scholarly journals Neuromodulatory Control and Language Recovery in Bilingual Aphasia: An Active Inference Approach

2020 ◽  
Vol 10 (10) ◽  
pp. 161
Author(s):  
Noor Sajid ◽  
Karl Friston ◽  
Justyna Ekert ◽  
Cathy Price ◽  
David Green
Keyword(s):  
In Silico ◽  
Acetylcholine Release ◽  
Hierarchical Control ◽  
Control Model ◽  
Loss Of Control ◽  
Active Inference ◽  
Recovery Pattern ◽  
Starting Point ◽  
Language Recovery ◽  
Bilingual Aphasia

Understanding the aetiology of the diverse recovery patterns in bilingual aphasia is a theoretical challenge with implications for treatment. Loss of control over intact language networks provides a parsimonious starting point that can be tested using in-silico lesions. We simulated a complex recovery pattern (alternate antagonism and paradoxical translation) to test the hypothesis—from an established hierarchical control model—that loss of control was mediated by constraints on neuromodulatory resources. We used active (Bayesian) inference to simulate a selective loss of sensory precision; i.e., confidence in the causes of sensations. This in-silico lesion altered the precision of beliefs about task relevant states, including appropriate actions, and reproduced exactly the recovery pattern of interest. As sensory precision has been linked to acetylcholine release, these simulations endorse the conjecture that loss of neuromodulatory control can explain this atypical recovery pattern. We discuss the relevance of this finding for other recovery patterns.

scholarly journals Run-to-Run Tuning of Model Predictive Control for Type 1 Diabetes Subjects: In Silico Trial

2009 ◽  
Vol 3 (5) ◽  
pp. 1091-1098 ◽  
Author(s):  
Lalo Magni ◽  
Marco Forgione ◽  
Chiara Toffanin ◽  
Chiara Dalla Man ◽  
Boris Kovatchev ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Insulin Sensitivity ◽  
Model Predictive Control ◽  
Predictive Control ◽  
In Silico ◽  
Insulin Pump ◽  
Artificial Pancreas ◽  
Arx Model ◽  
Starting Point

Background: The technological advancements in subcutaneous continuous glucose monitoring and insulin pump delivery systems have paved the way to clinical testing of artificial pancreas devices. The experience derived by clinical trials poses technological challenges to the automatic control expert, the most notable being the large interpatient and intrapatient variability and the inherent uncertainty of patient information. Methods: A new model predictive control (MPC) glucose control system is proposed. The starting point is an MPC algorithm applied in 20 type 1 diabetes mellitus (T1DM) subjects. Three main changes are introduced: individualization of the ARX model used for prediction; synthesis of the MPC law on top of the open-loop basal/bolus therapy; and a run-to-run approach for implementing day-by-day tuning of the algorithm. In order to individualize the ARX model, a sufficiently exciting insulin profile is imposed by splitting the premeal bolus into two smaller boluses (40% and 60%) injected 30 min before and 30 min after the meal. Results: The proposed algorithm was tested on 100 virtual subjects extracted from an in silico T1DM population. The trial simulates 44 consecutive days, during which the patient receives breakfast, lunch, and dinner each day. For 10 days, meals are multiplied by a random variable uniformly distributed in [0.5, 1.5], while insulin delivery is based on nominal meals. Moreover, for 10 days, either a linear increase or decrease of insulin sensitivity (±25% of nominal value) is introduced. Conclusions: The ARX model identification procedure offers an automatic tool for patient model individualization. The run-to-run approach is an effective way to auto-tune the aggressiveness of the closed-loop control law, is robust to meal variation, and is also capable of adapting the regulator to slow parameter variations, e.g., on insulin sensitivity.

scholarly journals In Silico Analysis of Ixodid Tick Aqauporin-1 Protein as a Candidate Anti-Tick Vaccine Antigen

2019 ◽  
Author(s):  
Christian Ndekezi ◽  
Joseph Nkamwesiga ◽  
Sylvester Ochwo ◽  
Magambo Phillip Kimuda ◽  
Frank Norbert Mwiine ◽  
...  
Keyword(s):  
In Silico ◽  
Prediction Models ◽  
Vaccine Development ◽  
Sequence Similarity ◽  
Vaccine Antigen ◽  
Systematic Research ◽  
Motif Analysis ◽  
Peptide Motifs ◽  
Starting Point ◽  
Tick Vaccine

