scholarly journals Beyond Plug and Pray: Context Sensitivity and in silico Design of Artificial Neomycin Riboswitches

2020 ◽  
Author(s):  
Christian Günzel ◽  
Felix Kühnl ◽  
Katharina Arnold ◽  
Sven Findeiß ◽  
Christina Weinberg ◽  
...  
Keyword(s):  
In Silico ◽  
Rna Structure ◽  
Computational Models ◽  
Switching Behavior ◽  
Genetic Circuits ◽  
Sequence Context ◽  
Translational Initiation ◽  
Structural Responses ◽  
The Impact

AbstractGene regulation in prokaryotes often depends on RNA elements such as riboswitches or RNA thermometers located in the 5’ untranslated region of mRNA. Rearrangements of the RNA structure in response, e. g., to the binding of small molecules or ions control translational initiation or premature termination of transcription and thus mRNA expression. Such structural responses are amenable to computational modeling, making it possible to rationally design synthetic riboswitches for a given aptamer. Starting from an artificial aptamer, we construct the first synthetic transcriptional riboswitches that respond to the antibiotic neomycin. We show that the switching behavior in vivo critically depends not only on the sequence of the riboswitch itself, but also on its sequence context. We therefore developed in silico methods to predict the impact of the context, making it possible to adapt the design and to rescue non-functional riboswitches. We furthermore analyze the influence of 5’ hairpins with varying stability on neomycin riboswitch activity. Our data highlight the limitations of a simple plug-and-play approach in the design of complex genetic circuits and demonstrate that detailed computational models significantly simplify, improve, and automate the design of transcriptional circuits. Our design software is available under a free license on Github.1

scholarly journals Synthesis, Antileishmanial Activity and in silico Studies of Aminoguanidine Hydrazones (AGH) and Thiosemicarbazones (TSC) Against Leishmania chagasi Amastigotes

2021 ◽  
Vol 17 ◽  
Author(s):  
Thiago M. de Aquino ◽  
Paulo H. B. França ◽  
Érica E. E. S. Rodrigues ◽  
Igor J. S. Nascimento ◽  
Paulo F. S. Santos-Júnior ◽  
...  
Keyword(s):  
In Silico ◽  
Biological Activities ◽  
Leishmania Species ◽  
Antileishmanial Activity ◽  
Trypanothione Reductase ◽  
Aromatic Substituent ◽  
In Silico Studies ◽  
Ic50 Values ◽  
The Impact

Background: Leishmaniasis is a worldwide health problem, highly endemic in developing countries. Among the four main clinical forms of the disease, visceral leishmaniasis is the most severe, fatal in 95% of cases. The undesired side-effects from first-line chemotherapy and the reported drug resistance search for effective drugs that can replace or supplement those currently used an urgent need. Aminoguanidine hydrazones (AGH's) have been explored for exhibiting a diverse spectrum of biological activities, in particular the antileishmanial activity of MGBG. The bioisosteres thiosemicarbazones (TSC's) offer a similar biological activity diversity, including antiprotozoal effects against Leishmania species and Trypanosoma cruzi. Objective: Considering the impact of leishmaniasis worldwide, this work aimed to design, synthesize, and perform a screening upon L. chagasi amastigotes and for the cytotoxicity of the small "in-house" library of both AGH and TSC derivatives and their structurally-related compounds. Method: A set of AGH's (3-7), TSC's (9, 10), and semicarbazones (11) were initially synthesized. Subsequently, different semi-constrained analogs were designed and also prepared, including thiazolidines (12), dihydrothiazines (13), imidazolines (15), pyrimidines (16, 18) azines (19, 20), and benzotriazepinones (23-25). All intermediates and target compounds were obtained with satisfactory yields and exhibited spectral data consistent with their structures. All final compounds were evaluated against L. chagasi amastigotes and J774.A1 cell line. Molecular docking was performed towards trypanothione reductase using GOLD® software. Result: The AGH's 3i, 4a, and 5d, and the TSC's 9i, 9k, and 9o were selected as valuable hits. These compounds presented antileishmanial activity compared with pentamidine, showing IC50 values ranged from 0.6 to 7.27 μM, maximal effects up to 55.3%, and satisfactory SI values (ranged from 11 to 87). On the other hand, most of the resulting semi-constrained analogs were found cytotoxic or presented reduced antileishmanial activity. In general, TSC class is more promising than its isosteric AGH analogs, and the beneficial aromatic substituent effects are not similar in both series. In silico studies have suggested that these hits are capable of inhibiting the trypanothione reductase from the amastigote forms. Conclusion: The promising antileishmanial activity of three AGH’s and three TSC’s was characterized. These compounds presented antileishmanial activity compared with PTD, showing IC50 values ranged from 0.6 to 7.27 μM, and satisfactory SI values. Further pharmacological assays involving other Leishmania strains are under progress, which will help to choose the best hits for in vivo experiments.

