Schizophrenia (SZ) is a prevalent functional psychosis characterized by clinical behavioural symptoms and underlying abnormalities in brain function. Genome-wide association studies (GWAS) of schizophrenia have revealed many loci that do not directly identify processes disturbed in the disease. For this reason, the development of cellular models containing SZ-associated variations has become a focus in the post-GWAS research era. The application of revolutionary clustered regularly interspaced palindromic repeats CRISPR/Cas9 gene-editing tools, along with recently developed technologies for cultivating brain organoids in vitro, have opened new perspectives for the construction of these models. In general, cellular models are intended to unravel particular biological phenomena. They can provide the missing link between schizophrenia-related phenotypic features (such as transcriptional dysregulation, oxidative stress and synaptic dysregulation) and data from pathomorphological, electrophysiological and behavioural studies. The objectives of this review are the systematization and classification of cellular models of schizophrenia, based on their complexity and validity for understanding schizophrenia-related phenotypes.

Schizophrenia (SZ) is a common psychiatric neurodevelopmental disorder with a complex genetic architecture. Genome-wide association studies indicate the involvement of several transcription factors, including ASCL1, in the pathogenesis of SZ. We aimed to identify ASCL1-dependent cellular and molecular mechanisms associated with SZ. We used Capture-C, CRISPR/Cas9 systems and RNA-seq analysis to confirm the involvement of ASCL1 in SZ-associated pathogenesis, establish a mutant SH-SY5Y line with a functional ASCL1 knockout (ASCL1-del) and elucidate differentially expressed genes that may underlie ASCL1-dependent pathogenic mechanisms. Capture-C confirmed the spatial interaction of the ASCL1 promoter with SZ-associated loci. Transcriptome analysis showed that ASCL1 regulation may be through a negative feedback mechanism. ASCL1 dysfunction affects the expression of genes associated with the pathogenesis of SZ, as well as bipolar and depressive disorders. Genes differentially expressed in ASCL1-del are involved in cell mitosis, neuronal projection, neuropeptide signaling, and the formation of intercellular contacts, including the synapse. After retinoic acid (RA)-induced differentiation, ASCL1 activity is restricted to a small subset of genes involved in neuroplasticity. These data suggest that ASCL1 dysfunction promotes SZ development predominantly before the onset of neuronal differentiation by slowing cell proliferation and impeding the formation of neuronal signatures.

Neuropsychiatric diseases are characterized by complex molecular underpinnings that remain challenging to fully elucidate. Molecular dynamics (MD) simulations have emerged as a powerful computational tool, providing a crucial bridge between static genetic data and the dynamic functional consequences of molecular alterations. This review offers a comprehensive overview of the application of MD simulations in studying the molecular basis of neuropsychiatric disorders. We highlight key applications, including the assessment of mutation pathogenicity in disease-associated proteins, the influence of post-translational modifications on protein function, folding, misfolding, and aggregation, and the characterization of psychopharmacological drug–target interactions at atomic resolution. Through relevant examples from research on psychiatric and neurodegenerative diseases, we illustrate how these computational methods are implemented to gain mechanistic insights. Importantly, this review traces the historical development of MD simulations in biological applications, critically examines the method’s limitations, and outlines future perspectives for simulating long-timescale physiological processes, large molecular ensembles, and even whole-cell environments. Ultimately, this work highlights MD simulations as a useful and complementary tool for modern neuropsychiatry research, capable of revealing disease mechanisms and guiding the development of novel therapeutic strategies.

Bang sensitivity (BS) is a well-characterized seizure-and-paralysis phenotype in Drosophila melanogaster, but its genetic basis remains unexamined in the phylogenetically distant sister species Drosophila funebris. Here, we identify a naturally occurring BS strain in D. funebris from a wild population near Lake Valday, characterized by acute mechanical shock-induced seizures and paralysis, and examine its molecular-genetic and lipidomic basis. Comparative transcriptomics identified 241 differentially expressed genes (FDR-adjusted p < 0.05), with “fatty acid metabolic process” as the most enriched GO term. Notably, within this pathway, the peroxisomal acyl-CoA oxidase gene Acox57D-d showed the most significant downregulation (log₂FC = −4.21, p_adj = 4.1 × 10⁻¹¹⁰), validated by head-specific RT-qPCR. Untargeted lipidomics of BS heads (LC-Q-TOF-MS) revealed 145 altered lipid species, dominated by oxygenated triacylglycerol accumulation, cardiolipin/phosphatidylethanolamine depletion, and a divergent shift—depletion of DG 29:0 and accumulation of DG 47:4, reflecting impaired peroxisomal β-oxidation and potential mitochondrial and Na⁺/K⁺-ATPase dysfunction. These findings nominate Acox57D-d as a leading candidate gene associated with the phenotype and molecular signature of the studied BS line and establish this natural BS strain as a potentially useful model for investigating the relationship between peroxisomal lipid metabolism, neuronal excitability, and insect thanatosis.