Articles 2017
Ethanolic extracts of Inula viscosa, Salix alba and Quercus calliprinos, negatively affect the development of the entomopathogenic nematode, Heterorhabditis bacteriophora – A model to compare gastro-intestinal nematodes developmental effect.
Santhi VS, Salame L, Dvash L, Muklada H, Azaizeh H, Mreny R, Awwad S, Markovics A, Landau SY, Glazer I
Journal of Invertebrate Pathology, Volume 145, May 2017, Pages 39-44. DOI: 10.1016/j.jip.2017.03.005
Abstract:
Heterorhabditis bacteriophora can represent a model system for herbal medication against gastro-intestinal strongylid parasites in determining the recovery and development due to their unique parasitic infectious cycle. The fact that plant extracts impair nematode development is known but their differential impact on stages of the life cycle of H. bacteriophora has never been investigated. We examined the developmental stages resumed from eggs, young juveniles (J1-3), infective juveniles (IJs), young and adult hermaphrodites of H. bacteriophora upon exposure to crude ethanolic extracts of Inula viscosa, Salix alba, and Quercus calliprinos at concentrations of 600, 1200, and 2400ppm. Our results showed that plant extracts were highly toxic to the survival of the eggs and young juveniles J1 to J3 at all concentrations. The plant extracts inhibited their development and were associated with low reproduction parameters (i.e. fecundity and viability of eggs). The IJs, J4, young and developed hermaphrodites displayed concentration-dependent negative effect on development with less egg count, poor vulval muscle development, loss of egg laying capacity and progeny development by matricidal hatching. Plant extract of I. viscosa at low (600ppm) concentration did not impair vulval development. These results suggest that these plant extracts show potential for the control of parasitic rhabditids.
Production of biochar from olive mill solid waste for heavy metal removal
Samya O.Abde lhadi, Carlos G.Dosoretz, Giora Rytwo, Yoram Gerchman, Hassan Azaizeh.
Journal of Bioresource Technology, Volume 244, Part 1, November 2017, Pages 759-76
https://doi.org/10.1016/j.biortech.2017.08.013
Abstract:
Commercial activated carbon (CAC) and biochar are useful adsorbents for removing heavy metals (HM) from water, but their production is costly. Biochar production from olive solid waste from two olive cultivars (Picual and Souri) and two oil production process (two- or three-phase) and two temperatures (350 and 450 °C) was tested. The biochar yield was 24–35% of the biomass, with a surface area of 1.65–8.12 m2 g−1, as compared to 1100 m2 g−1 for CAC. Picual residue from the two-phase milling technique, pyrolysed at 350 °C, had the best cumulative removal capacity for Cu+2, Pb+2, Cd+2, Ni+2 and Zn+2 with more than 85% compared to other biochar types and CAC. These results suggest that surface area cannot be used as a sole predictor of HM removal capacity. FTIR analysis revealed the presence of different functional groups in the different biochar types, which may be related to the differences in absorbing capacities.
Nature is the best source of anti-inflammatory drugs: indexing natural products for their anti-inflammatory bioactivity.
Aswad M, Rayan M, Abu-Lafi S, Falah M, Raiyn J, Abdallah Z, Rayan A.
Journal of Materials science citations 2011-2016. January 2018, Volume 67, Issue 1, pp 67–75| Cite as. Inflamm Res. 2018 Jan;67(1):67-75. doi: 10.1007/s00011-017-1096-5. Epub 2017 Sep 27.
Abstract:
OBJECTIVES:
The aim was to index natural products for less expensive preventive or curative anti-inflammatory therapeutic drugs.
MATERIALS:
A set of 441 anti-inflammatory drugs representing the active domain and 2892 natural products representing the inactive domain was used to construct a predictive model for bioactivity-indexing purposes.
METHOD:
The model for indexing the natural products for potential anti-inflammatory activity was constructed using the iterative stochastic elimination algorithm (ISE). ISE is capable of differentiating between active and inactive anti-inflammatory molecules.
