Virtual microscopy: an evaluation of its validity and diagnostic performance in routine histologic diagnosis of skin tumors.

PubMed

Nielsen, Patricia Switten; Lindebjerg, Jan; Rasmussen, Jan; Starklint, Henrik; Waldstrøm, Marianne; Nielsen, Bjarne

2010-12-01

Digitization of histologic slides is associated with many advantages, and its use in routine diagnosis holds great promise. Nevertheless, few articles evaluate virtual microscopy in routine settings. This study is an evaluation of the validity and diagnostic performance of virtual microscopy in routine histologic diagnosis of skin tumors. Our aim is to investigate whether conventional microscopy of skin tumors can be replaced by virtual microscopy. Ninety-six skin tumors and skin-tumor-like changes were consecutively gathered over a 1-week period. Specimens were routinely processed, and digital slides were captured on Mirax Scan (Carl Zeiss MicroImaging, Göttingen, Germany). Four pathologists evaluated the 96 virtual slides and the associated 96 conventional slides twice with intermediate time intervals of at least 3 weeks. Virtual slides that caused difficulties were reevaluated to identify possible reasons for this. The accuracy was 89.2% for virtual microscopy and 92.7% for conventional microscopy. All κ coefficients expressed very good intra- and interobserver agreement. The sensitivities were 85.7% (78.0%-91.0%) and 92.0% (85.5%-95.7%) for virtual and conventional microscopy, respectively. The difference between the sensitivities was 6.3% (0.8%-12.6%). The subsequent reevaluation showed that virtual slides were as useful as conventional slides when rendering a diagnosis. Differences seen are presumed to be due to the pathologists' lack of experience using the virtual microscope. We conclude that it is feasible to make histologic diagnosis on the skin tumor types represented in this study using virtual microscopy after pathologists have completed a period of training. Larger studies should be conducted to verify whether virtual microscopy can replace conventional microscopy in routine practice. Copyright © 2010 Elsevier Inc. All rights reserved.

Impact of virtual microscopy with conventional microscopy on student learning in dental histology.

PubMed

Hande, Alka Harish; Lohe, Vidya K; Chaudhary, Minal S; Gawande, Madhuri N; Patil, Swati K; Zade, Prajakta R

2017-01-01

In dental histology, the assimilation of histological features of different dental hard and soft tissues is done by conventional microscopy. This traditional method of learning prevents the students from screening the entire slide and change of magnification. To address these drawbacks, modification in conventional microscopy has evolved and become motivation for changing the learning tool. Virtual microscopy is the technique in which there is complete digitization of the microscopic glass slide, which can be analyzed on a computer. This research is designed to evaluate the effectiveness of virtual microscopy with conventional microscopy on student learning in dental histology. A cohort of 105 students were included and randomized into three groups: A, B, and C. Group A students studied the microscopic features of oral histologic lesions by conventional microscopy, Group B by virtual microscopy, and Group C by both conventional and virtual microscopy. The students' understanding of the subject was evaluated by a prepared questionnaire. The effectiveness of the study designs on knowledge gains and satisfaction levels was assessed by statistical assessment of differences in mean test scores. The difference in score between Groups A, B, and C at pre- and post-test was highly significant. This enhanced understanding of the subject may be due to benefits of using virtual microscopy in teaching histology. The augmentation of conventional microscopy with virtual microscopy shows enhancement of the understanding of the subject as compared to the use of conventional microscopy and virtual microscopy alone.

Quantitative simulation of intracellular signaling cascades in a Virtual Liver: estimating dose dependent changes in hepatocellular proliferation and apoptosis

EPA Science Inventory

The US EPA Virtual Liver (v-Liver™) is developing an approach to predict dose-dependent hepatotoxicity as an in vivo tissue level response using in vitro data. The v-Liver accomplishes this using an in silico agent-based systems model that dynamically integrates environmental exp...

Computer Simulation of Embryonic Systems: What can a virtual embryo teach us about developmental toxicity? (LA Conference on Computational Biology & Bioinformatics)

EPA Science Inventory

This presentation will cover work at EPA under the CSS program for: (1) Virtual Tissue Models built from the known biology of an embryological system and structured to recapitulate key cell signals and responses; (2) running the models with real (in vitro) or synthetic (in silico...

Combination of virtual screening protocol by in silico towards the discovery of novel 4-hydroxyphenylpyruvate dioxygenase inhibitors

NASA Astrophysics Data System (ADS)

Fu, Ying; Sun, Yi-Na; Yi, Ke-Han; Li, Ming-Qiang; Cao, Hai-Feng; Li, Jia-Zhong; Ye, Fei

2018-02-01

4-Hydroxyphenylpyruvate dioxygenase (EC 1.13.11.27, HPPD) is a potent new bleaching herbicide target. Therefore, in silico structure-based virtual screening was performed in order to speed up the identification of promising HPPD inhibitors. In this study, an integrated virtual screening protocol by combining 3D-pharmacophore model, molecular docking and molecular dynamics (MD) simulation was established to find novel HPPD inhibitors from four commercial databases. 3D-pharmacophore Hypo1 model was applied to efficiently narrow potential hits. The hit compounds were subsequently submitted to molecular docking studies, showing four compounds as potent inhibitor with the mechanism of the Fe(II) coordination and interaction with Phe360, Phe403 and Phe398. MD result demonstrated that nonpolar term of compound 3881 made great contributions to binding affinities. It showed an IC50 being 2.49 µM against AtHPPD in vitro. The results provided useful information for developing novel HPPD inhibitors, leading to further understanding of the interaction mechanism of HPPD inhibitors.

Combining structure-based pharmacophore modeling, virtual screening, and in silico ADMET analysis to discover novel tetrahydro-quinoline based pyruvate kinase isozyme M2 activators with antitumor activity

PubMed Central

Chen, Can; Wang, Ting; Wu, Fengbo; Huang, Wei; He, Gu; Ouyang, Liang; Xiang, Mingli; Peng, Cheng; Jiang, Qinglin

2014-01-01

Compared with normal differentiated cells, cancer cells upregulate the expression of pyruvate kinase isozyme M2 (PKM2) to support glycolytic intermediates for anabolic processes, including the synthesis of nucleic acids, amino acids, and lipids. In this study, a combination of the structure-based pharmacophore modeling and a hybrid protocol of virtual screening methods comprised of pharmacophore model-based virtual screening, docking-based virtual screening, and in silico ADMET (absorption, distribution, metabolism, excretion and toxicity) analysis were used to retrieve novel PKM2 activators from commercially available chemical databases. Tetrahydroquinoline derivatives were identified as potential scaffolds of PKM2 activators. Thus, the hybrid virtual screening approach was applied to screen the focused tetrahydroquinoline derivatives embedded in the ZINC database. Six hit compounds were selected from the final hits and experimental studies were then performed. Compound 8 displayed a potent inhibitory effect on human lung cancer cells. Following treatment with Compound 8, cell viability, apoptosis, and reactive oxygen species (ROS) production were examined in A549 cells. Finally, we evaluated the effects of Compound 8 on mice xenograft tumor models in vivo. These results may provide important information for further research on novel PKM2 activators as antitumor agents. PMID:25214764

Virtual Microscopy in Histopathology Training: Changing Student Attitudes in 3 Successive Academic Years.

PubMed

Bertram, Christof A; Firsching, Theresa; Klopfleisch, Robert

2018-01-01

Several veterinary faculties have integrated virtual microscopy into their curricula in recent years to improve and refine their teaching techniques. The many advantages of this recent technology are described in the literature, including remote access and an equal and constant slide quality for all students. However, no study has analyzed the change of perception toward virtual microscopy at different time points of students' academic educations. In the present study, veterinary students in 3 academic years were asked for their perspectives and attitudes toward virtual microscopy and conventional light microscopy. Third-, fourth-, and fifth-year veterinary students filled out a questionnaire with 12 questions. The answers revealed that virtual microscopy was overall well accepted by students of all academic years. Most students even suggested that virtual microscopy be implemented more extensively as the modality for final histopathology examinations. Nevertheless, training in the use of light microscopy and associated skills was surprisingly well appreciated. Regardless of their academic year, most students considered these skills important and necessary, and they felt that light microscopy should not be completely replaced. The reasons for this view differed depending on academic year, as the perceived main disadvantage of virtual microscopy varied. Third-year students feared that they would not acquire sufficient light microscopy skills. Fifth-year students considered technical difficulties (i.e., insufficient transmission speed) to be the main disadvantage of this newer teaching modality.

Combining in silico and in cerebro approaches for virtual screening and pose prediction in SAMPL4.

PubMed

Voet, Arnout R D; Kumar, Ashutosh; Berenger, Francois; Zhang, Kam Y J

2014-04-01

The SAMPL challenges provide an ideal opportunity for unbiased evaluation and comparison of different approaches used in computational drug design. During the fourth round of this SAMPL challenge, we participated in the virtual screening and binding pose prediction on inhibitors targeting the HIV-1 integrase enzyme. For virtual screening, we used well known and widely used in silico methods combined with personal in cerebro insights and experience. Regular docking only performed slightly better than random selection, but the performance was significantly improved upon incorporation of additional filters based on pharmacophore queries and electrostatic similarities. The best performance was achieved when logical selection was added. For the pose prediction, we utilized a similar consensus approach that amalgamated the results of the Glide-XP docking with structural knowledge and rescoring. The pose prediction results revealed that docking displayed reasonable performance in predicting the binding poses. However, prediction performance can be improved utilizing scientific experience and rescoring approaches. In both the virtual screening and pose prediction challenges, the top performance was achieved by our approaches. Here we describe the methods and strategies used in our approaches and discuss the rationale of their performances.

Combining in silico and in cerebro approaches for virtual screening and pose prediction in SAMPL4

NASA Astrophysics Data System (ADS)

Voet, Arnout R. D.; Kumar, Ashutosh; Berenger, Francois; Zhang, Kam Y. J.

2014-04-01

The SAMPL challenges provide an ideal opportunity for unbiased evaluation and comparison of different approaches used in computational drug design. During the fourth round of this SAMPL challenge, we participated in the virtual screening and binding pose prediction on inhibitors targeting the HIV-1 integrase enzyme. For virtual screening, we used well known and widely used in silico methods combined with personal in cerebro insights and experience. Regular docking only performed slightly better than random selection, but the performance was significantly improved upon incorporation of additional filters based on pharmacophore queries and electrostatic similarities. The best performance was achieved when logical selection was added. For the pose prediction, we utilized a similar consensus approach that amalgamated the results of the Glide-XP docking with structural knowledge and rescoring. The pose prediction results revealed that docking displayed reasonable performance in predicting the binding poses. However, prediction performance can be improved utilizing scientific experience and rescoring approaches. In both the virtual screening and pose prediction challenges, the top performance was achieved by our approaches. Here we describe the methods and strategies used in our approaches and discuss the rationale of their performances.

AutoClickChem: click chemistry in silico.

PubMed

Durrant, Jacob D; McCammon, J Andrew

2012-01-01

Academic researchers and many in industry often lack the financial resources available to scientists working in "big pharma." High costs include those associated with high-throughput screening and chemical synthesis. In order to address these challenges, many researchers have in part turned to alternate methodologies. Virtual screening, for example, often substitutes for high-throughput screening, and click chemistry ensures that chemical synthesis is fast, cheap, and comparatively easy. Though both in silico screening and click chemistry seek to make drug discovery more feasible, it is not yet routine to couple these two methodologies. We here present a novel computer algorithm, called AutoClickChem, capable of performing many click-chemistry reactions in silico. AutoClickChem can be used to produce large combinatorial libraries of compound models for use in virtual screens. As the compounds of these libraries are constructed according to the reactions of click chemistry, they can be easily synthesized for subsequent testing in biochemical assays. Additionally, in silico modeling of click-chemistry products may prove useful in rational drug design and drug optimization. AutoClickChem is based on the pymolecule toolbox, a framework that may facilitate the development of future python-based programs that require the manipulation of molecular models. Both the pymolecule toolbox and AutoClickChem are released under the GNU General Public License version 3 and are available for download from http://autoclickchem.ucsd.edu.

AutoClickChem: Click Chemistry in Silico

PubMed Central

Durrant, Jacob D.; McCammon, J. Andrew

2012-01-01

Academic researchers and many in industry often lack the financial resources available to scientists working in “big pharma.” High costs include those associated with high-throughput screening and chemical synthesis. In order to address these challenges, many researchers have in part turned to alternate methodologies. Virtual screening, for example, often substitutes for high-throughput screening, and click chemistry ensures that chemical synthesis is fast, cheap, and comparatively easy. Though both in silico screening and click chemistry seek to make drug discovery more feasible, it is not yet routine to couple these two methodologies. We here present a novel computer algorithm, called AutoClickChem, capable of performing many click-chemistry reactions in silico. AutoClickChem can be used to produce large combinatorial libraries of compound models for use in virtual screens. As the compounds of these libraries are constructed according to the reactions of click chemistry, they can be easily synthesized for subsequent testing in biochemical assays. Additionally, in silico modeling of click-chemistry products may prove useful in rational drug design and drug optimization. AutoClickChem is based on the pymolecule toolbox, a framework that may facilitate the development of future python-based programs that require the manipulation of molecular models. Both the pymolecule toolbox and AutoClickChem are released under the GNU General Public License version 3 and are available for download from http://autoclickchem.ucsd.edu. PMID:22438795

In silico clinical trials: concepts and early adoptions.

PubMed

Pappalardo, Francesco; Russo, Giulia; Tshinanu, Flora Musuamba; Viceconti, Marco

2018-06-02

Innovations in information and communication technology infuse all branches of science, including life sciences. Nevertheless, healthcare is historically slow in adopting technological innovation, compared with other industrial sectors. In recent years, new approaches in modelling and simulation have started to provide important insights in biomedicine, opening the way for their potential use in the reduction, refinement and partial substitution of both animal and human experimentation. In light of this evidence, the European Parliament and the United States Congress made similar recommendations to their respective regulators to allow wider use of modelling and simulation within the regulatory process. In the context of in silico medicine, the term 'in silico clinical trials' refers to the development of patient-specific models to form virtual cohorts for testing the safety and/or efficacy of new drugs and of new medical devices. Moreover, it could be envisaged that a virtual set of patients could complement a clinical trial (reducing the number of enrolled patients and improving statistical significance), and/or advise clinical decisions. This article will review the current state of in silico clinical trials and outline directions for a full-scale adoption of patient-specific modelling and simulation in the regulatory evaluation of biomedical products. In particular, we will focus on the development of vaccine therapies, which represents, in our opinion, an ideal target for this innovative approach.

Structural insights into pharmacophore-assisted in silico identification of protein-protein interaction inhibitors for inhibition of human toll-like receptor 4 - myeloid differentiation factor-2 (hTLR4-MD-2) complex.

PubMed

Mishra, Vinita; Pathak, Chandramani

2018-05-29

Toll-like receptor 4 (TLR4) is a member of Toll-Like Receptors (TLRs) family that serves as a receptor for bacterial lipopolysaccharide (LPS). TLR4 alone cannot recognize LPS without aid of co-receptor myeloid differentiation factor-2 (MD-2). Binding of LPS with TLR4 forms a LPS-TLR4-MD-2 complex and directs downstream signaling for activation of immune response, inflammation and NF-κB activation. Activation of TLR4 signaling is associated with various pathophysiological consequences. Therefore, targeting protein-protein interaction (PPI) in TLR4-MD-2 complex formation could be an attractive therapeutic approach for targeting inflammatory disorders. The aim of present study was directed to identify small molecule PPI inhibitors (SMPPIIs) using pharmacophore mapping-based approach of computational drug discovery. Here, we had retrieved the information about the hot spot residues and their pharmacophoric features at both primary (TLR4-MD-2) and dimerization (MD-2-TLR4*) protein-protein interaction interfaces in TLR4-MD-2 homo-dimer complex using in silico methods. Promising candidates were identified after virtual screening, which may restrict TLR4-MD-2 protein-protein interaction. In silico off-target profiling over the virtually screened compounds revealed other possible molecular targets. Two of the virtually screened compounds (C11 and C15) were predicted to have an inhibitory concentration in μM range after HYDE assessment. Molecular dynamics simulation study performed for these two compounds in complex with target protein confirms the stability of the complex. After virtual high throughput screening we found selective hTLR4-MD-2 inhibitors, which may have therapeutic potential to target chronic inflammatory diseases.

Traditional microscopy instruction versus process-oriented virtual microscopy instruction: a naturalistic experiment with control group.

PubMed

Helle, Laura; Nivala, Markus; Kronqvist, Pauliina; Gegenfurtner, Andreas; Björk, Pasi; Säljö, Roger

2011-03-30

Virtual microscopy is being introduced in medical education as an approach for learning how to interpret information in microscopic specimens. It is, however, far from evident how to incorporate its use into existing teaching practice. The aim of the study was to explore the consequences of introducing virtual microscopy tasks into an undergraduate pathology course in an attempt to render the instruction more process-oriented. The research questions were: 1) How is virtual microscopy perceived by students? 2) Does work on virtual microscopy tasks contribute to improvement in performance in microscopic pathology in comparison with attending assistant-led demonstrations only? During a one-week period, an experimental group completed three sets of virtual microscopy homework assignments in addition to attending demonstrations. A control group attended the demonstrations only. Performance in microscopic pathology was measured by a pre-test and a post-test. Student perceptions of regular instruction and virtual microscopy were collected one month later by administering the Inventory of Intrinsic Motivation and open-ended questions. The students voiced an appreciation for virtual microscopy for the purposes of the course and for self-study. As for learning gains, the results indicated that learning was speeded up in a subgroup of students consisting of conscientious high achievers. The enriched instruction model may be suited as such for elective courses following the basic course. However, the instructional model needs further development to be suited for basic courses.

Virtual screening and optimization of Type II inhibitors of JAK2 from a natural product library.

PubMed

Ma, Dik-Lung; Chan, Daniel Shiu-Hin; Wei, Guo; Zhong, Hai-Jing; Yang, Hui; Leung, Lai To; Gullen, Elizabeth A; Chiu, Pauline; Cheng, Yung-Chi; Leung, Chung-Hang

2014-11-21

Amentoflavone has been identified as a JAK2 inhibitor by structure-based virtual screening of a natural product library. In silico optimization using the DOLPHIN model yielded analogues with enhanced potency against JAK2 activity and HCV activity in cellulo. Molecular modeling and kinetic experiments suggested that the analogues may function as Type II inhibitors of JAK2.

Using Virtual Microscopy to Scaffold Learning of Pathology: A Naturalistic Experiment on the Role of Visual and Conceptual Cues

ERIC Educational Resources Information Center

Nivala, Markus; Saljo, Roger; Rystedt, Hans; Kronqvist, Pauliina; Lehtinen, Erno

2012-01-01

New representational technologies, such as virtual microscopy, create new affordances for medical education. In the article, a study on the following two issues is reported: (a) How does collaborative use of virtual microscopy shape students' engagement with and learning from virtual slides of tissue specimen? (b) How do visual and conceptual cues…

The e-evolution of microscopy in dental education.

PubMed

Farah, Camile S; Maybury, Terrence S

2009-08-01

Recent technological innovation has now made it possible to turn the computer into a microscope. This has entailed a shift from light microscopy to virtual microscopy. This development then foregrounds the issue of the pedagogy involved in this move from the analogue technology of the light microscope to the digital, computerized instance of virtual microscopy. In order to address this issue, undergraduate students enrolled in the Bachelor of Dental Science program at the University of Queensland School of Dentistry were surveyed to ascertain their preference for light or virtual microscopy. The value of this study is that it was conducted on the same cohort of students in two separate courses in 2006 and 2008, giving it longitudinal validity. The responses were overwhelmingly in favor of virtual microscopy. When it came to completely replacing the light microscope with virtual microscopy, however, students were much more ambivalent about such a wholesale change although this was less of an issue in the senior year. This shift from light to virtual microscopy signals larger changes in the tertiary sector from print-literate to electronic forms of knowledge and from teacher-centered to student-focused frames of learning. In short, we are in the midst of the e-evolution of microscopy in dental education.

Discovery of Anti-Hypertensive Oligopeptides from Adlay Based on In Silico Proteolysis and Virtual Screening

PubMed Central

Qiao, Liansheng; Li, Bin; Chen, Yankun; Li, Lingling; Chen, Xi; Wang, Lingzhi; Lu, Fang; Luo, Ganggang; Li, Gongyu; Zhang, Yanling

2016-01-01

Adlay (Coix larchryma-jobi L.) was the commonly used Traditional Chinese Medicine (TCM) with high content of seed storage protein. The hydrolyzed bioactive oligopeptides of adlay have been proven to be anti-hypertensive effective components. However, the structures and anti-hypertensive mechanism of bioactive oligopeptides from adlay were not clear. To discover the definite anti-hypertensive oligopeptides from adlay, in silico proteolysis and virtual screening were implemented to obtain potential oligopeptides, which were further identified by biochemistry assay and molecular dynamics simulation. In this paper, ten sequences of adlay prolamins were collected and in silico hydrolyzed to construct the oligopeptide library with 134 oligopeptides. This library was reverse screened by anti-hypertensive pharmacophore database, which was constructed by our research team and contained ten anti-hypertensive targets. Angiotensin-I converting enzyme (ACE) was identified as the main potential target for the anti-hypertensive activity of adlay oligopeptides. Three crystal structures of ACE were utilized for docking studies and 19 oligopeptides were finally identified with potential ACE inhibitory activity. According to mapping features and evaluation indexes of pharmacophore and docking, three oligopeptides were selected for biochemistry assay. An oligopeptide sequence, NPATY (IC50 = 61.88 ± 2.77 µM), was identified as the ACE inhibitor by reverse-phase high performance liquid chromatography (RP-HPLC) assay. Molecular dynamics simulation of NPATY was further utilized to analyze interactive bonds and key residues. ALA354 was identified as a key residue of ACE inhibitors. Hydrophobic effect of VAL518 and electrostatic effects of HIS383, HIS387, HIS513 and Zn2+ were also regarded as playing a key role in inhibiting ACE activities. This study provides a research strategy to explore the pharmacological mechanism of Traditional Chinese Medicine (TCM) proteins based on in silico proteolysis and virtual screening, which could be beneficial to reveal the pharmacological action of TCM proteins and provide new lead compounds for peptides-based drug design. PMID:27983650

The virtual microscopy database-sharing digital microscope images for research and education.

PubMed

Lee, Lisa M J; Goldman, Haviva M; Hortsch, Michael

2018-02-14

Over the last 20 years, virtual microscopy has become the predominant modus of teaching the structural organization of cells, tissues, and organs, replacing the use of optical microscopes and glass slides in a traditional histology or pathology laboratory setting. Although virtual microscopy image files can easily be duplicated, creating them requires not only quality histological glass slides but also an expensive whole slide microscopic scanner and massive data storage devices. These resources are not available to all educators and researchers, especially at new institutions in developing countries. This leaves many schools without access to virtual microscopy resources. The Virtual Microscopy Database (VMD) is a new resource established to address this problem. It is a virtual image file-sharing website that allows researchers and educators easy access to a large repository of virtual histology and pathology image files. With the support from the American Association of Anatomists (Bethesda, MD) and MBF Bioscience Inc. (Williston, VT), registration and use of the VMD are currently free of charge. However, the VMD site is restricted to faculty and staff of research and educational institutions. Virtual Microscopy Database users can upload their own collection of virtual slide files, as well as view and download image files for their own non-profit educational and research purposes that have been deposited by other VMD clients. Anat Sci Educ. © 2018 American Association of Anatomists. © 2018 American Association of Anatomists.

Innovative Strategies for Clinical Microscopy Instruction: Virtual Versus Light Microscopy.

PubMed

McDaniel, M Jane; Russell, Gregory B; Crandall, Sonia J

2018-06-01

The purpose of the study was to compare virtual microscopy with light microscopy to determine differences in learning outcomes and learner attitudes in teaching clinical microscopy to physician assistant (PA) students. A prospective, randomized, crossover design study was conducted with a convenience sample of 67 first-year PA students randomized to 2 groups. One group used light microscopes to find microscopic structures, whereas the other group used instructor-directed video streaming of microscopic elements. At the midpoint of the study, the groups switched instructional strategies. Learning outcomes were assessed via posttest after each section of the study, with comparison of final practical examination results to previous cohorts. Attitudes about the 2 educational strategies were assessed through a postcourse questionnaire with a Likert scale. Analysis of the first posttest demonstrated that students in the video-streamed group had significantly better learning outcomes than those in the light microscopy group (P = .004; Cohen's d = 0.74). Analysis of the posttest after crossover showed no differences between the 2 groups (P = .48). Between the 2 posttests, students first assigned to the light microscopy group scored a 6.6 mean point increase (±10.4 SD; p = .0011), whereas students first assigned to the virtual microscopy group scored a 1.3 mean point increase (±7.1 SD; p = .29). The light microscopy group improved more than the virtual microscopy group (P = .019). Analysis of practical examination data revealed higher scores for the study group compared with 5 previous cohorts of first-year students (P < .0001; Cohen's d = 0.66). Students preferred virtual microscopy to traditional light microscopy. Virtual microscopy is an effective educational strategy, and students prefer this method when learning to interpret images of clinical specimens.

In Silico Dynamics: computer simulation in a Virtual Embryo (SOT)

EPA Science Inventory

Abstract: Utilizing cell biological information to predict higher order biological processes is a significant challenge in predictive toxicology. This is especially true for highly dynamical systems such as the embryo where morphogenesis, growth and differentiation require preci...

In silico pharmacology for drug discovery: applications to targets and beyond

PubMed Central

Ekins, S; Mestres, J; Testa, B

2007-01-01

Computational (in silico) methods have been developed and widely applied to pharmacology hypothesis development and testing. These in silico methods include databases, quantitative structure-activity relationships, similarity searching, pharmacophores, homology models and other molecular modeling, machine learning, data mining, network analysis tools and data analysis tools that use a computer. Such methods have seen frequent use in the discovery and optimization of novel molecules with affinity to a target, the clarification of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The first part of this review discussed the methods that have been used for virtual ligand and target-based screening and profiling to predict biological activity. The aim of this second part of the review is to illustrate some of the varied applications of in silico methods for pharmacology in terms of the targets addressed. We will also discuss some of the advantages and disadvantages of in silico methods with respect to in vitro and in vivo methods for pharmacology research. Our conclusion is that the in silico pharmacology paradigm is ongoing and presents a rich array of opportunities that will assist in expediating the discovery of new targets, and ultimately lead to compounds with predicted biological activity for these novel targets. PMID:17549046

Multicellular Models of Morphogenesis

EPA Science Inventory

EPA’s Virtual Embryo project (v-Embryo™), in collaboration with developers of CompuCell3D, aims to create computer models of morphogenesis that can be used to address the effects of chemical perturbation on embryo development at the cellular level. Such computational (in silico) ...

A digital atlas of breast histopathology: an application of web based virtual microscopy

PubMed Central

Lundin, M; Lundin, J; Helin, H; Isola, J

2004-01-01

Aims: To develop an educationally useful atlas of breast histopathology, using advanced web based virtual microscopy technology. Methods: By using a robotic microscope and software adopted and modified from the aerial and satellite imaging industry, a virtual microscopy system was developed that allows fully automated slide scanning and image distribution via the internet. More than 150 slides were scanned at high resolution with an oil immersion ×40 objective (numerical aperture, 1.3) and archived on an image server residing in a high speed university network. Results: A publicly available website was constructed, http://www.webmicroscope.net/breastatlas, which features a comprehensive virtual slide atlas of breast histopathology according to the World Health Organisation 2003 classification. Users can view any part of an entire specimen at any magnification within a standard web browser. The virtual slides are supplemented with concise textual descriptions, but can also be viewed without diagnostic information for self assessment of histopathology skills. Conclusions: Using the technology described here, it is feasible to develop clinically and educationally useful virtual microscopy applications. Web based virtual microscopy will probably become widely used at all levels in pathology teaching. PMID:15563669

An Integrated In Silico Method to Discover Novel Rock1 Inhibitors: Multi- Complex-Based Pharmacophore, Molecular Dynamics Simulation and Hybrid Protocol Virtual Screening.

PubMed

Chen, Haining; Li, Sijia; Hu, Yajiao; Chen, Guo; Jiang, Qinglin; Tong, Rongsheng; Zang, Zhihe; Cai, Lulu

2016-01-01

Rho-associated, coiled-coil containing protein kinase 1 (ROCK1) is an important regulator of focal adhesion, actomyosin contraction and cell motility. In this manuscript, a combination of the multi-complex-based pharmacophore (MCBP), molecular dynamics simulation and a hybrid protocol of a virtual screening method, comprised of multipharmacophore- based virtual screening (PBVS) and ensemble docking-based virtual screening (DBVS) methods were used for retrieving novel ROCK1 inhibitors from the natural products database embedded in the ZINC database. Ten hit compounds were selected from the hit compounds, and five compounds were tested experimentally. Thus, these results may provide valuable information for further discovery of more novel ROCK1 inhibitors.

Virtual medicinal chemistry: in silico pre-docking functional group transformation for discovery of novel inhibitors of botulinum toxin serotype A light chain.

PubMed

O'Malley, Sean; Sareth, Sina; Jiao, Guan-Sheng; Kim, Seongjin; Thai, April; Cregar-Hernandez, Lynne; McKasson, Linda; Margosiak, Stephen A; Johnson, Alan T

2013-05-01

A novel method for applying high-throughput docking to challenging metalloenzyme targets is described. The method utilizes information-based virtual transformation of library carboxylates to hydroxamic acids prior to docking, followed by compound acquisition, one-pot (two steps) chemical synthesis and in vitro screening. In two experiments targeting the botulinum neurotoxin serotype A metalloprotease light chain, hit rates of 32% and 18% were observed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Chemical Space Expansion of Bromodomain Ligands Guided by in Silico Virtual Couplings (AutoCouple).

PubMed

Batiste, Laurent; Unzue, Andrea; Dolbois, Aymeric; Hassler, Fabrice; Wang, Xuan; Deerain, Nicholas; Zhu, Jian; Spiliotopoulos, Dimitrios; Nevado, Cristina; Caflisch, Amedeo

2018-02-28

Expanding the chemical space and simultaneously ensuring synthetic accessibility is of upmost importance, not only for the discovery of effective binders for novel protein classes but, more importantly, for the development of compounds against hard-to-drug proteins. Here, we present AutoCouple, a de novo approach to computational ligand design focused on the diversity-oriented generation of chemical entities via virtual couplings. In a benchmark application, chemically diverse compounds with low-nanomolar potency for the CBP bromodomain and high selectivity against the BRD4(1) bromodomain were achieved by the synthesis of about 50 derivatives of the original fragment. The binding mode was confirmed by X-ray crystallography, target engagement in cells was demonstrated, and antiproliferative activity was showcased in three cancer cell lines. These results reveal AutoCouple as a useful in silico coupling method to expand the chemical space in hit optimization campaigns resulting in potent, selective, and cell permeable bromodomain ligands.

Docking studies of antidepressants against single crystal structure of tryptophan 2, 3-dioxygenase using Molegro Virtual Docker software.

PubMed

Dawood, Shazia; Zarina, Shamshad; Bano, Samina

2014-09-01

Tryptophan 2, 3-dioxygenase (TDO) a heme containing enzyme found in mammalian liver is responsible for tryptophan (Trp) catabolism. Trp is an essential amino acid that is degraded in to N-formylkynurenine by the action of TDO. The protein ligand interaction plays a significant role in structural based drug designing. The current study illustrates the binding of established antidepressants (ADs) against TDO enzyme using in-silico docking studies. For this purpose, Fluoxetine, Paroxetine, Sertraline, Fluvoxamine, Seproxetine, Citalopram, Moclobamide, Hyperforin and Amoxepine were selected. In-silico docking studies were carried out using Molegro Virtual Docker (MVD) software. Docking results show that all ADs fit well in the active site of TDO moreover Hyperforin and Paroxetine exhibited high docking scores of -152.484k cal/mol and -139.706k cal/mol, respectively. It is concluded that Hyperforin and Paroxetine are possible lead molecules because of their high docking scores as compared to other ADs examined. Therefore, these two ADs stand as potent inhibitors of TDO enzyme.

QSAR Methods.

PubMed

Gini, Giuseppina

2016-01-01

In this chapter, we introduce the basis of computational chemistry and discuss how computational methods have been extended to some biological properties and toxicology, in particular. Since about 20 years, chemical experimentation is more and more replaced by modeling and virtual experimentation, using a large core of mathematics, chemistry, physics, and algorithms. Then we see how animal experiments, aimed at providing a standardized result about a biological property, can be mimicked by new in silico methods. Our emphasis here is on toxicology and on predicting properties through chemical structures. Two main streams of such models are available: models that consider the whole molecular structure to predict a value, namely QSAR (Quantitative Structure Activity Relationships), and models that find relevant substructures to predict a class, namely SAR. The term in silico discovery is applied to chemical design, to computational toxicology, and to drug discovery. We discuss how the experimental practice in biological science is moving more and more toward modeling and simulation. Such virtual experiments confirm hypotheses, provide data for regulation, and help in designing new chemicals.

Discovery of Novel Anti-prion Compounds Using In Silico and In Vitro Approaches

PubMed Central

Hyeon, Jae Wook; Choi, Jiwon; Kim, Su Yeon; Govindaraj, Rajiv Gandhi; Jam Hwang, Kyu; Lee, Yeong Seon; An, Seong Soo A.; Lee, Myung Koo; Joung, Jong Young; No, Kyoung Tai; Lee, Jeongmin

2015-01-01

Prion diseases are associated with the conformational conversion of the physiological form of cellular prion protein (PrPC) to the pathogenic form, PrPSc. Compounds that inhibit this process by blocking conversion to the PrPSc could provide useful anti-prion therapies. However, no suitable drugs have been identified to date. To identify novel anti-prion compounds, we developed a combined structure- and ligand-based virtual screening system in silico. Virtual screening of a 700,000-compound database, followed by cluster analysis, identified 37 compounds with strong interactions with essential hotspot PrP residues identified in a previous study of PrPC interaction with a known anti-prion compound (GN8). These compounds were tested in vitro using a multimer detection system, cell-based assays, and surface plasmon resonance. Some compounds effectively reduced PrPSc levels and one of these compounds also showed a high binding affinity for PrPC. These results provide a promising starting point for the development of anti-prion compounds. PMID:26449325

[Clinical pathology on the verge of virtual microscopy].

PubMed

Tolonen, Teemu; Näpänkangas, Juha; Isola, Jorma

2015-01-01

For more than 100 years, examinations of pathology specimens have relied on the use of the light microscope. The technological progress of the last few years is enabling the digitizing of histologic specimen slides and application of the virtual microscope in diagnostics. Virtual microscopy will facilitate consultation possibilities, and digital image analysis serves to enhance the level of diagnostics. Organizing and monitoring clinicopathological meetings will become easier. Digital archive of histologic specimens and the virtual microscopy network are expected to benefit training and research as well, particularly what applies to the Finnish biobank network which is currently being established.

Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform.

PubMed

Marshall-Colon, Amy; Long, Stephen P; Allen, Douglas K; Allen, Gabrielle; Beard, Daniel A; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A J; Cox, Donna J; Hart, John C; Hirst, Peter M; Kannan, Kavya; Katz, Daniel S; Lynch, Jonathan P; Millar, Andrew J; Panneerselvam, Balaji; Price, Nathan D; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J; Voit, Eberhard O; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang

2017-01-01

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop.

Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform

PubMed Central

Marshall-Colon, Amy; Long, Stephen P.; Allen, Douglas K.; Allen, Gabrielle; Beard, Daniel A.; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A. J.; Cox, Donna J.; Hart, John C.; Hirst, Peter M.; Kannan, Kavya; Katz, Daniel S.; Lynch, Jonathan P.; Millar, Andrew J.; Panneerselvam, Balaji; Price, Nathan D.; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G.; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J.; Voit, Eberhard O.; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang

2017-01-01

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop. PMID:28555150

Transition to Virtual Microscopy in Medical Undergraduate Pathology Education: First Experience of Turkey in Dokuz Eylül University Hospital.

PubMed

Sağol, Özgül; Yörükoğlu, Kutsal; Lebe, Banu; Durak, Merih Güray; Ulukuş, Çağnur; Tuna, Burçin; Musal, Berna; Canda, Tülay; Özer, Erdener

2015-01-01

Pathology education includes an important visual part supporting a wide range of theoretical knowledge. However, the use of traditional microscopes in pathology education has declined over the last decade and there is a lack of interest for microscopy. Virtual microscopy, which was first described in 1985 and has experienced a revolution since 2000, is an alternative technique to conventional microscopy, in which microscopic slides are scanned to form digital images and stored in the web. The aim of this study was to evaluate the use of virtual microscopy in practical pathology sessions and its effects on our students and undergraduate education at our faculty. Second and third year medical students who were used to conventional microscopes were included in the study. The practical sessions were carried out via virtual slides and the effect of the new technique was investigated by a scale at the end of each session. Academic staff from the pathology department joined sessions to promote discussion and respond to questions. Student ratings were analysed statistically. The evaluation of the ratings showed that the students were easily adapted to the use of virtual microscopy. They found it user-friendly and thought that the opportunity of viewing slides at home was advantageous. Collaboration between students and interactive discussions was also improved with this technique. It was concluded that the use of virtual microscopy could contribute to the pathology education of our students.

Virtual microscopy and digital pathology in training and education.

PubMed

Hamilton, Peter W; Wang, Yinhai; McCullough, Stephen J

2012-04-01

Traditionally, education and training in pathology has been delivered using textbooks, glass slides and conventional microscopy. Over the last two decades, the number of web-based pathology resources has expanded dramatically with centralized pathological resources being delivered to many students simultaneously. Recently, whole slide imaging technology allows glass slides to be scanned and viewed on a computer screen via dedicated software. This technology is referred to as virtual microscopy and has created enormous opportunities in pathological training and education. Students are able to learn key histopathological skills, e.g. to identify areas of diagnostic relevance from an entire slide, via a web-based computer environment. Students no longer need to be in the same room as the slides. New human-computer interfaces are also being developed using more natural touch technology to enhance the manipulation of digitized slides. Several major initiatives are also underway introducing online competency and diagnostic decision analysis using virtual microscopy and have important future roles in accreditation and recertification. Finally, researchers are investigating how pathological decision-making is achieved using virtual microscopy and modern eye-tracking devices. Virtual microscopy and digital pathology will continue to improve how pathology training and education is delivered. © 2012 The Authors APMIS © 2012 APMIS.

Implementing digital technology to enhance student learning of pathology.

PubMed

Farah, C S; Maybury, T

2009-08-01

The introduction of digital technologies into the dental curriculum is an ongoing feature of broader changes going on in tertiary education. This report examines the introduction of digital virtual microscopy technology into the curriculum of the School of Dentistry at the University of Queensland (UQ) in Brisbane, Australia. Sixty students studying a course in pathology in 2005 were introduced to virtual microscopy technology alongside the more traditional light microscope and then asked to evaluate their own learning outcomes from this technology via a structured 5-point LIKART survey. A wide variety of questions dealing the pedagogic implications of the introduction of virtual microscopy into pathology were asked of students with the overall result being that it positively enhanced their learning of pathology via digital microscopic means. The success of virtual microscopy in dentistry at UQ is then discussed in the larger context of changes going on in tertiary education. In particular, the change from the print-literate tradition to the electronic one, that is from 'literacy to electracy'. Virtual microscopy is designated as a component of this transformation to electracy. Whilst traditional microscopic skills may still be valued in dental curricula, the move to virtual microscopy and computer-assisted, student-centred learning of pathology appears to enhance the learning experience in relation to its effectiveness in helping students engage and interact with the course material.

Going glass to digital: virtual microscopy as a simulation-based revolution in pathology and laboratory science.

PubMed

Nelson, Danielle; Ziv, Amitai; Bandali, Karim S

2012-10-01

The recent technological advance of digital high resolution imaging has allowed the field of pathology and medical laboratory science to undergo a dramatic transformation with the incorporation of virtual microscopy as a simulation-based educational and diagnostic tool. This transformation has correlated with an overall increase in the use of simulation in medicine in an effort to address dwindling clinical resource availability and patient safety issues currently facing the modern healthcare system. Virtual microscopy represents one such simulation-based technology that has the potential to enhance student learning and readiness to practice while revolutionising the ability to clinically diagnose pathology collaboratively across the world. While understanding that a substantial amount of literature already exists on virtual microscopy, much more research is still required to elucidate the full capabilities of this technology. This review explores the use of virtual microscopy in medical education and disease diagnosis with a unique focus on key requirements needed to take this technology to the next level in its use in medical education and clinical practice.

Republished: going glass to digital: virtual microscopy as a simulation-based revolution in pathology and laboratory science.

PubMed

Nelson, Danielle; Ziv, Amitai; Bandali, Karim S

2013-10-01

The recent technological advance of digital high resolution imaging has allowed the field of pathology and medical laboratory science to undergo a dramatic transformation with the incorporation of virtual microscopy as a simulation-based educational and diagnostic tool. This transformation has correlated with an overall increase in the use of simulation in medicine in an effort to address dwindling clinical resource availability and patient safety issues currently facing the modern healthcare system. Virtual microscopy represents one such simulation-based technology that has the potential to enhance student learning and readiness to practice while revolutionising the ability to clinically diagnose pathology collaboratively across the world. While understanding that a substantial amount of literature already exists on virtual microscopy, much more research is still required to elucidate the full capabilities of this technology. This review explores the use of virtual microscopy in medical education and disease diagnosis with a unique focus on key requirements needed to take this technology to the next level in its use in medical education and clinical practice.

ToxCast and Virtual Embryo: in vitro data and in silico models for predictive toxicology

EPA Science Inventory

Human populations may be exposed to thousands of chemicals only a fraction of which have detailed toxicity data. Traditional in vivo animal testing is costly, lengthy and normally conducted with dosages that exceed relatively insensitive to concentrations of chemicals at realisti...

Virtual microscopy-The future of teaching histology in the medical curriculum?

PubMed

Paulsen, Friedrich P; Eichhorn, Michael; Bräuer, Lars

2010-12-20

Conventional continuing education in microscopic anatomy, histopathology, hematology and microbiology has hitherto been carried out using numerous sets of sectioned tissue specimens in a microscopy laboratory. In comparison, after digitalization of the sections it would be possible to access teaching specimens via virtual microscopy and the internet at any time and place. This would make it possible to put innumerable new learning scenarios into practice. The present article elucidates the advantages of virtual microscopy in histology instruction and presents a concept of how virtual microscopy could be introduced into the teaching of microscopic anatomy in several steps. Initially, the presently existing microscopic teaching specimens would be digitalized and made available on-line without restriction. In a second step, instruction would be shifted to an emphasis on virtual microscopy, utilizing all of the advantages offered by the technique. In a third step, the microscopic contents could be networked with other anatomical, radiological and clinical content on-line, thus opening new learning perspectives for students of human and dental medicine as well as those of medically related courses of study. The advantages and disadvantages of such a concept as well as some possibly arising consequences are discussed in the following. 2010 Elsevier GmbH. All rights reserved.

An Investigation of the Incorporation of Virtual Microscopy in the Cytotechnology Educational Curriculum

ERIC Educational Resources Information Center

Mukherjee, Maheswari S.

2012-01-01

Traditionally, cytotechnology (CT) students have been trained by using light microscopy (LM) and glass slides. However, this method of training has some drawbacks. Several other educational programs with similar issues have incorporated virtual microscopy (VM) in their curricula. In VM, the specimens on glass slides are converted into virtual…

Electronic Blending in Virtual Microscopy

ERIC Educational Resources Information Center

Maybury, Terrence S.; Farah, Camile S.

2010-01-01

Virtual microscopy (VM) is a relatively new technology that transforms the computer into a microscope. In essence, VM allows for the scanning and transfer of glass slides from light microscopy technology to the digital environment of the computer. This transition is also a function of the change from print knowledge to electronic knowledge, or as…

Optical versus Virtual: Teaching Assistant Perceptions of the Use of Virtual Microscopy in an Undergraduate Human Anatomy Course

ERIC Educational Resources Information Center

Collier, Larissa; Dunham, Stacey; Braun, Mark W.; O'Loughlin, Valerie Dean

2012-01-01

Many studies that evaluate the introduction of technology in the classroom focus on student performance and student evaluations. This study focuses on instructor evaluation of the introduction of virtual microscopy into an undergraduate anatomy class. Semi-structured interviews were conducted with graduate teaching assistants (TA) and analyzed…

In silico evaluation of gadofosveset pharmacokinetics in different population groups using the Simcyp® simulator platform.

PubMed

Spanakis, Marios; Marias, Kostas

2014-12-01

Gadofosveset is a Gd-based contrast agent used for magnetic resonance imaging (MRI). Gadolinium kinetic distribution models are implemented in T1-weighted dynamic contrast-enhanced perfusion MRI for characterization of lesion sites in the body. Physiology changes in a disease state potentially can influence the pharmacokinetics of drugs and to this respect modify the distribution properties of contrast agents. This work focuses on the in silico modelling of pharmacokinetic properties of gadofosveset in different population groups through the application of physiologically-based pharmacokinetic models (PBPK) embedded in Simcyp® population pharmacokinetics platform. Physicochemical and pharmacokinetic properties of gadofosveset were introduced into Simcyp® simulator platform and a min-PBPK model was applied. In silico clinical trials were generated simulating the administration of the recommended dose for the contrast agent (i.v., 30 mg/kg) in population cohorts of healthy volunteers, obese, renal and liver impairment, and in a generated virtual oncology population. Results were evaluated regarding basic pharmacokinetic parameters of Cmax, AUC and systemic CL and differences were assessed through ANOVA and estimation of ratio of geometric mean between healthy volunteers and the other population groups. Simcyp® predicted a mean Cmax = 551.60 mg/l, a mean AUC = 4079.12 mg/L*h and a mean systemic CL = 0.56 L/h for the virtual population of healthy volunteers. Obese population showed a modulation in Cmax and CL, attributed to increased administered dose. In renal and liver impairment cohorts a significant modulation in Cmax, AUC and CL of gadofosveset is predicted. Oncology population exhibited statistical significant differences regarding AUC when compared with healthy volunteers. This work employed Simcyp® population pharmacokinetics platform in order to compute gadofosveset's pharmacokinetic profiles through PBPK models and in silico clinical trials and evaluate possible differences between population groups. The approach showed promising results that could provide new insights regarding administration of contrast agents in special population cohorts. In silico pharmacokinetics could further be used for evaluating of possible toxicity, interpretation of MRI PK image maps and development of novel contrast agents.

Crops in silico: Generating virtual crops using an integrative and multi-scale modeling platform

USDA-ARS?s Scientific Manuscript database

There are currently 795 million hungry people in the world and 98 percent of them are in developing countries. Food demand is expected to increase by 70% by 2050. With a reduction in arable land, decreases in water availability, and an increasing impact of climate change, innovative technologies are...

Identification of potential glutaminyl cyclase inhibitors from lead-like libraries by in silico and in vitro fragment-based screening.

PubMed

Szaszkó, Mária; Hajdú, István; Flachner, Beáta; Dobi, Krisztina; Magyar, Csaba; Simon, István; Lőrincz, Zsolt; Kapui, Zoltán; Pázmány, Tamás; Cseh, Sándor; Dormán, György

2017-02-01

A glutaminyl cyclase (QC) fragment library was in silico selected by disconnection of the structure of known QC inhibitors and by lead-like 2D virtual screening of the same set. The resulting fragment library (204 compounds) was acquired from commercial suppliers and pre-screened by differential scanning fluorimetry followed by functional in vitro assays. In this way, 10 fragment hits were identified ([Formula: see text]5 % hit rate, best inhibitory activity: 16 [Formula: see text]). The in vitro hits were then docked to the active site of QC, and the best scoring compounds were analyzed for binding interactions. Two fragments bound to different regions in a complementary manner, and thus, linking those fragments offered a rational strategy to generate novel QC inhibitors. Based on the structure of the virtual linked fragment, a 77-membered QC target focused library was selected from vendor databases and docked to the active site of QC. A PubChem search confirmed that the best scoring analogues are novel, potential QC inhibitors.

Saturated virtual fluorescence emission difference microscopy based on detector array

NASA Astrophysics Data System (ADS)

Liu, Shaocong; Sun, Shiyi; Kuang, Cuifang; Ge, Baoliang; Wang, Wensheng; Liu, Xu

2017-07-01

Virtual fluorescence emission difference microscopy (vFED) has been proposed recently to enhance the lateral resolution of confocal microscopy with a detector array, implemented by scanning a doughnut-shaped pattern. Theoretically, the resolution can be enhanced by around 1.3-fold compared with that in confocal microscopy. For further improvement of the resolving ability of vFED, a novel method is presented utilizing fluorescence saturation for super-resolution imaging, which we called saturated virtual fluorescence emission difference microscopy (svFED). With a point detector array, matched solid and hollow point spread functions (PSF) can be obtained by photon reassignment, and the difference results between them can be used to boost the transverse resolution. Results show that the diffraction barrier can be surpassed by at least 34% compared with that in vFED and the resolution is around 2-fold higher than that in confocal microscopy.

Cytopathology whole slide images and adaptive tutorials for postgraduate pathology trainees: a randomized crossover trial.

PubMed

Van Es, Simone L; Kumar, Rakesh K; Pryor, Wendy M; Salisbury, Elizabeth L; Velan, Gary M

2015-09-01

To determine whether cytopathology whole slide images and virtual microscopy adaptive tutorials aid learning by postgraduate trainees, we designed a randomized crossover trial to evaluate the quantitative and qualitative impact of whole slide images and virtual microscopy adaptive tutorials compared with traditional glass slide and textbook methods of learning cytopathology. Forty-three anatomical pathology registrars were recruited from Australia, New Zealand, and Malaysia. Online assessments were used to determine efficacy, whereas user experience and perceptions of efficiency were evaluated using online Likert scales and open-ended questions. Outcomes of online assessments indicated that, with respect to performance, learning with whole slide images and virtual microscopy adaptive tutorials was equivalent to using traditional methods. High-impact learning, efficiency, and equity of learning from virtual microscopy adaptive tutorials were strong themes identified in open-ended responses. Participants raised concern about the lack of z-axis capability in the cytopathology whole slide images, suggesting that delivery of z-stacked whole slide images online may be important for future educational development. In this trial, learning cytopathology with whole slide images and virtual microscopy adaptive tutorials was found to be as effective as and perceived as more efficient than learning from glass slides and textbooks. The use of whole slide images and virtual microscopy adaptive tutorials has the potential to provide equitable access to effective learning from teaching material of consistently high quality. It also has broader implications for continuing professional development and maintenance of competence and quality assurance in specialist practice. Copyright © 2015 Elsevier Inc. All rights reserved.

ChemScreener: A Distributed Computing Tool for Scaffold based Virtual Screening.

PubMed

Karthikeyan, Muthukumarasamy; Pandit, Deepak; Vyas, Renu

2015-01-01

In this work we present ChemScreener, a Java-based application to perform virtual library generation combined with virtual screening in a platform-independent distributed computing environment. ChemScreener comprises a scaffold identifier, a distinct scaffold extractor, an interactive virtual library generator as well as a virtual screening module for subsequently selecting putative bioactive molecules. The virtual libraries are annotated with chemophore-, pharmacophore- and toxicophore-based information for compound prioritization. The hits selected can then be further processed using QSAR, docking and other in silico approaches which can all be interfaced within the ChemScreener framework. As a sample application, in this work scaffold selectivity, diversity, connectivity and promiscuity towards six important therapeutic classes have been studied. In order to illustrate the computational power of the application, 55 scaffolds extracted from 161 anti-psychotic compounds were enumerated to produce a virtual library comprising 118 million compounds (17 GB) and annotated with chemophore, pharmacophore and toxicophore based features in a single step which would be non-trivial to perform with many standard software tools today on libraries of this size.

In Silico PCR Tools for a Fast Primer, Probe, and Advanced Searching.

PubMed

Kalendar, Ruslan; Muterko, Alexandr; Shamekova, Malika; Zhambakin, Kabyl

2017-01-01

The polymerase chain reaction (PCR) is fundamental to molecular biology and is the most important practical molecular technique for the research laboratory. The principle of this technique has been further used and applied in plenty of other simple or complex nucleic acid amplification technologies (NAAT). In parallel to laboratory "wet bench" experiments for nucleic acid amplification technologies, in silico or virtual (bioinformatics) approaches have been developed, among which in silico PCR analysis. In silico NAAT analysis is a useful and efficient complementary method to ensure the specificity of primers or probes for an extensive range of PCR applications from homology gene discovery, molecular diagnosis, DNA fingerprinting, and repeat searching. Predicting sensitivity and specificity of primers and probes requires a search to determine whether they match a database with an optimal number of mismatches, similarity, and stability. In the development of in silico bioinformatics tools for nucleic acid amplification technologies, the prospects for the development of new NAAT or similar approaches should be taken into account, including forward-looking and comprehensive analysis that is not limited to only one PCR technique variant. The software FastPCR and the online Java web tool are integrated tools for in silico PCR of linear and circular DNA, multiple primer or probe searches in large or small databases and for advanced search. These tools are suitable for processing of batch files that are essential for automation when working with large amounts of data. The FastPCR software is available for download at http://primerdigital.com/fastpcr.html and the online Java version at http://primerdigital.com/tools/pcr.html .

In silico discovery and in vitro activity of inhibitors against Mycobacterium tuberculosis 7,8-diaminopelargonic acid synthase (Mtb BioA).

PubMed

Billones, Junie B; Carrillo, Maria Constancia O; Organo, Voltaire G; Sy, Jamie Bernadette A; Clavio, Nina Abigail B; Macalino, Stephani Joy Y; Emnacen, Inno A; Lee, Alexandra P; Ko, Paul Kenny L; Concepcion, Gisela P

2017-01-01

Computer-aided drug discovery and development approaches such as virtual screening, molecular docking, and in silico drug property calculations have been utilized in this effort to discover new lead compounds against tuberculosis. The enzyme 7,8-diaminopelargonic acid aminotransferase (BioA) in Mycobacterium tuberculosis ( Mtb ), primarily involved in the lipid biosynthesis pathway, was chosen as the drug target due to the fact that humans are not capable of synthesizing biotin endogenously. The computational screening of 4.5 million compounds from the Enamine REAL database has ultimately yielded 45 high-scoring, high-affinity compounds with desirable in silico absorption, distribution, metabolism, excretion, and toxicity properties. Seventeen of the 45 compounds were subjected to bioactivity validation using the resazurin microtiter assay. Among the 4 actives, compound 7 (( Z )- N -(2-isopropoxyphenyl)-2-oxo-2-((3-(trifluoromethyl)cyclohexyl)amino)acetimidic acid) displayed inhibitory activity up to 83% at 10 μg/mL concentration against the growth of the Mtb H37Ra strain.

In silico discovery and in vitro activity of inhibitors against Mycobacterium tuberculosis 7,8-diaminopelargonic acid synthase (Mtb BioA)

PubMed Central

Billones, Junie B; Carrillo, Maria Constancia O; Organo, Voltaire G; Sy, Jamie Bernadette A; Clavio, Nina Abigail B; Macalino, Stephani Joy Y; Emnacen, Inno A; Lee, Alexandra P; Ko, Paul Kenny L; Concepcion, Gisela P

2017-01-01

Computer-aided drug discovery and development approaches such as virtual screening, molecular docking, and in silico drug property calculations have been utilized in this effort to discover new lead compounds against tuberculosis. The enzyme 7,8-diaminopelargonic acid aminotransferase (BioA) in Mycobacterium tuberculosis (Mtb), primarily involved in the lipid biosynthesis pathway, was chosen as the drug target due to the fact that humans are not capable of synthesizing biotin endogenously. The computational screening of 4.5 million compounds from the Enamine REAL database has ultimately yielded 45 high-scoring, high-affinity compounds with desirable in silico absorption, distribution, metabolism, excretion, and toxicity properties. Seventeen of the 45 compounds were subjected to bioactivity validation using the resazurin microtiter assay. Among the 4 actives, compound 7 ((Z)-N-(2-isopropoxyphenyl)-2-oxo-2-((3-(trifluoromethyl)cyclohexyl)amino)acetimidic acid) displayed inhibitory activity up to 83% at 10 μg/mL concentration against the growth of the Mtb H37Ra strain. PMID:28280303

Model Predictive Control of Type 1 Diabetes: An in Silico Trial

PubMed Central

Magni, Lalo; Raimondo, Davide M.; Bossi, Luca; Man, Chiara Dalla; De Nicolao, Giuseppe; Kovatchev, Boris; Cobelli, Claudio

2007-01-01

Background The development of artificial pancreas has received a new impulse from recent technological advancements in subcutaneous continuous glucose monitoring and subcutaneous insulin pump delivery systems. However, the availability of innovative sensors and actuators, although essential, does not guarantee optimal glycemic regulation. Closed-loop control of blood glucose levels still poses technological challenges to the automatic control expert, most notable of which are the inevitable time delays between glucose sensing and insulin actuation. Methods A new in silico model is exploited for both design and validation of a linear model predictive control (MPC) glucose control system. The starting point is a recently developed meal glucose–insulin model in health, which is modified to describe the metabolic dynamics of a person with type 1 diabetes mellitus. The population distribution of the model parameters originally obtained in healthy 204 patients is modified to describe diabetic patients. Individual models of virtual patients are extracted from this distribution. A discrete-time MPC is designed for all the virtual patients from a unique input–output-linearized approximation of the full model based on the average population values of the parameters. The in silico trial simulates 4 consecutive days, during which the patient receives breakfast, lunch, and dinner each day. Results Provided that the regulator undergoes some individual tuning, satisfactory results are obtained even if the control design relies solely on the average patient model. Only the weight on the glucose concentration error needs to be tuned in a quite straightforward and intuitive way. The ability of the MPC to take advantage of meal announcement information is demonstrated. Imperfect knowledge of the amount of ingested glucose causes only marginal deterioration of performance. In general, MPC results in better regulation than proportional integral derivative, limiting significantly the oscillation of glucose levels. Conclusions The proposed in silico trial shows the potential of MPC for artificial pancreas design. The main features are a capability to consider meal announcement information, delay compensation, and simplicity of tuning and implementation. PMID:19885152

Effectiveness of atrial fibrillation rotor ablation is dependent on conduction velocity: An in-silico 3-dimensional modeling study

PubMed Central

Lim, Byounghyun; Hwang, Minki; Song, Jun-Seop; Ryu, Ah-Jin; Joung, Boyoung; Shim, Eun Bo; Ryu, Hyungon

2017-01-01

Background We previously reported that stable rotors are observed in in-silico human atrial fibrillation (AF) models, and are well represented by a dominant frequency (DF). In the current study, we hypothesized that the outcome of DF ablation is affected by conduction velocity (CV) conditions and examined this hypothesis using in-silico 3D-AF modeling. Methods We integrated 3D CT images of left atrium obtained from 10 patients with persistent AF (80% male, 61.8±13.5 years old) into in-silico AF model. We compared AF maintenance durations (max 300s), spatiotemporal stabilities of DF, phase singularity (PS) number, life-span of PS, and AF termination or defragmentation rates after virtual DF ablation with 5 different CV conditions (0.2, 0.3, 0.4, 0.5, and 0.6m/s). Results 1. AF maintenance duration (p<0.001), spatiotemporal mean variance of DF (p<0.001), and the number of PS (p = 0.023) showed CV dependent bimodal patterns (highest at CV0.4m/s and lowest at CV0.6m/s) consistently. 2. After 10% highest DF ablation, AF defragmentation rates were the lowest at CV0.4m/s (37.8%), but highest at CV0.5 and 0.6m/s (all 100%, p<0.001). 3. In the episodes with AF termination or defragmentation followed by 10% highest DF ablation, baseline AF maintenance duration was shorter (p<0.001), spatiotemporal mean variance of DF was lower (p = 0.014), and the number of PS was lower (p = 0.004) than those with failed AF defragmentation after DF ablation. Conclusion Virtual ablation of DF, which may indicate AF driver, was more likely to terminate or defragment AF with spatiotemporally stable DF, but not likely to do so in long-lasting and sustained AF conditions, depending on CV. PMID:29287119

Principles of Systems Biology, No. 29.

PubMed

2018-05-23

This month: in silico labeling of microscopy images (Christiansen/Finkbeiner), single-cell lineage trees and data integration (Rajewsky, Satija), gene expression (Weinberger/Simpson, Tavazoie, Ameres/Zuber), and signalling networks (Mercer/Wollscheid, Fussenegger). Copyright © 2018. Published by Elsevier Inc.

Virtual Interactomics of Proteins from Biochemical Standpoint

PubMed Central

Kubrycht, Jaroslav; Sigler, Karel; Souček, Pavel

2012-01-01

Virtual interactomics represents a rapidly developing scientific area on the boundary line of bioinformatics and interactomics. Protein-related virtual interactomics then comprises instrumental tools for prediction, simulation, and networking of the majority of interactions important for structural and individual reproduction, differentiation, recognition, signaling, regulation, and metabolic pathways of cells and organisms. Here, we describe the main areas of virtual protein interactomics, that is, structurally based comparative analysis and prediction of functionally important interacting sites, mimotope-assisted and combined epitope prediction, molecular (protein) docking studies, and investigation of protein interaction networks. Detailed information about some interesting methodological approaches and online accessible programs or databases is displayed in our tables. Considerable part of the text deals with the searches for common conserved or functionally convergent protein regions and subgraphs of conserved interaction networks, new outstanding trends and clinically interesting results. In agreement with the presented data and relationships, virtual interactomic tools improve our scientific knowledge, help us to formulate working hypotheses, and they frequently also mediate variously important in silico simulations. PMID:22928109

Performance evaluation of structure based and ligand based virtual screening methods on ten selected anti-cancer targets.

PubMed

Ramasamy, Thilagavathi; Selvam, Chelliah

2015-10-15

Virtual screening has become an important tool in drug discovery process. Structure based and ligand based approaches are generally used in virtual screening process. To date, several benchmark sets for evaluating the performance of the virtual screening tool are available. In this study, our aim is to compare the performance of both structure based and ligand based virtual screening methods. Ten anti-cancer targets and their corresponding benchmark sets from 'Demanding Evaluation Kits for Objective In silico Screening' (DEKOIS) library were selected. X-ray crystal structures of protein-ligand complexes were selected based on their resolution. Openeye tools such as FRED, vROCS were used and the results were carefully analyzed. At EF1%, vROCS produced better results but at EF5% and EF10%, both FRED and ROCS produced almost similar results. It was noticed that the enrichment factor values were decreased while going from EF1% to EF5% and EF10% in many cases. Published by Elsevier Ltd.

WEbcoli: an interactive and asynchronous web application for in silico design and analysis of genome-scale E.coli model.

PubMed

Jung, Tae-Sung; Yeo, Hock Chuan; Reddy, Satty G; Cho, Wan-Sup; Lee, Dong-Yup

2009-11-01

WEbcoli is a WEb application for in silico designing, analyzing and engineering Escherichia coli metabolism. It is devised and implemented using advanced web technologies, thereby leading to enhanced usability and dynamic web accessibility. As a main feature, the WEbcoli system provides a user-friendly rich web interface, allowing users to virtually design and synthesize mutant strains derived from the genome-scale wild-type E.coli model and to customize pathways of interest through a graph editor. In addition, constraints-based flux analysis can be conducted for quantifying metabolic fluxes and charactering the physiological and metabolic states under various genetic and/or environmental conditions. WEbcoli is freely accessible at http://webcoli.org. cheld@nus.edu.sg.

Implementing virtual microscopy improves outcomes in a hematology morphology course.

PubMed

Brueggeman, Mauri S; Swinehart, Cheryl; Yue, Mary Jane; Conway-Klaassen, Janice M; Wiesner, Stephen M

2012-01-01

In this study, we evaluated the efficacy of virtual microscopy as the primary mode of laboratory instruction in undergraduate level clinical hematology teaching. Distance education (DE) has become a popular option for expanding education and optimizing expenses but continues to be controversial. The challenge of delivering an equitable curriculum to distant locations along with the need to preserve our slide collection directed our effort to digitize the slide sets used in our teaching laboratories. Students enrolled at two performance sites were randomly assigned to either traditional microscopy (TM) or virtual microscopy (VM) instruction. The VM group performed significantly better than the TM group. We anticipate that this approach will play a central role in the distributed delivery of hematology through distance education as new programs are initiated to address workforce shortage needs.

The Virtual Mouse Brain: A Computational Neuroinformatics Platform to Study Whole Mouse Brain Dynamics.

PubMed

Melozzi, Francesca; Woodman, Marmaduke M; Jirsa, Viktor K; Bernard, Christophe

2017-01-01

Connectome-based modeling of large-scale brain network dynamics enables causal in silico interrogation of the brain's structure-function relationship, necessitating the close integration of diverse neuroinformatics fields. Here we extend the open-source simulation software The Virtual Brain (TVB) to whole mouse brain network modeling based on individual diffusion magnetic resonance imaging (dMRI)-based or tracer-based detailed mouse connectomes. We provide practical examples on how to use The Virtual Mouse Brain (TVMB) to simulate brain activity, such as seizure propagation and the switching behavior of the resting state dynamics in health and disease. TVMB enables theoretically driven experimental planning and ways to test predictions in the numerous strains of mice available to study brain function in normal and pathological conditions.

Cancer Genome Anatomy Project (CGAP) | Office of Cancer Genomics

Cancer.gov

CGAP generated a wide range of genomics data on cancerous cells that are accessible through easy-to-use online tools. Researchers, educators, and students can find "in silico" answers to biological questions through the CGAP website. Request a free copy of the CGAP Website Virtual Tour CD from ocg@mail.nih.gov to learn how to navigate the website.

in silico Whole Genome Sequencer & Analyzer (iWGS): a computational pipeline to guide the design and analysis of de novo genome sequencing studies

USDA-ARS?s Scientific Manuscript database

The availability of genomes across the tree of life is highly biased toward vertebrates, pathogens, human disease models, and organisms with relatively small and simple genomes. Recent progress in genomics has enabled the de novo decoding of the genome of virtually any organism, greatly expanding it...

In silico strategies for the selection of chelating compounds with potential application in metal-promoted neurodegenerative diseases

NASA Astrophysics Data System (ADS)

Rodríguez-Rodríguez, Cristina; Rimola, Albert; Alí-Torres, Jorge; Sodupe, Mariona; González-Duarte, Pilar

2011-01-01

The development of new strategies to find commercial molecules with promising biochemical features is a main target in the field of biomedicine chemistry. In this work we present an in silico-based protocol that allows identifying commercial compounds with suitable metal coordinating and pharmacokinetic properties to act as metal-ion chelators in metal-promoted neurodegenerative diseases (MpND). Selection of the chelating ligands is done by combining quantum chemical calculations with the search of commercial compounds on different databases via virtual screening. Starting from different designed molecular frameworks, which mainly constitute the binding site, the virtual screening on databases facilitates the identification of different commercial molecules that enclose such scaffolds and, by imposing a set of chemical and pharmacokinetic filters, obey some drug-like requirements mandatory to deal with MpND. The quantum mechanical calculations are useful to gauge the chelating properties of the selected candidate molecules by determining the structure of metal complexes and evaluating their stability constants. With the proposed strategy, commercial compounds containing N and S donor atoms in the binding sites and capable to cross the BBB have been identified and their chelating properties analyzed.

Pharmacophore Identification, Molecular Docking, Virtual Screening, and In Silico ADME Studies of Non-Nucleoside Reverse Transcriptase Inhibitors.

PubMed

Pirhadi, Somayeh; Ghasemi, Jahan B

2012-12-01

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) have gained a definitive place due to their unique antiviral potency, high specificity and low toxicity in antiretroviral combination therapies used to treat HIV. In this study, chemical feature based pharmacophore models of different classes of NNRT inhibitors of HIV-1 have been developed. The best HypoRefine pharmacophore model, Hypo 1, which has the best correlation coefficient (0.95) and the lowest RMS (0.97), contains two hydrogen bond acceptors, one hydrophobic and one ring aromatic feature, as well as four excluded volumes. Hypo 1 was further validated by test set and Fischer validation method. The best pharmacophore model was then utilized as a 3D search query to perform a virtual screening to retrieve potential inhibitors. The hit compounds were subsequently subjected to filtering by Lipinski's rule of five and docking studies by Libdock and Gold methods to refine the retrieved hits. Finally, 7 top ranked compounds based on Gold score fitness function were subjected to in silico ADME studies to investigate for compliance with the standard ranges. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Meal Disturbance Effect on Control of Blood Glucose Level for Critically-ill Patients using In-silico Works

NASA Astrophysics Data System (ADS)

Yusof, N. F. M.; Som, A. M.; Ali, S. A.; Azman, N. H.

2018-05-01

This study was conducted to determine the effect of meal disturbance on blood glucose level of the critically ill patients and to simulate the control algorithm previously developed using in-silico works. The study is significant so as to reduce the mortality rate of critically ill patients who usually encounter hyperglycaemia or/and hypoglycaemia while in treatment. The meal intake is believed to affect the blood glucose regulation and causes the hyperglycaemia to occur. Critically ill patients receive their meal through parenteral and enteral nutrition. Furthermore, by using in-silico works, time consumed and resources needed for clinical evaluation of the patients can be reduced. Hovorka model was employed in which the simulation study was carried out using MATLAB on the virtual patient and it was being compared with actual patient in which the data were provided by Institut Jantung Negara (IJN). Based on the simulation, the disturbance on enteral glucose supplied had affected the blood glucose level of the patient; however, it remained unchanged for the parental glucose. To reduce the occurrence of hypoglycaemia and hyperglycaemia, the patient was injected with 30 g/hr and 10 g/hr of enteral glucose, respectively. In conclusion, the disturbance of meal received can be controlled through in-silico works.

OpenVirtualToxLab--a platform for generating and exchanging in silico toxicity data.

PubMed

Vedani, Angelo; Dobler, Max; Hu, Zhenquan; Smieško, Martin

2015-01-22

The VirtualToxLab is an in silico technology for estimating the toxic potential--endocrine and metabolic disruption, some aspects of carcinogenicity and cardiotoxicity--of drugs, chemicals and natural products. The technology is based on an automated protocol that simulates and quantifies the binding of small molecules towards a series of currently 16 proteins, known or suspected to trigger adverse effects: 10 nuclear receptors (androgen, estrogen α, estrogen β, glucocorticoid, liver X, mineralocorticoid, peroxisome proliferator-activated receptor γ, progesterone, thyroid α, thyroid β), four members of the cytochrome P450 enzyme family (1A2, 2C9, 2D6, 3A4), a cytosolic transcription factor (aryl hydrocarbon receptor) and a potassium ion channel (hERG). The toxic potential of a compound--its ability to trigger adverse effects--is derived from its computed binding affinities toward these very proteins: the computationally demanding simulations are executed in client-server model on a Linux cluster of the University of Basel. The graphical-user interface supports all computer platforms, allows building and uploading molecular structures, inspecting and downloading the results and, most important, rationalizing any prediction at the atomic level by interactively analyzing the binding mode of a compound with its target protein(s) in real-time 3D. Access to the VirtualToxLab is available free of charge for universities, governmental agencies, regulatory bodies and non-profit organizations. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

THE INTEGRATED USE OF COMPUTATIONAL CHEMISTRY, SCANNING PROBE MICROSCOPY, AND VIRTUAL REALITY TO PREDICT THE CHEMICAL REACTIVITY OF ENVIRONMENTAL SURFACES

EPA Science Inventory

In the last decade three new techniques scanning probe microscopy (SPM), virtual reality (YR) and computational chemistry ave emerged with the combined capability of a priori predicting the chemically reactivity of environmental surfaces. Computational chemistry provides the cap...

PREDICTING CHEMICAL REACTIVITY OF HUMIC SUBSTANCES FOR MINERALS AND XENOBIOTICS: USE OF COMPUTATIONAL CHEMISTRY, SCANNING PROBE MICROSCOPY AND VIRTUAL REALITY

EPA Science Inventory

In this chapter we review the literature on scanning probe microscopy (SPM), virtual reality (VR), and computational chemistry and our earlier work dealing with modeling lignin, lignin-carbohydrate complexes (LCC), humic substances (HSs) and non-bonded organo-mineral interactions...

In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images.

PubMed

Christiansen, Eric M; Yang, Samuel J; Ando, D Michael; Javaherian, Ashkan; Skibinski, Gaia; Lipnick, Scott; Mount, Elliot; O'Neil, Alison; Shah, Kevan; Lee, Alicia K; Goyal, Piyush; Fedus, William; Poplin, Ryan; Esteva, Andre; Berndl, Marc; Rubin, Lee L; Nelson, Philip; Finkbeiner, Steven

2018-04-19

Microscopy is a central method in life sciences. Many popular methods, such as antibody labeling, are used to add physical fluorescent labels to specific cellular constituents. However, these approaches have significant drawbacks, including inconsistency; limitations in the number of simultaneous labels because of spectral overlap; and necessary perturbations of the experiment, such as fixing the cells, to generate the measurement. Here, we show that a computational machine-learning approach, which we call "in silico labeling" (ISL), reliably predicts some fluorescent labels from transmitted-light images of unlabeled fixed or live biological samples. ISL predicts a range of labels, such as those for nuclei, cell type (e.g., neural), and cell state (e.g., cell death). Because prediction happens in silico, the method is consistent, is not limited by spectral overlap, and does not disturb the experiment. ISL generates biological measurements that would otherwise be problematic or impossible to acquire. Copyright © 2018 Elsevier Inc. All rights reserved.

Optimized graph-based mosaicking for virtual microscopy

NASA Astrophysics Data System (ADS)

Steckhan, Dirk G.; Wittenberg, Thomas

2009-02-01

Virtual microscopy has the potential to partially replace traditional microscopy. For virtualization, the slide is scanned once by a fully automatized robotic microscope and saved digitally. Typically, such a scan results in several hundreds to thousands of fields of view. Since robotic stages have positioning errors, these fields of view have to be registered locally and globally in an additional step. In this work we propose a new global mosaicking method for the creation of virtual slides based on sub-pixel exact phase correlation for local alignment in combination with Prim's minimum spanning tree algorithm for global alignment. Our algorithm allows for a robust reproduction of the original slide even in the presence of views with little to no information content. This makes it especially suitable for the mosaicking of cervical smears. These smears often exhibit large empty areas, which do not contain enough information for common stitching approaches.

Mathematical and computational approaches can complement experimental studies of host-pathogen interactions.

PubMed

Kirschner, Denise E; Linderman, Jennifer J

2009-04-01

In addition to traditional and novel experimental approaches to study host-pathogen interactions, mathematical and computer modelling have recently been applied to address open questions in this area. These modelling tools not only offer an additional avenue for exploring disease dynamics at multiple biological scales, but also complement and extend knowledge gained via experimental tools. In this review, we outline four examples where modelling has complemented current experimental techniques in a way that can or has already pushed our knowledge of host-pathogen dynamics forward. Two of the modelling approaches presented go hand in hand with articles in this issue exploring fluorescence resonance energy transfer and two-photon intravital microscopy. Two others explore virtual or 'in silico' deletion and depletion as well as a new method to understand and guide studies in genetic epidemiology. In each of these examples, the complementary nature of modelling and experiment is discussed. We further note that multi-scale modelling may allow us to integrate information across length (molecular, cellular, tissue, organism, population) and time (e.g. seconds to lifetimes). In sum, when combined, these compatible approaches offer new opportunities for understanding host-pathogen interactions.

Dealing with Diversity in Computational Cancer Modeling

PubMed Central

Johnson, David; McKeever, Steve; Stamatakos, Georgios; Dionysiou, Dimitra; Graf, Norbert; Sakkalis, Vangelis; Marias, Konstantinos; Wang, Zhihui; Deisboeck, Thomas S.

2013-01-01

This paper discusses the need for interconnecting computational cancer models from different sources and scales within clinically relevant scenarios to increase the accuracy of the models and speed up their clinical adaptation, validation, and eventual translation. We briefly review current interoperability efforts drawing upon our experiences with the development of in silico models for predictive oncology within a number of European Commission Virtual Physiological Human initiative projects on cancer. A clinically relevant scenario, addressing brain tumor modeling that illustrates the need for coupling models from different sources and levels of complexity, is described. General approaches to enabling interoperability using XML-based markup languages for biological modeling are reviewed, concluding with a discussion on efforts towards developing cancer-specific XML markup to couple multiple component models for predictive in silico oncology. PMID:23700360

Teaching the Fluctuation Test "In Silico" by Using Mutate: A Program to Distinguish between the Adaptive and Spontaneous Mutation Hypotheses

ERIC Educational Resources Information Center

Carvajal-Rodriguez, Antonio

2012-01-01

Mutate is a program developed for teaching purposes to impart a virtual laboratory class for undergraduate students of Genetics in Biology. The program emulates the so-called fluctuation test whose aim is to distinguish between spontaneous and adaptive mutation hypotheses in bacteria. The plan is to train students in certain key multidisciplinary…

Optical versus virtual: teaching assistant perceptions of the use of virtual microscopy in an undergraduate human anatomy course.

