V. (2020). Mechanisms of CYP450 inhibition: understanding drug-drug interactions due to mechanism-based inhibition in clinical practice. Pharmaceutics, 12(9), 846.
40
[40] Saad, A. A. A., Zhang, F., Mohammed, E. A. H., & Wu, X. A. (2022). Clinical aspects of drug–Drug interaction and drug nephrotoxicity at renal organic cation transporters 2 (OCT2) and multidrug and toxin exclusion 1, and 2-K (MATE1/MATE2-K). Biological and Pharmaceutical Bulletin, 45(4), 382-393.
41
[41] Yim, D. S., Bae, S. H., & Choi, S. (2021). Predicting human pharmacokinetics from preclinical data: clearance. Translational and Clinical Pharmacology, 29(2), 78.