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Šegan S, Krunić MJ, Andrić DB, Šukalović VB, Penjišević JZ, Jevtić II. Evaluation of lipophilicity and drug-likeness of donepezil-like compounds using reversed-phase thin-layer chromatography. Biomed Chromatogr 2024; 38:e5867. [PMID: 38558037 DOI: 10.1002/bmc.5867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 02/08/2024] [Accepted: 03/07/2024] [Indexed: 04/04/2024]
Abstract
Fourteen donepezil-like acetylcholinesterase (AChE) inhibitors from our library were analyzed using reversed-phase thin-layer chromatography to assess their lipophilicity and blood-brain barrier permeability. Compounds possessed N-benzylpiperidine and N,N-diarylpiperazine moieties connected via a short carboxamide or amine linker. Retention parameters RM 0, b, and C0 were considered as the measures of lipophilicity. Besides, logD of the investigated compounds was determined chromatographically using standard compounds with known logPow and logD values at pH 11. Experimentally obtained lipophilicity parameters correlated well with in silico generated results, and the effect of the nature of the linker between two pharmacophores and substituents on the arylpiperazine part of the molecule was observed. As a result of drug-likeness analysis, both Lipinski's rule of five and Veber's rule parameters were determined, suggesting that examined compounds could be potential candidates for further drug development. Principal component analysis was performed to obtain an insight into a grouping of compounds based on calculated structural descriptors, experimentally obtained values of lipophilicity, and AChE inhibitory activity.
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Affiliation(s)
- Sandra Šegan
- Department of Chemistry, Institute of Chemistry, Technology and Metallurgy, University of Belgrade, Belgrade, Republic of Serbia
| | - Mihajlo J Krunić
- Department of Chemistry, Institute of Chemistry, Technology and Metallurgy, University of Belgrade, Belgrade, Republic of Serbia
| | - Deana B Andrić
- Department of Organic Chemistry, Faculty of Chemistry, University of Belgrade, Belgrade, Republic of Serbia
| | - Vladimir B Šukalović
- Department of Chemistry, Institute of Chemistry, Technology and Metallurgy, University of Belgrade, Belgrade, Republic of Serbia
| | - Jelena Z Penjišević
- Department of Chemistry, Institute of Chemistry, Technology and Metallurgy, University of Belgrade, Belgrade, Republic of Serbia
| | - Ivana I Jevtić
- Department of Chemistry, Institute of Chemistry, Technology and Metallurgy, University of Belgrade, Belgrade, Republic of Serbia
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Nisterenko W, Kułaga D, Woziński M, Singh YR, Judzińska B, Jagiello K, Greber KE, Sawicki W, Ciura K. Evaluation of Physicochemical Properties of Ipsapirone Derivatives Based on Chromatographic and Chemometric Approaches. Molecules 2024; 29:1862. [PMID: 38675682 PMCID: PMC11054528 DOI: 10.3390/molecules29081862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 04/14/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
Drug discovery is a challenging process, with many compounds failing to progress due to unmet pharmacokinetic criteria. Lipophilicity is an important physicochemical parameter that affects various pharmacokinetic processes, including absorption, metabolism, and excretion. This study evaluated the lipophilic properties of a library of ipsapirone derivatives that were previously synthesized to affect dopamine and serotonin receptors. Lipophilicity indices were determined using computational and chromatographic approaches. In addition, the affinity to human serum albumin (HSA) and phospholipids was assessed using biomimetic chromatography protocols. Quantitative Structure-Retention Relationship (QSRR) methodologies were used to determine the impact of theoretical descriptors on experimentally determined properties. A multiple linear regression (MLR) model was calculated to identify the most important features, and genetic algorithms (GAs) were used to assist in the selection of features. The resultant models showed commendable predictive accuracy, minimal error, and good concordance correlation coefficient values of 0.876, 0.149, and 0.930 for the validation group, respectively.
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Affiliation(s)
- Wiktor Nisterenko
- Department of Physical Chemistry, Faculty of Pharmacy, Medical University of Gdańsk, Aleja Generała Józefa Hallera 107, 80-416 Gdańsk, Poland; (W.N.); (M.W.); (K.E.G.); (W.S.)
| | - Damian Kułaga
- Department of Organic Chemistry and Technology, Faculty of Chemical Engineering and Technology, Cracow University of Technology, 24 Warszawska Street, 31-155 Cracow, Poland;
| | - Mateusz Woziński
- Department of Physical Chemistry, Faculty of Pharmacy, Medical University of Gdańsk, Aleja Generała Józefa Hallera 107, 80-416 Gdańsk, Poland; (W.N.); (M.W.); (K.E.G.); (W.S.)
| | - Yash Raj Singh
- Department of Pharmaceutical Quality Assurance, LJ Institute of Pharmacy, LJ University, Ahmedabad 382210, India;
| | - Beata Judzińska
- QSAR Lab, Trzy Lipy 3, 80-172 Gdańsk, Poland; (B.J.); (K.J.)
- Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Karolina Jagiello
- QSAR Lab, Trzy Lipy 3, 80-172 Gdańsk, Poland; (B.J.); (K.J.)
- Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
| | - Katarzyna Ewa Greber
- Department of Physical Chemistry, Faculty of Pharmacy, Medical University of Gdańsk, Aleja Generała Józefa Hallera 107, 80-416 Gdańsk, Poland; (W.N.); (M.W.); (K.E.G.); (W.S.)
| | - Wiesław Sawicki
- Department of Physical Chemistry, Faculty of Pharmacy, Medical University of Gdańsk, Aleja Generała Józefa Hallera 107, 80-416 Gdańsk, Poland; (W.N.); (M.W.); (K.E.G.); (W.S.)
| | - Krzesimir Ciura
- Laboratory of Environmental Chemoinformatics, Faculty of Chemistry, University of Gdansk, Wita Stwosza 63, 80-308 Gdansk, Poland
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Ciura K, Fryca I, Gromelski M. Prediction of the retention factor in cetyltrimethylammonium bromide modified micellar electrokinetic chromatography using a machine learning approach. Microchem J 2023. [DOI: 10.1016/j.microc.2023.108393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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