PubMed

Collier, Larissa; Dunham, Stacey; Braun, Mark W; O'Loughlin, Valerie Dean

2012-01-01

Many studies that evaluate the introduction of technology in the classroom focus on student performance and student evaluations. This study focuses on instructor evaluation of the introduction of virtual microscopy into an undergraduate anatomy class. Semi-structured interviews were conducted with graduate teaching assistants (TA) and analyzed through qualitative methods. This analysis showed that the teaching assistants found the virtual microscope to be an advantageous change in the classroom. They cite the ease of use of the virtual microscope, access to histology outside of designated laboratory time, and increasing student collaboration in class as the primary advantages. The teaching assistants also discuss principal areas where the use of the virtual microscope can be improved from a pedagogical standpoint, including requiring students to spend more time working on histology in class. Copyright © 2011 American Association of Anatomists.

Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them.

PubMed

Chase, J Geoffrey; Preiser, Jean-Charles; Dickson, Jennifer L; Pironet, Antoine; Chiew, Yeong Shiong; Pretty, Christopher G; Shaw, Geoffrey M; Benyo, Balazs; Moeller, Knut; Safaei, Soroush; Tawhai, Merryn; Hunter, Peter; Desaive, Thomas

2018-02-20

Critical care, like many healthcare areas, is under a dual assault from significantly increasing demographic and economic pressures. Intensive care unit (ICU) patients are highly variable in response to treatment, and increasingly aging populations mean ICUs are under increasing demand and their cohorts are increasingly ill. Equally, patient expectations are growing, while the economic ability to deliver care to all is declining. Better, more productive care is thus the big challenge. One means to that end is personalised care designed to manage the significant inter- and intra-patient variability that makes the ICU patient difficult. Thus, moving from current "one size fits all" protocolised care to adaptive, model-based "one method fits all" personalised care could deliver the required step change in the quality, and simultaneously the productivity and cost, of care. Computer models of human physiology are a unique tool to personalise care, as they can couple clinical data with mathematical methods to create subject-specific models and virtual patients to design new, personalised and more optimal protocols, as well as to guide care in real-time. They rely on identifying time varying patient-specific parameters in the model that capture inter- and intra-patient variability, the difference between patients and the evolution of patient condition. Properly validated, virtual patients represent the real patients, and can be used in silico to test different protocols or interventions, or in real-time to guide care. Hence, the underlying models and methods create the foundation for next generation care, as well as a tool for safely and rapidly developing personalised treatment protocols over large virtual cohorts using virtual trials. This review examines the models and methods used to create virtual patients. Specifically, it presents the models types and structures used and the data required. It then covers how to validate the resulting virtual patients and trials, and how these virtual trials can help design and optimise clinical trial. Links between these models and higher order, more complex physiome models are also discussed. In each section, it explores the progress reported up to date, especially on core ICU therapies in glycemic, circulatory and mechanical ventilation management, where high cost and frequency of occurrence provide a significant opportunity for model-based methods to have measurable clinical and economic impact. The outcomes are readily generalised to other areas of medical care.

Improved Learning Efficiency and Increased Student Collaboration through Use of Virtual Microscopy in the Teaching of Human Pathology

ERIC Educational Resources Information Center

Braun, Mark W.; Kearns, Katherine D.

2008-01-01

The implementation of virtual microscopy in the teaching of pathology at the Bloomington, Indiana extension of the Indiana University School of Medicine permitted the assessment of student attitudes, use and academic performance with respect to this new technology. A gradual and integrated approach allowed the parallel assessment with respect to…

Quantitative and Qualitative Changes in Teaching Histology by Means of Virtual Microscopy in an Introductory Course in Human Anatomy

ERIC Educational Resources Information Center

Husmann, Polly R.; O'Loughlin, Valerie Dean; Braun, Mark W.

2009-01-01

This study compares overall laboratory averages and individual test scores along with a student survey to determine the effects of using virtual microscopy in place of optical microscopes in a large undergraduate human anatomy course. T-tests revealed that the first two laboratory examinations (of four) and the overall laboratory averages were…

Engaging Students by Emphasising Botanical Concepts over Techniques: Innovative Practical Exercises Using Virtual Microscopy

ERIC Educational Resources Information Center

Bonser, Stephen P.; de Permentier, Patrick; Green, Jacinta; Velan, Gary M.; Adam, Paul; Kumar, Rakesh K.

2013-01-01

Student interest in botany and enrolment in plant sciences courses tends to be low compared to that in other biological disciplines. One potential way of increasing student interest in botany is to focus on course material designed to raise student enthusiasm and satisfaction. Here, we introduce and evaluate virtual microscopy in botany teaching.…

More Technology, Better Learning Resources, Better Learning? Lessons from Adopting Virtual Microscopy in Undergraduate Medical Education

ERIC Educational Resources Information Center

Helle, Laura; Nivala, Markus; Kronqvist, Pauliina

2013-01-01

The adoption of virtual microscopy at the University of Turku, Finland, created a unique real-world laboratory for exploring ways of reforming the learning environment. The purpose of this study was to evaluate the students' reactions and the impact of a set of measures designed to boost an experimental group's understanding of abnormal histology…

Virtual Microscopy: A Useful Tool for Meeting Evolving Challenges in the Veterinary Medical Curriculum

NASA Astrophysics Data System (ADS)

Kogan, Lori R.; Dowers, Kristy L.; Cerda, Jacey R.; Schoenfeld-Tacher, Regina M.; Stewart, Sherry M.

2014-12-01

Veterinary schools, similar to many professional health programs, face a myriad of evolving challenges in delivering their professional curricula including expansion of class size, costs to maintain expensive laboratories, and increased demands on veterinary educators to use curricular time efficiently and creatively. Additionally, exponential expansion of the knowledge base through ongoing biomedical research, educational goals to increase student engagement and clinical reasoning earlier in the curriculum, and students' desire to access course materials and enhance their educational experience through the use of technology all support the need to reassess traditional microscope laboratories within Professional Veterinary Medical (PVM) educational programs. While there is clear justification for teaching veterinary students how to use a microscope for clinical evaluation of cytological preparations (i.e., complete blood count, urinalysis, fecal analysis, fine needle aspirates, etc.), virtual microscopy may be a viable alternative to using light microscopy for teaching and learning fundamental histological concepts. This article discusses results of a survey given to assess Professional Veterinary Medical students' perceptions of using virtual microscope for learning basic histology/microscopic anatomy and implications of these results for using virtual microscopy as a pedagogical tool in teaching first-year Professional Veterinary Medical students' basic histology.

A case study on the in silico absorption simulations of levothyroxine sodium immediate-release tablets.

PubMed

Kocic, Ivana; Homsek, Irena; Dacevic, Mirjana; Grbic, Sandra; Parojcic, Jelena; Vucicevic, Katarina; Prostran, Milica; Miljkovic, Branislava

2012-04-01

The aim of this case study was to develop a drug-specific absorption model for levothyroxine (LT4) using mechanistic gastrointestinal simulation technology (GIST) implemented in the GastroPlus™ software package. The required input parameters were determined experimentally, in silico predicted and/or taken from the literature. The simulated plasma profile was similar and in a good agreement with the data observed in the in vivo bioequivalence study, indicating that the GIST model gave an accurate prediction of LT4 oral absorption. Additionally, plasma concentration-time profiles were simulated based on a set of experimental and virtual in vitro dissolution data in order to estimate the influence of different in vitro drug dissolution kinetics on the simulated plasma profiles and to identify biorelevant dissolution specification for LT4 immediate-release (IR) tablets. A set of experimental and virtual in vitro data was also used for correlation purposes. In vitro-in vivo correlation model based on the convolution approach was applied in order to assess the relationship between the in vitro and in vivo data. The obtained results suggest that dissolution specification of more than 85% LT4 dissolved in 60 min might be considered as biorelevant dissolution specification criteria for LT4 IR tablets. Copyright © 2012 John Wiley & Sons, Ltd.

Media Matter: The Effect of Medium of Presentation on Student's Recognition of Histopathology.

PubMed

Telang, Ajay; Jong, Nynke De; Dalen, Jan Van

2016-12-01

Pathology teaching has undergone transformation with the introduction of virtual microscopy as a teaching and learning tool. To assess if dental students can identify histopathology irrespective of the media of presentation and if the media affect student's oral pathology case based learning scores. The perception of students towards "hybrid" approach in teaching and learning histopathology in oral pathology was also assessed. A controlled experiment was conduc-ted on year 4 and year 5 dental student groups using a perfor-mance test and a questionnaire survey. A response rate of 81% was noted for the performance test as well as the questionnaire survey. Results show a significant effect of media on performance of students with virtual microscopy bringing out the best performance across all student groups in case based learning scenarios. The order of preference for media was found to be virtual microscopy followed by photomicrographs and light microscopy. However, 94% of students still prefer the present hybrid system for teaching and learning of oral pathology. The study shows that identification of histo-pathology by students is dependent on media and the type of media has a significant effect on the performance. Virtual microscopy is strongly perceived as a useful tool for learning which thus brings out the best performance, however; the hybrid approach still remains the most preferred approach for histopathology learning.

BioVeL: a virtual laboratory for data analysis and modelling in biodiversity science and ecology.

PubMed

Hardisty, Alex R; Bacall, Finn; Beard, Niall; Balcázar-Vargas, Maria-Paula; Balech, Bachir; Barcza, Zoltán; Bourlat, Sarah J; De Giovanni, Renato; de Jong, Yde; De Leo, Francesca; Dobor, Laura; Donvito, Giacinto; Fellows, Donal; Guerra, Antonio Fernandez; Ferreira, Nuno; Fetyukova, Yuliya; Fosso, Bruno; Giddy, Jonathan; Goble, Carole; Güntsch, Anton; Haines, Robert; Ernst, Vera Hernández; Hettling, Hannes; Hidy, Dóra; Horváth, Ferenc; Ittzés, Dóra; Ittzés, Péter; Jones, Andrew; Kottmann, Renzo; Kulawik, Robert; Leidenberger, Sonja; Lyytikäinen-Saarenmaa, Päivi; Mathew, Cherian; Morrison, Norman; Nenadic, Aleksandra; de la Hidalga, Abraham Nieva; Obst, Matthias; Oostermeijer, Gerard; Paymal, Elisabeth; Pesole, Graziano; Pinto, Salvatore; Poigné, Axel; Fernandez, Francisco Quevedo; Santamaria, Monica; Saarenmaa, Hannu; Sipos, Gergely; Sylla, Karl-Heinz; Tähtinen, Marko; Vicario, Saverio; Vos, Rutger Aldo; Williams, Alan R; Yilmaz, Pelin

2016-10-20

Making forecasts about biodiversity and giving support to policy relies increasingly on large collections of data held electronically, and on substantial computational capability and capacity to analyse, model, simulate and predict using such data. However, the physically distributed nature of data resources and of expertise in advanced analytical tools creates many challenges for the modern scientist. Across the wider biological sciences, presenting such capabilities on the Internet (as "Web services") and using scientific workflow systems to compose them for particular tasks is a practical way to carry out robust "in silico" science. However, use of this approach in biodiversity science and ecology has thus far been quite limited. BioVeL is a virtual laboratory for data analysis and modelling in biodiversity science and ecology, freely accessible via the Internet. BioVeL includes functions for accessing and analysing data through curated Web services; for performing complex in silico analysis through exposure of R programs, workflows, and batch processing functions; for on-line collaboration through sharing of workflows and workflow runs; for experiment documentation through reproducibility and repeatability; and for computational support via seamless connections to supporting computing infrastructures. We developed and improved more than 60 Web services with significant potential in many different kinds of data analysis and modelling tasks. We composed reusable workflows using these Web services, also incorporating R programs. Deploying these tools into an easy-to-use and accessible 'virtual laboratory', free via the Internet, we applied the workflows in several diverse case studies. We opened the virtual laboratory for public use and through a programme of external engagement we actively encouraged scientists and third party application and tool developers to try out the services and contribute to the activity. Our work shows we can deliver an operational, scalable and flexible Internet-based virtual laboratory to meet new demands for data processing and analysis in biodiversity science and ecology. In particular, we have successfully integrated existing and popular tools and practices from different scientific disciplines to be used in biodiversity and ecological research.

VirtualToxLab — A platform for estimating the toxic potential of drugs, chemicals and natural products

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vedani, Angelo, E-mail: angelo.vedani@unibas.ch; Department of Pharmaceutical Sciences, University of Basel, Klingelbergstrasse 50, 4056 Basel; Dobler, Max

The VirtualToxLab is an in silico technology for estimating the toxic potential (endocrine and metabolic disruption, some aspects of carcinogenicity and cardiotoxicity) of drugs, chemicals and natural products. The technology is based on an automated protocol that simulates and quantifies the binding of small molecules towards a series of proteins, known or suspected to trigger adverse effects. The toxic potential, a non-linear function ranging from 0.0 (none) to 1.0 (extreme), is derived from the individual binding affinities of a compound towards currently 16 target proteins: 10 nuclear receptors (androgen, estrogen α, estrogen β, glucocorticoid, liver X, mineralocorticoid, peroxisome proliferator-activated receptormore » γ, progesterone, thyroid α, and thyroid β), four members of the cytochrome P450 enzyme family (1A2, 2C9, 2D6, and 3A4), a cytosolic transcription factor (aryl hydrocarbon receptor) and a potassium ion channel (hERG). The interface to the technology allows building and uploading molecular structures, viewing and downloading results and, most importantly, rationalizing any prediction at the atomic level by interactively analyzing the binding mode of a compound with its target protein(s) in real-time 3D. The VirtualToxLab has been used to predict the toxic potential for over 2500 compounds: the results are posted on (http://www.virtualtoxlab.org). The free platform — the OpenVirtualToxLab — is accessible (in client–server mode) over the Internet. It is free of charge for universities, governmental agencies, regulatory bodies and non-profit organizations. -- Highlights: ► In silico technology for estimating the toxic potential of drugs and chemicals. ► Simulation of binding towards 16 proteins suspected to trigger adverse effects. ► Mechanistic interpretation and real-time 3D visualization. ► Accessible over the Internet. ► Free of charge for universities, governmental agencies, regulatory bodies and NPOs.« less

Quantitative and qualitative changes in teaching histology by means of virtual microscopy in an introductory course in human anatomy.

PubMed

Husmann, Polly R; O'Loughlin, Valerie Dean; Braun, Mark W

2009-10-01

This study compares overall laboratory averages and individual test scores along with a student survey to determine the effects of using virtual microscopy in place of optical microscopes in a large undergraduate human anatomy course. T-tests revealed that the first two laboratory examinations (of four) and the overall laboratory averages were significantly increased compared with the previous year. We hypothesize that this is due to students' ability to use and understand the technology quickly as opposed to learning how to maneuver an optical microscope. Students also responded positively in a survey about the virtual microscope, indicating that increased accessibility, ease of use, and the ability to understand the material were important components of the virtual microscope. In addition, an increase in student collaboration was noted because multiple students were able to view the image at a time. This level of acceptance of virtual microscopy has been reported in previous studies, though this level of increased examination scores is rare. We attribute this to differences between the medical students, with whom this technology has been researched in the past, and undergraduate introductory students.

Searching Fragment Spaces with feature trees.

PubMed

Lessel, Uta; Wellenzohn, Bernd; Lilienthal, Markus; Claussen, Holger

2009-02-01

Virtual combinatorial chemistry easily produces billions of compounds, for which conventional virtual screening cannot be performed even with the fastest methods available. An efficient solution for such a scenario is the generation of Fragment Spaces, which encode huge numbers of virtual compounds by their fragments/reagents and rules of how to combine them. Similarity-based searches can be performed in such spaces without ever fully enumerating all virtual products. Here we describe the generation of a huge Fragment Space encoding about 5 * 10(11) compounds based on established in-house synthesis protocols for combinatorial libraries, i.e., we encode practically evaluated combinatorial chemistry protocols in a machine readable form, rendering them accessible to in silico search methods. We show how such searches in this Fragment Space can be integrated as a first step in an overall workflow. It reduces the extremely huge number of virtual products by several orders of magnitude so that the resulting list of molecules becomes more manageable for further more elaborated and time-consuming analysis steps. Results of a case study are presented and discussed, which lead to some general conclusions for an efficient expansion of the chemical space to be screened in pharmaceutical companies.

Endothelialization of over- and undersized flow-diverter stents at covered vessel side branches: An in vivo and in silico study.

PubMed

Berg, Philipp; Iosif, Christina; Ponsonnard, Sebastien; Yardin, Catherine; Janiga, Gábor; Mounayer, Charbel

2016-01-04

Although flow-diverting devices are promising treatment options for intracranial aneurysms, jailed side branches might occlude leading to insufficient blood supply. Especially differences in the local stent strut compression may have a drastic influence on subsequent endothelialization. To investigate the outcome of different treatment scenarios, over- and undersized stent deployments were realized experimentally and computationally. Two Pipeline Embolization Devices were placed in the right common carotid artery of large white swine, crossing the right ascending pharyngeal artery. DSA and PC-MRI measurements were acquired pre- and post-stenting and after three months. To evaluate the stent strut endothelialization and the corresponding ostium patency, the swine were sacrificed and scanning electron microscopy measurements were carried out. A more detailed analysis of the near-stent hemodynamics was enabled by a realistic virtual stenting in combination with highly resolved Computational Fluid Dynamics simulations using case-specific boundary conditions. The oversizing resulted in an elongated stent deployment with more open stent pores, while for the undersized case a shorter deployment with more condensed pores was present. In consequence, the side branch of the first case remained patent after three months and the latter almost fully occluded. The virtual investigation confirmed the experimental findings by identifying differences between the individual velocities as well as stent shear stresses at the distal part of the ostia. The choice of flow-diverting device and the subsequent deployment strategy strongly influences the patency of jailed side branches. Therefore, careful treatment planning is required, to guarantee sufficient blood supply in the brain territories supplied those branches. Copyright © 2015 Elsevier Ltd. All rights reserved.

Factors to keep in mind when introducing virtual microscopy.

PubMed

Glatz-Krieger, Katharina; Spornitz, Udo; Spatz, Alain; Mihatsch, Michael J; Glatz, Dieter

2006-03-01

Digitization of glass slides and delivery of so-called virtual slides (VS) emulating a real microscope over the Internet have become reality due to recent improvements in technology. We have implemented a virtual microscope for instruction of medical students and for continuing medical education. Up to 30,000 images per slide are captured using a microscope with an automated stage. The images are post-processed and then served by a plain hypertext transfer protocol (http)-server. A virtual slide client (vMic) based on Macromedia's Flash MX, a highly accepted technology available on every modern Web browser, has been developed. All necessary virtual slide parameters are stored in an XML file together with the image. Evaluation of the courses by questionnaire indicated that most students and many but not all pathologists regard virtual slides as an adequate replacement for traditional slides. All our virtual slides are publicly accessible over the World Wide Web (WWW) at http://vmic.unibas.ch . Recently, several commercially available virtual slide acquisition systems (VSAS) have been developed that use various technologies to acquire and distribute virtual slides. These systems differ in speed, image quality, compatibility, viewer functionalities and price. This paper gives an overview of the factors to keep in mind when introducing virtual microscopy.

Identification of novel antitubulin agents by using a virtual screening approach based on a 7-point pharmacophore model of the tubulin colchi-site.

PubMed

Massarotti, Alberto; Theeramunkong, Sewan; Mesenzani, Ornella; Caldarelli, Antonio; Genazzani, Armando A; Tron, Gian Cesare

2011-12-01

Tubulin inhibition represents an established target in the field of anticancer research, and over the last 20 years, an intensive search for new antimicrotubule agents has occurred. Indeed, in silico models have been presented that might aid the discovery of novel agents. Among these, a 7-point pharmacophore model has been recently proposed. As a formal proof of this model, we carried out a ligand-based virtual screening on the colchicine-binding site. In vitro testing demonstrated that two compounds displayed a cytotoxic profile on neuroblastoma cancer cells (SH-SY5H) and one had an antitubulinic profile. © 2011 John Wiley & Sons A/S.

In silico identification of anthropogenic chemicals as ligands of zebrafish sex hormone binding globulin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thorsteinson, Nels; Ban, Fuqiang; Santos-Filho, Osvaldo

2009-01-01

Anthropogenic compounds with the capacity to interact with the steroid-binding site of sex hormone binding globulin (SHBG) pose health risks to humans and other vertebrates including fish. Building on studies of human SHBG, we have applied in silico drug discovery methods to identify potential binders for SHBG in zebrafish (Danio rerio) as a model aquatic organism. Computational methods, including; homology modeling, molecular dynamics simulations, virtual screening, and 3D QSAR analysis, successfully identified 6 non-steroidal substances from the ZINC chemical database that bind to zebrafish SHBG (zfSHBG) with low-micromolar to nanomolar affinities, as determined by a competitive ligand-binding assay. We alsomore » screened 80,000 commercial substances listed by the European Chemicals Bureau and Environment Canada, and 6 non-steroidal hits from this in silico screen were tested experimentally for zfSHBG binding. All 6 of these compounds displaced the [{sup 3}H]5{alpha}-dihydrotestosterone used as labeled ligand in the zfSHBG screening assay when tested at a 33 {mu}M concentration, and 3 of them (hexestrol, 4-tert-octylcatechol, and dihydrobenzo(a)pyren-7(8H)-one) bind to zfSHBG in the micromolar range. The study demonstrates the feasibility of large-scale in silico screening of anthropogenic compounds that may disrupt or highjack functionally important protein:ligand interactions. Such studies could increase the awareness of hazards posed by existing commercial chemicals at relatively low cost.« less

Combinatorial support vector machines approach for virtual screening of selective multi-target serotonin reuptake inhibitors from large compound libraries.

PubMed

Shi, Z; Ma, X H; Qin, C; Jia, J; Jiang, Y Y; Tan, C Y; Chen, Y Z

2012-02-01

Selective multi-target serotonin reuptake inhibitors enhance antidepressant efficacy. Their discovery can be facilitated by multiple methods, including in silico ones. In this study, we developed and tested an in silico method, combinatorial support vector machines (COMBI-SVMs), for virtual screening (VS) multi-target serotonin reuptake inhibitors of seven target pairs (serotonin transporter paired with noradrenaline transporter, H(3) receptor, 5-HT(1A) receptor, 5-HT(1B) receptor, 5-HT(2C) receptor, melanocortin 4 receptor and neurokinin 1 receptor respectively) from large compound libraries. COMBI-SVMs trained with 917-1951 individual target inhibitors correctly identified 22-83.3% (majority >31.1%) of the 6-216 dual inhibitors collected from literature as independent testing sets. COMBI-SVMs showed moderate to good target selectivity in misclassifying as dual inhibitors 2.2-29.8% (majority <15.4%) of the individual target inhibitors of the same target pair and 0.58-7.1% of the other 6 targets outside the target pair. COMBI-SVMs showed low dual inhibitor false hit rates (0.006-0.056%, 0.042-0.21%, 0.2-4%) in screening 17 million PubChem compounds, 168,000 MDDR compounds, and 7-8181 MDDR compounds similar to the dual inhibitors. Compared with similarity searching, k-NN and PNN methods, COMBI-SVM produced comparable dual inhibitor yields, similar target selectivity, and lower false hit rate in screening 168,000 MDDR compounds. The annotated classes of many COMBI-SVMs identified MDDR virtual hits correlate with the reported effects of their predicted targets. COMBI-SVM is potentially useful for searching selective multi-target agents without explicit knowledge of these agents. Copyright © 2011 Elsevier Inc. All rights reserved.

URPD: a specific product primer design tool

PubMed Central

2012-01-01

Background Polymerase chain reaction (PCR) plays an important role in molecular biology. Primer design fundamentally determines its results. Here, we present a currently available software that is not located in analyzing large sequence but used for a rather straight-forward way of visualizing the primer design process for infrequent users. Findings URPD (yoUR Primer Design), a web-based specific product primer design tool, combines the NCBI Reference Sequences (RefSeq), UCSC In-Silico PCR, memetic algorithm (MA) and genetic algorithm (GA) primer design methods to obtain specific primer sets. A friendly user interface is accomplished by built-in parameter settings. The incorporated smooth pipeline operations effectively guide both occasional and advanced users. URPD contains an automated process, which produces feasible primer pairs that satisfy the specific needs of the experimental design with practical PCR amplifications. Visual virtual gel electrophoresis and in silico PCR provide a simulated PCR environment. The comparison of Practical gel electrophoresis comparison to virtual gel electrophoresis facilitates and verifies the PCR experiment. Wet-laboratory validation proved that the system provides feasible primers. Conclusions URPD is a user-friendly tool that provides specific primer design results. The pipeline design path makes it easy to operate for beginners. URPD also provides a high throughput primer design function. Moreover, the advanced parameter settings assist sophisticated researchers in performing experiential PCR. Several novel functions, such as a nucleotide accession number template sequence input, local and global specificity estimation, primer pair redesign, user-interactive sequence scale selection, and virtual and practical PCR gel electrophoresis discrepancies have been developed and integrated into URPD. The URPD program is implemented in JAVA and freely available at http://bio.kuas.edu.tw/urpd/. PMID:22713312

Development and experimental test of support vector machines virtual screening method for searching Src inhibitors from large compound libraries.

PubMed

Han, Bucong; Ma, Xiaohua; Zhao, Ruiying; Zhang, Jingxian; Wei, Xiaona; Liu, Xianghui; Liu, Xin; Zhang, Cunlong; Tan, Chunyan; Jiang, Yuyang; Chen, Yuzong

2012-11-23

Src plays various roles in tumour progression, invasion, metastasis, angiogenesis and survival. It is one of the multiple targets of multi-target kinase inhibitors in clinical uses and trials for the treatment of leukemia and other cancers. These successes and appearances of drug resistance in some patients have raised significant interest and efforts in discovering new Src inhibitors. Various in-silico methods have been used in some of these efforts. It is desirable to explore additional in-silico methods, particularly those capable of searching large compound libraries at high yields and reduced false-hit rates. We evaluated support vector machines (SVM) as virtual screening tools for searching Src inhibitors from large compound libraries. SVM trained and tested by 1,703 inhibitors and 63,318 putative non-inhibitors correctly identified 93.53%~ 95.01% inhibitors and 99.81%~ 99.90% non-inhibitors in 5-fold cross validation studies. SVM trained by 1,703 inhibitors reported before 2011 and 63,318 putative non-inhibitors correctly identified 70.45% of the 44 inhibitors reported since 2011, and predicted as inhibitors 44,843 (0.33%) of 13.56M PubChem, 1,496 (0.89%) of 168 K MDDR, and 719 (7.73%) of 9,305 MDDR compounds similar to the known inhibitors. SVM showed comparable yield and reduced false hit rates in searching large compound libraries compared to the similarity-based and other machine-learning VS methods developed from the same set of training compounds and molecular descriptors. We tested three virtual hits of the same novel scaffold from in-house chemical libraries not reported as Src inhibitor, one of which showed moderate activity. SVM may be potentially explored for searching Src inhibitors from large compound libraries at low false-hit rates.

URPD: a specific product primer design tool.

PubMed

Chuang, Li-Yeh; Cheng, Yu-Huei; Yang, Cheng-Hong

2012-06-19

Polymerase chain reaction (PCR) plays an important role in molecular biology. Primer design fundamentally determines its results. Here, we present a currently available software that is not located in analyzing large sequence but used for a rather straight-forward way of visualizing the primer design process for infrequent users. URPD (yoUR Primer Design), a web-based specific product primer design tool, combines the NCBI Reference Sequences (RefSeq), UCSC In-Silico PCR, memetic algorithm (MA) and genetic algorithm (GA) primer design methods to obtain specific primer sets. A friendly user interface is accomplished by built-in parameter settings. The incorporated smooth pipeline operations effectively guide both occasional and advanced users. URPD contains an automated process, which produces feasible primer pairs that satisfy the specific needs of the experimental design with practical PCR amplifications. Visual virtual gel electrophoresis and in silico PCR provide a simulated PCR environment. The comparison of Practical gel electrophoresis comparison to virtual gel electrophoresis facilitates and verifies the PCR experiment. Wet-laboratory validation proved that the system provides feasible primers. URPD is a user-friendly tool that provides specific primer design results. The pipeline design path makes it easy to operate for beginners. URPD also provides a high throughput primer design function. Moreover, the advanced parameter settings assist sophisticated researchers in performing experiential PCR. Several novel functions, such as a nucleotide accession number template sequence input, local and global specificity estimation, primer pair redesign, user-interactive sequence scale selection, and virtual and practical PCR gel electrophoresis discrepancies have been developed and integrated into URPD. The URPD program is implemented in JAVA and freely available at http://bio.kuas.edu.tw/urpd/.

Virtual screening and pharmacophore design for a novel theoretical inhibitor of macrophage stimulating factor as a metastatic agent.

PubMed

Torktaz, Ibrahim; Mohamadhashem, Faezeh; Esmaeili, Abolghasem; Behjati, Mohaddeseh; Sharifzadeh, Sara

2013-01-01

Metastasis is a crucial aspect of cancer. Macrophage stimulating protein (MSP) is a single chain protein and can be cleaved by serum proteases. MSP has several roles in metastasis. In this in silico study, MSP as a metastatic agent was considered as a drug target. Crystallographic structure of MSP was retrieved from protein data bank. To find a chemical inhibitor of MSP, a library of KEGG compounds was screened and 1000 shape complemented ligands were retrieved with FindSite algorithm. Molegro Virtual Docker (MVD) software was used for docking simulation of shape complemented ligands against MSP. Moldock score was used as scoring function for virtual screening and potential inhibitors with more negative binding energy were obtained. PLANS scoring function was used for revaluation of virtual screening data. The top found chemical had binding affinity of -183.55 based on MolDock score and equal to -66.733 PLANTs score to MSP structure. Based on pharmacophore model of potential inhibitor, this study suggests that the chemical which was found in this research and its derivate can be used for subsequent laboratory studies.

The Pathologist 2.0: An Update on Digital Pathology in Veterinary Medicine.

PubMed

Bertram, Christof A; Klopfleisch, Robert

2017-09-01

Using light microscopy to describe the microarchitecture of normal and diseased tissues has changed very little since the middle of the 19th century. While the premise of histologic analysis remains intact, our relationship with the microscope is changing dramatically. Digital pathology offers new forms of visualization, and delivery of images is facilitated in unprecedented ways. This new technology can untether us entirely from our light microscopes, with many pathologists already performing their jobs using virtual microscopy. Several veterinary colleges have integrated virtual microscopy in their curriculum, and some diagnostic histopathology labs are switching to virtual microscopy as their main tool for the assessment of histologic specimens. Considering recent technical advancements of slide scanner and viewing software, digital pathology should now be considered a serious alternative to traditional light microscopy. This review therefore intends to give an overview of the current digital pathology technologies and their potential in all fields of veterinary pathology (ie, research, diagnostic service, and education). A future integration of digital pathology in the veterinary pathologist's workflow seems to be inevitable, and therefore it is proposed that trainees should be taught in digital pathology to keep up with the unavoidable digitization of the profession.

Identification of novel potential scaffold for class I HDACs inhibition: An in-silico protocol based on virtual screening, molecular dynamics, mathematical analysis and machine learning.

PubMed

Fan, Cong; Huang, Yanxin

2017-09-23

Histone deacetylases (HDACs) family has been widely reported as an important class of enzyme targets for cancer therapy. Much effort has been made in discovery of novel scaffolds for HDACs inhibition besides existing hydroxamic acids, cyclic peptides, benzamides, and short-chain fatty acids. Herein we set up an in-silico protocol which not only could detect potential Zn 2+ chelation bonds but also still adopted non-bonded model to be effective in discovery of Class I HDACs inhibitors, with little human's subjective visual judgment involved. We applied the protocol to screening of Chembridge database and selected out 7 scaffolds, 3 with probability of more than 99%. Biological assay results demonstrated that two of them exhibited HDAC-inhibitory activity and are thus considerable for structure modification to further improve their bio-activity. Copyright © 2017. Published by Elsevier Inc.

Applications and challenges of digital pathology and whole slide imaging.

PubMed

Higgins, C

2015-07-01

Virtual microscopy is a method for digitizing images of tissue on glass slides and using a computer to view, navigate, change magnification, focus and mark areas of interest. Virtual microscope systems (also called digital pathology or whole slide imaging systems) offer several advantages for biological scientists who use slides as part of their general, pharmaceutical, biotechnology or clinical research. The systems usually are based on one of two methodologies: area scanning or line scanning. Virtual microscope systems enable automatic sample detection, virtual-Z acquisition and creation of focal maps. Virtual slides are layered with multiple resolutions at each location, including the highest resolution needed to allow more detailed review of specific regions of interest. Scans may be acquired at 2, 10, 20, 40, 60 and 100 × or a combination of magnifications to highlight important detail. Digital microscopy starts when a slide collection is put into an automated or manual scanning system. The original slides are archived, then a server allows users to review multilayer digital images of the captured slides either by a closed network or by the internet. One challenge for adopting the technology is the lack of a universally accepted file format for virtual slides. Additional challenges include maintaining focus in an uneven sample, detecting specimens accurately, maximizing color fidelity with optimal brightness and contrast, optimizing resolution and keeping the images artifact-free. There are several manufacturers in the field and each has not only its own approach to these issues, but also its own image analysis software, which provides many options for users to enhance the speed, quality and accuracy of their process through virtual microscopy. Virtual microscope systems are widely used and are trusted to provide high quality solutions for teleconsultation, education, quality control, archiving, veterinary medicine, research and other fields.

Biomechanics-based in silico medicine: the manifesto of a new science.

PubMed

Viceconti, Marco

2015-01-21

In this perspective article we discuss the role of contemporary biomechanics in the light of recent applications such as the development of the so-called Virtual Physiological Human technologies for physiology-based in silico medicine. In order to build Virtual Physiological Human (VPH) models, computer models that capture and integrate the complex systemic dynamics of living organisms across radically different space-time scales, we need to re-formulate a vast body of existing biology and physiology knowledge so that it is formulated as a quantitative hypothesis, which can be expressed in mathematical terms. Once the predictive accuracy of these models is confirmed against controlled experiments and against clinical observations, we will have VPH model that can reliably predict certain quantitative changes in health status of a given patient, but also, more important, we will have a theory, in the true meaning this word has in the scientific method. In this scenario, biomechanics plays a very important role, biomechanics is one of the few areas of life sciences where we attempt to build full mechanistic explanations based on quantitative observations, in other words, we investigate living organisms like physical systems. This is in our opinion a Copernican revolution, around which the scope of biomechanics should be re-defined. Thus, we propose a new definition for our research domain "Biomechanics is the study of living organisms as mechanistic systems". Copyright © 2014 Elsevier Ltd. All rights reserved.

High throughput virtual screening and in silico ADMET analysis for rapid and efficient identification of potential PAP248-286 aggregation inhibitors as anti-HIV agents

NASA Astrophysics Data System (ADS)

Malik, Ruchi; Bunkar, Devendra; Choudhary, Bhanwar Singh; Srivastava, Shubham; Mehta, Pakhuri; Sharma, Manish

2016-10-01

Human semen is principal vehicle for transmission of HIV-1 and other enveloped viruses. Several endogenous peptides present in semen, including a 39-amino acid fragments of prostatic acid phosphatase (PAP248-286) assemble into amyloid fibrils named as semen-derived enhancer of viral infection (SEVI) that promote virion attachment to target cells which dramatically enhance HIV virus infection by up to 105-fold. Epigallocatechin-3-gallate (EGCG), a polyphenolic compound, is the major catechin found in green tea which disaggregates existing SEVI fibers, and inhibits the formation of SEVI fibers. The aim of this study was to screen a number of relevant polyphenols to develop a rational approach for designing PAP248-286 aggregation inhibitors as potential anti-HIV agents. The molecular docking based virtual screening results showed that polyphenolic compounds 2-6 possessed good docking score and interacted well with the active site residues of PAP248-286. Amino acid residues of binding site namely; Lys255, Ser256, Leu258 and Asn265 are involved in binding of these compounds. In silico ADMET prediction studies on these hits were also found to be promising. Polyphenolic compounds 2-6 identified as hits may act as novel leads for inhibiting aggregation of PAP248-286 into SEVI.

Five years of experience teaching pathology to dental students using the WebMicroscope

PubMed Central

2011-01-01

Background We describe development and evaluation of the user-friendly web based virtual microscopy - WebMicroscope for teaching and learning dental students basic and oral pathology. Traditional students microscopes were replaced by computer workstations. Methods The transition of the basic and oral pathology courses from light to virtual microscopy has been completed gradually over a five-year period. A pilot study was conducted in academic year 2005/2006 to estimate the feasibility of integrating virtual microscopy into a traditional light microscopy-based pathology course. The entire training set of glass slides was subsequently converted to virtual slides and placed on the WebMicroscope server. Giving access to fully digitized slides on the web with a browser and a viewer plug-in, the computer has become a perfect companion of the student. Results The study material consists now of over 400 fully digitized slides which covering 15 entities in basic and systemic pathology and 15 entities in oral pathology. Digitized slides are linked with still macro- and microscopic images, organized with clinical information into virtual cases and supplemented with text files, syllabus, PowerPoint presentations and animations on the web, serving additionally as material for individual studies. After their examinations, the students rated the use of the software, quality of the images, the ease of handling the images, and the effective use of virtual slides during the laboratory practicals. Responses were evaluated on a standardized scale. Because of the positive opinions and support from the students, the satisfaction surveys had shown a progressive improvement over the past 5 years. The WebMicroscope as a didactic tool for laboratory practicals was rated over 8 on a 1-10 scale for basic and systemic pathology and 9/10 for oral pathology especially as various students’ suggestions were implemented. Overall, the quality of the images was rated as very good. Conclusions An overwhelming majority of our students regarded a possibility of using virtual slides at their convenience as highly desirable. Our students and faculty consider the use of the virtual microscope for the study of basic as well as oral pathology as a significant improvement over the light microscope. PMID:21489183

μ Opioid receptor: novel antagonists and structural modeling

NASA Astrophysics Data System (ADS)

Kaserer, Teresa; Lantero, Aquilino; Schmidhammer, Helmut; Spetea, Mariana; Schuster, Daniela

2016-02-01

The μ opioid receptor (MOR) is a prominent member of the G protein-coupled receptor family and the molecular target of morphine and other opioid drugs. Despite the long tradition of MOR-targeting drugs, still little is known about the ligand-receptor interactions and structure-function relationships underlying the distinct biological effects upon receptor activation or inhibition. With the resolved crystal structure of the β-funaltrexamine-MOR complex, we aimed at the discovery of novel agonists and antagonists using virtual screening tools, i.e. docking, pharmacophore- and shape-based modeling. We suggest important molecular interactions, which active molecules share and distinguish agonists and antagonists. These results allowed for the generation of theoretically validated in silico workflows that were employed for prospective virtual screening. Out of 18 virtual hits evaluated in in vitro pharmacological assays, three displayed antagonist activity and the most active compound significantly inhibited morphine-induced antinociception. The new identified chemotypes hold promise for further development into neurochemical tools for studying the MOR or as potential therapeutic lead candidates.

A call for virtual experiments: accelerating the scientific process.

PubMed

Cooper, Jonathan; Vik, Jon Olav; Waltemath, Dagmar

2015-01-01

Experimentation is fundamental to the scientific method, whether for exploration, description or explanation. We argue that promoting the reuse of virtual experiments (the in silico analogues of wet-lab or field experiments) would vastly improve the usefulness and relevance of computational models, encouraging critical scrutiny of models and serving as a common language between modellers and experimentalists. We review the benefits of reusable virtual experiments: in specifying, assaying, and comparing the behavioural repertoires of models; as prerequisites for reproducible research; to guide model reuse and composition; and for quality assurance in the translational application of models. A key step towards achieving this is that models and experimental protocols should be represented separately, but annotated so as to facilitate the linking of models to experiments and data. Lastly, we outline how the rigorous, streamlined confrontation between experimental datasets and candidate models would enable a "continuous integration" of biological knowledge, transforming our approach to systems biology. Copyright © 2014 Elsevier Ltd. All rights reserved.

In Silico Simulation of a Clinical Trial Concerning Tumour Response to Radiotherapy

NASA Astrophysics Data System (ADS)

Dionysiou, Dimitra D.; Stamatakos, Georgios S.; Athanaileas, Theodoras E.; Merrychtas, Andreas; Kaklamani, Dimitra; Varvarigou, Theodora; Uzunoglu, Nikolaos

2008-11-01

The aim of this paper is to demonstrate how multilevel tumour growth and response to therapeutic treatment models can be used in order to simulate clinical trials, with the long-term intention of both better designing clinical studies and understanding their outcome based on basic biological science. For this purpose, an already developed computer simulation model of glioblastoma multiforme response to radiotherapy has been used and a clinical study concerning glioblastoma multiforme response to radiotherapy has been simulated. In order to facilitate the simulation of such virtual trials, a toolkit enabling the user-friendly execution of the simulations on grid infrastructures has been designed and developed. The results of the conducted virtual trial are in agreement with the outcome of the real clinical study.

Shape based virtual screening and molecular docking towards designing novel pancreatic lipase inhibitors

PubMed Central

Veeramachaneni, Ganesh Kumar; Raj, K Kranthi; Chalasani, Leela Madhuri; Annamraju, Sai Krishna; JS, Bondili; Talluri, Venkateswara Rao

2015-01-01

Increase in obesity rates and obesity associated health issues became one of the greatest health concerns in the present world population. With alarming increase in obese percentage there is a need to design new drugs related to the obesity targets. Among the various targets linked to obesity, pancreatic lipase was one of the promising targets for obesity treatment. Using the in silico methods like structure based virtual screening, QikProp, docking studies and binding energy calculations three molecules namely zinc85531017, zinc95919096 and zinc33963788 from the natural database were reported as the potential inhibitors for the pancreatic lipase. Among them zinc95919096 presented all the interactions matching to both standard and crystal ligand and hence it can be further proceeded to drug discovery process. PMID:26770027

Turning Microscopy in the Medical Curriculum Digital: Experiences from The Faculty of Health and Medical Sciences at University of Copenhagen

PubMed Central

Vainer, Ben; Mortensen, Niels Werner; Poulsen, Steen Seier; Sørensen, Allan Have; Olsen, Jørgen; Saxild, Hans Henrik; Johansen, Flemming Fryd

2017-01-01

Familiarity with the structure and composition of normal tissue and an understanding of the changes that occur during disease is pivotal to the study of the human body. For decades, microscope slides have been central to teaching pathology in medical courses and related subjects at the University of Copenhagen. Students had to learn how to use a microscope and envisage three-dimensional processes that occur in the body from two-dimensional glass slides. Here, we describe how a PathXL virtual microscopy system for teaching pathology and histology at the Faculty has recently been implemented, from an administrative, an economic, and a teaching perspective. This fully automatic digital microscopy system has been received positively by both teachers and students, and a decision was made to convert all courses involving microscopy to the virtual microscopy format. As a result, conventional analog microscopy will be phased out from the fall of 2016. PMID:28382225

In-silico Metabolome Target Analysis Towards PanC-based Antimycobacterial Agent Discovery.

PubMed

Khoshkholgh-Sima, Baharak; Sardari, Soroush; Izadi Mobarakeh, Jalal; Khavari-Nejad, Ramezan Ali

2015-01-01

Mycobacterium tuberculosis, the main cause of tuberculosis (TB), has still remained a global health crisis especially in developing countries. Tuberculosis treatment is a laborious and lengthy process with high risk of noncompliance, cytotoxicity adverse events and drug resistance in patient. Recently, there has been an alarming rise of drug resistant in TB. In this regard, it is an unmet need to develop novel antitubercular medicines that target new or more effective biochemical pathways to prevent drug resistant Mycobacterium. Integrated study of metabolic pathways through in-silico approach played a key role in antimycobacterial design process in this study. Our results suggest that pantothenate synthetase (PanC), anthranilate phosphoribosyl transferase (TrpD) and 3-isopropylmalate dehydratase (LeuD) might be appropriate drug targets. In the next step, in-silico ligand analysis was used for more detailed study of chemical tractability of targets. This was helpful to identify pantothenate synthetase (PanC, Rv3602c) as the best target for antimycobacterial design procedure. Virtual library screening on the best ligand of PanC was then performed for inhibitory ligand design. At the end, five chemical intermediates showed significant inhibition of Mycobacterium bovis with good selectivity indices (SI) ≥10 according to Tuberculosis Antimicrobial Acquisition & Coordinating Facility of US criteria for antimycobacterial screening programs.

Identification of hepta-histidine as a candidate drug for Huntington’s disease by in silico-in vitro- in vivo-integrated screens of chemical libraries

NASA Astrophysics Data System (ADS)

Imamura, Tomomi; Fujita, Kyota; Tagawa, Kazuhiko; Ikura, Teikichi; Chen, Xigui; Homma, Hidenori; Tamura, Takuya; Mao, Ying; Taniguchi, Juliana Bosso; Motoki, Kazumi; Nakabayashi, Makoto; Ito, Nobutoshi; Yamada, Kazunori; Tomii, Kentaro; Okano, Hideyuki; Kaye, Julia; Finkbeiner, Steven; Okazawa, Hitoshi

2016-09-01

We identified drug seeds for treating Huntington’s disease (HD) by combining in vitro single molecule fluorescence spectroscopy, in silico molecular docking simulations, and in vivo fly and mouse HD models to screen for inhibitors of abnormal interactions between mutant Htt and physiological Ku70, an essential DNA damage repair protein in neurons whose function is known to be impaired by mutant Htt. From 19,468 and 3,010,321 chemicals in actual and virtual libraries, fifty-six chemicals were selected from combined in vitro-in silico screens; six of these were further confirmed to have an in vivo effect on lifespan in a fly HD model, and two chemicals exerted an in vivo effect on the lifespan, body weight and motor function in a mouse HD model. Two oligopeptides, hepta-histidine (7H) and Angiotensin III, rescued the morphological abnormalities of primary neurons differentiated from iPS cells of human HD patients. For these selected drug seeds, we proposed a possible common structure. Unexpectedly, the selected chemicals enhanced rather than inhibited Htt aggregation, as indicated by dynamic light scattering analysis. Taken together, these integrated screens revealed a new pathway for the molecular targeted therapy of HD.

In Silico Investigation of a Surgical Interface for Remote Control of Modular Miniature Robots in Minimally Invasive Surgery

PubMed Central

Zygomalas, Apollon; Giokas, Konstantinos; Koutsouris, Dimitrios

2014-01-01

Aim. Modular mini-robots can be used in novel minimally invasive surgery techniques like natural orifice transluminal endoscopic surgery (NOTES) and laparoendoscopic single site (LESS) surgery. The control of these miniature assistants is complicated. The aim of this study is the in silico investigation of a remote controlling interface for modular miniature robots which can be used in minimally invasive surgery. Methods. The conceptual controlling system was developed, programmed, and simulated using professional robotics simulation software. Three different modes of control were programmed. The remote controlling surgical interface was virtually designed as a high scale representation of the respective modular mini-robot, therefore a modular controlling system itself. Results. With the proposed modular controlling system the user could easily identify the conformation of the modular mini-robot and adequately modify it as needed. The arrangement of each module was always known. The in silico investigation gave useful information regarding the controlling mode, the adequate speed of rearrangements, and the number of modules needed for efficient working tasks. Conclusions. The proposed conceptual model may promote the research and development of more sophisticated modular controlling systems. Modular surgical interfaces may improve the handling and the dexterity of modular miniature robots during minimally invasive procedures. PMID:25295187

In silico investigation of a surgical interface for remote control of modular miniature robots in minimally invasive surgery.

PubMed

Zygomalas, Apollon; Giokas, Konstantinos; Koutsouris, Dimitrios

2014-01-01

Aim. Modular mini-robots can be used in novel minimally invasive surgery techniques like natural orifice transluminal endoscopic surgery (NOTES) and laparoendoscopic single site (LESS) surgery. The control of these miniature assistants is complicated. The aim of this study is the in silico investigation of a remote controlling interface for modular miniature robots which can be used in minimally invasive surgery. Methods. The conceptual controlling system was developed, programmed, and simulated using professional robotics simulation software. Three different modes of control were programmed. The remote controlling surgical interface was virtually designed as a high scale representation of the respective modular mini-robot, therefore a modular controlling system itself. Results. With the proposed modular controlling system the user could easily identify the conformation of the modular mini-robot and adequately modify it as needed. The arrangement of each module was always known. The in silico investigation gave useful information regarding the controlling mode, the adequate speed of rearrangements, and the number of modules needed for efficient working tasks. Conclusions. The proposed conceptual model may promote the research and development of more sophisticated modular controlling systems. Modular surgical interfaces may improve the handling and the dexterity of modular miniature robots during minimally invasive procedures.

Identification of hepta-histidine as a candidate drug for Huntington’s disease by in silico-in vitro- in vivo-integrated screens of chemical libraries

PubMed Central

Imamura, Tomomi; Fujita, Kyota; Tagawa, Kazuhiko; Ikura, Teikichi; Chen, Xigui; Homma, Hidenori; Tamura, Takuya; Mao, Ying; Taniguchi, Juliana Bosso; Motoki, Kazumi; Nakabayashi, Makoto; Ito, Nobutoshi; Yamada, Kazunori; Tomii, Kentaro; Okano, Hideyuki; Kaye, Julia; Finkbeiner, Steven; Okazawa, Hitoshi

2016-01-01

We identified drug seeds for treating Huntington’s disease (HD) by combining in vitro single molecule fluorescence spectroscopy, in silico molecular docking simulations, and in vivo fly and mouse HD models to screen for inhibitors of abnormal interactions between mutant Htt and physiological Ku70, an essential DNA damage repair protein in neurons whose function is known to be impaired by mutant Htt. From 19,468 and 3,010,321 chemicals in actual and virtual libraries, fifty-six chemicals were selected from combined in vitro-in silico screens; six of these were further confirmed to have an in vivo effect on lifespan in a fly HD model, and two chemicals exerted an in vivo effect on the lifespan, body weight and motor function in a mouse HD model. Two oligopeptides, hepta-histidine (7H) and Angiotensin III, rescued the morphological abnormalities of primary neurons differentiated from iPS cells of human HD patients. For these selected drug seeds, we proposed a possible common structure. Unexpectedly, the selected chemicals enhanced rather than inhibited Htt aggregation, as indicated by dynamic light scattering analysis. Taken together, these integrated screens revealed a new pathway for the molecular targeted therapy of HD. PMID:27653664

Super-Resolution Scanning Laser Microscopy Based on Virtually Structured Detection

PubMed Central

Zhi, Yanan; Wang, Benquan; Yao, Xincheng

2016-01-01

Light microscopy plays a key role in biological studies and medical diagnosis. The spatial resolution of conventional optical microscopes is limited to approximately half the wavelength of the illumination light as a result of the diffraction limit. Several approaches—including confocal microscopy, stimulated emission depletion microscopy, stochastic optical reconstruction microscopy, photoactivated localization microscopy, and structured illumination microscopy—have been established to achieve super-resolution imaging. However, none of these methods is suitable for the super-resolution ophthalmoscopy of retinal structures because of laser safety issues and inevitable eye movements. We recently experimentally validated virtually structured detection (VSD) as an alternative strategy to extend the diffraction limit. Without the complexity of structured illumination, VSD provides an easy, low-cost, and phase artifact–free strategy to achieve super-resolution in scanning laser microscopy. In this article we summarize the basic principles of the VSD method, review our demonstrated single-point and line-scan super-resolution systems, and discuss both technical challenges and the potential of VSD-based instrumentation for super-resolution ophthalmoscopy of the retina. PMID:27480461

Virtual Screening and Pharmacophore Design for a Novel Theoretical Inhibitor of Macrophage Stimulating Factor as a Metastatic Agent

PubMed Central

Torktaz, Ibrahim; Mohamadhashem, Faezeh; Esmaeili, Abolghasem; Behjati, Mohaddeseh; Sharifzadeh, Sara

2013-01-01

Introduction: Metastasis is a crucial aspect of cancer. Macrophage stimulating protein (MSP) is a single chain protein and can be cleaved by serum proteases. MSP has several roles in metastasis. In this in silico study, MSP as a metastatic agent was considered as a drug target. Methods: Crystallographic structure of MSP was retrieved from protein data bank. To find a chemical inhibitor of MSP, a library of KEGG compounds was screened and 1000 shape complemented ligands were retrieved with FindSite algorithm. Molegro Virtual Docker (MVD) software was used for docking simulation of shape complemented ligands against MSP. Moldock score was used as scoring function for virtual screening and potential inhibitors with more negative binding energy were obtained. PLANS scoring function was used for revaluation of virtual screening data. Results: The top found chemical had binding affinity of -183.55 based on MolDock score and equal to -66.733 PLANTs score to MSP structure. Conclusion: Based on pharmacophore model of potential inhibitor, this study suggests that the chemical which was found in this research and its derivate can be used for subsequent laboratory studies. PMID:24163807

Modeling of Fibrin Gels Based on Confocal Microscopy and Light-Scattering Data

PubMed Central

Magatti, Davide; Molteni, Matteo; Cardinali, Barbara; Rocco, Mattia; Ferri, Fabio

2013-01-01

Fibrin gels are biological networks that play a fundamental role in blood coagulation and other patho/physiological processes, such as thrombosis and cancer. Electron and confocal microscopies show a collection of fibers that are relatively monodisperse in diameter, not uniformly distributed, and connected at nodal points with a branching order of ∼3–4. Although in the confocal images the hydrated fibers appear to be quite straight (mass fractal dimension Dm = 1), for the overall system 1

In silico models for the prediction of dose-dependent human hepatotoxicity

NASA Astrophysics Data System (ADS)

Cheng, Ailan; Dixon, Steven L.

2003-12-01

The liver is extremely vulnerable to the effects of xenobiotics due to its critical role in metabolism. Drug-induced hepatotoxicity may involve any number of different liver injuries, some of which lead to organ failure and, ultimately, patient death. Understandably, liver toxicity is one of the most important dose-limiting considerations in the drug development cycle, yet there remains a serious shortage of methods to predict hepatotoxicity from chemical structure. We discuss our latest findings in this area and present a new, fully general in silico model which is able to predict the occurrence of dose-dependent human hepatotoxicity with greater than 80% accuracy. Utilizing an ensemble recursive partitioning approach, the model classifies compounds as toxic or non-toxic and provides a confidence level to indicate which predictions are most likely to be correct. Only 2D structural information is required and predictions can be made quite rapidly, so this approach is entirely appropriate for data mining applications and for profiling large synthetic and/or virtual libraries.

Early assessment of proarrhythmic risk of drugs using the in vitro data and single-cell-based in silico models: proof of concept.

PubMed

Abbasi, Mitra; Small, Ben G; Patel, Nikunjkumar; Jamei, Masoud; Polak, Sebastian

2017-02-01

To determine the predictive performance of in silico models using drug-specific preclinical cardiac electrophysiology data to investigate drug-induced arrhythmia risk (e.g. Torsade de pointes (TdP)) in virtual human subjects. To assess drug proarrhythmic risk, we used a set of in vitro electrophysiological measurements describing ion channel inhibition triggered by the investigated drugs. The Cardiac Safety Simulator version 2.0 (CSS; Simcyp, Sheffield, UK) platform was used to simulate human left ventricular cardiac myocyte action potential models. This study shows the impact of drug concentration changes on particular ionic currents by using available experimental data. The simulation results display safety threshold according to drug concentration threshold and log (threshold concentration/ effective therapeutic plasma concentration (ETPC)). We reproduced the underlying biophysical characteristics of cardiac cells resulted in effects of drugs associated with cardiac arrhythmias (action potential duration (APD) and QT prolongation and TdP) which were observed in published 3D simulations, yet with much less computational burden.

In silico design of novel proton-pump inhibitors with reduced adverse effects.

PubMed

Li, Xiaoyi; Kang, Hong; Liu, Wensheng; Singhal, Sarita; Jiao, Na; Wang, Yong; Zhu, Lixin; Zhu, Ruixin

2018-05-30

The development of new proton-pump inhibitors (PPIs) with less adverse effects by lowering the pKa values of nitrogen atoms in pyrimidine rings has been previously suggested by our group. In this work, we proposed that new PPIs should have the following features: (1) number of ring II = number of ring I + 1; (2) preferably five, six, or seven-membered heteroatomic ring for stability; and (3) 1 < pKa1 < 4. Six molecular scaffolds based on the aforementioned criteria were constructed, and R groups were extracted from compounds in extensive data sources. A virtual molecule dataset was established, and the pKa values of specific atoms on the molecules in the dataset were calculated to select the molecules with required pKa values. Drug-likeness screening was further conducted to obtain the candidates that significantly reduced the adverse effects of long-term PPI use. This study provided insights and tools for designing targeted molecules in silico that are suitable for practical applications.

Monte Carlo simulations guided by imaging to predict the in vitro ranking of radiosensitizing nanoparticles.

PubMed

Retif, Paul; Reinhard, Aurélie; Paquot, Héna; Jouan-Hureaux, Valérie; Chateau, Alicia; Sancey, Lucie; Barberi-Heyob, Muriel; Pinel, Sophie; Bastogne, Thierry

This article addresses the in silico-in vitro prediction issue of organometallic nanoparticles (NPs)-based radiosensitization enhancement. The goal was to carry out computational experiments to quickly identify efficient nanostructures and then to preferentially select the most promising ones for the subsequent in vivo studies. To this aim, this interdisciplinary article introduces a new theoretical Monte Carlo computational ranking method and tests it using 3 different organometallic NPs in terms of size and composition. While the ranking predicted in a classical theoretical scenario did not fit the reference results at all, in contrast, we showed for the first time how our accelerated in silico virtual screening method, based on basic in vitro experimental data (which takes into account the NPs cell biodistribution), was able to predict a relevant ranking in accordance with in vitro clonogenic efficiency. This corroborates the pertinence of such a prior ranking method that could speed up the preclinical development of NPs in radiation therapy.

Rational design of novel TLR4 ligands by in silico screening and their functional and structural characterization in vitro.

PubMed

Honegr, Jan; Malinak, David; Dolezal, Rafael; Soukup, Ondrej; Benkova, Marketa; Hroch, Lukas; Benek, Ondrej; Janockova, Jana; Kuca, Kamil; Prymula, Roman

2018-02-25

The purpose of this study was to identify new small molecules that possess activity on human toll-like receptor 4 associated with the myeloid differentiation protein 2 (hTLR4/MD2). Following current rational drug design principles, we firstly performed a ligand and structure based virtual screening of more than 130 000 compounds to discover until now unknown class of hTLR4/MD2 modulators that could be used as novel type of immunologic adjuvants. The core of the in silico study was molecular docking of flexible ligands in a partially flexible hTLR4/MD2 receptor model using a peta-flops-scale supercomputer. The most promising substances resulting from this study, related to anthracene-succimide hybrids, were synthesized and tested. The best prepared candidate exhibited 80% of Monophosphoryl Lipid A in vitro agonistic activity in cell lines expressing hTLR4/MD2. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Emulation and design of terahertz reflection-mode confocal scanning microscopy based on virtual pinhole

NASA Astrophysics Data System (ADS)

Yang, Yong-fa; Li, Qi

2014-12-01

In the practical application of terahertz reflection-mode confocal scanning microscopy, the size of detector pinhole is an important factor that determines the performance of spatial resolution characteristic of the microscopic system. However, the use of physical pinhole brings some inconvenience to the experiment and the adjustment error has a great influence on the experiment result. Through reasonably selecting the parameter of matrix detector virtual pinhole (VPH), it can efficiently approximate the physical pinhole. By using this approach, the difficulty of experimental calibration is reduced significantly. In this article, an imaging scheme of terahertz reflection-mode confocal scanning microscopy that is based on the matrix detector VPH is put forward. The influence of detector pinhole size on the axial resolution of confocal scanning microscopy is emulated and analyzed. Then, the parameter of VPH is emulated when the best axial imaging performance is reached.

In-Silico Design, Synthesis and Evaluation of a Nanostructured Hydrogel as a Dimethoate Removal Agent.

PubMed

Avila-Salas, Fabian; Marican, Adolfo; Villaseñor, Jorge; Arenas-Salinas, Mauricio; Argandoña, Yerko; Caballero, Julio; Durán-Lara, Esteban F

2018-01-04

This study describes the in-silico design, synthesis, and evaluation of a cross-linked PVA hydrogel (CLPH) for the absorption of organophosphorus pesticide dimethoate from aqueous solutions. The crosslinking effectiveness of 14 dicarboxilic acids was evaluated through in-silico studies using semiempirical quantum mechanical calculations. According to the theoretical studies, the nanopore of PVA cross-linked with malic acid (CLPH-MA) showed the best interaction energy with dimethoate. Later, using all-atom molecular dynamics simulations, three hydrogels with different proportions of PVA:MA (10:2, 10:4, and 10:6) were used to evaluate their interactions with dimethoate. These results showed that the suitable crosslinking degree for improving the affinity for the pesticide was with 20% ( W %) of the cross-linker. In the experimental absorption study, the synthesized CLPH-MA20 recovered 100% of dimethoate from aqueous solutions. Therefore, the theoretical data were correlated with the experimental studies. Surface morphology of CLPH-MA20 by Scanning Electron Microscopy (SEM) was analyzed. In conclusion, the ability of CLPH-MA20 to remove dimethoate could be used as a technological alternative for the treatment of contaminated water.

In-Silico Design, Synthesis and Evaluation of a Nanostructured Hydrogel as a Dimethoate Removal Agent

PubMed Central

Avila-Salas, Fabian; Marican, Adolfo; Villaseñor, Jorge; Argandoña, Yerko

2018-01-01

This study describes the in-silico design, synthesis, and evaluation of a cross-linked PVA hydrogel (CLPH) for the absorption of organophosphorus pesticide dimethoate from aqueous solutions. The crosslinking effectiveness of 14 dicarboxilic acids was evaluated through in-silico studies using semiempirical quantum mechanical calculations. According to the theoretical studies, the nanopore of PVA cross-linked with malic acid (CLPH-MA) showed the best interaction energy with dimethoate. Later, using all-atom molecular dynamics simulations, three hydrogels with different proportions of PVA:MA (10:2, 10:4, and 10:6) were used to evaluate their interactions with dimethoate. These results showed that the suitable crosslinking degree for improving the affinity for the pesticide was with 20% (W%) of the cross-linker. In the experimental absorption study, the synthesized CLPH-MA20 recovered 100% of dimethoate from aqueous solutions. Therefore, the theoretical data were correlated with the experimental studies. Surface morphology of CLPH-MA20 by Scanning Electron Microscopy (SEM) was analyzed. In conclusion, the ability of CLPH-MA20 to remove dimethoate could be used as a technological alternative for the treatment of contaminated water. PMID:29300312

Novel Polyurethane Matrix Systems Reveal a Particular Sustained Release Behavior Studied by Imaging and Computational Modeling.

PubMed

Campiñez, María Dolores; Caraballo, Isidoro; Puchkov, Maxim; Kuentz, Martin

2017-07-01

The aim of the present work was to better understand the drug-release mechanism from sustained release matrices prepared with two new polyurethanes, using a novel in silico formulation tool based on 3-dimensional cellular automata. For this purpose, two polymers and theophylline as model drug were used to prepare binary matrix tablets. Each formulation was simulated in silico, and its release behavior was compared to the experimental drug release profiles. Furthermore, the polymer distributions in the tablets were imaged by scanning electron microscopy (SEM) and the changes produced by the tortuosity were quantified and verified using experimental data. The obtained results showed that the polymers exhibited a surprisingly high ability for controlling drug release at low excipient concentrations (only 10% w/w of excipient controlled the release of drug during almost 8 h). The mesoscopic in silico model helped to reveal how the novel biopolymers were controlling drug release. The mechanism was found to be a special geometrical arrangement of the excipient particles, creating an almost continuous barrier surrounding the drug in a very effective way, comparable to lipid or waxy excipients but with the advantages of a much higher compactability, stability, and absence of excipient polymorphism.

Active Learning: A Small Group Histology Laboratory Exercise in a Whole Class Setting Utilizing Virtual Slides and Peer Education

ERIC Educational Resources Information Center

Bloodgood, Robert A.

2012-01-01

Histology laboratory instruction is moving away from the sole use of the traditional combination of light microscopes and glass slides in favor of virtual microscopy and virtual slides. At the same time, medical curricula are changing so as to reduce scheduled time for basic science instruction as well as focusing on student-centered learning…

Discovery of the glycogen phosphorylase-modulating activity of a resveratrol glucoside by using a virtual screening protocol optimized for solvation effects.

PubMed

Mavrokefalos, Nikolaos; Myrianthopoulos, Vassilios; Chajistamatiou, Aikaterini S; Chrysina, Evangelia D; Mikros, Emmanuel

2015-04-01

The identification of natural products that can modulate blood glucose levels is of great interest as it can possibly facilitate the utilization of mild interventions such as herbal medicine or functional foods in the treatment of chronic diseases like diabetes. One of the established drug targets for antihyperglycemic therapy is glycogen phosphorylase. To evaluate the glycogen phosphorylase inhibitory properties of an in-house compound collection consisting to a large extent of natural products, a stepwise virtual and experimental screening protocol was devised and implemented. The fact that the active site of glycogen phosphorylase is highly hydrated emphasized that a methodological aspect needed to be efficiently addressed prior to an in silico evaluation of the compound collection. The effect of water molecules on docking calculations was regarded as a key parameter in terms of virtual screening protocol optimization. Statistical analysis of 125 structures of glycogen phosphorylase and solvent mapping focusing on the active site hydration motif in combination with a retrospective screening revealed the importance of a set of 29 crystallographic water molecules for achieving high enrichment as to the discrimination between active compounds and inactive decoys. The scaling of Van der Waals radii of system atoms had an additional effect on screening performance. Having optimized the in silico protocol, a prospective evaluation of the in-house compound collection derived a set of 18 top-ranked natural products that were subsequently evaluated in vitro for their activity as glycogen phosphorylase inhibitors. Two phenolic glucosides with glycogen phosphorylase-modulating activity were identified, whereas the most potent compound affording mid-micromolar inhibition was a glucosidic derivative of resveratrol, a stilbene well-known for its wide range of biological activities. Results show the possible phytotherapeutic and nutraceutical potential of products common in the Mediterranean countries, such as red wine and Vitis products in general or green raw salads and herbal preparations, where such compounds are abundant. Georg Thieme Verlag KG Stuttgart · New York.

Development and experimental test of support vector machines virtual screening method for searching Src inhibitors from large compound libraries

PubMed Central

2012-01-01

Background Src plays various roles in tumour progression, invasion, metastasis, angiogenesis and survival. It is one of the multiple targets of multi-target kinase inhibitors in clinical uses and trials for the treatment of leukemia and other cancers. These successes and appearances of drug resistance in some patients have raised significant interest and efforts in discovering new Src inhibitors. Various in-silico methods have been used in some of these efforts. It is desirable to explore additional in-silico methods, particularly those capable of searching large compound libraries at high yields and reduced false-hit rates. Results We evaluated support vector machines (SVM) as virtual screening tools for searching Src inhibitors from large compound libraries. SVM trained and tested by 1,703 inhibitors and 63,318 putative non-inhibitors correctly identified 93.53%~ 95.01% inhibitors and 99.81%~ 99.90% non-inhibitors in 5-fold cross validation studies. SVM trained by 1,703 inhibitors reported before 2011 and 63,318 putative non-inhibitors correctly identified 70.45% of the 44 inhibitors reported since 2011, and predicted as inhibitors 44,843 (0.33%) of 13.56M PubChem, 1,496 (0.89%) of 168 K MDDR, and 719 (7.73%) of 9,305 MDDR compounds similar to the known inhibitors. Conclusions SVM showed comparable yield and reduced false hit rates in searching large compound libraries compared to the similarity-based and other machine-learning VS methods developed from the same set of training compounds and molecular descriptors. We tested three virtual hits of the same novel scaffold from in-house chemical libraries not reported as Src inhibitor, one of which showed moderate activity. SVM may be potentially explored for searching Src inhibitors from large compound libraries at low false-hit rates. PMID:23173901

Myocardial electrical conduction blockade time dominated by irradiance on photodynamic reaction: in vitro and in silico study

NASA Astrophysics Data System (ADS)

Ogawa, Emiyu; Arai, Tsunenori

2018-02-01

The time for electrical conduction blockade induced by a photodynamic reaction was studied on a myocardial cell wire in vitro and an in silico simulation model was constructed to understand the necessary time for electrical conduction blockade for the wire. Vulnerable state of the cells on a laser interaction would be an unstable and undesirable state since the cells might progress to completely damaged or repaired to change significantly therapeutic effect. So that in silico model, which can calculate the vulnerable cell state, is needed. Understanding an immediate electrical conduction blockade is needed for our proposed new methodology for tachyarrhythmia catheter ablation applying a photodynamic reaction. We studied the electrical conduction blockade occurrence on the electrical conduction wire made of cultured myocardial cells in a line shape and constructed in silico model based on this experimental data. The intracellular Ca2+ ion concentrations were obtained using Fluo-4 AM dye under a confocal laser microscope. A cross-correlation function was used for the electrical conduction blockade judgment. The photodynamic reaction was performed under the confocal microscopy with 3-120 mW/cm2 in irradiance by the diode laser with 663 nm in wavelength. We obtained that the time for the electrical conduction blockade decreased with the irradiance increasing. We constructed a simulation model composed of three states; living cells, vulnerable cells, and blocked cells, using the obtained experimental data and we found the rate constant by an optimization using a conjugate gradient method.

Towards control of dexterous hand manipulations using a silicon Pattern Generator.

PubMed

Russell, Alexander; Tenore, Francesco; Singhal, Girish; Thakor, Nitish; Etienne-Cummings, Ralph

2008-01-01

This work demonstrates how an in silico Pattern Generator (PG) can be used as a low power control system for rhythmic hand movements in an upper-limb prosthesis. Neural spike patterns, which encode rotation of a cylindrical object, were implemented in a custom Very Large Scale Integration chip. PG control was tested by using the decoded control signals to actuate the fingers of a virtual prosthetic arm. This system provides a framework for prototyping and controlling dexterous hand manipulation tasks in a compact and efficient solution.

Virtual rough samples to test 3D nanometer-scale scanning electron microscopy stereo photogrammetry.

PubMed

Villarrubia, J S; Tondare, V N; Vladár, A E

2016-01-01

The combination of scanning electron microscopy for high spatial resolution, images from multiple angles to provide 3D information, and commercially available stereo photogrammetry software for 3D reconstruction offers promise for nanometer-scale dimensional metrology in 3D. A method is described to test 3D photogrammetry software by the use of virtual samples-mathematical samples from which simulated images are made for use as inputs to the software under test. The virtual sample is constructed by wrapping a rough skin with any desired power spectral density around a smooth near-trapezoidal line with rounded top corners. Reconstruction is performed with images simulated from different angular viewpoints. The software's reconstructed 3D model is then compared to the known geometry of the virtual sample. Three commercial photogrammetry software packages were tested. Two of them produced results for line height and width that were within close to 1 nm of the correct values. All of the packages exhibited some difficulty in reconstructing details of the surface roughness.

Virtual k -Space Modulation Optical Microscopy

NASA Astrophysics Data System (ADS)

Kuang, Cuifang; Ma, Ye; Zhou, Renjie; Zheng, Guoan; Fang, Yue; Xu, Yingke; Liu, Xu; So, Peter T. C.

2016-07-01

We report a novel superresolution microscopy approach for imaging fluorescence samples. The reported approach, termed virtual k -space modulation optical microscopy (VIKMOM), is able to improve the lateral resolution by a factor of 2, reduce the background level, improve the optical sectioning effect and correct for unknown optical aberrations. In the acquisition process of VIKMOM, we used a scanning confocal microscope setup with a 2D detector array to capture sample information at each scanned x -y position. In the recovery process of VIKMOM, we first modulated the captured data by virtual k -space coding and then employed a ptychography-inspired procedure to recover the sample information and correct for unknown optical aberrations. We demonstrated the performance of the reported approach by imaging fluorescent beads, fixed bovine pulmonary artery endothelial (BPAE) cells, and living human astrocytes (HA). As the VIKMOM approach is fully compatible with conventional confocal microscope setups, it may provide a turn-key solution for imaging biological samples with ˜100 nm lateral resolution, in two or three dimensions, with improved optical sectioning capabilities and aberration correcting.

Virtual Reality and Simulation in Neurosurgical Training.

PubMed

Bernardo, Antonio

2017-10-01

Recent biotechnological advances, including three-dimensional microscopy and endoscopy, virtual reality, surgical simulation, surgical robotics, and advanced neuroimaging, have continued to mold the surgeon-computer relationship. For developing neurosurgeons, such tools can reduce the learning curve, improve conceptual understanding of complex anatomy, and enhance visuospatial skills. We explore the current and future roles and application of virtual reality and simulation in neurosurgical training. Copyright © 2017 Elsevier Inc. All rights reserved.

Confocal microscopy imaging of solid tissue

EPA Science Inventory

Confocal laser scanning microscopy (CLSM) is a technique that is capable of generating serial sections of whole-mount tissue and then reassembling the computer acquired images as a virtual 3-dimensional structure. In many ways CLSM offers an alternative to traditional sectioning ...

Combinatorial In Silico Strategy towards Identifying Potential Hotspots during Inhibition of Structurally Identical HDAC1 and HDAC2 Enzymes for Effective Chemotherapy against Neurological Disorders

PubMed Central

Ganai, Shabir Ahmad; Abdullah, Ehsaan; Rashid, Romana; Altaf, Mohammad

2017-01-01

Histone deacetylases (HDACs) regulate epigenetic gene expression programs by modulating chromatin architecture and are required for neuronal development. Dysregulation of HDACs and aberrant chromatin acetylation homeostasis have been implicated in various diseases ranging from cancer to neurodegenerative disorders. Histone deacetylase inhibitors (HDACi), the small molecules interfering HDACs have shown enhanced acetylation of the genome and are gaining great attention as potent drugs for treating cancer and neurodegeneration. HDAC2 overexpression has implications in decreasing dendrite spine density, synaptic plasticity and in triggering neurodegenerative signaling. Pharmacological intervention against HDAC2 though promising also targets neuroprotective HDAC1 due to high sequence identity (94%) with former in catalytic domain, culminating in debilitating off-target effects and creating hindrance in the defined intervention. This emphasizes the need of designing HDAC2-selective inhibitors to overcome these vicious effects and for escalating the therapeutic efficacy. Here we report a top-down combinatorial in silico approach for identifying the structural variants that are substantial for interactions against HDAC1 and HDAC2 enzymes. We used extra-precision (XP)-molecular docking, Molecular Mechanics Generalized Born Surface Area (MMGBSA) for predicting affinity of inhibitors against the HDAC1 and HDAC2 enzymes. Importantly, we employed a novel in silico strategy of coupling the state-of-the-art molecular dynamics simulation (MDS) to energetically-optimized structure based pharmacophores (e-Pharmacophores) method via MDS trajectory clustering for hypothesizing the e-Pharmacophore models. Further, we performed e-Pharmacophores based virtual screening against phase database containing millions of compounds. We validated the data by performing the molecular docking and MM-GBSA studies for the selected hits among the retrieved ones. Our studies attributed inhibitor potency to the ability of forming multiple interactions and infirm potency to least interactions. Moreover, our studies delineated that a single HDAC inhibitor portrays differential features against HDAC1 and HDAC2 enzymes. The high affinity and selective HDAC2 inhibitors retrieved through e-Pharmacophores based virtual screening will play a critical role in ameliorating neurodegenerative signaling without hampering the neuroprotective isoform (HDAC1). PMID:29170627

VEDA: a web-based virtual environment for dynamic atomic force microscopy.

PubMed

Melcher, John; Hu, Shuiqing; Raman, Arvind

2008-06-01

We describe here the theory and applications of virtual environment dynamic atomic force microscopy (VEDA), a suite of state-of-the-art simulation tools deployed on nanoHUB (www.nanohub.org) for the accurate simulation of tip motion in dynamic atomic force microscopy (dAFM) over organic and inorganic samples. VEDA takes advantage of nanoHUB's cyberinfrastructure to run high-fidelity dAFM tip dynamics computations on local clusters and the teragrid. Consequently, these tools are freely accessible and the dAFM simulations are run using standard web-based browsers without requiring additional software. A wide range of issues in dAFM ranging from optimal probe choice, probe stability, and tip-sample interaction forces, power dissipation, to material property extraction and scanning dynamics over hetereogeneous samples can be addressed.