AbstractTicks are arthropod vectors of pathogens of both Veterinary and Public health importance. Ticks are largely controlled by acaricide application. However, acaricide efficacy is hampered by high cost, the need for regular application and selection of multi-acaricide resistant tick populations. In light of this, future tick control approaches are poised to rely on integration of rational acaricide application and other methods such as vaccination. To contribute to systematic research-guided efforts to produce anti-tick vaccines, we carried out an in silico tick Aquaporin-1 protein (AQP1) analysis to identify unique tick AQP1 peptide motifs that can be used in future peptide anti-tick vaccine development. We used multiple sequence alignment (MSA), motif analysis, homology modeling, and structural analysis to identify unique tick AQP1 peptide motifs. BepiPred, Chou & Fasman-Turn, Karplus & Schulz Flexibility and Parker-Hydrophilicity prediction models were used to asses these motifs’ abilities to induce antibody mediated immune responses. Tick AQP1 (MK334178) protein homology was largely similar to the bovine AQP1 (PDB:1J4N) (23% sequence similarity; Structural superimposition RMS=1.475). The highest similarities were observed in the transmembrane domains while differences were observed in the extra and intra cellular protein loops. Two unique tick AQP1 (MK334178) motifs, M7 (residues 106-125, p=5.4e-25) and M8 (residues 85-104, p=3.3e-24) were identified. These two motifs are located on the extra-cellular AQP1 domain and showed the highest Parker-Hydrophilicity prediction immunogenic scores of 1.153 and 2.612 respectively. The M7 and M8 motifs are a good starting point for the development of potential peptide-based anti-tick vaccine. Further analyses such as in vivo immunization assays are required to validate these findings.

scholarly journals Computer-Based Approaches for Determining the Pharmacological Profile of 5-(3-Nitro-Arylidene)-Thiazolidine-2,4-Dione

2021 ◽  
Vol 11 (6) ◽  
pp. 13806-13828
Keyword(s):  
Molecular Docking ◽  
In Silico ◽  
Density Functional ◽  
Biological Activities ◽  
Computational Approach ◽  
Basis Set ◽  
Pharmacological Profile ◽  
Dft Methods ◽  
Starting Point ◽  
In Silico Studies

The development of novel and safe compounds is a challenging task in the drug discovery trajectory. Accordingly, the individuation of promising core molecules with biological activities could pave the way to develop effective drugs to treat a given disease. The use of a computational approach can reduce the time for identifying promising core molecules characterizing their potential pharmacological profile and providing hints for the synthesis of novel derivatives with increased predicted pharmacological activity. Following this strategy, starting from a core molecule thiazolidine-2,4-dione, the derivative of 5-(3-nitro-arylidene)-thiazolidine-2,4-dione was synthesized to investigate the biological and pharmacological potential. An extensive computational investigation was performed employing ab initio calculations by using Density Functional Theory (DFT), and subsequent in silico studies were accomplished by molecular docking calculation. The structures 5-(3-nitro-arylidene)-thiazolidine-2,4-dione were fully optimized using multiparametric DFT methods were calculated at the B3LYP/6-31+G (d, p) level basis set. Besides gaining insights into the potential pharmacological profile of the selected derivative, molecular docking against some selected drug targets, ADME, and PASS prediction were performed. According to charges and molecular electrostatic potential (MESP) calculation, the N-H region could offer promising active site interactions for protein binding. Furthermore, Homo-Lumo and global reactivity values indicate a good profile for the selected compound, and UV-Vis provides further insights about its properties, potentially helpful for further experimental analysis. Notably, the in silico investigation indicated that EGFR and ORF2 enzymes could represent the selected drug-like compound's possible targets. Conclusively, the proposed computational approach demonstrated that it is possible to evaluate a proposed compound's bioactivity profile. We characterized 5-(3-nitro-arylidene)-thiazolidine-2,4-dione derivative, suggesting it as a good starting point for developing interesting hit compounds with a relevant pharmacological profile.

scholarly journals Working with Proteins in silico: A Review of Online Available Tools for Basic Identification of Proteins

2017 ◽  
Vol 5 (1) ◽  
pp. 65
Author(s):  
Caner Yavuz ◽  
Zahide Neslihan Öztürk
Keyword(s):  
Molecular Weight ◽  
Amino Acid ◽  
In Silico ◽  
In Silico Analysis ◽  
Tips And Tricks ◽  
Post Translational Modifications ◽  
Starting Point ◽  
Protein Research ◽  
Experimental Approaches ◽  
Silico Analysis

Increase in online available bioinformatics tools for protein research creates an important opportunity for scientists to reveal characteristics of the protein of interest by only starting from the predicted or known amino acid sequence without fully depending on experimental approaches. There are many sophisticated tools used for diverse purposes; however, there are not enough reviews covering the tips and tricks in selecting and using the correct tools as the literature mainly state the promotion of the new ones. In this review, with the aim of providing young scientists with no specific experience on protein work a reliable starting point for in silico analysis of the protein of interest, we summarized tools for annotation, identification of motifs and domains, determination isoelectric point, molecular weight, subcellular localization, and post-translational modifications by focusing on the important points to be considered while selecting from online available tools.

