Alzheimer9s disease is the neurodegenerative disorder that is a major cause of dementia in the elderly. There is no cure against AD. We have recently discovered novel TRPC6-mediated intracellular signaling pathway that regulates stability of dendritic spines and plays a role in memory formation. We have previously shown that TRPC6 agonists exert beneficial effects in models of AD and may serve as lead compounds for development of AD therapeutic agents. In the current study, we used Integrity database to search for additional TRPC6 agonists. We have selected four compounds to study them as potential neuroprotective agents. We applied bioinformatical analyses to test basic pharmacological properties of selected compounds. We performed in vitro screening of these compounds to validate their ability to protect mushroom spines from amyloid toxicity and determined that two of these compounds exert neuroprotective effects in the nanomolar concentration range. We have chosen one of these compounds (piperazine, PPZ) for further testing. In agreement with previously published data, we have shown that PPZ activates TRPC6 channels. We demonstrated that neuroprotective mechanism of investigated PPZ is based on activation of neuronal store-operated calcium entry (nSOCE) in spines. We have shown that PPZ restores long-term potentiation (LTP) induction in 6 months old 5xFAD mouse hippocampal slices. Obtained results suggest that PPZ and its derivatives are potential lead molecules for development of AD therapeutic agents.

Background: Retroelements (REs) are mobile genetic elements comprising ~40% of human DNA. They can reshape expression patterns of nearby genes by providing various regulatory sequences. The proportion of regulatory sequences held by REs can serve a measure of regulatory evolution rate of the respective genes and molecular pathways. Methods: We calculated RE-linked enrichment scores for individual genes and molecular pathways based on ENCODE project epigenome data for enhancer-specific histone modification H3K4me1 in five human cell lines. We identified consensus groups of molecular processes that are enriched and deficient in RE-linked H3K4me1 regulation. Results: We calculated H3K4me1 RE-linked enrichment scores for 24,070 human genes and 3095 molecular pathways. We ranked genes and pathways and identified those statistically significantly enriched and deficient in H3K4me1 RE-linked regulation. Conclusion: Non-coding RNA genes were statistically significantly enriched by RE-linked H3K4me1 regulatory modules, thus suggesting their high regulatory evolution rate. The processes of gene silencing by small RNAs, DNA metabolism/chromatin structure, sensory perception/neurotransmission and lipids metabolism showed signs of the fastest regulatory evolution, while the slowest processes were connected with immunity, protein ubiquitination/degradation, cell adhesion, migration and interaction, metals metabolism/ion transport, cell death, intracellular signaling pathways.

Molecular dynamics simulations offer insights into macromolecular structures and functions through extensive time-series atomic data. Two widely used metrics for assessing these simulations are RMSD and RMSF. While RMSD measures conformational convergence, it suffers from degeneracy, where different conformations can produce identical values relative to a reference. RMSF indicates relative mobility but lacks temporal specificity. As both metrics provide only global perspectives, there is a pressing need for novel metrics to capture local flexibility with temporal resolution. We introduce GEODES, a novel complementary 3D geometrical descriptor approach, and compare its effectiveness with conventional analyses using RMSD and RMSF. Through molecular dynamics simulations of the vitamin D receptor trimeric complex, we demonstrate that GEODES significantly enhances the molecular dynamics analysis workflow, offering deeper insights into the structural dynamics and interactions of this complex. This innovative and versatile approach holds great promise for applications in drug discovery, structural biology, and bioinformatics. The GEODES Python3 script toolbox is available at https://github.com/rinnifox/GEODES

Введение. Синтезирован ряд биологически активных гидрогалогенидов амидразонов, которые являются перспективной группой для разработки средств, обладающих антибактериальной и противогрибковой активностями. Цель исследования - осуществить прогноз и провести компьютерное моделирование взаимодействия синтезированных соединений с бактериальными и грибковыми мишенями. Материал и методы. Для полученных соединений с помощью программного обеспечения PASS, PASS Targets, Schrödinger Small-Molecule Drug Discovery Suite Release 2018-2, было проведено компьютерное моделирование взаимодействия производных амидразонов с потенциальными бактериальными и грибковыми мишенями. Результаты. Получен компьютерный прогноз спектра потенциальной биологической активности синтезированных гидрогалогенидов амидразонов 3a-f. Программой PASS Targets были предложены белки-мишени микроорганизмов: Escherichia coli -цистатионин--β-лиаза (1CL2), Bacillus cereus - фосфопантетеинил-трансфераза (1QR0), Candida albicans - экзо-β-(1,3)-глюканаза (2PB1), Staphylococcus aureus - дегидроскваленсинтаза (3ACX) для моделирования взаимодействия с амидразрнами 3a-f. Установлено, что две мишени (2PB1 и 3ACX) являются перспективными для разработки новых антибиотических препаратов на основе амидразонов. Результаты исследования могут быть использованы в качестве целенаправленного поиска и синтеза эффективных, малотоксичных противомикробных средств. Заключение. На основании предсказательного компьютерного моделирования ряда новых соединений (гидрогалогенидов амидразонов - 3) на основе N-арилбензолкарбоксимидогидразидов определены возможные мишени для взаимодействия с производными амидразонов. Обоснована их важность в процессах жизнедеятельности исследуемых микроорганизмов. Выбраны мишени, которые могут являться целевыми для соединений класса...

AlphaFold 2 has revolutionized protein structure prediction, yet systematic evaluations of its performance against experimental structures for specific protein families remain limited. Here we present the first comprehensive analysis comparing AlphaFold 2-predicted and experimental nuclear receptor structures, examining root-mean-square deviations, secondary structure elements, domain organization, and ligand-binding pocket geometry. While AlphaFold2 achieves high accuracy in predicting stable conformations with proper stereochemistry, it shows limitations in capturing the full spectrum of biologically relevant states, particularly in flexible regions and ligand-binding pockets. Statistical analysis reveals significant domain-specific variations, with ligand-binding domains showing higher structural variability (CV = 29.3%) compared to DNA-binding domains (CV = 17.7%). Notably, Alphafold 2 systematically underestimates ligand-binding pocket volumes and captures only single conformational states in homodimeric receptors where experimental structures show functionally important asymmetry. These findings provide critical insights for structure-based drug design targeting nuclear receptors and establish a framework for evaluating Alphafold 2 predictions across other protein families.