RESULTS:
By applying the prediction model to a mix set of (active/inactive) substances, we managed to capture 38% of the anti-inflammatory drugs in the top 1% of the screened set of chemicals, yielding enrichment factor of 38. Ten natural products that scored highly as potential anti-inflammatory drug candidates are disclosed. Searching the PubMed revealed that only three molecules (Moupinamide, Capsaicin, and Hypaphorine) out of the ten were tested and reported as anti-inflammatory. The other seven phytochemicals await evaluation for their anti-inflammatory activity in wet lab.
CONCLUSION:
The proposed anti-inflammatory model can be utilized for the virtual screening of large chemical databases and for indexing natural products for potential anti-inflammatory activity.
Indexing Natural Products for Their Potential Anti-Diabetic Activity: Filtering and Mapping Discriminative Physicochemical Properties.
Zeidan M, Rayan M, Zeidan N, Falah M, Rayan A.
US National Library of Medicine National Institutes of Health. Molecules. 2017 Sep 17;22(9). pii: E1563. doi: 10.3390/molecules22091563.
Abstract:
Diabetes mellitus (DM) poses a major health problem, for which there is an unmet need to develop novel drugs. The application of in silico techniques and optimization algorithms is instrumental to achieving this goal. A set of 97 approved anti-diabetic drugs, representing the active domain, and a set of 2892 natural products, representing the inactive domain, were used to construct predictive models and to index anti-diabetic bioactivity. Our recently-developed approach of ‘iterative stochastic elimination’ was utilized. This article describes a highly discriminative and robust model, with an area under the curve above 0.96. Using the indexing model and a mix ratio of 1:1000 (active/inactive), 65% of the anti-diabetic drugs in the sample were captured in the top 1% of the screened compounds, compared to 1% in the random model. Some of the natural products that scored highly as potential anti-diabetic drug candidates are disclosed. One of those natural products is caffeine, which is noted in the scientific literature as having the capability to decrease blood glucose levels. The other nine phytochemicals await evaluation in a wet lab for their anti-diabetic activity. The indexing model proposed herein is useful for the virtual screening of large chemical databases and for the construction of anti-diabetes focused libraries.
From medicinal plant extracts to defined chemical compounds targeting the histamine H4 receptor: Curcuma longa in the treatment of inflammation
Annika Frank, Saleh Abu-Lafi, Azmi Adawi, Johannes S. Schwed, Holger Stark, Anwar Rayan
Inflamm Res. 2017 Oct;66(10):923-929. doi: 10.1007/s00011-017-1075-x. Epub 2017 Jun 24.
Abstract:
Objectives
The aim was to evaluate the activity of seven medicinal, anti-inflammatory plants at the hH4R with focus on defined chemical compounds from Curcuma longa.
Materials
Activities were analyzed with membrane preparations from Sf9 cells, transiently expressing the hH4R, Gαi2 and Gβ1γ2 subunits.
Methods
From the methanolic extract of C. longa curcumin (1), demethoxycurcumin (2) and bis(4-hydroxy-cinnamoyl)methane (3) were isolated, purified with HPLC (elution-time 10.20, 9.66, 9.20 min, respectively) and together with six additional extracts, were characterized via radioligand binding studies at the hH4R.
Results
Compounds from C. longa were the most potent ligands at the hH4R. They exhibited estimated K ivalues of 4.26–6.26 µM (1.57–2.31 µg/mL) (1); 6.66––8.97 µM (2.26–3.04 µg/mL) (2) and 10.24–14.57 µM (3.16–4.49 µg/mL) (3) (95% CI). The estimated K i value of the crude extract of curcuma was 0.50–0.81 µg/mL. Fractionated curcumin and the crude extract surpassed the effect of pure curcumin with a K i value of 5.54 µM or 2.04 µg/mL [95% CI (4.47–6.86 µM), (1.65–2.53 µg/mL)].