scholarly journals Eyes Open on Sleep and Wake: In Vivo to In Silico Neural Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Amaury Vanvinckenroye ◽  
Gilles Vandewalle ◽  
Christophe Phillips ◽  
Sarah L. Chellappa
Keyword(s):  
In Silico ◽  
Brain Function ◽  
Computational Models ◽  
Temporal Dynamics ◽  
Brain Plasticity ◽  
Effective Connectivity ◽  
Normal Brain ◽  
Cortical Function ◽  
Eyes Open

Functional and effective connectivity of cortical areas are essential for normal brain function under different behavioral states. Appropriate cortical activity during sleep and wakefulness is ensured by the balanced activity of excitatory and inhibitory circuits. Ultimately, fast, millisecond cortical rhythmic oscillations shape cortical function in time and space. On a much longer time scale, brain function also depends on prior sleep-wake history and circadian processes. However, much remains to be established on how the brain operates at the neuronal level in humans during sleep and wakefulness. A key limitation of human neuroscience is the difficulty in isolating neuronal excitation/inhibition drive in vivo. Therefore, computational models are noninvasive approaches of choice to indirectly access hidden neuronal states. In this review, we present a physiologically driven in silico approach, Dynamic Causal Modelling (DCM), as a means to comprehend brain function under different experimental paradigms. Importantly, DCM has allowed for the understanding of how brain dynamics underscore brain plasticity, cognition, and different states of consciousness. In a broader perspective, noninvasive computational approaches, such as DCM, may help to puzzle out the spatial and temporal dynamics of human brain function at different behavioural states.

scholarly journals Andean Berry (Vaccinium meridionale Swartz) Juice in Combination With Aspirin Modulated Apoptotic Signaling in Colon Cancer In Vitro and In Vivo

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 261-261
Author(s):  
Sandra Arango-Varela ◽  
Ivan Luzardo ◽  
Maria Maldonado-Celis
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
In Silico ◽  
Aberrant Crypt Foci ◽  
Apoptotic Signaling ◽  
Polyphenolic Composition ◽  
Apoptotic Effects ◽  
The Impact

Abstract Objectives This research aimed to assess the impact of Andean Berry (Vaccinium meridionale Swartz) juice (ABJ) in combination with Aspirin in the apoptotic signaling in colon cancer in vitro and in vivo. We hypothesized that ABJ + Aspirin would produce the most effective anti-proliferative and pro-apoptotic effects in vitro and in vivo. Methods The polyphenolic composition of ABJ was carried out by HPLC-DAD. ABJ (0–30% v/v), Aspirin (0–20 mM), and their mixture were evaluated for their pro-apoptotic effects in human SW480 colorectal cancer cells, followed by human apoptosis proteomic and bioinformatic analysis and in silico docking potential between ABJ components and selected pro-apoptotic targets. For the in vivo assays, colorectal cancer was induced with two injections (separated 1 week each) of azoxymethane (AOM: 15 mg/kg body weight, BW), and treatments were evaluated for its chemopreventive and chemoprotective effects. Hence, 30 male and female Balb/c mice were randomly divided in 5 groups: negative control (basal diet, BD); and four AOM-induced groups: positive control (BD), Aspirin (25 mg/kg BW + BD), ABJ (30% v/v in drinking water ABJ + BD), and ABJ + Aspirin (30% v/v ABJ + 25 mg/kg BW Aspirin + BD). Macroscopic and histopathological parameters were evaluated in vivo. Results The mixture displayed the highest antiproliferative effects (+46%), arrested cell cycle at the G2/M phase, decreased cloning efficiency, but reduced Caspase 3/7 activity, suggesting an alternative apoptotic pathway, compared to untreated SW480 cells. Several pro-apoptotic (cytochrome C, TNFRSF1A, Bax, and Bad) and anti-apoptotic (Hsp70/Hsp32) proteins were decreased. ABJ flavonoids (rutin and kaempferol) exhibited the highest in silico affinity with proteins like TRAILR2 or Catalase. Both chemopreventive and chemoprotective approaches showed similar body/liver weight outcomes, but the mixture displayed the strongest aberrant crypt foci reduction in vivo. The chemopreventive approach was more effective in protecting the colon from AOM. Conclusions Results suggested the potential of ABJ to reduce Aspirin use in the alleviation of colorectal cancer markers in vitro and in vivo, modulating alternate pro-apoptotic signaling. Funding Sources The funding provided by COLCIENCIAS and DGAPA-CTIC-UNAM is appreciated.

