Neuroepithelial organoid patterning is mediated by Wnt-driven Turing mechanism

AbstractCell patterning in epithelia is critical for the establishment of tissue function during development. The organization of patterns in these tissues is mediated by the interpretation of signals operating across multiple length scales. How epithelial tissues coordinate changes in cell identity across these length scales to orchestrate cellular rearrangements and fate specification remains poorly understood. Here, we use human neural tube organoids as model systems to interrogate epithelial patterning principles that guide domain specification. In silico modeling of the patterning process by cellular automata, validated by in vitro experiments, reveal that the initial positions of floor plate cells, coupled with activator-inhibitor signaling interactions, deterministically dictate the patterning outcome according to a discretized Turing reaction-diffusion mechanism. This model predicts an enhancement of organoid patterning by modulating inhibitor levels. Receptor-ligand interaction analysis of scRNAseq data from multiple organoid domains reveals WNT-pathway ligands as the specific inhibitory agents, thereby allowing for the experimental validation of model predictions. These results demonstrate that neuroepithelia employ reaction-diffusion-based mechanisms during early embryonic human development to organize cellular identities and morphogen sources to achieve patterning. The wider implementation of such in vitro organoid models in combination with in-silico agent-based modeling coupled to receptor-ligand analysis of scRNAseq data opens avenues for a broader understanding of dynamic tissue patterning processes.

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A step forward in the sigma enigma: a role for chirality in the sigma1 receptor–ligand interaction?

MedChemComm ◽

10.1039/c4md00349g ◽

2015 ◽

Vol 6 (1) ◽

pp. 138-146 ◽

Cited By ~ 9

Author(s):

Daniela Rossi ◽

Annamaria Marra ◽

Marta Rui ◽

Erik Laurini ◽

Maurizio Fermeglia ◽

...

Keyword(s):

In Silico ◽

Receptor Interaction ◽

Ligand Interaction ◽

Receptor Ligand ◽

Sigma1 Receptor

To investigate the role of chirality in the ligand–σ1 receptor interaction, a series of enantiomeric arylalkylaminoalcohols and arylpyrrolidinols was evaluated by means of both in silico and in vitro studies.

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In Silico Molecular Docking and Interaction Analysis of Traditional Chinese Medicines Against SARS-CoV-2 Receptor

Natural Product Communications ◽

10.1177/1934578x211015030 ◽

2021 ◽

Vol 16 (5) ◽

pp. 1934578X2110150

Author(s):

Gang Li ◽

Wei Zhou ◽

Xiurong Zhao ◽

Ying Xie

Keyword(s):

Molecular Docking ◽

In Silico ◽

Interaction Analysis ◽

Herbal Remedies ◽

Receptor Protein ◽

Stable Complex ◽

Traditional Chinese Medicines ◽

Ligand Interaction ◽

Chinese Medicines ◽

In Silico Molecular Docking

The novel coronavirus, 2019-nCoV, has led to a major pandemic in 2020 and is responsible for more than 2.9 million officially recorded deaths worldwide. As well as synthetic anti-viral drugs, there is also a need to explore natural herbal remedies. The Traditional Chinese Medicines (TCMs) system has been used for thousands of years for the prevention, diagnosis, and treatment of several chronic diseases. In this paper, we performed an in silico molecular docking and interaction analysis of TCMs against SARS-CoV-2 receptor RNA-dependent RNA polymerase (RdRp). We obtained the 5 most effective plant compounds which had a better binding affinity towards the target receptor protein. These compounds areforsythoside A, rutin, ginkgolide C, icariside II, and nolinospiroside E. The top-ranked compound, based on docking score, was nolinospiroside, a glycoside found in Ophiopogon japonicas that has antioxidant properties. Protein-ligand interaction analysis discerned that nolinospiroside formed a strong bond between ARG 349 of the protein receptor and the carboxylate group of the ligand, forming a stable complex. Hence, nolinospiroside could be deployed as a lead compound against SARS-CoV-2 infection that can be further investigated for its potential benefits in curbing the viral infection.