Conclusion
Within this study, defined compounds of C. longa were recognized as potential ligands and reasonable lead structures at the hH4R. The mode of anti-inflammatory action of curcumin was further elucidated and the role of extracts in traditional phytomedicine was strengthened.
Inhibitory capacity of Rhus coriaria L. extract and its major component methyl gallate on Streptococcus mutans biofilm formation by optical profilometry: Potential applications for oral health.
Kacergius T, Abu-Lafi S, Kirkliauskiene A, Gabe V, Adawi A, Rayan M, Qutob M4, Stukas R, Utkus A, Zeidan M, Rayan A.
US National Library of Medicine National Institutes of Health. Mol Med Rep. 2017 Jul;16(1):949-956. doi: 10.3892/mmr.2017.6674. Epub 2017 Jun 1
Abstract:
Streptococcus mutans (S. mutans) bacterium is the most well recognized pathogen involved in pathogenesis of dental caries. Its virulence arises from its ability to produce a biofilm and acidogenicity, causing tooth decay. Discovery of natural products capable to inhibit biofilm formation is of high importance for developing health care products. To the best of our knowledge, in all previous scientific reports, a colorimetric assay was applied to test the effect of sumac and methyl gallate (MG) on S. mutans adherence. Quantitative assessment of the developed biofilm should be further performed by applying an optical profilometry assay, and by testing the effect on both surface roughness and thickness parameters of the biofilm. To the best of our knowledge, this is the first study to report the effect of sumac extract and its constituent MG on biofilm formation using an optical profilometry assay. Testing antibacterial activity of the sumac extract and its fractions revealed that MG is the most bioactive component against S. mutans bacteria. It reduced S. mutans biofilm biomass on the polystyrene surface by 68‑93%, whereas 1 mg/ml MG was able to decrease the biofilm roughness and thickness on the glass surface by 99%. MG also prevented a decrease in pH level by 97%. These bioactivities of MG occurred in a dose‑dependent manner and were significant vs. untreated bacteria. The findings are important for the development of novel pharmaceuticals and formulations of natural products and extracts that possess anti‑biofilm activities with primary applications for oral health, and in a broader context, for the treatment of various bacterial infections.
Homology-based Modeling of Rhodopsin-like Family Members in the Inactive State: Structural Analysis and Deduction of Tips for Modeling and Optimization.
Pappalardo M, Rayan M, Abu-Lafi S, Leonardi ME, Milardi D, Guccione S, Rayan A.
US National Library of Medicine National Institutes of Health. Mol Inform. 2017 Aug;36(8). doi: 10.1002/minf.201700014. Epub 2017 Apr 4.
Abstract:
Modeling G-Protein Coupled Receptors (GPCRs) is an emergent field of research, since utility of high-quality models in receptor structure-based strategies might facilitate the discovery of interesting drug candidates. The findings from a quantitative analysis of eighteen resolved structures of rhodopsin family “A” receptors crystallized with antagonists and 153 pairs of structures are described. A strategy termed endeca-amino acids fragmentation was used to analyze the structures models aiming to detect the relationship between sequence identity and Root Mean Square Deviation (RMSD) at each trans-membrane-domain. Moreover, we have applied the leave-one-out strategy to study the shiftiness likelihood of the helices. The type of correlation between sequence identity and RMSD was studied using the aforementioned set receptors as representatives of membrane proteins and 98 serine proteases with 4753 pairs of structures as representatives of globular proteins. Data analysis using fragmentation strategy revealed that there is some extent of correlation between sequence identity and global RMSD of 11AA width windows. However, spatial conservation is not always close to the endoplasmic side as was reported before. A comparative study with globular proteins shows that GPCRs have higher standard deviation and higher slope in the graph with correlation between sequence identity and RMSD. The extracted information disclosed in this paper could be incorporated in the modeling protocols while using technique for model optimization and refinement.
