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DOI 10.1186/s42162-026-00691-0

Медицинская библиотека · Energy informatics · 2026

Identifying people's energy information needs through Energy Citizen Personas.

Kumar Ajesh, Kuronen Toni, Naqvi Bilal, Annala Salla, Lensu Lasse, Massari Martina, Boulanger Saveria Olga Murielle, Wolff Annika

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Аннотация

UNLABELLED: Renal tuberculosis (TB) is an extrapulmonary form of TB, and is becoming more common and challenging to treat. This is because many anti-tubercular drugs have nephrotoxicity and have poor drug penetration into renal tissues. These problems highlight the urgent need for safer, kidney-targeted treatment regimes, particularly in patients with compromised kidney function. Thus, this study investigates lysozyme, which is a low-molecular-weight protein and has natural kidney-affinity, as a potential carrier for targeted renal drug delivery. Here, a comprehensive in silico approach has been utilized to identify non-nephrotoxic anti-TB drugs and evaluate their suitability for lysozyme-mediated renal-targeted delivery. For this study, a total of 21 clinically important anti-TB drugs, including first-line, second-line, and newly developed agents, were screened for nephrotoxicity using the SA-Predictor and ProTox 3.0 tools. Of these, eight drugs were predicted to be non-nephrotoxic and were used for molecular docking studies with hen egg-white lysozyme (HEWL). The non-nephrotoxic anti-TB drugs which showed better binding with HEWL, were subjected to 100 ns molecular dynamics simulations to examine protein-drug complex stability and were assessed using RMSD, RMSF, hydrogen-bond occupancy, and radius of gyration. Our study showed that ethambutol, pretomanid, and terizidone demonstrated the most stable interactions with HEWL. This work establishes a systematic computational pipeline that integrates nephrotoxicity profiling, molecular docking, and MD simulations to identify safe anti-TB drugs suitable for renal-targeted delivery. Additionally, in vitro and in vivo validation will be essential for advancing these findings toward clinical application.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40203-026-00691-8.

Для цитирования: Kumar Ajesh, Kuronen Toni, Naqvi Bilal, Annala Salla, Lensu Lasse, Massari Martina, Boulanger Saveria Olga Murielle, Wolff Annika. Identifying people's energy information needs through Energy Citizen Personas.. Energy informatics. 2026. DOI: 10.1186/s42162-026-00691-0.
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