scholarly journals Combined in silico, ex vivo, and in vivo Assessment of L-17, a Thiadiazine Derivative With Putative Neuroprotective and Antidepressant-Like Effects

2021 ◽  
Author(s):  
Alexey Sarapultsev ◽  
Pavel Vassiliev ◽  
Daniil Grinchii ◽  
Alexander Kiss ◽  
Mojmír Mach ◽  
...  
Keyword(s):  
Reuptake Inhibitor ◽  
In Silico ◽  
Ex Vivo ◽  
Brain Area ◽  
Antidepressant Drugs ◽  
Neural Mechanism ◽  
Central Nucleus ◽  
In Vivo Electrophysiology ◽  
In Silico Predictions

L-17 is a thiadiazine derivative with putative anti-inflammatory, neuroprotective, and antidepressant-like properties. In this study, we applied combined in silico, ex vivo, and in vivo electrophysiology techniques to reveal the potential mechanism of action of L-17. PASS 10.4 Professional Extended software suggested that L-17 might have pro-cognitive, antidepressant, and antipsychotic effects. Docking energy assessment with AutoDockVina predicted that the binding affinities of L-17 to the serotonin transporter (SERT) and serotonin receptors 3 and 1A (5-HT3 and 5-HT1A) receptors are compatible to the selective serotonin reuptake inhibitor (SSRI) fluoxetine and selective antagonists of 5-HT3 and 5-HT1A receptors, granisetron and WAY100135, respectively. Acute pre-treatment with L-17 robustly increased c-Fos immunoreactivity in the amygdala (central nucleus), suggesting increased neuronal excitability in this brain area after L-17 administration. Acute L-17 also dose-dependently inhibited of 5-HT neurons of the dorsal raphe nucleus (DRN). This inhibition was partially reversed by subsequent administration of WAY100135, suggesting the involvement of extracellular 5-HT. Based on in silico predictions, c-Fos immunohistochemistry, and in vivo electrophysiology, we suggest that L-17 is a potent 5-HT reuptake inhibitor and/or partial 5-HT1A receptor antagonist. Thus, L-17 might be a representative of a new class of antidepressant drugs. Since L-17 also possesses neuro- and cardio-protective properties, it can be useful in post-stroke and post-myocardial infarction (MI) depression. In general, combined in silico predictions and ex vivo neurochemical and in vivo electrophysiological assessment might be a useful strategy for early preclinical assessment of the affectivity and neural mechanism in action of the novel CNS drugs.

scholarly journals In Silico and In Vivo Assessment of L-17, a Thiadiazine Derivative with Putative Serotonin Reuptake Properties

2021 ◽  
Author(s):  
Alexey Sarapultsev ◽  
Pavel Vassiliev ◽  
Daniil Grinchii ◽  
Ruslan Paliokha ◽  
Andrey Kochetkov ◽  
...  
Keyword(s):  
Reuptake Inhibitor ◽  
In Silico ◽  
Serotonin Reuptake ◽  
Medical Condition ◽  
Partial Agonist ◽  
Antidepressant Drugs ◽  
Acute Administration ◽  
In Vivo Electrophysiology ◽  
General Medical Condition

L-17 is a thiadiazine derivative with putative anti-inflammatory, neuroprotective, and antidepressant-like properties. In this study, we applied combined in silico and in vivo electrophysiology techniques to reveal the potential mechanism of action of L-17. PASS 10.4 Professional Extended software suggested that L-17 might have pro-cognitive, antidepressant, and antipsychotic effects. Docking energy assessment with AutoDockVina predicted that the binding affinities of L-17 to the serotonin transporter (SERT) and serotonin receptors 3 and 1A (5-HT3 and 5-HT1A) are compatible to the selective serotonin reuptake inhibitor (SSRI) fluoxetine and selective antagonists of 5-HT3 and 5-HT1A receptors, granisetron and WAY100135, respectively. However, while the binding mechanisms of L-17 to the SERT and 5-HT1A receptor were similar to fluoxetine and WAY100135, its interacting with 5-HT3 receptor might be substantially different from this of granisetron. Acute administration of L-17 led to dose-dependent inhibition of firing activity of 5-HT neurons of the dorsal raphe nucleus. This inhibition was partially reversed by subsequent administration of WAY100135. Based on both in silico and in vivo electrophysiology assessments, we suggest that L-17 is a potent 5-HT reuptake inhibitor and a putative partial agonist of 5-HT1A receptors. As such, L-17 in particular and thiadiazine derivatives, in general, might be a representative of a new class of antidepressant drugs. Since L-17 also possesses neuro- and cardioprotective properties, it can be useful in affective illness developing due to the general medical condition, such as post-stroke and post-myocardial infarction (MI) depression.

