scholarly journals In Silico Predictions of Endocrine Disruptors Properties

Endocrinology ◽  
2019 ◽  
Vol 160 (11) ◽  
pp. 2709-2716 ◽  
Author(s):  
Melanie Schneider ◽  
Jean-Luc Pons ◽  
Gilles Labesse ◽  
William Bourguet
Keyword(s):  
Biological Activity ◽  
Endocrine Disruptors ◽  
In Silico ◽  
Chemical Structure ◽  
Structural Information ◽  
Broad Class ◽  
Computer Assisted ◽  
Screening Methods

Abstract Endocrine-disrupting chemicals (EDCs) are a broad class of molecules present in our environment that are suspected to cause adverse effects in the endocrine system by interfering with the synthesis, transport, degradation, or action of endogenous ligands. The characterization of the harmful interaction between environmental compounds and their potential cellular targets and the development of robust in vivo, in vitro, and in silico screening methods are important for assessment of the toxic potential of large numbers of chemicals. In this context, computer-aided technologies that will allow for activity prediction of endocrine disruptors and environmental risk assessments are being developed. These technologies must be able to cope with diverse data and connect chemistry at the atomic level with the biological activity at the cellular, organ, and organism levels. Quantitative structure–activity relationship methods became popular for toxicity issues. They correlate the chemical structure of compounds with biological activity through a number of molecular descriptors (e.g., molecular weight and parameters to account for hydrophobicity, topology, or electronic properties). Chemical structure analysis is a first step; however, modeling intermolecular interactions and cellular behavior will also be essential. The increasing number of three-dimensional crystal structures of EDCs’ targets has provided a wealth of structural information that can be used to predict their interactions with EDCs using docking and scoring procedures. In the present review, we have described the various computer-assisted approaches that use ligands and targets properties to predict endocrine disruptor activities.

scholarly journals Computational Chemogenomics Drug Repositioning Strategy Enables the Discovery of Epirubicin as a New Repurposed Hit for Plasmodium falciparum and P. vivax

2020 ◽  
Vol 64 (9) ◽  
Author(s):  
Letícia Tiburcio Ferreira ◽  
Juliana Rodrigues ◽  
Gustavo Capatti Cassiano ◽  
Tatyana Almeida Tavella ◽  
Kaira Cristina Peralis Tomaz ◽  
...  
Keyword(s):  
Plasmodium Falciparum ◽  
In Silico ◽  
Antimalarial Activity ◽  
Drug Repositioning ◽  
Dna Gyrase ◽  
Plasmodium Yoelii ◽  
Computer Assisted ◽  
Content Type

ABSTRACT Widespread resistance against antimalarial drugs thwarts current efforts for controlling the disease and urges the discovery of new effective treatments. Drug repositioning is increasingly becoming an attractive strategy since it can reduce costs, risks, and time-to-market. Herein, we have used this strategy to identify novel antimalarial hits. We used a comparative in silico chemogenomics approach to select Plasmodium falciparum and Plasmodium vivax proteins as potential drug targets and analyzed them using a computer-assisted drug repositioning pipeline to identify approved drugs with potential antimalarial activity. Among the seven drugs identified as promising antimalarial candidates, the anthracycline epirubicin was selected for further experimental validation. Epirubicin was shown to be potent in vitro against sensitive and multidrug-resistant P. falciparum strains and P. vivax field isolates in the nanomolar range, as well as being effective against an in vivo murine model of Plasmodium yoelii. Transmission-blocking activity was observed for epirubicin in vitro and in vivo. Finally, using yeast-based haploinsufficiency chemical genomic profiling, we aimed to get insights into the mechanism of action of epirubicin. Beyond the target predicted in silico (a DNA gyrase in the apicoplast), functional assays suggested a GlcNac-1-P-transferase (GPT) enzyme as a potential target. Docking calculations predicted the binding mode of epirubicin with DNA gyrase and GPT proteins. Epirubicin is originally an antitumoral agent and presents associated toxicity. However, its antiplasmodial activity against not only P. falciparum but also P. vivax in different stages of the parasite life cycle supports the use of this drug as a scaffold for hit-to-lead optimization in malaria drug discovery.

scholarly journals In Silico Identification of an Aryl Hydrocarbon Receptor Antagonist with Biological Activity In Vitro and In Vivo

