Azomethines with Long Alkyl Chains: Synthesis, Characterization, Biological Properties and Computational Lipophilicity Assessment

The search for new antibacterial agents is an important task due to the emergence of resistance to widely used drugs. Bromine-, chlorine-, and nitro-substituted phenyl ring azomethines with long alkyl chains (C12, C14, C16, and C18) were synthesized and characterized using several experimental methods (NMR and IR spectroscopy, elemental analysis, mass spectrometry). Antibacterial and antifungal activity was tested on several cultures; the synthesized compounds show activity at the level of some commercial antiseptics. Lipophilicity (an important descriptor for predicting biological properties) of the experimentally synthesized and isomeric molecules was determined by three different approaches: quantum chemistry, machine learning (GraphormerLogP model), and an atom contribution model (RDKit library). The quantum-chemical method can account for any spatial arrangements and can be considered the most accurate of the approaches used, but it requires significant computational time. The atom contribution model is the fastest of the methods used, but it gives underestimated results, and different isomers have exactly the same values, in contrast to the quantum chemistry results. Machine learning-based methods (GraphormerLogP) demonstrate acceptable accuracy, sensitivity to isomerism, and orders-of-magnitude higher throughput, making them an optimal tool for high-throughput screening.

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Journal
Chemistry
Published
2026-02-12
DOI
https://doi.org/10.3390/chemistry8020023
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Azomethines with Long Alkyl Chains: Synthesis, Characterization, Biological Properties and Computational Lipophilicity Assessment

Timur Gimadiev, Marina P. Shulaeva, Vyacheslav Alekseevich Grigorev, Khasan R. Khayarov et al.
Chemistry
Computational Drug Discovery Methods
article

Azomethines with Long Alkyl Chains: Synthesis, Characterization, Biological Properties and Computational Lipophilicity Assessment

Timur Gimadiev, Marina P. Shulaeva, Vyacheslav Alekseevich Grigorev, Khasan R. Khayarov, Nikita Yu. Serov
article en

Abstract

The search for new antibacterial agents is an important task due to the emergence of resistance to widely used drugs. Bromine-, chlorine-, and nitro-substituted phenyl ring azomethines with long alkyl chains (C12, C14, C16, and C18) were synthesized and characterized using several experimental methods (NMR and IR spectroscopy, elemental analysis, mass spectrometry). Antibacterial and antifungal activity was tested on several cultures; the synthesized compounds show activity at the level of some commercial antiseptics. Lipophilicity (an important descriptor for predicting biological properties) of the experimentally synthesized and isomeric molecules was determined by three different approaches: quantum chemistry, machine learning (GraphormerLogP model), and an atom contribution model (RDKit library). The quantum-chemical method can account for any spatial arrangements and can be considered the most accurate of the approaches used, but it requires significant computational time. The atom contribution model is the fastest of the methods used, but it gives underestimated results, and different isomers have exactly the same values, in contrast to the quantum chemistry results. Machine learning-based methods (GraphormerLogP) demonstrate acceptable accuracy, sensitivity to isomerism, and orders-of-magnitude higher throughput, making them an optimal tool for high-throughput screening.

ChemistryVol. 8(2)
Kazan Federal University (RU), Kazan Scientific Center (RU), Institute of Mechanics and Engineering (RU), Kazan State Medical Academy (RU)
Openalex Percentile: Top 56%
Computational Drug Discovery Methods
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Azomethines with Long Alkyl Chains: Synthesis, Characterization, Biological Properties and Computational Lipophilicity Assessment — Timur Gimadiev, Marina P. Shulaeva, et al. · Chemistry (2026) | TGRS Research Map | TGRS