Biology subjects

Simonyan, A.

Publications and source records attributed to Simonyan, A..

4 recordsLinked to original sources

bioRxiv2026

Extraocular Electrical Stimulation Activates Retinal Ganglion Cells In Vivo

Objective: Here, we directly demonstrate that extraocular electrical stimulation can reliably activate retinal ganglion cells (RGCs) in vivo and systematically identify optimal stimulation waveforms that maximize RGC activation at tolerable amplitudes. Approach: Using transpupillary two-photon calcium imaging in Thy1-GCaMP6f rats, we directly visualized RGC activation during extraocular electrical stimulation with single-cell resolution. We tested symmetric (SCB 1:1) and asymmetric (ACB 1:4) charge-balanced waveforms across frequencies ranging from 20 to 5,000 Hz and amplitudes from 1 to 300 uA, correlating cellular calcium responses with behavioral outcomes during awake stimulation. Main Results: ACB 1:4 stimulation at lower frequencies (20-50 Hz) robustly and reliably activates RGC somas in vivo, producing larger calcium responses at lower amplitudes than SCB 1:1. At comparable amplitudes, ACB stimulation generated 1.8-fold greater calcium responses. In contrast, SCB stimulation required higher amplitudes that exceeded animal tolerance before reliable RGC activation could be achieved. Significance: These findings provide direct evidence that extraocular electrodes can reliably activate RGCs in vivo. Notably, stimulation parameters previously associated with full-length optic nerve regeneration were found to be minimally effective at activating RGCs in vivo, suggesting increased gains could be had with newer approaches. The results further demonstrate that waveform asymmetry improves the efficiency of optic nerve stimulation by engaging RGC somas at lower, more tolerable, amplitudes. By combining two-photon imaging with behavioral tolerance testing, this work defines a practical therapeutic window for extraocular stimulation of the eye and establishes asymmetric charge-balanced waveforms as a more clinically translatable strategy for visual pathway neuromodulation.

bioengineering↗

bioRxiv2026

Overcoming the accuracy-generalization tradeoff in docking and scoring for prospective virtual screening

Virtual screening promises access to tens of billions of synthetically accessible, diverse compounds, yet it is rarely used as a primary hit-discovery strategy in contemporary drug-discovery campaigns. We argue that this gap reflects the real-world underperformance of the underlying docking and scoring methods: classical docking is generalizable but limited in accuracy by simple functional forms and parsimonious parameterization, whereas recent machine-learning approaches are highly expressive but do not generalize well to novel molecules and pockets, their reported accuracy often inflated by train-test leakage. To address these challenges, we introduce DODock and DOScore, docking and scoring ML/physics hybrid frameworks that are also highly expressive, yet generalize much better out of distribution compared with the prior ML approaches. This generalization has been prospectively tested in several ways. First, DODocks blind prediction of a drug candidate binding to PCSK9 was compared to the crystal structure that was subsequently solved, recovering the binding pose to 1.2 [A] RMSD. We also used DODock and DOScore in prospective virtual screening campaigns against four therapeutic targets, spanning an ectoenzyme (CD73), a kinase (IRAK4), an extended-substrate protease (FXI), and an allosteric inhibition of protein-protein interface (IL17). These screens yielded many chemically novel, biochemically and cellularly active inhibitors. In the case of CD73, which is a historically challenging target for virtual screening, our screen resulted in a roughly hundredfold improvement in hit rate over a recent machine-learning screen. Our results indicate that the apparent ceiling in the accuracy of virtual screening that seemed to have somewhat plateaued in the last two decades is not fundamental, and that structure-based interrogation of ultralarge chemical space may eventually become a credible primary route to novel chemical matter.

biophysics↗

bioRxiv2021

Telomere maintenance pathway activity analysis enables tissue- and gene-level inferences

Telomere maintenance is one of the mechanisms ensuring indefinite divisions of cancer and stem cells. Good understanding of telomere maintenance mechanisms (TMM) is important for studying cancers and designing therapies. However, molecular factors triggering selective activation of either the telomerase dependent (TEL) or the alternative lengthening of telomeres (ALT) pathway are poorly understood. In addition, more accurate and easy-to-use methodologies are required for TMM phenotyping. In this study, we have performed literature based reconstruction of signaling pathways for the ALT and TEL TMMs. Gene expression data were used for computational assessment of TMM pathway activities and compared with experimental assays for TEL and ALT. Explicit consideration of pathway topology makes bioinformatics analysis more informative compared to computational methods based on simple summary measures of gene expression. Application to healthy human tissues showed high ALT and TEL pathway activities in testis, and identified genes and pathways that may trigger TMM activation. Our approach offers a novel option for systematic investigation of TMM activation patterns across cancers and healthy tissues for dissecting pathway-based molecular markers with diagnostic impact.

bioinformatics↗

bioRxiv2019

Regulatory Feedbacks on Receptor and Non-receptor Synthesis for Robust Signaling

Elaborate feedback regulatory processes are thought to make biological developments robust, i.e., resistant to changes induced by genetic or environmental perturbations. How this might be done is still not completely understood. Previous numerical simulations on reaction-diffusion models of Dpp gradients in Drosophila wing imaginal disc showed that feedback (of the Hills function type) on (signaling) receptors and/or non-(signaling) receptors are of limited effectiveness in promoting robustness. Spatial nonuniformity of the feedback processes is thought to lead to serious shape distortion and a principal cause for ineffectiveness. Through mathematical modeling of a spatially uniform nonlocal feedback mechanism, the present paper provides a theoretical support of these observations. More significantly, the new approach also enables us to uncover in this paper a new, theory-based multi-feedback instrument for broadly effective promotion of robust signaling gradients.

developmental biology↗