2014 ◽  
Vol 86 (5) ◽  
pp. 593-608 ◽  
Author(s):  
Ashley J. Parks ◽  
Michael P. Pollastri ◽  
Mark E. Hahn ◽  
Elizabeth A. Stanford ◽  
Olga Novikov ◽  
...  
Keyword(s):  
Biological Activity ◽  
Receptor Antagonist ◽  
Aryl Hydrocarbon Receptor ◽  
In Silico ◽  
Aryl Hydrocarbon ◽  
In Silico Identification ◽  
Aryl Hydrocarbon Receptor Antagonist

scholarly journals Flexibility and mobility of SARS-CoV-2-related protein structures

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rudolf A. Römer ◽  
Navodya S. Römer ◽  
A. Katrine Wallis
Keyword(s):  
In Silico ◽  
Drug Targets ◽  
Large Scale ◽  
Structural Information ◽  
Protein Structures ◽  
Antiviral Drug ◽  
Docking Studies ◽  
Related Protein

AbstractThe worldwide CoVid-19 pandemic has led to an unprecedented push across the whole of the scientific community to develop a potent antiviral drug and vaccine as soon as possible. Existing academic, governmental and industrial institutions and companies have engaged in large-scale screening of existing drugs, in vitro, in vivo and in silico. Here, we are using in silico modelling of possible SARS-CoV-2 drug targets, as deposited on the Protein Databank (PDB), and ascertain their dynamics, flexibility and rigidity. For example, for the SARS-CoV-2 spike protein—using its complete homo-trimer configuration with 2905 residues—our method identifies a large-scale opening and closing of the S1 subunit through movement of the S$${}^\text{B}$$ B domain. We compute the full structural information of this process, allowing for docking studies with possible drug structures. In a dedicated database, we present similarly detailed results for the further, nearly 300, thus far resolved SARS-CoV-2-related protein structures in the PDB.

scholarly journals Cnicin as an Anti-SARS-CoV-2: An Integrated In Silico and In Vitro Approach for the Rapid Identification of Potential COVID-19 Therapeutics

Antibiotics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 542
Author(s):  
Hani A. Alhadrami ◽  
Ahmed M. Sayed ◽  
Hossam M. Hassan ◽  
Khayrya A. Youssif ◽  
Yasser Gaber ◽  
...  
Keyword(s):  
Natural Products ◽  
In Silico ◽  
Structural Information ◽  
Chemical Constituents ◽  
Rapid Identification ◽  
Dependent Manner ◽  
Modeling Tools ◽  
Clinical Experiments

Since the emergence of the SARS-CoV-2 pandemic in 2019, it has remained a significant global threat, especially with the newly evolved variants. Despite the presence of different COVID-19 vaccines, the discovery of proper antiviral therapeutics is an urgent necessity. Nature is considered as a historical trove for drug discovery, especially in global crises. During our efforts to discover potential anti-SARS CoV-2 natural therapeutics, screening our in-house natural products and plant crude extracts library led to the identification of C. benedictus extract as a promising candidate. To find out the main chemical constituents responsible for the extract’s antiviral activity, we utilized recently reported SARS CoV-2 structural information in comprehensive in silico investigations (e.g., ensemble docking and physics-based molecular modeling). As a result, we constructed protein–protein and protein–compound interaction networks that suggest cnicin as the most promising anti-SARS CoV-2 hit that might inhibit viral multi-targets. The subsequent in vitro validation confirmed that cnicin could impede the viral replication of SARS CoV-2 in a dose-dependent manner, with an IC50 value of 1.18 µg/mL. Furthermore, drug-like property calculations strongly recommended cnicin for further in vivo and clinical experiments. The present investigation highlighted natural products as crucial and readily available sources for developing antiviral therapeutics. Additionally, it revealed the key contributions of bioinformatics and computer-aided modeling tools in accelerating the discovery rate of potential therapeutics, particularly in emergency times like the current COVID-19 pandemic.

scholarly journals Multiepitope Subunit Vaccine Design against COVID-19 Based on the Spike Protein of SARS-CoV-2: An In Silico Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Hamza Arshad Dar ◽  
Yasir Waheed ◽  
Muzammil Hasan Najmi ◽  
Saba Ismail ◽  
Helal F. Hetta ◽  
...  
Keyword(s):  
In Silico ◽  
Negative Impact ◽  
In Silico Analysis ◽  
Positive Association ◽  
Computer Assisted ◽  
Economic Activities ◽  
Structural Investigations ◽  
Health Crisis