scholarly journals Modelling co-translational dimerisation for programmable nonlinearity in synthetic biology

2020 ◽  
Author(s):  
Ruud Stoof ◽  
Ángel Goñi-Moreno
Keyword(s):  
Nonlinear Dynamics ◽  
Biological Networks ◽  
Rational Design ◽  
Fine Tuning ◽  
Genetic Circuits ◽  
On Demand ◽  
Regulatory Circuits ◽  
Protein Dimers ◽  
The Impact

AbstractNonlinearity plays a fundamental role in the performance of both natural and synthetic biological networks. Key functional motifs in living microbial systems, such as the emergence of bistability or oscillations, rely on nonlinear molecular dynamics. Despite its core importance, the rational design of nonlinearity remains an unmet challenge. This is largely due to a lack of mathematical modelling that accounts for the mechanistic basics of nonlinearity. We introduce a model for gene regulatory circuits that explicitly simulates protein dimerization—a well-known source of nonlinear dynamics. Specifically, our approach focusses on modelling co-translational dimerization: the formation of protein dimers during—and not after—translation. This is in contrast to the prevailing assumption that dimer generation is only viable between freely diffusing monomers (i.e., post-translational dimerization). We provide a method for fine-tuning nonlinearity on demand by balancing the impact of co- versus post-translational dimerization. Furthermore, we suggest design rules, such as protein length or physical separation between genes, that may be used to adjust dimerization dynamics in-vivo. The design, build and test of genetic circuits with on-demand nonlinear dynamics will greatly improve the programmability of synthetic biological systems.

scholarly journals Theory of active chromatin remodeling

2019 ◽  
Author(s):  
Zhongling Jiang ◽  
Bin Zhang
Keyword(s):  
Chromatin Remodeling ◽  
Computational Models ◽  
Energy Landscape ◽  
Nucleosome Positioning ◽  
Active Chromatin ◽  
Intrinsic Signals ◽  
Biologically Relevant ◽  
The Impact ◽  
Prediction In Silico

Nucleosome positioning controls the accessible regions of chromatin and plays essential roles in DNA-templated processes. ATP driven remodeling enzymes are known to be crucial for its establishment in vivo, but their non-equilibrium nature has hindered the development of a unified theoretical framework for nucleosome positioning. Using a perturbation theory, we show that the effect of these enzymes can be well approximated by effective equilibrium models with rescaled temperatures and interactions. Numerical simulations support the accuracy of the theory in predicting both kinetic and steady-state quantities, including the effective temperature and the radial distribution function, in biologically relevant regimes. The energy landscape view emerging from our study provides an intuitive understanding for the impact of remodeling enzymes in either reinforcing or overwriting intrinsic signals for nucleosome positioning, and may help improve the accuracy of computational models for its prediction in silico.

scholarly journals Erythrocytes: Oxygen Sensors and Modulators of Vascular Tone

Physiology ◽  
2009 ◽  
Vol 24 (2) ◽  
pp. 107-116 ◽  
Author(s):  
Mary L. Ellsworth ◽  
Christopher G. Ellis ◽  
Daniel Goldman ◽  
Alan H. Stephenson ◽  
Hans H. Dietrich ◽  
...  
Keyword(s):  
Vascular Tone ◽  
Computational Models ◽  
Control Mechanism ◽  
Atp Release ◽  
Oxygen Demand ◽  
Oxygen Sensors ◽  
Feedback Mechanisms ◽  
In Vivo Experiments ◽  
The Impact

