scholarly journals Prediction of Anticancer Peptides with High Efficacy and Low Toxicity by Hybrid Model Based on 3D Structure of Peptides

2021 ◽  
Vol 22 (11) ◽  
pp. 5630
Author(s):  
Yuhong Zhao ◽  
Shijing Wang ◽  
Wenyi Fei ◽  
Yuqi Feng ◽  
Le Shen ◽  
...  
Keyword(s):  
Hybrid Model ◽  
Computational Models ◽  
3D Structure ◽  
Three Dimensional ◽  
Peptide Sequence ◽  
Sequence Information ◽  
Anticancer Peptides ◽  
Multiple Datasets ◽  
Toxic Peptides

Recently, anticancer peptides (ACPs) have emerged as unique and promising therapeutic agents for cancer treatment compared with antibody and small molecule drugs. In addition to experimental methods of ACPs discovery, it is also necessary to develop accurate machine learning models for ACP prediction. In this study, features were extracted from the three-dimensional (3D) structure of peptides to develop the model, compared to most of the previous computational models, which are based on sequence information. In order to develop ACPs with more potency, more selectivity and less toxicity, the model for predicting ACPs, hemolytic peptides and toxic peptides were established by peptides 3D structure separately. Multiple datasets were collected according to whether the peptide sequence was chemically modified. After feature extraction and screening, diverse algorithms were used to build the model. Twelve models with excellent performance (Acc > 90%) in the ACPs mixed datasets were used to form a hybrid model to predict the candidate ACPs, and then the optimal model of hemolytic peptides (Acc = 73.68%) and toxic peptides (Acc = 85.5%) was used for safety prediction. Novel ACPs were found by using those models, and five peptides were randomly selected to determine their anticancer activity and toxic side effects in vitro experiments.

scholarly journals CirBiTree: Citrullination Site Inference Based on a Fuzzy Neural Network and Flexible Neural Tree

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Chuandong Song ◽  
Haifeng Wang
Keyword(s):  
Neural Network ◽  
Fuzzy Neural Network ◽  
Classification Model ◽  
Peptide Sequence ◽  
Sequence Information ◽  
Post Translational Modification ◽  
Fuzzy Neural ◽  
Human Complex ◽  
Better Than

Emerging evidence demonstrates that post-translational modification plays an important role in several human complex diseases. Nevertheless, considering the inherent high cost and time consumption of classical and typical in vitro experiments, an increasing attention has been paid to the development of efficient and available computational tools to identify the potential modification sites in the level of protein. In this work, we propose a machine learning-based model called CirBiTree for identification the potential citrullination sites. More specifically, we initially utilize the biprofile Bayesian to extract peptide sequence information. Then, a flexible neural tree and fuzzy neural network are employed as the classification model. Finally, the most available length of identified peptides has been selected in this model. To evaluate the performance of the proposed methods, some state-of-the-art methods have been employed for comparison. The experimental results demonstrate that the proposed method is better than other methods. CirBiTree can achieve 83.07% in sn%, 80.50% in sp, 0.8201 in F1, and 0.6359 in MCC, respectively.

scholarly journals Prediction of Aerosol Deposition in the Human Respiratory Tract via Computational Models: A Review with Recent Updates

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 137 ◽  
Author(s):  
Vu Khac Hoang Bui ◽  
Ju-Young Moon ◽  
Minhe Chae ◽  
Duckshin Park ◽  
Young-Chul Lee
Keyword(s):  
Respiratory Tract ◽  
Particle Deposition ◽  
Computational Models ◽  
Aerosol Particles ◽  
Three Dimensional ◽  
Aerosol Deposition ◽  
Research Area ◽  
Human Respiratory Tract

The measurement of deposited aerosol particles in the respiratory tract via in vivo and in vitro approaches is difficult due to those approaches’ many limitations. In order to overcome these obstacles, different computational models have been developed to predict the deposition of aerosol particles inside the lung. Recently, some remarkable models have been developed based on conventional semi-empirical models, one-dimensional whole-lung models, three-dimensional computational fluid dynamics models, and artificial neural networks for the prediction of aerosol-particle deposition with a high accuracy relative to experimental data. However, these models still have some disadvantages that should be overcome shortly. In this paper, we take a closer look at the current research trends as well as the future directions of this research area.