Invited Article: VEDA: A web-based virtual environment for dynamic atomic force microscopy

NASA Astrophysics Data System (ADS)

Melcher, John; Hu, Shuiqing; Raman, Arvind

2008-06-01

We describe here the theory and applications of virtual environment dynamic atomic force microscopy (VEDA), a suite of state-of-the-art simulation tools deployed on nanoHUB (www.nanohub.org) for the accurate simulation of tip motion in dynamic atomic force microscopy (dAFM) over organic and inorganic samples. VEDA takes advantage of nanoHUB's cyberinfrastructure to run high-fidelity dAFM tip dynamics computations on local clusters and the teragrid. Consequently, these tools are freely accessible and the dAFM simulations are run using standard web-based browsers without requiring additional software. A wide range of issues in dAFM ranging from optimal probe choice, probe stability, and tip-sample interaction forces, power dissipation, to material property extraction and scanning dynamics over hetereogeneous samples can be addressed.

In silico identification of novel ligands for G-quadruplex in the c- MYC promoter

NASA Astrophysics Data System (ADS)

Kang, Hyun-Jin; Park, Hyun-Ju

2015-04-01

G-quadruplex DNA formed in NHEIII1 region of oncogene promoter inhibits transcription of the genes. In this study, virtual screening combining pharmacophore-based search and structure-based docking screening was conducted to discover ligands binding to G-quadruplex in promoter region of c- MYC. Several hit ligands showed the selective PCR-arresting effects for oligonucleotide containing c- MYC G-quadruplex forming sequence. Among them, three hits selectively inhibited cell proliferation and decreased c- MYC mRNA level in Ramos cells, where NHEIII1 is included in translocated c- MYC gene for overexpression. Promoter assay using two kinds of constructs with wild-type and mutant sequences showed that interaction of these ligands with the G-quadruplex resulted in turning-off of the reporter gene. In conclusion, combined virtual screening methods were successfully used for discovery of selective c- MYC promoter G-quadruplex binders with anticancer activity.

In-silico guided discovery of novel CCR9 antagonists

NASA Astrophysics Data System (ADS)

Zhang, Xin; Cross, Jason B.; Romero, Jan; Heifetz, Alexander; Humphries, Eric; Hall, Katie; Wu, Yuchuan; Stucka, Sabrina; Zhang, Jing; Chandonnet, Haoqun; Lippa, Blaise; Ryan, M. Dominic; Baber, J. Christian

2018-03-01

Antagonism of CCR9 is a promising mechanism for treatment of inflammatory bowel disease, including ulcerative colitis and Crohn's disease. There is limited experimental data on CCR9 and its ligands, complicating efforts to identify new small molecule antagonists. We present here results of a successful virtual screening and rational hit-to-lead campaign that led to the discovery and initial optimization of novel CCR9 antagonists. This work uses a novel data fusion strategy to integrate the output of multiple computational tools, such as 2D similarity search, shape similarity, pharmacophore searching, and molecular docking, as well as the identification and incorporation of privileged chemokine fragments. The application of various ranking strategies, which combined consensus and parallel selection methods to achieve a balance of enrichment and novelty, resulted in 198 virtual screening hits in total, with an overall hit rate of 18%. Several hits were developed into early leads through targeted synthesis and purchase of analogs.

Footprinting of Inhibitor Interactions of In Silico Identified Inhibitors of Trypanothione Reductase of Leishmania Parasite

PubMed Central

Venkatesan, Santhosh K.; Dubey, Vikash Kumar

2012-01-01

Structure-based virtual screening of NCI Diversity set II compounds was performed to indentify novel inhibitor scaffolds of trypanothione reductase (TR) from Leishmania infantum. The top 50 ranked hits were clustered using the AuPoSOM tool. Majority of the top-ranked compounds were Tricyclic. Clustering of hits yielded four major clusters each comprising varying number of subclusters differing in their mode of binding and orientation in the active site. Moreover, for the first time, we report selected alkaloids and dibenzothiazepines as inhibitors of Leishmania infantum TR. The mode of binding observed among the clusters also potentiates the probable in vitro inhibition kinetics and aids in defining key interaction which might contribute to the inhibition of enzymatic reduction of T[S] 2. The method provides scope for automation and integration into the virtual screening process employing docking softwares, for clustering the small molecule inhibitors based upon protein-ligand interactions. PMID:22550471

Sulfonylureas and Glinides as New PPARγ Agonists:. Virtual Screening and Biological Assays

NASA Astrophysics Data System (ADS)

Scarsi, Marco; Podvinec, Michael; Roth, Adrian; Hug, Hubert; Kersten, Sander; Albrecht, Hugo; Schwede, Torsten; Meyer, Urs A.; Rücker, Christoph

2007-12-01

This work combines the predictive power of computational drug discovery with experimental validation by means of biological assays. In this way, a new mode of action for type 2 diabetes drugs has been unvealed. Most drugs currently employed in the treatment of type 2 diabetes either target the sulfonylurea receptor stimulating insulin release (sulfonylureas, glinides), or target PPARγ improving insulin resistance (thiazolidinediones). Our work shows that sulfonylureas and glinides bind to PPARγ and exhibit PPARγ agonistic activity. This result was predicted in silico by virtual screening and confirmed in vitro by three biological assays. This dual mode of action of sulfonylureas and glinides may open new perspectives for the molecular pharmacology of antidiabetic drugs, since it provides evidence that drugs can be designed which target both the sulfonylurea receptor and PPARγ. Targeting both receptors could in principle allow to increase pancreatic insulin secretion, as well as to improve insulin resistance.

Identification of novel Trypanosoma cruzi prolyl oligopeptidase inhibitors by structure-based virtual screening

NASA Astrophysics Data System (ADS)

de Almeida, Hugo; Leroux, Vincent; Motta, Flávia Nader; Grellier, Philippe; Maigret, Bernard; Santana, Jaime M.; Bastos, Izabela Marques Dourado

2016-12-01

We have previously demonstrated that the secreted prolyl oligopeptidase of Trypanosoma cruzi (POPTc80) is involved in the infection process by facilitating parasite migration through the extracellular matrix. We have built a 3D structural model where POPTc80 is formed by a catalytic α/β-hydrolase domain and a β-propeller domain, and in which the substrate docks at the inter-domain interface, suggesting a "jaw opening" gating access mechanism. This preliminary model was refined by molecular dynamics simulations and next used for a virtual screening campaign, whose predictions were tested by standard binding assays. This strategy was successful as all 13 tested molecules suggested from the in silico calculations were found out to be active POPTc80 inhibitors in the micromolar range (lowest K i at 667 nM). This work paves the way for future development of innovative drugs against Chagas disease.

Plant Tissues in 3D via X-Ray Tomography: Simple Contrasting Methods Allow High Resolution Imaging

PubMed Central

Staedler, Yannick M.; Masson, David; Schönenberger, Jürg

2013-01-01

Computed tomography remains strongly underused in plant sciences despite its high potential in delivering detailed 3D phenotypical information because of the low X-ray absorption of most plant tissues. Existing protocols to study soft tissues display poor performance, especially when compared to those used on animals. More efficient protocols to study plant material are therefore needed. Flowers of Arabidopsis thaliana and Marcgravia caudata were immersed in a selection of contrasting agents used to treat samples for transmission electron microscopy. Grayscale values for floral tissues and background were measured as a function of time. Contrast was quantified via a contrast index. The thick buds of Marcgravia were scanned to determine which contrasting agents best penetrate thick tissues. The highest contrast increase with cytoplasm-rich tissues was obtained with phosphotungstate, whereas osmium tetroxide and bismuth tatrate displayed the highest contrast increase with vacuolated tissues. Phosphotungstate also displayed the best sample penetration. Furthermore, infiltration with phosphotungstate allowed imaging of all plants parts at a high resolution of 3 µm, which approaches the maximum resolution of our equipment: 1.5 µm. The high affinity of phosphotungstate for vasculature, cytoplasm-rich tissue, and pollen causes these tissues to absorb more X-rays than the surrounding tissues, which, in turn, makes these tissues appear brighter on the scan data. Tissues with different brightness can then be virtually dissected from each other by selecting the bracket of grayscale to be visualized. Promising directions for the future include in silico phenotyping and developmental studies of plant inner parts (e.g., ovules, vasculature, pollen, and cell nuclei) via virtual dissection as well as correlations of quantitative phenotypes with omics datasets. Therefore, this work represents a crucial improvement of previous methods, allowing new directions of research to be undertaken in areas ranging from morphology to systems biology. PMID:24086499

Classification and virtual screening of androgen receptor antagonists.

PubMed

Li, Jiazhong; Gramatica, Paola

2010-05-24

Computational tools, such as quantitative structure-activity relationship (QSAR), are highly useful as screening support for prioritization of substances of very high concern (SVHC). From the practical point of view, QSAR models should be effective to pick out more active rather than inactive compounds, expressed as sensitivity in classification works. This research investigates the classification of a big data set of endocrine-disrupting chemicals (EDCs)-androgen receptor (AR) antagonists, mainly aiming to improve the external sensitivity and to screen for potential AR binders. The kNN, lazy IB1, and ADTree methods and the consensus approach were used to build different models, which improve the sensitivity on external chemicals from 57.1% (literature) to 76.4%. Additionally, the models' predictive abilities were further validated on a blind collected data set (sensitivity: 85.7%). Then the proposed classifiers were used: (i) to distinguish a set of AR binders into antagonists and agonists; (ii) to screen a combined estrogen receptor binder database to find out possible chemicals that can bind to both AR and ER; and (iii) to virtually screen our in-house environmental chemical database. The in silico screening results suggest: (i) that some compounds can affect the normal endocrine system through a complex mechanism binding both to ER and AR; (ii) new EDCs, which are nonER binders, but can in silico bind to AR, are recognized; and (iii) about 20% of compounds in a big data set of environmental chemicals are predicted as new AR antagonists. The priority should be given to them to experimentally test the binding activities with AR.

In silico genotoxicity of coumarins: application of the Phenol-Explorer food database to functional food science.

PubMed

Guardado Yordi, E; Matos, M J; Pérez Martínez, A; Tornes, A C; Santana, L; Molina, E; Uriarte, E

2017-08-01

Coumarins are a group of phytochemicals that may be beneficial or harmful to health depending on their type and dosage and the matrix that contains them. Some of these compounds have been proven to display pro-oxidant and clastogenic activities. Therefore, in the current work, we have studied the coumarins that are present in food sources extracted from the Phenol-Explorer database in order to predict their clastogenic activity and identify the structure-activity relationships and genotoxic structural alerts using alternative methods in the field of computational toxicology. It was necessary to compile information on the type and amount of coumarins in different food sources through the analysis of databases of food composition available online. A virtual screening using a clastogenic model and different software, such as MODESLAB, ChemDraw and STATISTIC, was performed. As a result, a table of food composition was prepared and qualitative information from this data was extracted. The virtual screening showed that the esterified substituents inactivate molecules, while the methoxyl and hydroxyl substituents contribute to their activity and constitute, together with the basic structures of the studied subclasses, clastogenic structural alerts. Chemical subclasses of simple coumarins and furocoumarins were classified as active (xanthotoxin, isopimpinellin, esculin, scopoletin, scopolin and bergapten). In silico genotoxicity was mainly predicted for coumarins found in beer, sherry, dried parsley, fresh parsley and raw celery stalks. The results obtained can be interesting for the future design of functional foods and dietary supplements. These studies constitute a reference for the genotoxic chemoinformatic analysis of bioactive compounds present in databases of food composition.

Evaluation of virtual microscopy in medical histology teaching.

PubMed

Mione, Sylvia; Valcke, Martin; Cornelissen, Maria

2013-01-01

Histology stands as a major discipline in the life science curricula, and the practice of teaching it is based on theoretical didactic strategies along with practical training. Traditionally, students achieve practical competence in this subject by learning optical microscopy. Today, students can use newer information and communication technologies in the study of digital microscopic images. A virtual microscopy program was recently introduced at Ghent University. Since little empirical evidence is available concerning the impact of virtual microscopy (VM) versus optical microscopy (OM) on the acquisition of histology knowledge, this study was set up in the Faculty of Medicine and Health Sciences. A pretest-post test and cross-over design was adopted. In the first phase, the experiment yielded two groups in a total population of 199 students, Group 1 performing the practical sessions with OM versus Group 2 performing the same sessions with VM. In the second phase, the research subjects switched conditions. The prior knowledge level of all research subjects was assessed with a pretest. Knowledge acquisition was measured with a post test after each phase (T1 and T2). Analysis of covariance was carried out to study the differential gain in knowledge at T1 and T2, considering the possible differences in prior knowledge at the start of the study. The results pointed to non-significant differences at T1 and at T2. This supports the assumption that the acquisition of the histology knowledge is independent of the microscopy representation mode (VM versus OM) of the learning material. The conclusion that VM is equivalent to OM offers new directions in view of ongoing innovations in medical education technology. Copyright © 2013 American Association of Anatomists.

25 years of telepathology research: a bibliometric analysis.

PubMed

Della Mea, Vincenzo

2011-03-30

The first appearance of the word "telepathology" in a scientific paper can be tracked down to 1986, in a famous editorial of Ronald Weinstein. Since that paper, research in telepathology grew up developing different subfields, including static and dynamic telepathology and more recently virtual microscopy. The present work attempts an analysis of research in telepathology, starting from the tools provided by bibliometrics. A query has been developed to extract papers related to telepathology and virtual microscopy, and it has been then submitted to Pubmed by means of Entrez Utilities functions. Results obtained in XML have been processed through ad-hoc developed PHP scripts, in order to extract data on Authors, countries, and keywords. On PubMed, 967 papers related to telepathology and virtual microscopy have been retrieved, which involved 2904 Authors; corresponding authors were from 37 countries. Of those authors, 2213 co-authored just one paper. Papers were published on 344 different journals, of which only 52 from the Pathology field. An analysis of papers per year has been also attempted, that demonstrates variable research output in time. From the proposed analysis, telepathology seems to have been consistently studied, in time, by about 400 researchers, with occasional participation of many other people. Telepathology research seems also to have varied in time, although some peaks in paper publishing are certainly related to the proceedings of the European congress on telepathology series, when they have been published on journals. However, some clear sign appears that suggests research in traditional telepathology, after a peak in 2000, showed some decline until virtual microscopy became mainstream, topic that currently pushes research again. The low number of clinical trials calls for more randomized studies in telepathology, to enable evidence-based application.

25 years of telepathology research: a bibliometric analysis

PubMed Central

2011-01-01

Background The first appearance of the word “telepathology” in a scientific paper can be tracked down to 1986, in a famous editorial of Ronald Weinstein. Since that paper, research in telepathology grew up developing different subfields, including static and dynamic telepathology and more recently virtual microscopy. The present work attempts an analysis of research in telepathology, starting from the tools provided by bibliometrics. Methods A query has been developed to extract papers related to telepathology and virtual microscopy, and it has been then submitted to Pubmed by means of Entrez Utilities functions. Results obtained in XML have been processed through ad-hoc developed PHP scripts, in order to extract data on Authors, countries, and keywords. Results On PubMed, 967 papers related to telepathology and virtual microscopy have been retrieved, which involved 2904 Authors; corresponding authors were from 37 countries. Of those authors, 2213 co-authored just one paper. Papers were published on 344 different journals, of which only 52 from the Pathology field. An analysis of papers per year has been also attempted, that demonstrates variable research output in time. Conclusions From the proposed analysis, telepathology seems to have been consistently studied, in time, by about 400 researchers, with occasional participation of many other people. Telepathology research seems also to have varied in time, although some peaks in paper publishing are certainly related to the proceedings of the European congress on telepathology series, when they have been published on journals. However, some clear sign appears that suggests research in traditional telepathology, after a peak in 2000, showed some decline until virtual microscopy became mainstream, topic that currently pushes research again. The low number of clinical trials calls for more randomized studies in telepathology, to enable evidence-based application. PMID:21489197

Multi-MHz laser-scanning single-cell fluorescence microscopy by spatiotemporally encoded virtual source array

PubMed Central

Wu, Jianglai; Tang, Anson H. L.; Mok, Aaron T. Y.; Yan, Wenwei; Chan, Godfrey C. F.; Wong, Kenneth K. Y.; Tsia, Kevin K.

2017-01-01

Apart from the spatial resolution enhancement, scaling of temporal resolution, equivalently the imaging throughput, of fluorescence microscopy is of equal importance in advancing cell biology and clinical diagnostics. Yet, this attribute has mostly been overlooked because of the inherent speed limitation of existing imaging strategies. To address the challenge, we employ an all-optical laser-scanning mechanism, enabled by an array of reconfigurable spatiotemporally-encoded virtual sources, to demonstrate ultrafast fluorescence microscopy at line-scan rate as high as 8 MHz. We show that this technique enables high-throughput single-cell microfluidic fluorescence imaging at 75,000 cells/second and high-speed cellular 2D dynamical imaging at 3,000 frames per second, outperforming the state-of-the-art high-speed cameras and the gold-standard laser scanning strategies. Together with its wide compatibility to the existing imaging modalities, this technology could empower new forms of high-throughput and high-speed biological fluorescence microscopy that was once challenged. PMID:28966855

Comprehensive predictions of target proteins based on protein-chemical interaction using virtual screening and experimental verifications.

PubMed

Kobayashi, Hiroki; Harada, Hiroko; Nakamura, Masaomi; Futamura, Yushi; Ito, Akihiro; Yoshida, Minoru; Iemura, Shun-Ichiro; Shin-Ya, Kazuo; Doi, Takayuki; Takahashi, Takashi; Natsume, Tohru; Imoto, Masaya; Sakakibara, Yasubumi

2012-04-05

Identification of the target proteins of bioactive compounds is critical for elucidating the mode of action; however, target identification has been difficult in general, mostly due to the low sensitivity of detection using affinity chromatography followed by CBB staining and MS/MS analysis. We applied our protocol of predicting target proteins combining in silico screening and experimental verification for incednine, which inhibits the anti-apoptotic function of Bcl-xL by an unknown mechanism. One hundred eighty-two target protein candidates were computationally predicted to bind to incednine by the statistical prediction method, and the predictions were verified by in vitro binding of incednine to seven proteins, whose expression can be confirmed in our cell system.As a result, 40% accuracy of the computational predictions was achieved successfully, and we newly found 3 incednine-binding proteins. This study revealed that our proposed protocol of predicting target protein combining in silico screening and experimental verification is useful, and provides new insight into a strategy for identifying target proteins of small molecules.

Computational modeling of psychiatric illnesses via well-defined neurophysiological and neurocognitive biomarkers.

PubMed

Siekmeier, Peter J

2015-10-01

A good deal of recent research has centered on the identification of biomarkers and endophenotypic measures of psychiatric illnesses using in vivo and in vitro studies. This is understandable, as these measures-as opposed to complex clinical phenotypes-may be more closely related to neurobiological and genetic vulnerabilities. However, instantiation of such biomarkers using computational models-in silico studies-has received less attention. This approach could become increasingly important, given the wealth of detailed information produced by recent basic neuroscience research, and increasing availability of high capacity computing platforms. The purpose of this review is to survey the current state of the art of research in this area. We discuss computational approaches to schizophrenia, bipolar disorder, Alzheimer's disease, fragile X syndrome and autism, and argue that it represents a promising and underappreciated research modality. In conclusion, we outline specific avenues for future research; also, potential uses of in silico models to conduct "virtual experiments" and to generate novel hypotheses, and as an aid in neuropsychiatric drug development are discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Targeting Dengue Virus NS-3 Helicase by Ligand based Pharmacophore Modeling and Structure based Virtual Screening

NASA Astrophysics Data System (ADS)

Halim, Sobia A.; Khan, Shanza; Khan, Ajmal; Wadood, Abdul; Mabood, Fazal; Hussain, Javid; Al-Harrasi, Ahmed

2017-10-01

Dengue fever is an emerging public health concern, with several million viral infections occur annually, for which no effective therapy currently exist. Non-structural protein 3 (NS-3) Helicase encoded by the dengue virus (DENV) is considered as a potential drug target to design new and effective drugs against dengue. Helicase is involved in unwinding of dengue RNA. This study was conducted to design new NS-3 Helicase inhibitor by in silico ligand- and structure based approaches. Initially ligand-based pharmacophore model was generated that was used to screen a set of 1201474 compounds collected from ZINC Database. The compounds matched with the pharmacophore model were docked into the active site of NS-3 helicase. Based on docking scores and binding interactions, twenty five compounds are suggested to be potential inhibitors of NS3 Helicase. The pharmacokinetic properties of these hits were predicted. The selected hits revealed acceptable ADMET properties. This study identified potential inhibitors of NS-3 Helicase in silico, and can be helpful in the treatment of Dengue.

Discovery of novel Trypanosoma brucei phosphodiesterase B1 inhibitors by virtual screening against the unliganded TbrPDEB1 crystal structure

PubMed Central

Jansen, Chimed; Wang, Huanchen; Kooistra, Albert J.; de Graaf, Chris; Orrling, Kristina; Tenor, Hermann; Seebeck, Thomas; Bailey, David; de Esch, Iwan J.P.; Ke, Hengming; Leurs, Rob

2013-01-01

Trypanosoma brucei cyclic nucleotide phosphodiesterase B1 (TbrPDEB1) and TbrPDEB2 have recently been validated as new therapeutic targets for human African Trypanosomiasis by both genetic and pharmacological means. In this study we report the crystal structure of the catalytic domain of the unliganded TbrPDEB1 and its use for the in silico screening for new TbrPDEB1 inhibitors with novel scaffolds. The TbrPDEB1 crystal structure shows the characteristic folds of human PDE enzymes, but also contains the parasite-specific P-pocket found in the structures of Leishmania major PDEB1 and Trypanosoma cruzi PDEC. The unliganded TbrPDEB1 X-ray structure was subjected to a structure-based in silico screening approach that combines molecular docking simulations with a protein-ligand interaction fingerprint (IFP) scoring method. This approach identified, six novel TbrPDEB1 inhibitors with IC50 values of 10–80 μM, which may be further optimized as potential selective TbrPDEB inhibitors. PMID:23409953

IspE Inhibitors Identified by a Combination of In Silico and In Vitro High-Throughput Screening

PubMed Central

Tidten-Luksch, Naomi; Grimaldi, Raffaella; Torrie, Leah S.; Frearson, Julie A.; Hunter, William N.; Brenk, Ruth

2012-01-01

CDP-ME kinase (IspE) contributes to the non-mevalonate or deoxy-xylulose phosphate (DOXP) pathway for isoprenoid precursor biosynthesis found in many species of bacteria and apicomplexan parasites. IspE has been shown to be essential by genetic methods and since it is absent from humans it constitutes a promising target for antimicrobial drug development. Using in silico screening directed against the substrate binding site and in vitro high-throughput screening directed against both, the substrate and co-factor binding sites, non-substrate-like IspE inhibitors have been discovered and structure-activity relationships were derived. The best inhibitors in each series have high ligand efficiencies and favourable physico-chemical properties rendering them promising starting points for drug discovery. Putative binding modes of the ligands were suggested which are consistent with established structure-activity relationships. The applied screening methods were complementary in discovering hit compounds, and a comparison of both approaches highlights their strengths and weaknesses. It is noteworthy that compounds identified by virtual screening methods provided the controls for the biochemical screens. PMID:22563402

MAMMALIAN APOPTOSIS IN WHOLE NEONATAL OVARIES, EMBRYOS AND FETAL LIMBS USING CONFOCAL MICROSCOPY

EPA Science Inventory

The emergence of confocal laser scanning microscopy (CLSM) as a technique capable of optically generating serial sections of whole-mount tissue and then reassembling the computer-stored images as a virtual 3-dimensional structure offers a viable alternative to traditional section...

Evaluation of Virtual Microscopy in Medical Histology Teaching

ERIC Educational Resources Information Center

Mione, Sylvia; Valcke, Martin; Cornelissen, Maria

2013-01-01

Histology stands as a major discipline in the life science curricula, and the practice of teaching it is based on theoretical didactic strategies along with practical training. Traditionally, students achieve practical competence in this subject by learning optical microscopy. Today, students can use newer information and communication…

Confocal microscopy studies of morphology and apoptosis: ovaries, limbs, embryos and insects

EPA Science Inventory

Confocal laser scanning microscopy (CLSM) is a technique that is capable of generating serial sections of whole-mount tissue and then reassembling the computer-stored images as a virtual 3-dimensional structure. In many ways CLSM offers an alternative to traditional sectioning ap...

Confocal microscopy of thick tissue sections: 3D visualizaiton of rat kidney glomeruli

EPA Science Inventory

Confocal laser scanning microscopy (CLSM) as a technique capable of generating serial sections of whole-mount tissue and then reassembling the computer-acquired images as a virtual 3-dimentional structure. In many ways CLSM offers an alternative to traditional sectioning approac...

Confocal Microscopy of thick tissue sections: 3D Visualization of rat kidney glomeruli

EPA Science Inventory

Confocal laser scanning microscopy (CLSM) as a technique capable of generating serial sections of whole-mount tissue and then reassembling the computer-acquired images as a virtual 3-dimentional structure. In many ways CLSM offers an alternative to traditional sectioning approac...

In silico methods in the discovery of endocrine disrupting chemicals.

PubMed

Vuorinen, Anna; Odermatt, Alex; Schuster, Daniela

2013-09-01

The prevalence of sex hormone-dependent cancers, reproductive problems, obesity, and cardiovascular complications has risen especially in the Western world. It has been suggested, that the exposure to various endocrine disrupting chemicals (EDCs) contributes to the development and progression of these diseases. EDCs can interfere with various proteins: nuclear steroid hormone receptors, such as estrogen-, androgen-, glucocorticoid- and mineralocorticoid receptors (ER, AR, GR, MR), and enzymes that are involved in steroid hormone synthesis and metabolism, for example hydroxysteroid dehydrogenases (HSDs). Numerous chemicals are known as endocrine disruptors. However, the mechanism of action for most of these EDCs is still unknown. It is exhaustive and time consuming to test in vitro all chemicals - potential EDCs - used in industry, agriculture or as food preservatives against their effects on the endocrine system. Computational methods, such as virtual screening, quantitative structure activity relationships and docking, are already well recognized and used in drug development. The same methods could also aid the research on EDCs. So far, the computational methods in the search of EDCs have been retrospective. There are, however, some prospective studies reporting the use of in silico methods: five studies reporting the identification of previously unknown 17β-HSD3 inhibitors, MR agonists, and ER antagonists/agonists. This review provides an overview of case studies and in silico methods that are used in the search of EDCs. This article is part of a Special Issue entitled 'CSR 2013'. Copyright © 2013 Elsevier Ltd. All rights reserved.

Reprint of "In silico methods in the discovery of endocrine disrupting chemicals".

PubMed

Vuorinen, Anna; Odermatt, Alex; Schuster, Daniela

2015-09-01

The prevalence of sex hormone-dependent cancers, reproductive problems, obesity, and cardiovascular complications has risen especially in the Western world. It has been suggested, that the exposure to various endocrine disrupting chemicals (EDCs) contributes to the development and progression of these diseases. EDCs can interfere with various proteins: nuclear steroid hormone receptors, such as estrogen-, androgen-, glucocorticoid- and mineralocorticoid receptors (ER, AR, GR, MR), and enzymes that are involved in steroid hormone synthesis and metabolism, for example hydroxysteroid dehydrogenases (HSDs). Numerous chemicals are known as endocrine disruptors. However, the mechanism of action for most of these EDCs is still unknown. It is exhaustive and time consuming to test in vitro all chemicals - potential EDCs - used in industry, agriculture or as food preservatives against their effects on the endocrine system. Computational methods, such as virtual screening, quantitative structure activity relationships and docking, are already well recognized and used in drug development. The same methods could also aid the research on EDCs. So far, the computational methods in the search of EDCs have been retrospective. There are, however, some prospective studies reporting the use of in silico methods: five studies reporting the identification of previously unknown 17β-HSD3 inhibitors, MR agonists, and ER antagonists/agonists. This review provides an overview of case studies and in silico methods that are used in the search of EDCs. This article is part of a Special Issue entitled 'CSR 2013'. Copyright © 2015 Elsevier Ltd. All rights reserved.

Computational discovery of putative quorum sensing inhibitors against LasR and RhlR receptor proteins of Pseudomonas aeruginosa

NASA Astrophysics Data System (ADS)

Annapoorani, Angusamy; Umamageswaran, Venugopal; Parameswari, Radhakrishnan; Pandian, Shunmugiah Karutha; Ravi, Arumugam Veera

2012-09-01

Drugs have been discovered in the past mainly either by identification of active components from traditional remedies or by unpredicted discovery. A key motivation for the study of structure based virtual screening is the exploitation of such information to design targeted drugs. In this study, structure based virtual screening was used in search for putative quorum sensing inhibitors (QSI) of Pseudomonas aeruginosa. The virtual screening programme Glide version 5.5 was applied to screen 1,920 natural compounds/drugs against LasR and RhlR receptor proteins of P. aeruginosa. Based on the results of in silico docking analysis, five top ranking compounds namely rosmarinic acid, naringin, chlorogenic acid, morin and mangiferin were subjected to in vitro bioassays against laboratory strain PAO1 and two more antibiotic resistant clinical isolates, P. aeruginosa AS1 (GU447237) and P. aeruginosa AS2 (GU447238). Among the five compounds studied, except mangiferin other four compounds showed significant inhibition in the production of protease, elastase and hemolysin. Further, all the five compounds potentially inhibited the biofilm related behaviours. This interaction study provided promising ligands to inhibit the quorum sensing (QS) mediated virulence factors production in P. aeruginosa.

Vitual screening and binding mode elucidation of curcumin analogues on Cyclooxygenase-2 using AYO_COX2_V1.1 protocol

NASA Astrophysics Data System (ADS)

Mulatsari, E.; Mumpuni, E.; Herfian, A.

2017-05-01

Curcumin is yellow colored phenolic compounds contained in Curcuma longa. Curcumin is known to have biological activities as anti-inflammatory, antiviral, antioxidant, and anti-infective agent [1]. Synthesis of curcumin analogue compounds has been done and some of them had biological activity like curcumin. In this research, the virtual screening of curcumin analogue compounds has been conducted. The purpose of this research was to determine the activity of these compounds as selective Cyclooxygenase-2inhibitors in in-silico. Binding mode elucidation was made by active and inactive representative compounds to see the interaction of the amino acids in the binding site of the compounds. This research used AYO_COX2_V.1.1, a structure-based virtual screening protocol (SBVS) that has been validated by Mumpuni E et al, 2014 [2]. AYO_COX2_V.1.1 protocol using a variety of integrated applications such as SPORES, PLANTS, BKchem, OpenBabel and PyMOL. The results of virtual screening conducted on 49 curcumin analogue compounds obtained 8 compounds with 4 active amino acid residues (GLY340, ILE503, PHE343, and PHE367) that were considered active as COX-2 inhibitor.

Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

PubMed Central

Moss, Robert; Grosse, Thibault; Marchant, Ivanny; Lassau, Nathalie; Gueyffier, François; Thomas, S. Randall

2012-01-01

Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models. PMID:22761561

Omics approaches to individual variation: modeling networks and the virtual patient.

PubMed

Lehrach, Hans

2016-09-01

Every human is unique. We differ in our genomes, environment, behavior, disease history, and past and current medical treatment-a complex catalog of differences that often leads to variations in the way each of us responds to a particular therapy. We argue here that true personalization of drug therapies will rely on "virtual patient" models based on a detailed characterization of the individual patient by molecular, imaging, and sensor techniques. The models will be based, wherever possible, on the molecular mechanisms of disease processes and drug action but can also expand to hybrid models including statistics/machine learning/artificial intelligence-based elements trained on available data to address therapeutic areas or therapies for which insufficient information on mechanisms is available. Depending on the disease, its mechanisms, and the therapy, virtual patient models can be implemented at a fairly high level of abstraction, with molecular models representing cells, cell types, or organs relevant to the clinical question, interacting not only with each other but also the environment. In the future, "virtual patient/in-silico self" models may not only become a central element of our health care system, reducing otherwise unavoidable mistakes and unnecessary costs, but also act as "guardian angels" accompanying us through life to protect us against dangers and to help us to deal intelligently with our own health and wellness.

Omics approaches to individual variation: modeling networks and the virtual patient

PubMed Central

Lehrach, Hans

2016-01-01

Every human is unique. We differ in our genomes, environment, behavior, disease history, and past and current medical treatment—a complex catalog of differences that often leads to variations in the way each of us responds to a particular therapy. We argue here that true personalization of drug therapies will rely on “virtual patient” models based on a detailed characterization of the individual patient by molecular, imaging, and sensor techniques. The models will be based, wherever possible, on the molecular mechanisms of disease processes and drug action but can also expand to hybrid models including statistics/machine learning/artificial intelligence-based elements trained on available data to address therapeutic areas or therapies for which insufficient information on mechanisms is available. Depending on the disease, its mechanisms, and the therapy, virtual patient models can be implemented at a fairly high level of abstraction, with molecular models representing cells, cell types, or organs relevant to the clinical question, interacting not only with each other but also the environment. In the future, “virtual patient/in-silico self” models may not only become a central element of our health care system, reducing otherwise unavoidable mistakes and unnecessary costs, but also act as “guardian angels” accompanying us through life to protect us against dangers and to help us to deal intelligently with our own health and wellness. PMID:27757060

Large-scale virtual screening on public cloud resources with Apache Spark.

PubMed

Capuccini, Marco; Ahmed, Laeeq; Schaal, Wesley; Laure, Erwin; Spjuth, Ola

2017-01-01

Structure-based virtual screening is an in-silico method to screen a target receptor against a virtual molecular library. Applying docking-based screening to large molecular libraries can be computationally expensive, however it constitutes a trivially parallelizable task. Most of the available parallel implementations are based on message passing interface, relying on low failure rate hardware and fast network connection. Google's MapReduce revolutionized large-scale analysis, enabling the processing of massive datasets on commodity hardware and cloud resources, providing transparent scalability and fault tolerance at the software level. Open source implementations of MapReduce include Apache Hadoop and the more recent Apache Spark. We developed a method to run existing docking-based screening software on distributed cloud resources, utilizing the MapReduce approach. We benchmarked our method, which is implemented in Apache Spark, docking a publicly available target receptor against [Formula: see text]2.2 M compounds. The performance experiments show a good parallel efficiency (87%) when running in a public cloud environment. Our method enables parallel Structure-based virtual screening on public cloud resources or commodity computer clusters. The degree of scalability that we achieve allows for trying out our method on relatively small libraries first and then to scale to larger libraries. Our implementation is named Spark-VS and it is freely available as open source from GitHub (https://github.com/mcapuccini/spark-vs).Graphical abstract.

Development of Drugs for Epstein - Barr virus using High-Throughput in silico Virtual Screening

PubMed Central

Li, Ning; Thompson, Scott; Jiang, Hualiang; Lieberman, Paul M.; Luo, Cheng

2010-01-01

Importance of the field Epstein-Barr virus (EBV) is a ubiquitious human herpesvirus that is causally associated with endemic forms of Burkitt’s lymphoma (BL), nasopharyngeal carcinoma, and lymphoproliferative disease in immunosuppressed individuals. On a global scale, EBV infects over 90% of the adult population and is responsible for ~1% of all human cancers. To date, there is no efficacious drug or therapy for the treatment of EBV infection and EBV-related diseases. Areas covered in this review In this review, we discuss the existing anti-EBV inhibitors and those under development. We discuss the value of different molecular targets, including EBV lytic DNA replication enzymes, as well as proteins that are expressed exclusively during latent infection, like EBNA1 and LMP1. Since the atomic structure of the EBNA1 DNA binding domain has been described, it is an attractive target for in silico methods of drug design and small molecule screening. We discuss the use of computational methods that can greatly facilitate the development of novel inhibitors and how in silico screening methods can be applied to target proteins with known structures, like EBNA1, to treat EBV infection and disease. What the reader will gain The reader will be familiarized with the problems in targeting of EBV for inhibition by small molecules and how computational methods can greatly facilitate this process. Take home message Despite the impressive efficacy of nucleoside analogues for the treatment of herpesvirus lytic infection, there remain few effective treatments for latent infections. Since EBV-latent infection persists within and contributes to the formation of EBV-associated cancers, targeting EBV latent proteins is an unmet medical need. High throughput in silico screening can accelerate the process of drug discovery for novel and selective agents that inhibit EBV latent infection and associated disease. PMID:22822721

Rational design of small-molecule stabilizers of spermine synthase dimer by virtual screening and free energy-based approach.

PubMed

Zhang, Zhe; Martiny, Virginie; Lagorce, David; Ikeguchi, Yoshihiko; Alexov, Emil; Miteva, Maria A

2014-01-01

Snyder-Robinson Syndrome (SRS) is a rare mental retardation disorder which is caused by the malfunctioning of an enzyme, the spermine synthase (SMS), which functions as a homo-dimer. The malfunctioning of SMS in SRS patients is associated with several identified missense mutations that occur away from the active site. This investigation deals with a particular SRS-causing mutation, the G56S mutation, which was shown computationally and experimentally to destabilize the SMS homo-dimer and thus to abolish SMS enzymatic activity. As a proof-of-concept, we explore the possibility to restore the enzymatic activity of the malfunctioning SMS mutant G56S by stabilizing the dimer through small molecule binding at the mutant homo-dimer interface. For this purpose, we designed an in silico protocol that couples virtual screening and a free binding energy-based approach to identify potential small-molecule binders on the destabilized G56S dimer, with the goal to stabilize it and thus to increase SMS G56S mutant activity. The protocol resulted in extensive list of plausible stabilizers, among which we selected and tested 51 compounds experimentally for their capability to increase SMS G56S mutant enzymatic activity. In silico analysis of the experimentally identified stabilizers suggested five distinctive chemical scaffolds. This investigation suggests that druggable pockets exist in the vicinity of the mutation sites at protein-protein interfaces which can be used to alter the disease-causing effects by small molecule binding. The identified chemical scaffolds are drug-like and can serve as original starting points for development of lead molecules to further rescue the disease-causing effects of the Snyder-Robinson syndrome for which no efficient treatment exists up to now.

Electrophysiological Rotor Ablation in In-Silico Modeling of Atrial Fibrillation: Comparisons with Dominant Frequency, Shannon Entropy, and Phase Singularity.

PubMed

Hwang, Minki; Song, Jun-Seop; Lee, Young-Seon; Li, Changyong; Shim, Eun Bo; Pak, Hui-Nam

2016-01-01

Although rotors have been considered among the drivers of atrial fibrillation (AF), the rotor definition is inconsistent. We evaluated the nature of rotors in 2D and 3D in- silico models of persistent AF (PeAF) by analyzing phase singularity (PS), dominant frequency (DF), Shannon entropy (ShEn), and complex fractionated atrial electrogram cycle length (CFAE-CL) and their ablation. Mother rotor was spatiotemporally defined as stationary reentries with a meandering tip remaining within half the wavelength and lasting longer than 5 s. We generated 2D- and 3D-maps of the PS, DF, ShEn, and CFAE-CL during AF. The spatial correlations and ablation outcomes targeting each parameter were analyzed. 1. In the 2D PeAF model, we observed a mother rotor that matched relatively well with DF (>9 Hz, 71.0%, p<0.001), ShEn (upper 2.5%, 33.2%, p<0.001), and CFAE-CL (lower 2.5%, 23.7%, p<0.001). 2. The 3D-PeAF model also showed mother rotors that had spatial correlations with DF (>5.5 Hz, 39.7%, p<0.001), ShEn (upper 8.5%, 15.1%, p <0.001), and CFAE (lower 8.5%, 8.0%, p = 0.002). 3. In both the 2D and 3D models, virtual ablation targeting the upper 5% of the DF terminated AF within 20 s, but not the ablations based on long-lasting PS, high ShEn area, or lower CFAE-CL area. Mother rotors were observed in both 2D and 3D human AF models. Rotor locations were well represented by DF, and their virtual ablation altered wave dynamics and terminated AF.

Electrophysiological Rotor Ablation in In-Silico Modeling of Atrial Fibrillation: Comparisons with Dominant Frequency, Shannon Entropy, and Phase Singularity

PubMed Central

Hwang, Minki; Song, Jun-Seop; Lee, Young-Seon; Li, Changyong; Shim, Eun Bo; Pak, Hui-Nam

2016-01-01

Background Although rotors have been considered among the drivers of atrial fibrillation (AF), the rotor definition is inconsistent. We evaluated the nature of rotors in 2D and 3D in- silico models of persistent AF (PeAF) by analyzing phase singularity (PS), dominant frequency (DF), Shannon entropy (ShEn), and complex fractionated atrial electrogram cycle length (CFAE-CL) and their ablation. Methods Mother rotor was spatiotemporally defined as stationary reentries with a meandering tip remaining within half the wavelength and lasting longer than 5 s. We generated 2D- and 3D-maps of the PS, DF, ShEn, and CFAE-CL during AF. The spatial correlations and ablation outcomes targeting each parameter were analyzed. Results 1. In the 2D PeAF model, we observed a mother rotor that matched relatively well with DF (>9 Hz, 71.0%, p<0.001), ShEn (upper 2.5%, 33.2%, p<0.001), and CFAE-CL (lower 2.5%, 23.7%, p<0.001). 2. The 3D-PeAF model also showed mother rotors that had spatial correlations with DF (>5.5 Hz, 39.7%, p<0.001), ShEn (upper 8.5%, 15.1%, p <0.001), and CFAE (lower 8.5%, 8.0%, p = 0.002). 3. In both the 2D and 3D models, virtual ablation targeting the upper 5% of the DF terminated AF within 20 s, but not the ablations based on long-lasting PS, high ShEn area, or lower CFAE-CL area. Conclusion Mother rotors were observed in both 2D and 3D human AF models. Rotor locations were well represented by DF, and their virtual ablation altered wave dynamics and terminated AF. PMID:26909492

Virtual High-Throughput Screening To Identify Novel Activin Antagonists

PubMed Central

Zhu, Jie; Mishra, Rama K.; Schiltz, Gary E.; Makanji, Yogeshwar; Scheidt, Karl A.; Mazar, Andrew P.; Woodruff, Teresa K.

2015-01-01

Activin belongs to the TGFβ superfamily, which is associated with several disease conditions, including cancer-related cachexia, preterm labor with delivery, and osteoporosis. Targeting activin and its related signaling pathways holds promise as a therapeutic approach to these diseases. A small-molecule ligand-binding groove was identified in the interface between the two activin βA subunits and was used for a virtual high-throughput in silico screening of the ZINC database to identify hits. Thirty-nine compounds without significant toxicity were tested in two well-established activin assays: FSHβ transcription and HepG2 cell apoptosis. This screening workflow resulted in two lead compounds: NUCC-474 and NUCC-555. These potential activin antagonists were then shown to inhibit activin A-mediated cell proliferation in ex vivo ovary cultures. In vivo testing showed that our most potent compound (NUCC-555) caused a dose-dependent decrease in FSH levels in ovariectomized mice. The Blitz competition binding assay confirmed target binding of NUCC-555 to the activin A:ActRII that disrupts the activin A:ActRII complex’s binding with ALK4-ECD-Fc in a dose-dependent manner. The NUCC-555 also specifically binds to activin A compared with other TGFβ superfamily member myostatin (GDF8). These data demonstrate a new in silico-based strategy for identifying small-molecule activin antagonists. Our approach is the first to identify a first-in-class small-molecule antagonist of activin binding to ALK4, which opens a completely new approach to inhibiting the activity of TGFβ receptor superfamily members. in addition, the lead compound can serve as a starting point for lead optimization toward the goal of a compound that may be effective in activin-mediated diseases. PMID:26098096

Rational Drug Discovery of HCV Helicase Inhibitor: Improved Docking Accuracy with Multiple Seeding in AutoDock Vina and In Situ Minimization.

PubMed

Lim, See K; Othman, Rozana; Yusof, Rohana; Heh, Choon H

2017-01-01

Hepatitis C is a significant cause for end-stage liver diseases and liver transplantation which affects approximately 3% of the global populations. Despite the current several direct antiviral agents in the treatment of Hepatitis C, the standard treatment for HCV infection is accompanied by several drawbacks, such as adverse side effects, high pricing of medications and the rapid emerging rate of resistant HCV variants. To discover potential inhibitors for HCV helicase through an optimized in silico approach. In this study, a homology model (HCV Genotype 3 helicase) was used as the target and screened through a benzopyran-based virtual library. Multiple-seedings of AutoDock Vina and in situ minimization were to account for the non-deterministic nature of AutoDock Vina search algorithm and binding site flexibility, respectively. ADME/T and interaction analyses were also done on the top hits via FAFDRUG3 web server and Discovery Studio 4.5. This study involved the development of an improved flow for virtual screening via implemention of multiple-seeding screening approach and in situ minimization. With the new docking protocol, the redocked standards have shown better RMSD value in reference to their native conformations. Ten benzopyran-like compounds with satisfactory physicochemical properties were discovered to be potential inhibitors of HCV helicase. ZINC38649350 was identified as the most potential inhibitor. Ten potential HCV helicase inhibitors were discovered via a new docking optimization protocol with better docking accuracy. These findings could contribute to the discovery of novel HCV antivirals and serve as an alternative approach of in silico rational drug discovery. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Web-Based Virtual Microscopy for Parasitology: A Novel Tool for Education and Quality Assurance

PubMed Central

Linder, Ewert; Lundin, Mikael; Thors, Cecilia; Lebbad, Marianne; Winiecka-Krusnell, Jadwiga; Helin, Heikki; Leiva, Byron; Isola, Jorma; Lundin, Johan

2008-01-01

Background The basis for correctly assessing the burden of parasitic infections and the effects of interventions relies on a somewhat shaky foundation as long as we do not know how reliable the reported laboratory findings are. Thus virtual microscopy, successfully introduced as a histopathology tool, has been adapted for medical parasitology. Methodology/Principal Findings Specimens containing parasites in tissues, stools, and blood have been digitized and made accessible as a “webmicroscope for parasitology” (WMP) on the Internet (http://www.webmicroscope.net/parasitology).These digitized specimens can be viewed (“navigated” both in the x-axis and the y-axis) at the desired magnification by an unrestricted number of individuals simultaneously. For virtual microscopy of specimens containing stool parasites, it was necessary to develop the technique further in order to enable navigation in the z plane (i.e., “focusing”). Specimens were therefore scanned and photographed in two or more focal planes. The resulting digitized specimens consist of stacks of laterally “stiched” individual images covering the entire area of the sample photographed at high magnification. The digitized image information (∼10 GB uncompressed data per specimen) is accessible at data transfer speeds from 2 to 10 Mb/s via a network of five image servers located in different parts of Europe. Image streaming and rapid data transfer to an ordinary personal computer makes web-based virtual microscopy similar to conventional microscopy. Conclusion/Significance The potential of this novel technique in the field of medical parasitology to share identical parasitological specimens means that we can provide a “gold standard”, which can overcome several problems encountered in quality control of diagnostic parasitology. Thus, the WMP may have an impact on the reliability of data, which constitute the basis for our understanding of the vast problem of neglected tropical diseases. The WMP can be used also in the absence of a fast Internet communication. An ordinary PC, or even a laptop, may function as a local image server, e.g., in health centers in tropical endemic areas. PMID:18941514

Physically-based in silico light sheet microscopy for visualizing fluorescent brain models

PubMed Central

2015-01-01

Background We present a physically-based computational model of the light sheet fluorescence microscope (LSFM). Based on Monte Carlo ray tracing and geometric optics, our method simulates the operational aspects and image formation process of the LSFM. This simulated, in silico LSFM creates synthetic images of digital fluorescent specimens that can resemble those generated by a real LSFM, as opposed to established visualization methods producing visually-plausible images. We also propose an accurate fluorescence rendering model which takes into account the intrinsic characteristics of fluorescent dyes to simulate the light interaction with fluorescent biological specimen. Results We demonstrate first results of our visualization pipeline to a simplified brain tissue model reconstructed from the somatosensory cortex of a young rat. The modeling aspects of the LSFM units are qualitatively analysed, and the results of the fluorescence model were quantitatively validated against the fluorescence brightness equation and characteristic emission spectra of different fluorescent dyes. AMS subject classification Modelling and simulation PMID:26329404

G12V Kras mutations in cervical cancer under virtual microscope of molecular dynamics simulations.

PubMed

Chen, X P; Xu, W H; Xu, D F; Fu, S M; Ma, Z C

2016-01-01

Kras mutations and cancers are common and their role in the progression of cancer is well known and elucidated. The present work is searching for the most deleterious mutation of the four found at codon 12 and 13 of Kras in cervical cancers using prediction servers; different servers were used to look into different factors that govern the protein function. The in silico results predicted G12V to be the most devastating; this particular mutation was then subjected to molecular dynamics simulation (MDS) for further analysis. The authors' approach of MDSs helped them to place the native and mutant structure under virtual microscope and observe their dynamics over time. The results generated are enlightening the effect of G12V variation on the dynamics of Kras. The structural variation between the native and mutant Kras over 50 nanoseconds (ns) run varied at every parameter checked and the results are in excellent agreement with the available experimental data.

Rational Design of a New Class of Toll-Like Receptor 4 (TLR4) Tryptamine Related Agonists by Means of the Structure- and Ligand-Based Virtual Screening for Vaccine Adjuvant Discovery.

PubMed

Honegr, Jan; Dolezal, Rafael; Malinak, David; Benkova, Marketa; Soukup, Ondrej; Almeida, Joyce S F D de; Franca, Tanos C C; Kuca, Kamil; Prymula, Roman

2018-01-04

In order to identify novel lead structures for human toll-like receptor 4 ( h TLR4) modulation virtual high throughput screening by a peta-flops-scale supercomputer has been performed. Based on the in silico studies, a series of 12 compounds related to tryptamine was rationally designed to retain suitable molecular geometry for interaction with the h TLR4 binding site as well as to satisfy general principles of drug-likeness. The proposed compounds were synthesized, and tested by in vitro and ex vivo experiments, which revealed that several of them are capable to stimulate h TLR4 in vitro up to 25% activity of Monophosphoryl lipid A. The specific affinity of the in vitro most potent substance was confirmed by surface plasmon resonance direct-binding experiments. Moreover, two compounds from the series show also significant ability to elicit production of interleukin 6.

Selection of G1-PABA as a GPER1 ligand compared to phenol red via a ligand-based virtual screening coupled to molecular dynamics simulations and its anti-proliferative effects on breast cancer cells.

PubMed

Jose, Correa-Basurto; Trujillo-Ferrara, Jose G; Irene, Mendoza-Lujambio; Alfonso, Duenas-Gonzalez; Alma, Chavez-Blanco; Marlet, Martinez-Archundia; Bello, M; Ruben, Garcia Sanchez Jose; Jonathan, Fragoso-Vazquez Manuel; David, Mendez-Luna; Berenice, Prestegui-Martel; Alberto, Martinez-Munoz

2018-05-10

Recent reports have demonstrated the role of the G protein-coupled estrogen receptor (GPER1) on the growth and proliferation of breast cancer cells. The coupling of GPER1 to estrogen, tamoxifen or fulvestrant triggers cellular signaling pathways (PI3K and ERK) related to cell proliferation. In an effort to develop new therapeutic strategies against breast cancer, we performed an in silico study to explore the binding pose of a set of designed G15 and G1 analogue compounds, including phenol red. First, we included a carboxyl group instead of the acetyl group from G1 to form amides with several moieties to increase the affinity for GPER1. Then, all the target compounds were submitted to an in silico ADMET study. Then, the ligands were coupled to GPER1 using ligand-based virtual screening to finally achieve molecular dynamics simulations of the best molecule on GPER1, as well as of phenol red, to explore its recognition properties. According to the in silico ADMET and docking studies, the best molecule was named G1-PABA ((3aS,4R,9bR)-4-(6-bromobenzo[d][1,3]dioxol-5-yl)-3a,4,5,9b-tetrahydro-3H-cyclopenta[c]quinoline-8-carboxylic acid). It was synthesized and assayed in vitro in breast cancer (MCF-7 and MDA-MB-231) and normal (MCF-10A) cell lines. Experimental assays showed that the target compound was able to decrease cell proliferation, showing IC50 values of 15.93 M, 52.92 M and 32.45 M in the MCF-7, MDA-MB-231 and MCF-10A cell lines, respectively, after 72 h of treatment. Interestingly, the target compound showed better IC50 values without phenol red, suggesting that phenol red could interfere with the G1-PABA action at GPER, which is present in MCF-7 cells according to PCR studies and explains the cell proliferation effects. In conclusion, a concentration-dependent inhibition of cell proliferation occurred with G1-PABA in the assayed cell lines and could be due to its action on GPER1. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Virtual taphonomy using synchrotron tomographic microscopy reveals cryptic features and internal structure of modern and fossil plants

PubMed Central

Smith, Selena Y.; Collinson, Margaret E.; Rudall, Paula J.; Simpson, David A.; Marone, Federica; Stampanoni, Marco

2009-01-01

While more commonly applied in zoology, synchrotron radiation X-ray tomographic microscopy (SRXTM) is well-suited to nondestructive study of the morphology and anatomy of both fossil and modern plants. SRXTM uses hard X-rays and a monochromatic light source to provide high-resolution data with little beam-hardening, resulting in slice data with clear boundaries between materials. Anatomy is readily visualized, including various planes of section from a single specimen, as clear as in traditional histological sectioning at low magnifications. Thus, digital sectioning of rare or difficult material is possible. Differential X-ray attenuation allows visualization of different layers or chemistries to enable virtual 3-dimensional (3D) dissections of material. Virtual potential fossils can be visualized and digital tissue removal reveals cryptic underlying morphology. This is essential for fossil identification and for comparisons between assemblages where fossils are preserved by different means. SRXTM is a powerful approach for botanical studies using morphology and anatomy. The ability to gain search images in both 2D and 3D for potential fossils gives paleobotanists a tool—virtual taphonomy—to improve our understanding of plant evolution and paleobiogeography. PMID:19574457

Learning from a distance: high school students' perceptions of virtual presence, motivation, and science identity during a remote microscopy investigation

NASA Astrophysics Data System (ADS)

Childers, Gina; Jones, M. Gail

2017-02-01

Through partnerships with scientists, students can now conduct research in science laboratories from a distance through remote access technologies. The purpose of this study was to explore factors that contribute to a remote learning environment by documenting high school students' perceptions of science motivation, science identity, and virtual presence during a remote microscopy investigation. Exploratory factor analysis identified 3 factors accounting for 63% of the variance, which suggests that Science Learning Drive (students' perception of their competence and performance in science and intrinsic motivation to do science), Environmental Presence (students' perception of control of the remote technology, sensory, and distraction factors in the learning environment, and relatedness to scientists), and Inner Realism Presence (students' perceptions of how real is the remote programme and being recognised as a science-oriented individual) were factors that contribute to a student's experience during a remote investigation. Motivation, science identity, and virtual presence in remote investigations are explored.

Novel approaches for targeting the adenosine A2A receptor.

PubMed

Yuan, Gengyang; Gedeon, Nicholas G; Jankins, Tanner C; Jones, Graham B

2015-01-01

The adenosine A2A receptor (A2AR) represents a drug target for a wide spectrum of diseases. Approaches for targeting this membrane-bound protein have been greatly advanced by new stabilization techniques. The resulting X-ray crystal structures and subsequent analyses provide deep insight to the A2AR from both static and dynamic perspectives. Application of this, along with other biophysical methods combined with fragment-based drug design (FBDD), has become a standard approach in targeting A2AR. Complementarities of in silico screening based- and biophysical screening assisted- FBDD are likely to feature in future approaches in identifying novel ligands against this key receptor. This review describes evolution of the above approaches for targeting A2AR and highlights key modulators identified. It includes a review of: adenosine receptor structures, homology modeling, X-ray structural analysis, rational drug design, biophysical methods, FBDD and in silico screening. As a drug target, the A2AR is attractive as its function plays a role in a wide spectrum of diseases including oncologic, inflammatory, Parkinson's and cardiovascular diseases. Although traditional approaches such as high-throughput screening and homology model-based virtual screening (VS) have played a role in targeting A2AR, numerous shortcomings have generally restricted their applications to specific ligand families. Using stabilization methods for crystallization, X-ray structures of A2AR have greatly accelerated drug discovery and influenced development of biophysical-in silico hybrid screening methods. Application of these new methods to other ARs and G-protein-coupled receptors is anticipated in the future.

Biochemical profiling in silico--predicting substrate specificities of large enzyme families.

PubMed

Tyagi, Sadhna; Pleiss, Juergen

2006-06-25

A general high-throughput method for in silico biochemical profiling of enzyme families has been developed based on covalent docking of potential substrates into the binding sites of target enzymes. The method has been tested by systematically docking transition state--analogous intermediates of 12 substrates into the binding sites of 20 alpha/beta hydrolases from 15 homologous families. To evaluate the effect of side chain orientations to the docking results, 137 crystal structures were included in the analysis. A good substrate must fulfil two criteria: it must bind in a productive geometry with four hydrogen bonds between the substrate and the catalytic histidine and the oxyanion hole, and a high affinity of the enzyme-substrate complex as predicted by a high docking score. The modelling results in general reproduce experimental data on substrate specificity and stereoselectivity: the differences in substrate specificity of cholinesterases toward acetyl- and butyrylcholine, the changes of activity of lipases and esterases upon the size of the acid moieties, activity of lipases and esterases toward tertiary alcohols, and the stereopreference of lipases and esterases toward chiral secondary alcohols. Rigidity of the docking procedure was the major reason for false positive and false negative predictions, as the geometry of the complex and docking score may sensitively depend on the orientation of individual side chains. Therefore, appropriate structures have to be identified. In silico biochemical profiling provides a time efficient and cost saving protocol for virtual screening to identify the potential substrates of the members of large enzyme family from a library of molecules.

Transition of a dental histology course from light to virtual microscopy.

PubMed

Weaker, Frank J; Herbert, Damon C

2009-10-01

The transition of the dental histology course at the University of Texas Health Science Center at San Antonio Dental School was completed gradually over a five-year period. A pilot project was initially conducted to study the feasibility of integrating virtual microscopy into a traditional light microscopic lecture and laboratory course. Because of the difficulty of procuring quality calcified and decalcified sections of teeth, slides from the student loan collection in the oral histology block of the course were outsourced for conversion to digital images and placed on DVDs along with a slide viewer. The slide viewer mimicked the light microscope, allowing horizontal and vertical movement and changing of magnification, and, in addition, a feature to capture static images. In a survey, students rated the ease of use of the software, quality of the images, maneuverability of the images, and questions regarding use of the software, effective use of laboratory, and faculty time. Because of the positive support from the students, our entire student loan collection of 153 glass slides was subsequently converted to virtual images and distributed on an Apricorn pocket external hard drive. Students were asked to assess the virtual microscope over a four-year period. As a result of the surveys, light microscopes have been totally eliminated, and microscope exams have been replaced with project slide examinations. In the future, we plan to expand our virtual slides and incorporate computer testing.

Use of Interactive Live Digital Imaging to Enhance Histology Learning in Introductory Level Anatomy and Physiology Classes

ERIC Educational Resources Information Center

Higazi, Tarig B.

2011-01-01

Histology is one of the main subjects in introductory college-level Human Anatomy and Physiology classes. Institutions are moving toward the replacement of traditional microscope-based histology learning with virtual microscopy learning amid concerns of losing the valuable learning experience of traditional microscopy. This study used live digital…

In-silico screening for anti-Zika virus phytochemicals.

PubMed

Byler, Kendall G; Ogungbe, Ifedayo Victor; Setzer, William N

2016-09-01

Zika virus (ZIKV) is an arbovirus that has infected hundreds of thousands of people and is a rapidly expanding epidemic across Central and South America. ZIKV infection has caused serious, albeit rare, complications including Guillain-Barré syndrome and congenital microcephaly. There are currently no vaccines or antiviral agents to treat or prevent ZIKV infection, but there are several ZIKV non-structural proteins that may serve as promising antiviral drug targets. In this work, we have carried out an in-silico search for potential anti-Zika viral agents from natural sources. We have generated ZIKV protease, methyltransferase, and RNA-dependent RNA polymerase using homology modeling techniques and we have carried out molecular docking analyses of our in-house virtual library of phytochemicals with these protein targets as well as with ZIKV helicase. Overall, 2263 plant-derived secondary metabolites have been docked. Of these, 43 compounds that have drug-like properties have exhibited remarkable docking profiles to one or more of the ZIKV protein targets, and several of these are found in relatively common herbal medicines, suggesting promise for natural and inexpensive antiviral therapy for this emerging tropical disease. Copyright © 2016 Elsevier Inc. All rights reserved.

Discovering new mTOR inhibitors for cancer treatment through virtual screening methods and in vitro assays

NASA Astrophysics Data System (ADS)

Wang, Ling; Chen, Lei; Yu, Miao; Xu, Li-Hui; Cheng, Bao; Lin, Yong-Sheng; Gu, Qiong; He, Xian-Hui; Xu, Jun

2016-01-01

Mammalian target of rapamycin (mTOR) is an attractive target for new anticancer drug development. We recently developed in silico models to distinguish mTOR inhibitors and non-inhibitors. In this study, we developed an integrated strategy for identifying new mTOR inhibitors using cascaded in silico screening models. With this strategy, fifteen new mTOR kinase inhibitors including four compounds with IC50 values below 10 μM were discovered. In particular, compound 17 exhibited potent anticancer activities against four tumor cell lines, including MCF-7, HeLa, MGC-803, and C6, with IC50 values of 1.90, 2.74, 3.50 and 11.05 μM. Furthermore, cellular studies and western blot analyses revealed that 17 induces cell death via apoptosis by targeting both mTORC1 and mTORC2 within cells and arrests the cell cycle of HeLa at the G1/G0-phase. Finally, multi-nanosecond explicit solvent simulations and MM/GBSA analyses were carried out to study the inhibitory mechanisms of 13, 17, and 40 for mTOR. The potent compounds presented here are worthy of further investigation.

High-extinction virtually imaged phased array-based Brillouin spectroscopy of turbid biological media

NASA Astrophysics Data System (ADS)

Fiore, Antonio; Zhang, Jitao; Shao, Peng; Yun, Seok Hyun; Scarcelli, Giuliano

2016-05-01

Brillouin microscopy has recently emerged as a powerful technique to characterize the mechanical properties of biological tissue, cell, and biomaterials. However, the potential of Brillouin microscopy is currently limited to transparent samples, because Brillouin spectrometers do not have sufficient spectral extinction to reject the predominant non-Brillouin scattered light of turbid media. To overcome this issue, we combined a multi-pass Fabry-Perot interferometer with a two-stage virtually imaged phased array spectrometer. The Fabry-Perot etalon acts as an ultra-narrow band-pass filter for Brillouin light with high spectral extinction and low loss. We report background-free Brillouin spectra from Intralipid solutions and up to 100 μm deep within chicken muscle tissue.

Evaluation of Usage of Virtual Microscopy for the Study of Histology in the Medical, Dental, and Veterinary Undergraduate Programs of a UK University

ERIC Educational Resources Information Center

Gatumu, Margaret K.; MacMillan, Frances M.; Langton, Philip D.; Headley, P. Max; Harris, Judy R.

2014-01-01

This article describes the introduction of a virtual microscope (VM) that has allowed preclinical histology teaching to be fashioned to better suit the needs of approximately 900 undergraduate students per year studying medicine, dentistry, or veterinary science at the University of Bristol, United Kingdom. Features of the VM implementation…

D-VASim: an interactive virtual laboratory environment for the simulation and analysis of genetic circuits.

PubMed

Baig, Hasan; Madsen, Jan

2017-01-15

Simulation and behavioral analysis of genetic circuits is a standard approach of functional verification prior to their physical implementation. Many software tools have been developed to perform in silico analysis for this purpose, but none of them allow users to interact with the model during runtime. The runtime interaction gives the user a feeling of being in the lab performing a real world experiment. In this work, we present a user-friendly software tool named D-VASim (Dynamic Virtual Analyzer and Simulator), which provides a virtual laboratory environment to simulate and analyze the behavior of genetic logic circuit models represented in an SBML (Systems Biology Markup Language). Hence, SBML models developed in other software environments can be analyzed and simulated in D-VASim. D-VASim offers deterministic as well as stochastic simulation; and differs from other software tools by being able to extract and validate the Boolean logic from the SBML model. D-VASim is also capable of analyzing the threshold value and propagation delay of a genetic circuit model. D-VASim is available for Windows and Mac OS and can be downloaded from bda.compute.dtu.dk/downloads/. haba@dtu.dk, jama@dtu.dk. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

DOVIS: an implementation for high-throughput virtual screening using AutoDock.

PubMed

Zhang, Shuxing; Kumar, Kamal; Jiang, Xiaohui; Wallqvist, Anders; Reifman, Jaques

2008-02-27

Molecular-docking-based virtual screening is an important tool in drug discovery that is used to significantly reduce the number of possible chemical compounds to be investigated. In addition to the selection of a sound docking strategy with appropriate scoring functions, another technical challenge is to in silico screen millions of compounds in a reasonable time. To meet this challenge, it is necessary to use high performance computing (HPC) platforms and techniques. However, the development of an integrated HPC system that makes efficient use of its elements is not trivial. We have developed an application termed DOVIS that uses AutoDock (version 3) as the docking engine and runs in parallel on a Linux cluster. DOVIS can efficiently dock large numbers (millions) of small molecules (ligands) to a receptor, screening 500 to 1,000 compounds per processor per day. Furthermore, in DOVIS, the docking session is fully integrated and automated in that the inputs are specified via a graphical user interface, the calculations are fully integrated with a Linux cluster queuing system for parallel processing, and the results can be visualized and queried. DOVIS removes most of the complexities and organizational problems associated with large-scale high-throughput virtual screening, and provides a convenient and efficient solution for AutoDock users to use this software in a Linux cluster platform.

ChemHTPS - A virtual high-throughput screening program suite for the chemical and materials sciences

NASA Astrophysics Data System (ADS)

Afzal, Mohammad Atif Faiz; Evangelista, William; Hachmann, Johannes

The discovery of new compounds, materials, and chemical reactions with exceptional properties is the key for the grand challenges in innovation, energy and sustainability. This process can be dramatically accelerated by means of the virtual high-throughput screening (HTPS) of large-scale candidate libraries. The resulting data can further be used to study the underlying structure-property relationships and thus facilitate rational design capability. This approach has been extensively used for many years in the drug discovery community. However, the lack of openly available virtual HTPS tools is limiting the use of these techniques in various other applications such as photovoltaics, optoelectronics, and catalysis. Thus, we developed ChemHTPS, a general-purpose, comprehensive and user-friendly suite, that will allow users to efficiently perform large in silico modeling studies and high-throughput analyses in these applications. ChemHTPS also includes a massively parallel molecular library generator which offers a multitude of options to customize and restrict the scope of the enumerated chemical space and thus tailor it for the demands of specific applications. To streamline the non-combinatorial exploration of chemical space, we incorporate genetic algorithms into the framework. In addition to implementing smarter algorithms, we also focus on the ease of use, workflow, and code integration to make this technology more accessible to the community.

Interactive Volume Exploration of Petascale Microscopy Data Streams Using a Visualization-Driven Virtual Memory Approach.

PubMed

Hadwiger, M; Beyer, J; Jeong, Won-Ki; Pfister, H

2012-12-01

This paper presents the first volume visualization system that scales to petascale volumes imaged as a continuous stream of high-resolution electron microscopy images. Our architecture scales to dense, anisotropic petascale volumes because it: (1) decouples construction of the 3D multi-resolution representation required for visualization from data acquisition, and (2) decouples sample access time during ray-casting from the size of the multi-resolution hierarchy. Our system is designed around a scalable multi-resolution virtual memory architecture that handles missing data naturally, does not pre-compute any 3D multi-resolution representation such as an octree, and can accept a constant stream of 2D image tiles from the microscopes. A novelty of our system design is that it is visualization-driven: we restrict most computations to the visible volume data. Leveraging the virtual memory architecture, missing data are detected during volume ray-casting as cache misses, which are propagated backwards for on-demand out-of-core processing. 3D blocks of volume data are only constructed from 2D microscope image tiles when they have actually been accessed during ray-casting. We extensively evaluate our system design choices with respect to scalability and performance, compare to previous best-of-breed systems, and illustrate the effectiveness of our system for real microscopy data from neuroscience.

VirtualLeaf: an open-source framework for cell-based modeling of plant tissue growth and development.

PubMed

Merks, Roeland M H; Guravage, Michael; Inzé, Dirk; Beemster, Gerrit T S

2011-02-01

Plant organs, including leaves and roots, develop by means of a multilevel cross talk between gene regulation, patterned cell division and cell expansion, and tissue mechanics. The multilevel regulatory mechanisms complicate classic molecular genetics or functional genomics approaches to biological development, because these methodologies implicitly assume a direct relation between genes and traits at the level of the whole plant or organ. Instead, understanding gene function requires insight into the roles of gene products in regulatory networks, the conditions of gene expression, etc. This interplay is impossible to understand intuitively. Mathematical and computer modeling allows researchers to design new hypotheses and produce experimentally testable insights. However, the required mathematics and programming experience makes modeling poorly accessible to experimental biologists. Problem-solving environments provide biologically intuitive in silico objects ("cells", "regulation networks") required for setting up a simulation and present those to the user in terms of familiar, biological terminology. Here, we introduce the cell-based computer modeling framework VirtualLeaf for plant tissue morphogenesis. The current version defines a set of biologically intuitive C++ objects, including cells, cell walls, and diffusing and reacting chemicals, that provide useful abstractions for building biological simulations of developmental processes. We present a step-by-step introduction to building models with VirtualLeaf, providing basic example models of leaf venation and meristem development. VirtualLeaf-based models provide a means for plant researchers to analyze the function of developmental genes in the context of the biophysics of growth and patterning. VirtualLeaf is an ongoing open-source software project (http://virtualleaf.googlecode.com) that runs on Windows, Mac, and Linux.

A canopy architectural model to study the competitive ability of chickpea with sowthistle.

PubMed

Cici, S-Zahra-Hosseini; Adkins, Steve; Hanan, Jim

2008-06-01

Improving the competitive ability of crops is a sustainable method of weed management. This paper shows how a virtual plant model of competition between chickpea (Cicer arietinum) and sowthistle (Sonchus oleraceus) can be used as a framework for discovering and/or developing more competitive chickpea cultivars. The virtual plant models were developed using the L-systems formalism, parameterized according to measurements taken on plants at intervals during their development. A quasi-Monte Carlo light-environment model was used to model the effect of chickpea canopy on the development of sowthistle. The chickpea-light environment-sowthistle model (CLES model) captured the hypothesis that the architecture of chickpea plants modifies the light environment inside the canopy and determines sowthistle growth and development pattern. The resulting CLES model was parameterized for different chickpea cultivars (viz. 'Macarena', 'Bumper', 'Jimbour' and '99071-1001') to compare their competitive ability with sowthistle. To validate the CLES model, an experiment was conducted using the same four chickpea cultivars as different treatments with a sowthistle growing under their canopy. The growth of sowthistle, both in silico and in glasshouse experiments, was reduced most by '99071-1001', a cultivar with a short phyllochron. The second rank of competitive ability belonged to 'Macarena' and 'Bumper', while 'Jimbour' was the least competitive cultivar. The architecture of virtual chickpea plants modified the light inside the canopy, which influenced the growth and development of the sowthistle plants in response to different cultivars. This is the first time that a virtual plant model of a crop-weed interaction has been developed. This virtual plant model can serve as a platform for a broad range of applications in the study of chickpea-weed interactions and their environment.

In silico approaches to identify novel myeloid cell leukemia-1 (Mcl-1) inhibitors for treatment of cancer.

PubMed

Ren, Ji-Xia; Li, Cheng-Ping; Zhou, Xiu-Ling; Cao, Xue-Song; Xie, Yong

2017-08-22

Myeloid cell leukemia-1 (Mcl-1) has been a validated and attractive target for cancer therapy. Over-expression of Mcl-1 in many cancers allows cancer cells to evade apoptosis and contributes to the resistance to current chemotherapeutics. Here, we identified new Mcl-1 inhibitors using a multi-step virtual screening approach. First, based on two different ligand-receptor complexes, 20 pharmacophore models were established by simultaneously using 'Receptor-Ligand Pharmacophore Generation' method and manual build feature method, and then carefully validated by a test database. Then, pharmacophore-based virtual screening (PB-VS) could be performed by using the 20 pharmacophore models. In addition, docking study was used to predict the possible binding poses of compounds, and the docking parameters were optimized before performing docking-based virtual screening (DB-VS). Moreover, a 3D QSAR model was established by applying the 55 aligned Mcl-1 inhibitors. The 55 inhibitors sharing the same scaffold were docked into the Mcl-1 active site before alignment, then the inhibitors with possible binding conformations were aligned. For the training set, the 3D QSAR model gave a correlation coefficient r 2 of 0.996; for the test set, the correlation coefficient r 2 was 0.812. Therefore, the developed 3D QSAR model was a good model, which could be applied for carrying out 3D QSAR-based virtual screening (QSARD-VS). After the above three virtual screening methods orderly filtering, 23 potential inhibitors with novel scaffolds were identified. Furthermore, we have discussed in detail the mapping results of two potent compounds onto pharmacophore models, 3D QSAR model, and the interactions between the compounds and active site residues.

The application of laser scanning confocal microscopy to the examination of hairs and textile fibers: an initial investigation.

PubMed

Kirkbride, K Paul; Tridico, Silvana R

2010-02-25

An initial investigation of the application of laser scanning confocal microscopy to the examination of hairs and fibers has been conducted. This technique allows the production of virtual transverse and longitudinal cross-sectional images of a wide range of hairs and fibers. Special mounting techniques are not required; specimens that have been mounted for conventional microscopy require no further treatment. Unlike physical cross-sectioning, in which it is difficult to produce multiple cross-sections from a single hair or fiber and the process is destructive, confocal microscopy allows the examiner to image the cross-section at any point in the field of view along the hair or fiber and it is non-destructive. Confocal microscopy is a fluorescence-based technique. The images described in this article were collected using only the autofluorescence exhibited by the specimen (i.e. fluorescence staining was not necessary). Colorless fibers generally and hairs required excitation at 405 nm in order to stimulate useful autofluorescence; longer wavelength excitation was suitable for dyed fibers. Although confocal microscopy was found to be generally applicable to the generation virtual transverse cross-sections from a wide range of hairs and fibers, on some occasions the autofluorescence signal was attenuated by heavy pigmentation or the presence of an opaque medulla in hairs, and by heavy delustering or the presence of air-filled voids in the case of fibers. In these situations only partial cross-sections were obtained. 2009 Elsevier Ireland Ltd. All rights reserved.

DG-AMMOS: a new tool to generate 3d conformation of small molecules using distance geometry and automated molecular mechanics optimization for in silico screening.

PubMed

Lagorce, David; Pencheva, Tania; Villoutreix, Bruno O; Miteva, Maria A

2009-11-13

Discovery of new bioactive molecules that could enter drug discovery programs or that could serve as chemical probes is a very complex and costly endeavor. Structure-based and ligand-based in silico screening approaches are nowadays extensively used to complement experimental screening approaches in order to increase the effectiveness of the process and facilitating the screening of thousands or millions of small molecules against a biomolecular target. Both in silico screening methods require as input a suitable chemical compound collection and most often the 3D structure of the small molecules has to be generated since compounds are usually delivered in 1D SMILES, CANSMILES or in 2D SDF formats. Here, we describe the new open source program DG-AMMOS which allows the generation of the 3D conformation of small molecules using Distance Geometry and their energy minimization via Automated Molecular Mechanics Optimization. The program is validated on the Astex dataset, the ChemBridge Diversity database and on a number of small molecules with known crystal structures extracted from the Cambridge Structural Database. A comparison with the free program Balloon and the well-known commercial program Omega generating the 3D of small molecules is carried out. The results show that the new free program DG-AMMOS is a very efficient 3D structure generator engine. DG-AMMOS provides fast, automated and reliable access to the generation of 3D conformation of small molecules and facilitates the preparation of a compound collection prior to high-throughput virtual screening computations. The validation of DG-AMMOS on several different datasets proves that generated structures are generally of equal quality or sometimes better than structures obtained by other tested methods.

Is 'virtual histology' the next step after the 'virtual autopsy'? Magnetic resonance microscopy in forensic medicine.