scholarly journals Combined In Silico, Ex Vivo, and In Vivo Assessment of L-17, a Thiadiazine Derivative with Putative Neuro- and Cardioprotective and Antidepressant Effects

2021 ◽  
Vol 22 (24) ◽  
pp. 13626
Author(s):  
Alexey Sarapultsev ◽  
Pavel Vassiliev ◽  
Daniil Grinchii ◽  
Alexander Kiss ◽  
Mojmir Mach ◽  
...  
Keyword(s):  
Mechanism Of Action ◽  
In Silico ◽  
Neuronal Excitability ◽  
Medical Condition ◽  
Ex Vivo ◽  
Treatment Strategies ◽  
Neural Mechanism ◽  
Special Treatment ◽  
Early Assessment

Depression associated with poor general medical condition, such as post-stroke (PSD) or post-myocardial infarction (PMID) depression, is characterized by resistance to classical antidepressants. Special treatment strategies should thus be developed for these conditions. Our study aims to investigate the mechanism of action of 2-morpholino-5-phenyl-6H-1,3,4-thiadiazine, hydrobromide (L-17), a recently designed thiadiazine derivative with putative neuro- and cardioprotective and antidepressant-like effects, using combined in silico (for prediction of the molecular binding mechanisms), ex vivo (for assessment of the neural excitability using c-Fos immunocytochemistry), and in vivo (for direct examination of the neuronal excitability) methodological approaches. We found that the predicted binding affinities of L-17 to serotonin (5-HT) transporter (SERT) and 5-HT3 and 5-HT1A receptors are compatible with selective 5-HT serotonin reuptake inhibitors (SSRIs) and antagonists of 5-HT3 and 5-HT1A receptors, respectively. L-17 robustly increased c-Fos immunoreactivity in the amygdala and decreased it in the hippocampus. L-17 dose-dependently inhibited 5-HT neurons of the dorsal raphe nucleus; this inhibition was partially reversed by the 5-HT1A antagonist WAY100135. We suggest that L-17 is a potent 5-HT reuptake inhibitor and partial antagonist of 5-HT3 and 5-HT1A receptors; the effects of L-17 on amygdaloid and hippocampal excitability might be mediated via 5-HT, and putatively mediate the antidepressant-like effects of this drug. Since L-17 also possesses neuro- and cardioprotective properties, it can be beneficial in PSD and PMID. Combined in silico predictions with ex vivo neurochemical and in vivo electrophysiological assessments might be a useful strategy for early assessment of the efficacy and neural mechanism of action of novel CNS drugs.

scholarly journals In Silico Predicted Antifungal Peptides: In Vitro and In Vivo Anti-Candida Activity

2021 ◽  
Vol 7 (6) ◽  
pp. 439
Author(s):  
Tecla Ciociola ◽  
Walter Magliani ◽  
Tiziano De Simone ◽  
Thelma A. Pertinhez ◽  
Stefania Conti ◽  
...  
Keyword(s):  
In Silico ◽  
Mammalian Cells ◽  
Galleria Mellonella ◽  
Ex Vivo ◽  
Consensus Sequence ◽  
In Silico Analysis ◽  
Significant Activity ◽  
Synthetic Antibody

