Cheminformatics and Computational Chemical Biology

Biography:

Roberto Todeschini is a Full Professor of Chemometrics at the Department of Earth and Environmental Sciences of the University of Milano-Bicocca (Milano, Italy), where he constituted the Milano Chemometrics and QSAR Research Group. His main research activities concern chemo-metrics in all its aspects, QSAR, molecular descriptors, multi-criteria decision making and software development. He was the President of the International Academy of Mathematical Chemistry from 2008 to 2014 and is author of more than 180 publications in international journals and his last book is “Molecular Descriptors for Chemo-informatics” R. Todeschini and V. Consonni; Wiley-VCH, 2009.

Abstract:

Two novel classification methods, called N3 (N-Nearest Neighbors) and BNN (Binned Nearest Neighbors), are proposed. Both methods are inspired to the principles of the K-Nearest Neighbors (KNN) method, both based on object pair-wise similarities. Their performance was evaluated in comparison with eight well-known classification methods. In order to obtain reliable statistics, several comparisons were performed using 32 different literature data sets, which differ for number of objects, variables and classes. Results highlighted that N3 on average behaves as the most efficient classification method with similar performance to support vector machine based on radial basis function kernel (SVM/RBF). The method BNN showed on average slightly higher performance than the classical K-Nearest Neighbors method.

Biography:

Deqiang Dou has completed his PhD in 2000 from Shenyang Pharmaceutical University and postdoctoral studies from The State University of NewJersey, School of Medicine. He is the director of Department of Chinese Medicine Chemistry, Liaoning University of Traditional Chinese Medicine. He has published more than 200 papers in reputed journals and has been serving as an committee board member of World Federation of Chinese Medicine Societies etc..

Abstract:

Injection with natural compounds is an important method in the application of natural medicine, but its adverse drug reactions (ADRs) occur frequently, particularly the anaphylactoid reaction, which accounts for more than 77% of all reactions and has become a serious threat to public health. Here, the Xuesaitong injection (XSTI) was employed as an example to elucidate its anaphylactoid mechanism and look for potential biomarkers to assay the anaphylactoid reaction of herbal medicine injection by proteomics (iTRAQ method) and metabolomics. Proteins identification was performed using Mascot search engine against Uniprot database and 13 differential proteins were selected to further study, thus, Gpx1, Sc5b9 (C4d and Bb), F12, Kng1 and IgE which could be used as candidate biomarkers for the indication of direct stimulation, complement (classical and alternative), coagulation, kallikrein-kinin, and integrated pathways respectively were approved by ELISA method. And 28 differential metabolites were identified by METLIN, KEGG database, which were further approved by reference standards. Moreover, for a more detailed pathway analysis, the integrated pathway enrichment was analyzed using MetaboAnalyst 3.0, indicating XSTI-induced anaphylactoid reaction occurs via direct stimulation, complement and the kallikrein-kinin pathway and the effect substances include histamine, LTB4, uric acid and other metabolites are confirmed to be involved in arginine and proline metabolism, histidine metabolism, arachidonic acid metabolism, purine metabolism and the TCA cycle. Furthermore, separation experiments have indicated that 10-kDa molecules of XSTI are the main allergenic factor inducing an anaphylactoid reaction.

Biography:

Cristiano Garino joined the group of Food Chemistry in the Department of Drug Sciences of the University of Piemonte Orientale in 2005, and completed his PhD in Pharmaceutical and Food Biotechnologies in 2009. As postdoc, his main responsibilities are laboratory research and training of undergraduate students. Activities relates to the food molecular biology field (protein, RNA and DNA isolation, PCR and qPCR, production of recombinant proteins). Research Projects pointed towards the detection and characterization of hidden allergens and/or contaminants in foods, and to the protection of local food products through the setting up of molecular methods for the traceability/authenticity.