scholarly journals Benzimidazole Derivatives as New and Selective Inhibitors of Arginase from Leishmania mexicana with Biological Activity against Promastigotes and Amastigotes

2021 ◽  
Vol 22 (24) ◽  
pp. 13613
Author(s):  
Irene Betancourt-Conde ◽  
Claudia Avitia-Domínguez ◽  
Alicia Hernández-Campos ◽  
Rafael Castillo ◽  
Lilián Yépez-Mulia ◽  
...  
Keyword(s):  
Biological Activity ◽  
In Silico ◽  
Cytotoxic Effect ◽  
New Drugs ◽  
Dynamics Simulation ◽  
Benzimidazole Derivatives ◽  
Leishmania Mexicana ◽  
Arginase 1 ◽  
Excellent Starting Point ◽  
Starting Point

Leishmaniasis is a disease caused by parasites of the Leishmania genus that affects 98 countries worldwide, 2 million of new cases occur each year and more than 350 million people are at risk. The use of the actual treatments is limited due to toxicity concerns and the apparition of resistance strains. Therefore, there is an urgent necessity to find new drugs for the treatment of this disease. In this context, enzymes from the polyamine biosynthesis pathway, such as arginase, have been considered a good target. In the present work, a chemical library of benzimidazole derivatives was studied performing computational, enzyme kinetics, biological activity, and cytotoxic effect characterization, as well as in silico ADME-Tox predictions, to find new inhibitors for arginase from Leishmania mexicana (LmARG). The results show that the two most potent inhibitors (compounds 1 and 2) have an I50 values of 52 μM and 82 μM, respectively. Moreover, assays with human arginase 1 (HsARG) show that both compounds are selective for LmARG. According to molecular dynamics simulation studies these inhibitors interact with important residues for enzyme catalysis. Biological activity assays demonstrate that both compounds have activity against promastigote and amastigote, and low cytotoxic effect in murine macrophages. Finally, in silico prediction of their ADME-Tox properties suggest that these inhibitors support the characteristics to be considered drug candidates. Altogether, the results reported in our study suggest that the benzimidazole derivatives are an excellent starting point for design new drugs against leishmanisis.

scholarly journals Focus Your Screening Library: Rapid Identification of Novel PDE2 Inhibitors with in silico Driven Library Prioritization and MicroScale Thermophoresis

2020 ◽  
Author(s):  
Florian Kaiser ◽  
Maximilian G. Plach ◽  
Thomas Schubert ◽  
V. Joachim Haupt
Keyword(s):  
In Silico ◽  
High Throughput Screening ◽  
Rapid Identification ◽  
Chemical Diversity ◽  
Chemical Library ◽  
Binding Behavior ◽  
Microscale Thermophoresis ◽  
Excellent Starting Point ◽  
Starting Point

Accelerated development of lead structures is of high interest to the pharmaceutical industry in order to decrease development times and costs. We showcase how an intelligent combination of AI-based drug screening with state-of-the-art biophysics drives the rapid identification of novel inhibitor structures with high chemical diversity for cGMP-dependent 3’,5’-cyclic phosphodiesterase (PDE2). The starting point was an off-the-shelve chemical library of two million drug-like compounds. In a single in silico reduction step, we short-listed 125 compounds – the focused library – as potential binders to PDE2 and tested their binding behavior in vitro using MicroScale Thermophoresis (MST). Of this focused library, seven compounds indicated binding to PDE2, translating to a hit rate of 6%. Three of these compounds have affinities in the lower micromolar range. The compound with the highest affinity showed a KD of 10 µM and is thus an excellent starting point for further medicinal chemistry optimization. The results show how innovative and structure-driven in silico approaches and biophysics can be used to accelerate drug discovery and to obtain new molecular scaffolds at a fraction of the costs and time – compared with standard high-throughput screening.

scholarly journals Accessing Active Inference Theory through Its Implicit and Deliberative Practice in Human Organizations

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1521
Author(s):  
Stephen Fox
Keyword(s):  
Lived Experience ◽  
Public Institutions ◽  
Active Inference ◽  
Energy Principle ◽  
Private Companies ◽  
Free Energy Principle ◽  
Starting Point ◽  
And Mathematics ◽  
Autopoietic Organization ◽  
Inference Theory