It has been previously demonstrated that synthetic antibody-derived peptides could exert a significant activity in vitro, ex vivo, and/or in vivo against microorganisms and viruses, as well as immunomodulatory effects through the activation of immune cells. Based on the sequence of previously described antibody-derived peptides with recognized antifungal activity, an in silico analysis was conducted to identify novel antifungal candidates. The present study analyzed the candidacidal and structural properties of in silico designed peptides (ISDPs) derived by amino acid substitutions of the parent peptide KKVTMTCSAS. ISDPs proved to be more active in vitro than the parent peptide and all proved to be therapeutic in Galleria mellonella candidal infection, without showing toxic effects on mammalian cells. ISDPs were studied by circular dichroism spectroscopy, demonstrating different structural organization. These results allowed to validate a consensus sequence for the parent peptide KKVTMTCSAS that may be useful in the development of novel antimicrobial molecules.

Synthesis and characterization of Chitosan-Catechol conjugates: Development and in vitro, in silico and in vivo evaluation of mucoadhesive pellets of lafutidine

2021 ◽  
pp. 088391152199784
Author(s):  
Loveleen Kaur ◽  
Ajay Kumar Thakur ◽  
Pradeep Kumar ◽  
Inderbir Singh
Keyword(s):  
Drug Release ◽  
In Silico ◽  
Ex Vivo ◽  
Strong Interactions ◽  
Dissolution Time ◽  
Sem Images ◽  
In Vivo Evaluation ◽  
Release Studies

Present study was aimed to synthesize and characterize Chitosan-Catechol conjugates and to design and develop mucoadhesive pellets loaded with lafutidine. SEM images indicated the presence of fibrous structures responsible for enhanced mucoadhesive potential of Chitosan-Catechol conjugates. Thermodynamic stability and amorphous nature of conjugates was confirmed by DSC and XRD studies respectively. Rheological studies were used to evaluate polymer mucin interactions wherein strong interactions between Chitosan-Catechol conjugate and mucin was observed in comparison to pristine chitosan and mucin. The mucoadhesion potential of Chitosan-Catechol (Cht-C) versus Chitosan (Cht) was assessed in silico using molecular mechanics simulations and the results obtained were compared with the in vitro and ex vivo results. Cht-C/mucin demonstrated much higher energy stabilization (∆E ≈ −65 kcal/mol) as compared to Cht/mucin molecular complex. Lafutidine-loaded pellets were prepared from Chitosan (LPC) and Chitosan-Catechol conjugates (LPCC) and were evaluated for various physical properties viz. flow, circularity, roundness, friability, drug content, particle size and percent mucoadhesion. In vitro drug release studies on LPC and LPCC pellets were performed for computing t50%, t90% and mean dissolution time. The values of release exponent from Korsmeyer-Peppas model was reported to be 0.443 and 0.759 for LPC and LPCC pellets suggesting Fickian and non-Fickian mechanism representing drug release, respectively. In vivo results depicted significant controlled release and enhanced residence of the drug after being released from the chitosan-catechol coated pellets. Chitosan-Catechol conjugates were found to be a promising biooadhesive polymer for the development of various mucoadhesive formulations.

scholarly journals 248 Empiric profiling of peripheral T cell recall responses to tumor mutanomes versus in silico predictions in NSCLC patients undergoing pembrolizumab treatment ± chemotherapy

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A268-A268
Author(s):  
Madison Milaszewski ◽  
James Loizeaux ◽  
Emily Tjon ◽  
Crystal Cabral ◽  
Tulin Dadali ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Combination Therapy ◽  
In Silico ◽  
Ex Vivo ◽  
T Cell Responses ◽  
Patient Specific ◽  
In Silico Prediction ◽  
Cell Responses ◽  
In Silico Predictions