The global health crisis caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of COVID-19, has resulted in a negative impact on human health and on social and economic activities worldwide. Researchers around the globe need to design and develop successful therapeutics as well as vaccines against the novel COVID-19 disease. In the present study, we conducted comprehensive computer-assisted analysis on the spike glycoprotein of SARS-CoV-2 in order to design a safe and potent multiepitope vaccine. In silico epitope prioritization shortlisted six HLA I epitopes and six B-cell-derived HLA II epitopes. These high-ranked epitopes were all connected to each other via flexible GPGPG linkers, and at the N-terminus side, the sequence of Cholera Toxin β subunit was attached via an EAAAK linker. Structural modeling of the vaccine was performed, and molecular docking analysis strongly suggested a positive association of a multiepitope vaccine with Toll-like Receptor 3. The structural investigations of the vaccine-TLR3 complex revealed the formation of fifteen interchain hydrogen bonds, thus validating its integrity and stability. Moreover, it was found that this interaction was thermodynamically feasible. In conclusion, our data supports the proposition that a multiepitope vaccine will provide protective immunity against COVID-19. However, further in vivo and in vitro experiments are needed to validate the immunogenicity and safety of the candidate vaccine.

scholarly journals Flexibility and mobility of SARS-CoV-2-related protein structures

2020 ◽  
Author(s):  
Rudolf A. Römer ◽  
Navodya S. Römer ◽  
A. Katrine Wallis
Keyword(s):  
In Silico ◽  
Drug Targets ◽  
Large Scale ◽  
Structural Information ◽  
Protein Structures ◽  
Antiviral Drug ◽  
Docking Studies ◽  
Related Protein

ABSTRACTThe worldwide CoVid-19 pandemic has led to an unprecedented push across the whole of the scientific community to develop a potent antiviral drug and vaccine as soon as possible. Existing academic, governmental and industrial institutions and companies have engaged in large-scale screening of existing drugs, in vitro, in vivo and in silico. Here, we are using in silico modelling of SARS-CoV-2 drug targets, i.e. SARS-CoV-2 protein structures as deposited on the Protein Databank (PDB). We study their flexibility, rigidity and mobility, an important first step in trying to ascertain their dynamics for further drug-related docking studies. We are using a recent protein flexibility modelling approach, combining protein structural rigidity with possible motion consistent with chemical bonds and sterics. For example, for the SARS-CoV-2 spike protein in the open configuration, our method identifies a possible further opening and closing of the S1 subunit through movement of SB domain. With full structural information of this process available, docking studies with possible drug structures are then possible in silico. In our study, we present full results for the more than 200 thus far published SARS-CoV-2-related protein structures in the PDB.

Effect of C6-Volatiles on Bioluminescent Plant Pathogens

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 557d-557
Author(s):  
Jennifer Warr ◽  
Fenny Dane ◽  
Bob Ebel
Keyword(s):  
Biological Activity ◽  
Bacterial Growth ◽  
Xanthomonas Campestris ◽  
Plant Pathogens ◽  
Genetically Engineered ◽  
The Other ◽  
Computer Assisted ◽  
Signal Molecules ◽  
Low Concentrations

C6 volatile compounds are known to be produced by the plant upon pathogen attack or other stress-related events. The biological activity of many of these substances is poorly understood, but some might produce signal molecules important in host–pathogen interactions. In this research we explored the possibility that lipid-derived C6 volatiles have a direct effect on bacterial plant pathogens. To this purpose we used a unique tool, a bacterium genetically engineered to bioluminesce. Light-producing genes from a fish-associated bacterium were introduced into Xanthomonas campestris pv. campestris, enabling nondestructive detection of bacteria in vitro and in the plant with special computer-assisted camera equipment. The effects of different C6 volatiles (trans-2 hexanal, trans-2 hexen-1-ol and cis-3 hexenol) on growth of bioluminescent Xanthomonas campestris were investigated. Different volatile concentrations were used. Treatment with trans-2 hexanal appeared bactericidal at low concentrations (1% and 10%), while treatments with the other volatiles were not inhibitive to bacterial growth. The implications of these results with respect to practical use of trans-2 hexanal in pathogen susceptible and resistant plants will be discussed.