PubMed

Thali, M J; Dirnhofer, R; Becker, R; Oliver, W; Potter, K

2004-10-01

The study aimed to validate magnetic resonance microscopy (MRM) studies of forensic tissue specimens (skin samples with electric injury patterns) against the results from routine histology. Computed tomography and magnetic resonance imaging are fast becoming important tools in clinical and forensic pathology. This study is the first forensic application of MRM to the analysis of electric injury patterns in human skin. Three-dimensional high-resolution MRM images of fixed skin specimens provided a complete 3D view of the damaged tissues at the site of an electric injury as well as in neighboring tissues, consistent with histologic findings. The image intensity of the dermal layer in T2-weighted MRM images was reduced in the central zone due to carbonization or coagulation necrosis and increased in the intermediate zone because of dermal edema. A subjacent blood vessel with an intravascular occlusion supports the hypothesis that current traveled through the vascular system before arcing to ground. High-resolution imaging offers a noninvasive alternative to conventional histology in forensic wound analysis and can be used to perform 3D virtual histology.

An adaptable navigation strategy for Virtual Microscopy from mobile platforms.

PubMed

Corredor, Germán; Romero, Eduardo; Iregui, Marcela

2015-04-01

Real integration of Virtual Microscopy with the pathologist service workflow requires the design of adaptable strategies for any hospital service to interact with a set of Whole Slide Images. Nowadays, mobile devices have the actual potential of supporting an online pervasive network of specialists working together. However, such devices are still very limited. This article introduces a novel highly adaptable strategy for streaming and visualizing WSI from mobile devices. The presented approach effectively exploits and extends the granularity of the JPEG2000 standard and integrates it with different strategies to achieve a lossless, loosely-coupled, decoder and platform independent implementation, adaptable to any interaction model. The performance was evaluated by two expert pathologists interacting with a set of 20 virtual slides. The method efficiently uses the available device resources: the memory usage did not exceed a 7% of the device capacity while the decoding times were smaller than the 200 ms per Region of Interest, i.e., a window of 256×256 pixels. This model is easily adaptable to other medical imaging scenarios. Copyright © 2015 Elsevier Inc. All rights reserved.

Computational Modeling and Simulation of Developmental ...

EPA Pesticide Factsheets

SYNOPSIS: The question of how tissues and organs are shaped during development is crucial for understanding human birth defects. Data from high-throughput screening assays on human stem cells may be utilized predict developmental toxicity with reasonable accuracy. Other types of models are necessary, however, for mechanism-specific analysis because embryogenesis requires precise timing and control. Agent-based modeling and simulation (ABMS) is an approach to virtually reconstruct these dynamics, cell-by-cell and interaction-by-interaction. Using ABMS, HTS lesions from ToxCast can be integrated with patterning systems heuristically to propagate key events This presentation to FDA-CFSAN will update progress on the applications of in silico modeling tools and approaches for assessing developmental toxicity.

Cytopathology whole slide images and adaptive tutorials for senior medical students: a randomized crossover trial.

PubMed

Van Es, Simone L; Kumar, Rakesh K; Pryor, Wendy M; Salisbury, Elizabeth L; Velan, Gary M

2016-01-08

Diagnostic cytopathology is an essential part of clinical decision-making. However, due to a combination of factors including curriculum reform and shortage of pathologists to teach introductory cytopathology, this area of pathology receives little or no formal attention in most medical school curricula. We have previously described the successful use of efficient and effective digital learning resources, including whole slide images (WSI) and virtual microscopy adaptive tutorials (VMATs), to teach cytopathology to pathology specialist trainees - a group that had prior exposure to cytopathology in their day to day practice. Consequently, in the current study we attempted to demonstrate the efficiency and efficacy of this eLearning resource in a cohort of senior medical students that was completely naïve to the subject matter (cytopathology). We evaluated both the quantitative and qualitative impact of these digital educational materials for learning cytopathology compared with existing resources (e-textbooks and online atlases). The senior medical students were recruited from The University of New South Wales Australia for a randomized cross-over trial. Online assessments, administered after each arm of the trial, contained questions which related directly to a whole slide image. Two categories of questions in the assessments (focusing on either diagnosis or identification of cellular features) were utilized to determine efficacy. User experience and perceptions of efficiency were evaluated using online questionnaires containing Likert scale items and open-ended questions. For this cohort of senior medical students, virtual microscopy adaptive tutorials (VMATs) proved to be at least as effective as existing digital resources for learning cytopathology. Importantly, virtual microscopy adaptive tutorials had superior efficacy in facilitating accurate diagnosis on whole slide images. Student perceptions of VMATs were positive, particularly regarding the immediate feedback, interactivity and equity of learning which this learning resource provides. Virtual microscopy adaptive tutorials have the potential to improve the efficacy of learning microscopic pathology for medical students. The enhanced learning experience provided by these eLearning tools merits further investigation of their utility for other cohorts, including specialist trainees.

[Whole slide imaging technology: from digitization to online applications].

PubMed

Ameisen, David; Le Naour, Gilles; Daniel, Christel

2012-11-01

As e-health becomes essential to modern care, whole slide images (virtual slides) are now an important clinical, teaching and research tool in pathology. Virtual microscopy consists of digitizing a glass slide by acquiring hundreds of tiles of regions of interest at different zoom levels and assembling them into a structured file. This gigapixel image can then be remotely viewed over a terminal, exactly the way pathologists use a microscope. In this article, we will first describe the key elements of this technology, from the acquisition, using a scanner or a motorized microscope, to the broadcasting of virtual slides through a local or distant viewer over an intranet or Internet connection. As virtual slides are now commonly used in virtual classrooms, clinical data and research databases, we will highlight the main issues regarding its uses in modern pathology. Emphasis will be made on quality assurance policies, standardization and scaling. © 2012 médecine/sciences – Inserm / SRMS.

The Virtual Physiological Human - a European initiative for in silico human modelling -.

PubMed

Viceconti, Marco; Clapworthy, Gordon; Van Sint Jan, Serge

2008-12-01

The Virtual Physiological Human (VPH) is an initiative, strongly supported by the European Commission (EC), that seeks to develop an integrated model of human physiology at multiple scales from the whole body through the organ, tissue, cell and molecular levels to the genomic level. VPH had its beginnings in 2005 with informal discussions amongst like-minded scientists which led to the STEP project, a Coordination Action funded by the EC that began in early 2006. The STEP project greatly accelerated the progress of the VPH and proved to be a catalyst for wide-ranging discussions within Europe and for outreach activities designed to develop a broad international approach to the huge scientific and technological challenges involved in this area. This paper provides an overview of the VPH and the developments it has engendered in the rapidly expanding worldwide activities associated with the physiome. It then uses one particular project, the Living Human Project, to illustrate the type of advances that are taking place to further the aims of the VPH and similar initiatives worldwide.

Computational methods in drug discovery

PubMed Central

Leelananda, Sumudu P

2016-01-01

The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein–ligand docking, pharmacophore modeling and QSAR techniques are reviewed. PMID:28144341

In silico study toward the identification of new and safe potential inhibitors of photosynthetic electron transport.

PubMed

Ribeiro, Taisa Pereira Piacentini; Manarin, Flávia Giovana; Borges de Melo, Eduardo

2018-05-30

To address the rising global demand for food, it is necessary to search for new herbicides that can control resistant weeds. We performed a 2D-quantitative structure-activity relationship (QSAR) study to predict compounds with photosynthesis-inhibitory activity. A data set of 44 compounds (quinolines and naphthalenes), which are described as photosynthetic electron transport (PET) inhibitors, was used. The obtained model was approved in internal and external validation tests. 2D Similarity-based virtual screening was performed and 64 compounds were selected from the ZINC database. By using the VEGA QSAR software, 48 compounds were shown to have potential toxic effects (mutagenicity and carcinogenicity). Therefore, the model was also tested using a set of 16 molecules obtained by a similarity search of the ZINC database. Six compounds showed good predicted inhibition of PET. The obtained model shows potential utility in the design of new PET inhibitors, and the hit compounds found by virtual screening are novel bicyclic scaffolds of this class. Copyright © 2018 Elsevier Inc. All rights reserved.

In Silico Identification of a Novel Hinge-Binding Scaffold for Kinase Inhibitor Discovery.

PubMed

Wang, Yanli; Sun, Yuze; Cao, Ran; Liu, Dan; Xie, Yuting; Li, Li; Qi, Xiangbing; Huang, Niu

2017-10-26

To explore novel kinase hinge-binding scaffolds, we carried out structure-based virtual screening against p38α MAPK as a model system. With the assistance of developed kinase-specific structural filters, we identify a novel lead compound that selectively inhibits a panel of kinases with threonine as the gatekeeper residue, including BTK and LCK. These kinases play important roles in lymphocyte activation, which encouraged us to design novel kinase inhibitors as drug candidates for ameliorating inflammatory diseases and cancers. Therefore, we chemically modified our substituted triazole-class lead compound to improve the binding affinity and selectivity via a "minimal decoration" strategy, which resulted in potent and selective kinase inhibitors against LCK (18 nM) and BTK (8 nM). Subsequent crystallographic experiments validated our design. These rationally designed compounds exhibit potent on-target inhibition against BTK in B cells or LCK in T cells, respectively. Our work demonstrates that structure-based virtual screening can be applied to facilitate the development of novel chemical entities in crowded chemical space in the field of kinase inhibitor discovery.

Computational methods in drug discovery.

PubMed

Leelananda, Sumudu P; Lindert, Steffen

2016-01-01

The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein-ligand docking, pharmacophore modeling and QSAR techniques are reviewed.

Increasing thermal stability and catalytic activity of glutamate decarboxylase in E. coli: An in silico study.

PubMed

Tavakoli, Yasaman; Esmaeili, Abolghasem; Saber, Hossein

2016-10-01

Glutamate decarboxylase (GAD) is an enzyme that converts l-glutamate to gamma amino butyric acid (GABA) that is a widely used drug to treat mental disorders like Alzheimer's disease. In this study for the first time point mutation was performed virtually in the active site of the E. coli GAD in order to increase thermal stability and catalytic activity of the enzyme. Energy minimization and addition of water box were performed using GROMACS 5.4.6 package. PoPMuSiC 2.1 web server was used to predict potential spots for point mutation and Modeller software was used to perform point mutation on three dimensional model. Molegro virtual docker software was used for cavity detection and stimulated docking study. Results indicate that performing mutation separately at positions 164, 302, 304, 393, 396, 398 and 410 increase binding affinity to substrate. The enzyme is predicted to be more thermo- stable in all 7 mutants based on ΔΔG value. Copyright © 2016 Elsevier Ltd. All rights reserved.

3D Pharmacophore-Based Virtual Screening and Docking Approaches toward the Discovery of Novel HPPD Inhibitors.

PubMed

Fu, Ying; Sun, Yi-Na; Yi, Ke-Han; Li, Ming-Qiang; Cao, Hai-Feng; Li, Jia-Zhong; Ye, Fei

2017-06-09

p -Hydroxyphenylpyruvate dioxygenase (HPPD) is not only the useful molecular target in treating life-threatening tyrosinemia type I, but also an important target for chemical herbicides. A combined in silico structure-based pharmacophore and molecular docking-based virtual screening were performed to identify novel potential HPPD inhibitors. The complex-based pharmacophore model (CBP) with 0.721 of ROC used for screening compounds showed remarkable ability to retrieve known active ligands from among decoy molecules. The ChemDiv database was screened using CBP-Hypo2 as a 3D query, and the best-fit hits subjected to molecular docking with two methods of LibDock and CDOCKER in Accelrys Discovery Studio 2.5 (DS 2.5) to discern interactions with key residues at the active site of HPPD. Four compounds with top rankings in the HipHop model and well-known binding model were finally chosen as lead compounds with potential inhibitory effects on the active site of target. The results provided powerful insight into the development of novel HPPD inhibitors herbicides using computational techniques.

Global methylation screening in the Arabidopsis thaliana and Mus musculus genome: applications of virtual image restriction landmark genomic scanning (Vi-RLGS)

PubMed Central

Matsuyama, Tomoki; Kimura, Makoto T.; Koike, Kuniaki; Abe, Tomoko; Nakano, Takeshi; Asami, Tadao; Ebisuzaki, Toshikazu; Held, William A.; Yoshida, Shigeo; Nagase, Hiroki

2003-01-01

Understanding the role of ‘epigenetic’ changes such as DNA methylation and chromatin remodeling has now become critical in understanding many biological processes. In order to delineate the global methylation pattern in a given genomic DNA, computer software has been developed to create a virtual image of restriction landmark genomic scanning (Vi-RLGS). When using a methylation- sensitive enzyme such as NotI as the restriction landmark, the comparison between real and in silico RLGS profiles of the genome provides a methylation map of genomic NotI sites. A methylation map of the Arabidopsis genome was created that could be confirmed by a methylation-sensitive PCR assay. The method has also been applied to the mouse genome. Although a complete methylation map has not been completed, a region of methylation difference between two tissues has been tested and confirmed by bisulfite sequencing. Vi-RLGS in conjunction with real RLGS will make it possible to develop a more complete map of genomic sites that are methylated or demethylated as a consequence of normal or abnormal development. PMID:12888509

Novel fatty acid binding protein 4 (FABP4) inhibitors: virtual screening, synthesis and crystal structure determination.

PubMed

Cai, Haiyan; Liu, Qiufeng; Gao, Dingding; Wang, Ting; Chen, Tiantian; Yan, Guirui; Chen, Kaixian; Xu, Yechun; Wang, Heyao; Li, Yingxia; Zhu, Weiliang

2015-01-27

Fatty acid binding protein 4 (FABP4) is a potential drug target for diabetes and atherosclerosis. For discovering new chemical entities as FABP4 inhibitors, structure-based virtual screening (VS) was performed, bioassay demonstrated that 16 of 251 tested compounds are FABP4 inhibitors, among which compound m1 are more active than endogenous ligand linoleic acid (LA). Based on the structure of m1, new derivatives were designed and prepared, leading to the discovery of two more potent inhibitors, compounds 9 and 10. To further explore the binding mechanisms of these new inhibitors, we determined the X-ray structures of the complexes of FABP4-9 and FABP4-10, which revealed similar binding conformations of the two compounds. Residue Ser53 and Arg126 formed direct hydrogen bonding with the ligands. We also found that 10 could significantly reduce the levels of lipolysis on mouse 3T3-L1 adipocytes. Taken together, in silico, in vitro and crystallographic data provide useful hints for future development of novel inhibitors against FABP4. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Virtual unfolding of light sheet fluorescence microscopy dataset for quantitative analysis of the mouse intestine

NASA Astrophysics Data System (ADS)

Candeo, Alessia; Sana, Ilenia; Ferrari, Eleonora; Maiuri, Luigi; D'Andrea, Cosimo; Valentini, Gianluca; Bassi, Andrea

2016-05-01

Light sheet fluorescence microscopy has proven to be a powerful tool to image fixed and chemically cleared samples, providing in depth and high resolution reconstructions of intact mouse organs. We applied light sheet microscopy to image the mouse intestine. We found that large portions of the sample can be readily visualized, assessing the organ status and highlighting the presence of regions with impaired morphology. Yet, three-dimensional (3-D) sectioning of the intestine leads to a large dataset that produces unnecessary storage and processing overload. We developed a routine that extracts the relevant information from a large image stack and provides quantitative analysis of the intestine morphology. This result was achieved by a three step procedure consisting of: (1) virtually unfold the 3-D reconstruction of the intestine; (2) observe it layer-by-layer; and (3) identify distinct villi and statistically analyze multiple samples belonging to different intestinal regions. Even if the procedure has been developed for the murine intestine, most of the underlying concepts have a general applicability.

Cytology 3D structure formation based on optical microscopy images

NASA Astrophysics Data System (ADS)

Pronichev, A. N.; Polyakov, E. V.; Shabalova, I. P.; Djangirova, T. V.; Zaitsev, S. M.

2017-01-01

The article the article is devoted to optimization of the parameters of imaging of biological preparations in optical microscopy using a multispectral camera in visible range of electromagnetic radiation. A model for the image forming of virtual preparations was proposed. The optimum number of layers was determined for the object scan in depth and holistic perception of its switching according to the results of the experiment.

Web-based virtual microscopy at the RWTH Aachen University: didactic concept, methods and analysis of acceptance by the students.

PubMed

Merk, Magdalene; Knuechel, Ruth; Perez-Bouza, Alberto

2010-12-20

Fundamental knowledge of microscopic anatomy and pathology has always been an essential part in medical education. The traditional didactic concept comprises theoretical and practical lessons using a light microscope and glass slides. High-speed Internet connections and technical improvement in whole-slide digital microscopy (commonly termed "virtual microscopy") provide a new and attractive approach for both teachers and students. High picture quality and unlimited temporal and spatial availability of histology samples from different fields are key advantages of web-based digital microscopy. In this report we discuss the technical requirements, system efficiency, optical resolution and didactic concept. Furthermore, we present a review of the experience gained in the course of one year based on an analysis of student acceptance. Three groups with a total of 192 students between the 3rd and 5th year of medical studies attending the practical courses of general and advanced histopathology had access to both glass-mounted and digitalized slides. Prior to exams, students were asked to answer an anonymous questionnaire. The results of the study reflect the high acceptance and intensive use of the web-based digital histology by students, thus encouraging the development of further Web-based learning strategies for the teaching of histology and pathology. 2010 Elsevier GmbH. All rights reserved.

Identification of Natural Compound Inhibitors for Multidrug Efflux Pumps of Escherichia coli and Pseudomonas aeruginosa Using In Silico High-Throughput Virtual Screening and In Vitro Validation

PubMed Central

Aparna, Vasudevan; Dineshkumar, Kesavan; Mohanalakshmi, Narasumani; Velmurugan, Devadasan; Hopper, Waheeta

2014-01-01

Pseudomonas aeruginosa and Escherichia coli are resistant to wide range of antibiotics rendering the treatment of infections very difficult. A main mechanism attributed to the resistance is the function of efflux pumps. MexAB-OprM and AcrAB-TolC are the tripartite efflux pump assemblies, responsible for multidrug resistance in P. aeruginosa and E. coli respectively. Substrates that are more susceptible for efflux are predicted to have a common pharmacophore feature map. In this study, a new criterion of excluding compounds with efflux substrate-like features was used, thereby refining the selection process and enriching the inhibitor identification process. An in-house database of phytochemicals was created and screened using high-throughput virtual screening against AcrB and MexB proteins and filtered by matching with the common pharmacophore models (AADHR, ADHNR, AAHNR, AADHN, AADNR, AAADN, AAADR, AAANR, AAAHN, AAADD and AAADH) generated using known efflux substrates. Phytochemical hits that matched with any one or more of the efflux substrate models were excluded from the study. Hits that do not have features similar to the efflux substrate models were docked using XP docking against the AcrB and MexB proteins. The best hits of the XP docking were validated by checkerboard synergy assay and ethidium bromide accumulation assay for their efflux inhibition potency. Lanatoside C and diadzein were filtered based on the synergistic potential and validated for their efflux inhibition potency using ethidium bromide accumulation study. These compounds exhibited the ability to increase the accumulation of ethidium bromide inside the bacterial cell as evidenced by these increase in fluorescence in the presence of the compounds. With this good correlation between in silico screening and positive efflux inhibitory activity in vitro, the two compounds, lanatoside C and diadzein could be promising efflux pump inhibitors and effective to use in combination therapy against drug resistant strains of P. aeruginosa and E. coli. PMID:25025665

Identification of natural compound inhibitors for multidrug efflux pumps of Escherichia coli and Pseudomonas aeruginosa using in silico high-throughput virtual screening and in vitro validation.

PubMed

Aparna, Vasudevan; Dineshkumar, Kesavan; Mohanalakshmi, Narasumani; Velmurugan, Devadasan; Hopper, Waheeta

2014-01-01

Pseudomonas aeruginosa and Escherichia coli are resistant to wide range of antibiotics rendering the treatment of infections very difficult. A main mechanism attributed to the resistance is the function of efflux pumps. MexAB-OprM and AcrAB-TolC are the tripartite efflux pump assemblies, responsible for multidrug resistance in P. aeruginosa and E. coli respectively. Substrates that are more susceptible for efflux are predicted to have a common pharmacophore feature map. In this study, a new criterion of excluding compounds with efflux substrate-like features was used, thereby refining the selection process and enriching the inhibitor identification process. An in-house database of phytochemicals was created and screened using high-throughput virtual screening against AcrB and MexB proteins and filtered by matching with the common pharmacophore models (AADHR, ADHNR, AAHNR, AADHN, AADNR, AAADN, AAADR, AAANR, AAAHN, AAADD and AAADH) generated using known efflux substrates. Phytochemical hits that matched with any one or more of the efflux substrate models were excluded from the study. Hits that do not have features similar to the efflux substrate models were docked using XP docking against the AcrB and MexB proteins. The best hits of the XP docking were validated by checkerboard synergy assay and ethidium bromide accumulation assay for their efflux inhibition potency. Lanatoside C and diadzein were filtered based on the synergistic potential and validated for their efflux inhibition potency using ethidium bromide accumulation study. These compounds exhibited the ability to increase the accumulation of ethidium bromide inside the bacterial cell as evidenced by these increase in fluorescence in the presence of the compounds. With this good correlation between in silico screening and positive efflux inhibitory activity in vitro, the two compounds, lanatoside C and diadzein could be promising efflux pump inhibitors and effective to use in combination therapy against drug resistant strains of P. aeruginosa and E. coli.

In-Silico Screening of Ligand Based Pharmacophore, Database Mining and Molecular Docking on 2, 5-Diaminopyrimidines Azapurines as Potential Inhibitors of Glycogen Synthase Kinase-3β.

PubMed

Mishra, Pooja; Kesar, Seema; Paliwal, Sarvesh K; Chauhan, Monika; Madan, Kirtika

2018-05-29

Glycogen synthase kinase-3β plays a significant role in the regulation of various pathological pathways relating to central nervous system (CNS). Dysregulation of Glycogen synthase kinase 3 (GSK-3) activity gives a rise to numerous neuroinflammation and neurodegenerative related disorders that affect the whole central nervous system. By the sequential application of in-silico tools, efforts have been attempted to design the novel GSK-3β inhibitors. Owing to the potential role of GSK-3β in nervous disorders, we have attempted to develop the quantitative four featured pharmacophore model comprising two hydrogen bond acceptors (HBA), one ring aromatic (RA), and one hydrophobe (HY), which were further affirmed by cost-function analysis, rm2 matrices, internal and external test set validation and Güner-Henry (GH) scoring analysis. Validated pharmacophoric model was used for virtual screening and out of 345 compounds, two potential virtual hits were finalized that were on the basis of fit value, estimated activity and Lipinski's violation. The chosen compounds were subjected to dock within the active site of GSK-3β Result: Four essential features, i.e., two hydrogen bond acceptors(HBA), one ring aromatic(RA), and one hydrophobe(HY), were subjected to build the pharmacophoric model and showed good correlation coefficient, RMSD and cost difference values of 0.91, 0.94 and 42.9 respectively and further model was validated employing cost-function analysis, rm2-matrices, internal and external test set prediction with r2 value of 0.77 and 0.84. Docked conformations showed potential interactions in between the features of the identified hits (NCI 4296, NCI 3034) and the amino acids present in the active site. In line with the overhead discussion, and through our stepwise computational approaches, we have identified novel, structurally diverse glycogen synthase kinase inhibitors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

An in silico approach helped to identify the best experimental design, population, and outcome for future randomized clinical trials.

PubMed

Bajard, Agathe; Chabaud, Sylvie; Cornu, Catherine; Castellan, Anne-Charlotte; Malik, Salma; Kurbatova, Polina; Volpert, Vitaly; Eymard, Nathalie; Kassai, Behrouz; Nony, Patrice

2016-01-01

The main objective of our work was to compare different randomized clinical trial (RCT) experimental designs in terms of power, accuracy of the estimation of treatment effect, and number of patients receiving active treatment using in silico simulations. A virtual population of patients was simulated and randomized in potential clinical trials. Treatment effect was modeled using a dose-effect relation for quantitative or qualitative outcomes. Different experimental designs were considered, and performances between designs were compared. One thousand clinical trials were simulated for each design based on an example of modeled disease. According to simulation results, the number of patients needed to reach 80% power was 50 for crossover, 60 for parallel or randomized withdrawal, 65 for drop the loser (DL), and 70 for early escape or play the winner (PW). For a given sample size, each design had its own advantage: low duration (parallel, early escape), high statistical power and precision (crossover), and higher number of patients receiving the active treatment (PW and DL). Our approach can help to identify the best experimental design, population, and outcome for future RCTs. This may be particularly useful for drug development in rare diseases, theragnostic approaches, or personalized medicine. Copyright © 2016 Elsevier Inc. All rights reserved.

Virtual screening for development of new effective compounds against Staphylococcus aureus.

PubMed

Diniz, Roseane Costa; Soares, Lucas Weba; da Silva, Luis Claudio Nascimento

2018-03-26

Staphylococcus aureus is a notorious pathogenic bacterium causing a wide range of diseases from soft-tissue contamination, to more serious and deep-seated infections. This species is highlighted by its ability to express several kinds of virulence factors and to acquire genes related to drug resistance. Target this number of factors to design any drug is not an easy task. In this review we discuss the importance of computational methods to impulse the development of new drugs against S. aureus. The application of docking methods to screen large library of natural or synthetic compounds and to provide insights into action mechanisms is demonstrated. Particularly, highlighted the studies that validated in silico results with biochemical and microbiological assays. We also comment the computer-aided design of new molecules using some known inhibitors. The confirmation of in silico results with biochemical and microbiological assays allowed the identification of lead molecules that could be used for drug design such as rhodomyrtone, quinuclidine, berberine (and their derivative compounds). The fast development in the computational methods is essential to improve our ability to discovery new drugs, as well as to expand understanding about drug-target interactions. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

In Silico Dynamics: computer simulation in a Virtual Embryo ...

EPA Pesticide Factsheets

Abstract: Utilizing cell biological information to predict higher order biological processes is a significant challenge in predictive toxicology. This is especially true for highly dynamical systems such as the embryo where morphogenesis, growth and differentiation require precisely orchestrated interactions between diverse cell populations. In patterning the embryo, genetic signals setup spatial information that cells then translate into a coordinated biological response. This can be modeled as ‘biowiring diagrams’ representing genetic signals and responses. Because the hallmark of multicellular organization resides in the ability of cells to interact with one another via well-conserved signaling pathways, multiscale computational (in silico) models that enable these interactions provide a platform to translate cellular-molecular lesions perturbations into higher order predictions. Just as ‘the Cell’ is the fundamental unit of biology so too should it be the computational unit (‘Agent’) for modeling embryogenesis. As such, we constructed multicellular agent-based models (ABM) with ‘CompuCell3D’ (www.compucell3d.org) to simulate kinematics of complex cell signaling networks and enable critical tissue events for use in predictive toxicology. Seeding the ABMs with HTS/HCS data from ToxCast demonstrated the potential to predict, quantitatively, the higher order impacts of chemical disruption at the cellular or biochemical level. This is demonstrate

In Silico Characterization of miRNA and Long Non-Coding RNA Interplay in Multiple Myeloma

PubMed Central

Ronchetti, Domenica; Manzoni, Martina; Todoerti, Katia; Neri, Antonino; Agnelli, Luca

2016-01-01

The identification of deregulated microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. In addition, the cross-regulation between lncRNAs and miRNAs has begun to emerge, and theoretical and experimental studies have demonstrated the competing endogenous RNA (ceRNA) activity of lncRNAs as natural miRNA decoys in pathophysiological conditions, including cancer. Currently, information concerning lncRNA and miRNA interplay in MM is virtually absent. Herein, we investigated in silico the lncRNA and miRNA relationship in a representative datasets encompassing 95 MM and 30 plasma cell leukemia patients at diagnosis and in four normal controls, whose expression profiles were generated by a custom annotation pipeline to detect specific lncRNAs. We applied target prediction analysis based on miRanda and RNA22 algorithms to 235 lncRNAs and 459 miRNAs selected with a potential pivotal role in the pathology of MM. Among pairs that showed a significant correlation between lncRNA and miRNA expression levels, we identified 11 lncRNA–miRNA relationships suggestive of a novel ceRNA network with relevance in MM. PMID:27916857

Comparative in silico analyses of Cannabis sativa, Prunella vulgaris and Withania somnifera compounds elucidating the medicinal properties against rheumatoid arthritis.

PubMed

Zaka, Mehreen; Sehgal, Sheikh Arslan; Shafique, Shagufta; Abbasi, Bilal Haider

2017-06-01

From last decade, there has been progressive improvement in computational drug designing. Several diseases are being cured from different plant extracts and products. Rheumatoid Arthritis (RA) is the most shared disease among auto-inflammatory diseases. Tumour necrosis factor (TNF)-α is associated with RA pathway and has adverse effects. Extensive literature review showed that plant species under study (Cannabis sativa, Prunella vulgaris and Withania somnifera) possess anti-inflammatory, anti-arthritic and anti-rheumatic properties. 13 anti-inflammatory compounds were characterised and filtered out from medicinal plant species and analysed for RA by targeting TNF-α through in silico analyses. By using ligand based pharmacophore generation approach and virtual screening against natural products libraries we retrieved twenty unique molecules that displayed utmost binding affinity, least binding energies and effective drug properties. The docking analyses revealed that Ala-22, Glu-23, Ser-65, Gln-67, Tyr-141, Leu-142, Asp-143, Phe-144 and Ala-145 were critical interacting residues for receptor-ligand interactions. It is proposed that the RA patients should use reported compounds for the prescription of RA by targeting TNF-α. This report is opening new dimensions for designing innovative therapeutic targets to cure RA. Copyright © 2017 Elsevier Inc. All rights reserved.

In silico identification of a therapeutic target for photo-activated disinfection with indocyanine green: Modeling and virtual screening analysis of Arg-gingipain from Porphyromonas gingivalis.

PubMed

Pourhajibagher, Maryam; Bahador, Abbas

2017-06-01

Porphyromonas gingivalis is a momentous bacterial etiological agent associated with periodontitis, peri-implantitis as well as endodontic infections. The potential advantage of Photo-activated disinfection (PAD) as a promising novel approach is the choice of a suitable target site, specific photosensitizer, and wavelength of light for delivery of the light from source to target. Since Arg-gingipain is a cysteine proteinase that is involved in the virulence of P. gingivalis, it was evaluated as a target site for PAD with indocyanine green (ICG) as a photosensitizer. In this study, we used a range of in silico strategies, bioinformatics tools, biological databases, and computer simulation molecular modeling to evaluate the capacity of Arg-gingipain. The predicted structure of Arg-gingipain indicated that it is located outside the cell and has nine domains and 17 ligands, including two calcium ions and three sodium ions with positive charges which can be a site of interaction for anionic ICG. Based on the results of this study, anionic ICG desires to bind and interact with residues of Arg-gingipain during PAD as a main site to enhance the yield of treatment of endo-periodontal lesions. Copyright © 2017 Elsevier B.V. All rights reserved.

Discovery of Dual ETA/ETB Receptor Antagonists from Traditional Chinese Herbs through in Silico and in Vitro Screening

PubMed Central

Wang, Xing; Zhang, Yuxin; Liu, Qing; Ai, Zhixin; Zhang, Yanling; Xiang, Yuhong; Qiao, Yanjiang

2016-01-01

Endothelin-1 receptors (ETAR and ETBR) act as a pivotal regulator in the biological effects of ET-1 and represent a potential drug target for the treatment of multiple cardiovascular diseases. The purpose of the study is to discover dual ETA/ETB receptor antagonists from traditional Chinese herbs. Ligand- and structure-based virtual screening was performed to screen an in-house database of traditional Chinese herbs, followed by a series of in vitro bioassay evaluation. Aristolochic acid A (AAA) was first confirmed to be a dual ETA/ETB receptor antagonist based intracellular calcium influx assay and impedance-based assay. Dose-response curves showed that AAA can block both ETAR and ETBR with IC50 of 7.91 and 7.40 μM, respectively. Target specificity and cytotoxicity bioassay proved that AAA is a selective dual ETA/ETB receptor antagonist and has no significant cytotoxicity on HEK293/ETAR and HEK293/ETBR cells within 24 h. It is a feasible and effective approach to discover bioactive compounds from traditional Chinese herbs using in silico screening combined with in vitro bioassay evaluation. The structural characteristic of AAA for its activity was especially interpreted, which could provide valuable reference for the further structural modification of AAA. PMID:26999111

In Silico Discovery of a Substituted 6-Methoxy-quinalidine with Leishmanicidal Activity in Leishmania infantum.

PubMed

Stevanović, Strahinja; Perdih, Andrej; Senćanski, Milan; Glišić, Sanja; Duarte, Margarida; Tomás, Ana M; Sena, Filipa V; Sousa, Filipe M; Pereira, Manuela M; Solmajer, Tom

2018-03-27

There is an urgent need for the discovery of new antileishmanial drugs with a new mechanism of action. Type 2 NADH dehydrogenase from Leishmania infantum ( Li NDH2) is an enzyme of the parasite's respiratory system, which catalyzes the electron transfer from NADH to ubiquinone without coupled proton pumping. In previous studies of the related NADH: ubiquinone oxidoreductase crystal structure from Saccharomyces cerevisiae , two ubiquinone-binding sites (UQ I and UQ II ) were identified and shown to play an important role in the NDH-2-catalyzed oxidoreduction reaction. Based on the available structural data, we developed a three-dimensional structural model of Li NDH2 using homology detection methods and performed an in silico virtual screening campaign to search for potential inhibitors targeting the Li NDH2 ubiquinone-binding site 1-UQ I . Selected compounds displaying favorable properties in the computational screening experiments were assayed for inhibitory activity in the structurally similar recombinant NDH-2 from S. aureus and leishmanicidal activity was determined in the wild-type axenic amastigotes and promastigotes of L. infantum . The identified compound, a substituted 6-methoxy-quinalidine, showed promising nanomolar leishmanicidal activity on wild-type axenic promastigotes and amastigotes of L. infantum and the potential for further development.

In silico-designed novel non-peptidic ABAD LD hot spot mimetics reverse Aβ-induced mitochondrial impairments in vitro.

PubMed

Viswanath, Ambily Nath Indu; Kim, TaeHun; Jung, Seo Yun; Lim, Sang Min; Pae, Ae Nim

2017-12-01

Present work aimed to introduce non-peptidic ABAD loop D (L D ) hot spot mimetics as ABAD-Aβ inhibitors. A full-length atomistic model of ABAD-Aβ complex was built as a scaffold to launch the lead design and its topology later verified by cross-checking the computational mutagenesis results with that of in vitro data. Thereafter, the interactions of prime Aβ-binding L D residues-Tyr101, Thr108, and Thr110-were translated into specific pharmacophore features and this hypothesis subsequently used as a virtual screen query. ELISA-based screening of 20 hits identified two promising lead candidates, VC15 and VC19 with an IC 50 of 4.4 ± 0.3 and 9.6 ± 0.1 μm, respectively. They productively reversed Aβ-induced mitochondrial dysfunctions such as mitochondrial membrane potential loss (JC-1 assay), toxicity (MTT assay), and ATP reduction (ATP assay) in addition to increased cell viabilities. This is the first reporting of L D hot spot-centric in silico scheme to discover novel compounds with promising ABAD-Aβ inhibitory potential. These chemotypes are proposed for further structural optimization to derive novel Alzheimer's disease (AD) therapeutics. © 2017 John Wiley & Sons A/S.

Exploring root symbiotic programs in the model legume Medicago truncatula using EST analysis.

PubMed

Journet, Etienne-Pascal; van Tuinen, Diederik; Gouzy, Jérome; Crespeau, Hervé; Carreau, Véronique; Farmer, Mary-Jo; Niebel, Andreas; Schiex, Thomas; Jaillon, Olivier; Chatagnier, Odile; Godiard, Laurence; Micheli, Fabienne; Kahn, Daniel; Gianinazzi-Pearson, Vivienne; Gamas, Pascal

2002-12-15

We report on a large-scale expressed sequence tag (EST) sequencing and analysis program aimed at characterizing the sets of genes expressed in roots of the model legume Medicago truncatula during interactions with either of two microsymbionts, the nitrogen-fixing bacterium Sinorhizobium meliloti or the arbuscular mycorrhizal fungus Glomus intraradices. We have designed specific tools for in silico analysis of EST data, in relation to chimeric cDNA detection, EST clustering, encoded protein prediction, and detection of differential expression. Our 21 473 5'- and 3'-ESTs could be grouped into 6359 EST clusters, corresponding to distinct virtual genes, along with 52 498 other M.truncatula ESTs available in the dbEST (NCBI) database that were recruited in the process. These clusters were manually annotated, using a specifically developed annotation interface. Analysis of EST cluster distribution in various M.truncatula cDNA libraries, supported by a refined R test to evaluate statistical significance and by 'electronic northern' representation, enabled us to identify a large number of novel genes predicted to be up- or down-regulated during either symbiotic root interaction. These in silico analyses provide a first global view of the genetic programs for root symbioses in M.truncatula. A searchable database has been built and can be accessed through a public interface.

IFPTarget: A Customized Virtual Target Identification Method Based on Protein-Ligand Interaction Fingerprinting Analyses.

PubMed

Li, Guo-Bo; Yu, Zhu-Jun; Liu, Sha; Huang, Lu-Yi; Yang, Ling-Ling; Lohans, Christopher T; Yang, Sheng-Yong

2017-07-24

Small-molecule target identification is an important and challenging task for chemical biology and drug discovery. Structure-based virtual target identification has been widely used, which infers and prioritizes potential protein targets for the molecule of interest (MOI) principally via a scoring function. However, current "universal" scoring functions may not always accurately identify targets to which the MOI binds from the retrieved target database, in part due to a lack of consideration of the important binding features for an individual target. Here, we present IFPTarget, a customized virtual target identification method, which uses an interaction fingerprinting (IFP) method for target-specific interaction analyses and a comprehensive index (Cvalue) for target ranking. Evaluation results indicate that the IFP method enables substantially improved binding pose prediction, and Cvalue has an excellent performance in target ranking for the test set. When applied to screen against our established target library that contains 11,863 protein structures covering 2842 unique targets, IFPTarget could retrieve known targets within the top-ranked list and identified new potential targets for chemically diverse drugs. IFPTarget prediction led to the identification of the metallo-β-lactamase VIM-2 as a target for quercetin as validated by enzymatic inhibition assays. This study provides a new in silico target identification tool and will aid future efforts to develop new target-customized methods for target identification.

Enhanced weak-signal sensitivity in two-photon microscopy by adaptive illumination.

PubMed

Chu, Kengyeh K; Lim, Daryl; Mertz, Jerome

2007-10-01

We describe a technique to enhance both the weak-signal relative sensitivity and the dynamic range of a laser scanning optical microscope. The technique is based on maintaining a fixed detection power by fast feedback control of the illumination power, thereby transferring high measurement resolution to weak signals while virtually eliminating the possibility of image saturation. We analyze and demonstrate the benefits of adaptive illumination in two-photon fluorescence microscopy.

Robust Phagocyte Recruitment Controls the Opportunistic Fungal Pathogen Mucor circinelloides in Innate Granulomas In Vivo

PubMed Central

2018-01-01

ABSTRACT Mucormycosis is an emerging fungal infection with extremely high mortality rates in patients with defects in their innate immune response, specifically in functions mediated through phagocytes. However, we currently have a limited understanding of the molecular and cellular interactions between these innate immune effectors and mucormycete spores during the early immune response. Here, the early events of innate immune recruitment in response to infection by Mucor circinelloides spores are modeled by a combined in silico modeling approach and real-time in vivo microscopy. Phagocytes are rapidly recruited to the site of infection in a zebrafish larval model of mucormycosis. This robust early recruitment protects from disease onset in vivo. In silico analysis identified that protection is dependent on the number of phagocytes at the infection site, but not the speed of recruitment. The mathematical model highlights the role of proinflammatory signals for phagocyte recruitment and the importance of inhibition of spore germination for protection from active fungal disease. These in silico data are supported by an in vivo lack of fungal spore killing and lack of reactive oxygen burst, which together result in latent fungal infection. During this latent stage of infection, spores are controlled in innate granulomas in vivo. Disease can be reactivated by immunosuppression. Together, these data represent the first in vivo real-time analysis of innate granuloma formation during the early stages of a fungal infection. The results highlight a potential latent stage during mucormycosis that should urgently be considered for clinical management of patients. PMID:29588406

Automated Protocol for Large-Scale Modeling of Gene Expression Data.

PubMed

Hall, Michelle Lynn; Calkins, David; Sherman, Woody

2016-11-28

With the continued rise of phenotypic- and genotypic-based screening projects, computational methods to analyze, process, and ultimately make predictions in this field take on growing importance. Here we show how automated machine learning workflows can produce models that are predictive of differential gene expression as a function of a compound structure using data from A673 cells as a proof of principle. In particular, we present predictive models with an average accuracy of greater than 70% across a highly diverse ∼1000 gene expression profile. In contrast to the usual in silico design paradigm, where one interrogates a particular target-based response, this work opens the opportunity for virtual screening and lead optimization for desired multitarget gene expression profiles.

Protocols for the Design of Kinase-focused Compound Libraries.

PubMed

Jacoby, Edgar; Wroblowski, Berthold; Buyck, Christophe; Neefs, Jean-Marc; Meyer, Christophe; Cummings, Maxwell D; van Vlijmen, Herman

2018-05-01

Protocols for the design of kinase-focused compound libraries are presented. Kinase-focused compound libraries can be differentiated based on the design goal. Depending on whether the library should be a discovery library specific for one particular kinase, a general discovery library for multiple distinct kinase projects, or even phenotypic screening, there exists today a variety of in silico methods to design candidate compound libraries. We address the following scenarios: 1) Datamining of SAR databases and kinase focused vendor catalogues; 2) Predictions and virtual screening; 3) Structure-based design of combinatorial kinase inhibitors; 4) Design of covalent kinase inhibitors; 5) Design of macrocyclic kinase inhibitors; and 6) Design of allosteric kinase inhibitors and activators. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Virtual microscopes in podiatric medical education.

PubMed

Becker, John H

2006-01-01

In many medical schools, microscopes are being replaced as teaching tools by computers with software that emulates the use of a light microscope. This article chronicles the adoption of "virtual microscopes" by a podiatric medical school and presents the results of educational research on the effectiveness of this adoption in a histology course. If the trend toward virtual microscopy in education continues, many 21st-century physicians will not be trained to operate a light microscope. The replacement of old technologies by new is discussed. The fundamental question is whether all podiatric physicians should be trained in the use of a particular tool or only those who are likely to use it in their own practice.

Elevated heart rate triggers action potential alternans and sudden death. translational study of a homozygous KCNH2 mutation.

PubMed

Schweigmann, Ulrich; Biliczki, Peter; Ramirez, Rafael J; Marschall, Christoph; Takac, Ina; Brandes, Ralf P; Kotzot, Dieter; Girmatsion, Zenawit; Hohnloser, Stefan H; Ehrlich, Joachim R

2014-01-01

Long QT syndrome (LQTS) leads to arrhythmic events and increased risk for sudden cardiac death (SCD). Homozygous KCNH2 mutations underlying LQTS-2 have previously been termed "human HERG knockout" and typically express severe phenotypes. We studied genotype-phenotype correlations of an LQTS type 2 mutation identified in the homozygous index patient from a consanguineous Turkish family after his brother died suddenly during febrile illness. Clinical work-up, DNA sequencing, mutagenesis, cell culture, patch-clamp, in silico mathematical modelling, protein biochemistry, confocal microscopy were performed. Genetic analysis revealed a homozygous C-terminal KCNH2 mutation (p.R835Q) in the index patient (QTc ∼506 ms with notched T waves). Parents were I° cousins - both heterozygous for the mutation and clinically unremarkable (QTc ∼447 ms, father and ∼396 ms, mother). Heterologous expression of KCNH2-R835Q showed mildly reduced current amplitudes. Biophysical properties of ionic currents were also only nominally changed with slight acceleration of deactivation and more negative V50 in R835Q-currents. Protein biochemistry and confocal microscopy revealed similar expression patterns and trafficking of WT and R835Q, even at elevated temperature. In silico analysis demonstrated mildly prolonged ventricular action potential duration (APD) compared to WT at a cycle length of 1000 ms. At a cycle length of 350 ms M-cell APD remained stable in WT, but displayed APD alternans in R835Q. Kv11.1 channels affected by the C-terminal R835Q mutation display mildly modified biophysical properties, but leads to M-cell APD alternans with elevated heart rate and could precipitate SCD under specific clinical circumstances associated with high heart rates.

Electron microscopy, histochemistry, and microbiology of bacterial adhesion in trichomycosis axillaris.

PubMed

Shelley, W B; Miller, M A

1984-06-01

Study of a case of trichomycosis axillaris by electron microscopy revealed a specific encapsulated Corynebacterium adhering to but not penetrating the hair shaft. External to this were two other biochemically distinctive pleomorphic Corynebacteria shown to be incapable of direct adherence to the hair. All three types were entrapped in a virtually insoluble cement substance, which they elaborate and which is responsible for the grossly visible colonization that is so characteristic of this disease.

Novel Mycosin Protease MycP1 Inhibitors Identified by Virtual Screening and 4D Fingerprints

PubMed Central

2015-01-01

The rise of drug-resistant Mycobacterium tuberculosis lends urgency to the need for new drugs for the treatment of tuberculosis (TB). The identification of a serine protease, mycosin protease-1 (MycP1), as the crucial agent in hydrolyzing the virulence factor, ESX-secretion-associated protein B (EspB), potentially opens the door to new tuberculosis treatment options. Using the crystal structure of mycobacterial MycP1 in the apo form, we performed an iterative ligand- and structure-based virtual screening (VS) strategy to identify novel, nonpeptide, small-molecule inhibitors against MycP1 protease. Screening of ∼485 000 ligands from databases at the Genomics Research Institute (GRI) at the University of Cincinnati and the National Cancer Institute (NCI) using our VS approach, which integrated a pharmacophore model and consensus molecular shape patterns of active ligands (4D fingerprints), identified 81 putative inhibitors, and in vitro testing subsequently confirmed two of them as active inhibitors. Thereafter, the lead structures of each VS round were used to generate a new 4D fingerprint that enabled virtual rescreening of the chemical libraries. Finally, the iterative process identified a number of diverse scaffolds as lead compounds that were tested and found to have micromolar IC50 values against the MycP1 target. This study validated the efficiency of the SABRE 4D fingerprints as a means of identifying novel lead compounds in each screening round of the databases. Together, these results underscored the value of using a combination of in silico iterative ligand- and structure-based virtual screening of chemical libraries with experimental validation for the identification of promising structural scaffolds, such as the MycP1 inhibitors. PMID:24628123

Nanotechnology: toxicologic pathology.

PubMed

Hubbs, Ann F; Sargent, Linda M; Porter, Dale W; Sager, Tina M; Chen, Bean T; Frazer, David G; Castranova, Vincent; Sriram, Krishnan; Nurkiewicz, Timothy R; Reynolds, Steven H; Battelli, Lori A; Schwegler-Berry, Diane; McKinney, Walter; Fluharty, Kara L; Mercer, Robert R

2013-02-01

Nanotechnology involves technology, science, and engineering in dimensions less than 100 nm. A virtually infinite number of potential nanoscale products can be produced from many different molecules and their combinations. The exponentially increasing number of nanoscale products will solve critical needs in engineering, science, and medicine. However, the virtually infinite number of potential nanotechnology products is a challenge for toxicologic pathologists. Because of their size, nanoparticulates can have therapeutic and toxic effects distinct from micron-sized particulates of the same composition. In the nanoscale, distinct intercellular and intracellular translocation pathways may provide a different distribution than that obtained by micron-sized particulates. Nanoparticulates interact with subcellular structures including microtubules, actin filaments, centrosomes, and chromatin; interactions that may be facilitated in the nanoscale. Features that distinguish nanoparticulates from fine particulates include increased surface area per unit mass and quantum effects. In addition, some nanotechnology products, including the fullerenes, have a novel and reactive surface. Augmented microscopic procedures including enhanced dark-field imaging, immunofluorescence, field-emission scanning electron microscopy, transmission electron microscopy, and confocal microscopy are useful when evaluating nanoparticulate toxicologic pathology. Thus, the pathology assessment is facilitated by understanding the unique features at the nanoscale and the tools that can assist in evaluating nanotoxicology studies.

Nanotechnology: Toxicologic Pathology

PubMed Central

Hubbs, Ann F.; Sargent, Linda M.; Porter, Dale W.; Sager, Tina M.; Chen, Bean T.; Frazer, David G.; Castranova, Vincent; Sriram, Krishnan; Nurkiewicz, Timothy R.; Reynolds, Steven H.; Battelli, Lori A.; Schwegler-Berry, Diane; McKinney, Walter; Fluharty, Kara L.; Mercer, Robert R.

2015-01-01

Nanotechnology involves technology, science, and engineering in dimensions less than 100 nm. A virtually infinite number of potential nanoscale products can be produced from many different molecules and their combinations. The exponentially increasing number of nanoscale products will solve critical needs in engineering, science, and medicine. However, the virtually infinite number of potential nanotechnology products is a challenge for toxicologic pathologists. Because of their size, nanoparticulates can have therapeutic and toxic effects distinct from micron-sized particulates of the same composition. In the nanoscale, distinct intercellular and intracellular translocation pathways may provide a different distribution than that obtained by micron-sized particulates. Nanoparticulates interact with subcellular structures including microtubules, actin filaments, centrosomes, and chromatin; interactions that may be facilitated in the nanoscale. Features that distinguish nanoparticulates from fine particulates include increased surface area per unit mass and quantum effects. In addition, some nanotechnology products, including the fullerenes, have a novel and reactive surface. Augmented microscopic procedures including enhanced dark-field imaging, immunofluorescence, field-emission scanning electron microscopy, transmission electron microscopy, and confocal microscopy are useful when evaluating nanoparticulate toxicologic pathology. Thus, the pathology assessment is facilitated by understanding the unique features at the nanoscale and the tools that can assist in evaluating nanotoxicology studies. PMID:23389777

A Canopy Architectural Model to Study the Competitive Ability of Chickpea with Sowthistle

PubMed Central

Cici, S-Zahra-Hosseini; Adkins, Steve; Hanan, Jim

2008-01-01

Background and Aims Improving the competitive ability of crops is a sustainable method of weed management. This paper shows how a virtual plant model of competition between chickpea (Cicer arietinum) and sowthistle (Sonchus oleraceus) can be used as a framework for discovering and/or developing more competitive chickpea cultivars. Methods The virtual plant models were developed using the L-systems formalism, parameterized according to measurements taken on plants at intervals during their development. A quasi-Monte Carlo light-environment model was used to model the effect of chickpea canopy on the development of sowthistle. The chickpea–light environment–sowthistle model (CLES model) captured the hypothesis that the architecture of chickpea plants modifies the light environment inside the canopy and determines sowthistle growth and development pattern. The resulting CLES model was parameterized for different chickpea cultivars (viz. ‘Macarena’, ‘Bumper’, ‘Jimbour’ and ‘99071-1001’) to compare their competitive ability with sowthistle. To validate the CLES model, an experiment was conducted using the same four chickpea cultivars as different treatments with a sowthistle growing under their canopy. Results and Conclusions The growth of sowthistle, both in silico and in glasshouse experiments, was reduced most by ‘99071-1001’, a cultivar with a short phyllochron. The second rank of competitive ability belonged to ‘Macarena’ and ‘Bumper’, while ‘Jimbour’ was the least competitive cultivar. The architecture of virtual chickpea plants modified the light inside the canopy, which influenced the growth and development of the sowthistle plants in response to different cultivars. This is the first time that a virtual plant model of a crop–weed interaction has been developed. This virtual plant model can serve as a platform for a broad range of applications in the study of chickpea–weed interactions and their environment. PMID:18375962

Fast Two-Dimensional Bubble Analysis of Biopolymer Filamentous Networks Pore Size from Confocal Microscopy Thin Data Stacks

PubMed Central

Molteni, Matteo; Magatti, Davide; Cardinali, Barbara; Rocco, Mattia; Ferri, Fabio

2013-01-01

The average pore size ξ0 of filamentous networks assembled from biological macromolecules is one of the most important physical parameters affecting their biological functions. Modern optical methods, such as confocal microscopy, can noninvasively image such networks, but extracting a quantitative estimate of ξ0 is a nontrivial task. We present here a fast and simple method based on a two-dimensional bubble approach, which works by analyzing one by one the (thresholded) images of a series of three-dimensional thin data stacks. No skeletonization or reconstruction of the full geometry of the entire network is required. The method was validated by using many isotropic in silico generated networks of different structures, morphologies, and concentrations. For each type of network, the method provides accurate estimates (a few percent) of the average and the standard deviation of the three-dimensional distribution of the pore sizes, defined as the diameters of the largest spheres that can be fit into the pore zones of the entire gel volume. When applied to the analysis of real confocal microscopy images taken on fibrin gels, the method provides an estimate of ξ0 consistent with results from elastic light scattering data. PMID:23473499

Identification of some novel pyrazolo[1,5-a]pyrimidine derivatives as InhA inhibitors through pharmacophore-based virtual screening and molecular docking.

PubMed

Modi, Palmi; Patel, Shivani; Chhabria, Mahesh T

2018-05-04

The InhA inhibitors play key role in mycolic acid synthesis by preventing the fatty acid biosynthesis pathway. In this present article, Pharmacophore modelling and molecular docking study followed by in silico virtual screening could be considered as effective strategy to identify newer enoyl-ACP reductase inhibitors. Pyrrolidine carboxamide derivatives were opted to generate pharmacophore models using HypoGen algorithm in Discovery studio 2.1. Further it was employed to screen Zinc and Minimaybridge databases to identify and design newer potent hit molecules. The retrieved newer hits were further evaluated for their drug likeliness and docked against enoyl acyl carrier protein reductase. Here, novel pyrazolo[1,5-a]pyrimidine analogues were designed and synthesized with good yields. Structural elucidation of synthesized final molecules was perform through IR, MASS, 1 H-NMR, 13 C-NMR spectroscopy and further tested for its in vitro anti-tubercular activity against H37Rv strain using Microplate Alamar blue assay (MABA) method. Most of the synthesized compounds displayed strong anti-tubercular activities. Further, these potent compounds were gauged for MDR-TB, XDR-TB and cytotoxic study.

Discovery of novel and cardioselective diltiazem-like calcium channel blockers via virtual screening.

PubMed

Carosati, Emanuele; Budriesi, Roberta; Ioan, Pierfranco; Ugenti, Maria P; Frosini, Maria; Fusi, Fabio; Corda, Gaetano; Cosimelli, Barbara; Spinelli, Domenico; Chiarini, Alberto; Cruciani, Gabriele

2008-09-25

With the effort to discover new chemotypes blocking L-type calcium channels (LTCCs), ligand-based virtual screening was applied with a specific interest toward the diltiazem binding site. Roughly 50000 commercially available compounds served as a database for screening. The filtering through predicted pharmacokinetic properties and structural requirements reduced the initial database to a few compounds for which the similarity was calculated toward two template molecules, diltiazem and 4-chloro-Ncyclopropyl- N-(4-piperidinyl)benzene-sulfonamide, the most interesting hit of a previous screening experiment. For 18 compounds, inotropic and chronotropic activity as well as the vasorelaxant effect on guinea pig were studied "in vitro", and for the most promising, binding studies to the diltiazem site were carried out. The procedure yielded several hits, confirming in silico techniques to be useful for finding new chemotypes. In particular, N-[2-(dimethylamino)ethyl]-3-hydroxy-2-naphthamide, N,Ndimethyl- N'-(2-pyridin-3-ylquinolin-4-yl)ethane-1,2-diamine, 2-[(4-chlorophenyl)(pyridin-2-yl)methoxy]- N,N-dimethylethanamine (carbinoxamine), and 7-[2-(diethylamino)ethoxy]-2H-chromen-2-one revealed interesting activity and binding to the benzothiazepine site.

The EuroPhysiome, STEP and a roadmap for the virtual physiological human.

PubMed

Fenner, J W; Brook, B; Clapworthy, G; Coveney, P V; Feipel, V; Gregersen, H; Hose, D R; Kohl, P; Lawford, P; McCormack, K M; Pinney, D; Thomas, S R; Van Sint Jan, S; Waters, S; Viceconti, M

2008-09-13

Biomedical science and its allied disciplines are entering a new era in which computational methods and technologies are poised to play a prevalent role in supporting collaborative investigation of the human body. Within Europe, this has its focus in the virtual physiological human (VPH), which is an evolving entity that has emerged from the EuroPhysiome initiative and the strategy for the EuroPhysiome (STEP) consortium. The VPH is intended to be a solution to common infrastructure needs for physiome projects across the globe, providing a unifying architecture that facilitates integration and prediction, ultimately creating a framework capable of describing Homo sapiens in silico. The routine reliance of the biomedical industry, biomedical research and clinical practice on information technology (IT) highlights the importance of a tailor-made and robust IT infrastructure, but numerous challenges need to be addressed if the VPH is to become a mature technological reality. Appropriate investment will reap considerable rewards, since it is anticipated that the VPH will influence all sectors of society, with implications predominantly for improved healthcare, improved competitiveness in industry and greater understanding of (patho)physiological processes. This paper considers issues pertinent to the development of the VPH, highlighted by the work of the STEP consortium.

The Proximal Lilly Collection: Mapping, Exploring and Exploiting Feasible Chemical Space.

PubMed

Nicolaou, Christos A; Watson, Ian A; Hu, Hong; Wang, Jibo

2016-07-25

Venturing into the immensity of the small molecule universe to identify novel chemical structure is a much discussed objective of many methods proposed by the chemoinformatics community. To this end, numerous approaches using techniques from the fields of computational de novo design, virtual screening and reaction informatics, among others, have been proposed. Although in principle this objective is commendable, in practice there are several obstacles to useful exploitation of the chemical space. Prime among them are the sheer number of theoretically feasible compounds and the practical concern regarding the synthesizability of the chemical structures conceived using in silico methods. We present the Proximal Lilly Collection initiative implemented at Eli Lilly and Co. with the aims to (i) define the chemical space of small, drug-like compounds that could be synthesized using in-house resources and (ii) facilitate access to compounds in this large space for the purposes of ongoing drug discovery efforts. The implementation of PLC relies on coupling access to available synthetic knowledge and resources with chemo/reaction informatics techniques and tools developed for this purpose. We describe in detail the computational framework supporting this initiative and elaborate on the characteristics of the PLC virtual collection of compounds. As an example of the opportunities provided to drug discovery researchers by easy access to a large, realistically feasible virtual collection such as the PLC, we describe a recent application of the technology that led to the discovery of selective kinase inhibitors.

Small molecule correctors of F508del-CFTR discovered by structure-based virtual screening

NASA Astrophysics Data System (ADS)

Kalid, Ori; Mense, Martin; Fischman, Sharon; Shitrit, Alina; Bihler, Hermann; Ben-Zeev, Efrat; Schutz, Nili; Pedemonte, Nicoletta; Thomas, Philip J.; Bridges, Robert J.; Wetmore, Diana R.; Marantz, Yael; Senderowitz, Hanoch

2010-12-01

Folding correctors of F508del-CFTR were discovered by in silico structure-based screening utilizing homology models of CFTR. The intracellular segment of CFTR was modeled and three cavities were identified at inter-domain interfaces: (1) Interface between the two Nucleotide Binding Domains (NBDs); (2) Interface between NBD1 and Intracellular Loop (ICL) 4, in the region of the F508 deletion; (3) multi-domain interface between NBD1:2:ICL1:2:4. We hypothesized that compounds binding at these interfaces may improve the stability of the protein, potentially affecting the folding yield or surface stability. In silico structure-based screening was performed at the putative binding-sites and a total of 496 candidate compounds from all three sites were tested in functional assays. A total of 15 compounds, representing diverse chemotypes, were identified as F508del folding correctors. This corresponds to a 3% hit rate, tenfold higher than hit rates obtained in corresponding high-throughput screening campaigns. The same binding sites also yielded potentiators and, most notably, compounds with a dual corrector-potentiator activity (dual-acting). Compounds harboring both activity types may prove to be better leads for the development of CF therapeutics than either pure correctors or pure potentiators. To the best of our knowledge this is the first report of structure-based discovery of CFTR modulators.

Nimbolide targets BCL2 and induces apoptosis in preclinical models of Waldenströms macroglobulinemia

PubMed Central

Chitta, K; Paulus, A; Caulfield, T R; Akhtar, S; Blake, M-KK; Ailawadhi, S; Knight, J; Heckman, M G; Pinkerton, A; Chanan-Khan, A

2014-01-01

Neem leaf extract (NLE) has medicinal properties, which have been attributed to its limonoid content. We identified the NLE tetranorterpenoid, nimbolide, as being the key limonoid responsible for the cytotoxicity of NLE in various preclinical models of human B-lymphocyte cancer. Of the models tested, Waldenströms macroglobulinemia (WM) cells were most sensitive to nimbolide, undergoing significant mitochondrial mediated apoptosis. Notably, nimbolide toxicity was also observed in drug-resistant (bortezomib or ibrutinib) WM cells. To identify putative targets of nimbolide, relevant in WM, we used chemoinformatics-based approaches comprised of virtual in silico screening, molecular modeling and target–ligand reverse docking. In silico analysis revealed the antiapoptotic protein BCL2 was the preferential binding partner of nimbolide. The significance of this finding was further tested in vitro in RS4;11 (BCL2-dependent) tumor cells, in which nimbolide induced significantly more apoptosis compared with BCL2 mutated (Jurkat BCL2Ser70-Ala) cells. Lastly, intraperitoneal administration of nimbolide in WM tumor xenografted mice, significantly reduced tumor growth and IgM secretion in vivo, while modulating the expression of several proteins as seen on immunohistochemistry. Overall, our data demonstrate that nimbolide is highly active in WM cells, as well as other B-cell cancers, and engages BCL2 to exert its cytotoxic activity. PMID:25382610

An in silico high-throughput screen identifies potential selective inhibitors for the non-receptor tyrosine kinase Pyk2

PubMed Central

Meirson, Tomer; Samson, Abraham O; Gil-Henn, Hava

2017-01-01

The non-receptor tyrosine kinase proline-rich tyrosine kinase 2 (Pyk2) is a critical mediator of signaling from cell surface growth factor and adhesion receptors to cell migration, proliferation, and survival. Emerging evidence indicates that signaling by Pyk2 regulates hematopoietic cell response, bone density, neuronal degeneration, angiogenesis, and cancer. These physiological and pathological roles of Pyk2 warrant it as a valuable therapeutic target for invasive cancers, osteoporosis, Alzheimer’s disease, and inflammatory cellular response. Despite its potential as a therapeutic target, no potent and selective inhibitor of Pyk2 is available at present. As a first step toward discovering specific potential inhibitors of Pyk2, we used an in silico high-throughput screening approach. A virtual library of six million lead-like compounds was docked against four different high-resolution Pyk2 kinase domain crystal structures and further selected for predicted potency and ligand efficiency. Ligand selectivity for Pyk2 over focal adhesion kinase (FAK) was evaluated by comparative docking of ligands and measurement of binding free energy so as to obtain 40 potential candidates. Finally, the structural flexibility of a subset of the docking complexes was evaluated by molecular dynamics simulation, followed by intermolecular interaction analysis. These compounds may be considered as promising leads for further development of highly selective Pyk2 inhibitors. PMID:28572720

Antibody quantum dot conjugates developed via copper-free click chemistry for rapid analysis of biological samples using a microfluidic microsphere array system.

PubMed

Kotagiri, Nalinikanth; Li, Zhenyu; Xu, Xiaoxiao; Mondal, Suman; Nehorai, Arye; Achilefu, Samuel

2014-07-16

Antibody-based proteomics is an enabling technology that has significant implications for cancer biomarker discovery, diagnostic screening, prognostic and pharmacodynamic evaluation of disease state, and targeted therapeutics. Quantum dot based fluoro-immunoconjugates possess promising features toward realization of this goal such as high photostability, brightness, and multispectral tunability. However, current strategies to generate such conjugates are riddled with complications such as improper orientation of antigen binding sites of the antibody, aggregation, and stability issues. We report a facile yet effective strategy to conjugate anti-epidermal growth factor receptor (EGFR) antibody to quantum dots using copper-free click reaction, and compared them to similar constructs prepared using traditional strategies such as succinimidyl-4-(N-maleimidomethyl) cyclohexane-1-carboxylate (SMCC) and biotin-streptavidin schemes. The Fc and Fab regions of the conjugates retain their binding potential, compared to those generated through the traditional schemes. We further applied the conjugates in testing a novel microsphere array device designed to carry out sensitive detection of cancer biomarkers through fluoroimmunoassays. Using purified EGFR, we determined the limit of detection of the microscopy centric system to be 12.5 ng/mL. The biological assay, in silico, was successfully tested and validated by using tumor cell lysates, as well as human serum from breast cancer patients, and the results were compared to normal serum. A pattern consistent with established clinical data was observed, which further validates the effectiveness of the developed conjugates and its successful implementation both in vitro as well as in silico fluoroimmunoassays. The results suggest the potential development of a high throughput in silico paradigm for predicting the class of patient cancer based on EGFR expression levels relative to normal reference levels in blood.

Isolation, characterization and in silico docking studies of synergistic estrogen receptor a anticancer polyphenols from Syzygium alternifolium (Wt.) Walp.

PubMed Central

Yugandhar, Pulicherla; Kumar, Konidala Kranthi; Neeraja, Pabbaraju; Savithramma, Nataru

2017-01-01

Aim: This study aims to isolate, characterize, and in silico evaluate of anticancer polyphenols from different parts of Syzygium alternifolium. Materials and Methods: The polyphenols were isolated by standard protocol and characterized using Fourier-transform infrared (FT-IR), High performance liquid chromatography - Photodiode array detector coupled with Electrospray ionization - mass spectrometry (MS/MS). The compounds were elucidated based on retention time and molecular ions (m/z) either by [M+H]+/[M-H]− with the comparison of standard phenols as well as ReSpect software tool. Furthermore, absorption, distribution, metabolism, and excretion (ADME)/toxicity properties of selected phenolic scaffolds were screened using OSIRIS and SwissADME programs, which incorporate toxicity risk assessments, pharmacokinetics, and rule of five principles. Molecular docking studies were carried out for selected toxicity filtered compounds against breast cancer estrogen receptor a (ERa) structure (protein data bank-ID: 1A52) through AutoDock scoring functions by PyRx virtual screening program. Results: The obtained results showed two intensive peaks in each polyphenol fraction analyzed with FT-IR, confirms O-H/C-O stretch of the phenolic functional group. A total of 40 compounds were obtained, which categorized as 9 different classes. Among them, flavonol group represents more number of polyphenols. In silico studies suggest seven compounds have the possibility to use as future nontoxic inhibitors. Molecular docking studies with ERa revealed the lead molecules unequivocally interact with Leu346, Glu353, Leu391, Arg394, Gly521, Leu525 residues, and Phe404 formed atomic π-stacking with dihydrochromen-4-one ring of ligands as like estrodial, which stabilizes the receptor structure and complicated to generate a single mutation for drug resistance. Conclusion: Overall, these results significantly proposed that isolated phenolics could be served as potential ER mitigators for breast cancer therapy. PMID:28894629

The PILGRIM study: in silico modeling of a predictive low glucose management system and feasibility in youth with type 1 diabetes during exercise.

PubMed

Danne, Thomas; Tsioli, Christiana; Kordonouri, Olga; Blaesig, Sarah; Remus, Kerstin; Roy, Anirban; Keenan, Barry; Lee, Scott W; Kaufman, Francine R

2014-06-01

Predictive low glucose management (PLGM) may help prevent hypoglycemia by stopping insulin pump delivery based on predicted sensor glucose values. Hypoglycemic challenges were simulated using the Food and Drug Administration-accepted glucose simulator with 100 virtual patients. PLGM was then tested with a system composed of a Paradigm(®) insulin pump (Medtronic, Northridge, CA), an Enlite™ glucose sensor (Medtronic), and a BlackBerry(®) (Waterloo, ON, Canada)-based controller. Subjects (n=22) on continuous subcutaneous insulin infusion (five females, 17 males; median [range] age, 15 [range, 14-20] years; median [range] diabetes duration, 7 [2-14] years; median [range] glycated hemoglobin, 8.0% [6.7-10.4%]) exercised until the PLGM system suspended insulin delivery or until the reference blood glucose value (HemoCue(®); HemoCue GmbH, Großostheim, Germany) reached the predictive suspension threshold setting. PLGM reduced hypoglycemia (<70 mg/dL) in silico by 26.7% compared with no insulin suspension, as opposed to a 5.3% reduction in hypoglycemia with use of low glucose suspend (LGS). The median duration of hypoglycemia (time spent <70 mg/dL) with PLGM was significantly less than with LGS (58 min vs. 101 min, respectively; P<0.001). In the clinical trial the hypoglycemic threshold during exercise was reached in 73% of the patients, and hypoglycemia was prevented in 80% of the successful experiments. The mean (±SD) sensor glucose at predictive suspension was 92±7 mg/dL, resulting in a postsuspension nadir (by HemoCue) of 77±22 mg/dL. The suspension lasted for 90±35 (range, 30-120) min, resulting in a sensor glucose level at insulin resumption of 97±19 mg/dL. In silico modeling and early feasibility data demonstrate that PLGM may further reduce the severity of hypoglycemia beyond that already established for algorithms that use a threshold-based suspension.

[Dynamics of Irreversible Evaporation of a Water-Protein Droplet and a Problem of Structural and Dynamical Experiments with Single Molecules].

PubMed

Shaitan, K V; Armeev, G A; Shaytan, A K

2016-01-01

We discuss the effect of isothermal and adiabatic evaporation of water on the state of a water-protein droplet. The discussed problem is of current importance due to development of techniques to perform single molecule experiments using free electron lasers. In such structure-dynamic experiments the delivery of a sample into the X-ray beam is performed using the microdroplet injector. The time between the injection and delivery is in the order of microseconds. In this paper we developed a specialized variant of all-atom molecular dynamics simulations for the study of irreversible isothermal evaporation of the droplet. Using in silico experiments we determined the parameters of isothermal evaporation of the water-protein droplet with the sodium and chloride ions in the concentration range of 0.3 M at different temperatures. The energy of irreversible evaporation determined from in silico experiments at the initial stages of evaporation virtually coincides with the specific heat of evaporation for water. For the kinetics of irreversible adiabatic evaporation an exact analytical solution was obtained in the limit of high thermal conductivity of the droplet (or up to the droplet size of -100 Å). This analytical solution incorporates parameters that are determined using in silico. experiments on isothermal droplet evaporation. We show that the kinetics of adiabatic evaporation and cooling of the droplet scales with the droplet size. Our estimates of the water-protemi droplet. freezing rate in the adiabatic regime in a vacuum chamber show that additional techniques for stabilizing the temperature inside the droplet should be used in order to study the conformational transitions of the protein in single molecules. Isothermal and quasi-isothermal conditions are most suitable for studying the conformational transitions upon object functioning. However, in this case it is necessary to take into account the effects of dehydration and rapid increase of ionic strength in an aqueous microenvironment surrounding the protein.

Examining the Real Merits of the Virtual Microscope

NASA Astrophysics Data System (ADS)

Hennessy, Ronan; Meere, Pat; Ho, Timsie; Menuge, Julian; Tyrrell, Shane; Kamber, Balz; Higgs, Bettie; Kelley, Simon

2017-04-01

The Geoscience e-Laboratory (GeoLAB) project is a cooperative digital petrological microscopy technology enhanced learning (TEL) resource development project involving the four main university geoscience teaching centres in Ireland. Collaborating with the Open University (UK), a new digital library of petrographic thin sections has been added to the Virtual Microscope for Earth Sciences (VMfES) online repository. The collection was compiled with a view to introducing high-quality samples to teaching programmes in a manner that hitherto was limited by sample and microscope availability and cost and the temporal limits of laboratory access. The project has proceeded to explore the pedagogical implications of using the Virtual Microscope in teaching programmes. Online assessments and self-guided exercises developed using applications such as Google Forms have been introduced into programmes at each centre, and complimented by tutorial and interactive videos designed to support self-guided learning. The GeoLab project is reporting on the pedagogical implications of providing students with unimpeded access to high-quality petrographic learning resources during the term of semester and in advance of student assessments. Additionally, the project is collating data on the perceptions of both teachers and learners to using online learning media in mineralogy and petrology programmes, and if there are benefits therein to the more traditional styles of petrology and microscopy teaching and learning.

Simulation and performance analysis of a novel high-accuracy sheathless microfluidic impedance cytometer with coplanar electrode layout.

PubMed

Caselli, Federica; Bisegna, Paolo

2017-10-01

The performance of a novel microfluidic impedance cytometer (MIC) with coplanar configuration is investigated in silico. The main feature of the device is the ability to provide accurate particle-sizing despite the well-known measurement sensitivity to particle trajectory. The working principle of the device is presented and validated by means of an original virtual laboratory providing close-to-experimental synthetic data streams. It is shown that a metric correlating with particle trajectory can be extracted from the signal traces and used to compensate the trajectory-induced error in the estimated particle size, thus reaching high-accuracy. An analysis of relevant parameters of the experimental setup is also presented. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Developing science gateways for drug discovery in a grid environment.

PubMed

Pérez-Sánchez, Horacio; Rezaei, Vahid; Mezhuyev, Vitaliy; Man, Duhu; Peña-García, Jorge; den-Haan, Helena; Gesing, Sandra

2016-01-01

Methods for in silico screening of large databases of molecules increasingly complement and replace experimental techniques to discover novel compounds to combat diseases. As these techniques become more complex and computationally costly we are faced with an increasing problem to provide the research community of life sciences with a convenient tool for high-throughput virtual screening on distributed computing resources. To this end, we recently integrated the biophysics-based drug-screening program FlexScreen into a service, applicable for large-scale parallel screening and reusable in the context of scientific workflows. Our implementation is based on Pipeline Pilot and Simple Object Access Protocol and provides an easy-to-use graphical user interface to construct complex workflows, which can be executed on distributed computing resources, thus accelerating the throughput by several orders of magnitude.

Revealing the first uridyl peptide antibiotic biosynthetic gene cluster and probing pacidamycin biosynthesis.

PubMed

Rackham, Emma J; Grüschow, Sabine; Goss, Rebecca J M

2011-01-01

There is an urgent need for new antibiotics with resistance continuing to emerge toward existing classes. The pacidamycin antibiotics possess a novel scaffold and exhibit unexploited bioactivity rendering them attractive research targets. We recently reported the first identification of a biosynthetic cluster encoding uridyl peptide antibiotic assembly and the engineering of pacidamycin biosynthesis into a heterologous host. We report here our methods toward identifying the biosynthetic cluster. Our initial experiments employed conventional methods of probing a cosmid library using PCR and Southern blotting, however it became necessary to adopt a state-of-the-art genome scanning  and in silico hybridization approach  to pin point the cluster. Here we describe our "real" and "virtual" probing methods and contrast the benefits and pitfalls of each approach. 

Small molecule inhibitors of ERCC1-XPF protein-protein interaction synergize alkylating agents in cancer cells.

PubMed

Jordheim, Lars Petter; Barakat, Khaled H; Heinrich-Balard, Laurence; Matera, Eva-Laure; Cros-Perrial, Emeline; Bouledrak, Karima; El Sabeh, Rana; Perez-Pineiro, Rolando; Wishart, David S; Cohen, Richard; Tuszynski, Jack; Dumontet, Charles

2013-07-01

The benefit of cancer chemotherapy based on alkylating agents is limited because of the action of DNA repair enzymes, which mitigate the damage induced by these agents. The interaction between the proteins ERCC1 and XPF involves two major components of the nucleotide excision repair pathway. Here, novel inhibitors of this interaction were identified by virtual screening based on available structures with use of the National Cancer Institute diversity set and a panel of DrugBank small molecules. Subsequently, experimental validation of the in silico screening was undertaken. Top hits were evaluated on A549 and HCT116 cancer cells. In particular, the compound labeled NSC 130813 [4-[(6-chloro-2-methoxy-9-acridinyl)amino]-2-[(4-methyl-1-piperazinyl)methyl

A workflow to process 3D+time microscopy images of developing organisms and reconstruct their cell lineage

PubMed Central

Faure, Emmanuel; Savy, Thierry; Rizzi, Barbara; Melani, Camilo; Stašová, Olga; Fabrèges, Dimitri; Špir, Róbert; Hammons, Mark; Čúnderlík, Róbert; Recher, Gaëlle; Lombardot, Benoît; Duloquin, Louise; Colin, Ingrid; Kollár, Jozef; Desnoulez, Sophie; Affaticati, Pierre; Maury, Benoît; Boyreau, Adeline; Nief, Jean-Yves; Calvat, Pascal; Vernier, Philippe; Frain, Monique; Lutfalla, Georges; Kergosien, Yannick; Suret, Pierre; Remešíková, Mariana; Doursat, René; Sarti, Alessandro; Mikula, Karol; Peyriéras, Nadine; Bourgine, Paul

2016-01-01

The quantitative and systematic analysis of embryonic cell dynamics from in vivo 3D+time image data sets is a major challenge at the forefront of developmental biology. Despite recent breakthroughs in the microscopy imaging of living systems, producing an accurate cell lineage tree for any developing organism remains a difficult task. We present here the BioEmergences workflow integrating all reconstruction steps from image acquisition and processing to the interactive visualization of reconstructed data. Original mathematical methods and algorithms underlie image filtering, nucleus centre detection, nucleus and membrane segmentation, and cell tracking. They are demonstrated on zebrafish, ascidian and sea urchin embryos with stained nuclei and membranes. Subsequent validation and annotations are carried out using Mov-IT, a custom-made graphical interface. Compared with eight other software tools, our workflow achieved the best lineage score. Delivered in standalone or web service mode, BioEmergences and Mov-IT offer a unique set of tools for in silico experimental embryology. PMID:26912388

Pore Breathing of Metal-Organic Frameworks by Environmental Transmission Electron Microscopy.