Abstract:

Non-specific lipid transfer proteins (nsLTPs) are common allergens particularly widespread within the plant kingdom. They have a highly conserved three-dimensional structure that generate a strong cross-reactivity. In the last years, several web tools for the prediction of allergenicity of new molecules based on their homology with known allergens have been released. The allergenicity of 28 amino acid sequences of nsLTPs homologues was predicted using seven publicly available web tools. Moreover, to evaluate their potential cross-reactivity, their similarity degree to their closest known LTP allergens was calculated. Finally, all sequences were studied for their identity degree with the prototype peach allergen Pru p 3. Most of the analysed sequences displayed a high probability to be allergenic according to all the software employed. The analysed LTPs from bell pepper, cassava, mango, mungbean and soybean showed high homology (>70%) with some known allergenic nsLTPs, revealing a potential risk of cross-reactivity for sensitized individuals. Other analysed amino acid sequences displayed a high degree of identity with Pru p 3 within the consensus sequence responsible for the formation, at three-dimensional level, of its major conformational epitope. Recent studies highlighted how in patients mono-sensitized to peach LTP the levels of IgE seem directly proportional to the chance of developing cross-reactivity to other nsLTPs, and these chances increase the more similar the protein is to Pru p 3. These proteins should be taken into special account for future studies aimed at evaluating the risk of cross-allergenicity in highly sensitized individuals.

Biography:

Abstract:

Although all-oral direct-acting antiviral (DAA) therapy for hepatitis C virus (HCV) treatment is now a reality, today’s HCV drugs are expensive, and more affordable drugs are still urgently needed. In this work, we report the identification of the 2-phenyl-4,5,6,7-tetrahydro-1H-indole fragments that inhibits cellular replication of HCV genotype 1b and 2a subgenomic replicons.. The most potent fragment displayed EC50 values of 7.9 and 2.6 µM in genotype 1b and 2a, respectively. Biochemical assays showed that this fragment (39) had no effect on HCV NS5B polymerase, NS3 helicase, IRES mediated translation and selected host factors.

Biography:

Jin Ouyang received her PhD degree from Ghent University, Belgium. She is the professor of analytical chemistry in College of Chemistry, Beijing Normal University, China. She is now working on the development of analytical methods to biological and pharmaceutical samples study and published over 90 papers in SCI journals.

Abstract:

Mass spectrometry (MS) provides a powerful method for high throughput screening (HTS) small molecular drugs because its high speed, sensitivity and property of label free. However, there were some limits for traditional MS methods in the application of high-throughput screening. Herein, we developed a simple interface which coupled droplet segmented system to a venturi easy ambient sonic-spray ionization mass spectrometry (V-EASI-MS). It is fabricated by using a single capillary to act as both sampling probe and the emitter, which simplifies the construction, reduces the cost and shorten the sampling time. Samples sucked by venturi effect are segmented to nanoliter plugs by air, then the plugs can be detected by MS directly. The new system has been applied to screen angiotensin converting enzyme inhibitors successfully. A house-made desorption electrospray ionization mass spectrometry (DESI-MS) is also established for high-throughput screening system. In addition, we have also synthesized new aggregation induced emission (AIE) compounds to apply as new matrics in the analysis of small molecules by MALDI-TOF-MS as well. The sensitivity of the AIE matrix is high because they decreased the generation of matrix interference.

Biography:

Faheem Shehzad BALOCH has completed his PhD from Çukurova University, Adana, Turkey under combined fellowship program of Cultural Exchange Scholarship Scheme for PhD studies and Doctoral fellowship of TUBİTAK, Turkey. He is working as Assistant Professor at Abant İzzet Baysal University, Bolu, Turkey. His areas of research are genetic diversity and characterization, QTL mapping, Genoe wide association mapping of trait of interest using DNA molecular markers. I have more than 30 publication international peer reviewed journal and participated in several national and international conferences of repute. He took training and attended many advance course use of molecular markers in plant sciences at many European and American Universities. He also serves as an Editorial Board Member in some journals. He has several projects on molecular characterization of natural landraces collected from their area of origin, diversity and domestication, mapping QTL for trait of economic importance and many more.

