Computational modelling of trans-synaptic nanocolumns, a modulator of synaptic transmission

AbstractNanocolumns are trans-synaptic structures which align presynaptic vesicles release sites and postsynaptic receptors. However, how these nano structures shape synaptic signaling remains little understood. Given the difficulty to probe submicroscopic structures experimentally, computer modelling is a usefull approach to investigate the possible functional impacts of nanocolumns. In our in silico model, as has been experimentally observed, a nanocolumn is characterized by a tight distribution of postsynaptic receptors aligned with the presynaptic vesicle release site and by the presence of trans-synaptic molecules which can modulate neurotransmitter diffusion. We found that nanocolumns can play an important role in reinforcing synaptic current mostly when the presynaptic vesicle contains a small number of neurotransmitters. We also show that synapses with and without nanocolumns could have differentiated responses to spontaneous or evoked events. Our work provides a new methodology to investigate in silico the role of the submicroscopic organization of the synapse.Author summaryNeurotransmitter release, diffusion, and binding to postsynaptic receptors are key steps in synaptic transmission. However, the submicroscopic arrangement of receptors and presynaptic sites of neurotransmitter release remains little investigated. Experimental observations revealed the presence of trans-synaptic nanocolumns which span both the pre and post synaptic sites and fine tune the position of the post synaptic receptors. The functional impact of these nanocolumns (i.e. their influence on synaptic current) is both little understood and difficult to investigate experimentally. Here we construct a novel in silico model to investigate the functional impact of nanocolumns and show that they could play a functional role in reinforcing weak synapses.

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LGI1–ADAM22–MAGUK configures transsynaptic nanoalignment for synaptic transmission and epilepsy prevention

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2022580118 ◽

2021 ◽

Vol 118 (3) ◽

pp. e2022580118

Author(s):

Yuko Fukata ◽

Xiumin Chen ◽

Satomi Chiken ◽

Yoko Hirano ◽

Atsushi Yamagata ◽

...

Keyword(s):

Synaptic Transmission ◽

Ampa Receptors ◽

Neurotransmitter Release ◽

Epileptic Encephalopathy ◽

Secreted Protein ◽

Gene Products ◽

Molecular Identity ◽

Postsynaptic Receptors ◽

Epilepsy Gene ◽

The Brain

Physiological functioning and homeostasis of the brain rely on finely tuned synaptic transmission, which involves nanoscale alignment between presynaptic neurotransmitter-release machinery and postsynaptic receptors. However, the molecular identity and physiological significance of transsynaptic nanoalignment remain incompletely understood. Here, we report that epilepsy gene products, a secreted protein LGI1 and its receptor ADAM22, govern transsynaptic nanoalignment to prevent epilepsy. We found that LGI1–ADAM22 instructs PSD-95 family membrane-associated guanylate kinases (MAGUKs) to organize transsynaptic protein networks, including NMDA/AMPA receptors, Kv1 channels, and LRRTM4–Neurexin adhesion molecules. Adam22ΔC5/ΔC5 knock-in mice devoid of the ADAM22–MAGUK interaction display lethal epilepsy of hippocampal origin, representing the mouse model for ADAM22-related epileptic encephalopathy. This model shows less-condensed PSD-95 nanodomains, disordered transsynaptic nanoalignment, and decreased excitatory synaptic transmission in the hippocampus. Strikingly, without ADAM22 binding, PSD-95 cannot potentiate AMPA receptor-mediated synaptic transmission. Furthermore, forced coexpression of ADAM22 and PSD-95 reconstitutes nano-condensates in nonneuronal cells. Collectively, this study reveals LGI1–ADAM22–MAGUK as an essential component of transsynaptic nanoarchitecture for precise synaptic transmission and epilepsy prevention.

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Computer-Aided Discovery in Antimicrobial Research: In Silico Model for Virtual Screening of Potent and Safe Anti-Pseudomonas Agents

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207318666150305144249 ◽

2015 ◽

Vol 18 (3) ◽

pp. 305-314 ◽

Cited By ~ 13

Author(s):

Alejandro Speck-Planche ◽

Maria Cordeiro

Keyword(s):

Virtual Screening ◽

In Silico ◽

In Silico Model ◽

Computer Aided

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Usefulness of collaboration between mathematical models and cell engineering for elucidating complex disease mechanisms and discover effective drugs

European Heart Journal ◽

10.1093/ehjci/ehaa946.3600 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

H Kohjitani ◽

A Kashiwa ◽

T Makiyama ◽

F Toyoda ◽

Y Yamamoto ◽

...