BackgroundEffective immune checkpoint blockade (ICB) treatment is dependent on T-cell recognition of patient-specific mutations (neoantigens). Empirical identification of neoantigens ex vivo has revealed shortcomings of in silico predictions.1 To better understand the impact of ICB treatment on T cell responses and differences between in silico and in vitro methods, neoantigen-specific T cell responses were evaluated in patients with non-small cell lung cancer undergoing first-line therapy with pembrolizumab ± chemotherapy.MethodsTumor and whole blood samples were collected from 14 patients prior to and after immunotherapy; seven each in monotherapy and combination therapy cohorts. The ex vivo ATLAS™ platform was used to profile neoantigen-specific T-cell responses. Patient-specific tumor mutations identified by next-generation sequencing (NGS) were expressed individually as ATLAS clones, processed patient-specific autologous antigen presenting cells, and presented to their T cells in vitro. ATLAS-verified antigens were compared with epitope predictions made using algorithms.ResultsOn average, 150 (range 37–339) non-synonymous mutations were identified. Pre-treatment, ATLAS identified T cell responses to a median of 15% (9–25%) of mutations, with nearly equal proportions of neoantigens (8%, 5–15%) and Inhibigens™, targets of suppressive T cell responses (8%, 3–13%). The combination therapy cohort had more confirmed neoantigens (46, 20–103) than the monotherapy cohort (7, 6–79). After treatment, the median ratio of CD4:CD8 T cells doubled in the monotherapy but not combination cohort (1.2 to 2.4 v. 1.6 to 1.3). Upon non-specific stimulation, T cells from patients on combination therapy expanded poorly relative to monotherapy (24 v. 65-fold, p = 0.014); no significant differences were observed pre-treatment (22 v. 18-fold, p = 0.1578). Post-treatment, the median number of CD8 neoantigens increased in the combination therapy cohort (11 to 15) but in monotherapy were mostly unchanged (6 to 7). Across timepoints, 36% of ATLAS-identified responses overlapped. In silico analysis resulted in 1,895 predicted epitopes among 961 total mutations; among those, 30% were confirmed with ATLAS, although nearly half were Inhibigens, which could not be predicted. Moreover, 50% of confirmed neoantigens were missed by in silico prediction.ConclusionsMonotherapy and combination therapy had differential effects on CD4:CD8 T cell ratios and their non-specific expansion. A greater proportion of neoantigens was identified than previously reported in studies employing in silico predictions prior to empirical verification.2 Overlap between confirmed antigens and in silico prediction was observed, but in silico prediction continued to have a large false negative rate and could not characterize Inhibigens.AcknowledgementsWe would like to acknowledge and thank the patients and their families for participating in this study.ReferencesLam H, McNeil LK, Starobinets H, DeVault VL, Cohen RB, Twardowski P, Johnson ML, Gillison ML, Stein MN, Vaishampayan UN, DeCillis AP, Foti JJ, Vemulapalli V, Tjon E, Ferber K, DeOliveira DB, Broom W, Agnihotri P, Jaffee EM, Wong KK, Drake CG, Carroll PM, Davis TA, Flechtner JB. An empirical antigen selection method identifies neoantigens that either elicit broad antitumor T-cell responses or drive tumor growth. Cancer Discov 2021;11(3):696–713. doi: 10.1158/2159- 8290.CD-20-0377. Epub 2021 January 27. PMID: 33504579. Rosenberg SA. Immersion in the search for effective cancer immunotherapies. Mol Med 27,63(2021). https://doi.org/10.1186/s10020-021-00321-3

scholarly journals Quantification of vascular networks in photoacoustic mesoscopy

2021 ◽  
Author(s):  
Emma L Brown ◽  
Thierry L Lefebvre ◽  
Paul W Sweeney ◽  
Bernadette Stolz ◽  
Janek Gröhl ◽  
...  
Keyword(s):  
Blood Volume ◽  
Network Structure ◽  
In Silico ◽  
Ex Vivo ◽  
Image Filtering ◽  
Vascular Networks ◽  
Ground Truth Data ◽  
Rule Based ◽  
Segmentation Methods