Abstract:

The Fertile Crescent, particularly southeastern Turkey, is thought to be the primary center of wheat domestication and diversity. In spite of the importance of the genetic diversity from this area, a severe lack of information on the genetic structure of the durum wheat gene pool from this region is evident. For example, thus far, no efforts have been made to understand the genetic structure of the Anatolian durum wheat gene pool, despite its importance in durum wheat breeding. Limited studies have been conducted using genetic resources from Turkey and Syria. However, the landraces evaluated so far represent only a small subset of available resources; furthermore, they come from few geographic regions and do not allow the study of the genetic structure of durum wheat landraces in Turkey and Syria. Diversity Arrays Technology (DArTseq) and SNP marker systems were applied to durum wheat from Central Fertile Crescent countries. We focused on 91 accessions covering the whole geographical regions of Turkey and Syria collected by ICARDA to examine the pattern of variation and to check whether or not diversity in durum wheat is associated with geographical coordinates. Diversity Arrays Technology (DArT) is based on genotyping by sequencing technology and is a sequence-independent genotyping method that generates genome-wide genetic fingerprints. Here we used 61K DArTseq markers and 26K SNP to check the phylogenetic relationship and assess the genetic diversity in durum wheat landraces from Central Fertile crescent. It was evident that durum wheat landraces from the same geographical region were often placed in different groups in both neighbor joining analysis and principal component analysis indicating that grouping based on genetic parameters was not closely related to the geographical origin. The population structure was determined by using STRUCTURE software and five populations K=5 were identified among landrace through both marker systems. There was high diversity in durum wheat landraces and we also tested the association of geographical coordinated with both SNP and DArTseq distances and observed that genetic distance is not correlated with geographical coordinates. The wide diversity present in Turkish and Syrian durum wheat landraces could be used as genetic resource in designing breeding program for developing new cultivars adapted to different geographic and climatic conditions, and may also contribute to worldwide breeding programs. We are now using this genotypic data for genome wide association mapping for different traits of interest in durum wheat.

Biography:

Abstract:

Several tools for design of metal ion binders in water were realized to apply the consensus QSPR models based on sub-structural molecular fragments (SMF) as descriptors: property predictor, generator of virtual combinatorial libraries and interactive designer of compounds. The developed consensus models (CM) for predicting stability constants (log K) of the metal ion –organic ligand complexation are integrated in Forecast by Molecular Fragments (FMF) predictor. Ligands can be submitted as an SD file. The predicted log K are evaluated as an arithmetic mean of values obtained by numerous individual Multiple Linear Regression models excluding those leading to outlying values and being outside applicability domain (AD) of individual models. Three types of AD definitions can be used simultaneously or separately: bounding box, fragment control and ‘‘quorum control’’. Outlying predictions of some individual models are excluded from the CM by Thompson’s rule. Chemical editor Ed-ChemS includes a generator of virtual combinatorial libraries named Combi-Lib. various libraries are generated by attaching substituent to molecular scaffolds. Then the log K values for generated compounds are estimated by the FMF predictor. An interactive designer of organic compounds is realized by interaction of the chemical editor EdChemS with the FMF predictor using coloring of atoms of chemical formula according the SMF contributions. If molecular structure is edited on the screen by EdChemS, the FMF predicts the property interactively using loaded CM. Atoms of molecular formula are colored according to the SMF contributions of CM. Color depth of atom is double sum, where first sum includes contributions of molecular fragments containing given atom, and second sum includes all individual models of CM. The fragments and their contributions are convenient tools for the rationale design of the ligands with desirable thermodynamic stability of their complexes: the data manager EdiSDF estimates mean-fragment contributions according to a set of individual models in CM. The tools use the developed QSPR models for the stability constants log-K of the 1:1 (M: L) complexes of metal ions (M) with different classes of organic ligands (L) in aqueous solution at 298 K and an ionic strength 0.1 M. The CM were prepared by the ISIDA/QSPR program for 42 metal ions: Li+, Na+, K+, Be2+, Mg2+, Ca2+, Sr2+, Ba2+, Al3+, Ga3+, In3+, Pb2+, Y3+, La3+, VO2+, Mn2+, Fe2+, Fe3+,Co2+, Ni2+, Cu2+,Ag+, Zn2+, Cd2+, Hg2+, Ce3+, Pr3+, Nd3+, Sm3+, Eu3+,Gd3+, Tb3+, Dy3+, Ho3+, Er3+, Tm3+, Yb3+, Lu3+, Th4+, UO22+, NpO2+ and Am3+. Studied ligands are molecules of various organic classes and data sets from 883 (Cu2+) to 28 (Am3+) organic ligands. The models have reasonable prediction performance: root-mean squared error in external 5-fold cross-validations varies from 0.49 (Li+) to 2.30 (In3+) (the log K units) which is close to observed experimental systematic errors.