Through oxygen-dependent release of the vasodilator ATP, the mobile erythrocyte plays a fundamental role in matching microvascular oxygen supply with local tissue oxygen demand. Signal transduction within the erythrocyte and microvessels as well as feedback mechanisms controlling ATP release have been described. Our understanding of the impact of this novel control mechanism will rely on the integration of in vivo experiments and computational models.

scholarly journals Trans-Activator Binding Site Context in RCNMV Modulates Subgenomic mRNA Transcription

Viruses ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2252
Author(s):  
Jennifer S. H. Im ◽  
Laura R. Newburn ◽  
Gregory Kent ◽  
K. Andrew White
Keyword(s):  
Binding Site ◽  
Rna Structure ◽  
Red Clover ◽  
Mrna Levels ◽  
Mrna Transcription ◽  
Base Pairing ◽  
Independent Manner ◽  
The Impact

Many positive-sense RNA viruses transcribe subgenomic (sg) mRNAs during infections that template the translation of a subset of viral proteins. Red clover necrotic mosaic virus (RCNMV) expresses its capsid protein through the transcription of a sg mRNA from RNA1 genome segment. This transcription event is activated by an RNA structure formed by base pairing between a trans-activator (TA) in RNA2 and a trans-activator binding site (TABS) in RNA1. In this study, the impact of the structural context of the TABS in RNA1 on the TA–TABS interaction and sg mRNA transcription was investigated using in vitro and in vivo approaches. The results (i) generated RNA secondary structure models for the TA and TABS, (ii) revealed that the TABS is partially base paired with proximal upstream sequences, which limits TA access, (iii) demonstrated that the aforementioned intra-RNA1 base pairing involving the TABS modulates the TA–TABS interaction in vitro and sg mRNA levels during infections, and (iv) revealed that the TABS in RNA1 can be modified to mediate sg mRNA transcription in a TA-independent manner. These findings advance our understanding of transcriptional regulation in RCNMV and provide novel insights into the origin of the TA–TABS interaction.

scholarly journals Location-Specific Comparison Between a 3D In-Stent Restenosis Model and Micro-CT and Histology Data from Porcine In Vivo Experiments

2019 ◽  
Vol 10 (4) ◽  
pp. 568-582 ◽  
Author(s):  
P. S. Zun ◽  
A. J. Narracott ◽  
C. Chiastra ◽  
J. Gunn ◽  
A. G. Hoekstra
Keyword(s):  
Experimental Data ◽  
In Silico ◽  
Computational Models ◽  
Tissue Growth ◽  
Micro Ct ◽  
Stent Deployment ◽  
Stent Restenosis ◽  
In Stent Restenosis ◽  
Good Agreement

Abstract Background Coronary artery restenosis is an important side effect of percutaneous coronary intervention. Computational models can be used to better understand this process. We report on an approach for validation of an in silico 3D model of in-stent restenosis in porcine coronary arteries and illustrate this approach by comparing the modelling results to in vivo data for 14 and 28 days post-stenting. Methods This multiscale model includes single-scale models for stent deployment, blood flow and tissue growth in the stented vessel, including smooth muscle cell (SMC) proliferation and extracellular matrix (ECM) production. The validation procedure uses data from porcine in vivo experiments, by simulating stent deployment using stent geometry obtained from micro computed tomography (micro-CT) of the stented vessel and directly comparing the simulation results of neointimal growth to histological sections taken at the same locations. Results Metrics for comparison are per-strut neointimal thickness and per-section neointimal area. The neointimal area predicted by the model demonstrates a good agreement with the detailed experimental data. For 14 days post-stenting the relative neointimal area, averaged over all vessel sections considered, was 20 ± 3% in vivo and 22 ± 4% in silico. For 28 days, the area was 42 ± 3% in vivo and 41 ± 3% in silico. Conclusions The approach presented here provides a very detailed, location-specific, validation methodology for in silico restenosis models. The model was able to closely match both histology datasets with a single set of parameters. Good agreement was obtained for both the overall amount of neointima produced and the local distribution. It should be noted that including vessel curvature and ECM production in the model was paramount to obtain a good agreement with the experimental data.