Producing Neurospheroids and Hydrogels to Create a Three-dimensional in Vitro Model for the Use of Conduits in Peripheral Nerve Regeneration

Neurosurgery ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. E272-E272
Author(s):  
Devyani Shete ◽  
Aran Batth ◽  
Aditi Nijhawan ◽  
Jaffer Choudhary ◽  
Ian Thompson
Keyword(s):  
Peripheral Nerve ◽  
Nerve Regeneration ◽  
Schwann Cells ◽  
Peripheral Nerve Regeneration ◽  
3D Structure ◽  
Three Dimensional ◽  
Negative Control ◽  
Cellular Growth ◽  
Live Cells

Abstract INTRODUCTION Peripheral nerve regeneration is a complex challenge that requires suitable nerve guidance systems to bridge the severed ends of 2 nerves back together. Current polymeric conduits on the market provide good cellular growth but are limited by the length of gap defect they can repair, and complete functional recovery is rare. This project focused on creating a three-dimensional (3D) in Vitro spheroidal sprouting assay for peripheral nerve regeneration, as well as producing and testing different polymeric hydrogels as potential scaffold materials for the conduit. METHODS Different concentrations of chitosan, methylcellulose (MC) and sodium alginate were produced, as well as blends of these materials. These hydrogels were seeded with 3D neurospheroids, along with NG108-15 (neuronal) cells and Schwann cells to test their biocompatibility. RESULTS MTT assays showed the mean absorbance of chitosan gels with NG108-15 cells at 24 hr (P < .001) and 72 hr (P > .05) was similar/slightly higher than the negative control. Live-Dead data showed 93.4% of live cells at DIV7 on MC: Ch blends, compared to 72% with chitosan alone. CONCLUSION Overall, both chitosan and MC were nontoxic and biocompatible with NG108-15 and Schwann cells. Blending chitosan with MC improved its chemical and physical properties. The cells formed spheroids that well on a gel; this pseudo-3D structure is excellent for research purposes compared to 2D as it mimics the body's internal environment.

scholarly journals A Better, Faster Road From Biological Data to Human Health: A Systems Biology Approach for Engineered Cell Cultures

2017 ◽  
Author(s):  
Brian T. Hawkins ◽  
Sonia Grego
Keyword(s):  
Systems Biology ◽  
Computational Models ◽  
Three Dimensional ◽  
Toxicity Testing ◽  
Biological Data ◽  
Physiological Relevance ◽  
Toxicity Risk ◽  
Therapeutic Development ◽  
Single Cell Type

Traditionally, the interactions of drugs and toxicants with human tissue have been investigated in a reductionist way—for example, by focusing on specific molecular targets and using single-cell-type cultures before testing compounds in whole organisms. More recently, “systems biology” approaches attempt to enhance the predictive value of in vitro biological data by adopting a comprehensive description of biological systems and using computational tools that are sophisticated enough to handle the complexity of these systems. However, the utility of computational models resulting from these efforts completely relies on the quality of the data used to construct them. Here, we propose that recent advances in the development of bioengineered, three-dimensional, multicellular constructs provide in vitro data of sufficient complexity and physiological relevance to be used in predictive systems biology models of human responses. Such predictive models are essential to maximally leveraging these emerging bioengineering technologies to improve both therapeutic development and toxicity risk assessment. This brief outlines the opportunities presented by emerging technologies and approaches for the acceleration of drug development and toxicity testing, as well as the challenges lying ahead for the field.

scholarly journals A New Bioreactor to Promote Follicular Growth With or Without Activin A

2021 ◽  
Author(s):  
Cynthia Jovet ◽  
Eloise Fraison ◽  
Jacqueline Lornage ◽  
Nicolas Morel-journel ◽  
Antoine Gavoille ◽  
...  
Keyword(s):  
3D Structure ◽  
Three Dimensional ◽  
Activin A ◽  
Structure Group ◽  
Dimensional Structure ◽  
Follicular Growth ◽  
Primordial Follicles ◽  
Estradiol Secretion ◽  
Follicular Density

Abstract Background: The aim of the present study was to evaluate the effect of Activin A on the activation of in vitro folliculogenesis of human ovarian tissues with or without our new three-dimensional structure (3D-structure). Methods: Five fresh ovarian human tissues were cultured in vitro in 4 groups with 100ng/mL Activin A or without Activine A and within or without a 3D-structure for 20 or 22 days of in vitro culture. Follicular density and quality were evaluated, and follicular diameters were measured. Estradiol secretion was quantified. Proliferation and apoptosis through immunostaining were performed.Results: The proportion of primordial follicles was significantly reduced, and the proportion of primary and secondary follicles was significantly increased in all four groups (p<0.001). Antral cavities were observed in the four culture groups. Activin A supplementation did not significantly affect the follicular density, follicular quality, follicular growth, or estradiol secretion (p>0.05). The 3D-structure increased the density of primary follicles and decreased the estradiol secretion (p<0.001). Tissular proliferation was significantly lower in the 3D-structure group compared to the non-3D-structure group (p=0.008). Regarding tissular apoptosis, it was significantly higher in the Activin group compared to the non-Activin group (0.006). Conclusion: The presence of Activin A did not seem to play a key role in in vitro folliculogenesis activation. However, the results may indicate that the 3D-structure could be more physiological and could prevent a pejorative in vitro folliculogenesis flare-up.