PubMed

Parent, Lucas R; Pham, C Huy; Patterson, Joseph P; Denny, Michael S; Cohen, Seth M; Gianneschi, Nathan C; Paesani, Francesco

2017-10-11

Metal-organic frameworks (MOFs) have emerged as a versatile platform for the rational design of multifunctional materials, combining large specific surface areas with flexible, periodic frameworks that can undergo reversible structural transitions, or "breathing", upon temperature and pressure changes, and through gas adsorption/desorption processes. Although MOF breathing can be inferred from the analysis of adsorption isotherms, direct observation of the structural transitions has been lacking, and the underlying processes of framework reorganization in individual MOF nanocrystals is largely unknown. In this study, we describe the characterization and elucidation of these processes through the combination of in situ environmental transmission electron microscopy (ETEM) and computer simulations. This combined approach enables the direct monitoring of the breathing behavior of individual MIL-53(Cr) nanocrystals upon reversible water adsorption and temperature changes. The ability to characterize structural changes in single nanocrystals and extract lattice level information through in silico correlation provides fundamental insights into the relationship between pore size/shape and host-guest interactions.

A virtual size-variable pinhole for single photon confocal microscopy

NASA Astrophysics Data System (ADS)

Gao, Guangjun; Khoobehi, Bahram

2013-03-01

Pinhole is a critical device in single photon confocal microscopy (SPCM) owning to its ability to block the background noise scattered from back and forth of the focal plane. Without pinhole, the sectioning ability of SPCM will be degraded and many background noise signals will occurred together with useful signals, and sometimes these bad noises can submerge the details that we are interested in. However a pinhole with too small diameter will block both background noises and part of signals and decrease the intensity of the image. Therefore in many cases pinhole size should be selected carefully. Unfortunately because of constrains in mechanics, a pinhole that can change its size continuously, for example from 10 μm to 100 μm, is unavailable. For most commercial confocal microscopies, only several discrete pinhole sizes are provided, such as 10 μm, 30 μm, 60 μm etc. Things will be even harder for some imaging systems which use the input interface of a single mode fiber as the pinhole of SPCM, and then the pinhole size of these systems will be fixed, which far limit the optimization of systems' performance. In this paper, we design a size-variable pinhole setup that can offer a virtual pinhole with its diameter adjustable, which includes a physical pinhole (or single mode fiber) and a fine designed zoom relay (ZR) optical system. The magnification ratio of this ZR can vary smoothly while keeping the conjugation distance unchanged. The aberrations of the ZR are well balanced and diffraction-limited image performance are obtained so that the virtual pinhole can block background scattering noise and pass the in-focus signal effectively and accurately. Simulation results are also provided and discussed.

Quantitative pathology in virtual microscopy: history, applications, perspectives.

PubMed

Kayser, Gian; Kayser, Klaus

2013-07-01

With the emerging success of commercially available personal computers and the rapid progress in the development of information technologies, morphometric analyses of static histological images have been introduced to improve our understanding of the biology of diseases such as cancer. First applications have been quantifications of immunohistochemical expression patterns. In addition to object counting and feature extraction, laws of thermodynamics have been applied in morphometric calculations termed syntactic structure analysis. Here, one has to consider that the information of an image can be calculated for separate hierarchical layers such as single pixels, cluster of pixels, segmented small objects, clusters of small objects, objects of higher order composed of several small objects. Using syntactic structure analysis in histological images, functional states can be extracted and efficiency of labor in tissues can be quantified. Image standardization procedures, such as shading correction and color normalization, can overcome artifacts blurring clear thresholds. Morphometric techniques are not only useful to learn more about biological features of growth patterns, they can also be helpful in routine diagnostic pathology. In such cases, entropy calculations are applied in analogy to theoretical considerations concerning information content. Thus, regions with high information content can automatically be highlighted. Analysis of the "regions of high diagnostic value" can deliver in the context of clinical information, site of involvement and patient data (e.g. age, sex), support in histopathological differential diagnoses. It can be expected that quantitative virtual microscopy will open new possibilities for automated histological support. Automated integrated quantification of histological slides also serves for quality assurance. The development and theoretical background of morphometric analyses in histopathology are reviewed, as well as their application and potential future implementation in virtual microscopy. Copyright © 2012 Elsevier GmbH. All rights reserved.

Direct comparison between confocal and multiphoton microscopy for rapid histopathological evaluation of unfixed human breast tissue.

PubMed

Yoshitake, Tadayuki; Giacomelli, Michael G; Cahill, Lucas C; Schmolze, Daniel B; Vardeh, Hilde; Faulkner-Jones, Beverly E; Connolly, James L; Fujimoto, James G

2016-12-01

Rapid histopathological examination of surgical specimen margins using fluorescence microscopy during breast conservation therapy has the potential to reduce the rate of positive margins on postoperative histopathology and the need for repeat surgeries. To assess the suitability of imaging modalities, we perform a direct comparison between confocal fluorescence microscopy and multiphoton microscopy for imaging unfixed tissue and compare to paraffin-embedded histology. An imaging protocol including dual channel detection of two contrast agents to implement virtual hematoxylin and eosin images is introduced that provides high quality imaging under both one and two photon excitation. Corresponding images of unfixed human breast tissue show that both confocal and multiphoton microscopy can reproduce the appearance of conventional histology without the need for physical sectioning. We further compare normal breast tissue and invasive cancer specimens imaged at multiple magnifications, and assess the effects of photobleaching for both modalities using the staining protocol. The results demonstrate that confocal fluorescence microscopy is a promising and cost-effective alternative to multiphoton microscopy for rapid histopathological evaluation of ex vivo breast tissue.

Direct comparison between confocal and multiphoton microscopy for rapid histopathological evaluation of unfixed human breast tissue

PubMed Central

Yoshitake, Tadayuki; Giacomelli, Michael G.; Cahill, Lucas C.; Schmolze, Daniel B.; Vardeh, Hilde; Faulkner-Jones, Beverly E.; Connolly, James L.; Fujimoto, James G.

2016-01-01

Abstract. Rapid histopathological examination of surgical specimen margins using fluorescence microscopy during breast conservation therapy has the potential to reduce the rate of positive margins on postoperative histopathology and the need for repeat surgeries. To assess the suitability of imaging modalities, we perform a direct comparison between confocal fluorescence microscopy and multiphoton microscopy for imaging unfixed tissue and compare to paraffin-embedded histology. An imaging protocol including dual channel detection of two contrast agents to implement virtual hematoxylin and eosin images is introduced that provides high quality imaging under both one and two photon excitation. Corresponding images of unfixed human breast tissue show that both confocal and multiphoton microscopy can reproduce the appearance of conventional histology without the need for physical sectioning. We further compare normal breast tissue and invasive cancer specimens imaged at multiple magnifications, and assess the effects of photobleaching for both modalities using the staining protocol. The results demonstrate that confocal fluorescence microscopy is a promising and cost-effective alternative to multiphoton microscopy for rapid histopathological evaluation of ex vivo breast tissue. PMID:28032121

Direct comparison between confocal and multiphoton microscopy for rapid histopathological evaluation of unfixed human breast tissue

NASA Astrophysics Data System (ADS)

Yoshitake, Tadayuki; Giacomelli, Michael G.; Cahill, Lucas C.; Schmolze, Daniel B.; Vardeh, Hilde; Faulkner-Jones, Beverly E.; Connolly, James L.; Fujimoto, James G.

2016-12-01

Rapid histopathological examination of surgical specimen margins using fluorescence microscopy during breast conservation therapy has the potential to reduce the rate of positive margins on postoperative histopathology and the need for repeat surgeries. To assess the suitability of imaging modalities, we perform a direct comparison between confocal fluorescence microscopy and multiphoton microscopy for imaging unfixed tissue and compare to paraffin-embedded histology. An imaging protocol including dual channel detection of two contrast agents to implement virtual hematoxylin and eosin images is introduced that provides high quality imaging under both one and two photon excitation. Corresponding images of unfixed human breast tissue show that both confocal and multiphoton microscopy can reproduce the appearance of conventional histology without the need for physical sectioning. We further compare normal breast tissue and invasive cancer specimens imaged at multiple magnifications, and assess the effects of photobleaching for both modalities using the staining protocol. The results demonstrate that confocal fluorescence microscopy is a promising and cost-effective alternative to multiphoton microscopy for rapid histopathological evaluation of ex vivo breast tissue.

Computational tissue volume reconstruction of a peripheral nerve using high-resolution light-microscopy and reconstruct.

PubMed

Gierthmuehlen, Mortimer; Freiman, Thomas M; Haastert-Talini, Kirsten; Mueller, Alexandra; Kaminsky, Jan; Stieglitz, Thomas; Plachta, Dennis T T

2013-01-01

The development of neural cuff-electrodes requires several in vivo studies and revisions of the electrode design before the electrode is completely adapted to its target nerve. It is therefore favorable to simulate many of the steps involved in this process to reduce costs and animal testing. As the restoration of motor function is one of the most interesting applications of cuff-electrodes, the position and trajectories of myelinated fibers in the simulated nerve are important. In this paper, we investigate a method for building a precise neuroanatomical model of myelinated fibers in a peripheral nerve based on images obtained using high-resolution light microscopy. This anatomical model describes the first aim of our "Virtual workbench" project to establish a method for creating realistic neural simulation models based on image datasets. The imaging, processing, segmentation and technical limitations are described, and the steps involved in the transition into a simulation model are presented. The results showed that the position and trajectories of the myelinated axons were traced and virtualized using our technique, and small nerves could be reliably modeled based on of light microscopy images using low-cost OpenSource software and standard hardware. The anatomical model will be released to the scientific community.

Computational Tissue Volume Reconstruction of a Peripheral Nerve Using High-Resolution Light-Microscopy and Reconstruct

PubMed Central

Gierthmuehlen, Mortimer; Freiman, Thomas M.; Haastert-Talini, Kirsten; Mueller, Alexandra; Kaminsky, Jan; Stieglitz, Thomas; Plachta, Dennis T. T.

2013-01-01

The development of neural cuff-electrodes requires several in vivo studies and revisions of the electrode design before the electrode is completely adapted to its target nerve. It is therefore favorable to simulate many of the steps involved in this process to reduce costs and animal testing. As the restoration of motor function is one of the most interesting applications of cuff-electrodes, the position and trajectories of myelinated fibers in the simulated nerve are important. In this paper, we investigate a method for building a precise neuroanatomical model of myelinated fibers in a peripheral nerve based on images obtained using high-resolution light microscopy. This anatomical model describes the first aim of our “Virtual workbench” project to establish a method for creating realistic neural simulation models based on image datasets. The imaging, processing, segmentation and technical limitations are described, and the steps involved in the transition into a simulation model are presented. The results showed that the position and trajectories of the myelinated axons were traced and virtualized using our technique, and small nerves could be reliably modeled based on of light microscopy images using low-cost OpenSource software and standard hardware. The anatomical model will be released to the scientific community. PMID:23785485

Identification of STAT1 and STAT3 Specific Inhibitors Using Comparative Virtual Screening and Docking Validation

PubMed Central

Szelag, Malgorzata; Czerwoniec, Anna; Wesoly, Joanna; Bluyssen, Hans A. R.

2015-01-01

Signal transducers and activators of transcription (STATs) facilitate action of cytokines, growth factors and pathogens. STAT activation is mediated by a highly conserved SH2 domain, which interacts with phosphotyrosine motifs for specific STAT-receptor contacts and STAT dimerization. The active dimers induce gene transcription in the nucleus by binding to a specific DNA-response element in the promoter of target genes. Abnormal activation of STAT signaling pathways is implicated in many human diseases, like cancer, inflammation and auto-immunity. Searches for STAT-targeting compounds, exploring the phosphotyrosine (pTyr)-SH2 interaction site, yielded many small molecules for STAT3 but sparsely for other STATs. However, many of these inhibitors seem not STAT3-specific, thereby questioning the present modeling and selection strategies of SH2 domain-based STAT inhibitors. We generated new 3D structure models for all human (h)STATs and developed a comparative in silico docking strategy to obtain further insight into STAT-SH2 cross-binding specificity of a selection of previously identified STAT3 inhibitors. Indeed, by primarily targeting the highly conserved pTyr-SH2 binding pocket the majority of these compounds exhibited similar binding affinity and tendency scores for all STATs. By comparative screening of a natural product library we provided initial proof for the possibility to identify STAT1 as well as STAT3-specific inhibitors, introducing the ‘STAT-comparative binding affinity value’ and ‘ligand binding pose variation’ as selection criteria. In silico screening of a multi-million clean leads (CL) compound library for binding of all STATs, likewise identified potential specific inhibitors for STAT1 and STAT3 after docking validation. Based on comparative virtual screening and docking validation, we developed a novel STAT inhibitor screening tool that allows identification of specific STAT1 and STAT3 inhibitory compounds. This could increase our understanding of the functional role of these STATs in different diseases and benefit the clinical need for more drugable STAT inhibitors with high specificity, potency and excellent bioavailability. PMID:25710482

WISDOM-II: screening against multiple targets implicated in malaria using computational grid infrastructures.

PubMed

Kasam, Vinod; Salzemann, Jean; Botha, Marli; Dacosta, Ana; Degliesposti, Gianluca; Isea, Raul; Kim, Doman; Maass, Astrid; Kenyon, Colin; Rastelli, Giulio; Hofmann-Apitius, Martin; Breton, Vincent

2009-05-01

Despite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the Plasmodium parasite, some are promising targets to carry out rational drug discovery. Recent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR), and on a new promising one, glutathione-S-transferase. In silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate in silico docking and in information technology to design and operate large scale grid infrastructures. On the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, In vitro results are underway for all the targets against which screening is performed. The current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software on computational grids in finding hits against three different targets (PfGST, PfDHFR, PvDHFR (wild type and mutant forms) implicated in malaria. Grid-enabled virtual screening approach is proposed to produce focus compound libraries for other biological targets relevant to fight the infectious diseases of the developing world.

A calibrated agent-based computer model of stochastic cell dynamics in normal human colon crypts useful for in silico experiments.

PubMed

Bravo, Rafael; Axelrod, David E

2013-11-18

Normal colon crypts consist of stem cells, proliferating cells, and differentiated cells. Abnormal rates of proliferation and differentiation can initiate colon cancer. We have measured the variation in the number of each of these cell types in multiple crypts in normal human biopsy specimens. This has provided the opportunity to produce a calibrated computational model that simulates cell dynamics in normal human crypts, and by changing model parameter values, to simulate the initiation and treatment of colon cancer. An agent-based model of stochastic cell dynamics in human colon crypts was developed in the multi-platform open-source application NetLogo. It was assumed that each cell's probability of proliferation and probability of death is determined by its position in two gradients along the crypt axis, a divide gradient and in a die gradient. A cell's type is not intrinsic, but rather is determined by its position in the divide gradient. Cell types are dynamic, plastic, and inter-convertible. Parameter values were determined for the shape of each of the gradients, and for a cell's response to the gradients. This was done by parameter sweeps that indicated the values that reproduced the measured number and variation of each cell type, and produced quasi-stationary stochastic dynamics. The behavior of the model was verified by its ability to reproduce the experimentally observed monocolonal conversion by neutral drift, the formation of adenomas resulting from mutations either at the top or bottom of the crypt, and by the robust ability of crypts to recover from perturbation by cytotoxic agents. One use of the virtual crypt model was demonstrated by evaluating different cancer chemotherapy and radiation scheduling protocols. A virtual crypt has been developed that simulates the quasi-stationary stochastic cell dynamics of normal human colon crypts. It is unique in that it has been calibrated with measurements of human biopsy specimens, and it can simulate the variation of cell types in addition to the average number of each cell type. The utility of the model was demonstrated with in silico experiments that evaluated cancer therapy protocols. The model is available for others to conduct additional experiments.

Fluorescence Live Cell Imaging

PubMed Central

Ettinger, Andreas

2014-01-01

Fluorescence microscopy of live cells has become an integral part of modern cell biology. Fluorescent protein tags, live cell dyes, and other methods to fluorescently label proteins of interest provide a range of tools to investigate virtually any cellular process under the microscope. The two main experimental challenges in collecting meaningful live cell microscopy data are to minimize photodamage while retaining a useful signal-to-noise ratio, and to provide a suitable environment for cells or tissues to replicate physiological cell dynamics. This chapter aims to give a general overview on microscope design choices critical for fluorescence live cell imaging that apply to most fluorescence microscopy modalities, and on environmental control with a focus on mammalian tissue culture cells. In addition, we provide guidance on how to design and evaluate fluorescent protein constructs by spinning disk confocal microscopy. PMID:24974023

Functional imaging of hippocampal place cells at cellular resolution during virtual navigation

PubMed Central

Dombeck, Daniel A.; Harvey, Christopher D.; Tian, Lin; Looger, Loren L.; Tank, David W.

2010-01-01

Spatial navigation is a widely employed behavior in rodent studies of neuronal circuits underlying cognition, learning and memory. In vivo microscopy combined with genetically-encoded indicators provides important new tools to study neuronal circuits, but has been technically difficult to apply during navigation. We describe methods to image the activity of hippocampal CA1 neurons with sub-cellular resolution in behaving mice. Neurons expressing the genetically encoded calcium indicator GCaMP3 were imaged through a chronic hippocampal window. Head-fixed mice performed spatial behaviors within a setup combining a virtual reality system and a custom built two-photon microscope. Populations of place cells were optically identified, and the correlation between the location of their place fields in the virtual environment and their anatomical location in the local circuit was measured. The combination of virtual reality and high-resolution functional imaging should allow for a new generation of studies to probe neuronal circuit dynamics during behavior. PMID:20890294

Bioactivity Studies of β-Lactam Derived Polycyclic Fused Pyrroli-Dine/Pyrrolizidine Derivatives in Dentistry: In Vitro, In Vivo and In Silico Studies

PubMed Central

Winfred, Sofi Beaula; Mannivanan, Bhavani; Bhoopalan, Hemadev; Shankar, Venkatesh; Sekar, Sathiya; Venkatachalam, Deepa Parvathi; Pitani, Ravishankar; Nagendrababu, Venkateshbabu; Thaiman, Malini; Devivanayagam, Kandaswamy; Jayaraman, Jeyakanthan; Ragavachary, Raghunathan; Venkatraman, Ganesh

2015-01-01

The antibacterial activity of β-lactam derived polycyclic fused pyrrolidine/pyrrolizidine derivatives synthesized by 1, 3-dipolar cycloaddition reaction was evaluated against microbes involved in dental infection. Fifteen compounds were screened; among them compound 3 showed efficient antibacterial activity in an ex vivo dentinal tubule model and in vivo mice infectious model. In silico docking studies showed greater affinity to penicillin binding protein. Cell damage was observed under Scanning Electron Microscopy (SEM) which was further proved by Confocal Laser Scanning Microscope (CLSM) and quantified using Flow Cytometry by PI up-take. Compound 3 treated E. faecalis showed ROS generation and loss of membrane integrity was quantified by flow cytometry. Compound 3 was also found to be active against resistant E. faecalis strains isolated from failed root canal treatment cases. Further, compound 3 was found to be hemocompatible, not cytotoxic to normal mammalian NIH 3T3 cells and non mutagenic. It was concluded that β-lactam compound 3 exhibited promising antibacterial activity against E. faecalis involved in root canal infections and the mechanism of action was deciphered. The results of this research can be further implicated in the development of potent antibacterial medicaments with applications in dentistry. PMID:26185985

Arboreality, terrestriality and bipedalism

PubMed Central

Crompton, Robin Huw; Sellers, William I.; Thorpe, Susannah K. S.

2010-01-01

The full publication of Ardipithecus ramidus has particular importance for the origins of hominin bipedality, and strengthens the growing case for an arboreal origin. Palaeontological techniques however inevitably concentrate on details of fragmentary postcranial bones and can benefit from a whole-animal perspective. This can be provided by field studies of locomotor behaviour, which provide a real-world perspective of adaptive context, against which conclusions drawn from palaeontology and comparative osteology may be assessed and honed. Increasingly sophisticated dynamic modelling techniques, validated against experimental data for living animals, offer a different perspective where evolutionary and virtual ablation experiments, impossible for living mammals, may be run in silico, and these can analyse not only the interactions and behaviour of rigid segments but increasingly the effects of compliance, which are of crucial importance in guiding the evolution of an arboreally derived lineage. PMID:20855304

Improving the physiological realism of experimental models.

PubMed

Vinnakota, Kalyan C; Cha, Chae Y; Rorsman, Patrik; Balaban, Robert S; La Gerche, Andre; Wade-Martins, Richard; Beard, Daniel A; Jeneson, Jeroen A L

2016-04-06

The Virtual Physiological Human (VPH) project aims to develop integrative, explanatory and predictive computational models (C-Models) as numerical investigational tools to study disease, identify and design effective therapies and provide an in silico platform for drug screening. Ultimately, these models rely on the analysis and integration of experimental data. As such, the success of VPH depends on the availability of physiologically realistic experimental models (E-Models) of human organ function that can be parametrized to test the numerical models. Here, the current state of suitable E-models, ranging from in vitro non-human cell organelles to in vivo human organ systems, is discussed. Specifically, challenges and recent progress in improving the physiological realism of E-models that may benefit the VPH project are highlighted and discussed using examples from the field of research on cardiovascular disease, musculoskeletal disorders, diabetes and Parkinson's disease.

Modeling liver physiology: combining fractals, imaging and animation.

PubMed

Lin, Debbie W; Johnson, Scott; Hunt, C Anthony

2004-01-01

Physiological modeling of vascular and microvascular networks in several key human organ systems is critical for a deeper understanding of pharmacology and the effect of pharmacotherapies on disease. Like the lung and the kidney, the morphology of its vascular and microvascular system plays a major role in its functional capability. To understand liver function in absorption and metabolism of food and drugs, one must examine the morphology and physiology at both higher and lower level liver function. We have developed validated virtualized dynamic three dimensional (3D) models of liver secondary units and primary units by combining a number of different methods: three-dimensional rendering, fractals, and animation. We have simulated particle dynamics in the liver secondary unit. The resulting models are suitable for use in helping researchers easily visualize and gain intuition on results of in silico liver experiments.

Application of Image Intensifier Technology to the Military, Scientific, Industrial, Educational, and Medical Communities.

DTIC Science & Technology

1980-05-30

afflicted with Retinitis Pigmentosa , commonly called night blindness. People who suffer from this are virtually blind in absence of normal room light...image intensification 5. Low light ophthalmological surgery 6. Retinitis Pigmentosa patients 7. Mine rescue and first aid 8. TV microscopy 9

Virtual Microscopy: A Useful Tool for Meeting Evolving Challenges in the Veterinary Medical Curriculum

ERIC Educational Resources Information Center

Kogan, Lori R.; Dowers, Kristy L.; Cerda, Jacey R.; Schoenfeld-Tacher, Regina M.; Stewart, Sherry M.

2014-01-01

Veterinary schools, similar to many professional health programs, face a myriad of evolving challenges in delivering their professional curricula including expansion of class size, costs to maintain expensive laboratories, and increased demands on veterinary educators to use curricular time efficiently and creatively. Additionally, exponential…

pH-selective mutagenesis of protein-protein interfaces: in silico design of therapeutic antibodies with prolonged half-life.

PubMed

Spassov, Velin Z; Yan, Lisa

2013-04-01

Understanding the effects of mutation on pH-dependent protein binding affinity is important in protein design, especially in the area of protein therapeutics. We propose a novel method for fast in silico mutagenesis of protein-protein complexes to calculate the effect of mutation as a function of pH. The free energy differences between the wild type and mutants are evaluated from a molecular mechanics model, combined with calculations of the equilibria of proton binding. The predicted pH-dependent energy profiles demonstrate excellent agreement with experimentally measured pH-dependency of the effect of mutations on the dissociation constants for the complex of turkey ovomucoid third domain (OMTKY3) and proteinase B. The virtual scanning mutagenesis identifies all hotspots responsible for pH-dependent binding of immunoglobulin G (IgG) to neonatal Fc receptor (FcRn) and the results support the current understanding of the salvage mechanism of the antibody by FcRn based on pH-selective binding. The method can be used to select mutations that change the pH-dependent binding profiles of proteins and guide the time consuming and expensive protein engineering experiments. As an application of this method, we propose a computational strategy to search for mutations that can alter the pH-dependent binding behavior of IgG to FcRn with the aim of improving the half-life of therapeutic antibodies in the target organism. Copyright © 2013 Wiley Periodicals, Inc.

The in silico identification and characterization of a bread wheat/Triticum militinae introgression line.

PubMed

Abrouk, Michael; Balcárková, Barbora; Šimková, Hana; Komínkova, Eva; Martis, Mihaela M; Jakobson, Irena; Timofejeva, Ljudmilla; Rey, Elodie; Vrána, Jan; Kilian, Andrzej; Järve, Kadri; Doležel, Jaroslav; Valárik, Miroslav

2017-02-01

The capacity of the bread wheat (Triticum aestivum) genome to tolerate introgression from related genomes can be exploited for wheat improvement. A resistance to powdery mildew expressed by a derivative of the cross-bread wheat cv. Tähti × T. militinae (Tm) is known to be due to the incorporation of a Tm segment into the long arm of chromosome 4A. Here, a newly developed in silico method termed rearrangement identification and characterization (RICh) has been applied to characterize the introgression. A virtual gene order, assembled using the GenomeZipper approach, was obtained for the native copy of chromosome 4A; it incorporated 570 4A DArTseq markers to produce a zipper comprising 2132 loci. A comparison between the native and introgressed forms of the 4AL chromosome arm showed that the introgressed region is located at the distal part of the arm. The Tm segment, derived from chromosome 7G, harbours 131 homoeologs of the 357 genes present on the corresponding region of Chinese Spring 4AL. The estimated number of Tm genes transferred along with the disease resistance gene was 169. Characterizing the introgression's position, gene content and internal gene order should not only facilitate gene isolation, but may also be informative with respect to chromatin structure and behaviour studies. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Computational Approaches for Decoding Select Odorant-Olfactory Receptor Interactions Using Mini-Virtual Screening

PubMed Central

Harini, K.; Sowdhamini, Ramanathan

2015-01-01

Olfactory receptors (ORs) belong to the class A G-Protein Coupled Receptor superfamily of proteins. Unlike G-Protein Coupled Receptors, ORs exhibit a combinatorial response to odors/ligands. ORs display an affinity towards a range of odor molecules rather than binding to a specific set of ligands and conversely a single odorant molecule may bind to a number of olfactory receptors with varying affinities. The diversity in odor recognition is linked to the highly variable transmembrane domains of these receptors. The purpose of this study is to decode the odor-olfactory receptor interactions using in silico docking studies. In this study, a ligand (odor molecules) dataset of 125 molecules was used to carry out in silico docking using the GLIDE docking tool (SCHRODINGER Inc Pvt LTD). Previous studies, with smaller datasets of ligands, have shown that orthologous olfactory receptors respond to similarly-tuned ligands, but are dramatically different in their efficacy and potency. Ligand docking results were applied on homologous pairs (with varying sequence identity) of ORs from human and mouse genomes and ligand binding residues and the ligand profile differed among such related olfactory receptor sequences. This study revealed that homologous sequences with high sequence identity need not bind to the same/ similar ligand with a given affinity. A ligand profile has been obtained for each of the 20 receptors in this analysis which will be useful for expression and mutation studies on these receptors. PMID:26221959

Super-resolved linear fluorescence localization microscopy using photostable fluorophores: A virtual microscopy study

NASA Astrophysics Data System (ADS)

Birk, Udo; Szczurek, Aleksander; Cremer, Christoph

2017-12-01

Current approaches to overcome the conventional limit of the resolution potential of light microscopy (of about 200 nm for visible light), often suffer from non-linear effects, which render the quantification of the image intensities in the reconstructions difficult, and also affect the quantification of the biological structure under investigation. As an attempt to face these difficulties, we discuss a particular method of localization microscopy which is based on photostable fluorescent dyes. The proposed method can potentially be implemented as a fast alternative for quantitative localization microscopy, circumventing the need for the acquisition of thousands of image frames and complex, highly dye-specific imaging buffers. Although the need for calibration remains in order to extract quantitative data (such as the number of emitters), multispectral approaches are largely facilitated due to the much less stringent requirements on imaging buffers. Furthermore, multispectral acquisitions can be readily obtained using commercial instrumentation such as e.g. the conventional confocal laser scanning microscope.

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets.

PubMed

Wasko, Michael J; Pellegrene, Kendy A; Madura, Jeffry D; Surratt, Christopher K

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for "growing" the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies.

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets

PubMed Central

Wasko, Michael J.; Pellegrene, Kendy A.; Madura, Jeffry D.; Surratt, Christopher K.

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for “growing” the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies. PMID:26441817

Screening of synthetic and natural product databases: Identification of novel androgens and antiandrogens.

PubMed

Bobach, Claudia; Tennstedt, Stephanie; Palberg, Kristin; Denkert, Annika; Brandt, Wolfgang; de Meijere, Armin; Seliger, Barbara; Wessjohann, Ludger A

2015-01-27

The androgen receptor is an important pharmaceutical target for a variety of diseases. This paper presents an in silico/in vitro screening procedure to identify new androgen receptor ligands. The two-step virtual screening procedure uses a three-dimensional pharmacophore model and a docking/scoring routine. About 39,000 filtered compounds were docked with PLANTS and scored by Chemplp. Subsequent to virtual screening, 94 compounds, including 28 steroidal and 66 nonsteroidal compounds, were tested by an androgen receptor fluorescence polarization ligand displacement assay. As a result, 30 compounds were identified that show a relative binding affinity of more than 50% in comparison to 100 nM dihydrotestosterone and were classified as androgen receptor binders. For 11 androgen receptor binders of interest IC50 and Ki values were determined. The compound with the highest affinity exhibits a Ki value of 10.8 nM. Subsequent testing of the 11 compounds in a PC-3 and LNCaP multi readout proliferation assay provides insights into the potential mode of action. Further steroid receptor ligand displacement assays and docking studies on estrogen receptors α and β, glucocorticoid receptor, and progesterone receptor gave information about the specificity of the 11 most active compounds. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

In silico investigation of potential mTOR inhibitors from traditional Chinese medicine for treatment of Leigh syndrome.

PubMed

Chen, Kuan-Chung; Lee, Wen-Yuan; Chen, Hsin-Yi; Chen, Calvin Yu-Chian

2014-01-01

A recent research demonstrates that the inhibition of mammalian target of rapamycin (mTOR) improves survival and health for patients with Leigh syndrome. mTOR proteins can be treated as drug target proteins against Leigh syndrome and other mitochondrial disorders. In this study, we aim to identify potent TCM compounds from the TCM Database@Taiwan as lead compounds of mTOR inhibitors. PONDR-Fit protocol was employed to predict the disordered disposition in mTOR protein before virtual screening. After virtual screening, the MD simulation was employed to validate the stability of interactions between each ligand and mTOR protein in the docking poses from docking simulation. The top TCM compounds, picrasidine M and acerosin, have higher binding affinities with target protein in docking simulation than control. There have H-bonds with residues Val2240 and π interactions with common residue Trp2239. After MD simulation, the top TCM compounds maintain similar docking poses under dynamic conditions. The top two TCM compounds, picrasidine M and acerosin, were extracted from Picrasma quassioides (D. Don) Benn. and Vitex negundo L. Hence, we propose the TCM compounds, picrasidine M and acerosin, as potential candidates as lead compounds for further study in drug development process with the mTOR protein against Leigh syndrome and other mitochondrial disorders.

Open Innovation Drug Discovery (OIDD): a potential path to novel therapeutic chemical space.

PubMed

Alvim-Gaston, Maria; Grese, Timothy; Mahoui, Abdelaziz; Palkowitz, Alan D; Pineiro-Nunez, Marta; Watson, Ian

2014-01-01

The continued development of computational and synthetic methods has enabled the enumeration or preparation of a nearly endless universe of chemical structures. Nevertheless, the ability of this chemical universe to deliver small molecules that can both modulate biological targets and have drug-like physicochemical properties continues to be a topic of interest to the pharmaceutical industry and academic researchers alike. The chemical space described by public, commercial, in-house and virtual compound collections has been interrogated by multiple approaches including biochemical, cellular and virtual screening, diversity analysis, and in-silico profiling. However, current drugs and known chemical probes derived from these efforts are contained within a remarkably small volume of the predicted chemical space. Access to more diverse classes of chemical scaffolds that maintain the properties relevant for drug discovery is certainly needed to meet the increasing demands for pharmaceutical innovation. The Lilly Open Innovation Drug Discovery platform (OIDD) was designed to tackle barriers to innovation through the identification of novel molecules active in relevant disease biology models. In this article we will discuss several computational approaches towards describing novel, biologically active, drug-like chemical space and illustrate how the OIDD program may facilitate access to previously untapped molecules that may aid in the search for innovative pharmaceuticals.

Virtual screening for novel Staphylococcus Aureus NorA efflux pump inhibitors from natural products.

PubMed

Thai, Khac-Minh; Ngo, Trieu-Du; Phan, Thien-Vy; Tran, Thanh-Dao; Nguyen, Ngoc-Vinh; Nguyen, Thien-Hai; Le, Minh-Tri

2015-01-01

NorA is a member of the Major Facilitator Superfamily (MFS) drug efflux pumps that have been shown to mediate antibiotic resistance in Staphylococcus aureus (SA). In this study, QSAR analysis, virtual screening and molecular docking were implemented in an effort to discover novel SA NorA efflux pump inhibitors. Originally, a set of 47 structurally diverse compounds compiled from the literature was used to develop linear QSAR models and another set of 15 different compounds were chosen for extra validation. The final model which was estimated by statistical values for the full data set (n = 45, Q(2) = 0.80, RMSE = 0.20) and for the external test set (n = 15, R(2) = 0.60, |res|max = 0.75, |res|min = 0.02) was applied on the collection of 182 flavonoides and the traditional Chinese medicine (TCM) database to screen for novel NorA inhibitors. Finally, 33 lead compounds that met the Lipinski's rules of five/three and had good predicted pIC50 values from in silico screening process were employed to analyze the binding ability by docking studies on NorA homology model in place of its unavailable crystal structures at two active sites, the central channel and the Walker B.

Docking ligands into flexible and solvated macromolecules. 7. Impact of protein flexibility and water molecules on docking-based virtual screening accuracy.

PubMed

Therrien, Eric; Weill, Nathanael; Tomberg, Anna; Corbeil, Christopher R; Lee, Devin; Moitessier, Nicolas

2014-11-24

The use of predictive computational methods in the drug discovery process is in a state of continual growth. Over the last two decades, an increasingly large number of docking tools have been developed to identify hits or optimize lead molecules through in-silico screening of chemical libraries to proteins. In recent years, the focus has been on implementing protein flexibility and water molecules. Our efforts led to the development of Fitted first reported in 2007 and further developed since then. In this study, we wished to evaluate the impact of protein flexibility and occurrence of water molecules on the accuracy of the Fitted docking program to discriminate active compounds from inactive compounds in virtual screening (VS) campaigns. For this purpose, a total of 171 proteins cocrystallized with small molecules representing 40 unique enzymes and receptors as well as sets of known ligands and decoys were selected from the Protein Data Bank (PDB) and the Directory of Useful Decoys (DUD), respectively. This study revealed that implementing displaceable crystallographic or computationally placed particle water molecules and protein flexibility can improve the enrichment in active compounds. In addition, an informed decision based on library diversity or research objectives (hit discovery vs lead optimization) on which implementation to use may lead to significant improvements.

CHIPMUNK: A Virtual Synthesizable Small-Molecule Library for Medicinal Chemistry, Exploitable for Protein-Protein Interaction Modulators.

PubMed

Humbeck, Lina; Weigang, Sebastian; Schäfer, Till; Mutzel, Petra; Koch, Oliver

2018-03-20

A common issue during drug design and development is the discovery of novel scaffolds for protein targets. On the one hand the chemical space of purchasable compounds is rather limited; on the other hand artificially generated molecules suffer from a grave lack of accessibility in practice. Therefore, we generated a novel virtual library of small molecules which are synthesizable from purchasable educts, called CHIPMUNK (CHemically feasible In silico Public Molecular UNiverse Knowledge base). Altogether, CHIPMUNK covers over 95 million compounds and encompasses regions of the chemical space that are not covered by existing databases. The coverage of CHIPMUNK exceeds the chemical space spanned by the Lipinski rule of five to foster the exploration of novel and difficult target classes. The analysis of the generated property space reveals that CHIPMUNK is well suited for the design of protein-protein interaction inhibitors (PPIIs). Furthermore, a recently developed structural clustering algorithm (StruClus) for big data was used to partition the sub-libraries into meaningful subsets and assist scientists to process the large amount of data. These clustered subsets also contain the target space based on ChEMBL data which was included during clustering. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Resonant Scanning with Large Field of View Reduces Photobleaching and Enhances Fluorescence Yield in STED Microscopy.

PubMed

Wu, Yong; Wu, Xundong; Lu, Rong; Zhang, Jin; Toro, Ligia; Stefani, Enrico

2015-10-01

Photobleaching is a major limitation of superresolution Stimulated Depletion Emission (STED) microscopy. Fast scanning has long been considered an effective means to reduce photobleaching in fluorescence microscopy, but a careful quantitative study of this issue is missing. In this paper, we show that the photobleaching rate in STED microscopy can be slowed down and the fluorescence yield be enhanced by scanning with high speed, enabled by using large field of view in a custom-built resonant-scanning STED microscope. The effect of scanning speed on photobleaching and fluorescence yield is more remarkable at higher levels of depletion laser irradiance, and virtually disappears in conventional confocal microscopy. With ≥6 GW∙cm(-2) depletion irradiance, we were able to extend the fluorophore survival time of Atto 647N and Abberior STAR 635P by ~80% with 8-fold wider field of view. We confirm that STED Photobleaching is primarily caused by the depletion light acting upon the excited fluorophores. Experimental data agree with a theoretical model. Our results encourage further increasing the linear scanning speed for photobleaching reduction in STED microscopy.

Simulating the decentralized processes of the human immune system in a virtual anatomy model.

PubMed

Sarpe, Vladimir; Jacob, Christian

2013-01-01

Many physiological processes within the human body can be perceived and modeled as large systems of interacting particles or swarming agents. The complex processes of the human immune system prove to be challenging to capture and illustrate without proper reference to the spatial distribution of immune-related organs and systems. Our work focuses on physical aspects of immune system processes, which we implement through swarms of agents. This is our first prototype for integrating different immune processes into one comprehensive virtual physiology simulation. Using agent-based methodology and a 3-dimensional modeling and visualization environment (LINDSAY Composer), we present an agent-based simulation of the decentralized processes in the human immune system. The agents in our model - such as immune cells, viruses and cytokines - interact through simulated physics in two different, compartmentalized and decentralized 3-dimensional environments namely, (1) within the tissue and (2) inside a lymph node. While the two environments are separated and perform their computations asynchronously, an abstract form of communication is allowed in order to replicate the exchange, transportation and interaction of immune system agents between these sites. The distribution of simulated processes, that can communicate across multiple, local CPUs or through a network of machines, provides a starting point to build decentralized systems that replicate larger-scale processes within the human body, thus creating integrated simulations with other physiological systems, such as the circulatory, endocrine, or nervous system. Ultimately, this system integration across scales is our goal for the LINDSAY Virtual Human project. Our current immune system simulations extend our previous work on agent-based simulations by introducing advanced visualizations within the context of a virtual human anatomy model. We also demonstrate how to distribute a collection of connected simulations over a network of computers. As a future endeavour, we plan to use parameter tuning techniques on our model to further enhance its biological credibility. We consider these in silico experiments and their associated modeling and optimization techniques as essential components in further enhancing our capabilities of simulating a whole-body, decentralized immune system, to be used both for medical education and research as well as for virtual studies in immunoinformatics.

Fostering Student Engagement with Digital Microscopic Images Using ThingLink, an Image Annotation Program

ERIC Educational Resources Information Center

Appasamy, Pierette

2018-01-01

The teaching of histology has changed dramatically with virtual microscopy. Fewer students of histology spend significant time viewing slides on a microscope and instead study images available in digital slide sets, generally accessible via the internet. However, students must still be able to correctly identify the defining characteristics of…

Concurrent access to a virtual microscope using a web service oriented architecture

NASA Astrophysics Data System (ADS)

Corredor, Germán.; Iregui, Marcela; Arias, Viviana; Romero, Eduardo

2013-11-01

Virtual microscopy (VM) facilitates visualization and deployment of histopathological virtual slides (VS), a useful tool for education, research and diagnosis. In recent years, it has become popular, yet its use is still limited basically because of the very large sizes of VS, typically of the order of gigabytes. Such volume of data requires efficacious and efficient strategies to access the VS content. In an educative or research scenario, several users may require to access and interact with VS at the same time, so, due to large data size, a very expensive and powerful infrastructure is usually required. This article introduces a novel JPEG2000-based service oriented architecture for streaming and visualizing very large images under scalable strategies, which in addition need not require very specialized infrastructure. Results suggest that the proposed architecture enables transmission and simultaneous visualization of large images, while it is efficient using resources and offering users proper response times.

Open source tools for management and archiving of digital microscopy data to allow integration with patient pathology and treatment information

PubMed Central

2013-01-01

Background Virtual microscopy includes digitisation of histology slides and the use of computer technologies for complex investigation of diseases such as cancer. However, automated image analysis, or website publishing of such digital images, is hampered by their large file sizes. Results We have developed two Java based open source tools: Snapshot Creator and NDPI-Splitter. Snapshot Creator converts a portion of a large digital slide into a desired quality JPEG image. The image is linked to the patient’s clinical and treatment information in a customised open source cancer data management software (Caisis) in use at the Australian Breast Cancer Tissue Bank (ABCTB) and then published on the ABCTB website (http://www.abctb.org.au) using Deep Zoom open source technology. Using the ABCTB online search engine, digital images can be searched by defining various criteria such as cancer type, or biomarkers expressed. NDPI-Splitter splits a large image file into smaller sections of TIFF images so that they can be easily analysed by image analysis software such as Metamorph or Matlab. NDPI-Splitter also has the capacity to filter out empty images. Conclusions Snapshot Creator and NDPI-Splitter are novel open source Java tools. They convert digital slides into files of smaller size for further processing. In conjunction with other open source tools such as Deep Zoom and Caisis, this suite of tools is used for the management and archiving of digital microscopy images, enabling digitised images to be explored and zoomed online. Our online image repository also has the capacity to be used as a teaching resource. These tools also enable large files to be sectioned for image analysis. Virtual Slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/5330903258483934 PMID:23402499

Imperfect duplicate insertions type of mutations in plasmepsin V modulates binding properties of PEXEL motifs of export proteins in Indian Plasmodium vivax.

PubMed

Rawat, Manmeet; Vijay, Sonam; Gupta, Yash; Tiwari, Pramod Kumar; Sharma, Arun

2013-01-01

Plasmepsin V (PM-V) have functionally conserved orthologues across the Plasmodium genus who's binding and antigenic processing at the PEXEL motifs for export about 200-300 essential proteins is important for the virulence and viability of the causative Plasmodium species. This study was undertaken to determine P. vivax plasmepsin V Ind (PvPM-V-Ind) PEXEL motif export pathway for pathogenicity-related proteins/antigens export thereby altering plasmodium exportome during erythrocytic stages. We identify and characterize Plasmodium vivax plasmepsin-V-Ind (mutant) gene by cloning, sequence analysis, in silico bioinformatic protocols and structural modeling predictions based on docking studies on binding capacity with PEXEL motifs processing in terms of binding and accessibility of export proteins. Cloning and sequence analysis for genetic diversity demonstrates PvPM-V-Ind (mutant) gene is highly conserved among all isolates from different geographical regions of India. Imperfect duplicate insertion types of mutations (SVSE from 246-249 AA and SLSE from 266-269 AA) were identified among all Indian isolates in comparison to P.vivax Sal-1 (PvPM-V-Sal 1) isolate. In silico bioinformatics interaction studies of PEXEL peptide and active enzyme reveal that PvPM-V-Ind (mutant) is only active in endoplasmic reticulum lumen and membrane embedding is essential for activation of plasmepsin V. Structural modeling predictions based on docking studies with PEXEL motif show significant variation in substrate protein binding of these imperfect mutations with data mined PEXEL sequences. The predicted variation in the docking score and interacting amino acids of PvPM-V-Ind (mutant) proteins with PEXEL and lopinavir suggests a modulation in the activity of PvPM-V in terms of binding and accessibility at these sites. Our functional modeled validation of PvPM-V-Ind (mutant) imperfect duplicate insertions with data mined PEXEL sequences leading to altered binding and substrate accessibility of the enzyme makes it a plausible target to investigate export mechanisms for in silico virtual screening and novel pharmacophore designing.

Imperfect Duplicate Insertions Type of Mutations in Plasmepsin V Modulates Binding Properties of PEXEL Motifs of Export Proteins in Indian Plasmodium vivax

PubMed Central

Rawat, Manmeet; Vijay, Sonam; Gupta, Yash; Tiwari, Pramod Kumar; Sharma, Arun

2013-01-01

Introduction Plasmepsin V (PM-V) have functionally conserved orthologues across the Plasmodium genus who's binding and antigenic processing at the PEXEL motifs for export about 200–300 essential proteins is important for the virulence and viability of the causative Plasmodium species. This study was undertaken to determine P. vivax plasmepsin V Ind (PvPM-V-Ind) PEXEL motif export pathway for pathogenicity-related proteins/antigens export thereby altering plasmodium exportome during erythrocytic stages. Method We identify and characterize Plasmodium vivax plasmepsin-V-Ind (mutant) gene by cloning, sequence analysis, in silico bioinformatic protocols and structural modeling predictions based on docking studies on binding capacity with PEXEL motifs processing in terms of binding and accessibility of export proteins. Results Cloning and sequence analysis for genetic diversity demonstrates PvPM-V-Ind (mutant) gene is highly conserved among all isolates from different geographical regions of India. Imperfect duplicate insertion types of mutations (SVSE from 246–249 AA and SLSE from 266–269 AA) were identified among all Indian isolates in comparison to P.vivax Sal-1 (PvPM-V-Sal 1) isolate. In silico bioinformatics interaction studies of PEXEL peptide and active enzyme reveal that PvPM-V-Ind (mutant) is only active in endoplasmic reticulum lumen and membrane embedding is essential for activation of plasmepsin V. Structural modeling predictions based on docking studies with PEXEL motif show significant variation in substrate protein binding of these imperfect mutations with data mined PEXEL sequences. The predicted variation in the docking score and interacting amino acids of PvPM-V-Ind (mutant) proteins with PEXEL and lopinavir suggests a modulation in the activity of PvPM-V in terms of binding and accessibility at these sites. Conclusion/Significance Our functional modeled validation of PvPM-V-Ind (mutant) imperfect duplicate insertions with data mined PEXEL sequences leading to altered binding and substrate accessibility of the enzyme makes it a plausible target to investigate export mechanisms for in silico virtual screening and novel pharmacophore designing. PMID:23555891

Identification of novel target sites and an inhibitor of the dengue virus E protein.

PubMed

Yennamalli, Ragothaman; Subbarao, Naidu; Kampmann, Thorsten; McGeary, Ross P; Young, Paul R; Kobe, Bostjan

2009-06-01

Dengue and related flaviviruses represent a significant global health threat. The envelope glycoprotein E mediates virus attachment to a host cell and the subsequent fusion of viral and host cell membranes. The fusion process is driven by conformational changes in the E protein and is an essential step in the virus life cycle. In this study, we analyzed the pre-fusion and post-fusion structures of the dengue virus E protein to identify potential novel sites that could bind small molecules, which could interfere with the conformational transitions that mediate the fusion process. We used an in silico virtual screening approach combining three different docking algorithms (DOCK, GOLD and FlexX) to identify compounds that are likely to bind to these sites. Seven structurally diverse molecules were selected to test experimentally for inhibition of dengue virus propagation. The best compound showed an IC(50) in the micromolar range against dengue virus type 2.

Identification of novel target sites and an inhibitor of the dengue virus E protein

NASA Astrophysics Data System (ADS)

Yennamalli, Ragothaman; Subbarao, Naidu; Kampmann, Thorsten; McGeary, Ross P.; Young, Paul R.; Kobe, Bostjan

2009-06-01

Dengue and related flaviviruses represent a significant global health threat. The envelope glycoprotein E mediates virus attachment to a host cell and the subsequent fusion of viral and host cell membranes. The fusion process is driven by conformational changes in the E protein and is an essential step in the virus life cycle. In this study, we analyzed the pre-fusion and post-fusion structures of the dengue virus E protein to identify potential novel sites that could bind small molecules, which could interfere with the conformational transitions that mediate the fusion process. We used an in silico virtual screening approach combining three different docking algorithms (DOCK, GOLD and FlexX) to identify compounds that are likely to bind to these sites. Seven structurally diverse molecules were selected to test experimentally for inhibition of dengue virus propagation. The best compound showed an IC50 in the micromolar range against dengue virus type 2.

Improving the physiological realism of experimental models

PubMed Central

Vinnakota, Kalyan C.; Cha, Chae Y.; Rorsman, Patrik; Balaban, Robert S.; La Gerche, Andre; Wade-Martins, Richard; Beard, Daniel A.

2016-01-01

The Virtual Physiological Human (VPH) project aims to develop integrative, explanatory and predictive computational models (C-Models) as numerical investigational tools to study disease, identify and design effective therapies and provide an in silico platform for drug screening. Ultimately, these models rely on the analysis and integration of experimental data. As such, the success of VPH depends on the availability of physiologically realistic experimental models (E-Models) of human organ function that can be parametrized to test the numerical models. Here, the current state of suitable E-models, ranging from in vitro non-human cell organelles to in vivo human organ systems, is discussed. Specifically, challenges and recent progress in improving the physiological realism of E-models that may benefit the VPH project are highlighted and discussed using examples from the field of research on cardiovascular disease, musculoskeletal disorders, diabetes and Parkinson's disease. PMID:27051507

An In-Silico Investigation of Phytochemicals as Antiviral Agents Against Dengue Fever.

PubMed

Powers, Chelsea N; Setzer, William N

2016-01-01

A virtual screening analysis of our library of phytochemical structures with dengue virus protein targets has been carried out using a molecular docking approach. A total of 2194 plant-derived secondary metabolites have been docked. This molecule set comprised of 290 alkaloids (68 indole alkaloids, 153 isoquinoline alkaloids, 5 quinoline alkaloids, 13 piperidine alkaloids, 14 steroidal alkaloids, and 37 miscellaneous alkaloids), 678 terpenoids (47 monoterpenoids, 169 sesquiterpenoids, 265 diterpenoids, 81 steroids, and 96 triterpenoids), 20 aurones, 81 chalcones, 349 flavonoids, 120 isoflavonoids, 74 lignans, 58 stilbenoids, 169 miscellaneous polyphenolic compounds, 100 coumarins, 28 xanthones, 67 quinones, and 160 miscellaneous phytochemicals. Dengue virus protein targets examined included dengue virus protease (NS2B-NS3pro), helicase (NS3 helicase), methyltransferase (MTase), RNA-dependent RNA polymerase (RdRp), and the dengue virus envelope protein. Polyphenolic compounds, flavonoids, chalcones, and other phenolics were the most numerous of the strongly docking ligands for dengue virus protein targets.

ChemPreview: an augmented reality-based molecular interface.

PubMed

Zheng, Min; Waller, Mark P

2017-05-01

Human computer interfaces make computational science more comprehensible and impactful. Complex 3D structures such as proteins or DNA are magnified by digital representations and displayed on two-dimensional monitors. Augmented reality has recently opened another door to access the virtual three-dimensional world. Herein, we present an augmented reality application called ChemPreview with the potential to manipulate bio-molecular structures at an atomistic level. ChemPreview is available at https://github.com/wallerlab/chem-preview/releases, and is built on top of the Meta 1 platform https://www.metavision.com/. ChemPreview can be used to interact with a protein in an intuitive way using natural hand gestures, thereby making it appealing to computational chemists or structural biologists. The ability to manipulate atoms in real world could eventually provide new and more efficient ways of extracting structural knowledge, or designing new molecules in silico. Copyright © 2017 Elsevier Inc. All rights reserved.

Scanning EM of non-heavy metal stained biosamples: Large-field of view, high contrast and highly efficient immunolabeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuipers, Jeroen; Boer, Pascal de; Giepmans, Ben N.G., E-mail: b.n.g.giepmans@umcg.nl

Scanning electron microscopy (SEM) is increasing its application in life sciences for electron density measurements of ultrathin sections. These are traditionally analyzed with transmission electron microscopy (TEM); by most labs, SEM analysis still is associated with surface imaging only. Here we report several advantages of SEM for thin sections over TEM, both for structural inspection, as well as analyzing immuno-targeted labels such as quantum dots (QDs) and gold, where we find that QD-labeling is ten times more efficient than gold-labeling. Furthermore, we find that omitting post-staining with uranyl and lead leads to QDs readily detectable over the ultrastructure, but undermore » these conditions ultrastructural contrast was even almost invisible in TEM examination. Importantly, imaging in SEM with STEM detection leads to both outstanding QDs and ultrastructural contrast. STEM imaging is superior over back-scattered electron imaging of these non-contrasted samples, whereas secondary electron detection cannot be used at all. We conclude that examination of ultrathin sections by SEM, which may be immunolabeled with QDs, will allow rapid and straightforward analysis of large fields with more efficient labeling than can be achieved with immunogold. The large fields of view routinely achieved with SEM, but not with TEM, allows straightforward raw data sharing using virtual microscopy, also known as nanotomy when this concerns EM data in the life sciences. - Highlights: • High resolution and large fields of view via nanotomy or virtual microscopy. • Highly relevant for EM‐datasets where information density is high. • Sample preparation with low contrast good for STEM, not TEM. • Quantum dots now stand out in STEM‐based detection. • 10 Times more efficient labeling with quantum dots compared to gold.« less

Virtual Screening as a Strategy for the Identification of Xenobiotics Disrupting Corticosteroid Action

PubMed Central

Praxmarer, Lukas; Chantong, Boonrat; Cereghetti, Diego; Winiger, Rahel; Schuster, Daniela; Odermatt, Alex

2012-01-01

Background Impaired corticosteroid action caused by genetic and environmental influence, including exposure to hazardous xenobiotics, contributes to the development and progression of metabolic diseases, cardiovascular complications and immune disorders. Novel strategies are thus needed for identifying xenobiotics that interfere with corticosteroid homeostasis. 11β-hydroxysteroid dehydrogenase 2 (11β-HSD2) and mineralocorticoid receptors (MR) are major regulators of corticosteroid action. 11β-HSD2 converts the active glucocorticoid cortisol to the inactive cortisone and protects MR from activation by glucocorticoids. 11β-HSD2 has also an essential role in the placenta to protect the fetus from high maternal cortisol concentrations. Methods and Principal Findings We employed a previously constructed 3D-structural library of chemicals with proven and suspected endocrine disrupting effects for virtual screening using a chemical feature-based 11β-HSD pharmacophore. We tested several in silico predicted chemicals in a 11β-HSD2 bioassay. The identified antibiotic lasalocid and the silane-coupling agent AB110873 were found to concentration-dependently inhibit 11β-HSD2. Moreover, the silane AB110873 was shown to activate MR and stimulate mitochondrial ROS generation and the production of the proinflammatory cytokine interleukin-6 (IL-6). Finally, we constructed a MR pharmacophore, which successfully identified the silane AB110873. Conclusions Screening of virtual chemical structure libraries can facilitate the identification of xenobiotics inhibiting 11β-HSD2 and/or activating MR. Lasalocid and AB110873 belong to new classes of 11β-HSD2 inhibitors. The silane AB110873 represents to the best of our knowledge the first industrial chemical shown to activate MR. Furthermore, the MR pharmacophore can now be used for future screening purposes. PMID:23056542

AMPK modulatory activity of olive-tree leaves phenolic compounds: Bioassay-guided isolation on adipocyte model and in silico approach.

PubMed

Jiménez-Sánchez, Cecilia; Olivares-Vicente, Mariló; Rodríguez-Pérez, Celia; Herranz-López, María; Lozano-Sánchez, Jesús; Segura-Carretero, Antonio; Fernández-Gutiérrez, Alberto; Encinar, José Antonio; Micol, Vicente

2017-01-01

Olive-tree polyphenols have demonstrated potential for the management of obesity-related pathologies. We aimed to explore the capacity of Olive-tree leaves extract to modulate triglyceride accumulation and AMP-activated protein kinase activity (AMPK) on a hypertrophic adipocyte model. Intracellular triglycerides and AMPK activity were measured on the hypertrophic 3T3-L1 adipocyte model by AdipoRed and immunofluorescence microscopy, respectively. Reverse phase high performance liquid chromatography coupled to time-of-flight mass detection with electrospray ionization (RP-HPLC-ESI-TOF/MS) was used for the fractionation of the extract and the identification of the compounds. In-silico molecular docking of the AMPK alpha-2, beta and gamma subunits with the identified compounds was performed. Olive-tree leaves extract decreased the intracellular lipid accumulation through AMPK-dependent mechanisms in hypertrophic adipocytes. Secoiridoids, cinnamic acids, phenylethanoids and phenylpropanoids, flavonoids and lignans were the candidates predicted to account for this effect. Molecular docking revealed that some compounds may be AMPK-gamma modulators. The modulatory effects of compounds over the alpha and beta AMPK subunits appear to be less probable. Olive-tree leaves polyphenols modulate AMPK activity, which may become a therapeutic aid in the management of obesity-associated disturbances. The natural occurrence of these compounds may have important nutritional implications for the design of functional ingredients.

AMPK modulatory activity of olive–tree leaves phenolic compounds: Bioassay-guided isolation on adipocyte model and in silico approach

PubMed Central

Jiménez-Sánchez, Cecilia; Olivares-Vicente, Mariló; Rodríguez-Pérez, Celia; Herranz-López, María; Lozano-Sánchez, Jesús; Segura-Carretero, Antonio; Fernández-Gutiérrez, Alberto; Encinar, José Antonio; Micol, Vicente

2017-01-01

Scope Olive-tree polyphenols have demonstrated potential for the management of obesity-related pathologies. We aimed to explore the capacity of Olive-tree leaves extract to modulate triglyceride accumulation and AMP-activated protein kinase activity (AMPK) on a hypertrophic adipocyte model. Methods Intracellular triglycerides and AMPK activity were measured on the hypertrophic 3T3-L1 adipocyte model by AdipoRed and immunofluorescence microscopy, respectively. Reverse phase high performance liquid chromatography coupled to time-of-flight mass detection with electrospray ionization (RP-HPLC-ESI-TOF/MS) was used for the fractionation of the extract and the identification of the compounds. In-silico molecular docking of the AMPK alpha-2, beta and gamma subunits with the identified compounds was performed. Results Olive-tree leaves extract decreased the intracellular lipid accumulation through AMPK-dependent mechanisms in hypertrophic adipocytes. Secoiridoids, cinnamic acids, phenylethanoids and phenylpropanoids, flavonoids and lignans were the candidates predicted to account for this effect. Molecular docking revealed that some compounds may be AMPK-gamma modulators. The modulatory effects of compounds over the alpha and beta AMPK subunits appear to be less probable. Conclusions Olive-tree leaves polyphenols modulate AMPK activity, which may become a therapeutic aid in the management of obesity-associated disturbances. The natural occurrence of these compounds may have important nutritional implications for the design of functional ingredients. PMID:28278224

Combining Basal–Bolus Insulin Infusion for Tight Postprandial Glucose Control: An in Silico Evaluation in Adults, Children, and Adolescents

PubMed Central

Revert, Ana; Rossetti, Paolo; Calm, Remei; Vehí, Josep; Bondia, Jorge

2010-01-01

Background Achieving good postprandial glycemic control, without triggering hypoglycemia events, is a challenge of treatment strategies for type 1 diabetes subjects. Continuous subcutaneous insulin infusion, the gold standard of therapy, is based on heuristic adjustments of both basal and prandial insulin. Some tools, such as bolus calculators, are available to aid patients in selecting a meal-related insulin dose. However, they are still based on empiric parameters such as the insulin-to-carbohydrate ratio and on the physicians’ and patients’ ability to fit bolus mode to meal composition. Method In this article, a nonheuristic method for assessment of prandial insulin administration is presented and evaluated. An algorithm based on set inversion via interval analysis is used to coordinate basal and bolus insulin infusions to deal with postprandial glucose excursions. The evaluation is carried out through an in silico study using the 30 virtual patients available in the educational version of the Food and Drug Administration-accepted University of Virginia simulator. Results obtained using the standard bolus strategy and different coordinated basal–bolus solutions provided by the algorithm are compared. Results Coordinated basal–bolus solutions improve postprandial glucose performance in most cases, mainly in terms of reducing hypoglycemia risk, but also increasing the percentage of time in normoglycemia. Moreover, glycemic variability is reduced considerably by using these innovative solutions. Conclusions The algorithm presented here is a robust nonheuristic alternative to deal with postprandial glycemic control. It is shown as a powerful tool that could be integrated in future smart insulin pumps. PMID:21129338

Electrical stimulation of gut motility guided by an in silico model

NASA Astrophysics Data System (ADS)

Barth, Bradley B.; Henriquez, Craig S.; Grill, Warren M.; Shen, Xiling

2017-12-01

Objective. Neuromodulation of the central and peripheral nervous systems is becoming increasingly important for treating a diverse set of diseases—ranging from Parkinson’s Disease and epilepsy to chronic pain. However, neuromodulation of the gastrointestinal (GI) tract has achieved relatively limited success in treating functional GI disorders, which affect a significant population, because the effects of stimulation on the enteric nervous system (ENS) and gut motility are not well understood. Here we develop an integrated neuromechanical model of the ENS and assess neurostimulation strategies for enhancing gut motility, validated by in vivo experiments. Approach. The computational model included a network of enteric neurons, smooth muscle fibers, and interstitial cells of Cajal, which regulated propulsion of a virtual pellet in a model of gut motility. Main results. Simulated extracellular stimulation of ENS-mediated motility revealed that sinusoidal current at 0.5 Hz was more effective at increasing intrinsic peristalsis and reducing colon transit time than conventional higher frequency rectangular current pulses, as commonly used for neuromodulation therapy. Further analysis of the model revealed that the 0.5 Hz sinusoidal currents were more effective at modulating the pacemaker frequency of interstitial cells of Cajal. To test the predictions of the model, we conducted in vivo electrical stimulation of the distal colon while measuring bead propulsion in awake rats. Experimental results confirmed that 0.5 Hz sinusoidal currents were more effective than higher frequency pulses at enhancing gut motility. Significance. This work demonstrates an in silico GI neuromuscular model to enable GI neuromodulation parameter optimization and suggests that low frequency sinusoidal currents may improve the efficacy of GI pacing.

In Silico Assessment of Literature Insulin Bolus Calculation Methods Accounting for Glucose Rate of Change.

PubMed

Cappon, Giacomo; Marturano, Francesca; Vettoretti, Martina; Facchinetti, Andrea; Sparacino, Giovanni

2018-05-01

The standard formula (SF) used in bolus calculators (BCs) determines meal insulin bolus using "static" measurement of blood glucose concentration (BG) obtained by self-monitoring of blood glucose (SMBG) fingerprick device. Some methods have been proposed to improve efficacy of SF using "dynamic" information provided by continuous glucose monitoring (CGM), and, in particular, glucose rate of change (ROC). This article compares, in silico and in an ideal framework limiting the exposition to possibly confounding factors (such as CGM noise), the performance of three popular techniques devised for such a scope, that is, the methods of Buckingham et al (BU), Scheiner (SC), and Pettus and Edelman (PE). Using the UVa/Padova Type 1 diabetes simulator we generated data of 100 virtual subjects in noise-free, single-meal scenarios having different preprandial BG and ROC values. Meal insulin bolus was computed using SF, BU, SC, and PE. Performance was assessed with the blood glucose risk index (BGRI) on the 9 hours after meal. On average, BU, SC, and PE improve BGRI compared to SF. When BG is rapidly decreasing, PE obtains the best performance. In the other ROC scenarios, none of the considered methods prevails in all the preprandial BG conditions tested. Our study showed that, at least in the considered ideal framework, none of the methods to correct SF according to ROC is globally better than the others. Critical analysis of the results also suggests that further investigations are needed to develop more effective formulas to account for ROC information in BCs.

In-silico evidences for binding of Glucokinase activators to EGFR C797S to overcome EGFR resistance obstacle with mutant-selective allosteric inhibition.

PubMed

Patel, Harun; Pawara, Rahul; Surana, Sanjay

2018-03-29

The tyrosine kinase inhibitors (TKI) against epidermal growth factor receptor (EGFR) are generally utilized as a part of patients with non-small cell lung carcinoma (NSCLC). However, EGFR T790M mutation results in resistance to most clinically available EGFR TKIs. Third-generation EGFR TKIs against the T790M mutation has been in active clinical development to triumph the resistance problem; they covalently bind with conserved Cys797 inside the EGFR active site, offering both potency and kinase-selectivity. Third generation drugs target C797, which makes the C797S resistance mutation more subtle. EGFR C797S mutation was accounted to be a main mechanism of resistance to the third-generation inhibitors. The C797S mutation gives off an impression of being an ideal target for conquering the acquired resistance to the third generation inhibitors. We have performed structure based-virtual screening strategies for binding of glucokinase activator to EGFR C797S, which can overcome EGFR resistance impediment with mutant-selective allosteric inhibition towards all kinds of mutant EGFR (T790M, L858R, TMLR) and WT EGFR. The final filter of Lipinski's Rule of Five, Jargan's Rule of Three and in silico ADME predictions gave 23 hits, which conform to Lipinski's rule and Jorgensen's rule and all their pharmacokinetic parameters are inside the appropriate range characterized for human use, in this manner demonstrating their potential as a drug-like molecule. Copyright © 2018 Elsevier Ltd. All rights reserved.

In silico serotyping of E. coli from short read data identifies limited novel O-loci but extensive diversity of O:H serotype combinations within and between pathogenic lineages.

PubMed

Ingle, Danielle J; Valcanis, Mary; Kuzevski, Alex; Tauschek, Marija; Inouye, Michael; Stinear, Tim; Levine, Myron M; Robins-Browne, Roy M; Holt, Kathryn E

2016-07-01

The lipopolysaccharide (O) and flagellar (H) surface antigens of Escherichia coli are targets for serotyping that have traditionally been used to identify pathogenic lineages. These surface antigens are important for the survival of E. coli within mammalian hosts. However, traditional serotyping has several limitations, and public health reference laboratories are increasingly moving towards whole genome sequencing (WGS) to characterize bacterial isolates. Here we present a method to rapidly and accurately serotype E. coli isolates from raw, short read WGS data. Our approach bypasses the need for de novo genome assembly by directly screening WGS reads against a curated database of alleles linked to known and novel E. coli O-groups and H-types (the EcOH database) using the software package srst2. We validated the approach by comparing in silico results for 197 enteropathogenic E. coli isolates with those obtained by serological phenotyping in an independent laboratory. We then demonstrated the utility of our method to characterize isolates in public health and clinical settings, and to explore the genetic diversity of >1500 E. coli genomes from multiple sources. Importantly, we showed that transfer of O- and H-antigen loci between E. coli chromosomal backbones is common, with little evidence of constraints by host or pathotype, suggesting that E. coli ' strain space' may be virtually unlimited, even within specific pathotypes. Our findings show that serotyping is most useful when used in combination with strain genotyping to characterize microevolution events within an inferred population structure.

Hit identification of novel heparanase inhibitors by structure- and ligand-based approaches.

PubMed

Gozalbes, Rafael; Mosulén, Silvia; Ortí, Leticia; Rodríguez-Díaz, Jesús; Carbajo, Rodrigo J; Melnyk, Patricia; Pineda-Lucena, Antonio

2013-04-01

Heparanase is a key enzyme involved in the dissemination of metastatic cancer cells. In this study a combination of in silico techniques and experimental methods was used to identify new potential inhibitors against this target. A 3D model of heparanase was built from sequence homology and applied to the virtual screening of a library composed of 27 known heparanase inhibitors and a commercial collection of drugs and drug-like compounds. The docking results from this campaign were combined with those obtained from a pharmacophore model recently published based in the same set of chemicals. Compounds were then ranked according to their theoretical binding affinity, and the top-rated commercial drugs were selected for further experimental evaluation. Biophysical methods (NMR and SPR) were applied to assess experimentally the interaction of the selected compounds with heparanase. The binding site was evaluated via competition experiments, using a known inhibitor of heparanase. Three of the selected drugs were found to bind to the active site of the protein and their KD values were determined. Among them, the antimalarial drug amodiaquine presented affinity towards the protein in the low-micromolar range, and was singled out for a SAR study based on its chemical scaffold. A subset of fourteen 4-arylaminoquinolines from a global set of 249 analogues of amodiaquine was selected based on the application of in silico models, a QSAR solubility prediction model and a chemical diversity analysis. Some of these compounds displayed binding affinities in the micromolar range. Copyright © 2013 Elsevier Ltd. All rights reserved.

Identification of potential inhibitors for oncogenic target of dihydroorotate dehydrogenase using in silico approaches

NASA Astrophysics Data System (ADS)

Surekha, Kanagarajan; Nachiappan, Mutharasappan; Prabhu, Dhamodharan; Choubey, Sanjay Kumar; Biswal, Jayashree; Jeyakanthan, Jeyaraman

2017-01-01

Dihydroorotate dehydrogenase (DHODH) plays a major role in the rate limiting step of de novo pyrimidine biosynthesis pathway and it is pronounced as a novel target for drug development of cancer. The currently available drugs against DHODH are ineffective and bear various side effects. Three-dimensional structure of the targeted protein was constructed using molecular modeling approach followed by 100 ns molecular dynamics simulations. In this study, High Throughput Virtual Screening (HTVS) was performed using various compound libraries to identify pharmacologically potential molecules. The top four identified lead molecules includes NCI_47074, HitFinder_7630, Binding_66981 and Specs_108872 with high docking score of -9.45, -8.29, -8.04 and -8.03 kcal/mol and the corresponding binding free energy were -16.25, -56.37, -26.93 and -48.04 kcal/mol respectively. Arg122, Arg185, Glu255 and Gly257 are the key residues found to be interacting with the ligands. Molecular dynamics simulations of DHODH-inhibitors complexes were performed to assess the stability of various conformations from complex structures of TtDHODH. Furthermore, stereoelectronic features of the ligands were explored to facilitate charge transfer during the protein-ligand interactions using Density Functional Theoretical approach. Based on in silico analysis, the ligand NCI_47074 ((2Z)-3-({6-[(2Z)-3-carboxylatoprop-2-enamido]pyridin-2-yl}carbamoyl)prop-2-enoate) was found to be the most potent lead molecule which was validated using energetic and electronic parameters and it could serve as a template for designing effective anticancerous drug molecule.

In silico toxicology protocols.

PubMed

Myatt, Glenn J; Ahlberg, Ernst; Akahori, Yumi; Allen, David; Amberg, Alexander; Anger, Lennart T; Aptula, Aynur; Auerbach, Scott; Beilke, Lisa; Bellion, Phillip; Benigni, Romualdo; Bercu, Joel; Booth, Ewan D; Bower, Dave; Brigo, Alessandro; Burden, Natalie; Cammerer, Zoryana; Cronin, Mark T D; Cross, Kevin P; Custer, Laura; Dettwiler, Magdalena; Dobo, Krista; Ford, Kevin A; Fortin, Marie C; Gad-McDonald, Samantha E; Gellatly, Nichola; Gervais, Véronique; Glover, Kyle P; Glowienke, Susanne; Van Gompel, Jacky; Gutsell, Steve; Hardy, Barry; Harvey, James S; Hillegass, Jedd; Honma, Masamitsu; Hsieh, Jui-Hua; Hsu, Chia-Wen; Hughes, Kathy; Johnson, Candice; Jolly, Robert; Jones, David; Kemper, Ray; Kenyon, Michelle O; Kim, Marlene T; Kruhlak, Naomi L; Kulkarni, Sunil A; Kümmerer, Klaus; Leavitt, Penny; Majer, Bernhard; Masten, Scott; Miller, Scott; Moser, Janet; Mumtaz, Moiz; Muster, Wolfgang; Neilson, Louise; Oprea, Tudor I; Patlewicz, Grace; Paulino, Alexandre; Lo Piparo, Elena; Powley, Mark; Quigley, Donald P; Reddy, M Vijayaraj; Richarz, Andrea-Nicole; Ruiz, Patricia; Schilter, Benoit; Serafimova, Rositsa; Simpson, Wendy; Stavitskaya, Lidiya; Stidl, Reinhard; Suarez-Rodriguez, Diana; Szabo, David T; Teasdale, Andrew; Trejo-Martin, Alejandra; Valentin, Jean-Pierre; Vuorinen, Anna; Wall, Brian A; Watts, Pete; White, Angela T; Wichard, Joerg; Witt, Kristine L; Woolley, Adam; Woolley, David; Zwickl, Craig; Hasselgren, Catrin

2018-07-01

The present publication surveys several applications of in silico (i.e., computational) toxicology approaches across different industries and institutions. It highlights the need to develop standardized protocols when conducting toxicity-related predictions. This contribution articulates the information needed for protocols to support in silico predictions for major toxicological endpoints of concern (e.g., genetic toxicity, carcinogenicity, acute toxicity, reproductive toxicity, developmental toxicity) across several industries and regulatory bodies. Such novel in silico toxicology (IST) protocols, when fully developed and implemented, will ensure in silico toxicological assessments are performed and evaluated in a consistent, reproducible, and well-documented manner across industries and regulatory bodies to support wider uptake and acceptance of the approaches. The development of IST protocols is an initiative developed through a collaboration among an international consortium to reflect the state-of-the-art in in silico toxicology for hazard identification and characterization. A general outline for describing the development of such protocols is included and it is based on in silico predictions and/or available experimental data for a defined series of relevant toxicological effects or mechanisms. The publication presents a novel approach for determining the reliability of in silico predictions alongside experimental data. In addition, we discuss how to determine the level of confidence in the assessment based on the relevance and reliability of the information. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Reduction of Photo Bleaching and Long Term Archiving of Chemically Cleared GFP-Expressing Mouse Brains

PubMed Central

Becker, Klaus; Hahn, Christian Markus; Saghafi, Saiedeh; Jährling, Nina; Wanis, Martina; Dodt, Hans-Ulrich

2014-01-01

Tissue clearing allows microscopy of large specimens as whole mouse brains or embryos. However, lipophilic tissue clearing agents as dibenzyl ether limit storage time of GFP-expressing samples to several days and do not prevent them from photobleaching during microscopy. To preserve GFP fluorescence, we developed a transparent solid resin formulation, which maintains the specimens' transparency and provides a constant signal to noise ratio even after hours of continuous laser irradiation. If required, high-power illumination or long exposure times can be applied with virtually no loss in signal quality and samples can be archived for years. PMID:25463047

Atomic force microscopy as a tool to study Xenopus laevis embryo

NASA Astrophysics Data System (ADS)

Pukhlyakova, E. A.; Efremov, Yu M.; Bagrov, D. V.; Luchinskaya, N. N.; Kiryukhin, D. O.; Belousov, L. V.; Shaitan, K. V.

