_1700053107 20231115125827000 Editor editor.jddt@gmail.com Universal Journal of Pharmaceutical Research Universal Journal of Pharmaceutical Research Univ J Pharm Res 2456-8058 2831-5235 11 15 2023 Issouf Soro https://orcid.org/0009-0007-8281-5981 Hermann N’Guessan https://orcid.org/0009-0002-7088-6727 Akoun Abou https://orcid.org/0000-0001-6902-1027 Raymond Kre N’Guessan https://orcid.org/0009-0008-7881-0587 Eugene Megnassan https://orcid.org/0000-0003-1505-5277 Objective: A novel subnanomolar anticancer hydroxamic acid containing drug candidates, inhibitors of human M1 aminopeptidase (APN) a recent validated target and has reached the predicted subnanomolar range of inhibitory potency. Methods: A quantitative structure activity relationships (QSAR) complexation model has been developed from a compounds of 37 hydroxamic acid derivatives (AHD1-37 as training set, TS) to establish a linear correlation between the calculated relative Gibbs free energies (GFE: ΔΔGcom) of APN-AHDx complex formation and the experimental inhibition potency (Kiexp). The predictive power of the QSAR model was then validated first with 9 other AHDs not included in the TS and thereafter with the generation of a 3D-QSAR-PH4 pharmacophore (PH4) model to screen the AHD chemical subspace built as a virtual combinatorial library of more than 58,644 AHD analogs). Finally the best PH4 hits were evaluated with the initial QSAR model for predicted potency (Kipre) and pharmacokinetic profile. Results: The QSAR model linear correlation equation: pKiexp=-0.1901×∆∆Gcom + 8.2886 , R2=0.94, the subsequent PH4 model linear correlation between experiment and PH4-estimated Ki: pKiexp=1.0006× pKipre + 0.0028, R2=0.79 documents the high predictive power of this approach. Finally the screening of the virtual library of AHD analogs yielded 95 orally bioavailable candidates the best reaching a predicted potency (Kipre) of 50 pM and displaying favorable pharmacokinetic profile. Conclusion: The combined use of molecular modeling (QSAR) and in silico PH4-based screening of the hypothetical combinatorial library has resulted in proposed and predicted potent anticancer candidates with a suitable pharmacokinetic profile.                        Peer Review History: Received: 3 August 2023; Revised: 12 September; Accepted: 25 October, Available online: 15 November 2023 Academic Editor: Dr. Nuray Arı, Ankara University, Turkiye, ari@ankara.edu.tr Received file:                             Reviewer's Comments: Average Peer review marks at initial stage: 7.0/10 Average Peer review marks at publication stage: 9.0/10 Reviewers: Prof. Hassan A.H. Al-Shamahy, Sana'a University, Yemen, shmahe@yemen.net.ye Prof. Dr. A. Hakan AKTAŞ, Süleyman Demirel University, Faculty of Science and Art, Department of Chemistry, Isparta-Turkey, hakanaktas@sdu.edu.tr 11 15 2023 http://creativecommons.org/licenses/by-nc/4.0 10.22270/ujpr.v8i5.1011 https://ujpr.org/index.php/journal/article/view/1011 https://ujpr.org/index.php/journal/article/download/1011/1485 https://ujpr.org/index.php/journal/article/download/1011/1485 https://ujpr.org/index.php/journal/article/download/1011/1490 https://ujpr.org/index.php/journal/article/download/1011/1508