scholarly journals Patient-Specific Aortic Phantom With Tunable Compliance

2019 ◽  
Vol 2 (4) ◽  
Author(s):  
Antonio Gallarello ◽  
Andrea Palombi ◽  
Giacomo Annio ◽  
Shervanthi Homer-Vanniasinkam ◽  
Elena De Momi ◽  
...  
Keyword(s):  
Aortic Arch ◽  
Computational Models ◽  
Three Dimensional ◽  
Complex Interventions ◽  
Patient Specific ◽  
Arch Model ◽  
Magnetic Resonance Imaging Mri ◽  
Variable Wall ◽  
Silicone Model

Abstract Validation of computational models using in vitro phantoms is a nontrivial task, especially in the replication of the mechanical properties of the vessel walls, which varies with age and pathophysiological state. In this paper, we present a novel aortic phantom reconstructed from patient-specific data with variable wall compliance that can be tuned without recreating the phantom. The three-dimensional (3D) geometry of an aortic arch was retrieved from a computed tomography angiography scan. A rubber-like silicone phantom was manufactured and connected to a compliance chamber in order to tune its compliance. A lumped resistance was also coupled with the system. The compliance of the aortic arch model was validated using the Young's modulus and characterized further with respect to clinically relevant indicators. The silicone model demonstrates that compliance can be finely tuned with this system under pulsatile flow conditions. The phantom replicated values of compliance in the physiological range. Both, the pressure curves and the asymmetrical behavior of the expansion, are in agreement with the literature. This novel design approach allows obtaining for the first time a phantom with tunable compliance. Vascular phantoms designed and developed with the methodology proposed in this paper have high potential to be used in diverse conditions. Applications include training of physicians, pre-operative trials for complex interventions, testing of medical devices for cardiovascular diseases (CVDs), and comparative Magnetic-resonance-imaging (MRI)-based computational studies.

scholarly journals Alvaxanthone, a Thymidylate Synthase Inhibitor with Nematocidal and Tumoricidal Activities

Molecules ◽  
2020 ◽  
Vol 25 (12) ◽  
pp. 2894 ◽  
Author(s):  
Piotr Maj ◽  
Mattia Mori ◽  
Justyna Sobich ◽  
Joanna Markowicz ◽  
Łukasz Uram ◽  
...  
Keyword(s):  
Tumor Cells ◽  
Thymidylate Synthase ◽  
Antitumor Agents ◽  
3D Structure ◽  
Three Dimensional ◽  
Human Tumor ◽  
Selective Toxicity ◽  
C Elegans ◽  
Synthase Inhibitor

With the aim to identify novel inhibitors of parasitic nematode thymidylate synthase (TS), we screened in silico an in-house library of natural compounds, taking advantage of a model of nematode TS three-dimensional (3D) structure and choosing candidate compounds potentially capable of enzyme binding/inhibition. Selected compounds were tested as (i) inhibitors of the reaction catalyzed by TSs of different species, (ii) agents toxic to a nematode parasite model (C. elegans grown in vitro), (iii) inhibitors of normal human cell growth, and (iv) antitumor agents affecting human tumor cells grown in vitro. The results pointed to alvaxanthone as a relatively strong TS inhibitor that causes C. elegans population growth reduction with nematocidal potency similar to the anthelmintic drug mebendazole. Alvaxanthone also demonstrated an antiproliferative effect in tumor cells, associated with a selective toxicity against mitochondria observed in cancer cells compared to normal cells.

scholarly journals iAmideV-Deep: Valine Amidation Site Prediction in Proteins Using Deep Learning and Pseudo Amino Acid Compositions

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 560
Author(s):  
Sheraz Naseer ◽  
Rao Faizan Ali ◽  
Amgad Muneer ◽  
Suliman Mohamed Fati
Keyword(s):  
Amino Acid ◽  
Computational Models ◽  
Ex Vivo ◽  
Biologically Active ◽  
Peptide Sequence ◽  
Post Translational Modification ◽  
Amino Acid Compositions ◽  
Efficient Alternative