2012-02-01

Atomic force microscopy (AFM) has become a powerful tool for imaging biological structures (from single molecules to living cells) and carrying out measurements of their mechanical properties. AFM provides three-dimensional high-resolution images of the studied biological objects in physiological environment. However there are only few AFM investigations of fresh tissue explants and virtually no such research on a whole organism, since most researchers work with cell cultures. In the current work AFM was used to observe the surface of living and fixed embryos and to measure mechanical properties of naive embryos and embryos with overexpression of guanine nucleotide-binding protein G-alpha-13.

[The actual possibilities of robotic microscopy in analysis automation and laboratory telemedicine].

PubMed

Medovyĭ, V S; Piatnitskiĭ, A M; Sokolinskiĭ, B Z; Balugian, R Sh

2012-10-01

The article discusses the possibilities of automation microscopy complexes manufactured by Cellavision and MEKOS to perform the medical analyses of blood films and other biomaterials. The joint work of the complex and physician in the regimen of automatic load stages, screening, sampling and sorting on types with simple morphology, visual sorting of sub-sample with complex morphology provides significant increase of method sensitivity, load decrease and enhancement of physician work conditions. The information technologies, the virtual slides and laboratory telemedicine included permit to develop the representative samples of rare types and pathologies to promote automation methods and medical research targets.

Applications of two-photon fluorescence microscopy in deep-tissue imaging

NASA Astrophysics Data System (ADS)

Dong, Chen-Yuan; Yu, Betty; Hsu, Lily L.; Kaplan, Peter D.; Blankschstein, D.; Langer, Robert; So, Peter T. C.

2000-07-01

Based on the non-linear excitation of fluorescence molecules, two-photon fluorescence microscopy has become a significant new tool for biological imaging. The point-like excitation characteristic of this technique enhances image quality by the virtual elimination of off-focal fluorescence. Furthermore, sample photodamage is greatly reduced because fluorescence excitation is limited to the focal region. For deep tissue imaging, two-photon microscopy has the additional benefit in the greatly improved imaging depth penetration. Since the near- infrared laser sources used in two-photon microscopy scatter less than their UV/glue-green counterparts, in-depth imaging of highly scattering specimen can be greatly improved. In this work, we will present data characterizing both the imaging characteristics (point-spread-functions) and tissue samples (skin) images using this novel technology. In particular, we will demonstrate how blind deconvolution can be used further improve two-photon image quality and how this technique can be used to study mechanisms of chemically-enhanced, transdermal drug delivery.

Central pathology review for phase III clinical trials: the enabling effect of virtual microscopy.

PubMed

Mroz, Pawel; Parwani, Anil V; Kulesza, Piotr

2013-04-01

Central pathology review (CPR) was initially designed as a quality control measure. The potential of CPR in clinical trials was recognized as early as in the 1960s and quickly became embedded as an integral part of many clinical trials since. To review the current experience with CPR in clinical trials, to summarize current developments in virtual microscopy, and to discuss the potential advantages and disadvantages of this technology in the context of CPR. A PubMed (US National Library of Medicine) search for published studies was conducted, and the relevant articles were reviewed, accompanied by the authors' experience at their practicing institution. The review of the available literature strongly suggests the growing importance of CPR both in the clinical trial setting as well as in second opinion cases. However, the currently applied approach significantly impedes efficient transfer of slides and patient data. Recent advances in imaging, digital microscopy, and Internet technologies suggest that the CPR process may be dramatically streamlined in the foreseeable future to allow for better diagnosis and quality assurance than ever before. In particular, whole slide imaging may play an important role in this process and result in a substantial reduction of the overall turnaround time required for slide review at the central location. Above all, this new approach may benefit the large clinical trials organized by oncology cooperative groups, since most of those trials involve complicated logistics owing to enrollment of large number of patients at several remotely located participating institutions.

Strength of bond with Comspan Opaque to three silicoated alloys and titanium.

PubMed

Hansson, O

1990-06-01

In Sweden high-gold alloys or cobalt-chromium alloys are used for resin-bonded prostheses. The bond strength between a resin cement and different sandblasted or silicoated metals were measured before and after thermocycling; in connection with this some rapid thermocycling methods were studied. The effect of different storage times and different protection coatings on bond strength were tested. Finally, the influence of rubbing and contamination with saliva on bond strength were investigated. Silicoating increased the bond strength significantly. The highest bond strengths were these of silicoated Wirobond and titanium, unsusceptible to thermal stress; the bond strengths of the sandblasted metals were the weakest, and sensitive to thermocycling as well. The influence on bond strength for silicoated gold alloys, protected with an unpolymerized composite resin coating, stored in sealed plastic bags up to 7 days, was negligible. Rubbing and contamination with saliva did not influence bond strength. Preferably, silicoated Wirobond and titanium should be used for resin-bonded prostheses, but gold alloys may still be adequate for clinical use. The experimental method described for storing, sealing, and cleaning the silicoated metal surfaces in this article can be recommended for laboratory and clinical use.

Enabling virtual screening of potent and safer antimicrobial agents against noma: mtk-QSBER model for simultaneous prediction of antibacterial activities and ADMET properties.

PubMed

Speck-Planche, Alejandro; Cordeiro, M N D S

2015-01-01

Neglected diseases are infections that thrive mainly among underdeveloped countries, particularly those belonging to regions found in Asia, Africa, and America. One of the most complex diseases is noma, a dangerous health condition characterized by a polymicrobial and opportunistic nature. The search for potent and safer antibacterial agents against this disease is therefore a goal of particular interest. Chemoinformatics can be used to rationalize the discovery of drug candidates, diminishing time and financial resources. However, in the case of noma, there is no in silico model available for its use in the discovery of efficacious antibacterial agents. This work is devoted to report the first mtk-QSBER model, which integrates dissimilar kinds of chemical and biological data. The model was generated with the aim of simultaneously predicting activity against bacteria present in noma, and ADMET (absorption, distribution, metabolism, elimination, toxicity) parameters. The mtk-QSBER model was constructed by employing a large and heterogeneous dataset of chemicals and displayed accuracies higher than 90% in both training and prediction sets. We confirmed the practical applicability of the model by predicting multiple profiles of the investigational antibacterial drug delafloxacin, and the predictions converged with the experimental reports. To date, this is the first model focused on the virtual search for desirable anti-noma agents.

Encompassing receptor flexibility in virtual screening using ensemble docking-based hybrid QSAR: discovery of novel phytochemicals for BACE1 inhibition.

PubMed

Chakraborty, Sandipan; Ramachandran, Balaji; Basu, Soumalee

2014-10-01

Mimicking receptor flexibility during receptor-ligand binding is a challenging task in computational drug design since it is associated with a large increase in the conformational search space. In the present study, we have devised an in silico design strategy incorporating receptor flexibility in virtual screening to identify potential lead compounds as inhibitors for flexible proteins. We have considered BACE1 (β-secretase), a key target protease from a therapeutic perspective for Alzheimer's disease, as the highly flexible receptor. The protein undergoes significant conformational transitions from open to closed form upon ligand binding, which makes it a difficult target for inhibitor design. We have designed a hybrid structure-activity model containing both ligand based descriptors and energetic descriptors obtained from molecular docking based on a dataset of structurally diverse BACE1 inhibitors. An ensemble of receptor conformations have been used in the docking study, further improving the prediction ability of the model. The designed model that shows significant prediction ability judged by several statistical parameters has been used to screen an in house developed 3-D structural library of 731 phytochemicals. 24 highly potent, novel BACE1 inhibitors with predicted activity (Ki) ≤ 50 nM have been identified. Detailed analysis reveals pharmacophoric features of these novel inhibitors required to inhibit BACE1.

Ligand- and structure-based in silico studies to identify kinesin spindle protein (KSP) inhibitors as potential anticancer agents.

PubMed

Balakumar, Chandrasekaran; Ramesh, Muthusamy; Tham, Chuin Lean; Khathi, Samukelisiwe Pretty; Kozielski, Frank; Srinivasulu, Cherukupalli; Hampannavar, Girish A; Sayyad, Nisar; Soliman, Mahmoud E; Karpoormath, Rajshekhar

2017-11-29

Kinesin spindle protein (KSP) belongs to the kinesin superfamily of microtubule-based motor proteins. KSP is responsible for the establishment of the bipolar mitotic spindle which mediates cell division. Inhibition of KSP expedites the blockade of the normal cell cycle during mitosis through the generation of monoastral MT arrays that finally cause apoptotic cell death. As KSP is highly expressed in proliferating/cancer cells, it has gained considerable attention as a potential drug target for cancer chemotherapy. Therefore, this study envisaged to design novel KSP inhibitors by employing computational techniques/tools such as pharmacophore modelling, virtual database screening, molecular docking and molecular dynamics. Initially, the pharmacophore models were generated from the data-set of highly potent KSP inhibitors and the pharmacophore models were validated against in house test set ligands. The validated pharmacophore model was then taken for database screening (Maybridge and ChemBridge) to yield hits, which were further filtered for their drug-likeliness. The potential hits retrieved from virtual database screening were docked using CDOCKER to identify the ligand binding landscape. The top-ranked hits obtained from molecular docking were progressed to molecular dynamics (AMBER) simulations to deduce the ligand binding affinity. This study identified MB-41570 and CB-10358 as potential hits and evaluated these experimentally using in vitro KSP ATPase inhibition assays.

Pharmacophore Modeling and in Silico/in Vitro Screening for Human Cytochrome P450 11B1 and Cytochrome P450 11B2 Inhibitors.

PubMed

Akram, Muhammad; Waratchareeyakul, Watcharee; Haupenthal, Joerg; Hartmann, Rolf W; Schuster, Daniela

2017-01-01

Cortisol synthase (CYP11B1) is the main enzyme for the endogenous synthesis of cortisol and its inhibition is a potential way for the treatment of diseases associated with increased cortisol levels, such as Cushing's syndrome, metabolic diseases, and delayed wound healing. Aldosterone synthase (CYP11B2) is the key enzyme for aldosterone biosynthesis and its inhibition is a promising approach for the treatment of congestive heart failure, cardiac fibrosis, and certain forms of hypertension. Both CYP11B1 and CYP11B2 are structurally very similar and expressed in the adrenal cortex. To facilitate the identification of novel inhibitors of these enzymes, ligand-based pharmacophore models of CYP11B1 and CYP11B2 inhibition were developed. A virtual screening of the SPECS database was performed with our pharmacophore queries. Biological evaluation of the selected hits lead to the discovery of three potent novel inhibitors of both CYP11B1 and CYP11B2 in the submicromolar range (compounds 8 - 10 ), one selective CYP11B1 inhibitor (Compound 11 , IC 50 = 2.5 μM), and one selective CYP11B2 inhibitor (compound 12 , IC 50 = 1.1 μM), respectively. The overall success rate of this prospective virtual screening experiment is 20.8% indicating good predictive power of the pharmacophore models.

Identification of novel PfDHODH inhibitors as antimalarial agents via pharmacophore-based virtual screening followed by molecular docking and in vivo antimalarial activity.

PubMed

Vyas, V K; Qureshi, G; Ghate, M; Patel, H; Dalai, S

2016-06-01

Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) catalyses the fourth reaction of de novo pyrimidine biosynthesis in parasites, and represents an important target for the treatment of malaria. In this study, we describe pharmacophore-based virtual screening combined with docking study and biological evaluation as a rational strategy for identification of novel hits as antimalarial agents. Pharmacophore models were established from known PfDHODH inhibitors using the GALAHAD module with IC50 values ranging from 0.033 μM to 142 μM. The best pharmacophore model consisted of three hydrogen bond acceptor, one hydrogen bond donor and one hydrophobic features. The pharmacophore models were validated through receiver operating characteristic and Günere-Henry scoring methods. The best pharmacophore model as a 3D search query was searched against the IBS database. Several compounds with different structures (scaffolds) were retrieved as hit molecules. Among these compounds, those with a QFIT value of more than 81 were docked in the PfDHODH enzyme to further explore the binding modes of these compounds. In silico pharmacokinetic and toxicities were predicted for the best docked molecules. Finally, the identified hits were evaluated in vivo for their antimalarial activity in a parasite inhibition assay. The hits reported here showed good potential to become novel antimalarial agents.

Molpher: a software framework for systematic chemical space exploration

PubMed Central

2014-01-01

Background Chemical space is virtual space occupied by all chemically meaningful organic compounds. It is an important concept in contemporary chemoinformatics research, and its systematic exploration is vital to the discovery of either novel drugs or new tools for chemical biology. Results In this paper, we describe Molpher, an open-source framework for the systematic exploration of chemical space. Through a process we term ‘molecular morphing’, Molpher produces a path of structurally-related compounds. This path is generated by the iterative application of so-called ‘morphing operators’ that represent simple structural changes, such as the addition or removal of an atom or a bond. Molpher incorporates an optimized parallel exploration algorithm, compound logging and a two-dimensional visualization of the exploration process. Its feature set can be easily extended by implementing additional morphing operators, chemical fingerprints, similarity measures and visualization methods. Molpher not only offers an intuitive graphical user interface, but also can be run in batch mode. This enables users to easily incorporate molecular morphing into their existing drug discovery pipelines. Conclusions Molpher is an open-source software framework for the design of virtual chemical libraries focused on a particular mechanistic class of compounds. These libraries, represented by a morphing path and its surroundings, provide valuable starting data for future in silico and in vitro experiments. Molpher is highly extensible and can be easily incorporated into any existing computational drug design pipeline. PMID:24655571

Molpher: a software framework for systematic chemical space exploration.

PubMed

Hoksza, David; Skoda, Petr; Voršilák, Milan; Svozil, Daniel

2014-03-21

Chemical space is virtual space occupied by all chemically meaningful organic compounds. It is an important concept in contemporary chemoinformatics research, and its systematic exploration is vital to the discovery of either novel drugs or new tools for chemical biology. In this paper, we describe Molpher, an open-source framework for the systematic exploration of chemical space. Through a process we term 'molecular morphing', Molpher produces a path of structurally-related compounds. This path is generated by the iterative application of so-called 'morphing operators' that represent simple structural changes, such as the addition or removal of an atom or a bond. Molpher incorporates an optimized parallel exploration algorithm, compound logging and a two-dimensional visualization of the exploration process. Its feature set can be easily extended by implementing additional morphing operators, chemical fingerprints, similarity measures and visualization methods. Molpher not only offers an intuitive graphical user interface, but also can be run in batch mode. This enables users to easily incorporate molecular morphing into their existing drug discovery pipelines. Molpher is an open-source software framework for the design of virtual chemical libraries focused on a particular mechanistic class of compounds. These libraries, represented by a morphing path and its surroundings, provide valuable starting data for future in silico and in vitro experiments. Molpher is highly extensible and can be easily incorporated into any existing computational drug design pipeline.

Pharmacophore modeling and in silico / in vitro screening for human cytochrome P450 11B1 & cytochrome P450 11B2 inhibitors

NASA Astrophysics Data System (ADS)

Akram, Muhammad; Waratchareeyakul, Watcharee; Haupenthal, Joerg; Hartmann, Rolf W.; Schuster, Daniela

2017-12-01

Cortisol synthase (CYP11B1) is the main enzyme for the endogenous synthesis of cortisol and its inhibition is a potential way for the treatment of diseases associated with increased cortisol levels, such as Cushing’s syndrome, metabolic diseases, and delayed wound healing. Aldosterone synthase (CYP11B2) is the key enzyme for aldosterone biosynthesis and its inhibition is a promising approach for the treatment of congestive heart failure, cardiac fibrosis, and certain forms of hypertension. Both CYP11B1 and CYP11B2 are structurally very similar and expressed in the adrenal cortex. To facilitate the identification of novel inhibitors of these enzymes, ligand-based pharmacophore models of CYP11B1 and CYP11B2 inhibition were developed. A virtual screening of the SPECS database was performed with our pharmacophore queries. Biological evaluation of the selected hits lead to the discovery of three potent novel inhibitors of both CYP11B1 and CYP11B2 in the submicromolar range (compounds 8-10), one selective CYP11B1 inhibitor (Compound 11, IC50 = 2.5 µM), and one selective CYP11B2 inhibitor (compound 12, IC50 = 1.1 µM), respectively. The overall success rate of this prospective virtual screening experiment is 20.8% indicating good predictive power of the pharmacophore models.

Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification

PubMed Central

Ballester, Pedro J.; Mangold, Martina; Howard, Nigel I.; Robinson, Richard L. Marchese; Abell, Chris; Blumberger, Jochen; Mitchell, John B. O.

2012-01-01

One of the initial steps of modern drug discovery is the identification of small organic molecules able to inhibit a target macromolecule of therapeutic interest. A small proportion of these hits are further developed into lead compounds, which in turn may ultimately lead to a marketed drug. A commonly used screening protocol used for this task is high-throughput screening (HTS). However, the performance of HTS against antibacterial targets has generally been unsatisfactory, with high costs and low rates of hit identification. Here, we present a novel computational methodology that is able to identify a high proportion of structurally diverse inhibitors by searching unusually large molecular databases in a time-, cost- and resource-efficient manner. This virtual screening methodology was tested prospectively on two versions of an antibacterial target (type II dehydroquinase from Mycobacterium tuberculosis and Streptomyces coelicolor), for which HTS has not provided satisfactory results and consequently practically all known inhibitors are derivatives of the same core scaffold. Overall, our protocols identified 100 new inhibitors, with calculated Ki ranging from 4 to 250 μM (confirmed hit rates are 60% and 62% against each version of the target). Most importantly, over 50 new active molecular scaffolds were discovered that underscore the benefits that a wide application of prospectively validated in silico screening tools is likely to bring to antibacterial hit identification. PMID:22933186

Hierarchical virtual screening for the discovery of new molecular scaffolds in antibacterial hit identification.

PubMed

Ballester, Pedro J; Mangold, Martina; Howard, Nigel I; Robinson, Richard L Marchese; Abell, Chris; Blumberger, Jochen; Mitchell, John B O

2012-12-07

One of the initial steps of modern drug discovery is the identification of small organic molecules able to inhibit a target macromolecule of therapeutic interest. A small proportion of these hits are further developed into lead compounds, which in turn may ultimately lead to a marketed drug. A commonly used screening protocol used for this task is high-throughput screening (HTS). However, the performance of HTS against antibacterial targets has generally been unsatisfactory, with high costs and low rates of hit identification. Here, we present a novel computational methodology that is able to identify a high proportion of structurally diverse inhibitors by searching unusually large molecular databases in a time-, cost- and resource-efficient manner. This virtual screening methodology was tested prospectively on two versions of an antibacterial target (type II dehydroquinase from Mycobacterium tuberculosis and Streptomyces coelicolor), for which HTS has not provided satisfactory results and consequently practically all known inhibitors are derivatives of the same core scaffold. Overall, our protocols identified 100 new inhibitors, with calculated K(i) ranging from 4 to 250 μM (confirmed hit rates are 60% and 62% against each version of the target). Most importantly, over 50 new active molecular scaffolds were discovered that underscore the benefits that a wide application of prospectively validated in silico screening tools is likely to bring to antibacterial hit identification.

Provisional in-silico biopharmaceutics classification (BCS) to guide oral drug product development

PubMed Central

Wolk, Omri; Agbaria, Riad; Dahan, Arik

2014-01-01

The main objective of this work was to investigate in-silico predictions of physicochemical properties, in order to guide oral drug development by provisional biopharmaceutics classification system (BCS). Four in-silico methods were used to estimate LogP: group contribution (CLogP) using two different software programs, atom contribution (ALogP), and element contribution (KLogP). The correlations (r2) of CLogP, ALogP and KLogP versus measured LogP data were 0.97, 0.82, and 0.71, respectively. The classification of drugs with reported intestinal permeability in humans was correct for 64.3%–72.4% of the 29 drugs on the dataset, and for 81.82%–90.91% of the 22 drugs that are passively absorbed using the different in-silico algorithms. Similar permeability classification was obtained with the various in-silico methods. The in-silico calculations, along with experimental melting points, were then incorporated into a thermodynamic equation for solubility estimations that largely matched the reference solubility values. It was revealed that the effect of melting point on the solubility is minor compared to the partition coefficient, and an average melting point (162.7°C) could replace the experimental values, with similar results. The in-silico methods classified 20.76% (±3.07%) as Class 1, 41.51% (±3.32%) as Class 2, 30.49% (±4.47%) as Class 3, and 6.27% (±4.39%) as Class 4. In conclusion, in-silico methods can be used for BCS classification of drugs in early development, from merely their molecular formula and without foreknowledge of their chemical structure, which will allow for the improved selection, engineering, and developability of candidates. These in-silico methods could enhance success rates, reduce costs, and accelerate oral drug products development. PMID:25284986

In-silico studies in Chinese herbal medicines' research: evaluation of in-silico methodologies and phytochemical data sources, and a review of research to date.

PubMed

Barlow, D J; Buriani, A; Ehrman, T; Bosisio, E; Eberini, I; Hylands, P J

2012-04-10

The available databases that catalogue information on traditional Chinese medicines are reviewed in terms of their content and utility for in-silico research on Chinese herbal medicines, as too are the various protein database resources, and the software available for use in such studies. The software available for bioinformatics and 'omics studies of Chinese herbal medicines are summarised, and a critical evaluation given of the various in-silico methods applied in screening Chinese herbal medicines, including classification trees, neural networks, support vector machines, docking and inverse docking algorithms. Recommendations are made regarding any future in-silico studies of Chinese herbal medicines. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Students as Virtual Scientists: An Exploration of Students' and Teachers' Perceived Realness of a Remote Electron Microscopy Investigation

ERIC Educational Resources Information Center

Childers, Gina; Jones, M. Gail

2015-01-01

Remote access technologies enable students to investigate science by utilizing scientific tools and communicating in real-time with scientists and researchers with only a computer and an Internet connection. Very little is known about student perceptions of how real remote investigations are and how immersed the students are in the experience.…

Learning from a Distance: High School Students' Perceptions of Virtual Presence, Motivation, and Science Identity during a Remote Microscopy Investigation

ERIC Educational Resources Information Center

Childers, Gina; Jones, M. Gail

2017-01-01

Through partnerships with scientists, students can now conduct research in science laboratories from a distance through remote access technologies. The purpose of this study was to explore factors that contribute to a remote learning environment by documenting high school students' perceptions of science motivation, science identity, and virtual…

Virtual microscopy in a veterinary curriculum.

PubMed

Sims, Michael H; Mendis-Handagama, Chamindrani; Moore, Robert N

2007-01-01

Teaching faculty in the University of Tennessee College of Veterinary Medicine assist students in their professional education by providing a new way of viewing microscopic slides digitally. Faculty who teach classes in which glass slides are used participate in a program called Virtual Microscopy. Glass slides are digitized using a state-of-the-art integrated system, and a personal computer functions as the "microscope." Additionally, distribution of the interactive images is enhanced because they are available to students online. The digital slide offers equivalent quality and resolution to the original glass slide viewed on a microscope and has several additional advantages over microscopes. Students can choose to examine the entire slide at any of several objectives; they are able to access the slides (called WebSlides) from the college's server, using either Internet Explorer or a special browser developed by Bacus Laboratories, Inc.,(a) called the WebSlide browser, which lets the student simultaneously view a low-objective image and one or two high-objective images of the same slide. The student can "move the slide" by clicking and dragging the image to a new location. Easy archiving, annotation of images, and Web conferencing are additional features of the system.

State of the art and trends for digital pathology.

PubMed

García Rojo, Marcial

2012-01-01

Anatomic pathology is a medical specialty where both information management systems and digital images systems paly a most important role. Digital pathology is a new concept that considers all uses of this information, including diagnosis, biomedical research and education. Virtual microscopy or whole slide imaging, resulting in digital slides, is an outreaching technology in anatomic pathology. Limiting factors in the expansion of virtual microscopy are formidable storage dimension, scanning speed, quality of image and cultural change. Anatomic pathology data and images should be an important part of the patient electronic health records as well as of clinical data warehouse, epidemiological or biomedical research databases, and platforms dedicated to translational medicine. Integrating anatomic pathology to the "healthcare enterprise" can only be achieved using existing and emerging medical informatics standards like Digital Imaging and Communications in Medicine (DICOM®¹), Health Level Seven (HL7®), and Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT®), following the recommendations of Integrating the Healthcare Enterprise (IHE®). The consequences of the full digitalization of pathology departments are hard to foresee, but short term issues have arisen that imply interesting challenges for health care standards bodies.

In silico fragment-based drug design.

PubMed

Konteatis, Zenon D

2010-11-01

In silico fragment-based drug design (FBDD) is a relatively new approach inspired by the success of the biophysical fragment-based drug discovery field. Here, we review the progress made by this approach in the last decade and showcase how it complements and expands the capabilities of biophysical FBDD and structure-based drug design to generate diverse, efficient drug candidates. Advancements in several areas of research that have enabled the development of in silico FBDD and some applications in drug discovery projects are reviewed. The reader is introduced to various computational methods that are used for in silico FBDD, the fragment library composition for this technique, special applications used to identify binding sites on the surface of proteins and how to assess the druggability of these sites. In addition, the reader will gain insight into the proper application of this approach from examples of successful programs. In silico FBDD captures a much larger chemical space than high-throughput screening and biophysical FBDD increasing the probability of developing more diverse, patentable and efficient molecules that can become oral drugs. The application of in silico FBDD holds great promise for historically challenging targets such as protein-protein interactions. Future advances in force fields, scoring functions and automated methods for determining synthetic accessibility will all aid in delivering more successes with in silico FBDD.

Assessment of the predictive accuracy of five in silico prediction tools, alone or in combination, and two metaservers to classify long QT syndrome gene mutations.

PubMed

Leong, Ivone U S; Stuckey, Alexander; Lai, Daniel; Skinner, Jonathan R; Love, Donald R

2015-05-13

Long QT syndrome (LQTS) is an autosomal dominant condition predisposing to sudden death from malignant arrhythmia. Genetic testing identifies many missense single nucleotide variants of uncertain pathogenicity. Establishing genetic pathogenicity is an essential prerequisite to family cascade screening. Many laboratories use in silico prediction tools, either alone or in combination, or metaservers, in order to predict pathogenicity; however, their accuracy in the context of LQTS is unknown. We evaluated the accuracy of five in silico programs and two metaservers in the analysis of LQTS 1-3 gene variants. The in silico tools SIFT, PolyPhen-2, PROVEAN, SNPs&GO and SNAP, either alone or in all possible combinations, and the metaservers Meta-SNP and PredictSNP, were tested on 312 KCNQ1, KCNH2 and SCN5A gene variants that have previously been characterised by either in vitro or co-segregation studies as either "pathogenic" (283) or "benign" (29). The accuracy, sensitivity, specificity and Matthews Correlation Coefficient (MCC) were calculated to determine the best combination of in silico tools for each LQTS gene, and when all genes are combined. The best combination of in silico tools for KCNQ1 is PROVEAN, SNPs&GO and SIFT (accuracy 92.7%, sensitivity 93.1%, specificity 100% and MCC 0.70). The best combination of in silico tools for KCNH2 is SIFT and PROVEAN or PROVEAN, SNPs&GO and SIFT. Both combinations have the same scores for accuracy (91.1%), sensitivity (91.5%), specificity (87.5%) and MCC (0.62). In the case of SCN5A, SNAP and PROVEAN provided the best combination (accuracy 81.4%, sensitivity 86.9%, specificity 50.0%, and MCC 0.32). When all three LQT genes are combined, SIFT, PROVEAN and SNAP is the combination with the best performance (accuracy 82.7%, sensitivity 83.0%, specificity 80.0%, and MCC 0.44). Both metaservers performed better than the single in silico tools; however, they did not perform better than the best performing combination of in silico tools. The combination of in silico tools with the best performance is gene-dependent. The in silico tools reported here may have some value in assessing variants in the KCNQ1 and KCNH2 genes, but caution should be taken when the analysis is applied to SCN5A gene variants.

Virtual substrate method for nanomaterials characterization

PubMed Central

Da, Bo; Liu, Jiangwei; Yamamoto, Mahito; Ueda, Yoshihiro; Watanabe, Kazuyuki; Cuong, Nguyen Thanh; Li, Songlin; Tsukagoshi, Kazuhito; Yoshikawa, Hideki; Iwai, Hideo; Tanuma, Shigeo; Guo, Hongxuan; Gao, Zhaoshun; Sun, Xia; Ding, Zejun

2017-01-01

Characterization techniques available for bulk or thin-film solid-state materials have been extended to substrate-supported nanomaterials, but generally non-quantitatively. This is because the nanomaterial signals are inevitably buried in the signals from the underlying substrate in common reflection-configuration techniques. Here, we propose a virtual substrate method, inspired by the four-point probe technique for resistance measurement as well as the chop-nod method in infrared astronomy, to characterize nanomaterials without the influence of underlying substrate signals from four interrelated measurements. By implementing this method in secondary electron (SE) microscopy, a SE spectrum (white electrons) associated with the reflectivity difference between two different substrates can be tracked and controlled. The SE spectrum is used to quantitatively investigate the covering nanomaterial based on subtle changes in the transmission of the nanomaterial with high efficiency rivalling that of conventional core-level electrons. The virtual substrate method represents a benchmark for surface analysis to provide ‘free-standing' information about supported nanomaterials. PMID:28548114

In silico simulations of tunneling barrier measurements for molecular orbital-mediated junctions: A molecular orbital theory approach to scanning tunneling microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Terryn, Raymond J.; Sriraman, Krishnan; Olson, Joel A., E-mail: jolson@fit.edu

A new simulator for scanning tunneling microscopy (STM) is presented based on the linear combination of atomic orbitals molecular orbital (LCAO-MO) approximation for the effective tunneling Hamiltonian, which leads to the convolution integral when applied to the tip interaction with the sample. This approach intrinsically includes the structure of the STM tip. Through this mechanical emulation and the tip-inclusive convolution model, dI/dz images for molecular orbitals (which are closely associated with apparent barrier height, ϕ{sub ap}) are reported for the first time. For molecular adsorbates whose experimental topographic images correspond well to isolated-molecule quantum chemistry calculations, the simulator makes accuratemore » predictions, as illustrated by various cases. Distortions in these images due to the tip are shown to be in accord with those observed experimentally and predicted by other ab initio considerations of tip structure. Simulations of the tunneling current dI/dz images are in strong agreement with experiment. The theoretical framework provides a solid foundation which may be applied to LCAO cluster models of adsorbate–substrate systems, and is extendable to emulate several aspects of functional STM operation.« less

Evaluations of carbon nanotube field emitters for electron microscopy

NASA Astrophysics Data System (ADS)

Nakahara, Hitoshi; Kusano, Yoshikazu; Kono, Takumi; Saito, Yahachi

2009-11-01

Brightness of carbon nanotube (CNT) emitters was already reported elsewhere. However, brightness of electron emitter is affected by a virtual source size of the emitter, which strongly depends on electron optical configuration around the emitter. In this work, I- V characteristics and brightness of a CNT emitter are measured under a practical field emission electron gun (e-gun) configuration to investigate availability of CNT for electron microscopy. As a result, it is obtained that an emission area of MWNT is smaller than its tip surface area, and the emission area corresponds to a five-membered-ring with 2nd nearest six-membered-rings on the MWNT cap surface. Reduced brightness of MWNT is measured as at least 2.6×109 A/m 2 sr V. It is concluded that even a thick MWNT has enough brightness under a practical e-gun electrode configuration and suitable for electron microscopy.

Dermatopathology education in the era of modern technology.

PubMed

Shahriari, Neda; Grant-Kels, Jane; Murphy, Michael J

2017-09-01

Continuing technological advances are inevitably impacting the study and practice of dermatopathology (DP). We are seeing the transition from glass slide microscopy to virtual microscopy, which is serving both as an accessible educational medium for medical students, residents and fellows in the form of online databases and atlases, as well as a research tool to better inform us regarding the development of visual diagnostic expertise. Expansion in mobile technology is simplifying slide image attainment and providing greater opportunities for phone- and tablet-based microscopy, including teledermatopathology instruction and consultation in resource-poor areas with lack of specialists. Easily accessible mobile and computer-based applications ("apps"), including myDermPath and Clearpath, are providing an interactive medium for DP instruction. The Internet and social networking sites are enabling rapid global communication of DP information and image-sharing, promoting collaborative diagnostic research and scholastic endeavors. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Super-nonlinear fluorescence microscopy for high-contrast deep tissue imaging

NASA Astrophysics Data System (ADS)

Wei, Lu; Zhu, Xinxin; Chen, Zhixing; Min, Wei

2014-02-01

Two-photon excited fluorescence microscopy (TPFM) offers the highest penetration depth with subcellular resolution in light microscopy, due to its unique advantage of nonlinear excitation. However, a fundamental imaging-depth limit, accompanied by a vanishing signal-to-background contrast, still exists for TPFM when imaging deep into scattering samples. Formally, the focusing depth, at which the in-focus signal and the out-of-focus background are equal to each other, is defined as the fundamental imaging-depth limit. To go beyond this imaging-depth limit of TPFM, we report a new class of super-nonlinear fluorescence microscopy for high-contrast deep tissue imaging, including multiphoton activation and imaging (MPAI) harnessing novel photo-activatable fluorophores, stimulated emission reduced fluorescence (SERF) microscopy by adding a weak laser beam for stimulated emission, and two-photon induced focal saturation imaging with preferential depletion of ground-state fluorophores at focus. The resulting image contrasts all exhibit a higher-order (third- or fourth- order) nonlinear signal dependence on laser intensity than that in the standard TPFM. Both the physical principles and the imaging demonstrations will be provided for each super-nonlinear microscopy. In all these techniques, the created super-nonlinearity significantly enhances the imaging contrast and concurrently extends the imaging depth-limit of TPFM. Conceptually different from conventional multiphoton processes mediated by virtual states, our strategy constitutes a new class of fluorescence microscopy where high-order nonlinearity is mediated by real population transfer.

Robust graphene membranes in a silicon carbide frame.

PubMed

Waldmann, Daniel; Butz, Benjamin; Bauer, Sebastian; Englert, Jan M; Jobst, Johannes; Ullmann, Konrad; Fromm, Felix; Ammon, Maximilian; Enzelberger, Michael; Hirsch, Andreas; Maier, Sabine; Schmuki, Patrik; Seyller, Thomas; Spiecker, Erdmann; Weber, Heiko B

2013-05-28

We present a fabrication process for freely suspended membranes consisting of bi- and trilayer graphene grown on silicon carbide. The procedure, involving photoelectrochemical etching, enables the simultaneous fabrication of hundreds of arbitrarily shaped membranes with an area up to 500 μm(2) and a yield of around 90%. Micro-Raman and atomic force microscopy measurements confirm that the graphene layer withstands the electrochemical etching and show that the membranes are virtually unstrained. The process delivers membranes with a cleanliness suited for high-resolution transmission electron microscopy (HRTEM) at atomic scale. The membrane, and its frame, is very robust with respect to thermal cycling above 1000 °C as well as harsh acidic or alkaline treatment.

Photoinduced force microscopy: A technique for hyperspectral nanochemical mapping

NASA Astrophysics Data System (ADS)

Murdick, Ryan A.; Morrison, William; Nowak, Derek; Albrecht, Thomas R.; Jahng, Junghoon; Park, Sung

2017-08-01

Advances in nanotechnology have intensified the need for tools that can characterize newly synthesized nanomaterials. A variety of techniques has recently been shown which combines atomic force microscopy (AFM) with optical illumination including tip-enhanced Raman spectroscopy (TERS), scattering-type scanning near-field optical microscopy (sSNOM), and photothermal induced resonance microscopy (PTIR). To varying degrees, these existing techniques enable optical spectroscopy with the nanoscale spatial resolution inherent to AFM, thereby providing nanochemical interrogation of a specimen. Here we discuss photoinduced force microscopy (PiFM), a recently developed technique for nanoscale optical spectroscopy that exploits image forces acting between an AFM tip and sample to detect wavelength-dependent polarization within the sample to generate absorption spectra. This approach enables ∼10 nm spatial resolution with spectra that show correlation with macroscopic optical absorption spectra. Unlike other techniques, PiFM achieves this high resolution with virtually no constraints on sample or substrate properties. The applicability of PiFM to a variety of archetypal systems is reported here, highlighting the potential of PiFM as a useful tool for a wide variety of industrial and academic investigations, including semiconducting nanoparticles, nanocellulose, block copolymers, and low dimensional systems, as well as chemical and morphological mixing at interfaces.

In silico platform for xenobiotics ADME-T pharmacological properties modeling and prediction. Part II: The body in a Hilbertian space.

PubMed

Jacob, Alexandre; Pratuangdejkul, Jaturong; Buffet, Sébastien; Launay, Jean-Marie; Manivet, Philippe

2009-04-01

We have broken old surviving dogmas and concepts used in computational chemistry and created an efficient in silico ADME-T pharmacological properties modeling and prediction toolbox for any xenobiotic. With the help of an innovative and pragmatic approach combining various in silico techniques, like molecular modeling, quantum chemistry and in-house developed algorithms, the interactions between drugs and those enzymes, transporters and receptors involved in their biotransformation can be studied. ADME-T pharmacological parameters can then be predicted after in vitro and in vivo validations of in silico models.

Molecular imaging of melanin distribution in vivo and quantitative differential diagnosis of human pigmented lesions using label-free harmonic generation biopsy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Sun, Chi-Kuang; Wei, Ming-Liang; Su, Yu-Hsiang; Weng, Wei-Hung; Liao, Yi-Hua

2017-02-01

Harmonic generation microscopy is a noninvasive repetitive imaging technique that provides real-time 3D microscopic images of human skin with a sub-femtoliter resolution and high penetration down to the reticular dermis. In this talk, we show that with a strong resonance effect, the third-harmonic-generation (THG) modality provides enhanced contrast on melanin and allows not only differential diagnosis of various pigmented skin lesions but also quantitative imaging for longterm tracking. This unique capability makes THG microscopy the only label-free technique capable of identifying the active melanocytes in human skin and to image their different dendriticity patterns. In this talk, we will review our recent efforts to in vivo image melanin distribution and quantitatively diagnose pigmented skin lesions using label-free harmonic generation biopsy. This talk will first cover the spectroscopic study on the melanin enhanced THG effect in human cells and the calibration strategy inside human skin for quantitative imaging. We will then review our recent clinical trials including: differential diagnosis capability study on pigmented skin tumors; as well as quantitative virtual biopsy study on pre- and post- treatment evaluation on melasma and solar lentigo. Our study indicates the unmatched capability of harmonic generation microscopy to perform virtual biopsy for noninvasive histopathological diagnosis of various pigmented skin tumors, as well as its unsurpassed capability to noninvasively reveal the pathological origin of different hyperpigmentary diseases on human face as well as to monitor the efficacy of laser depigmentation treatments. This work is sponsored by National Health Research Institutes.

RUCS: rapid identification of PCR primers for unique core sequences.

PubMed

Thomsen, Martin Christen Frølund; Hasman, Henrik; Westh, Henrik; Kaya, Hülya; Lund, Ole

2017-12-15

Designing PCR primers to target a specific selection of whole genome sequenced strains can be a long, arduous and sometimes impractical task. Such tasks would benefit greatly from an automated tool to both identify unique targets, and to validate the vast number of potential primer pairs for the targets in silico. Here we present RUCS, a program that will find PCR primer pairs and probes for the unique core sequences of a positive genome dataset complement to a negative genome dataset. The resulting primer pairs and probes are in addition to simple selection also validated through a complex in silico PCR simulation. We compared our method, which identifies the unique core sequences, against an existing tool called ssGeneFinder, and found that our method was 6.5-20 times more sensitive. We used RUCS to design primer pairs that would target a set of genomes known to contain the mcr-1 colistin resistance gene. Three of the predicted pairs were chosen for experimental validation using PCR and gel electrophoresis. All three pairs successfully produced an amplicon with the target length for the samples containing mcr-1 and no amplification products were produced for the negative samples. The novel methods presented in this manuscript can reduce the time needed to identify target sequences, and provide a quick virtual PCR validation to eliminate time wasted on ambiguously binding primers. Source code is freely available on https://bitbucket.org/genomicepidemiology/rucs. Web service is freely available on https://cge.cbs.dtu.dk/services/RUCS. mcft@cbs.dtu.dk. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Rational drug design for anti-cancer chemotherapy: multi-target QSAR models for the in silico discovery of anti-colorectal cancer agents.

PubMed

Speck-Planche, Alejandro; Kleandrova, Valeria V; Luan, Feng; Cordeiro, M Natália D S

2012-08-01

The discovery of new and more potent anti-cancer agents constitutes one of the most active fields of research in chemotherapy. Colorectal cancer (CRC) is one of the most studied cancers because of its high prevalence and number of deaths. In the current pharmaceutical design of more efficient anti-CRC drugs, the use of methodologies based on Chemoinformatics has played a decisive role, including Quantitative-Structure-Activity Relationship (QSAR) techniques. However, until now, there is no methodology able to predict anti-CRC activity of compounds against more than one CRC cell line, which should constitute the principal goal. In an attempt to overcome this problem we develop here the first multi-target (mt) approach for the virtual screening and rational in silico discovery of anti-CRC agents against ten cell lines. Here, two mt-QSAR classification models were constructed using a large and heterogeneous database of compounds. The first model was based on linear discriminant analysis (mt-QSAR-LDA) employing fragment-based descriptors while the second model was obtained using artificial neural networks (mt-QSAR-ANN) with global 2D descriptors. Both models correctly classified more than 90% of active and inactive compounds in training and prediction sets. Some fragments were extracted from the molecules and their contributions to anti-CRC activity were calculated using mt-QSAR-LDA model. Several fragments were identified as potential substructural features responsible for the anti-CRC activity and new molecules designed from those fragments with positive contributions were suggested and correctly predicted by the two models as possible potent and versatile anti-CRC agents. Copyright © 2012 Elsevier Ltd. All rights reserved.

Novel Non-Peptide Inhibitors against SmCL1 of Schistosoma mansoni: In Silico Elucidation, Implications and Evaluation via Knowledge Based Drug Discovery

PubMed Central

Zafar, Atif; Ahmad, Sabahuddin; Rizvi, Asim; Ahmad, Masood

2015-01-01

Schistosomiasis is a major endemic disease known for excessive mortality and morbidity in developing countries. Because praziquantel is the only drug available for its treatment, the risk of drug resistance emphasizes the need to discover new drugs for this disease. Cathepsin SmCL1 is the critical target for drug design due to its essential role in the digestion of host proteins for growth and development of Schistosoma mansoni. Inhibiting the function of SmCL1 could control the wide spread of infections caused by S. mansoni in humans. With this objective, a homology modeling approach was used to obtain theoretical three-dimensional (3D) structure of SmCL1. In order to find the potential inhibitors of SmCL1, a plethora of in silico techniques were employed to screen non-peptide inhibitors against SmCL1 via structure-based drug discovery protocol. Receiver operating characteristic (ROC) curve analysis and molecular dynamics (MD) simulation were performed on the results of docked protein-ligand complexes to identify top ranking molecules against the modelled 3D structure of SmCL1. MD simulation results suggest the phytochemical Simalikalactone-D as a potential lead against SmCL1, whose pharmacophore model may be useful for future screening of potential drug molecules. To conclude, this is the first report to discuss the virtual screening of non-peptide inhibitors against SmCL1 of S. mansoni, with significant therapeutic potential. Results presented herein provide a valuable contribution to identify the significant leads and further derivatize them to suitable drug candidates for antischistosomal therapy. PMID:25933436

in silico Whole Genome Sequencer & Analyzer (iWGS): A Computational Pipeline to Guide the Design and Analysis of de novo Genome Sequencing Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Xiaofan; Peris, David; Kominek, Jacek

The availability of genomes across the tree of life is highly biased toward vertebrates, pathogens, human disease models, and organisms with relatively small and simple genomes. Recent progress in genomics has enabled the de novo decoding of the genome of virtually any organism, greatly expanding its potential for understanding the biology and evolution of the full spectrum of biodiversity. The increasing diversity of sequencing technologies, assays, and de novo assembly algorithms have augmented the complexity of de novo genome sequencing projects in nonmodel organisms. To reduce the costs and challenges in de novo genome sequencing projects and streamline their experimentalmore » design and analysis, we developed iWGS (in silico Whole Genome Sequencer and Analyzer), an automated pipeline for guiding the choice of appropriate sequencing strategy and assembly protocols. iWGS seamlessly integrates the four key steps of a de novo genome sequencing project: data generation (through simulation), data quality control, de novo assembly, and assembly evaluation and validation. The last three steps can also be applied to the analysis of real data. iWGS is designed to enable the user to have great flexibility in testing the range of experimental designs available for genome sequencing projects, and supports all major sequencing technologies and popular assembly tools. Three case studies illustrate how iWGS can guide the design of de novo genome sequencing projects, and evaluate the performance of a wide variety of user-specified sequencing strategies and assembly protocols on genomes of differing architectures. iWGS, along with a detailed documentation, is freely available at https://github.com/zhouxiaofan1983/iWGS.« less

Utilizing random Forest QSAR models with optimized parameters for target identification and its application to target-fishing server.

PubMed

Lee, Kyoungyeul; Lee, Minho; Kim, Dongsup

2017-12-28

The identification of target molecules is important for understanding the mechanism of "target deconvolution" in phenotypic screening and "polypharmacology" of drugs. Because conventional methods of identifying targets require time and cost, in-silico target identification has been considered an alternative solution. One of the well-known in-silico methods of identifying targets involves structure activity relationships (SARs). SARs have advantages such as low computational cost and high feasibility; however, the data dependency in the SAR approach causes imbalance of active data and ambiguity of inactive data throughout targets. We developed a ligand-based virtual screening model comprising 1121 target SAR models built using a random forest algorithm. The performance of each target model was tested by employing the ROC curve and the mean score using an internal five-fold cross validation. Moreover, recall rates for top-k targets were calculated to assess the performance of target ranking. A benchmark model using an optimized sampling method and parameters was examined via external validation set. The result shows recall rates of 67.6% and 73.9% for top-11 (1% of the total targets) and top-33, respectively. We provide a website for users to search the top-k targets for query ligands available publicly at http://rfqsar.kaist.ac.kr . The target models that we built can be used for both predicting the activity of ligands toward each target and ranking candidate targets for a query ligand using a unified scoring scheme. The scores are additionally fitted to the probability so that users can estimate how likely a ligand-target interaction is active. The user interface of our web site is user friendly and intuitive, offering useful information and cross references.

Crops in silico: A community wide multi-scale computational modeling framework of plant canopies

NASA Astrophysics Data System (ADS)

Srinivasan, V.; Christensen, A.; Borkiewic, K.; Yiwen, X.; Ellis, A.; Panneerselvam, B.; Kannan, K.; Shrivastava, S.; Cox, D.; Hart, J.; Marshall-Colon, A.; Long, S.

2016-12-01

Current crop models predict a looming gap between supply and demand for primary foodstuffs over the next 100 years. While significant yield increases were achieved in major food crops during the early years of the green revolution, the current rates of yield increases are insufficient to meet future projected food demand. Furthermore, with projected reduction in arable land, decrease in water availability, and increasing impacts of climate change on future food production, innovative technologies are required to sustainably improve crop yield. To meet these challenges, we are developing Crops in silico (Cis), a biologically informed, multi-scale, computational modeling framework that can facilitate whole plant simulations of crop systems. The Cis framework is capable of linking models of gene networks, protein synthesis, metabolic pathways, physiology, growth, and development in order to investigate crop response to different climate scenarios and resource constraints. This modeling framework will provide the mechanistic details to generate testable hypotheses toward accelerating directed breeding and engineering efforts to increase future food security. A primary objective for building such a framework is to create synergy among an inter-connected community of biologists and modelers to create a realistic virtual plant. This framework advantageously casts the detailed mechanistic understanding of individual plant processes across various scales in a common scalable framework that makes use of current advances in high performance and parallel computing. We are currently designing a user friendly interface that will make this tool equally accessible to biologists and computer scientists. Critically, this framework will provide the community with much needed tools for guiding future crop breeding and engineering, understanding the emergent implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment.

in silico Whole Genome Sequencer & Analyzer (iWGS): A Computational Pipeline to Guide the Design and Analysis of de novo Genome Sequencing Studies

DOE PAGES

Zhou, Xiaofan; Peris, David; Kominek, Jacek; ...

2016-09-16

The availability of genomes across the tree of life is highly biased toward vertebrates, pathogens, human disease models, and organisms with relatively small and simple genomes. Recent progress in genomics has enabled the de novo decoding of the genome of virtually any organism, greatly expanding its potential for understanding the biology and evolution of the full spectrum of biodiversity. The increasing diversity of sequencing technologies, assays, and de novo assembly algorithms have augmented the complexity of de novo genome sequencing projects in nonmodel organisms. To reduce the costs and challenges in de novo genome sequencing projects and streamline their experimentalmore » design and analysis, we developed iWGS (in silico Whole Genome Sequencer and Analyzer), an automated pipeline for guiding the choice of appropriate sequencing strategy and assembly protocols. iWGS seamlessly integrates the four key steps of a de novo genome sequencing project: data generation (through simulation), data quality control, de novo assembly, and assembly evaluation and validation. The last three steps can also be applied to the analysis of real data. iWGS is designed to enable the user to have great flexibility in testing the range of experimental designs available for genome sequencing projects, and supports all major sequencing technologies and popular assembly tools. Three case studies illustrate how iWGS can guide the design of de novo genome sequencing projects, and evaluate the performance of a wide variety of user-specified sequencing strategies and assembly protocols on genomes of differing architectures. iWGS, along with a detailed documentation, is freely available at https://github.com/zhouxiaofan1983/iWGS.« less

In silico probing and biological evaluation of SETDB1/ESET-targeted novel compounds that reduce tri-methylated histone H3K9 (H3K9me3) level

NASA Astrophysics Data System (ADS)

Park, Insun; Hwang, Yu Jin; Kim, TaeHun; Viswanath, Ambily Nath Indu; Londhe, Ashwini M.; Jung, Seo Yun; Sim, Kyoung Mi; Min, Sun-Joon; Lee, Ji Eun; Seong, Jihye; Kim, Yun Kyung; No, Kyoung Tai; Ryu, Hoon; Pae, Ae Nim

2017-10-01

ERG-associated protein with the SET domain (ESET/SET domain bifurcated 1/SETDB1/KMT1E) is a histone lysine methyltransferase (HKMT) and it preferentially tri-methylates lysine 9 of histone H3 (H3K9me3). SETDB1/ESET leads to heterochromatin condensation and epigenetic gene silencing. These functional changes are reported to correlate with Huntington's disease (HD) progression and mood-related disorders which make SETDB1/ESET a viable drug target. In this context, the present investigation was performed to identify novel peptide-competitive small molecule inhibitors of the SETDB1/ESET by a combined in silico-in vitro approach. A ligand-based pharmacophore model was built and employed for the virtual screening of ChemDiv and Asinex database. Also, a human SETDB1/ESET homology model was constructed to supplement the data further. Biological evaluation of the selected 21 candidates singled out 5 compounds exhibiting a notable reduction of the H3K9me3 level via inhibitory potential of SETDB1/ESET activity in SETDB1/ESET-inducible cell line and HD striatal cells. Later on, we identified two compounds as final hits that appear to have neuronal effects without cytotoxicity based on the result from MTT assay. These compounds hold the calibre to become the future lead compounds and can provide structural insights into more SETDB1/ESET-focused drug discovery research. Moreover, these SETDB1/ESET inhibitors may be applicable for the preclinical study to ameliorate neurodegenerative disorders via epigenetic regulation.

Crystal structure of the mobile metallo-β-lactamase AIM-1 from Pseudomonas aeruginosa: insights into antibiotic binding and the role of Gln157.

PubMed

Leiros, Hanna-Kirsti S; Borra, Pardha S; Brandsdal, Bjørn Olav; Edvardsen, Kine Susann Waade; Spencer, James; Walsh, Timothy R; Samuelsen, Orjan

2012-08-01

Metallo-β-lactamase (MBL) genes confer resistance to virtually all β-lactam antibiotics and are rapidly disseminated by mobile genetic elements in Gram-negative bacteria. MBLs belong to three different subgroups, B1, B2, and B3, with the mobile MBLs largely confined to subgroup B1. The B3 MBLs are a divergent subgroup of predominantly chromosomally encoded enzymes. AIM-1 (Adelaide IMipenmase 1) from Pseudomonas aeruginosa was the first B3 MBL to be identified on a readily mobile genetic element. Here we present the crystal structure of AIM-1 and use in silico docking and quantum mechanics and molecular mechanics (QM/MM) calculations, together with site-directed mutagenesis, to investigate its interaction with β-lactams. AIM-1 adopts the characteristic αβ/βα sandwich fold of MBLs but differs from other B3 enzymes in the conformation of an active site loop (residues 156 to 162) which is involved both in disulfide bond formation and, we suggest, interaction with substrates. The structure, together with docking and QM/MM calculations, indicates that the AIM-1 substrate binding site is narrower and more restricted than those of other B3 MBLs, possibly explaining its higher catalytic efficiency. The location of Gln157 adjacent to the AIM-1 zinc center suggests a role in drug binding that is supported by our in silico studies. However, replacement of this residue by either Asn or Ala resulted in only modest reductions in AIM-1 activity against the majority of β-lactam substrates, indicating that this function is nonessential. Our study reveals AIM-1 to be a subclass B3 MBL with novel structural and mechanistic features.

Crystal Structure of the Mobile Metallo-β-Lactamase AIM-1 from Pseudomonas aeruginosa: Insights into Antibiotic Binding and the Role of Gln157

PubMed Central

Borra, Pardha S.; Brandsdal, Bjørn Olav; Edvardsen, Kine Susann Waade; Spencer, James; Walsh, Timothy R.; Samuelsen, Ørjan

2012-01-01

Metallo-β-lactamase (MBL) genes confer resistance to virtually all β-lactam antibiotics and are rapidly disseminated by mobile genetic elements in Gram-negative bacteria. MBLs belong to three different subgroups, B1, B2, and B3, with the mobile MBLs largely confined to subgroup B1. The B3 MBLs are a divergent subgroup of predominantly chromosomally encoded enzymes. AIM-1 (Adelaide IMipenmase 1) from Pseudomonas aeruginosa was the first B3 MBL to be identified on a readily mobile genetic element. Here we present the crystal structure of AIM-1 and use in silico docking and quantum mechanics and molecular mechanics (QM/MM) calculations, together with site-directed mutagenesis, to investigate its interaction with β-lactams. AIM-1 adopts the characteristic αβ/βα sandwich fold of MBLs but differs from other B3 enzymes in the conformation of an active site loop (residues 156 to 162) which is involved both in disulfide bond formation and, we suggest, interaction with substrates. The structure, together with docking and QM/MM calculations, indicates that the AIM-1 substrate binding site is narrower and more restricted than those of other B3 MBLs, possibly explaining its higher catalytic efficiency. The location of Gln157 adjacent to the AIM-1 zinc center suggests a role in drug binding that is supported by our in silico studies. However, replacement of this residue by either Asn or Ala resulted in only modest reductions in AIM-1 activity against the majority of β-lactam substrates, indicating that this function is nonessential. Our study reveals AIM-1 to be a subclass B3 MBL with novel structural and mechanistic features. PMID:22664968

In silico probing and biological evaluation of SETDB1/ESET-targeted novel compounds that reduce tri-methylated histone H3K9 (H3K9me3) level.

PubMed

Park, Insun; Hwang, Yu Jin; Kim, TaeHun; Viswanath, Ambily Nath Indu; Londhe, Ashwini M; Jung, Seo Yun; Sim, Kyoung Mi; Min, Sun-Joon; Lee, Ji Eun; Seong, Jihye; Kim, Yun Kyung; No, Kyoung Tai; Ryu, Hoon; Pae, Ae Nim

2017-10-01

ERG-associated protein with the SET domain (ESET/SET domain bifurcated 1/SETDB1/KMT1E) is a histone lysine methyltransferase (HKMT) and it preferentially tri-methylates lysine 9 of histone H3 (H3K9me3). SETDB1/ESET leads to heterochromatin condensation and epigenetic gene silencing. These functional changes are reported to correlate with Huntington's disease (HD) progression and mood-related disorders which make SETDB1/ESET a viable drug target. In this context, the present investigation was performed to identify novel peptide-competitive small molecule inhibitors of the SETDB1/ESET by a combined in silico-in vitro approach. A ligand-based pharmacophore model was built and employed for the virtual screening of ChemDiv and Asinex database. Also, a human SETDB1/ESET homology model was constructed to supplement the data further. Biological evaluation of the selected 21 candidates singled out 5 compounds exhibiting a notable reduction of the H3K9me3 level via inhibitory potential of SETDB1/ESET activity in SETDB1/ESET-inducible cell line and HD striatal cells. Later on, we identified two compounds as final hits that appear to have neuronal effects without cytotoxicity based on the result from MTT assay. These compounds hold the calibre to become the future lead compounds and can provide structural insights into more SETDB1/ESET-focused drug discovery research. Moreover, these SETDB1/ESET inhibitors may be applicable for the preclinical study to ameliorate neurodegenerative disorders via epigenetic regulation.

Scanning fluorescent microscopy is an alternative for quantitative fluorescent cell analysis.

PubMed

Varga, Viktor Sebestyén; Bocsi, József; Sipos, Ferenc; Csendes, Gábor; Tulassay, Zsolt; Molnár, Béla

2004-07-01

Fluorescent measurements on cells are performed today with FCM and laser scanning cytometry. The scientific community dealing with quantitative cell analysis would benefit from the development of a new digital multichannel and virtual microscopy based scanning fluorescent microscopy technology and from its evaluation on routine standardized fluorescent beads and clinical specimens. We applied a commercial motorized fluorescent microscope system. The scanning was done at 20 x (0.5 NA) magnification, on three channels (Rhodamine, FITC, Hoechst). The SFM (scanning fluorescent microscopy) software included the following features: scanning area, exposure time, and channel definition, autofocused scanning, densitometric and morphometric cellular feature determination, gating on scatterplots and frequency histograms, and preparation of galleries of the gated cells. For the calibration and standardization Immuno-Brite beads were used. With application of shading compensation, the CV of fluorescence of the beads decreased from 24.3% to 3.9%. Standard JPEG image compression until 1:150 resulted in no significant change. The change of focus influenced the CV significantly only after +/-5 microm error. SFM is a valuable method for the evaluation of fluorescently labeled cells. Copyright 2004 Wiley-Liss, Inc.

Different patterns of collagen-proteoglycan interaction: a scanning electron microscopy and atomic force microscopy study.

PubMed

Raspanti, M; Congiu, T; Alessandrini, A; Gobbi, P; Ruggeri, A

2000-01-01

The extracellular matrix of unfixed, unstained rat corneal stroma, visualized with high-resolution scanning electron microscopy and atomic force microscopy after minimal preliminary treatment, appears composed of straight, parallel, uniform collagen fibrils regularly spaced by a three-dimensional, irregular network of thin, delicate proteoglycan filaments. Rat tail tendon, observed under identical conditions, appears instead made of heterogeneous, closely packed fibrils interwoven with orthogonal proteoglycan filaments. Pre-treatment with cupromeronic blue just thickens the filaments without affecting their spatial layout. Digestion with chondroitinase ABC rids the tendon matrix of all its interconnecting filaments while the corneal stroma architecture remains virtually unaffected, its fibrils always being separated by an evident interfibrillar spacing which is never observed in tendon. Our observations indicate that matrix proteoglycans are responsible for both the highly regular interfibrillar spacing which is distinctive of corneal stroma, and the strong interfibrillar binding observed in tendon. These opposite interaction patterns appear to be distinctive of different proteoglycan species. The molecular details of proteoglycan interactions are still incompletely understood and are the subject of ongoing research.

A data model and database for high-resolution pathology analytical image informatics.

PubMed

Wang, Fusheng; Kong, Jun; Cooper, Lee; Pan, Tony; Kurc, Tahsin; Chen, Wenjin; Sharma, Ashish; Niedermayr, Cristobal; Oh, Tae W; Brat, Daniel; Farris, Alton B; Foran, David J; Saltz, Joel

2011-01-01

The systematic analysis of imaged pathology specimens often results in a vast amount of morphological information at both the cellular and sub-cellular scales. While microscopy scanners and computerized analysis are capable of capturing and analyzing data rapidly, microscopy image data remain underutilized in research and clinical settings. One major obstacle which tends to reduce wider adoption of these new technologies throughout the clinical and scientific communities is the challenge of managing, querying, and integrating the vast amounts of data resulting from the analysis of large digital pathology datasets. This paper presents a data model, which addresses these challenges, and demonstrates its implementation in a relational database system. This paper describes a data model, referred to as Pathology Analytic Imaging Standards (PAIS), and a database implementation, which are designed to support the data management and query requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines on whole-slide images and tissue microarrays (TMAs). (1) Development of a data model capable of efficiently representing and storing virtual slide related image, annotation, markup, and feature information. (2) Development of a database, based on the data model, capable of supporting queries for data retrieval based on analysis and image metadata, queries for comparison of results from different analyses, and spatial queries on segmented regions, features, and classified objects. The work described in this paper is motivated by the challenges associated with characterization of micro-scale features for comparative and correlative analyses involving whole-slides tissue images and TMAs. Technologies for digitizing tissues have advanced significantly in the past decade. Slide scanners are capable of producing high-magnification, high-resolution images from whole slides and TMAs within several minutes. Hence, it is becoming increasingly feasible for basic, clinical, and translational research studies to produce thousands of whole-slide images. Systematic analysis of these large datasets requires efficient data management support for representing and indexing results from hundreds of interrelated analyses generating very large volumes of quantifications such as shape and texture and of classifications of the quantified features. We have designed a data model and a database to address the data management requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines. The data model represents virtual slide related image, annotation, markup and feature information. The database supports a wide range of metadata and spatial queries on images, annotations, markups, and features. We currently have three databases running on a Dell PowerEdge T410 server with CentOS 5.5 Linux operating system. The database server is IBM DB2 Enterprise Edition 9.7.2. The set of databases consists of 1) a TMA database containing image analysis results from 4740 cases of breast cancer, with 641 MB storage size; 2) an algorithm validation database, which stores markups and annotations from two segmentation algorithms and two parameter sets on 18 selected slides, with 66 GB storage size; and 3) an in silico brain tumor study database comprising results from 307 TCGA slides, with 365 GB storage size. The latter two databases also contain human-generated annotations and markups for regions and nuclei. Modeling and managing pathology image analysis results in a database provide immediate benefits on the value and usability of data in a research study. The database provides powerful query capabilities, which are otherwise difficult or cumbersome to support by other approaches such as programming languages. Standardized, semantic annotated data representation and interfaces also make it possible to more efficiently share image data and analysis results.

Unlocking the potential of publicly available microarray data using inSilicoDb and inSilicoMerging R/Bioconductor packages.

PubMed

Taminau, Jonatan; Meganck, Stijn; Lazar, Cosmin; Steenhoff, David; Coletta, Alain; Molter, Colin; Duque, Robin; de Schaetzen, Virginie; Weiss Solís, David Y; Bersini, Hugues; Nowé, Ann

2012-12-24

With an abundant amount of microarray gene expression data sets available through public repositories, new possibilities lie in combining multiple existing data sets. In this new context, analysis itself is no longer the problem, but retrieving and consistently integrating all this data before delivering it to the wide variety of existing analysis tools becomes the new bottleneck. We present the newly released inSilicoMerging R/Bioconductor package which, together with the earlier released inSilicoDb R/Bioconductor package, allows consistent retrieval, integration and analysis of publicly available microarray gene expression data sets. Inside the inSilicoMerging package a set of five visual and six quantitative validation measures are available as well. By providing (i) access to uniformly curated and preprocessed data, (ii) a collection of techniques to remove the batch effects between data sets from different sources, and (iii) several validation tools enabling the inspection of the integration process, these packages enable researchers to fully explore the potential of combining gene expression data for downstream analysis. The power of using both packages is demonstrated by programmatically retrieving and integrating gene expression studies from the InSilico DB repository [https://insilicodb.org/app/].

Stabilizers influence drug–polymer interactions and physicochemical properties of disulfiram-loaded poly-lactide-co-glycolide nanoparticles

PubMed Central

Hoda, Muddasarul; Sufi, Shamim Akhtar; Cavuturu, Bindumadhuri; Rajagopalan, Rukkumani

2018-01-01

Aim: Stabilizers are known to be an integral component of polymeric nanostructures. Ideally, they manipulate physicochemical properties of nanoparticles. Based on this hypothesis, we demonstrated that disulfiram (drug) and Poly-lactide-co-glycolide (polymer) interactions and physicochemical properties of their nanoparticles formulations are significantly influenced by the choice of stabilizers. Methodology: Electron microscopy, differential scanning calorimetry, x-ray diffraction, Raman spectrum analysis, isothermal titration calorimetry and in silico docking studies were performed. Results & discussion: Polysorbate 80 imparted highest crystallinity while Triton-X 100 imparted highest rigidity, possibly influencing drug bioavailability, blood-retention time, cellular uptake and sustained drug release. All the molecular interactions were hydrophobic in nature and entropy driven. Therefore, polymeric nanoparticles may be critically manipulated to streamline the passive targeting of drug-loaded nanoparticles. PMID:29379637

Simulation-based planning of surgical interventions in pediatric cardiology

NASA Astrophysics Data System (ADS)

Marsden, Alison

2012-11-01

Hemodynamics plays an essential role in the progression and treatment of cardiovascular disease. This is particularly true in pediatric cardiology, due to the wide variation in anatomy observed in congenital heart disease patients. While medical imaging provides increasingly detailed anatomical information, clinicians currently have limited knowledge of important fluid mechanical parameters. Treatment decisions are therefore often made using anatomical information alone, despite the known links between fluid mechanics and disease progression. Patient-specific simulations now offer the means to provide this missing information, and, more importantly, to perform in-silico testing of new surgical designs at no risk to the patient. In this talk, we will outline the current state of the art in methods for cardiovascular blood flow simulation and virtual surgery. We will then present new methodology for coupling optimization with simulation and uncertainty quantification to customize treatments for individual patients. Finally, we will present examples in pediatric cardiology that illustrate the potential impact of these tools in the clinical setting.

An In-Silico Investigation of Phytochemicals as Antiviral Agents Against Dengue Fever

PubMed Central

Powers, Chelsea N.; Setzer, William N.

2016-01-01

Abstract: A virtual screening analysis of our library of phytochemical structures with dengue virus protein targets has been carried out using a molecular docking approach. A total of 2194 plant-derived secondary metabolites have been docked. This molecule set comprised of 290 alkaloids (68 indole alkaloids, 153 isoquinoline alkaloids, 5 quinoline alkaloids, 13 piperidine alkaloids, 14 steroidal alkaloids, and 37 miscellaneous alkaloids), 678 terpenoids (47 monoterpenoids, 169 sesquiterpenoids, 265 diterpenoids, 81 steroids, and 96 triterpenoids), 20 aurones, 81 chalcones, 349 flavonoids, 120 isoflavonoids, 74 lignans, 58 stilbenoids, 169 miscellaneous polyphenolic compounds, 100 coumarins, 28 xanthones, 67 quinones, and 160 miscellaneous phytochemicals. Dengue virus protein targets examined included dengue virus protease (NS2B-NS3pro), helicase (NS3 helicase), methyltransferase (MTase), RNA-dependent RNA polymerase (RdRp), and the dengue virus envelope protein. Polyphenolic compounds, flavonoids, chalcones, and other phenolics were the most numerous of the strongly docking ligands for dengue virus protein targets. PMID:27151482

Combining bioinformatics, chemoinformatics and experimental approaches to design chemical probes: Applications in the field of blood coagulation.

PubMed

Villoutreix, B O

2016-07-01

Bioinformatics and chemoinformatics approaches contribute to the discovery of novel targets, chemical probes, hits, leads and medicinal drugs. A vast repertoire of computational methods has indeed been reported over the years and in this review, I will briefly introduce some concepts and approaches, namely the analysis of potential therapeutic target binding pockets, the preparation of compound collections and virtual screening. An example of application is provided for two proteins acting in the blood coagulation system. Overall, in silico methods have been shown to improve R and D productivity in both, academic settings and in the private sector, if they are integrated in a rational manner with experimental approaches. However, integration of tools and pluridisciplinarity are seldom achieved. Efforts should be done in this direction as pluridisciplinarity and a true acknowledgment of all the contributing actors along the value chain could enhance innovation and reduce skyrocketing costs. Copyright © 2016 Académie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.

Monte Carlo simulations guided by imaging to predict the in vitro ranking of radiosensitizing nanoparticles

PubMed Central

Retif, Paul; Reinhard, Aurélie; Paquot, Héna; Jouan-Hureaux, Valérie; Chateau, Alicia; Sancey, Lucie; Barberi-Heyob, Muriel; Pinel, Sophie; Bastogne, Thierry

2016-01-01

This article addresses the in silico–in vitro prediction issue of organometallic nanoparticles (NPs)-based radiosensitization enhancement. The goal was to carry out computational experiments to quickly identify efficient nanostructures and then to preferentially select the most promising ones for the subsequent in vivo studies. To this aim, this interdisciplinary article introduces a new theoretical Monte Carlo computational ranking method and tests it using 3 different organometallic NPs in terms of size and composition. While the ranking predicted in a classical theoretical scenario did not fit the reference results at all, in contrast, we showed for the first time how our accelerated in silico virtual screening method, based on basic in vitro experimental data (which takes into account the NPs cell biodistribution), was able to predict a relevant ranking in accordance with in vitro clonogenic efficiency. This corroborates the pertinence of such a prior ranking method that could speed up the preclinical development of NPs in radiation therapy. PMID:27920524

Contributions of computational chemistry and biophysical techniques to fragment-based drug discovery.

PubMed

Gozalbes, Rafael; Carbajo, Rodrigo J; Pineda-Lucena, Antonio

2010-01-01

In the last decade, fragment-based drug discovery (FBDD) has evolved from a novel approach in the search of new hits to a valuable alternative to the high-throughput screening (HTS) campaigns of many pharmaceutical companies. The increasing relevance of FBDD in the drug discovery universe has been concomitant with an implementation of the biophysical techniques used for the detection of weak inhibitors, e.g. NMR, X-ray crystallography or surface plasmon resonance (SPR). At the same time, computational approaches have also been progressively incorporated into the FBDD process and nowadays several computational tools are available. These stretch from the filtering of huge chemical databases in order to build fragment-focused libraries comprising compounds with adequate physicochemical properties, to more evolved models based on different in silico methods such as docking, pharmacophore modelling, QSAR and virtual screening. In this paper we will review the parallel evolution and complementarities of biophysical techniques and computational methods, providing some representative examples of drug discovery success stories by using FBDD.

Ring system-based chemical graph generation for de novo molecular design

NASA Astrophysics Data System (ADS)

Miyao, Tomoyuki; Kaneko, Hiromasa; Funatsu, Kimito

2016-05-01

Generating chemical graphs in silico by combining building blocks is important and fundamental in virtual combinatorial chemistry. A premise in this area is that generated structures should be irredundant as well as exhaustive. In this study, we develop structure generation algorithms regarding combining ring systems as well as atom fragments. The proposed algorithms consist of three parts. First, chemical structures are generated through a canonical construction path. During structure generation, ring systems can be treated as reduced graphs having fewer vertices than those in the original ones. Second, diversified structures are generated by a simple rule-based generation algorithm. Third, the number of structures to be generated can be estimated with adequate accuracy without actual exhaustive generation. The proposed algorithms were implemented in structure generator Molgilla. As a practical application, Molgilla generated chemical structures mimicking rosiglitazone in terms of a two dimensional pharmacophore pattern. The strength of the algorithms lies in simplicity and flexibility. Therefore, they may be applied to various computer programs regarding structure generation by combining building blocks.

Identification and preliminary structure-activity relationships of 1-Indanone derivatives as novel indoleamine-2,3-dioxygenase 1 (IDO1) inhibitors.

PubMed

Gao, Dingding; Li, Yingxia

2017-07-15

Indoleamine 2,3-dioxygenase 1 (IDO1) plays a vital role in the catabolism of tryptophan along with the kynurenine pathway which is involved in many human diseases including cancer, Alzheimer's disease, etc. In this study, compound 1 bearing a 1-Indanone scaffold was identified as a novel IDO1 inhibitor by structure-based virtual screening, with moderate to good enzymatic and cellular inhibitory activities. Also, surface plasmon resonance analysis validated the direct interaction between compound 1 and IDO1 protein. The preliminary SAR was further explored and the binding mode with IDO1 protein was predicted by experiment along with molecular docking. Subsequent ADME properties of these active compounds were analyzed in silico, and the results showed good pharmacokinetic efficiencies. We believe this study contributes a lot to the structural diversity for the future development of highly potent IDO1 inhibitors. Copyright © 2017. Published by Elsevier Ltd.

CGBVS-DNN: Prediction of Compound-protein Interactions Based on Deep Learning.

PubMed

Hamanaka, Masatoshi; Taneishi, Kei; Iwata, Hiroaki; Ye, Jun; Pei, Jianguo; Hou, Jinlong; Okuno, Yasushi

2017-01-01

Computational prediction of compound-protein interactions (CPIs) is of great importance for drug design as the first step in in-silico screening. We previously proposed chemical genomics-based virtual screening (CGBVS), which predicts CPIs by using a support vector machine (SVM). However, the CGBVS has problems when training using more than a million datasets of CPIs since SVMs require an exponential increase in the calculation time and computer memory. To solve this problem, we propose the CGBVS-DNN, in which we use deep neural networks, a kind of deep learning technique, instead of the SVM. Deep learning does not require learning all input data at once because the network can be trained with small mini-batches. Experimental results show that the CGBVS-DNN outperformed the original CGBVS with a quarter million CPIs. Results of cross-validation show that the accuracy of the CGBVS-DNN reaches up to 98.2 % (σ<0.01) with 4 million CPIs. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

High performance in silico virtual drug screening on many-core processors.

PubMed

McIntosh-Smith, Simon; Price, James; Sessions, Richard B; Ibarra, Amaurys A

2015-05-01

Drug screening is an important part of the drug development pipeline for the pharmaceutical industry. Traditional, lab-based methods are increasingly being augmented with computational methods, ranging from simple molecular similarity searches through more complex pharmacophore matching to more computationally intensive approaches, such as molecular docking. The latter simulates the binding of drug molecules to their targets, typically protein molecules. In this work, we describe BUDE, the Bristol University Docking Engine, which has been ported to the OpenCL industry standard parallel programming language in order to exploit the performance of modern many-core processors. Our highly optimized OpenCL implementation of BUDE sustains 1.43 TFLOP/s on a single Nvidia GTX 680 GPU, or 46% of peak performance. BUDE also exploits OpenCL to deliver effective performance portability across a broad spectrum of different computer architectures from different vendors, including GPUs from Nvidia and AMD, Intel's Xeon Phi and multi-core CPUs with SIMD instruction sets.

High performance in silico virtual drug screening on many-core processors

PubMed Central

Price, James; Sessions, Richard B; Ibarra, Amaurys A

2015-01-01

Drug screening is an important part of the drug development pipeline for the pharmaceutical industry. Traditional, lab-based methods are increasingly being augmented with computational methods, ranging from simple molecular similarity searches through more complex pharmacophore matching to more computationally intensive approaches, such as molecular docking. The latter simulates the binding of drug molecules to their targets, typically protein molecules. In this work, we describe BUDE, the Bristol University Docking Engine, which has been ported to the OpenCL industry standard parallel programming language in order to exploit the performance of modern many-core processors. Our highly optimized OpenCL implementation of BUDE sustains 1.43 TFLOP/s on a single Nvidia GTX 680 GPU, or 46% of peak performance. BUDE also exploits OpenCL to deliver effective performance portability across a broad spectrum of different computer architectures from different vendors, including GPUs from Nvidia and AMD, Intel’s Xeon Phi and multi-core CPUs with SIMD instruction sets. PMID:25972727

Issues for application of virtual microscopy to cytoscreening, perspectives based on questionnaire to Japanese cytotechnologists

PubMed Central

Mori, Ichiro; Nunobiki, Osamu; Ozaki, Takashi; Taniguchi, Emiko; Kakudo, Kennichi

2008-01-01

To clarify the issues associated with the applications of virtual microscopy to the daily cytology slide screening, we conducted a survey at a slide conference of cytology. The survey was conducted specifically to the Japanese cytology technologists who use microscopes on a routine basis. Virtual slides (VS) were prepared from cytology slides using NanoZoomer (Hamamatsu Photonics, Japan), which is capable of adjusting focus on any part of the slide. A total of ten layers were scanned from the same slides, with 2 micrometer intervals. To simulate the cytology slide screening, no marker points were created. The total data volume of six slides was approximately 25 Giga Bytes. The slides were stored on the Windows 2003 Server, and were made accessible on the web to the cytology technologists. Most cytotechnologists answered "Satisfied" or "Acceptable" to the VS resolution and drawing speed, and "Dissatisfied" to the operation speed. To the ten layered focus, an answer "insufficient" was slightly more frequent than the answer "sufficient", while no one answered "fewer is acceptable" or "no need for depth". As for the use of cytology slide screening, answers "usable, but requires effort" and "not usable" were about equal in number. In a Japanese cytology meeting, a unique VS system has been used in slide conferences with markings to the discussion point for years. Therefore, Japanese cytotechnologists are relatively well accustomed to the use of VS, and the survey results showed that they regarded VS more positively than we expected. Currently, VS has the acceptable resolution and drawing speed even on the web. Most cytotechnologists regard the focusing capability crucial for cytology slide screening, but the consequential enlargement of data size, longer scanning time, and slower drawing speed are the issues that are yet to be resolved. PMID:18673503

An International Ki67 Reproducibility Study in Adrenal Cortical Carcinoma.