Active inference theory (AIT) is a corollary of the free-energy principle, which formalizes cognition of living system’s autopoietic organization. AIT comprises specialist terminology and mathematics used in theoretical neurobiology. Yet, active inference is common practice in human organizations, such as private companies, public institutions, and not-for-profits. Active inference encompasses three interrelated types of actions, which are carried out to minimize uncertainty about how organizations will survive. The three types of action are updating work beliefs, shifting work attention, and/or changing how work is performed. Accordingly, an alternative starting point for grasping active inference, rather than trying to understand AIT specialist terminology and mathematics, is to reflect upon lived experience. In other words, grasping active inference through autoethnographic research. In this short communication paper, accessing AIT through autoethnography is explained in terms of active inference in existing organizational practice (implicit active inference), new organizational methodologies that are informed by AIT (deliberative active inference), and combining implicit and deliberative active inference. In addition, these autoethnographic options for grasping AIT are related to generative learning.

scholarly journals Berberine Derivatives as Pseudomonas aeruginosa MexXY-OprM Inhibitors: Activity and In Silico Insights

Molecules ◽  
2021 ◽  
Vol 26 (21) ◽  
pp. 6644
Author(s):  
Giorgia Giorgini ◽  
Gianmarco Mangiaterra ◽  
Nicholas Cedraro ◽  
Emiliano Laudadio ◽  
Giulia Sabbatini ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
In Silico ◽  
Rational Design ◽  
Specific Binding ◽  
In Silico Analysis ◽  
In Vitro Assays ◽  
Binding Modes ◽  
Starting Point ◽  
Berberine Derivatives

The natural alkaloid berberine has been demonstrated to inhibit the Pseudomonas aeruginosa multidrug efflux system MexXY-OprM, which is responsible for tobramycin extrusion by binding the inner membrane transporter MexY. To find a structure with improved inhibitory activity, we compared by molecular dynamics investigations the binding affinity of berberine and three aromatic substituents towards the three polymorphic sequences of MexY found in P. aeruginosa (PAO1, PA7, and PA14). The synergy of the combinations of berberine or berberine derivatives/tobramycin against the same strains was then evaluated by checkerboard and time-kill assays. The in silico analysis evidenced different binding modes depending on both the structure of the berberine derivative and the specific MexY polymorphism. In vitro assays showed an evident MIC reduction (32-fold and 16-fold, respectively) and a 2–3 log greater killing effect after 2 h of exposure to the combinations of 13-(2-methylbenzyl)- and 13-(4-methylbenzyl)-berberine with tobramycin against the tobramycin-resistant strain PA7, a milder synergy (a 4-fold MIC reduction) against PAO1 and PA14, and no synergy against the ΔmexXY strain K1525, confirming the MexY-specific binding and the computational results. These berberine derivatives could thus be considered new hit compounds to select more effective berberine substitutions and their common path of interaction with MexY as the starting point for the rational design of novel MexXY-OprM inhibitors.

scholarly journals Comprehensive in silico survey of the Mycolicibacterium mobilome reveals an as yet underexplored diversity

2021 ◽  
Author(s):  
Sergio Mascarenhas Morgado ◽  
Ana Carolina Paulo Vicente
Keyword(s):  
In Silico ◽  
Content Type ◽  
Genetic Elements ◽  
Link Type ◽  
Type Vii Secretion ◽  
Starting Point ◽  
The Family ◽  
Single Host ◽  
Genes Encoding ◽  
Ecological Importance

The mobilome plays a crucial role in bacterial adaptation and is therefore a starting point to understand and establish the gene flow occurring in the process of bacterial evolution. This is even more so if we consider that the mobilome of environmental bacteria can be the reservoir of genes that may later appear in the clinic. Recently, new genera have been proposed in the family Mycobacteriaceae , including the genus Mycolicibacterium , which encompasses dozens of species of agricultural, biotechnological, clinical and ecological importance, being ubiquitous in several environments. The current scenario in the Mycobacteriaceae mobilome has some bias because most of the characterized mycobacteriophages were isolated using a single host strain, and the few plasmids reported mainly relate to the genus Mycobacterium . To fill in the gaps in these issues, we performed a systematic in silico study of these mobile elements based on 242 available genomes of the genus Mycolicibacterium . The analyses identified 156 putative plasmids (19 conjugative, 45 mobilizable and 92 non-mobilizable) and 566 prophages in 86 and 229 genomes, respectively. Moreover, a contig was characterized by resembling an actinomycete integrative and conjugative element (AICE). Within this diversity of mobile genetic elements, there is a pool of genes associated with several canonical functions, in addition to adaptive traits, such as virulence and resistance to antibiotics and metals (mercury and arsenic). The type-VII secretion system was a common feature in the predicted plasmids, being associated with genes encoding virulent proteins (EsxA, EsxB, PE and PPE). In addition to the characterization of plasmids and prophages of the family Mycobacteriaceae , this study showed an abundance of these genetic elements in a dozen species of the genus Mycolicibacterium .

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