Amidation is an important post translational modification where a peptide ends with an amide group (–NH2) rather than carboxyl group (–COOH). These amidated peptides are less sensitive to proteolytic degradation with extended half-life in the bloodstream. Amides are used in different industries like pharmaceuticals, natural products, and biologically active compounds. The in-vivo, ex-vivo, and in-vitro identification of amidation sites is a costly and time-consuming but important task to study the physiochemical properties of amidated peptides. A less costly and efficient alternative is to supplement wet lab experiments with accurate computational models. Hence, an urgent need exists for efficient and accurate computational models to easily identify amidated sites in peptides. In this study, we present a new predictor, based on deep neural networks (DNN) and Pseudo Amino Acid Compositions (PseAAC), to learn efficient, task-specific, and effective representations for valine amidation site identification. Well-known DNN architectures are used in this contribution to learn peptide sequence representations and classify peptide chains. Of all the different DNN based predictors developed in this study, Convolutional neural network-based model showed the best performance surpassing all other DNN based models and reported literature contributions. The proposed model will supplement in-vivo methods and help scientists to determine valine amidation very efficiently and accurately, which in turn will enhance understanding of the valine amidation in different biological processes.

scholarly journals A Novel Three-Dimensional Culture Device Favors a Myelinating Morphology of Neural Stem Cell-Derived Oligodendrocytes

2021 ◽  
Vol 9 ◽  
Author(s):  
Alessandra Flagelli ◽  
Olivia Candini ◽  
Stella Frabetti ◽  
Massimo Dominici ◽  
Luciana Giardino ◽  
...  
Keyword(s):  
3D Structure ◽  
Three Dimensional ◽  
3D Culture ◽  
Precursor Cell ◽  
Research Report ◽  
Mrna Levels ◽  
Differentiation Markers ◽  
Functional Components

The complexity of the central nervous system (CNS) requires researchers to consider all the variables linked to the interaction between the different cell inhabitants. On this basis, any in vitro study of the physiological and pathological processes regarding the CNS should consider the balance between the standardization of the assay and the complexity of the cellular system which mimics the in vivo microenvironment. One of the main structural and functional components of the CNS is the oligodendrocyte precursor cell (OPC), responsible for developmental myelination and myelin turnover and repair during adulthood following differentiation into mature oligodendrocytes. In the present brief research report, we describe a 3D culture tool (VITVO) based on an inert and biocompatible synthetic polymer material scaffold, functionalized with laminin coating, and tested as a new culture microenvironment for neural stem/precursor cell (NSPC) differentiation compared to standard 2D cultures. NSPCs spontaneously differentiate in the three neural lineages (neurons, astrocytes and OPCs), identified by specific markers, along the fibers in the 3D structure. Analysis of the mRNA levels for lineage differentiation markers reveals a higher expression compared to those seeded on a 2D surface, suggesting an acceleration of the differentiation process. We then focused on the oligodendroglial lineage, showing that in VITVO, mature oligodendrocytes exhibit a myelinating morphology, proven by 3D image elaboration, linked to a higher expression of mature oligodendrocyte markers. This preliminary study on an innovative 3D culture system is the first robust step in producing new microenvironment-based strategies to investigate in vitro OPC and oligodendrocyte biology.

scholarly journals Cohesin Releasing Factor WAPL Regulates Genome Structure and Function of Mature T Cells

2021 ◽  
Author(s):  
Yaping Sun ◽  
Gabrielle A. Dotson ◽  
Lindsey A. Muir ◽  
Scott Ronquist ◽  
Katherine Oravecz-Wilson ◽  
...  
Keyword(s):  
T Cells ◽  
Hematopoietic Cell Transplantation ◽  
Genome Structure ◽  
3D Structure ◽  
Three Dimensional ◽  
Structure And Function ◽  
Cell Functions ◽  
And Function

ABSTRACTThe cohesin complex modulates gene expression and cellular functions by shaping three-dimensional (3D) organization of chromatin. WAPL, cohesin’s DNA releasing factor, regulates 3D chromatin architecture. The 3D genome structure and its relevance to mature T cell functions is not well understood. We show that in vivo lymphopenic expansion, and allo-antigen driven proliferation, alters the 3D structure and function of the genome in mature T cells. Conditional deletion of Wapl in T cells reduced long-range genomic interactions, altered chromatin A/B compartments and the topologically associating domains (TAD) of the chromatin in T cells at baseline. Comparison of chromatin structure in normal and WAPL-deficient T cells after lymphopenic and allo-antigen driven stimulation revealed reduced loop extensions with changes in cell cycling genes. WAPL-mediated changes in 3D architecture of chromatin regulated activation, cycling and proliferation of T cells in vitro and in vivo. Finally, WAPL-deficient T cells caused reduced severity of graft-versus-host disease following experimental allogeneic hematopoietic cell transplantation. These data collectively characterize 3D genomic architecture of T cells in vivo and demonstrate biological and clinical implications for its disruption by cohesin releasing factor WAPL.

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