Mesoscopic photoacoustic imaging (PAI) enables non-invasive visualisation of tumour vasculature and has the potential to assess prognosis and therapeutic response. Currently, evaluating vasculature using mesoscopic PAI involves visual or semi-quantitative 2D measurements, which fail to capture 3D vessel network complexity, and lack robust ground truths for assessment of segmentation accuracy. Here, we developed an in silico, phantom, in vivo, and ex vivo-validated end-to-end framework to quantify 3D vascular networks captured using mesoscopic PAI. We applied our framework to evaluate the capacity of rule-based and machine learning-based segmentation methods, with or without vesselness image filtering, to preserve blood volume and network structure by employing topological data analysis. We first assessed segmentation performance against ground truth data of in silico synthetic vasculatures and a photoacoustic string phantom. Our results indicate that learning-based segmentation best preserves vessel diameter and blood volume at depth, while rule-based segmentation with vesselness image filtering accurately preserved network structure in superficial vessels. Next, we applied our framework to breast cancer patient-derived xenografts (PDXs), with corresponding ex vivo immunohistochemistry. We demonstrated that the above segmentation methods can reliably delineate the vasculature of 2 breast PDX models from mesoscopic PA images. Our results underscore the importance of evaluating the choice of segmentation method when applying mesoscopic PAI as a tool to evaluate vascular networks in vivo.

A Dual-Biotic System for the Concurrent Delivery of Antibiotics and Probiotics: In Vitro, Ex Vivo, In Vivo and In Silico Evaluation and Correlation

2016 ◽  
Vol 33 (12) ◽  
pp. 3057-3071 ◽  
Author(s):  
Mershen Govender ◽  
Yahya E. Choonara ◽  
Sandy van Vuuren ◽  
Pradeep Kumar ◽  
Lisa C. du Toit ◽  
...  
Keyword(s):  
In Silico ◽  
Ex Vivo

scholarly journals In silico predictions; in vivo veritas

10.1038/9833 ◽  
1999 ◽  
Vol 17 (6) ◽  
pp. 533-534 ◽  
Author(s):  
Anne S. De Groot ◽  
Frank G. Rothman
Keyword(s):  
In Silico ◽  
In Silico Predictions

scholarly journals How Can Biomolecules Improve Mucoadhesion of Oral Insulin? A Comprehensive Insight using Ex-Vivo, In Silico, and In Vivo Models

Biomolecules ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 675 ◽  
Author(s):  
Mariana Amaral ◽  
Ana Sofia Martins ◽  
José Catarino ◽  
Pedro Faísca ◽  
Pradeep Kumar ◽  
...  
Keyword(s):  
In Silico ◽  
Ex Vivo ◽  
Polymeric Nanoparticles ◽  
Spherical Shape ◽  
Diabetic Rats ◽  
Laser Scattering ◽  
In Vivo Models ◽  
Mean Size

Currently, insulin can only be administered through the subcutaneous route. Due to the flaws associated with this route, it is of interest to orally deliver this drug. However, insulin delivered orally has several barriers to overcome as it is degraded by the stomach’s low pH, enzymatic content, and poor absorption in the gastrointestinal tract. Polymers with marine source like chitosan are commonly used in nanotechnology and drug delivery due to their biocompatibility and special features. This work focuses on the preparation and characterization of mucoadhesive insulin-loaded polymeric nanoparticles. Results showed a suitable mean size for oral administration (<600 nm by dynamic laser scattering), spherical shape, encapsulation efficiency (59.8%), and high recovery yield (80.6%). Circular dichroism spectroscopy demonstrated that protein retained its secondary structure after encapsulation. Moreover, the mucoadhesive potential of the nanoparticles was assessed in silico and the results, corroborated with ex-vivo experiments, showed that using chitosan strongly increases mucoadhesion. Besides, in vitro and in vivo safety assessment of the final formulation were performed, showing no toxicity. Lastly, the insulin-loaded nanoparticles were effective in reducing diabetic rats’ glycemia. Overall, the coating of insulin-loaded nanoparticles with chitosan represents a potentially safe and promising approach to protect insulin and enhance peroral delivery.

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