Computational exploration of mechanistic determinants of antibody drug-conjugate pharmacokinetics using quantitative systems pharmacology modeling strategies.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e14000-e14000
Author(s):  
John M Burke ◽  
Anna Katharina Wilkins ◽  
Andrew Matteson ◽  
Lore Gruenbaum ◽  
Josh F Apgar
Keyword(s):  
Half Life ◽  
Computational Models ◽  
Systems Pharmacology ◽  
Antibody Drug Conjugate ◽  
Quantitative Systems Pharmacology ◽  
Drug Conjugate ◽  
Drug Antibody Ratio ◽  
The Impact ◽  
Antibody Drug

e14000 Background: The pharmacokinetics of antibody drug conjugate (ADC) therapeutics typically show a discrepancy between the PK of total antibody (conjugated and unconjugated antibody) and that of conjugated antibody, carrying one or more payload molecules This discrepancy is often attributed to deconjugation (Kamath, 2014), however recent evidence suggests that the underlying mechanisms may be more complex. Methods: This work employs a computational quantitative systems pharmacology (QSP) approach to understand the impact of drug antibody ratio (DAR) and the resulting changes in molecular properties on overall PK and relative payload disposition as observed in preclinical and clinical studies. Results: Using QSP approaches, the model (1) describes the kinetics of individual DAR species and agrees well with typical ADC PK, individual DAR PK, and average DAR measurements in vivo; (2), quantitatively describes the trade-off between higher DAR and lower exposure; consequently, we predict that ADC2 is half as potent as ADC4 and ADC8, which are equipotent; (3) longer mAb half-life reduces payload delivery after multiple doses; and (4) ADC half-life affects the percent of payload delivered through different mechanisms. Conclusions: A QSP model describing mechanism is a useful tool to translate and understand PK from preclinical species to human, by acting as a central repository of data, knowledge, and hypotheses. It provided a rational basis to generate testable hypotheses and provide early insights into complex ADC PK data and established the benefit of using computational models to design novel ADCs and to optimize the discovery and development of existing ADCs.

Harnessing tumor immunity with chemotherapy: Mathematical modeling for decision-making in combinatorial regimen with immune-oncology drugs.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e14095-e14095
Author(s):  
Vesna Cuplov ◽  
Guillaume Sicard ◽  
Dominique Barbolosi ◽  
Joseph Ciccolini ◽  
Fabrice Barlesi
Keyword(s):  
Mathematical Modeling ◽  
T Cells ◽  
In Silico ◽  
Checkpoint Inhibitors ◽  
Cytotoxic T Cells ◽  
Model Parameters ◽  
In Vivo Experiments ◽  
The Impact

e14095 Background: Combining chemotherapy and immune checkpoint inhibitors (ICI) is challenging due to the near-infinite choice of dosing, scheduling and sequencing between drugs. The aim of this work is to develop a phenomenological model that describes the synergistic effect between cytotoxics and immune check point inhibitors in patients with cancer. Methods: Inspired from literature, we have developed an integrative mathematical model that includes tumor cells, cytotoxic T cells (CTLs) and regulatory T cells (TREGs) plus pharmacokinetics (PK) inputs. Loss in tumor mass is due to combined effect of direct chemotherapy-induced cytotoxicity and CTLs immune response, which is in turn inhibited by the tumor and mitigated by TREGs in the tumor micro-environment. The model describes as well the impact of chemotherapy-induced lymphodepletion on immune tolerance, whereas ICIs protect CTLs against tumor inhibition. Identification of model’s parameters and simulations of various scheduling were performed using Mlxplore software and a Python standalone code. In vitro and in vivo experiments using lung cancer models generate experimental data to adjust model parameters. Results: Complex interplays between cytotoxics and immune cells were best described by a 10-parameters model so as to ensure better identifiability. PK/PD relationships were integrated using compartmental modeling. In silico simulations show how changes in dosing and scheduling impact efficacy endpoints, an observation in line with data from the literature. Ongoing in vitro and in vivo experiments with pemetrexed-cisplatin doublet and anti-PD1 pembrolizumab help optimizing the model’s parameters in a self-learning loop. Conclusions: This work is at the frontier between mathematical modeling and experimental therapeutics with ICIs. In silico modeling and simulations could help narrow down the treatment choices and define optimal combinations prior to running clinical trials. Such model will help identify optimal dosing and scheduling, so as to achieve better synergism and efficacy.

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