Delivery is key: lessons learnt from developing splice-switching antisense therapies
Caroline Godfrey, Lourdes R Desviat, Bård Smedsrød, France Piétri‐Rouxel, Michela A Denti, Petra Disterer, Stéphanie Lorain, Gisela Nogales‐Gadea, Valentina Sardone, Rayan Anwar, Samir EL Andaloussi, Taavi Lehto, Bernard Khoo, Camilla Brolin, Willeke MC van Roon‐Mom, Aurélie Goyenvalle, Annemieke Aartsma‐Rus, View ORCID ProfileVirginia Arechavala‐Gomeza
EMBO Molecular Medicine (2017) e201607199. DOI 10.15252/emmm.201607199 | Published online 13.03.2017
Abstract:
The use of splice‐switching antisense therapy is highly promising, with a wealth of pre‐clinical data and numerous clinical trials ongoing. Nevertheless, its potential to treat a variety of disorders has yet to be realized. The main obstacle impeding the clinical translation of this approach is the relatively poor delivery of antisense oligonucleotides to target tissues after systemic delivery. We are a group of researchers closely involved in the development of these therapies and would like to communicate our discussions concerning the validity of standard methodologies currently used in their pre‐clinical development, the gaps in current knowledge and the pertinent challenges facing the field. We therefore make recommendations in order to focus future research efforts and facilitate a wider application of therapeutic antisense oligonucleotides.
Avogadro Program for Chemistry Education: To What Extent can Molecular Visualization and Three-dimensional Simulations Enhance Meaningful Chemistry Learning?
Baraa Rayan, Anwar Rayan
World Journal of Chemical Education. 2017, 5(4), 136-141.
DOI: 10.12691/wjce-5-4-4
Abstract:
In developing this study, we hypothesized that the integration of computerized techniques and modeling tools into traditional face-to-face instruction can produce a better hybrid model of teaching, capable of motivating students and improving their attitude toward science in general, and toward chemistry in particular. We tested how molecular visualizations and three-dimensional simulations affect students’ conceptual understanding of chemistry and their attitudes toward learning chemistry. During the academic year 2016-2017, we incorporated Avogadro software into teaching and tested how it affected students’ performance on chemistry exams in their courses. The difference in average scores between the two groups (8.2 points for the experimental group and 6.4 points for the control group) was significant. Student feedback following the initiative was positive and encouraging. Most students indicated that learning chemistry with Avogadro was extremely helpful, bringing the microscopic world of molecules closer to them, and they felt that they would like to see such software integrated into their chemistry studies from day one. Other parameters will be tested in continuation of this study, such as students’ attitudes toward learning chemistry and their inquiry skills.
Nature is the best source of anticancer drugs: Indexing natural products for their anticancer bioactivity
Anwar Rayan, Jamal Raiyn, Mizied Falah
Published: November 9, 2017https://doi.org/10.1371/journal.pone.0187925
Abstract:
Cancer is considered one of the primary diseases that cause morbidity and mortality in millions of people worldwide and due to its prevalence, there is undoubtedly an unmet need to discover novel anticancer drugs. However, the traditional process of drug discovery and development is lengthy and expensive, so the application of in silico techniques and optimization algorithms in drug discovery projects can provide a solution, saving time and costs. A set of 617 approved anticancer drugs, constituting the active domain, and a set of 2,892 natural products, constituting the inactive domain, were employed to build predictive models and to index natural products for their anticancer bioactivity. Using the iterative stochastic elimination optimization technique, we obtained a highly discriminative and robust model, with an area under the curve of 0.95. Twelve natural products that scored highly as potential anticancer drug candidates are disclosed. Searching the scientific literature revealed that few of those molecules (Neoechinulin, Colchicine, and Piperolactam) have already been experimentally screened for their anticancer activity and found active. The other phytochemicals await evaluation for their anticancerous activity in wet lab.
