Abstract
The widespread problem of resistance development in bacteria has become a critical issue for modern medicine. To limit that phenomenon, many compounds have been extensively studied. Among them were derivatives of available drugs, but also alternative novel detergents such as Gemini surfactants. Over the last decade, they have been massively synthesized and studied to obtain the most effective antimicrobial agents, as well as the most selective aids for nanoparticles drug delivery. Various protocols and distinct bacterial strains used in Minimal Inhibitory Concentration experimental studies prevented performance benchmarking of different surfactant classes over these last years. Motivated by this limitation, we designed a theoretical methodology implemented in custom fast screening software to assess the surfactant activity on model lipid membranes. Experimentally based QSAR (quantitative structure-activity relationship) prediction delivered a set of parameters underlying the Diptool software engine for high-throughput agent-membrane interactions analysis. We validated our software by comparing score energy profiles with Gibbs free energy from the Adaptive Biasing Force approach on octenidine and chlorhexidine, popular antimicrobials. Results from Diptool can reflect the molecule behavior in the lipid membrane and correctly predict free energy of translocation much faster than classic molecular dynamics. This opens a new venue for searching novel classes of detergents with sharp biologic activity.
Highlights
We decided to avoid averaging the error to derive a wider range for random membrane components generator and deliver a complex expertise of membrane-agent interactions. Such a procedure allows employing many types of lipids reflecting many membrane species supposing that dipole moments are known. At this stage a membrane size may be adjusted in all axes, whereas a number of lipids is automatically calculated based on the given volume and area per lipid (APL)
We presented a novel, self−made methodology supported with a software solution named Diptool—a screening tool for a rapid determination of the Gemini agent affinity to various types of homogenous lipid membranes delivering particle trajectory visualization and free energy analysis
In the presented study we introduced from scratch the genesis and background of delivered methodology, discussed the calculation core of the Diptool software, and validated and tested our tool with known antimicrobial candidates: OCT and CHX
Summary
The increasing problem of antibiotic resistance was identified by The World Health. One of the approaches to limit this phenomenon involves the application of antibacterial candidates with a broad spectrum of activity. The complex interaction with various cellular structures may significantly reduce the bacteria’s resistance development [2,3]. Cationic Gemini surfactants belong to a class of compounds with broad-spectrum activity, effective against Gram-positives and Gram-negatives even in low concentrations, and are used in drug nanoparticles delivery. Specific Gemini detergents are used in the paint industry as corrosion inhibitors [4,5]. Only a few new classes of surface-active compounds have been discovered and have attracted the attention of researchers and industrial innovation units. Several novel groups of bio-active detergents have been synthesized
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