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Reaction-Diffusion Modeling of Photopolymerization During Femtosecond Projection Two-Photon Lithography

Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability ◽

10.1115/msec2021-60255 ◽

2021 ◽

Author(s):

Rushil Pingali ◽

Sourabh K. Saha

Keyword(s):

Diffusion Mechanism ◽

Chemical Properties ◽

Reaction Diffusion ◽

Element Model ◽

Polymerization Process ◽

Layer By Layer ◽

Length Scales ◽

Two Photon ◽

Reaction Diffusion Model ◽

Direct Laser

Abstract Two-photon lithography (TPL) is a polymerization-based direct laser writing process that is capable of fabricating arbitrarily complex three-dimensional (3D) structures with submicron features. Traditional TPL techniques have limited scalability due to the slow point-by-point serial writing scheme. The femtosecond projection TPL (FP-TPL) technique increases printing rate by a thousand times by enabling layer-by-layer parallelization. However, parallelization alters the time and the length scales of the underlying polymerization process. It is therefore challenging to apply the models of serial TPL to accurately predict process outcome during FP-TPL. To solve this problem, we have generated a finite element model of the polymerization process on the time and length scales relevant to FP-TPL. The model is based on the reaction-diffusion mechanism that underlies polymerization. We have applied this model to predict the geometry of nanowires printed under a variety of conditions and compared these predictions against empirical data. Our model accurately predicts the nanowire widths. However, accuracy of aspect ratio prediction is hindered by uncertain values of the chemical properties of the photopolymer. Nevertheless, our results demonstrate that the reaction-diffusion model can accurately capture the effect of controllable parameters on FP-TPL process outcome and can therefore be used for process control and optimization.

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An in vitro–in silico interface platform for spatiotemporal analysis of pattern formation in collective epithelial cells

Integrative Biology ◽

10.1039/c6ib00073h ◽

2016 ◽

Vol 8 (8) ◽

pp. 861-868 ◽

Cited By ~ 6

Author(s):

M. Hagiwara

Keyword(s):

Cell Culture ◽

Pattern Formation ◽

Epithelial Cells ◽

In Silico ◽

Reaction Diffusion ◽

Spatiotemporal Analysis ◽

Bronchial Epithelial ◽

Reaction Diffusion Model ◽

2D Pattern

The mechanisms of 2D pattern formation in bronchial epithelial cells were dynamically analyzed by controlled cell culture and a reaction-diffusion model.

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Structurally Selective Mechanism of Liver X Receptor Ligand: In Silico and In Vitro Studies

Journal of Chemical Information and Modeling ◽

10.1021/acs.jcim.9b00292 ◽

2019 ◽

Vol 59 (7) ◽

pp. 3277-3290 ◽

Cited By ~ 2

Author(s):

Peng Ding ◽

Ziyang Chen ◽

Hao Chen ◽

Zizhen Zhang ◽

Zhihong Liu ◽

...

Keyword(s):

In Silico ◽

Liver X Receptor ◽

In Vitro Studies ◽

Receptor Ligand ◽

Selective Mechanism

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Faculty Opinions recommendation of Prediction of brain:blood unbound concentration ratios in CNS drug discovery employing in silico and in vitro model systems.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.732870171.793554459 ◽

2018 ◽

Author(s):

Peter R Bernstein

Keyword(s):

Drug Discovery ◽

In Silico ◽

In Vitro Model ◽

Model Systems ◽

Unbound Concentration ◽

Vitro Model ◽

Concentration Ratios

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Identification of Chinese Herbal Compounds with Potential as JAK3 Inhibitors

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2019/4982062 ◽

2019 ◽

Vol 2019 ◽

pp. 1-11 ◽

Cited By ~ 2

Author(s):

Dan Su ◽

Yu-Qiao Gao ◽

Yong-Jie Deng ◽

Han-Hui Zhang ◽

You-Ru Wu ◽

...