PubMed

Papathomas, Thomas G; Pucci, Eugenio; Giordano, Thomas J; Lu, Hao; Duregon, Eleonora; Volante, Marco; Papotti, Mauro; Lloyd, Ricardo V; Tischler, Arthur S; van Nederveen, Francien H; Nose, Vania; Erickson, Lori; Mete, Ozgur; Asa, Sylvia L; Turchini, John; Gill, Anthony J; Matias-Guiu, Xavier; Skordilis, Kassiani; Stephenson, Timothy J; Tissier, Frédérique; Feelders, Richard A; Smid, Marcel; Nigg, Alex; Korpershoek, Esther; van der Spek, Peter J; Dinjens, Winand N M; Stubbs, Andrew P; de Krijger, Ronald R

2016-04-01

Despite the established role of Ki67 labeling index in prognostic stratification of adrenocortical carcinomas and its recent integration into treatment flow charts, the reproducibility of the assessment method has not been determined. The aim of this study was to investigate interobserver variability among endocrine pathologists using a web-based virtual microscopy approach. Ki67-stained slides of 76 adrenocortical carcinomas were analyzed independently by 14 observers, each according to their method of preference including eyeballing, formal manual counting, and digital image analysis. The interobserver variation was statistically significant (P<0.001) in the absence of any correlation between the various methods. Subsequently, 61 static images were distributed among 15 observers who were instructed to follow a category-based scoring approach. Low levels of interobserver (F=6.99; Fcrit=1.70; P<0.001) as well as intraobserver concordance (n=11; Cohen κ ranging from -0.057 to 0.361) were detected. To improve harmonization of Ki67 analysis, we tested the utility of an open-source Galaxy virtual machine application, namely Automated Selection of Hotspots, in 61 virtual slides. The software-provided Ki67 values were validated by digital image analysis in identical images, displaying a strong correlation of 0.96 (P<0.0001) and dividing the cases into 3 classes (cutoffs of 0%-15%-30% and/or 0%-10%-20%) with significantly different overall survivals (P<0.05). We conclude that current practices in Ki67 scoring assessment vary greatly, and interobserver variation sets particular limitations to its clinical utility, especially around clinically relevant cutoff values. Novel digital microscopy-enabled methods could provide critical aid in reducing variation, increasing reproducibility, and improving reliability in the clinical setting.

Computer-aided discovery in antimicrobial research: In silico model for virtual screening of potent and safe anti-pseudomonas agents.

PubMed

Speck-Planche, Alejandro; Cordeiro, Maria N D S

2015-01-01

Resistance of bacteria to current antibiotics is an alarming health problem. In this sense, Pseudomonas represents a genus of Gram-negative pathogens, which has emerged as one of the most dangerous species causing nosocomial infections. Despite the effort of the scientific community, drug resistant strains of bacteria belonging to Pseudomonas spp. prevail. The high costs associated to drug discovery and the urgent need for more efficient antimicrobial chemotherapies envisage the fact that computeraided methods can rationalize several stages involved in the development of a new drug. In this work, we introduce a chemoinformatic methodology devoted to the construction of a multitasking model for quantitative-structure biological effect relationships (mtk-QSBER). The purpose of this model was to perform simultaneous predictions of anti-Pseudomonas activities and ADMET (absorption, distribution, metabolism, elimination, and toxicity) properties of organic compounds. The mtk-QSBER model was created from a large and heterogeneous dataset (more than 54000 cases) and displayed accuracies higher than 90% in both training and prediction sets. In order to demonstrate the applicability of our mtk-QSBER model, we used the investigational antibacterial drug delafloxacin as a case of study, for which experimental results were recently reported. The predictions performed for many biological effects of this drug exhibited a remarkable convergence with the experimental assays, confirming that our model can serve as useful tool for virtual screening of potent and safer anti-Pseudomonas agents.

Influence relevance voting: an accurate and interpretable virtual high throughput screening method.

PubMed

Swamidass, S Joshua; Azencott, Chloé-Agathe; Lin, Ting-Wan; Gramajo, Hugo; Tsai, Shiou-Chuan; Baldi, Pierre

2009-04-01

Given activity training data from high-throughput screening (HTS) experiments, virtual high-throughput screening (vHTS) methods aim to predict in silico the activity of untested chemicals. We present a novel method, the Influence Relevance Voter (IRV), specifically tailored for the vHTS task. The IRV is a low-parameter neural network which refines a k-nearest neighbor classifier by nonlinearly combining the influences of a chemical's neighbors in the training set. Influences are decomposed, also nonlinearly, into a relevance component and a vote component. The IRV is benchmarked using the data and rules of two large, open, competitions, and its performance compared to the performance of other participating methods, as well as of an in-house support vector machine (SVM) method. On these benchmark data sets, IRV achieves state-of-the-art results, comparable to the SVM in one case, and significantly better than the SVM in the other, retrieving three times as many actives in the top 1% of its prediction-sorted list. The IRV presents several other important advantages over SVMs and other methods: (1) the output predictions have a probabilistic semantic; (2) the underlying inferences are interpretable; (3) the training time is very short, on the order of minutes even for very large data sets; (4) the risk of overfitting is minimal, due to the small number of free parameters; and (5) additional information can easily be incorporated into the IRV architecture. Combined with its performance, these qualities make the IRV particularly well suited for vHTS.

Discovery of Specific Inhibitors for Intestinal E. coli   β-Glucuronidase through In Silico Virtual Screening

PubMed Central

Cheng, Ta-Chun; Cheng, Kai-Wen; Leu, Yu-Lin; Chuang, Chih-Hung; Huang, Chien-Chaio; Hsieh, Yuan-Chin; Chang, Long-Sen; Cheng, Tian-Lu

2015-01-01

Glucuronidation is a major metabolism process of detoxification for carcinogens, 4-(methylnitrosamino)-1-(3-pyridy)-1-butanone (NNK) and 1,2-dimethylhydrazine (DMH), of reactive oxygen species (ROS). However, intestinal E. coli    β-glucuronidase (eβG) has been considered pivotal to colorectal carcinogenesis. Specific inhibition of eβG may prevent reactivating the glucuronide-carcinogen and protect the intestine from ROS-mediated carcinogenesis. In order to develop specific eβG inhibitors, we found that 59 candidate compounds obtained from the initial virtual screening had high inhibition specificity against eβG but not human βG. In particular, we found that compounds 7145 and 4041 with naphthalenylidene-benzenesulfonamide (NYBS) are highly effective and selective to inhibit eβG activity. Compound 4041  (IC50 = 2.8 μM) shows a higher inhibiting ability than compound 7145  (IC50 = 31.6 μM) against eβG. Furthermore, the molecular docking analysis indicates that compound 4041 has two hydrophobic contacts to residues L361 and I363 in the bacterial loop, but 7145 has one contact to L361. Only compound 4041 can bind to key residue (E413) at active site of eβG via hydrogen-bonding interactions. These novel NYBS-based eβG specific inhibitors may provide as novel candidate compounds, which specifically inhibit eβG to reduce eβG-based carcinogenesis and intestinal injury. PMID:25839056

Discovery of specific inhibitors for intestinal E. coli  β-glucuronidase through in silico virtual screening.

PubMed

Cheng, Ta-Chun; Chuang, Kuo-Hsiang; Roffler, Steve R; Cheng, Kai-Wen; Leu, Yu-Lin; Chuang, Chih-Hung; Huang, Chien-Chaio; Kao, Chien-Han; Hsieh, Yuan-Chin; Chang, Long-Sen; Cheng, Tian-Lu; Chen, Chien-Shu

2015-01-01

Glucuronidation is a major metabolism process of detoxification for carcinogens, 4-(methylnitrosamino)-1-(3-pyridy)-1-butanone (NNK) and 1,2-dimethylhydrazine (DMH), of reactive oxygen species (ROS). However, intestinal E. coli   β-glucuronidase (eβG) has been considered pivotal to colorectal carcinogenesis. Specific inhibition of eβG may prevent reactivating the glucuronide-carcinogen and protect the intestine from ROS-mediated carcinogenesis. In order to develop specific eβG inhibitors, we found that 59 candidate compounds obtained from the initial virtual screening had high inhibition specificity against eβG but not human βG. In particular, we found that compounds 7145 and 4041 with naphthalenylidene-benzenesulfonamide (NYBS) are highly effective and selective to inhibit eβG activity. Compound 4041  (IC50 = 2.8 μM) shows a higher inhibiting ability than compound 7145  (IC50 = 31.6 μM) against eβG. Furthermore, the molecular docking analysis indicates that compound 4041 has two hydrophobic contacts to residues L361 and I363 in the bacterial loop, but 7145 has one contact to L361. Only compound 4041 can bind to key residue (E413) at active site of eβG via hydrogen-bonding interactions. These novel NYBS-based eβG specific inhibitors may provide as novel candidate compounds, which specifically inhibit eβG to reduce eβG-based carcinogenesis and intestinal injury.

PyRhO: A Multiscale Optogenetics Simulation Platform

PubMed Central

Evans, Benjamin D.; Jarvis, Sarah; Schultz, Simon R.; Nikolic, Konstantin

2016-01-01

Optogenetics has become a key tool for understanding the function of neural circuits and controlling their behavior. An array of directly light driven opsins have been genetically isolated from several families of organisms, with a wide range of temporal and spectral properties. In order to characterize, understand and apply these opsins, we present an integrated suite of open-source, multi-scale computational tools called PyRhO. The purpose of developing PyRhO is three-fold: (i) to characterize new (and existing) opsins by automatically fitting a minimal set of experimental data to three-, four-, or six-state kinetic models, (ii) to simulate these models at the channel, neuron and network levels, and (iii) provide functional insights through model selection and virtual experiments in silico. The module is written in Python with an additional IPython/Jupyter notebook based GUI, allowing models to be fit, simulations to be run and results to be shared through simply interacting with a webpage. The seamless integration of model fitting algorithms with simulation environments (including NEURON and Brian2) for these virtual opsins will enable neuroscientists to gain a comprehensive understanding of their behavior and rapidly identify the most suitable variant for application in a particular biological system. This process may thereby guide not only experimental design and opsin choice but also alterations of the opsin genetic code in a neuro-engineering feed-back loop. In this way, we expect PyRhO will help to significantly advance optogenetics as a tool for transforming biological sciences. PMID:27148037

PyRhO: A Multiscale Optogenetics Simulation Platform.

PubMed

Evans, Benjamin D; Jarvis, Sarah; Schultz, Simon R; Nikolic, Konstantin

2016-01-01

Optogenetics has become a key tool for understanding the function of neural circuits and controlling their behavior. An array of directly light driven opsins have been genetically isolated from several families of organisms, with a wide range of temporal and spectral properties. In order to characterize, understand and apply these opsins, we present an integrated suite of open-source, multi-scale computational tools called PyRhO. The purpose of developing PyRhO is three-fold: (i) to characterize new (and existing) opsins by automatically fitting a minimal set of experimental data to three-, four-, or six-state kinetic models, (ii) to simulate these models at the channel, neuron and network levels, and (iii) provide functional insights through model selection and virtual experiments in silico. The module is written in Python with an additional IPython/Jupyter notebook based GUI, allowing models to be fit, simulations to be run and results to be shared through simply interacting with a webpage. The seamless integration of model fitting algorithms with simulation environments (including NEURON and Brian2) for these virtual opsins will enable neuroscientists to gain a comprehensive understanding of their behavior and rapidly identify the most suitable variant for application in a particular biological system. This process may thereby guide not only experimental design and opsin choice but also alterations of the opsin genetic code in a neuro-engineering feed-back loop. In this way, we expect PyRhO will help to significantly advance optogenetics as a tool for transforming biological sciences.

Pharmacophore Modeling and in Silico/in Vitro Screening for Human Cytochrome P450 11B1 and Cytochrome P450 11B2 Inhibitors

PubMed Central

Akram, Muhammad; Waratchareeyakul, Watcharee; Haupenthal, Joerg; Hartmann, Rolf W.; Schuster, Daniela

2017-01-01

Cortisol synthase (CYP11B1) is the main enzyme for the endogenous synthesis of cortisol and its inhibition is a potential way for the treatment of diseases associated with increased cortisol levels, such as Cushing's syndrome, metabolic diseases, and delayed wound healing. Aldosterone synthase (CYP11B2) is the key enzyme for aldosterone biosynthesis and its inhibition is a promising approach for the treatment of congestive heart failure, cardiac fibrosis, and certain forms of hypertension. Both CYP11B1 and CYP11B2 are structurally very similar and expressed in the adrenal cortex. To facilitate the identification of novel inhibitors of these enzymes, ligand-based pharmacophore models of CYP11B1 and CYP11B2 inhibition were developed. A virtual screening of the SPECS database was performed with our pharmacophore queries. Biological evaluation of the selected hits lead to the discovery of three potent novel inhibitors of both CYP11B1 and CYP11B2 in the submicromolar range (compounds 8–10), one selective CYP11B1 inhibitor (Compound 11, IC50 = 2.5 μM), and one selective CYP11B2 inhibitor (compound 12, IC50 = 1.1 μM), respectively. The overall success rate of this prospective virtual screening experiment is 20.8% indicating good predictive power of the pharmacophore models. PMID:29312923

Virtual reality visual feedback for hand-controlled scanning probe microscopy manipulation of single molecules.

PubMed

Leinen, Philipp; Green, Matthew F B; Esat, Taner; Wagner, Christian; Tautz, F Stefan; Temirov, Ruslan

2015-01-01

Controlled manipulation of single molecules is an important step towards the fabrication of single molecule devices and nanoscale molecular machines. Currently, scanning probe microscopy (SPM) is the only technique that facilitates direct imaging and manipulations of nanometer-sized molecular compounds on surfaces. The technique of hand-controlled manipulation (HCM) introduced recently in Beilstein J. Nanotechnol. 2014, 5, 1926-1932 simplifies the identification of successful manipulation protocols in situations when the interaction pattern of the manipulated molecule with its environment is not fully known. Here we present a further technical development that substantially improves the effectiveness of HCM. By adding Oculus Rift virtual reality goggles to our HCM set-up we provide the experimentalist with 3D visual feedback that displays the currently executed trajectory and the position of the SPM tip during manipulation in real time, while simultaneously plotting the experimentally measured frequency shift (Δf) of the non-contact atomic force microscope (NC-AFM) tuning fork sensor as well as the magnitude of the electric current (I) flowing between the tip and the surface. The advantages of the set-up are demonstrated by applying it to the model problem of the extraction of an individual PTCDA molecule from its hydrogen-bonded monolayer grown on Ag(111) surface.

Drift-insensitive distributed calibration of probe microscope scanner in nanometer range: Virtual mode

NASA Astrophysics Data System (ADS)

Lapshin, Rostislav V.

2016-08-01

A method of distributed calibration of a probe microscope scanner is suggested. The main idea consists in a search for a net of local calibration coefficients (LCCs) in the process of automatic measurement of a standard surface, whereby each point of the movement space of the scanner can be characterized by a unique set of scale factors. Feature-oriented scanning (FOS) methodology is used as a basis for implementation of the distributed calibration permitting to exclude in situ the negative influence of thermal drift, creep and hysteresis on the obtained results. Possessing the calibration database enables correcting in one procedure all the spatial systematic distortions caused by nonlinearity, nonorthogonality and spurious crosstalk couplings of the microscope scanner piezomanipulators. To provide high precision of spatial measurements in nanometer range, the calibration is carried out using natural standards - constants of crystal lattice. One of the useful modes of the developed calibration method is a virtual mode. In the virtual mode, instead of measurement of a real surface of the standard, the calibration program makes a surface image ;measurement; of the standard, which was obtained earlier using conventional raster scanning. The application of the virtual mode permits simulation of the calibration process and detail analysis of raster distortions occurring in both conventional and counter surface scanning. Moreover, the mode allows to estimate the thermal drift and the creep velocities acting while surface scanning. Virtual calibration makes possible automatic characterization of a surface by the method of scanning probe microscopy (SPM).

InSilico DB genomic datasets hub: an efficient starting point for analyzing genome-wide studies in GenePattern, Integrative Genomics Viewer, and R/Bioconductor.

PubMed

Coletta, Alain; Molter, Colin; Duqué, Robin; Steenhoff, David; Taminau, Jonatan; de Schaetzen, Virginie; Meganck, Stijn; Lazar, Cosmin; Venet, David; Detours, Vincent; Nowé, Ann; Bersini, Hugues; Weiss Solís, David Y

2012-11-18

Genomics datasets are increasingly useful for gaining biomedical insights, with adoption in the clinic underway. However, multiple hurdles related to data management stand in the way of their efficient large-scale utilization. The solution proposed is a web-based data storage hub. Having clear focus, flexibility and adaptability, InSilico DB seamlessly connects genomics dataset repositories to state-of-the-art and free GUI and command-line data analysis tools. The InSilico DB platform is a powerful collaborative environment, with advanced capabilities for biocuration, dataset sharing, and dataset subsetting and combination. InSilico DB is available from https://insilicodb.org.

Identification by Virtual Screening and In Vitro Testing of Human DOPA Decarboxylase Inhibitors

PubMed Central

Cellini, Barbara; Macchiarulo, Antonio; Giardina, Giorgio; Bossa, Francesco; Borri Voltattorni, Carla

2012-01-01

Dopa decarboxylase (DDC), a pyridoxal 5′-phosphate (PLP) enzyme responsible for the biosynthesis of dopamine and serotonin, is involved in Parkinson's disease (PD). PD is a neurodegenerative disease mainly due to a progressive loss of dopamine-producing cells in the midbrain. Co-administration of L-Dopa with peripheral DDC inhibitors (carbidopa or benserazide) is the most effective symptomatic treatment for PD. Although carbidopa and trihydroxybenzylhydrazine (the in vivo hydrolysis product of benserazide) are both powerful irreversible DDC inhibitors, they are not selective because they irreversibly bind to free PLP and PLP-enzymes, thus inducing diverse side effects. Therefore, the main goals of this study were (a) to use virtual screening to identify potential human DDC inhibitors and (b) to evaluate the reliability of our virtual-screening (VS) protocol by experimentally testing the “in vitro” activity of selected molecules. Starting from the crystal structure of the DDC-carbidopa complex, a new VS protocol, integrating pharmacophore searches and molecular docking, was developed. Analysis of 15 selected compounds, obtained by filtering the public ZINC database, yielded two molecules that bind to the active site of human DDC and behave as competitive inhibitors with Ki values ≥10 µM. By performing in silico similarity search on the latter compounds followed by a substructure search using the core of the most active compound we identified several competitive inhibitors of human DDC with Ki values in the low micromolar range, unable to bind free PLP, and predicted to not cross the blood-brain barrier. The most potent inhibitor with a Ki value of 500 nM represents a new lead compound, targeting human DDC, that may be the basis for lead optimization in the development of new DDC inhibitors. To our knowledge, a similar approach has not been reported yet in the field of DDC inhibitors discovery. PMID:22384042

Identification by virtual screening and in vitro testing of human DOPA decarboxylase inhibitors.

PubMed

Daidone, Frederick; Montioli, Riccardo; Paiardini, Alessandro; Cellini, Barbara; Macchiarulo, Antonio; Giardina, Giorgio; Bossa, Francesco; Borri Voltattorni, Carla

2012-01-01

Dopa decarboxylase (DDC), a pyridoxal 5'-phosphate (PLP) enzyme responsible for the biosynthesis of dopamine and serotonin, is involved in Parkinson's disease (PD). PD is a neurodegenerative disease mainly due to a progressive loss of dopamine-producing cells in the midbrain. Co-administration of L-Dopa with peripheral DDC inhibitors (carbidopa or benserazide) is the most effective symptomatic treatment for PD. Although carbidopa and trihydroxybenzylhydrazine (the in vivo hydrolysis product of benserazide) are both powerful irreversible DDC inhibitors, they are not selective because they irreversibly bind to free PLP and PLP-enzymes, thus inducing diverse side effects. Therefore, the main goals of this study were (a) to use virtual screening to identify potential human DDC inhibitors and (b) to evaluate the reliability of our virtual-screening (VS) protocol by experimentally testing the "in vitro" activity of selected molecules. Starting from the crystal structure of the DDC-carbidopa complex, a new VS protocol, integrating pharmacophore searches and molecular docking, was developed. Analysis of 15 selected compounds, obtained by filtering the public ZINC database, yielded two molecules that bind to the active site of human DDC and behave as competitive inhibitors with K(i) values ≥10 µM. By performing in silico similarity search on the latter compounds followed by a substructure search using the core of the most active compound we identified several competitive inhibitors of human DDC with K(i) values in the low micromolar range, unable to bind free PLP, and predicted to not cross the blood-brain barrier. The most potent inhibitor with a K(i) value of 500 nM represents a new lead compound, targeting human DDC, that may be the basis for lead optimization in the development of new DDC inhibitors. To our knowledge, a similar approach has not been reported yet in the field of DDC inhibitors discovery.

GPCRs from fusarium graminearum detection, modeling and virtual screening - the search for new routes to control head blight disease.

PubMed

Bresso, Emmanuel; Togawa, Roberto; Hammond-Kosack, Kim; Urban, Martin; Maigret, Bernard; Martins, Natalia Florencio

2016-12-15

Fusarium graminearum (FG) is one of the major cereal infecting pathogens causing high economic losses worldwide and resulting in adverse effects on human and animal health. Therefore, the development of new fungicides against FG is an important issue to reduce cereal infection and economic impact. In the strategy for developing new fungicides, a critical step is the identification of new targets against which innovative chemicals weapons can be designed. As several G-protein coupled receptors (GPCRs) are implicated in signaling pathways critical for the fungi development and survival, such proteins could be valuable efficient targets to reduce Fusarium growth and therefore to prevent food contamination. In this study, GPCRs were predicted in the FG proteome using a manually curated pipeline dedicated to the identification of GPCRs. Based on several successive filters, the most appropriate GPCR candidate target for developing new fungicides was selected. Searching for new compounds blocking this particular target requires the knowledge of its 3D-structure. As no experimental X-Ray structure of the selected protein was available, a 3D model was built by homology modeling. The model quality and stability was checked by 100 ns of molecular dynamics simulations. Two stable conformations representative of the conformational families of the protein were extracted from the 100 ns simulation and were used for an ensemble docking campaign. The model quality and stability was checked by 100 ns of molecular dynamics simulations previously to the virtual screening step. The virtual screening step comprised the exploration of a chemical library with 11,000 compounds that were docked to the GPCR model. Among these compounds, we selected the ten top-ranked nontoxic molecules proposed to be experimentally tested to validate the in silico simulation. This study provides an integrated process merging genomics, structural bioinformatics and drug design for proposing innovative solutions to a world wide threat to grain producers and consumers.

A technique system for the measurement, reconstruction and character extraction of rice plant architecture

PubMed Central

Li, Xumeng; Wang, Xiaohui; Wei, Hailin; Zhu, Xinguang; Peng, Yulin; Li, Ming; Li, Tao; Huang, Huang

2017-01-01

This study developed a technique system for the measurement, reconstruction, and trait extraction of rice canopy architectures, which have challenged functional–structural plant modeling for decades and have become the foundation of the design of ideo-plant architectures. The system uses the location-separation-measurement method (LSMM) for the collection of data on the canopy architecture and the analytic geometry method for the reconstruction and visualization of the three-dimensional (3D) digital architecture of the rice plant. It also uses the virtual clipping method for extracting the key traits of the canopy architecture such as the leaf area, inclination, and azimuth distribution in spatial coordinates. To establish the technique system, we developed (i) simple tools to measure the spatial position of the stem axis and azimuth of the leaf midrib and to capture images of tillers and leaves; (ii) computer software programs for extracting data on stem diameter, leaf nodes, and leaf midrib curves from the tiller images and data on leaf length, width, and shape from the leaf images; (iii) a database of digital architectures that stores the measured data and facilitates the reconstruction of the 3D visual architecture and the extraction of architectural traits; and (iv) computation algorithms for virtual clipping to stratify the rice canopy, to extend the stratified surface from the horizontal plane to a general curved surface (including a cylindrical surface), and to implement in silico. Each component of the technique system was quantitatively validated and visually compared to images, and the sensitivity of the virtual clipping algorithms was analyzed. This technique is inexpensive and accurate and provides high throughput for the measurement, reconstruction, and trait extraction of rice canopy architectures. The technique provides a more practical method of data collection to serve functional–structural plant models of rice and for the optimization of rice canopy types. Moreover, the technique can be easily adapted for other cereal crops such as wheat, which has numerous stems and leaves sheltering each other. PMID:28558045

Virtual microscopy in virtual tumor banking.

PubMed

Isabelle, M; Teodorovic, I; Oosterhuis, J W; Riegman, P H J; Passioukov, A; Lejeune, S; Therasse, P; Dinjens, W N M; Lam, K H; Oomen, M H A; Spatz, A; Ratcliffe, C; Knox, K; Mager, R; Kerr, D; Pezzella, F; Van Damme, B; Van de Vijver, M; Van Boven, H; Morente, M M; Alonso, S; Kerjaschki, D; Pammer, J; López-Guerrero, J A; Llombart-Bosch, A; Carbone, A; Gloghini, A; Van Veen, E B

2006-01-01

Many systems have already been designed and successfully used for sharing histology images over large distances, without transfer of the original glass slides. Rapid evolution was seen when digital images could be transferred over the Internet. Nowadays, sophisticated virtual microscope systems can be acquired, with the capability to quickly scan large batches of glass slides at high magnification and compress and store the large images on disc, which subsequently can be consulted through the Internet. The images are stored on an image server, which can give simple, easy to transfer pictures to the user specifying a certain magnification on any position in the scan. This offers new opportunities in histology review, overcoming the necessity of the dynamic telepathology systems to have compatible software systems and microscopes and in addition, an adequate connection of sufficient bandwidth. Consulting the images now only requires an Internet connection and a computer with a high quality monitor. A system of complete pathology review supporting biorepositories is described, based on the implementation of this technique in the European Human Frozen Tumor Tissue Bank (TuBaFrost).

TuBaFrost 6: virtual microscopy in virtual tumour banking.

PubMed

Teodorovic, I; Isabelle, M; Carbone, A; Passioukov, A; Lejeune, S; Jaminé, D; Therasse, P; Gloghini, A; Dinjens, W N M; Lam, K H; Oomen, M H A; Spatz, A; Ratcliffe, C; Knox, K; Mager, R; Kerr, D; Pezzella, F; van Damme, B; van de Vijver, M; van Boven, H; Morente, M M; Alonso, S; Kerjaschki, D; Pammer, J; Lopez-Guerrero, J A; Llombart Bosch, A; van Veen, E-B; Oosterhuis, J W; Riegman, P H J

2006-12-01

Many systems have already been designed and successfully used for sharing histology images over large distances, without transfer of the original glass slides. Rapid evolution was seen when digital images could be transferred over the Internet. Nowadays, sophisticated Virtual Microscope systems can be acquired, with the capability to quickly scan large batches of glass slides at high magnification and compress and store the large images on disc, which subsequently can be consulted through the Internet. The images are stored on an image server, which can give simple, easy to transfer pictures to the user specifying a certain magnification on any position in the scan. This offers new opportunities in histology review, overcoming the necessity of the dynamic telepathology systems to have compatible software systems and microscopes and in addition, an adequate connection of sufficient bandwidth. Consulting the images now only requires an Internet connection and a computer with a high quality monitor. A system of complete pathology review supporting bio-repositories is described, based on the implementation of this technique in the European Human Frozen Tumor Tissue Bank (TuBaFrost).

Optimizing low-light microscopy with back-illuminated electron multiplying charge-coupled device: enhanced sensitivity, speed, and resolution.

PubMed

Coates, Colin G; Denvir, Donal J; McHale, Noel G; Thornbury, Keith D; Hollywood, Mark A

2004-01-01

The back-illuminated electron multiplying charge-coupled device (EMCCD) camera is having a profound influence on the field of low-light dynamic cellular microscopy, combining highest possible photon collection efficiency with the ability to virtually eliminate the readout noise detection limit. We report here the use of this camera, in 512 x 512 frame-transfer chip format at 10-MHz pixel readout speed, in optimizing a demanding ultra-low-light intracellular calcium flux microscopy setup. The arrangement employed includes a spinning confocal Nipkow disk, which, while facilitating the need to both generate images at very rapid frame rates and minimize background photons, yields very weak signals. The challenge for the camera lies not just in detecting as many of these scarce photons as possible, but also in operating at a frame rate that meets the temporal resolution requirements of many low-light microscopy approaches, a particular demand of smooth muscle calcium flux microscopy. Results presented illustrate both the significant sensitivity improvement offered by this technology over the previous standard in ultra-low-light CCD detection, the GenIII+intensified charge-coupled device (ICCD), and also portray the advanced temporal and spatial resolution capabilities of the EMCCD. Copyright 2004 Society of Photo-Optical Instrumentation Engineers.

Environmental metabarcodes for insects: in silico PCR reveals potential for taxonomic bias.

PubMed

Clarke, Laurence J; Soubrier, Julien; Weyrich, Laura S; Cooper, Alan

2014-11-01

Studies of insect assemblages are suited to the simultaneous DNA-based identification of multiple taxa known as metabarcoding. To obtain accurate estimates of diversity, metabarcoding markers ideally possess appropriate taxonomic coverage to avoid PCR-amplification bias, as well as sufficient sequence divergence to resolve species. We used in silico PCR to compare the taxonomic coverage and resolution of newly designed insect metabarcodes (targeting 16S) with that of existing markers [16S and cytochrome oxidase c subunit I (COI)] and then compared their efficiency in vitro. Existing metabarcoding primers amplified in silico <75% of insect species with complete mitochondrial genomes available, whereas new primers targeting 16S provided >90% coverage. Furthermore, metabarcodes targeting COI appeared to introduce taxonomic PCR-amplification bias, typically amplifying a greater percentage of Lepidoptera and Diptera species, while failing to amplify certain orders in silico. To test whether bias predicted in silico was observed in vitro, we created an artificial DNA blend containing equal amounts of DNA from 14 species, representing 11 insect orders and one arachnid. We PCR-amplified the blend using five primer sets, targeting either COI or 16S, with high-throughput amplicon sequencing yielding more than 6 million reads. In vitro results typically corresponded to in silico PCR predictions, with newly designed 16S primers detecting 11 insect taxa present, thus providing equivalent or better taxonomic coverage than COI metabarcodes. Our results demonstrate that in silico PCR is a useful tool for predicting taxonomic bias in mixed template PCR and that researchers should be wary of potential bias when selecting metabarcoding markers. © 2014 John Wiley & Sons Ltd.

Efficacy of Silicosec, a diatomaceous earth formulation against Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae).

PubMed

Ziaee, Masumeh; Safaralizadeh, Mohammad H; Shayesteh, Nouraddin

2007-11-01

Laboratory bioassays were carried out to evaluate the insecticidal efficacy of SilicoSec against 7- 14-days-old adults of Tribolium castaneum; old and young larvae with the mean weight of 3.4 +/- 0.1 and 0.6 +/- 0.1 mg, respectively at 27 degrees C and 55 +/- 5% r.h in the dark. Wheat treated with four dose rates of SilicoSec with three replications. Adult's mortality was measured after 2, 7 and 14 days of exposure. After 14 days mortality count, all adults were removed and samples retained under the same conditions for a further 60 days to assess progeny production. In the case of larvae, mortality was counted after 1, 2 and 7 days. After 2 days of exposure no concentration achieved 11% mortality for adults, however; adult's mortality exceeds 89.65% when exposed for 7 days to SilicoSec. Mortality of old and young larvae at 0.6 g kg(-1) after 2 days were 28.88 and 22.22%, respectively and exceed to 60.71 and 69.04% at longer exposure of 7 days. Results indicated that mortality of T. castaneum was influenced by interval exposed to wheat treated with SilicoSec and over this exposure; the increases in application rate of SilicoSec had significant effect on the mortality. Young larvae of red flour beetle were more sensitive to SilicoSec than old larvae and adults were more tolerant. Reproductive potential of adults in the treated wheat was suppressed when compared with untreated wheat. The high retention level of SilicoSec (78.62%) was noted in wheat kernels.

Open source tools for management and archiving of digital microscopy data to allow integration with patient pathology and treatment information.

PubMed

Khushi, Matloob; Edwards, Georgina; de Marcos, Diego Alonso; Carpenter, Jane E; Graham, J Dinny; Clarke, Christine L

2013-02-12

Virtual microscopy includes digitisation of histology slides and the use of computer technologies for complex investigation of diseases such as cancer. However, automated image analysis, or website publishing of such digital images, is hampered by their large file sizes. We have developed two Java based open source tools: Snapshot Creator and NDPI-Splitter. Snapshot Creator converts a portion of a large digital slide into a desired quality JPEG image. The image is linked to the patient's clinical and treatment information in a customised open source cancer data management software (Caisis) in use at the Australian Breast Cancer Tissue Bank (ABCTB) and then published on the ABCTB website (http://www.abctb.org.au) using Deep Zoom open source technology. Using the ABCTB online search engine, digital images can be searched by defining various criteria such as cancer type, or biomarkers expressed. NDPI-Splitter splits a large image file into smaller sections of TIFF images so that they can be easily analysed by image analysis software such as Metamorph or Matlab. NDPI-Splitter also has the capacity to filter out empty images. Snapshot Creator and NDPI-Splitter are novel open source Java tools. They convert digital slides into files of smaller size for further processing. In conjunction with other open source tools such as Deep Zoom and Caisis, this suite of tools is used for the management and archiving of digital microscopy images, enabling digitised images to be explored and zoomed online. Our online image repository also has the capacity to be used as a teaching resource. These tools also enable large files to be sectioned for image analysis. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/5330903258483934.

Two-Layer Elastographic 3-D Traction Force Microscopy

PubMed Central

Álvarez-González, Begoña; Zhang, Shun; Gómez-González, Manuel; Meili, Ruedi; Firtel, Richard A.; Lasheras, Juan C.; del Álamo, Juan C.

2017-01-01

Cellular traction force microscopy (TFM) requires knowledge of the mechanical properties of the substratum where the cells adhere to calculate cell-generated forces from measurements of substratum deformation. Polymer-based hydrogels are broadly used for TFM due to their linearly elastic behavior in the range of measured deformations. However, the calculated stresses, particularly their spatial patterns, can be highly sensitive to the substratum’s Poisson’s ratio. We present two-layer elastographic TFM (2LETFM), a method that allows for simultaneously measuring the Poisson’s ratio of the substratum while also determining the cell-generated forces. The new method exploits the analytical solution of the elastostatic equation and deformation measurements from two layers of the substratum. We perform an in silico analysis of 2LETFM concluding that this technique is robust with respect to TFM experimental parameters, and remains accurate even for noisy measurement data. We also provide experimental proof of principle of 2LETFM by simultaneously measuring the stresses exerted by migrating Physarum amoeboae on the surface of polyacrylamide substrata, and the Poisson’s ratio of the substrata. The 2LETFM method could be generalized to concurrently determine the mechanical properties and cell-generated forces in more physiologically relevant extracellular environments, opening new possibilities to study cell-matrix interactions. PMID:28074837

Directly Observing Micelle Fusion and Growth in Solution by Liquid-Cell Transmission Electron Microscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parent, Lucas R.; Bakalis, Evangelos; Ramírez-Hernández, Abelardo

Amphiphilic small molecules and polymers form commonplace nanoscale macromolecular compartments and bilayers, and as such are truly essential components in all cells and in many cellular processes. The nature of these architectures, including their formation, phase changes, and stimuli-response behaviors, is necessary for the most basic functions of life, and over the past half-century, these natural micellar structures have inspired a vast diversity of industrial products, from biomedicines to detergents, lubricants, and coatings. The importance of these materials and their ubiquity have made them the subject of intense investigation regarding their nanoscale dynamics with increasing interest in obtaining sufficient temporalmore » and spatial resolution to directly observe nanoscale processes. However, the vast majority of experimental methods involve either bulk-averaging techniques including light, neutron, and X-ray scattering, or are static in nature including even the most advanced cryogenic transmission electron microscopy techniques. Here, we employ in situ liquid-cell transmission electron microscopy (LCTEM) to directly observe the evolution of individual amphiphilic block copolymer micellar nanoparticles in solution, in real time with nanometer spatial resolution. These observations, made on a proof-of-concept bioconjugate polymer amphiphile, revealed growth and evolution occurring by unimer addition processes and by particle-particle collision-and-fusion events. The experimental approach, combining direct LCTEM observation, quantitative analysis of LCTEM data, and correlated in silico simulations, provides a unique view of solvated soft matter nanoassemblies as they morph and evolve in time and space, enabling us to capture these phenomena in solution.« less

Graph Theory-Based Analysis of the Lymph Node Fibroblastic Reticular Cell Network.

PubMed

Novkovic, Mario; Onder, Lucas; Bocharov, Gennady; Ludewig, Burkhard

2017-01-01

Secondary lymphoid organs have developed segregated niches that are able to initiate and maintain effective immune responses. Such global organization requires tight control of diverse cellular components, specifically those that regulate lymphocyte trafficking. Fibroblastic reticular cells (FRCs) form a densely interconnected network in lymph nodes and provide key factors necessary for T cell migration and retention, and foster subsequent interactions between T cells and dendritic cells. Development of integrative systems biology approaches has made it possible to elucidate this multilevel complexity of the immune system. Here, we present a graph theory-based analysis of the FRC network in murine lymph nodes, where generation of the network topology is performed using high-resolution confocal microscopy and 3D reconstruction. This approach facilitates the analysis of physical cell-to-cell connectivity, and estimation of topological robustness and global behavior of the network when it is subjected to perturbation in silico.

A Unique Spatial Arrangement of the snRNPs within the Native Spliceosome Emerges from In-Silico Studies

PubMed Central

Frankenstein, Ziv; Sperling, Joseph; Sperling, Ruth; Eisenstein, Miriam

2012-01-01

Summary The spliceosome is a mega-Dalton ribonucleoprotein (RNP) assembly that processes primary RNA transcripts, producing functional mRNA. The electron microscopy structures of the native spliceosome and of several spliceosomal subcomplexes are available but the spatial arrangement of the latter within the native spliceosome is not known. We designed a new computational procedure to efficiently fit thousands of conformers into the spliceosome envelope. Despite the low resolution limitations, we obtained only one model that complies with the available biochemical data. Our model localizes the five small nuclear RNPs (snRNPs) mostly within the large subunit of the native spliceosome, requiring only minor conformation changes. The remaining free volume presumably accommodates additional spliceosomal components. The constituents of the active core of the spliceosome are juxtaposed, forming a continuous surface deep within the large spliceosomal cavity, which provides a sheltered environment for the splicing reaction. PMID:22578543

Nodal Cilia Dynamics and the Specification of the Left/Right Axis in Early Vertebrate Embryo Development

PubMed Central

Buceta, Javier; Ibañes, Marta; Rasskin-Gutman, Diego; Okada, Yasushi; Hirokawa, Nobutaka; Izpisúa-Belmonte, Juan Carlos

2005-01-01

Nodal cilia dynamics is a key factor for left/right axis determination in mouse embryos through the induction of a leftward fluid flow. So far it has not been clearly established how such dynamics is able to induce the asymmetric leftward flow within the node. Herein we propose that an asymmetric two-phase nonplanar beating cilia dynamics that involves the bending of the ciliar axoneme is responsible for the leftward fluid flow. We support our proposal with a host of hydrodynamic arguments, in silico experiments and in vivo video microscopy data in wild-type embryos and inv mutants. Our phenomenological modeling approach underscores how the asymmetry and speed of the flow depends on different relevant parameters. In addition, we discuss how the combination of internal and external mechanisms might cause the two-phase beating cilia dynamics. PMID:16040754

Chemically Resolved Imaging of Biological Cells and Thin Films by Infrared Scanning Near-Field Optical Microscopy

PubMed Central

Cricenti, Antonio; Generosi, Renato; Luce, Marco; Perfetti, Paolo; Margaritondo, Giorgio; Talley, David; Sanghera, Jas S.; Aggarwal, Ishwar D.; Tolk, Norman H.; Congiu-Castellano, Agostina; Rizzo, Mark A.; Piston, David W.

2003-01-01

The infrared (IR) absorption of a biological system can potentially report on fundamentally important microchemical properties. For example, molecular IR profiles are known to change during increases in metabolic flux, protein phosphorylation, or proteolytic cleavage. However, practical implementation of intracellular IR imaging has been problematic because the diffraction limit of conventional infrared microscopy results in low spatial resolution. We have overcome this limitation by using an IR spectroscopic version of scanning near-field optical microscopy (SNOM), in conjunction with a tunable free-electron laser source. The results presented here clearly reveal different chemical constituents in thin films and biological cells. The space distribution of specific chemical species was obtained by taking SNOM images at IR wavelengths (λ) corresponding to stretch absorption bands of common biochemical bonds, such as the amide bond. In our SNOM implementation, this chemical sensitivity is combined with a lateral resolution of 0.1 μm (≈λ/70), well below the diffraction limit of standard infrared microscopy. The potential applications of this approach touch virtually every aspect of the life sciences and medical research, as well as problems in materials science, chemistry, physics, and environmental research. PMID:14507733

Unwarping confocal microscopy images of bee brains by nonrigid registration to a magnetic resonance microscopy image.

PubMed

Rohlfing, Torsten; Schaupp, Frank; Haddad, Daniel; Brandt, Robert; Haase, Axel; Menzel, Randolf; Maurer, Calvin R

2005-01-01

Confocal microscopy (CM) is a powerful image acquisition technique that is well established in many biological applications. It provides 3-D acquisition with high spatial resolution and can acquire several different channels of complementary image information. Due to the specimen extraction and preparation process, however, the shapes of imaged objects may differ considerably from their in vivo appearance. Magnetic resonance microscopy (MRM) is an evolving variant of magnetic resonance imaging, which achieves microscopic resolutions using a high magnetic field and strong magnetic gradients. Compared to CM imaging, MRM allows for in situ imaging and is virtually free of geometrical distortions. We propose to combine the advantages of both methods by unwarping CM images using a MRM reference image. Our method incorporates a sequence of image processing operators applied to the MRM image, followed by a two-stage intensity-based registration to compute a nonrigid coordinate transformation between the CM images and the MRM image. We present results obtained using CM images from the brains of 20 honey bees and a MRM image of an in situ bee brain. Copyright 2005 Society of Photo-Optical Instrumentation Engineers.

Graphene engineering by neon ion beams

DOE PAGES

Iberi, Vighter; Ievlev, Anton V.; Vlassiouk, Ivan; ...

2016-02-18

Achieving the ultimate limits of materials and device performance necessitates the engineering of matter with atomic, molecular, and mesoscale fidelity. While common for organic and macromolecular chemistry, these capabilities are virtually absent for 2D materials. In contrast to the undesired effect of ion implantation from focused ion beam (FIB) lithography with gallium ions, and proximity effects in standard e-beam lithography techniques, the shorter mean free path and interaction volumes of helium and neon ions offer a new route for clean, resist free nanofabrication. Furthermore, with the advent of scanning helium ion microscopy, maskless He + and Ne + beam lithographymore » of graphene based nanoelectronics is coming to the forefront. Here, we will discuss the use of energetic Ne ions in engineering graphene devices and explore the mechanical, electromechanical and chemical properties of the ion-milled devices using scanning probe microscopy (SPM). By using SPM-based techniques such as band excitation (BE) force modulation microscopy, Kelvin probe force microscopy (KPFM) and Raman spectroscopy, we demonstrate that the mechanical, electrical and optical properties of the exact same devices can be quantitatively extracted. Additionally, the effect of defects inherent in ion beam direct-write lithography, on the overall performance of the fabricated devices is elucidated.« less

BRCA1/2 missense mutations and the value of in-silico analyses.

PubMed

Sadowski, Carolin E; Kohlstedt, Daniela; Meisel, Cornelia; Keller, Katja; Becker, Kerstin; Mackenroth, Luisa; Rump, Andreas; Schröck, Evelin; Wimberger, Pauline; Kast, Karin

2017-11-01

The clinical implications of genetic variants in BRCA1/2 in healthy and affected individuals are considerable. Variant interpretation, however, is especially challenging for missense variants. The majority of them are classified as variants of unknown clinical significance (VUS). Computational (in-silico) predictive programs are easy to access, but represent only one tool out of a wide range of complemental approaches to classify VUS. With this single-center study, we aimed to evaluate the impact of in-silico analyses in a spectrum of different BRCA1/2 missense variants. We conducted mutation analysis of BRCA1/2 in 523 index patients with suspected hereditary breast and ovarian cancer (HBOC). Classification of the genetic variants was performed according to the German Consortium (GC)-HBOC database. Additionally, all missense variants were classified by the following three in-silico prediction tools: SIFT, Mutation Taster (MT2) and PolyPhen2 (PPH2). Overall 201 different variants, 68 of which constituted missense variants were ranked as pathogenic, neutral, or unknown. The classification of missense variants by in-silico tools resulted in a higher amount of pathogenic mutations (25% vs. 13.2%) compared to the GC-HBOC-classification. Altogether, more than fifty percent (38/68, 55.9%) of missense variants were ranked differently. Sensitivity of in-silico-tools for mutation prediction was 88.9% (PPH2), 100% (SIFT) and 100% (MT2). We found a relevant discrepancy in variant classification by using in-silico prediction tools, resulting in potential overestimation and/or underestimation of cancer risk. More reliable, notably gene-specific, prediction tools and functional tests are needed to improve clinical counseling. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Metabolism of captopril carboxyl ester derivatives for percutaneous absorption.

PubMed

Gullick, Darren R; Ingram, Matthew J; Pugh, W John; Cox, Paul A; Gard, Paul; Smart, John D; Moss, Gary P

2009-02-01

To determine the metabolism of captopril n-carboxyl derivatives and how this may impact on their use as transdermal prodrugs. The pharmacological activity of the ester derivatives was also characterised in order to compare the angiotensin converting enzyme inhibitory potency of the derivatives compared with the parent drug, captopril. The metabolism rates of the ester derivatives were determined in vitro (using porcine liver esterase and porcine ear skin) and in silico (using molecular modelling to investigate the potential to predict metabolism). Relatively slow pseudo first-order metabolism of the prodrugs was observed, with the ethyl ester displaying the highest rate of metabolism. A strong relationship was established between in-vitro methods, while in-silico methods support the use of in-vitro methods and highlight the potential of in-silico techniques to predict metabolism. All the prodrugs behaved as angiotensin converting enzyme inhibitors, with the methyl ester displaying optimum inhibition. In-vitro porcine liver esterase metabolism rates inform in-vitro skin rates well, and in-silico interaction energies relate well to both. Thus, in-silico methods may be developed that include interaction energies to predict metabolism rates.

Analysis of composition and microstructures of Ge grown on porous silicon using Raman spectroscopy and transmission electron microscopy

NASA Astrophysics Data System (ADS)

Aouassa, Mansour; Jadli, Imen; Hassayoun, Latifa Slimen; Maaref, Hassen; Panczer, Gerard; Favre, Luc; Ronda, Antoine; Berbezier, Isabelle

2017-12-01

Composition and microstructure of Ge grown on porous silicon (PSi) by Molecular Beam Epitaxy (MBE) at different temperatures are examined using High Resolution Transmission Electron Microscopy (HRTEM) and Raman spectroscopy. Ge grown at 400 °C on PSi buffer produces a planar Ge film with high crystalline quality compared to Ge grown on bulk Si. This result is attributed to the compliant nature of PSi. Increasing growth temperature >600 °C, changes the PSi morphology, increase the Ge/Si intermixing in the pores during Ge growth and lead to obtain a composite SiGe/Si substrate. Ge content in the composite SiGe substrate can controlled via growth temperature. These substrates serve as low cost virtual substrate for high efficiency III-V/Si solar cells.

Purely in silico BCS classification: science based quality standards for the world's drugs.

PubMed

Dahan, Arik; Wolk, Omri; Kim, Young Hoon; Ramachandran, Chandrasekharan; Crippen, Gordon M; Takagi, Toshihide; Bermejo, Marival; Amidon, Gordon L

2013-11-04

BCS classification is a vital tool in the development of both generic and innovative drug products. The purpose of this work was to provisionally classify the world's top selling oral drugs according to the BCS, using in silico methods. Three different in silico methods were examined: the well-established group contribution (CLogP) and atom contribution (ALogP) methods, and a new method based solely on the molecular formula and element contribution (KLogP). Metoprolol was used as the benchmark for the low/high permeability class boundary. Solubility was estimated in silico using a thermodynamic equation that relies on the partition coefficient and melting point. The validity of each method was affirmed by comparison to reference data and literature. We then used each method to provisionally classify the orally administered, IR drug products found in the WHO Model list of Essential Medicines, and the top-selling oral drug products in the United States (US), Great Britain (GB), Spain (ES), Israel (IL), Japan (JP), and South Korea (KR). A combined list of 363 drugs was compiled from the various lists, and 257 drugs were classified using the different in silico permeability methods and literature solubility data, as well as BDDCS classification. Lastly, we calculated the solubility values for 185 drugs from the combined set using in silico approach. Permeability classification with the different in silico methods was correct for 69-72.4% of the 29 reference drugs with known human jejunal permeability, and for 84.6-92.9% of the 14 FDA reference drugs in the set. The correlations (r(2)) between experimental log P values of 154 drugs and their CLogP, ALogP and KLogP were 0.97, 0.82 and 0.71, respectively. The different in silico permeability methods produced comparable results: 30-34% of the US, GB, ES and IL top selling drugs were class 1, 27-36.4% were class 2, 22-25.5% were class 3, and 5.46-14% were class 4 drugs, while ∼8% could not be classified. The WHO list included significantly less class 1 and more class 3 drugs in comparison to the countries' lists, probably due to differences in commonly used drugs in developing vs industrial countries. BDDCS classified more drugs as class 1 compared to in silico BCS, likely due to the more lax benchmark for metabolism (70%), in comparison to the strict permeability benchmark (metoprolol). For 185 out of the 363 drugs, in silico solubility values were calculated, and successfully matched the literature solubility data. In conclusion, relatively simple in silico methods can be used to estimate both permeability and solubility. While CLogP produced the best correlation to experimental values, even KLogP, the most simplified in silico method that is based on molecular formula with no knowledge of molecular structure, produced comparable BCS classification to the sophisticated methods. This KLogP, when combined with a mean melting point and estimated dose, can be used to provisionally classify potential drugs from just molecular formula, even before synthesis. 49-59% of the world's top-selling drugs are highly soluble (class 1 and class 3), and are therefore candidates for waivers of in vivo bioequivalence studies. For these drugs, the replacement of expensive human studies with affordable in vitro dissolution tests would ensure their bioequivalence, and encourage the development and availability of generic drug products in both industrial and developing countries.

ConfocalVR: Immersive Visualization Applied to Confocal Microscopy.

PubMed

Stefani, Caroline; Lacy-Hulbert, Adam; Skillman, Thomas

2018-06-24

ConfocalVR is a virtual reality (VR) application created to improve the ability of researchers to study the complexity of cell architecture. Confocal microscopes take pictures of fluorescently labeled proteins or molecules at different focal planes to create a stack of 2D images throughout the specimen. Current software applications reconstruct the 3D image and render it as a 2D projection onto a computer screen where users need to rotate the image to expose the full 3D structure. This process is mentally taxing, breaks down if you stop the rotation, and does not take advantage of the eye's full field of view. ConfocalVR exploits consumer-grade virtual reality (VR) systems to fully immerse the user in the 3D cellular image. In this virtual environment the user can: 1) adjust image viewing parameters without leaving the virtual space, 2) reach out and grab the image to quickly rotate and scale the image to focus on key features, and 3) interact with other users in a shared virtual space enabling real-time collaborative exploration and discussion. We found that immersive VR technology allows the user to rapidly understand cellular architecture and protein or molecule distribution. We note that it is impossible to understand the value of immersive visualization without experiencing it first hand, so we encourage readers to get access to a VR system, download this software, and evaluate it for yourself. The ConfocalVR software is available for download at http://www.confocalvr.com, and is free for nonprofits. Copyright © 2018. Published by Elsevier Ltd.

Automated complete slide digitization: a medium for simultaneous viewing by multiple pathologists.

PubMed

Leong, F J; McGee, J O

2001-11-01

Developments in telepathology robotic systems have evolved the concept of a 'virtual microscope' handling 'digital slides'. Slide digitization is a method of archiving salient histological features in numerical (digital) form. The value and potential of this have begun to be recognized by several international centres. Automated complete slide digitization has application at all levels of clinical practice and will benefit undergraduate, postgraduate, and continuing education. Unfortunately, as the volume of potential data on a histological slide represents a significant problem in terms of digitization, storage, and subsequent manipulation, the reality of virtual microscopy to date has comprised limited views at inadequate resolution. This paper outlines a system refined in the authors' laboratory, which employs a combination of enhanced hardware, image capture, and processing techniques designed for telepathology. The system is able to scan an entire slide at high magnification and create a library of such slides that may exist on an internet server or be distributed on removable media (such as CD-ROM or DVD). A digital slide allows image data manipulation at a level not possible with conventional light microscopy. Combinations of multiple users, multiple magnifications, annotations, and addition of ancillary textual and visual data are now possible. This demonstrates that with increased sophistication, the applications of telepathology technology need not be confined to second opinion, but can be extended on a wider front. Copyright 2001 John Wiley & Sons, Ltd.

New Trends of Emerging Technologies in Digital Pathology.

PubMed

Bueno, Gloria; Fernández-Carrobles, M Milagro; Deniz, Oscar; García-Rojo, Marcial

2016-01-01

The future paradigm of pathology will be digital. Instead of conventional microscopy, a pathologist will perform a diagnosis through interacting with images on computer screens and performing quantitative analysis. The fourth generation of virtual slide telepathology systems, so-called virtual microscopy and whole-slide imaging (WSI), has allowed for the storage and fast dissemination of image data in pathology and other biomedical areas. These novel digital imaging modalities encompass high-resolution scanning of tissue slides and derived technologies, including automatic digitization and computational processing of whole microscopic slides. Moreover, automated image analysis with WSI can extract specific diagnostic features of diseases and quantify individual components of these features to support diagnoses and provide informative clinical measures of disease. Therefore, the challenge is to apply information technology and image analysis methods to exploit the new and emerging digital pathology technologies effectively in order to process and model all the data and information contained in WSI. The final objective is to support the complex workflow from specimen receipt to anatomic pathology report transmission, that is, to improve diagnosis both in terms of pathologists' efficiency and with new information. This article reviews the main concerns about and novel methods of digital pathology discussed at the latest workshop in the field carried out within the European project AIDPATH (Academia and Industry Collaboration for Digital Pathology). © 2016 S. Karger AG, Basel.

Virtual Screening of Peptide and Peptidomimetic Fragments Targeted to Inhibit Bacterial Dithiol Oxidase DsbA.

PubMed

Duprez, Wilko; Bachu, Prabhakar; Stoermer, Martin J; Tay, Stephanie; McMahon, Róisín M; Fairlie, David P; Martin, Jennifer L

2015-01-01

Antibacterial drugs with novel scaffolds and new mechanisms of action are desperately needed to address the growing problem of antibiotic resistance. The periplasmic oxidative folding system in Gram-negative bacteria represents a possible target for anti-virulence antibacterials. By targeting virulence rather than viability, development of resistance and side effects (through killing host native microbiota) might be minimized. Here, we undertook the design of peptidomimetic inhibitors targeting the interaction between the two key enzymes of oxidative folding, DsbA and DsbB, with the ultimate goal of preventing virulence factor assembly. Structures of DsbB--or peptides--complexed with DsbA revealed key interactions with the DsbA active site cysteine, and with a hydrophobic groove adjacent to the active site. The present work aimed to discover peptidomimetics that target the hydrophobic groove to generate non-covalent DsbA inhibitors. The previously reported structure of a Proteus mirabilis DsbA active site cysteine mutant, in a non-covalent complex with the heptapeptide PWATCDS, was used as an in silico template for virtual screening of a peptidomimetic fragment library. The highest scoring fragment compound and nine derivatives were synthesized and evaluated for DsbA binding and inhibition. These experiments discovered peptidomimetic fragments with inhibitory activity at millimolar concentrations. Although only weakly potent relative to larger covalent peptide inhibitors that interact through the active site cysteine, these fragments offer new opportunities as templates to build non-covalent inhibitors. The results suggest that non-covalent peptidomimetics may need to interact with sites beyond the hydrophobic groove in order to produce potent DsbA inhibitors.

Plant-Derived Polyphenols in Human Health: Biological Activity, Metabolites and Putative Molecular Targets.

PubMed

Olivares-Vicente, Marilo; Barrajon-Catalan, Enrique; Herranz-Lopez, Maria; Segura-Carretero, Antonio; Joven, Jorge; Encinar, Jose Antonio; Micol, Vicente

2018-01-01

Hibiscus sabdariffa, Lippia citriodora, Rosmarinus officinalis and Olea europaea, are rich in bioactive compounds that represent most of the phenolic compounds' families and have exhibited potential benefits in human health. These plants have been used in folk medicine for their potential therapeutic properties in human chronic diseases. Recent evidence leads to postulate that polyphenols may account for such effects. Nevertheless, the compounds or metabolites that are responsible for reaching the molecular targets are unknown. data based on studies directly using complex extracts on cellular models, without considering metabolic aspects, have limited applicability. In contrast, studies exploring the absorption process, metabolites in the blood circulation and tissues have become essential to identify the intracellular final effectors that are responsible for extracts bioactivity. Once the cellular metabolites are identified using high-resolution mass spectrometry, docking techniques suppose a unique tool for virtually screening a large number of compounds on selected targets in order to elucidate their potential mechanisms. we provide an updated overview of the in vitro and in vivo studies on the toxicity, absorption, permeability, pharmacokinetics and cellular metabolism of bioactive compounds derived from the abovementioned plants to identify the potential compounds that are responsible for the observed health effects. we propose the use of targeted metabolomics followed by in silico studies to virtually screen identified metabolites on selected protein targets, in combination with the use of the candidate metabolites in cellular models, as the methods of choice for elucidating the molecular mechanisms of these compounds. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Virtual surgical planning, flow simulation, and 3-dimensional electrospinning of patient-specific grafts to optimize Fontan hemodynamics.

PubMed

Siallagan, Dominik; Loke, Yue-Hin; Olivieri, Laura; Opfermann, Justin; Ong, Chin Siang; de Zélicourt, Diane; Petrou, Anastasios; Daners, Marianne Schmid; Kurtcuoglu, Vartan; Meboldt, Mirko; Nelson, Kevin; Vricella, Luca; Johnson, Jed; Hibino, Narutoshi; Krieger, Axel

2018-04-01

Despite advances in the Fontan procedure, there is an unmet clinical need for patient-specific graft designs that are optimized for variations in patient anatomy. The objective of this study is to design and produce patient-specific Fontan geometries, with the goal of improving hepatic flow distribution (HFD) and reducing power loss (P loss ), and manufacturing these designs by electrospinning. Cardiac magnetic resonance imaging data from patients who previously underwent a Fontan procedure (n = 2) was used to create 3-dimensional models of their native Fontan geometry using standard image segmentation and geometry reconstruction software. For each patient, alternative designs were explored in silico, including tube-shaped and bifurcated conduits, and their performance in terms of P loss and HFD probed by computational fluid dynamic (CFD) simulations. The best-performing options were then fabricated using electrospinning. CFD simulations showed that the bifurcated conduit improved HFD between the left and right pulmonary arteries, whereas both types of conduits reduced P loss . In vitro testing with a flow-loop chamber supported the CFD results. The proposed designs were then successfully electrospun into tissue-engineered vascular grafts. Our unique virtual cardiac surgery approach has the potential to improve the quality of surgery by manufacturing patient-specific designs before surgery, that are also optimized with balanced HFD and minimal P loss , based on refinement of commercially available options for image segmentation, computer-aided design, and flow simulations. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Real Patient and its Virtual Twin: Application of Quantitative Systems Toxicology Modelling in the Cardiac Safety Assessment of Citalopram.

PubMed

Patel, Nikunjkumar; Wiśniowska, Barbara; Jamei, Masoud; Polak, Sebastian

2017-11-27

A quantitative systems toxicology (QST) model for citalopram was established to simulate, in silico, a 'virtual twin' of a real patient to predict the occurrence of cardiotoxic events previously reported in patients under various clinical conditions. The QST model considers the effects of citalopram and its most notable electrophysiologically active primary (desmethylcitalopram) and secondary (didesmethylcitalopram) metabolites, on cardiac electrophysiology. The in vitro cardiac ion channel current inhibition data was coupled with the biophysically detailed model of human cardiac electrophysiology to investigate the impact of (i) the inhibition of multiple ion currents (I Kr , I Ks , I CaL ); (ii) the inclusion of metabolites in the QST model; and (iii) unbound or total plasma as the operating drug concentration, in predicting clinically observed QT prolongation. The inclusion of multiple ion channel current inhibition and metabolites in the simulation with unbound plasma citalopram concentration provided the lowest prediction error. The predictive performance of the model was verified with three additional therapeutic and supra-therapeutic drug exposure clinical cases. The results indicate that considering only the hERG ion channel inhibition of only the parent drug is potentially misleading, and the inclusion of active metabolite data and the influence of other ion channel currents should be considered to improve the prediction of potential cardiac toxicity. Mechanistic modelling can help bridge the gaps existing in the quantitative translation from preclinical cardiac safety assessment to clinical toxicology. Moreover, this study shows that the QST models, in combination with appropriate drug and systems parameters, can pave the way towards personalised safety assessment.

A Computational Systems Biology Software Platform for Multiscale Modeling and Simulation: Integrating Whole-Body Physiology, Disease Biology, and Molecular Reaction Networks

PubMed Central

Eissing, Thomas; Kuepfer, Lars; Becker, Corina; Block, Michael; Coboeken, Katrin; Gaub, Thomas; Goerlitz, Linus; Jaeger, Juergen; Loosen, Roland; Ludewig, Bernd; Meyer, Michaela; Niederalt, Christoph; Sevestre, Michael; Siegmund, Hans-Ulrich; Solodenko, Juri; Thelen, Kirstin; Telle, Ulrich; Weiss, Wolfgang; Wendl, Thomas; Willmann, Stefan; Lippert, Joerg

2011-01-01

Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multiscale by nature, project work, and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim® and MoBi® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug–drug, or drug–metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach. PMID:21483730

In Silico and In Vitro Anticancer Activity of Isolated Novel Marker Compound from Chemically Modified Bioactive Fraction from Curcuma longa (NCCL).

PubMed

Naqvi, Arshi; Malasoni, Richa; Gupta, Swati; Srivastava, Akansha; Pandey, Rishi R; Dwivedi, Anil Kumar

2017-10-01

Turmeric ( Curcuma longa ) is reported to possess wide array of biological activities. Herbal Medicament (HM) is a standardized hexane-soluble fraction of C. longa and is well known for its neuroprotective effect. In this study, we attempted to synthesize a novel chemically modified bioactive fraction from HM (NCCL) along with isolation and characterization of a novel marker compound (I). NCCL was prepared from HM. The chemical structure of the marker compound isolated from NCCL was determined from 1D/2D nuclear magnetic resonance, mass spectroscopy, and Fourier transform infrared. The compound so isolated was subjected to in silico and in vitro screenings to test its inhibitory effect on estrogen receptors. Molecular docking studies revealed that the binding poses of the compound I was energetically favorable. Among NCCL and compound I taken for in vitro studies, NCCL had exhibited good anti-cancer activity over compound I against MCF-7, MDA-MB-231, DU-145, and PC-3 cells. This is the first study about the synthesis of a chemically modified bioactive fraction which used a standardized extract since the preparation of the HM. It may be concluded that NCCL fraction having residual components induce more cell death than compound I alone. Thus, NCCL may be used as a potent therapeutic drug. In the present paper, a standardized hexane soluble fraction of Curcuma longa (HM) was chemically modified to give a novel bioactive fraction (NCCL). A novel marker compound was isolated from NCCL and was characerized using various spectral techniques. The compound so isolated was investigated for in-silico screenings. NCCL and isolated compound was subjected to in-vitro anti-cancer screenings against MCF 7, MDA MB 231 (breast adenocarcinoma) and DU 145 and PC 3 cell lines (androgen independent human prostate cancer cells). The virtual screenings reveals that isolated compound has shown favourable drug like properties. NCCL fraction having residual components induces more cell death in these four cancer cell lines than isolated compound alone. Abbreviations used: HM: Herbal Medicament; NCCL: Chemically modified HM; FT-IR: Fourier transform-infrared spectroscopy; NMR: Nuclear magnetic resonance spectroscopy; MS: Mass spectroscopy; HPLC: High-performance liquid chromatography; ER: Estrogen receptor; MTT: 3-(4,5 dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide; MIC: Minimum inhibitory concentration; TAM: Tamoxifen KBr: Potassium bromide; DMSO: Dimethyl sulfoxide; ACN: Acetonitrile; PDB: Protein Data Bank; PDA: Photodiode array detector.

A novel strategy for classifying the output from an in silico vaccine discovery pipeline for eukaryotic pathogens using machine learning algorithms.

PubMed

Goodswen, Stephen J; Kennedy, Paul J; Ellis, John T

2013-11-02

An in silico vaccine discovery pipeline for eukaryotic pathogens typically consists of several computational tools to predict protein characteristics. The aim of the in silico approach to discovering subunit vaccines is to use predicted characteristics to identify proteins which are worthy of laboratory investigation. A major challenge is that these predictions are inherent with hidden inaccuracies and contradictions. This study focuses on how to reduce the number of false candidates using machine learning algorithms rather than relying on expensive laboratory validation. Proteins from Toxoplasma gondii, Plasmodium sp., and Caenorhabditis elegans were used as training and test datasets. The results show that machine learning algorithms can effectively distinguish expected true from expected false vaccine candidates (with an average sensitivity and specificity of 0.97 and 0.98 respectively), for proteins observed to induce immune responses experimentally. Vaccine candidates from an in silico approach can only be truly validated in a laboratory. Given any in silico output and appropriate training data, the number of false candidates allocated for validation can be dramatically reduced using a pool of machine learning algorithms. This will ultimately save time and money in the laboratory.

A novel strategy for classifying the output from an in silico vaccine discovery pipeline for eukaryotic pathogens using machine learning algorithms

PubMed Central

2013-01-01

Background An in silico vaccine discovery pipeline for eukaryotic pathogens typically consists of several computational tools to predict protein characteristics. The aim of the in silico approach to discovering subunit vaccines is to use predicted characteristics to identify proteins which are worthy of laboratory investigation. A major challenge is that these predictions are inherent with hidden inaccuracies and contradictions. This study focuses on how to reduce the number of false candidates using machine learning algorithms rather than relying on expensive laboratory validation. Proteins from Toxoplasma gondii, Plasmodium sp., and Caenorhabditis elegans were used as training and test datasets. Results The results show that machine learning algorithms can effectively distinguish expected true from expected false vaccine candidates (with an average sensitivity and specificity of 0.97 and 0.98 respectively), for proteins observed to induce immune responses experimentally. Conclusions Vaccine candidates from an in silico approach can only be truly validated in a laboratory. Given any in silico output and appropriate training data, the number of false candidates allocated for validation can be dramatically reduced using a pool of machine learning algorithms. This will ultimately save time and money in the laboratory. PMID:24180526

Virtual microscopy and digital cytology: state of the art.

PubMed

Giansanti, Daniele; Grigioni, Mauro; D'Avenio, Giuseppe; Morelli, Sandra; Maccioni, Giovanni; Bondi, Arrigo; Giovagnoli, Maria Rosaria

2010-01-01

The paper approaches a new technological scenario relevant for the introduction of the digital cytology (D-CYT) in the health service. A detailed analysis of the state of the art on the status of the introduction of D-CYT in the hospital and more in general in the dispersed territory has been conducted. The analysis was conducted in a form of review and was arranged into two parts: the first part focused on the technological tools needed to carry out a successful service (client server architectures, e-learning, quality assurance issues); the second part focused on issues oriented to help the introduction and evaluation of the technology (specific training in D-CYT, health technology assessment in-routine application, data format standards and picture archiving computerized systems (PACS) implementation, image quality assessment, strategies of navigation, 3D-virtual-reality potentialities). The work enlightens future scenarios of actions relevant for the introduction of the technology.

Femtosecond pump-probe microscopy generates virtual cross-sections in historic artwork

PubMed Central

Villafana, Tana Elizabeth; Brown, William P.; Delaney, John K.; Palmer, Michael; Warren, Warren S.; Fischer, Martin C.

2014-01-01

The layering structure of a painting contains a wealth of information about the artist's choice of materials and working methods, but currently, no 3D noninvasive method exists to replace the taking of small paint samples in the study of the stratigraphy. Here, we adapt femtosecond pump-probe imaging, previously shown in tissue, to the case of the color palette in paintings, where chromophores have much greater variety. We show that combining the contrasts of multispectral and multidelay pump-probe spectroscopy permits nondestructive 3D imaging of paintings with molecular and structural contrast, even for pigments with linear absorption spectra that are broad and relatively featureless. We show virtual cross-sectioning capabilities in mockup paintings, with pigment separation and nondestructive imaging on an intact 14th century painting (The Crucifixion by Puccio Capanna). Our approach makes it possible to extract microscopic information for a broad range of applications to cultural heritage. PMID:24449855

In Silico Studies of the Toxcast Chemicals Interacting with Biomolecular targets

EPA Science Inventory

Molecular docking, a structure-based in silico tool for chemical library pre-screening in drug discovery, can be used to explore the potential toxicity of environmental chemicals acting at specific biomelcular targets.

Robust Phagocyte Recruitment Controls the Opportunistic Fungal Pathogen Mucor circinelloides in Innate Granulomas In Vivo.

PubMed

Inglesfield, Sarah; Jasiulewicz, Aleksandra; Hopwood, Matthew; Tyrrell, James; Youlden, George; Mazon-Moya, Maria; Millington, Owain R; Mostowy, Serge; Jabbari, Sara; Voelz, Kerstin

2018-03-27

Mucormycosis is an emerging fungal infection with extremely high mortality rates in patients with defects in their innate immune response, specifically in functions mediated through phagocytes. However, we currently have a limited understanding of the molecular and cellular interactions between these innate immune effectors and mucormycete spores during the early immune response. Here, the early events of innate immune recruitment in response to infection by Mucor circinelloides spores are modeled by a combined in silico modeling approach and real-time in vivo microscopy. Phagocytes are rapidly recruited to the site of infection in a zebrafish larval model of mucormycosis. This robust early recruitment protects from disease onset in vivo In silico analysis identified that protection is dependent on the number of phagocytes at the infection site, but not the speed of recruitment. The mathematical model highlights the role of proinflammatory signals for phagocyte recruitment and the importance of inhibition of spore germination for protection from active fungal disease. These in silico data are supported by an in vivo lack of fungal spore killing and lack of reactive oxygen burst, which together result in latent fungal infection. During this latent stage of infection, spores are controlled in innate granulomas in vivo Disease can be reactivated by immunosuppression. Together, these data represent the first in vivo real-time analysis of innate granuloma formation during the early stages of a fungal infection. The results highlight a potential latent stage during mucormycosis that should urgently be considered for clinical management of patients. IMPORTANCE Mucormycosis is a dramatic fungal infection frequently leading to the death of patients. We know little about the immune response to the fungus causing this infection, although evidence points toward defects in early immune events after infection. Here, we dissect this early immune response to infectious fungal spores. We show that specialized white blood cells (phagocytes) rapidly respond to these spores and accumulate around the fungus. However, we demonstrate that the mechanisms that enable phagocytes to kill the fungus fail, allowing for survival of spores. Instead a cluster of phagocytes resembling an early granuloma is formed around spores to control the latent infection. This study is the first detailed analysis of early granuloma formation during a fungal infection highlighting a latent stage that needs to be considered for clinical management of patients. Copyright © 2018 Inglesfield et al.

Rational Discovery of (+) (S) Abscisic Acid as a Potential Antifungal Agent: a Repurposing Approach.

PubMed

Khedr, Mohammed A; Massarotti, Alberto; Mohamed, Maged E

2018-06-04

Fungal infections are spreading widely worldwide, and the types of treatment are limited due to the lack of diverse therapeutic agents and their associated side effects and toxicity. The discovery of new antifungal classes is vital and critical. We discovered the antifungal activity of abscisic acid through a rational drug design methodology that included the building of homology models for fungal chorismate mutases and a pharmacophore model derived from a transition state inhibitor. Ligand-based virtual screening resulted in some hits that were filtered using molecular docking and molecular dynamic simulations studies. Both in silico methods and in vitro antifungal assays were used as tools to select and validate the abscisic acid repurposing. Abscisic acid inhibition assays confirmed the inhibitory effect of abscisic acid on chorismate mutase through the inhibition of phenylpyruvate production. The repositioning of abscisic acid, the well-known and naturally occurring plant growth regulator, as a potential antifungal agent because of its suggested action as an inhibitor to several fungal chorismate mutases was the main result of this work.

Identification and Structure–Activity Relationships of Novel Compounds that Potentiate the Activities of Antibiotics in Escherichia coli

DOE PAGES

Haynes, Keith M.; Abdali, Narges; Jhawar, Varsha; ...

2017-06-26

In Gram-negative bacteria, efflux pumps are able to prevent effective cellular concentrations from being achieved for a number of antibiotics. Small molecule adjuvants that act as efflux pump inhibitors (EPIs) have the potential to reinvigorate existing antibiotics that are currently ineffective due to efflux mechanisms. Through a combination of rigorous experimental screening and in silico virtual screening, we recently identified novel classes of EPIs that interact with the membrane fusion protein AcrA, a critical component of the AcrAB-TolC efflux pump in Escherichia coli. In this paper, we present initial optimization efforts and structure–activity relationships around one of those previously describedmore » hits, NSC 60339 (1). Finally, from these efforts we identified two compounds, SLUPP-225 (17h) and SLUPP-417 (17o), which demonstrate favorable properties as potential EPIs in E. coli cells including the ability to penetrate the outer membrane, improved inhibition of efflux relative to 1, and potentiation of the activity of novobiocin and erythromycin.« less

Generation of ligand-based pharmacophore model and virtual screening for identification of novel tubulin inhibitors with potent anticancer activity.

PubMed

Chiang, Yi-Kun; Kuo, Ching-Chuan; Wu, Yu-Shan; Chen, Chung-Tong; Coumar, Mohane Selvaraj; Wu, Jian-Sung; Hsieh, Hsing-Pang; Chang, Chi-Yen; Jseng, Huan-Yi; Wu, Ming-Hsine; Leou, Jiun-Shyang; Song, Jen-Shin; Chang, Jang-Yang; Lyu, Ping-Chiang; Chao, Yu-Sheng; Wu, Su-Ying

2009-07-23

A pharmacophore model, Hypo1, was built on the basis of 21 training-set indole compounds with varying levels of antiproliferative activity. Hypo1 possessed important chemical features required for the inhibitors and demonstrated good predictive ability for biological activity, with high correlation coefficients of 0.96 and 0.89 for the training-set and test-set compounds, respectively. Further utilization of the Hypo1 pharmacophore model to screen chemical database in silico led to the identification of four compounds with antiproliferative activity. Among these four compounds, 43 showed potent antiproliferative activity against various cancer cell lines with the strongest inhibition on the proliferation of KB cells (IC(50) = 187 nM). Further biological characterization revealed that 43 effectively inhibited tubulin polymerization and significantly induced cell cycle arrest in G(2)-M phase. In addition, 43 also showed the in vivo-like anticancer effects. To our knowledge, 43 is the most potent antiproliferative compound with antitubulin activity discovered by computer-aided drug design. The chemical novelty of 43 and its anticancer activities make this compound worthy of further lead optimization.