Neurotoxicity of Pesticides: The Roadmap for the Cubic Mode of Action

2020 ◽  
Vol 27 (1) ◽  
pp. 54-77 ◽  
Author(s):  
Bogdan Bumbăcilă ◽  
Mihai V. Putz
Keyword(s):  
Biological Activity ◽  
Wiener Index ◽  
Laboratory Animals ◽  
Covalent Bonds ◽  
Organophosphate Compounds ◽  
Sar Studies ◽  
Structure Activity ◽  
Cubic Structure

Pesticides are used today on a planetary-wide scale. The rising need for substances with this biological activity due to an increasing consumption of agricultural and animal products and to the development of urban areas makes the chemical industry to constantly investigate new molecules or to improve the physicochemical characteristics, increase the biological activities and improve the toxicity profiles of the already known ones. Molecular databases are increasingly accessible for in vitro and in vivo bioavailability studies. In this context, structure-activity studies, by their in silico - in cerebro methods, are used to precede in vitro and in vivo studies in plants and experimental animals because they can indicate trends by statistical methods or biological activity models expressed as mathematical equations or graphical correlations, so a direction of study can be developed or another can be abandoned, saving financial resources, time and laboratory animals. Following this line of research the present paper reviews the Structure-Activity Relationship (SAR) studies and proposes a correlation between a topological connectivity index and the biological activity or toxicity made as a result of a study performed on 11 molecules of organophosphate compounds, randomly chosen, with a basic structure including a Phosphorus atom double bounded to an Oxygen atom or to a Sulfur one and having three other simple covalent bonds with two alkoxy (-methoxy or -ethoxy) groups and to another functional group different from the alkoxy groups. The molecules were packed on a cubic structure consisting of three adjacent cubes, respecting a principle of topological efficiency, that of occupying a minimal space in that cubic structure, a method that was called the Clef Method. The central topological index selected for correlation was the Wiener index, since it was possible this way to discuss different adjacencies between the nodes in the graphs corresponding to the organophosphate compounds molecules packed on the cubic structure; accordingly, "three dimensional" variants of these connectivity indices could be considered and further used for studying the qualitative-quantitative relationships for the specific molecule-enzyme interaction complexes, including correlation between the Wiener weights (nodal specific contributions to the total Wiener index of the molecular graph) and the biochemical reactivity of some of the atoms. Finally, when passing from SAR to Q(uantitative)-SAR studies, especially by the present advanced method of the cubic molecule (Clef Method) and its good assessment of the (neuro)toxicity of the studied molecules and of their inhibitory effect on the target enzyme - acetylcholinesterase, it can be seen that a predictability of the toxicity and activity of different analogue compounds can be ensured, facilitating the in vivo experiments or improving the usage of pesticides.

Recent In Vitro and In Silico Advances in the Understanding of Intranasal Drug Delivery

2020 ◽  
Vol 26 ◽  
Author(s):  
John Chen ◽  
Andrew Martin ◽  
Warren H. Finlay
Keyword(s):  
Drug Delivery ◽  
In Silico ◽  
Local Drug Delivery ◽  
In Vivo Studies ◽  
Intranasal Drug Delivery ◽  
Nasal Sprays ◽  
In Silico Studies ◽  
Drug Delivery Devices

Background: Many drugs are delivered intranasally for local or systemic effect, typically in the form of droplets or aerosols. Because of the high cost of in vivo studies, drug developers and researchers often turn to in vitro or in silico testing when first evaluating the behavior and properties of intranasal drug delivery devices and formulations. Recent advances in manufacturing and computer technologies have allowed for increasingly realistic and sophisticated in vitro and in silico reconstructions of the human nasal airways. Objective: To perform a summary of advances in understanding of intranasal drug delivery based on recent in vitro and in silico studies. Conclusion: The turbinates are a common target for local drug delivery applications, and while nasal sprays are able to reach this region, there is currently no broad consensus across the in vitro and in silico literature concerning optimal parameters for device design, formulation properties and patient technique which would maximize turbinate deposition. Nebulizers are able to more easily target the turbinates, but come with the disadvantage of significant lung deposition. Targeting of the olfactory region of the nasal cavity has been explored for potential treatment of central nervous system conditions. Conventional intranasal devices, such as nasal sprays and nebulizers, deliver very little dose to the olfactory region. Recent progress in our understanding of intranasal delivery will be useful in the development of the next generation of intranasal drug delivery devices.

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