Keyword(s):

Mathematical Model ◽

In Silico ◽

Complex Disease ◽

Ion Selectivity ◽

Public Institution ◽

Cell Engineering ◽

Funding Source ◽

Patch Clamp Technique ◽

In Silico Model

Abstract Background A missense mutation, CACNA1C-E1115K, located in the cardiac L-type calcium channel (LTCC), was recently reported to be associated with diverse arrhythmias. Several studies reported in-vivo and in-vitro modeling of this mutation, but actual mechanism and target drug of this disease has not been clarified due to its complex ion-mechanisms. Objective To reveal the mechanism of this diverse arrhythmogenic phenotype using combination of in-vitro and in-silico model. Methods and results Cell-Engineering Phase: We generated human induced pluripotent stem cell (hiPSC) from a patient carrying heterozygous CACNA1C-E1115K and differentiated into cardiomyocytes. Spontaneous APs were recorded from spontaneously beating single cardiomyocytes by using the perforated patch-clamp technique. Mathematical-Modeling Phase: We newly developed ICaL-mutation mathematical model, fitted into experimental data, including its impaired ion selectivity. Furthermore, we installed this mathematical model into hiPSC-CM simulation model. Collaboration Phase: Mutant in-silico model showed APD prolongation and frequent early afterdepolarization (EAD), which are same as in-vitro model. In-silico model revealed this EAD was mostly related to robust late-mode of sodium current occurred by Na+ overload and suggested that mexiletine is capable of reducing arrhythmia. Afterward, we applicated mexiletine onto hiPSC-CMs mutant model and found mexiletine suppress EADs. Conclusions Precise in-silico disease model can elucidate complicated ion currents and contribute predicting result of drug-testing. Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): Japan Society for the Promotion of Science, Grant-in-Aid for Young Scientists

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A corneal-PAMPA-based in silico model for predicting corneal permeability

Journal of Pharmaceutical and Biomedical Analysis ◽

10.1016/j.jpba.2021.114218 ◽

2021 ◽

pp. 114218

Author(s):

Anna Vincze ◽

Gergö Dargó ◽

Anita Rácz ◽

György T. Balogh

Keyword(s):

In Silico ◽

Corneal Permeability ◽

In Silico Model

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Initial mechanical conditions within an optimized bone scaffold do not ensure bone regeneration – an in silico analysis

Biomechanics and Modeling in Mechanobiology ◽

10.1007/s10237-021-01472-2 ◽

2021 ◽

Author(s):

Camille Perier-Metz ◽

Georg N. Duda ◽

Sara Checa

Keyword(s):

Bone Regeneration ◽

In Silico ◽

Volume Fraction ◽

Computer Modelling ◽

Mechanical Strain ◽

In Silico Analysis ◽

Bone Volume ◽

Mechanical Stimuli ◽

Design Strategies ◽

Scaffold Design

AbstractLarge bone defects remain a clinical challenge because they do not heal spontaneously. 3-D printed scaffolds are a promising treatment option for such critical defects. Recent scaffold design strategies have made use of computer modelling techniques to optimize scaffold design. In particular, scaffold geometries have been optimized to avoid mechanical failure and recently also to provide a distinct mechanical stimulation to cells within the scaffold pores. This way, mechanical strain levels are optimized to favour the bone tissue formation. However, bone regeneration is a highly dynamic process where the mechanical conditions immediately after surgery might not ensure optimal regeneration throughout healing. Here, we investigated in silico whether scaffolds presenting optimal mechanical conditions for bone regeneration immediately after surgery also present an optimal design for the full regeneration process. A computer framework, combining an automatic parametric scaffold design generation with a mechano-biological bone regeneration model, was developed to predict the level of regenerated bone volume for a large range of scaffold designs and to compare it with the scaffold pore volume fraction under favourable mechanical stimuli immediately after surgery. We found that many scaffold designs could be considered as highly beneficial for bone healing immediately after surgery; however, most of them did not show optimal bone formation in later regenerative phases. This study allowed to gain a more thorough understanding of the effect of scaffold geometry changes on bone regeneration and how to maximize regenerated bone volume in the long term.

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