Keyword(s):

Inhibitory Activity ◽

Tyrosine Kinases ◽

Interaction Analysis ◽

Inflammatory Diseases ◽

Ligand Interaction ◽

Hek 293 ◽

Acquired Drug Resistance ◽

Chinese Herbal ◽

Protein Ligand Interaction

The Janus kinases (JAKs) consist of four similar tyrosine kinases and function as key hubs in the signaling pathways that are implicated in both innate and adaptive immunity. Among the four members, JAK3 is probably the more attractive target for treatment of inflammatory diseases because its inhibition demonstrates the greatest immunosuppression and most profound effect in the treatment of such disorders. Although many JAK3 inhibitors are already available, certain shortcomings have been identified, mostly acquired drug resistance or unwanted side effects. To discover and identify new promising lead candidates, in this study, the structure of JAK3 (3LXK) was obtained from the Protein Data Bank and used for simulation modeling and protein-ligand interaction analysis. The ~36,000 Chinese herbal compounds obtained from TCM Database@Taiwan were virtually screened by AutoDock Vina docking program and filtered with Lipinski’s Rules and ADME/T virtual predictions. Because of high occurrence of fake hits during docking, we selected 12 phytochemicals which have demonstrated modulating JAKs expressions among the top 50 chemicals from docking results. To validate whether these compounds are able to directly mediate JAK3 kinase, we have investigated the inhibitory activity using enzymatic activity assays, western blot, and HEK 293 cell STAT5 transactivity assays. The molecular analysis included docking and molecular dynamics (MD) simulations in order to investigate structural conformations and to explore the key amino acids in the interaction between JAK3 kinase and its putative ligands. The results demonstrated that Cryptotanshinone, Icaritin, and Indirubin exhibited substantial inhibitory activity against JAK3 kinase in vitro. The results also provide binding models of the protein-ligand interaction, detailing the interacting amino acid residues at the active ATP-binding domains of JAK3 kinase. In conclusion, our work discovered 3 potential natural inhibitors of JAK3 kinase and could provide new possibilities and stimulate new insights for the treatment of JAK3-targeted diseases.

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CISSAMPELOS PAREIRA: PROTEIN-LIGAND DOCKING TO IDENTIFY SUITABLE TARGETS FOR HEPATOCELLULAR CARCINOMA (HCC) BY IN-SILICO TECHNIQUES AND TOOLS

Jurnal Teknologi ◽

10.11113/jt.v77.5982 ◽

2015 ◽

Vol 77 (2) ◽

Author(s):

B. Samuel Thavamani ◽

Molly Mathew ◽

Dhanabal S. Palaniswamy

Keyword(s):

Hepatocellular Carcinoma ◽

Growth Factor ◽

In Silico ◽

B Cell Lymphoma ◽

Aurora Kinase ◽

Pharmacological Action ◽

Ligand Docking ◽

Ligand Interaction

Protein-ligand interaction plays a major role in identification of the possible mechanism by which a ligand can bind with the target and exerts the pharmacological action. The present study aims to identify new possible candidates for treating Hepatocellular Carcinoma (HCC) by docking the reported phytochemicals present in Cissampelos pareira with the well known HCC targets using in-silico techniques. Although C. pareira demonstrated in vitro and in vivo anti-heptatocellular carcinoma activities, the mechanism remains uncertain. Selected compounds from C. pareira were docked using GLIDE software with known targets of hepatocellular carcinoma viz. Aurora Kinase, c-Kit, Fibroblast Growth Factor (FGF), Nuclear Factor kappa B (NF-kB), B-cell lymphoma-extra large (Bcl-xL) and Vascular Endothelial Growth Factor (VEGF). Among the compounds docked, pareitropone and pareirubrine B exhibited good hydrogen bonding interactions and binding energy with the targets of HCC taken in the study. Hence these compounds deserve consideration for further studies towards HCC.

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