From BACE1 Inhibitor to Multifunctionality of Tryptoline and Tryptamine Triazole Derivatives for Alzheimer’s Disease

PubMed Central

Jiaranaikulwanitch, Jutamas; Govitrapong, Piyarat; Fokin, Valery V.; Vajragupta, Opa

2013-01-01

Efforts to discover new drugs for Alzheimer’s disease emphasizing multiple targets was conducted seeking to inhibit amyloid oligomer formation and to prevent radical formation. The tryptoline and tryptamine cores of BACE1 inhibitors previously identified by virtual screening were modified in silico for additional modes of action. These core structures were readily linked to different side chains using 1,2,3-triazole rings as bridges by copper catalyzed azide-alkyne cycloaddition reactions. Three compounds among the sixteen designed compounds exerted multifunctional activities including β-secretase inhibitory action, anti-amyloid aggregation, metal chelating and antioxidant effects at micromolar levels. The neuroprotective effects of the multifunctional compounds 6h, 12c and 12h on Aβ1–42 induced neuronal cell death at 1 μM were significantly greater than those of the potent single target compound, BACE1 inhibitor IV and were comparable to curcumin. The observed synergistic effect resulting from the reduction of the Aβ1–42 neurotoxicity cascade substantiates the validity of our multifunctional strategy in drug discovery for Alzheimer’s disease. PMID:22781443

Use of artificial intelligence in the design of small peptide antibiotics effective against a broad spectrum of highly antibiotic-resistant superbugs.

PubMed

Cherkasov, Artem; Hilpert, Kai; Jenssen, Håvard; Fjell, Christopher D; Waldbrook, Matt; Mullaly, Sarah C; Volkmer, Rudolf; Hancock, Robert E W

2009-01-16

Increased multiple antibiotic resistance in the face of declining antibiotic discovery is one of society's most pressing health issues. Antimicrobial peptides represent a promising new class of antibiotics. Here we ask whether it is possible to make small broad spectrum peptides employing minimal assumptions, by capitalizing on accumulating chemical biology information. Using peptide array technology, two large random 9-amino-acid peptide libraries were iteratively created using the amino acid composition of the most active peptides. The resultant data was used together with Artificial Neural Networks, a powerful machine learning technique, to create quantitative in silico models of antibiotic activity. On the basis of random testing, these models proved remarkably effective in predicting the activity of 100,000 virtual peptides. The best peptides, representing the top quartile of predicted activities, were effective against a broad array of multidrug-resistant "Superbugs" with activities that were equal to or better than four highly used conventional antibiotics, more effective than the most advanced clinical candidate antimicrobial peptide, and protective against Staphylococcus aureus infections in animal models.

Machine learning-, rule- and pharmacophore-based classification on the inhibition of P-glycoprotein and NorA.

PubMed

Ngo, T-D; Tran, T-D; Le, M-T; Thai, K-M

2016-09-01

The efflux pumps P-glycoprotein (P-gp) in humans and NorA in Staphylococcus aureus are of great interest for medicinal chemists because of their important roles in multidrug resistance (MDR). The high polyspecificity as well as the unavailability of high-resolution X-ray crystal structures of these transmembrane proteins lead us to combining ligand-based approaches, which in the case of this study were machine learning, perceptual mapping and pharmacophore modelling. For P-gp inhibitory activity, individual models were developed using different machine learning algorithms and subsequently combined into an ensemble model which showed a good discrimination between inhibitors and noninhibitors (acctrain-diverse = 84%; accinternal-test = 92% and accexternal-test = 100%). For ligand promiscuity between P-gp and NorA, perceptual maps and pharmacophore models were generated for the detection of rules and features. Based on these in silico tools, hit compounds for reversing MDR were discovered from the in-house and DrugBank databases through virtual screening in an attempt to restore drug sensitivity in cancer cells and bacteria.

Computational methods for analysis and inference of kinase/inhibitor relationships

PubMed Central

Ferrè, Fabrizio; Palmeri, Antonio; Helmer-Citterich, Manuela

2014-01-01

The central role of kinases in virtually all signal transduction networks is the driving motivation for the development of compounds modulating their activity. ATP-mimetic inhibitors are essential tools for elucidating signaling pathways and are emerging as promising therapeutic agents. However, off-target ligand binding and complex and sometimes unexpected kinase/inhibitor relationships can occur for seemingly unrelated kinases, stressing that computational approaches are needed for learning the interaction determinants and for the inference of the effect of small compounds on a given kinase. Recently published high-throughput profiling studies assessed the effects of thousands of small compound inhibitors, covering a substantial portion of the kinome. This wealth of data paved the road for computational resources and methods that can offer a major contribution in understanding the reasons of the inhibition, helping in the rational design of more specific molecules, in the in silico prediction of inhibition for those neglected kinases for which no systematic analysis has been carried yet, in the selection of novel inhibitors with desired selectivity, and offering novel avenues of personalized therapies. PMID:25071826

Identification and Structure–Activity Relationships of Novel Compounds that Potentiate the Activities of Antibiotics in Escherichia coli

DOE Office of Scientific and Technical Information (OSTI.GOV)

Haynes, Keith M.; Abdali, Narges; Jhawar, Varsha

In Gram-negative bacteria, efflux pumps are able to prevent effective cellular concentrations from being achieved for a number of antibiotics. Small molecule adjuvants that act as efflux pump inhibitors (EPIs) have the potential to reinvigorate existing antibiotics that are currently ineffective due to efflux mechanisms. Through a combination of rigorous experimental screening and in silico virtual screening, we recently identified novel classes of EPIs that interact with the membrane fusion protein AcrA, a critical component of the AcrAB-TolC efflux pump in Escherichia coli. In this paper, we present initial optimization efforts and structure–activity relationships around one of those previously describedmore » hits, NSC 60339 (1). Finally, from these efforts we identified two compounds, SLUPP-225 (17h) and SLUPP-417 (17o), which demonstrate favorable properties as potential EPIs in E. coli cells including the ability to penetrate the outer membrane, improved inhibition of efflux relative to 1, and potentiation of the activity of novobiocin and erythromycin.« less

FilTer BaSe: A web accessible chemical database for small compound libraries.

PubMed

Kolte, Baban S; Londhe, Sanjay R; Solanki, Bhushan R; Gacche, Rajesh N; Meshram, Rohan J

2018-03-01

Finding novel chemical agents for targeting disease associated drug targets often requires screening of large number of new chemical libraries. In silico methods are generally implemented at initial stages for virtual screening. Filtering of such compound libraries on physicochemical and substructure ground is done to ensure elimination of compounds with undesired chemical properties. Filtering procedure, is redundant, time consuming and requires efficient bioinformatics/computer manpower along with high end software involving huge capital investment that forms a major obstacle in drug discovery projects in academic setup. We present an open source resource, FilTer BaSe- a chemoinformatics platform (http://bioinfo.net.in/filterbase/) that host fully filtered, ready to use compound libraries with workable size. The resource also hosts a database that enables efficient searching the chemical space of around 348,000 compounds on the basis of physicochemical and substructure properties. Ready to use compound libraries and database presented here is expected to aid a helping hand for new drug developers and medicinal chemists. Copyright © 2017 Elsevier Inc. All rights reserved.

Axenic cultivation of a pathogenic Phytomonas species isolated from tomato fruit, and from its phytophagic insect vector, Phthia picta (Hemiptera: Coreidae).

PubMed

Fiorini, J E; de Faria e Silva, P M; Brazil, R P; Attias, M; Esteves, M J; Angluster, J

1993-01-01

Axenic cultures of Phytomonas sp. were obtained from naturally infected tomatoes and from Phthia picta, a predator of tomato plants, by using a biphasic medium with Roitman's complex medium overlaying rabbit blood-agar slants. Light and electron microscopy of both isolates showed a similarity of morphological characteristics among the flagellates in fresh material or after cultivation. Other properties, including their agglutinability with the haemolymph of Phthia picta, suggest that these isolates are virtually identical.

Insights and Perspectives on Emerging Inputs to Weight of Evidence Determinations for Food Safety: Workshop Proceedings

PubMed Central

Bialk, Heidi; Llewellyn, Craig; Kretser, Alison; Canady, Richard; Lane, Richard; Barach, Jeffrey

2013-01-01

This workshop aimed to elucidate the contribution of computational and emerging in vitro methods to the weight of evidence used by risk assessors in food safety assessments. The following issues were discussed: using in silico and high-throughput screening (HTS) data to confirm the safety of approved food ingredients, applying in silico and HTS data in the process of assessing the safety of a new food ingredient, and utilizing in silico and HTS data in communicating the safety of food ingredients while enhancing the public’s trust in the food supply. Perspectives on integrating computational modeling and HTS assays as well as recommendations for optimizing predictive methods for risk assessment were also provided. Given the need to act quickly or proceed cautiously as new data emerge, this workshop also focused on effectively identifying a path forward in communicating in silico and in vitro data. PMID:24296863

In Silico Prediction of Organ Level Toxicity: Linking Chemistry to Adverse Effects

PubMed Central

Cronin, Mark T.D.; Enoch, Steven J.; Mellor, Claire L.; Przybylak, Katarzyna R.; Richarz, Andrea-Nicole; Madden, Judith C.

2017-01-01

In silico methods to predict toxicity include the use of (Quantitative) Structure-Activity Relationships ((Q)SARs) as well as grouping (category formation) allowing for read-across. A challenging area for in silico modelling is the prediction of chronic toxicity and the No Observed (Adverse) Effect Level (NO(A)EL) in particular. A proposed solution to the prediction of chronic toxicity is to consider organ level effects, as opposed to modelling the NO(A)EL itself. This review has focussed on the use of structural alerts to identify potential liver toxicants. In silico profilers, or groups of structural alerts, have been developed based on mechanisms of action and informed by current knowledge of Adverse Outcome Pathways. These profilers are robust and can be coded computationally to allow for prediction. However, they do not cover all mechanisms or modes of liver toxicity and recommendations for the improvement of these approaches are given. PMID:28744348

In Silico Prediction of Organ Level Toxicity: Linking Chemistry to Adverse Effects.

PubMed

Cronin, Mark T D; Enoch, Steven J; Mellor, Claire L; Przybylak, Katarzyna R; Richarz, Andrea-Nicole; Madden, Judith C

2017-07-01

In silico methods to predict toxicity include the use of (Quantitative) Structure-Activity Relationships ((Q)SARs) as well as grouping (category formation) allowing for read-across. A challenging area for in silico modelling is the prediction of chronic toxicity and the No Observed (Adverse) Effect Level (NO(A)EL) in particular. A proposed solution to the prediction of chronic toxicity is to consider organ level effects, as opposed to modelling the NO(A)EL itself. This review has focussed on the use of structural alerts to identify potential liver toxicants. In silico profilers, or groups of structural alerts, have been developed based on mechanisms of action and informed by current knowledge of Adverse Outcome Pathways. These profilers are robust and can be coded computationally to allow for prediction. However, they do not cover all mechanisms or modes of liver toxicity and recommendations for the improvement of these approaches are given.

In Vitro and In Silico Risk Assessment in Acquired Long QT Syndrome: The Devil Is in the Details.

PubMed

Lee, William; Windley, Monique J; Vandenberg, Jamie I; Hill, Adam P

2017-01-01

Acquired long QT syndrome, mostly as a result of drug block of the Kv11. 1 potassium channel in the heart, is characterized by delayed cardiac myocyte repolarization, prolongation of the T interval on the ECG, syncope and sudden cardiac death due to the polymorphic ventricular arrhythmia Torsade de Pointes (TdP). In recent years, efforts are underway through the Comprehensive in vitro proarrhythmic assay (CiPA) initiative, to develop better tests for this drug induced arrhythmia based in part on in silico simulations of pharmacological disruption of repolarization. However, drug binding to Kv11.1 is more complex than a simple binary molecular reaction, meaning simple steady state measures of potency are poor surrogates for risk. As a result, there is a plethora of mechanistic detail describing the drug/Kv11.1 interaction-such as drug binding kinetics, state preference, temperature dependence and trapping-that needs to be considered when developing in silico models for risk prediction. In addition to this, other factors, such as multichannel pharmacological profile and the nature of the ventricular cell models used in simulations also need to be considered in the search for the optimum in silico approach. Here we consider how much of mechanistic detail needs to be included for in silico models to accurately predict risk and further, how much of this detail can be retrieved from protocols that are practical to implement in high throughout screens as part of next generation of preclinical in silico drug screening approaches?

Pharmacological validation of in-silico guided novel nootropic potential of Achyranthes aspera L.

PubMed

Gawande, Dinesh Yugraj; Goel, Rajesh Kumar

2015-12-04

Achyranthes aspera (A. aspera) has been used as a brain tonic in folk medicine. Although, ethnic use of medicinal plant has been basis for drug discovery from medicinal plants, but the available in-silico tools can be useful to find novel pharmacological uses of medicinal plants beyond their ethnic use. To validate in-silico prediction for novel nootropic effect of A. aspera by employing battery of tests in mice. Phytoconstituents of A. aspera reported in Dictionary of Natural Product were subjected to in-silico prediction using PASS and Pharmaexpert. The nootropic activity predicted for A. aspera was assessed using radial arm maze, passive shock avoidance and novel object recognition tests in mice. After behavioral evaluation animals were decapitated and their brains were collected and stored for estimation of glutamate levels and acetylcholinesterase activity. In-silico activity spectrum for majority of A. aspera phytoconstituents exhibited excellent prediction score for nootropic activity of this plant. A. aspera extract treatment significantly improved the learning and memory as evident by decreased working memory errors, reference memory errors and latency time in radial arm maze, step through latency in passive shock avoidance and increased recognition index in novel object recognition were observed, moreover significantly enhanced glutamate levels and reduced acetylcholinesterase activity in hippocampus and cortex were observed as compared to the saline treated group. In-silico and in-vivo results suggest that A. aspera plant may improve the learning and memory by modulating the brain glutamatergic and cholinergic neurotransmission. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Effect of Different Sampling Schedules on Results of Bioavailability and Bioequivalence Studies: Evaluation by Means of Monte Carlo Simulations.

PubMed

Kano, Eunice Kazue; Chiann, Chang; Fukuda, Kazuo; Porta, Valentina

2017-08-01

Bioavailability and bioequivalence study is one of the most frequently performed investigations in clinical trials. Bioequivalence testing is based on the assumption that 2 drug products will be therapeutically equivalent when they are equivalent in the rate and extent to which the active drug ingredient or therapeutic moiety is absorbed and becomes available at the site of drug action. In recent years there has been a significant growth in published papers that use in silico studies based on mathematical simulations to analyze pharmacokinetic and pharmacodynamic properties of drugs, including bioavailability and bioequivalence aspects. The goal of this study is to evaluate the usefulness of in silico studies as a tool in the planning of bioequivalence, bioavailability and other pharmacokinetic assays, e.g., to determine an appropriate sampling schedule. Monte Carlo simulations were used to define adequate blood sampling schedules for a bioequivalence assay comparing 2 different formulations of cefadroxil oral suspensions. In silico bioequivalence studies comparing different formulation of cefadroxil oral suspensions using various sampling schedules were performed using models. An in vivo study was conducted to confirm in silico results. The results of in silico and in vivo bioequivalence studies demonstrated that schedules with fewer sampling times are as efficient as schedules with larger numbers of sampling times in the assessment of bioequivalence, but only if T max is included as a sampling time. It was also concluded that in silico studies are useful tools in the planning of bioequivalence, bioavailability and other pharmacokinetic in vivo assays. © Georg Thieme Verlag KG Stuttgart · New York.

Espina: A Tool for the Automated Segmentation and Counting of Synapses in Large Stacks of Electron Microscopy Images

PubMed Central

Morales, Juan; Alonso-Nanclares, Lidia; Rodríguez, José-Rodrigo; DeFelipe, Javier; Rodríguez, Ángel; Merchán-Pérez, Ángel

2011-01-01

The synapses in the cerebral cortex can be classified into two main types, Gray's type I and type II, which correspond to asymmetric (mostly glutamatergic excitatory) and symmetric (inhibitory GABAergic) synapses, respectively. Hence, the quantification and identification of their different types and the proportions in which they are found, is extraordinarily important in terms of brain function. The ideal approach to calculate the number of synapses per unit volume is to analyze 3D samples reconstructed from serial sections. However, obtaining serial sections by transmission electron microscopy is an extremely time consuming and technically demanding task. Using focused ion beam/scanning electron microscope microscopy, we recently showed that virtually all synapses can be accurately identified as asymmetric or symmetric synapses when they are visualized, reconstructed, and quantified from large 3D tissue samples obtained in an automated manner. Nevertheless, the analysis, segmentation, and quantification of synapses is still a labor intensive procedure. Thus, novel solutions are currently necessary to deal with the large volume of data that is being generated by automated 3D electron microscopy. Accordingly, we have developed ESPINA, a software tool that performs the automated segmentation and counting of synapses in a reconstructed 3D volume of the cerebral cortex, and that greatly facilitates and accelerates these processes. PMID:21633491

The Empirical Foundations of Telepathology: Evidence of Feasibility and Intermediate Effects

PubMed Central

Krupinski, Elizabeth A.; Weinstein, Ronald S.; Dunn, Matthew R.; Bashshur, Noura

2017-01-01

Abstract Introduction: Telepathology evolved from video microscopy (i.e., “television microscopy”) research in the early 1950s to video microscopy used in basic research in the biological sciences to a basic diagnostic tool in telemedicine clinical applications. Its genesis can be traced to pioneering feasibility studies regarding the importance of color and other image-based parameters for rendering diagnoses and a series of studies assessing concordance of virtual slide and light microscopy diagnoses. This article documents the empirical foundations of telepathology. Methods: A selective review of the research literature during the past decade (2005–2016) was conducted using robust research design and adequate sample size as criteria for inclusion. Conclusions: The evidence regarding feasibility/acceptance of telepathology and related information technology applications has been well documented for several decades. The majority of evidentiary studies focused on intermediate outcomes, as indicated by comparability between telepathology and conventional light microscopy. A consistent trend of concordance between the two modalities was observed in terms of diagnostic accuracy and reliability. Additional benefits include use of telepathology and whole slide imaging for teaching, research, and outreach to resource-limited countries. Challenges still exist, however, in terms of use of telepathology as an effective diagnostic modality in clinical practice. PMID:28170313

Assessing sensor accuracy for non-adjunct use of continuous glucose monitoring.

PubMed

Kovatchev, Boris P; Patek, Stephen D; Ortiz, Edward Andrew; Breton, Marc D

2015-03-01

The level of continuous glucose monitoring (CGM) accuracy needed for insulin dosing using sensor values (i.e., the level of accuracy permitting non-adjunct CGM use) is a topic of ongoing debate. Assessment of this level in clinical experiments is virtually impossible because the magnitude of CGM errors cannot be manipulated and related prospectively to clinical outcomes. A combination of archival data (parallel CGM, insulin pump, self-monitoring of blood glucose [SMBG] records, and meals for 56 pump users with type 1 diabetes) and in silico experiments was used to "replay" real-life treatment scenarios and relate sensor error to glycemic outcomes. Nominal blood glucose (BG) traces were extracted using a mathematical model, yielding 2,082 BG segments each initiated by insulin bolus and confirmed by SMBG. These segments were replayed at seven sensor accuracy levels (mean absolute relative differences [MARDs] of 3-22%) testing six scenarios: insulin dosing using sensor values, threshold, and predictive alarms, each without or with considering CGM trend arrows. In all six scenarios, the occurrence of hypoglycemia (frequency of BG levels ≤50 mg/dL and BG levels ≤39 mg/dL) increased with sensor error, displaying an abrupt slope change at MARD =10%. Similarly, hyperglycemia (frequency of BG levels ≥250 mg/dL and BG levels ≥400 mg/dL) increased and displayed an abrupt slope change at MARD=10%. When added to insulin dosing decisions, information from CGM trend arrows, threshold, and predictive alarms resulted in improvement in average glycemia by 1.86, 8.17, and 8.88 mg/dL, respectively. Using CGM for insulin dosing decisions is feasible below a certain level of sensor error, estimated in silico at MARD=10%. In our experiments, further accuracy improvement did not contribute substantively to better glycemic outcomes.

Assessing Sensor Accuracy for Non-Adjunct Use of Continuous Glucose Monitoring

PubMed Central

Patek, Stephen D.; Ortiz, Edward Andrew; Breton, Marc D.

2015-01-01

Abstract Background: The level of continuous glucose monitoring (CGM) accuracy needed for insulin dosing using sensor values (i.e., the level of accuracy permitting non-adjunct CGM use) is a topic of ongoing debate. Assessment of this level in clinical experiments is virtually impossible because the magnitude of CGM errors cannot be manipulated and related prospectively to clinical outcomes. Materials and Methods: A combination of archival data (parallel CGM, insulin pump, self-monitoring of blood glucose [SMBG] records, and meals for 56 pump users with type 1 diabetes) and in silico experiments was used to “replay” real-life treatment scenarios and relate sensor error to glycemic outcomes. Nominal blood glucose (BG) traces were extracted using a mathematical model, yielding 2,082 BG segments each initiated by insulin bolus and confirmed by SMBG. These segments were replayed at seven sensor accuracy levels (mean absolute relative differences [MARDs] of 3–22%) testing six scenarios: insulin dosing using sensor values, threshold, and predictive alarms, each without or with considering CGM trend arrows. Results: In all six scenarios, the occurrence of hypoglycemia (frequency of BG levels ≤50 mg/dL and BG levels ≤39 mg/dL) increased with sensor error, displaying an abrupt slope change at MARD =10%. Similarly, hyperglycemia (frequency of BG levels ≥250 mg/dL and BG levels ≥400 mg/dL) increased and displayed an abrupt slope change at MARD=10%. When added to insulin dosing decisions, information from CGM trend arrows, threshold, and predictive alarms resulted in improvement in average glycemia by 1.86, 8.17, and 8.88 mg/dL, respectively. Conclusions: Using CGM for insulin dosing decisions is feasible below a certain level of sensor error, estimated in silico at MARD=10%. In our experiments, further accuracy improvement did not contribute substantively to better glycemic outcomes. PMID:25436913

In Silico QT and APD Prolongation Assay for Early Screening of Drug-Induced Proarrhythmic Risk.

PubMed

Romero, Lucia; Cano, Jordi; Gomis-Tena, Julio; Trenor, Beatriz; Sanz, Ferran; Pastor, Manuel; Saiz, Javier

2018-04-23

Drug-induced proarrhythmicity is a major concern for regulators and pharmaceutical companies. For novel drug candidates, the standard assessment involves the evaluation of the potassium hERG channels block and the in vivo prolongation of the QT interval. However, this method is known to be too restrictive and to stop the development of potentially valuable therapeutic drugs. The aim of this work is to create an in silico tool for early detection of drug-induced proarrhythmic risk. The system is based on simulations of how different compounds affect the action potential duration (APD) of isolated endocardial, midmyocardial, and epicardial cells as well as the QT prolongation in a virtual tissue. Multiple channel-drug interactions and state-of-the-art human ventricular action potential models ( O'Hara , T. , PLos Comput. Biol. 2011 , 7 , e1002061 ) were used in our simulations. Specifically, 206.766 cellular and 7072 tissue simulations were performed by blocking the slow and the fast components of the delayed rectifier current ( I Ks and I Kr , respectively) and the L-type calcium current ( I CaL ) at different levels. The performance of our system was validated by classifying the proarrhythmic risk of 84 compounds, 40 of which present torsadogenic properties. On the basis of these results, we propose the use of a new index (Tx) for discriminating torsadogenic compounds, defined as the ratio of the drug concentrations producing 10% prolongation of the cellular endocardial, midmyocardial, and epicardial APDs and the QT interval, over the maximum effective free therapeutic plasma concentration (EFTPC). Our results show that the Tx index outperforms standard methods for early identification of torsadogenic compounds. Indeed, for the analyzed compounds, the Tx tests accuracy was in the range of 87-88% compared with a 73% accuracy of the hERG IC 50 based test.

SigWin-detector: a Grid-enabled workflow for discovering enriched windows of genomic features related to DNA sequences.

PubMed

Inda, Márcia A; van Batenburg, Marinus F; Roos, Marco; Belloum, Adam S Z; Vasunin, Dmitry; Wibisono, Adianto; van Kampen, Antoine H C; Breit, Timo M

2008-08-08

Chromosome location is often used as a scaffold to organize genomic information in both the living cell and molecular biological research. Thus, ever-increasing amounts of data about genomic features are stored in public databases and can be readily visualized by genome browsers. To perform in silico experimentation conveniently with this genomics data, biologists need tools to process and compare datasets routinely and explore the obtained results interactively. The complexity of such experimentation requires these tools to be based on an e-Science approach, hence generic, modular, and reusable. A virtual laboratory environment with workflows, workflow management systems, and Grid computation are therefore essential. Here we apply an e-Science approach to develop SigWin-detector, a workflow-based tool that can detect significantly enriched windows of (genomic) features in a (DNA) sequence in a fast and reproducible way. For proof-of-principle, we utilize a biological use case to detect regions of increased and decreased gene expression (RIDGEs and anti-RIDGEs) in human transcriptome maps. We improved the original method for RIDGE detection by replacing the costly step of estimation by random sampling with a faster analytical formula for computing the distribution of the null hypothesis being tested and by developing a new algorithm for computing moving medians. SigWin-detector was developed using the WS-VLAM workflow management system and consists of several reusable modules that are linked together in a basic workflow. The configuration of this basic workflow can be adapted to satisfy the requirements of the specific in silico experiment. As we show with the results from analyses in the biological use case on RIDGEs, SigWin-detector is an efficient and reusable Grid-based tool for discovering windows enriched for features of a particular type in any sequence of values. Thus, SigWin-detector provides the proof-of-principle for the modular e-Science based concept of integrative bioinformatics experimentation.

Linking ice accretion and crown structure: towards a model of the effect of freezing rain on tree canopies

PubMed Central

Nock, Charles A.; Lecigne, Bastien; Taugourdeau, Olivier; Greene, David F.; Dauzat, Jean; Delagrange, Sylvain; Messier, Christian

2016-01-01

Background and Aims Despite a longstanding interest in variation in tree species vulnerability to ice storm damage, quantitative analyses of the influence of crown structure on within-crown variation in ice accretion are rare. In particular, the effect of prior interception by higher branches on lower branch accumulation remains unstudied. The aim of this study was to test the hypothesis that intra-crown ice accretion can be predicted by a measure of the degree of sheltering by neighbouring branches. Methods Freezing rain was artificially applied to Acer platanoides L., and in situ branch-ice thickness was measured directly and from LiDAR point clouds. Two models of freezing rain interception were developed: ‘IceCube’, which uses point clouds to relate ice accretion to a voxel-based index (sheltering factor; SF) of the sheltering effect of branch elements above a measurement point; and ‘IceTree’, a simulation model for in silico evaluation of the interception pattern of freezing rain in virtual tree crowns. Key Results Intra-crown radial ice accretion varied strongly, declining from the tips to the bases of branches and from the top to the base of the crown. SF for branches varied strongly within the crown, and differences among branches were consistent for a range of model parameters. Intra-crown variation in ice accretion on branches was related to SF (R2 = 0·46), with in silico results from IceTree supporting empirical relationships from IceCube. Conclusions Empirical results and simulations confirmed a key role for crown architecture in determining intra-crown patterns of ice accretion. As suspected, the concentration of freezing rain droplets is attenuated by passage through the upper crown, and thus higher branches accumulate more ice than lower branches. This is the first step in developing a model that can provide a quantitative basis for investigating intra-crown and inter-specific variation in freezing rain damage. PMID:27107412

Modelling the effect of race surface and racehorse limb parameters on in silico fetlock motion and propensity for injury.

PubMed

Symons, J E; Hawkins, D A; Fyhrie, D P; Upadhyaya, S K; Stover, S M

2017-09-01

The metacarpophalangeal joint (fetlock) is the most commonly affected site of racehorse injury, with multiple observed pathologies consistent with extreme fetlock dorsiflexion. Race surface mechanics affect musculoskeletal structure loading and injury risk because surface forces applied to the hoof affect limb motions. Race surface mechanics are a function of controllable factors. Thus, race surface design has the potential to reduce the incidence of musculoskeletal injury through modulation of limb motions. However, the relationship between race surface mechanics and racehorse limb motions is unknown. To determine the effect of changing race surface and racehorse limb model parameters on distal limb motions. Sensitivity analysis of in silico fetlock motion to changes in race surface and racehorse limb parameters using a validated, integrated racehorse and race surface computational model. Fetlock motions were determined during gallop stance from simulations on virtual surfaces with differing average vertical stiffness, upper layer (e.g. cushion) depth and linear stiffness, horizontal friction, tendon and ligament mechanics, as well as fetlock position at heel strike. Upper layer depth produced the greatest change in fetlock motion, with lesser depths yielding greater fetlock dorsiflexion. Lesser fetlock changes were observed for changes in lower layer (e.g. base or pad) mechanics (nonlinear), as well as palmar ligament and tendon stiffness. Horizontal friction and fetlock position contributed less than 1° change in fetlock motion. Simulated fetlock motions are specific to one horse's anatomy reflected in the computational model. Anatomical differences among horses may affect the magnitude of limb flexion, but will likely have similar limb motion responses to varied surface mechanics. Race surface parameters affected by maintenance produced greater changes in fetlock motion than other parameters studied. Simulations can provide evidence to inform race surface design and management to reduce the incidence of injury. © 2017 EVJ Ltd.

Effect of training data size and noise level on support vector machines virtual screening of genotoxic compounds from large compound libraries.

PubMed

Kumar, Pankaj; Ma, Xiaohua; Liu, Xianghui; Jia, Jia; Bucong, Han; Xue, Ying; Li, Ze Rong; Yang, Sheng Yong; Wei, Yu Quan; Chen, Yu Zong

2011-05-01

Various in vitro and in-silico methods have been used for drug genotoxicity tests, which show limited genotoxicity (GT+) and non-genotoxicity (GT-) identification rates. New methods and combinatorial approaches have been explored for enhanced collective identification capability. The rates of in-silco methods may be further improved by significantly diversified training data enriched by the large number of recently reported GT+ and GT- compounds, but a major concern is the increased noise levels arising from high false-positive rates of in vitro data. In this work, we evaluated the effect of training data size and noise level on the performance of support vector machines (SVM) method known to tolerate high noise levels in training data. Two SVMs of different diversity/noise levels were developed and tested. H-SVM trained by higher diversity higher noise data (GT+ in any in vivo or in vitro test) outperforms L-SVM trained by lower noise lower diversity data (GT+ in in vivo or Ames test only). H-SVM trained by 4,763 GT+ compounds reported before 2008 and 8,232 GT- compounds excluding clinical trial drugs correctly identified 81.6% of the 38 GT+ compounds reported since 2008, predicted 83.1% of the 2,008 clinical trial drugs as GT-, and 23.96% of 168 K MDDR and 27.23% of 17.86M PubChem compounds as GT+. These are comparable to the 43.1-51.9% GT+ and 75-93% GT- rates of existing in-silico methods, 58.8% GT+ and 79% GT- rates of Ames method, and the estimated percentages of 23% in vivo and 31-33% in vitro GT+ compounds in the "universe of chemicals". There is a substantial level of agreement between H-SVM and L-SVM predicted GT+ and GT- MDDR compounds and the prediction from TOPKAT. SVM showed good potential in identifying GT+ compounds from large compound libraries based on higher diversity and higher noise training data.

Marine derived compounds as binders of the White spot syndrome virus VP28 envelope protein: In silico insights from molecular dynamics and binding free energy calculations.

PubMed

Sivakumar, K C; Sajeevan, T P; Bright Singh, I S

2016-10-01

White spot syndrome virus (WSSV) remains as one of the most dreadful pathogen of the shrimp aquaculture industry owing to its high virulence. The cumulative mortality reaches up to 100% within in 2-10days in a shrimp farm. Currently, no chemotherapeutics are available to control WSSV. The viral envelope protein, VP28, located on the surface of the virus particle acts as a vital virulence factor in the initial phases of inherent WSSV infection in shrimp. Hence, inhibition of envelope protein VP28 could be a novel way to deal with infection by inhibiting its interaction in the endocytic pathway. In this direction, a timely attempt was made to recognize a potential drug candidate of marine origin against WSSV using VP28 as a target by employing in silico docking and molecular dynamic simulations. A virtual library of 388 marine bioactive compounds was extracted from reports published in Marine Drugs. The top ranking compounds from docking studies were chosen from the flexible docking based on the binding affinities (ΔGb). In addition, the MD simulation and binding free energy analysis were implemented to validate and capture intermolecular interactions. The results suggested that the two compounds obtained a negative binding free energy with -40.453kJ/mol and -31.031kJ/mol for compounds with IDs 30797199 and 144162 respectively. The RMSD curve indicated that 30797199 moves into the hydrophobic core, while the position of 144162 atoms changes abruptly during simulation and is mostly stabilized by water bridges. The shift in RMSD values of VP28 corresponding to ligand RMSD gives an insight into the ligand induced conformational changes in the protein. This study is first of its kind to elucidate the explicit binding of chemical inhibitor to WSSV major structural protein VP28. Copyright © 2016 Elsevier Ltd. All rights reserved.

Overview of telepathology, virtual microscopy, and whole slide imaging: prospects for the future.

PubMed

Weinstein, Ronald S; Graham, Anna R; Richter, Lynne C; Barker, Gail P; Krupinski, Elizabeth A; Lopez, Ana Maria; Erps, Kristine A; Bhattacharyya, Achyut K; Yagi, Yukako; Gilbertson, John R

2009-08-01

Telepathology, the practice of pathology at a long distance, has advanced continuously since 1986. Today, fourth-generation telepathology systems, so-called virtual slide telepathology systems, are being used for education applications. Both conventional and innovative surgical pathology diagnostic services are being designed and implemented as well. The technology has been commercialized by more than 30 companies in Asia, the United States, and Europe. Early adopters of telepathology have been laboratories with special challenges in providing anatomic pathology services, ranging from the need to provide anatomic pathology services at great distances to the use of the technology to increase efficiency of services between hospitals less than a mile apart. As to what often happens in medicine, early adopters of new technologies are professionals who create model programs that are successful and then stimulate the creation of infrastructure (ie, reimbursement, telecommunications, information technologies, and so on) that forms the platforms for entry of later, mainstream, adopters. The trend at medical schools, in the United States, is to go entirely digital for their pathology courses, discarding their student light microscopes, and building virtual slide laboratories. This may create a generation of pathology trainees who prefer digital pathology imaging over the traditional hands-on light microscopy. The creation of standards for virtual slide telepathology is early in its development but accelerating. The field of telepathology has now reached a tipping point at which major corporations now investing in the technology will insist that standards be created for pathology digital imaging as a value added business proposition. A key to success in teleradiology, already a growth industry, has been the implementation of standards for digital radiology imaging. Telepathology is already the enabling technology for new, innovative laboratory services. Examples include STAT QA surgical pathology second opinions at a distance and a telehealth-enabled rapid breast care service. The innovative bundling of telemammography, telepathology, and teleoncology services may represent a new paradigm in breast care that helps address the serious issue of fragmentation of breast cancer care in the United States and elsewhere. Legal and regulatory issues in telepathology are being addressed and are regarded as a potential catalyst for the next wave of telepathology advances, applications, and implementations.

In Silico Strategies for Modeling Stereoselective Metabolism of Pyrethroids

EPA Science Inventory

In silico methods are invaluable tools to researchers seeking to understand and predict metabolic processes within PBPK models. Even though these methods have been successfully utilized to predict and quantify metabolic processes, there are many challenges involved. Stereochemica...

Influence of Basicity on High-Chromium Vanadium-Titanium Magnetite Sinter Properties, Productivity, and Mineralogy

NASA Astrophysics Data System (ADS)

Zhou, Mi; Yang, Songtao; Jiang, Tao; Xue, Xiangxin

2015-05-01

The effect of basicity on high-chromium vanadium-titanium magnetite (V-Ti-Cr) sintering was studied via sintering pot tests. The sinter rate, yield, and productivity were calculated before determining sinter strength (TI) and reduction degradation index (RDI). Furthermore, the effect of basicity on V-Ti-Cr sinter mineralogy was clarified using metallographic microscopy, x-ray diffraction, and scanning electron microscopy-energy-dispersive x-ray spectroscopy. The results indicate that increasing basicity quickly increases the sintering rate from 25.4 mm min-1 to 28.9 mm min-1, yield from 75.3% to 87.2%, TI from 55.4% to 64.8%, and productivity from 1.83 t (m2 h)-1 to 1.94 t (m2 h)-1 before experiencing a slight drop. The V-Ti-Cr sinter shows complex mineral composition, with main mineral phases such as magnetite, hematite, silicate (dicalcium silicate, Ca-Fe olivine, glass), calcium and aluminum silico-ferrite (SFCA/SFCAI) and perovskite. Perovskite is notable because it lowers the V-Ti sinter strength and RDI. The well intergrowths between magnetite and SFCA/SFCAI, and the decrease in perovskite and secondary skeletal hematite are the key for improving TI and RDI. Finally, a comprehensive index was calculated, and the optimal V-Ti-Cr sinter basicity also for industrial application was 2.55.

Modeling and Prediction of Drug Dispersability in Polyvinylpyrrolidone-Vinyl Acetate Copolymer Using a Molecular Descriptor.

PubMed

DeBoyace, Kevin; Buckner, Ira S; Gong, Yuchuan; Ju, Tzu-Chi Rob; Wildfong, Peter L D

2018-01-01

The expansion of a novel in silico model for the prediction of the dispersability of 18 model compounds with polyvinylpyrrolidone-vinyl acetate copolymer is described. The molecular descriptor R3m (atomic mass weighted 3rd-order autocorrelation index) is shown to be predictive of the formation of amorphous solid dispersions at 2 drug loadings (15% and 75% w/w) using 2 preparation methods (melt quenching and solvent evaporation using a rotary evaporator). Cosolidified samples were characterized using a suite of analytical techniques, which included differential scanning calorimetry, powder X-ray diffraction, pair distribution function analysis, polarized light microscopy, and hot stage microscopy. Logistic regression was applied, where appropriate, to model the success and failure of compound dispersability in polyvinylpyrrolidone-vinyl acetate copolymer. R3m had combined prediction accuracy greater than 90% for tested samples. The usefulness of this descriptor appears to be associated with the presence of heavy atoms in the molecular structure of the active pharmaceutical ingredient, and their location with respect to the geometric center of the molecule. Given the higher electronegativity and atomic volume of these types of atoms, it is hypothesized that they may impact the molecular mobility of the active pharmaceutical ingredient, or increase the likelihood of forming nonbonding interactions with the carrier polymer. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Identification of Inhibitors against Metastasis Protein “Survivin:” In silico Discovery Using Virtual Screening and Molecular Docking Studies

PubMed Central

Mishra, Swechha; Singh, Sangeeta

2017-01-01

Background: In experimental therapy of cancer, survivin is considered to be one of the well-established targets. Studies have found that it is overexpression in most of the human tumors, but it is rarely found in normal tissues. It is having varied structural and functional role. It controls cell division and cellular stress response and also regulates metastasis and migration of cancerous cells. It has also been recognized as a biomarker which makes it unconventional drug target. In spite of being one of the centrally active components in metastasis and invasion, their clinical use is minimal. To increase the therapeutic efficiency of cancer and its various stages, it is important to survey novel reagents targeting the pathways and mechanism involving survivin. Objective: The aim of this study was to identify novel survivin inhibitor candidates using in silico screening. Materials and Methods: In this course of work, virtual screening on a dataset of natural compounds retrieved from ZINC and other libraries were performed. Comparative analysis of the protein was done by studying the binding affinity of inhibitors that are already available. The best interacting complex was set for molecular dynamics simulation for 25 ns to validate the stability of system. These molecules were checked for their toxicity and absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties using OSIRIS and pre-ADMET tools. Results: We discovered ten such candidates with better binding efficiency with survivin in comparison to marketed chemical against the same. Furthermore, these inhibitor candidates did not induce cell toxicity. Binding affinity of reference molecules was varied from −6.8 to −8.5 kcal/mol while that of top scoring compound ZINC00689728 is −9.3 kcal/mol binding energy. Good placement and strong bond formation of selected molecule was observed during course of work. It is also having permissible ADMET property. Conclusion: Considering all the parameters, the screened molecule can be considered as a potential lead compound for designing new drug against survivin. Further investigation and testing will be required to make it to the final stage. SUMMARY Survivin is one of the important protein of metastasis. Inhibiting survivin might led to the increased therapeutic efficiency of cancer. In this work we are screening library of natural compounds in view of finding some potent inhibitor against survivin. Abbreviations used: MD: Molecular dynamics, LogS: Aqueous solubility, Acceptor HB: Hydrogen bond acceptor, Donor HB: Donor hydrogen bond donor, ADMET: Absorption, distribution, metabolism, excretion, and toxicity, RCSB: Research Collaboratory for Structural Bioinformatics, OPLS: Optimized potentials for liquid simulations, RMSD: Root-mean-square deviation. PMID:29491627

The acceptance of in silico models for REACH: Requirements, barriers, and perspectives

PubMed Central

2011-01-01

In silico models have prompted considerable interest and debate because of their potential value in predicting the properties of chemical substances for regulatory purposes. The European REACH legislation promotes innovation and encourages the use of alternative methods, but in practice the use of in silico models is still very limited. There are many stakeholders influencing the regulatory trajectory of quantitative structure-activity relationships (QSAR) models, including regulators, industry, model developers and consultants. Here we outline some of the issues and challenges involved in the acceptance of these methods for regulatory purposes. PMID:21982269

Molecular level in silico studies for oncology. Direct models review

NASA Astrophysics Data System (ADS)

Psakhie, S. G.; Tsukanov, A. A.

2017-09-01

The combination of therapy and diagnostics in one process "theranostics" is a trend in a modern medicine, especially in oncology. Such an approach requires development and usage of multifunctional hybrid nanoparticles with a hierarchical structure. Numerical methods and mathematical models play a significant role in the design of the hierarchical nanoparticles and allow looking inside the nanoscale mechanisms of agent-cell interactions. The current position of in silico approach in biomedicine and oncology is discussed. The review of the molecular level in silico studies in oncology, which are using the direct models, is presented.

Propagating annotations of molecular networks using in silico fragmentation

PubMed Central

da Silva, Ricardo R.; Wang, Mingxun; Fox, Evan; Balunas, Marcy J.; Klassen, Jonathan L.; Dorrestein, Pieter C.

2018-01-01

The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp. PMID:29668671

Propagating annotations of molecular networks using in silico fragmentation.

PubMed

da Silva, Ricardo R; Wang, Mingxun; Nothias, Louis-Félix; van der Hooft, Justin J J; Caraballo-Rodríguez, Andrés Mauricio; Fox, Evan; Balunas, Marcy J; Klassen, Jonathan L; Lopes, Norberto Peporine; Dorrestein, Pieter C

2018-04-01

The annotation of small molecules is one of the most challenging and important steps in untargeted mass spectrometry analysis, as most of our biological interpretations rely on structural annotations. Molecular networking has emerged as a structured way to organize and mine data from untargeted tandem mass spectrometry (MS/MS) experiments and has been widely applied to propagate annotations. However, propagation is done through manual inspection of MS/MS spectra connected in the spectral networks and is only possible when a reference library spectrum is available. One of the alternative approaches used to annotate an unknown fragmentation mass spectrum is through the use of in silico predictions. One of the challenges of in silico annotation is the uncertainty around the correct structure among the predicted candidate lists. Here we show how molecular networking can be used to improve the accuracy of in silico predictions through propagation of structural annotations, even when there is no match to a MS/MS spectrum in spectral libraries. This is accomplished through creating a network consensus of re-ranked structural candidates using the molecular network topology and structural similarity to improve in silico annotations. The Network Annotation Propagation (NAP) tool is accessible through the GNPS web-platform https://gnps.ucsd.edu/ProteoSAFe/static/gnps-theoretical.jsp.

Reliability of rapid diagnostic test for diagnosing peripheral and placental malaria in an area of unstable malaria transmission in Eastern Sudan

PubMed Central

2013-01-01

Background Diagnosing Plasmodium falciparum malaria during pregnancy is a great challenge for clinicians because of the low density of parasites in the peripheral blood and parasite sequestration in the placenta. Nevertheless, few data on the use of malaria rapid diagnostic test (RDT) during pregnancy have been published. Methods P. falciparum infections were assessed in 156 febrile pregnant women by microscopic examination of their blood smears and by RDT and polymerase chain reactions (PCR). In addition, 150 women were assessed at the time of delivery by microscopy, RDT, PCR and placental histology investigations. The study was conducted at the Gadarif Hospital, Eastern Sudan. The SD Bioline P. f / P. v (Bio Standard Diagnostics, Gurgaon, Korea) RDT kit was evaluated in this study. Results Among the febrile pregnant women, 17 (11.0%), 26 (16.7%) and 18 (11.5%) positive cases of P. falciparum were detected by microscopy, RDT, and PCR, respectively. The sensitivity and specificity of the microscopy was 94.4% and 100%, respectively. The corresponding values for RDT evaluation were 83.3% and 92.0%, as compared with PCR as the gold standard. While there were no detected cases of malaria by microscopic examination of blood smears, 27 (18.0%), 21(14.0%) and 46 (30.7%) out of the 150 placentae investigated had P. falciparum as determined by RDT, PCR, and histology, respectively. The sensitivity and specificity for RDT was 17.4% and 81.7%, respectively. The corresponding values for PCR were 6.5% and 82.7%, where histology was used as the gold standard. Conclusions The RDT kit used in this study has poor performance for peripheral and placental P. falciparum malaria detection in this setting. Virtual slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1092363465928479 PMID:23587371

DockScreen: A database of in silico biomolecular interactions to support computational toxicology

EPA Science Inventory

We have developed DockScreen, a database of in silico biomolecular interactions designed to enable rational molecular toxicological insight within a computational toxicology framework. This database is composed of chemical/target (receptor and enzyme) binding scores calculated by...

Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Liying; Sedykh, Alexander; Tripathi, Ashutosh

2013-10-01

Identification of endocrine disrupting chemicals is one of the important goals of environmental chemical hazard screening. We report on the development of validated in silico predictors of chemicals likely to cause estrogen receptor (ER)-mediated endocrine disruption to facilitate their prioritization for future screening. A database of relative binding affinity of a large number of ERα and/or ERβ ligands was assembled (546 for ERα and 137 for ERβ). Both single-task learning (STL) and multi-task learning (MTL) continuous quantitative structure–activity relationship (QSAR) models were developed for predicting ligand binding affinity to ERα or ERβ. High predictive accuracy was achieved for ERα bindingmore » affinity (MTL R{sup 2} = 0.71, STL R{sup 2} = 0.73). For ERβ binding affinity, MTL models were significantly more predictive (R{sup 2} = 0.53, p < 0.05) than STL models. In addition, docking studies were performed on a set of ER agonists/antagonists (67 agonists and 39 antagonists for ERα, 48 agonists and 32 antagonists for ERβ, supplemented by putative decoys/non-binders) using the following ER structures (in complexes with respective ligands) retrieved from the Protein Data Bank: ERα agonist (PDB ID: 1L2I), ERα antagonist (PDB ID: 3DT3), ERβ agonist (PDB ID: 2NV7), and ERβ antagonist (PDB ID: 1L2J). We found that all four ER conformations discriminated their corresponding ligands from presumed non-binders. Finally, both QSAR models and ER structures were employed in parallel to virtually screen several large libraries of environmental chemicals to derive a ligand- and structure-based prioritized list of putative estrogenic compounds to be used for in vitro and in vivo experimental validation. - Highlights: • This is the largest curated dataset inclusive of ERα and β (the latter is unique). • New methodology that for the first time affords acceptable ERβ models. • A combination of QSAR and docking enables prediction of affinity and function. • The results have potential applications to green chemistry. • Models are publicly available for virtual screening via a web portal.« less

Evaluation of a genome-scale in silico metabolic model for Geobacter metallireducens by using proteomic data from a field biostimulation experiment.

PubMed

Fang, Yilin; Wilkins, Michael J; Yabusaki, Steven B; Lipton, Mary S; Long, Philip E

2012-12-01

Accurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within an in silico model using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model of Geobacter metallireducens-specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment.

Alzheimer's disease biomarker discovery using in silico literature mining and clinical validation

PubMed Central

2012-01-01

Background Alzheimer’s Disease (AD) is the most widespread form of dementia in the elderly but despite progress made in recent years towards a mechanistic understanding, there is still an urgent need for disease modification therapy and for early diagnostic tests. Substantial international efforts are being made to discover and validate biomarkers for AD using candidate analytes and various data-driven 'omics' approaches. Cerebrospinal fluid is in many ways the tissue of choice for biomarkers of brain disease but is limited by patient and clinician acceptability, and increasing attention is being paid to the search for blood-based biomarkers. The aim of this study was to use a novel in silico approach to discover a set of candidate biomarkers for AD. Methods We used an in silico literature mining approach to identify potential biomarkers by creating a summarized set of assertional metadata derived from relevant legacy information. We then assessed the validity of this approach using direct assays of the identified biomarkers in plasma by immunodetection methods. Results Using this in silico approach, we identified 25 biomarker candidates, at least three of which have subsequently been reported to be altered in blood or CSF from AD patients. Two further candidate biomarkers, indicated from the in silico approach, were choline acetyltransferase and urokinase-type plasminogen activator receptor. Using immunodetection, we showed that, in a large sample set, these markers are either altered in disease or correlate with MRI markers of atrophy. Conclusions These data support as a proof of concept the use of data mining and in silico analyses to derive valid biomarker candidates for AD and, by extension, for other disorders. PMID:23113945

In silico regenerative medicine: how computational tools allow regulatory and financial challenges to be addressed in a volatile market

PubMed Central

Geris, L.; Guyot, Y.; Schrooten, J.; Papantoniou, I.

2016-01-01

The cell therapy market is a highly volatile one, due to the use of disruptive technologies, the current economic situation and the small size of the market. In such a market, companies as well as academic research institutes are in need of tools to advance their understanding and, at the same time, reduce their R&D costs, increase product quality and productivity, and reduce the time to market. An additional difficulty is the regulatory path that needs to be followed, which is challenging in the case of cell-based therapeutic products and should rely on the implementation of quality by design (QbD) principles. In silico modelling is a tool that allows the above-mentioned challenges to be addressed in the field of regenerative medicine. This review discusses such in silico models and focuses more specifically on the bioprocess. Three (clusters of) examples related to this subject are discussed. The first example comes from the pharmaceutical engineering field where QbD principles and their implementation through the use of in silico models are both a regulatory and economic necessity. The second example is related to the production of red blood cells. The described in silico model is mainly used to investigate the manufacturing process of the cell-therapeutic product, and pays special attention to the economic viability of the process. Finally, we describe the set-up of a model capturing essential events in the development of a tissue-engineered combination product in the context of bone tissue engineering. For each of the examples, a short introduction to some economic aspects is given, followed by a description of the in silico tool or tools that have been developed to allow the implementation of QbD principles and optimal design. PMID:27051516

In silico regenerative medicine: how computational tools allow regulatory and financial challenges to be addressed in a volatile market.

PubMed

Geris, L; Guyot, Y; Schrooten, J; Papantoniou, I

2016-04-06

The cell therapy market is a highly volatile one, due to the use of disruptive technologies, the current economic situation and the small size of the market. In such a market, companies as well as academic research institutes are in need of tools to advance their understanding and, at the same time, reduce their R&D costs, increase product quality and productivity, and reduce the time to market. An additional difficulty is the regulatory path that needs to be followed, which is challenging in the case of cell-based therapeutic products and should rely on the implementation of quality by design (QbD) principles. In silico modelling is a tool that allows the above-mentioned challenges to be addressed in the field of regenerative medicine. This review discusses such in silico models and focuses more specifically on the bioprocess. Three (clusters of) examples related to this subject are discussed. The first example comes from the pharmaceutical engineering field where QbD principles and their implementation through the use of in silico models are both a regulatory and economic necessity. The second example is related to the production of red blood cells. The described in silico model is mainly used to investigate the manufacturing process of the cell-therapeutic product, and pays special attention to the economic viability of the process. Finally, we describe the set-up of a model capturing essential events in the development of a tissue-engineered combination product in the context of bone tissue engineering. For each of the examples, a short introduction to some economic aspects is given, followed by a description of the in silico tool or tools that have been developed to allow the implementation of QbD principles and optimal design.

Machine Learning-based Virtual Screening and Its Applications to Alzheimer's Drug Discovery: A Review.

PubMed

Carpenter, Kristy A; Huang, Xudong

2018-06-07

Virtual Screening (VS) has emerged as an important tool in the drug development process, as it conducts efficient in silico searches over millions of compounds, ultimately increasing yields of potential drug leads. As a subset of Artificial Intelligence (AI), Machine Learning (ML) is a powerful way of conducting VS for drug leads. ML for VS generally involves assembling a filtered training set of compounds, comprised of known actives and inactives. After training the model, it is validated and, if sufficiently accurate, used on previously unseen databases to screen for novel compounds with desired drug target binding activity. The study aims to review ML-based methods used for VS and applications to Alzheimer's disease (AD) drug discovery. To update the current knowledge on ML for VS, we review thorough backgrounds, explanations, and VS applications of the following ML techniques: Naïve Bayes (NB), k-Nearest Neighbors (kNN), Support Vector Machines (SVM), Random Forests (RF), and Artificial Neural Networks (ANN). All techniques have found success in VS, but the future of VS is likely to lean more heavily toward the use of neural networks - and more specifically, Convolutional Neural Networks (CNN), which are a subset of ANN that utilize convolution. We additionally conceptualize a work flow for conducting ML-based VS for potential therapeutics of for AD, a complex neurodegenerative disease with no known cure and prevention. This both serves as an example of how to apply the concepts introduced earlier in the review and as a potential workflow for future implementation. Different ML techniques are powerful tools for VS, and they have advantages and disadvantages albeit. ML-based VS can be applied to AD drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

In Silico Identification of Mimicking Molecules as Defense Inducers Triggering Jasmonic Acid Mediated Immunity against Alternaria Blight Disease in Brassica Species

PubMed Central

Pathak, Rajesh K.; Baunthiyal, Mamta; Shukla, Rohit; Pandey, Dinesh; Taj, Gohar; Kumar, Anil

2017-01-01

Alternaria brassicae and Alternaria brassicicola are two major phytopathogenic fungi which cause Alternaria blight, a recalcitrant disease on Brassica crops throughout the world, which is highly destructive and responsible for significant yield losses. Since no resistant source is available against Alternaria blight, therefore, efforts have been made in the present study to identify defense inducer molecules which can induce jasmonic acid (JA) mediated defense against the disease. It is believed that JA triggered defense response will prevent necrotrophic mode of colonization of Alternaria brassicae fungus. The JA receptor, COI1 is one of the potential targets for triggering JA mediated immunity through interaction with JA signal. In the present study, few mimicking compounds more efficient than naturally occurring JA in terms of interaction with COI1 were identified through virtual screening and molecular dynamics simulation studies. A high quality structural model of COI1 was developed using the protein sequence of Brassica rapa. This was followed by virtual screening of 767 analogs of JA from ZINC database for interaction with COI1. Two analogs viz. ZINC27640214 and ZINC43772052 showed more binding affinity with COI1 as compared to naturally occurring JA. Molecular dynamics simulation of COI1 and COI1-JA complex, as well as best screened interacting structural analogs of JA with COI1 was done for 50 ns to validate the stability of system. It was found that ZINC27640214 possesses efficient, stable, and good cell permeability properties. Based on the obtained results and its physicochemical properties, it is capable of mimicking JA signaling and may be used as defense inducers for triggering JA mediated resistance against Alternaria blight, only after further validation through field trials. PMID:28487711

Benzene-1,3-dicarboxylic acid 2,5-dimethylpyrrole derivatives as multiple inhibitors of bacterial Mur ligases (MurC-MurF).

PubMed

Perdih, Andrej; Hrast, Martina; Barreteau, Hélène; Gobec, Stanislav; Wolber, Gerhard; Solmajer, Tom

2014-08-01

Enzymes catalyzing the biosynthesis of bacterial peptidoglycan represent traditionally a collection of highly selective targets for novel antibacterial drug design. Four members of the bacterial Mur ligase family-MurC, MurD, MurE and MurF-are involved in the intracellular steps of peptidoglycan biosynthesis, catalyzing the synthesis of the peptide moiety of the Park's nucleotide. In our previous virtual screening campaign, a chemical class of benzene-1,3-dicarboxylic acid 2,5-dimethylpyrrole derivatives exhibiting dual MurD/MurE inhibition properties was discovered. In the present study we further investigated this class of compounds by performing inhibition assays on all four Mur ligases (MurC-MurF). Furthermore, molecular dynamics (MD) simulation studies of one of the initially discovered compound 1 were performed to explore its geometry as well as its energetic behavior based on the Linear Interaction Energy (LIE) method. Further in silico virtual screening (VS) experiments based on the parent active compound 1 were conducted to optimize the discovered series. Selected hits were assayed against all Escherichia coli MurC-MurF enzymes in biochemical inhibition assays and molecules 10-14 containing benzene-1,3-dicarboxylic acid 2,5-dimethylpyrrole coupled with five member-ring rhodanine moiety were found to be multiple inhibitors of the whole MurC-MurF cascade of bacterial enzymes in the micromolar range. Steady-state kinetics studies suggested this class to act as competitive inhibitors of the MurD enzyme towards d-Glu. These compounds represent novel valuable starting point in the development of novel antibacterial agents. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cheminformatics-aided discovery of small-molecule Protein-Protein Interaction (PPI) dual inhibitors of Tumor Necrosis Factor (TNF) and Receptor Activator of NF-κB Ligand (RANKL).

PubMed

Melagraki, Georgia; Ntougkos, Evangelos; Rinotas, Vagelis; Papaneophytou, Christos; Leonis, Georgios; Mavromoustakos, Thomas; Kontopidis, George; Douni, Eleni; Afantitis, Antreas; Kollias, George

2017-04-01

We present an in silico drug discovery pipeline developed and applied for the identification and virtual screening of small-molecule Protein-Protein Interaction (PPI) compounds that act as dual inhibitors of TNF and RANKL through the trimerization interface. The cheminformatics part of the pipeline was developed by combining structure-based with ligand-based modeling using the largest available set of known TNF inhibitors in the literature (2481 small molecules). To facilitate virtual screening, the consensus predictive model was made freely available at: http://enalos.insilicotox.com/TNFPubChem/. We thus generated a priority list of nine small molecules as candidates for direct TNF function inhibition. In vitro evaluation of these compounds led to the selection of two small molecules that act as potent direct inhibitors of TNF function, with IC50 values comparable to those of a previously-described direct inhibitor (SPD304), but with significantly reduced toxicity. These molecules were also identified as RANKL inhibitors and validated in vitro with respect to this second functionality. Direct binding of the two compounds was confirmed both for TNF and RANKL, as well as their ability to inhibit the biologically-active trimer forms. Molecular dynamics calculations were also carried out for the two small molecules in each protein to offer additional insight into the interactions that govern TNF and RANKL complex formation. To our knowledge, these compounds, namely T8 and T23, constitute the second and third published examples of dual small-molecule direct function inhibitors of TNF and RANKL, and could serve as lead compounds for the development of novel treatments for inflammatory and autoimmune diseases.

Virtual quantification of metabolites by capillary electrophoresis-electrospray ionization-mass spectrometry: predicting ionization efficiency without chemical standards.

PubMed

Chalcraft, Kenneth R; Lee, Richard; Mills, Casandra; Britz-McKibbin, Philip

2009-04-01

A major obstacle in metabolomics remains the identification and quantification of a large fraction of unknown metabolites in complex biological samples when purified standards are unavailable. Herein we introduce a multivariate strategy for de novo quantification of cationic/zwitterionic metabolites using capillary electrophoresis-electrospray ionization-mass spectrometry (CE-ESI-MS) based on fundamental molecular, thermodynamic, and electrokinetic properties of an ion. Multivariate calibration was used to derive a quantitative relationship between the measured relative response factor (RRF) of polar metabolites with respect to four physicochemical properties associated with ion evaporation in ESI-MS, namely, molecular volume (MV), octanol-water distribution coefficient (log D), absolute mobility (mu(o)), and effective charge (z(eff)). Our studies revealed that a limited set of intrinsic solute properties can be used to predict the RRF of various classes of metabolites (e.g., amino acids, amines, peptides, acylcarnitines, nucleosides, etc.) with reasonable accuracy and robustness provided that an appropriate training set is validated and ion responses are normalized to an internal standard(s). The applicability of the multivariate model to quantify micromolar levels of metabolites spiked in red blood cell (RBC) lysates was also examined by CE-ESI-MS without significant matrix effects caused by involatile salts and/or major co-ion interferences. This work demonstrates the feasibility for virtual quantification of low-abundance metabolites and their isomers in real-world samples using physicochemical properties estimated by computer modeling, while providing deeper insight into the wide disparity of solute responses in ESI-MS. New strategies for predicting ionization efficiency in silico allow for rapid and semiquantitative analysis of newly discovered biomarkers and/or drug metabolites in metabolomics research when chemical standards do not exist.

Blocking the interaction between HIV-1 integrase and human LEDGF/p75: mutational studies, virtual screening and molecular dynamics simulations.

PubMed

Reddy, Karnati Konda; Singh, Poonam; Singh, Sanjeev Kumar

2014-03-04

HIV-1 integrase (IN) mediates integration of viral cDNA into the host cell genome, an essential step in the retroviral life cycle. The human lens epithelium-derived growth factor (LEDGF/p75) is a co-factor of HIV-1 IN that plays a crucial role in viral integration. Because of its crucial role in early steps of HIV replication, the IN-LEDGF/p75 interaction represents an attractive target for anti-HIV drug discovery. In this study, the IN-LEDGF/p75 interaction was studied by in silico mutational studies and molecular dynamics simulations. The results showed that all of the key residues in the LEDGF/p75 binding pocket of IN protein are important for stabilization of the complex. Structure-based virtual screening against HIV-1 IN using the ChemBridge database was performed through three different protocols of docking simulations with varying precisions and computational intensities. Six compounds based on the docking score, binding affinity and pharmacokinetic parameters were selected and an analysis of the interactions with key amino acid residues of IN was carried out. Subsequently, molecular dynamics simulations of these compounds in the LEDGF/p75 binding site of IN were carried out in order to study the stability of complexes and their hydrogen bonding interactions. IN residues Glu170, His171, and Thr174 in chain A as well as Gln95 and Thr125 in chain B were discovered to play important roles in the binding of compounds. These findings could be helpful for blocking IN-LEDGF/p75 interaction, and provide a method for avoiding viral resistance and cross-resistance.

Virtual tissues in toxicology.

PubMed

Shah, Imran; Wambaugh, John

2010-02-01

New approaches are vital for efficiently evaluating human health risk of thousands of chemicals in commerce. In vitro models offer a high-throughput approach for assaying chemical-induced molecular and cellular changes; however, bridging these perturbations to in vivo effects across chemicals, dose, time, and species remains challenging. Technological advances in multiresolution imaging and multiscale simulation are making it feasible to reconstruct tissues in silico. In toxicology, these "virtual" tissues (VT) aim to predict histopathological outcomes from alterations of cellular phenotypes that are controlled by chemical-induced perturbations in molecular pathways. The behaviors of thousands of heterogeneous cells in tissues are simulated discretely using agent-based modeling (ABM), in which computational "agents" mimic cell interactions and cellular responses to the microenvironment. The behavior of agents is constrained by physical laws and biological rules derived from experimental evidence. VT extend compartmental physiologic models to simulate both acute insults as well as the chronic effects of low-dose exposure. Furthermore, agent behavior can encode the logic of signaling and genetic regulatory networks to evaluate the role of different pathways in chemical-induced injury. To extrapolate toxicity across species, chemicals, and doses, VT require four main components: (a) organization of prior knowledge on physiologic events to define the mechanistic rules for agent behavior, (b) knowledge on key chemical-induced molecular effects, including activation of stress sensors and changes in molecular pathways that alter the cellular phenotype, (c) multiresolution quantitative and qualitative analysis of histologic data to characterize and measure chemical-, dose-, and time-dependent physiologic events, and (d) multiscale, spatiotemporal simulation frameworks to effectively calibrate and evaluate VT using experimental data. This investigation presents the motivation, implementation, and application of VT with examples from hepatotoxicity and carcinogenesis.

TARGETED DELIVERY OF INHALED PHARMACEUTICALS USING AN IN SILICO DOSIMETRY MODEL

EPA Science Inventory

We present an in silico dosimetry model which can be used for inhalation toxicology (risk assessment of inhaled air pollutants) and aerosol therapy ( targeted delivery of inhaled drugs). This work presents scientific and clinical advances beyond the development of the original in...

Multiscale 3D virtual dissections of 100-million-year-old flowers using X-ray synchrotron micro- and nanotomography.

PubMed

Moreau, Jean-David; Cloetens, Peter; Gomez, Bernard; Daviero-Gomez, Véronique; Néraudeau, Didier; Lafford, Tamzin A; Tafforeau, Paul

2014-02-01

A multiscale approach combining phase-contrast X-ray micro- and nanotomography is applied for imaging a Cretaceous fossil inflorescence in the resolution range from 0.75 μm to 50 nm. The wide range of scale views provides three-dimensional reconstructions from the external gross morphology of the inflorescence fragment to the finest exine sculptures of in situ pollen. This approach enables most of the characteristics usually observed under light microscopy, or with low magnification under scanning and transmission electron microscopy, to be obtained nondestructively. In contrast to previous tomography studies of fossil and extant flowers that used resolutions down to the micron range, we used voxels with a 50 nm side in local tomography scans. This high level of resolution enables systematic affinities of fossil flowers to be established without breaking or slicing specimens.

Retrieving spin textures on curved magnetic thin films with full-field soft X-ray microscopies

DOE PAGES

Streubel, Robert; Kronast, Florian; Fischer, Peter; ...

2015-07-03

X-ray tomography is a well-established technique to characterize 3D structures in material sciences and biology; its magnetic analogue—magnetic X-ray tomography—is yet to be developed. We demonstrate the visualization and reconstruction of magnetic domain structures in a 3D curved magnetic thin films with tubular shape by means of full-field soft X-ray microscopies. In the 3D arrangement of the magnetization is retrieved from a set of 2D projections by analysing the evolution of the magnetic contrast with varying projection angle. By using reconstruction algorithms to analyse the angular evolution of 2D projections provides quantitative information about domain patterns and magnetic coupling phenomenamore » between windings of azimuthally and radially magnetized tubular objects. In conclusion, the present approach represents a first milestone towards visualizing magnetization textures of 3D curved thin films with virtually arbitrary shape.« less

Applying tattoo dye as a third-harmonic generation contrast agent for in vivo optical virtual biopsy of human skin

NASA Astrophysics Data System (ADS)

Tsai, Ming-Rung; Lin, Chen-Yu; Liao, Yi-Hua; Sun, Chi-Kuang

2013-02-01

Third-harmonic generation (THG) microscopy has been reported to provide intrinsic contrast in elastic fibers, cytoplasmic membrane, nucleus, actin filaments, lipid bodies, hemoglobin, and melanin in human skin. For advanced molecular imaging, exogenous contrast agents are developed for a higher structural or molecular specificity. We demonstrate the potential of the commonly adopted tattoo dye as a THG contrast agent for in vivo optical biopsy of human skin. Spectroscopy and microscopy experiments were performed on cultured cells with tattoo dyes, in tattooed mouse skin, and in tattooed human skin to demonstrate the THG enhancement effect. Compared with other absorbing dyes or nanoparticles used as exogenous THG contrast agents, tattoo dyes are widely adopted in human skin so that future clinical biocompatibility evaluation is relatively achievable. Combined with the demonstrated THG enhancement effect, tattoo dyes show their promise for future clinical imaging applications.

Imaging calcium sparks in cardiac myocytes.

PubMed

Guatimosim, Silvia; Guatimosim, Cristina; Song, Long-Sheng

2011-01-01

Calcium ions play fundamental roles in many cellular processes in virtually all type of cells. The use of Ca(2+) sensitive fluorescent indicators has proven to be an indispensable tool for studying the spatio-temporal dynamics of intracellular calcium ([Ca(2+)](i)). With the aid of laser scanning confocal microscopy and new generation of Ca(2+) indicators, highly localized, short-lived Ca(2+) signals, namely Ca(2+) sparks, were revealed as elementary Ca(2+) release events during excitation-contraction coupling in cardiomyocytes. Since the discovery of Ca(2+) sparks in 1993, the demonstration of dynamic Ca(2+) micro-domains in living cardiomyocytes has revolutionized our understanding of Ca(2+)-mediated signal transduction in normal and diseased hearts. In this chapter, we have described a commonly used method for recording local and global Ca(2+) signals in cardiomyocytes using the fluorescent indicator fluo-4 acetoxymethyl (AM) and laser scanning confocal microscopy.

Simulation-based Extraction of Key Material Parameters from Atomic Force Microscopy

NASA Astrophysics Data System (ADS)

Alsafi, Huseen; Peninngton, Gray

Models for the atomic force microscopy (AFM) tip and sample interaction contain numerous material parameters that are often poorly known. This is especially true when dealing with novel material systems or when imaging samples that are exposed to complicated interactions with the local environment. In this work we use Monte Carlo methods to extract sample material parameters from the experimental AFM analysis of a test sample. The parameterized theoretical model that we use is based on the Virtual Environment for Dynamic AFM (VEDA) [1]. The extracted material parameters are then compared with the accepted values for our test sample. Using this procedure, we suggest a method that can be used to successfully determine unknown material properties in novel and complicated material systems. We acknowledge Fisher Endowment Grant support from the Jess and Mildred Fisher College of Science and Mathematics,Towson University.

Atomic force microscopy – looking at mechanosensors on the cell surface

PubMed Central

Heinisch, Jürgen J.; Lipke, Peter N.; Beaussart, Audrey; El Kirat Chatel, Sofiane; Dupres, Vincent; Alsteens, David; Dufrêne, Yves F.

2012-01-01

Summary Living cells use cell surface proteins, such as mechanosensors, to constantly sense and respond to their environment. However, the way in which these proteins respond to mechanical stimuli and assemble into large complexes remains poorly understood at the molecular level. In the past years, atomic force microscopy (AFM) has revolutionized the way in which biologists analyze cell surface proteins to molecular resolution. In this Commentary, we discuss how the powerful set of advanced AFM techniques (e.g. live-cell imaging and single-molecule manipulation) can be integrated with the modern tools of molecular genetics (i.e. protein design) to study the localization and molecular elasticity of individual mechanosensors on the surface of living cells. Although we emphasize recent studies on cell surface proteins from yeasts, the techniques described are applicable to surface proteins from virtually all organisms, from bacteria to human cells. PMID:23077172

Preparation of herpes simplex virus-infected primary neurons for transmission electron microscopy.

PubMed

Miranda-Saksena, Monica; Boadle, Ross; Cunningham, Anthony L

2014-01-01

Transmission electron microscopy (TEM) provides the resolution necessary to identify both viruses and subcellular components of cells infected with many types of viruses, including herpes simplex virus. Recognized as a powerful tool in both diagnostic and research-based virology laboratories, TEM has made possible the identification of new viruses and has contributed to the elucidation of virus life cycle and virus-host cell interaction. Whilst there are many sample preparation techniques for TEM, conventional processing using chemical fixation and resin embedding remains a useful technique, available in virtually all EM laboratories, for studying virus/cell ultrastructure. In this chapter, we describe the preparation of herpes simplex virus-infected primary neurons, grown on plastic cover slips, to allow sectioning of neurons and axons in their growth plane. This technique allows TEM examination of cell bodies, axons, growth cones, and varicosities, providing powerful insights into virus-cell interaction.

Retrieving spin textures on curved magnetic thin films with full-field soft X-ray microscopies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Streubel, Robert; Kronast, Florian; Fischer, Peter

X-ray tomography is a well-established technique to characterize 3D structures in material sciences and biology; its magnetic analogue—magnetic X-ray tomography—is yet to be developed. We demonstrate the visualization and reconstruction of magnetic domain structures in a 3D curved magnetic thin films with tubular shape by means of full-field soft X-ray microscopies. In the 3D arrangement of the magnetization is retrieved from a set of 2D projections by analysing the evolution of the magnetic contrast with varying projection angle. By using reconstruction algorithms to analyse the angular evolution of 2D projections provides quantitative information about domain patterns and magnetic coupling phenomenamore » between windings of azimuthally and radially magnetized tubular objects. In conclusion, the present approach represents a first milestone towards visualizing magnetization textures of 3D curved thin films with virtually arbitrary shape.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sotomayor, Marcos

Hair cell mechanotransduction happens in tens of microseconds, involves forces of a few picoNewtons, and is mediated by nanometer-scale molecular conformational changes. As proteins involved in this process become identified and their high resolution structures become available, multiple tools are being used to explore their “single-molecule responses” to force. Optical tweezers and atomic force microscopy offer exquisite force and extension resolution, but cannot reach the high loading rates expected for high frequency auditory stimuli. Molecular dynamics (MD) simulations can reach these fast time scales, and also provide a unique view of the molecular events underlying protein mechanics, but its predictionsmore » must be experimentally verified. Thus a combination of simulations and experiments might be appropriate to study the molecular mechanics of hearing. Here I review the basics of MD simulations and the different methods used to apply force and study protein mechanics in silico. Simulations of tip link proteins are used to illustrate the advantages and limitations of this method.« less

Deciphering the Minimal Algorithm for Development and Information-genesis

NASA Astrophysics Data System (ADS)

Li, Zhiyuan; Tang, Chao; Li, Hao

During development, cells with identical genomes acquires different fates in a highly organized manner. In order to decipher the principles underlining development, we used C.elegans as the model organism. Based on a large set of microscopy imaging, we first constructed a ``standard worm'' in silico: from the single zygotic cell to about 500 cell stage, the lineage, position, cell-cell contact and gene expression dynamics are quantified for each cell in order to investigate principles underlining these intensive data. Next, we reverse-engineered the possible gene-gene/cell-cell interaction rules that are capable of running a dynamic model recapitulating the early fate decisions during C.elegans development. we further formulized the C.elegans embryogenesis in the language of information genesis. Analysis towards data and model uncovered the global landscape of development in the cell fate space, suggested possible gene regulatory architectures and cell signaling processes, revealed diversity and robustness as the essential trade-offs in development, and demonstrated general strategies in building multicellular organisms.

Analysis of Protein Kinetics Using Fluorescence Recovery After Photobleaching (FRAP).

PubMed

Giakoumakis, Nickolaos Nikiforos; Rapsomaniki, Maria Anna; Lygerou, Zoi

2017-01-01

Fluorescence recovery after photobleaching (FRAP) is a cutting-edge live-cell functional imaging technique that enables the exploration of protein dynamics in individual cells and thus permits the elucidation of protein mobility, function, and interactions at a single-cell level. During a typical FRAP experiment, fluorescent molecules in a defined region of interest within the cell are bleached by a short and powerful laser pulse, while the recovery of the fluorescence in the region is monitored over time by time-lapse microscopy. FRAP experimental setup and image acquisition involve a number of steps that need to be carefully executed to avoid technical artifacts. Equally important is the subsequent computational analysis of FRAP raw data, to derive quantitative information on protein diffusion and binding parameters. Here we present an integrated in vivo and in silico protocol for the analysis of protein kinetics using FRAP. We focus on the most commonly encountered challenges and technical or computational pitfalls and their troubleshooting so that valid and robust insight into protein dynamics within living cells is gained.

Fusion, fission, and transport control asymmetric inheritance of mitochondria and protein aggregates

PubMed Central

Böckler, Stefan; Chelius, Xenia; Hock, Nadine; Weiss, Matthias

2017-01-01

Partitioning of cell organelles and cytoplasmic components determines the fate of daughter cells upon asymmetric division. We studied the role of mitochondria in this process using budding yeast as a model. Anterograde mitochondrial transport is mediated by the myosin motor, Myo2. A genetic screen revealed an unexpected interaction of MYO2 and genes required for mitochondrial fusion. Genetic analyses, live-cell microscopy, and simulations in silico showed that fused mitochondria become critical for inheritance and transport across the bud neck in myo2 mutants. Similarly, fused mitochondria are essential for retention in the mother when bud-directed transport is enforced. Inheritance of a less than critical mitochondrial quantity causes a severe decline of replicative life span of daughter cells. Myo2-dependent mitochondrial distribution also is critical for the capture of heat stress–induced cytosolic protein aggregates and their retention in the mother cell. Together, these data suggest that coordination of mitochondrial transport, fusion, and fission is critical for asymmetric division and rejuvenation of daughter cells. PMID:28615194