Biography:

Elisa Fasoli has completed her PhD in Neuroscience at the age of 28 years from Verona University and postdoctoral studies from Politecnico di Milano, Department of Chemistry, Materials and Chemical Engineering. She is Associate Professor, directing Proteomic laboratory focused on protein analysis through electrophoresis (SDS-PAGE and 2D-electrophoresis) and protein identification through mass spectrometry. Elisa Fasoli is co‐author of 40 original peer‐reviewed ISI papers (Hindex = 17), collecting more than 700 citations (source Web of Science). She has presented her scientific results in oral (9) and poster communications (more than 25) at national and international meetings.

Abstract:

Panax ginseng is a well-known Asian traditional herbal medicine, belonging to the genus Panax of the family Araliaceae, traditionally considered as a panacea, capable of treating all kinds of diseases. The present study aims at characterizing the Panax ginseng proteome in order to correlate protein properties with protective functions attributed to root by traditional oriental medicine. The Panax ginseng proteins were extracted from root powder and captured by using the combinatorial peptide ligand library technology. After SDS-PAGE separation, proteins were identified by nLC-MS/MS, by using an Orbitrap mass spectrometer, in order to extensively map the proteome for a consequent exploration of protein functions via Gene Ontology analysis. Moreover, also an interactomic map was built up by exploiting the STRING v.9.1 software, set on Arabidopsis Thaliana as organism database and a final peptidome analysis was performed by an in-silico human gastrointestinal digestion (Software ProteinProspector v 5.14.0, MS-Digest program set on UniProtKB Database). The proteomic fingerprinting of Panax gingseng yielded 209 unique gene products, searched in Uniprot_Arabidopsis Thaliana and Uniprot_Panax, with a prevalence of structural proteins and species connected with metabolic functions. The protein-protein interaction network was formed by 196 nodes and 1554 interactions and from all generated peptides (660), 6 have demonstrated a potential antimicrobial action. The present study has contributed not only to map the Panax ginseng proteome and its peptidome, but also to correlate proteomic data with biological functions in order to understand the medical properties that have made so popular this root in traditional oriental medicine.

Biography:

Rhazi Naima is a PhD Student and has co-supervised thesis between the University of Pau et des Pays d’Adour (France) and University Hassan II (Morocco). Her subject in PhD entitled “Elaboration of ecological adhesives and bio-composites from Moroccan Acacia mollissima Barks”. She has a specialized Master degree in Quality Control of Food, Pharmaceutical and Cosmetics Industries and has training in Integrated Management System: Health, Quality, Safety and Environment in food alimentary and plastics center. She has given 5 oral presentations, 2 posters in international workshops and conferences and also published 2 papers in reputed journals: Industrial Crops and Products and Arabian Journal of Chemistry.

Abstract:

In order to increase the yield extraction of condensed tannins, to preserve the quality and the reactivity of phenolic compounds extracted and also to find new environmentally-friendly extraction conditions a response surface methodology (RSM) was used. This methodology was an effective and powerful statistical method to optimize extraction process while giving a maximum of information, reducing number of experimental trials required and giving the best precision of the results calculated with the established model. The development of the experimental design was described by Rhazi et al., (2015 a). RSM was used to identify the significant factors to improve yield extraction, to reduce solvent proportion and time extraction. It permit to model extraction conditions and also to determine optimal conditions, which give higher yield of condensed tannins using lower proprtion of solvent and shorter time extraction. The present study aims to develop green extraction process of phenolic compounds extracted from Moroccan barks of Acacia mollissima using a traditional maceration. The parameters studies in this research are time extraction (X1), methanol proportion (X2) and bark ages (X3). The result of RSM showed a good agreement between the predicted and experimental values (R2= 0.98; 0.97 and 0.99 respectively for the extracts).

Biography:

Ahmed Haroun has completed his PhD from University of Tokyo in Mechanical Engineering. He is currently a Post-doctoral research fellow at National University of Singapore (NUS) and holding the position of Lecturer Assistant at Cairo University. His research interests include energy harvesting for implantable and wearable devices; MEMS-based energy harvesting; MEMS sensors and actuators, Implantable bio-MEMS; Vibration energy harvesting and Dynamics of multi-body systems.

Abstract:

Self-powering of wireless sensors and wireless micro devices attract the attention of many researches nowadays. Problems associated with chemical batteries such as limited life time and minimization restrictions can be solved using the approach of energy harvesting. Various ambient energy sources such as vibration, thermal, light, wind, etc. could be harvested and converted into electrical energy. However, vibration energy harvesting is more convenient for important kinds of applications such as machine condition monitoring, where sensors are placed in a deep dark place and human body-powered devices whether they are wearable or implantable. Some problems arise when dealing with human motion energy harvesting. Human body provides a kind of unsteady low frequency vibrations which are difficult to match by most common resonant harvesters. Instead, a way of non-resonant low frequency energy harvesting should be used. In this speech, a micro electromagnetic non-resonant energy harvester based on free/impact motion will be presented. Free relative motion is allowed between tube-carrying an electrical coil directly connected to the vibration source and a permanent magnet inside. Impacts appear between the magnet and two hard end stops. Free motion enhances power harvesting at low frequency, while combined free/impact motion results in a non-resonant behavior in which the output power increases with input amplitude and/or frequency. In addition, the harvester has a simple construction which allows fabrication with small sizes. Hence, the harvester can be well suited for small size applications encountered variable large amplitude – low frequency vibrations such as human powered devices.

Biography:

Elyette Martin is a computational chemistry scientist at Philip Morris R&D in the cheminformatics team. She received her PhD in Molecular Biology from the Strasbourg University (France) before working at the Institut de Recherche Servier, a French pharma company, in a postdoctoral position. At Philip Morris she manages the corporate chemical and spectral database and cheminformatics development (properties calculation, development of QSAR models…).

Abstract:

In order to assess and evaluate the toxicity of new products in a wide range of industrial settings (e.g., food and beverage, cosmeceutical industries), it is important to understand their chemical composition. Non-targeted screening of small molecules in complex matrices can be performed using various analytical techniques such as gas chromatography coupled to mass spectrometry. However, compound identification using a conventional mass spectral library search, e.g., NIST MSSearch, generally does not provide sufficient confidence regarding the proposed structures. The application of cheminformatics provides analytical chemists with tools to increase the accuracy for identifying compound structures, and to accelerate and standardize the identification process. QSPR (Quantitative Structure Property Relationship) models predict retention times and/or indices for all constituents potentially present in the complex matrix. These predicted retention times/indices enhance the level of confidence in the correct assignment of mass spectra to the right compounds. This poster presents QSPR models, which have been developed using different methodologies/algorithms and software tools, including ChromGenius (ACDLabs), RapidMiner, Dragon, and Pipeline Pilot. It describes the improvement afforded by such tools for elucidating the chemical composition of Reduced-Risk Products developed by Philip Morris.

Biography:

Rhazi Naima is a PhD Student and has co-supervised thesis between the University of Pau et des Pays d’Adour (France) and University Hassan II (Morocco). Her subject in PhD entitled “Elaboration of ecological adhesives and bio-composites from Moroccan Acacia mollissima Barks”. She has a specialized Master degree in Quality Control of Food, Pharmaceutical and Cosmetics Industries and has training in Integrated Management System: Health, Quality, Safety and Environment in food alimentary and plastics center. She has given 5 oral presentations, 2 posters in international workshops and conferences and also published 2 papers in reputed journals: Industrial Crops and Products and Arabian Journal of Chemistry.

Abstract:

In order to increase the yield extraction of condensed tannins, to preserve the quality and the reactivity of phenolic compounds extracted and also to find new environmentally-friendly extraction conditions a response surface methodology (RSM) was used. This methodology was an effective and powerful statistical method to optimize extraction process while giving a maximum of information, reducing number of experimental trials required and giving the best precision of the results calculated with the established model. The development of the experimental design was described by Rhazi et al., (2015 a). RSM was used to identify the significant factors to improve yield extraction, to reduce solvent proportion and time extraction. It permit to model extraction conditions and also to determine optimal conditions, which give higher yield of condensed tannins using lower proprtion of solvent and shorter time extraction. The present study aims to develop green extraction process of phenolic compounds extracted from Moroccan barks of Acacia mollissima using a traditional maceration. The parameters studies in this research are time extraction (X1), methanol proportion (X2) and bark ages (X3). The result of RSM showed a good agreement between the predicted and experimental values (R2= 0.98; 0.97 and 0.99 respectively for the extracts).