Search results for: molecular descriptors

Authors: Sidra Naeem, Ayesha Naeem, Sahar Rahim, Nadia Nawaz Qadri

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Citrus greening is a bacterial disease that causes considerable damage to citrus fruits worldwide. Efficient method for this disease detection must be carried out to minimize the production loss. This paper presents a pattern recognition system that comprises three stages for the detection of citrus greening from Orange leaves: segmentation, feature extraction and classification. Image segmentation is accomplished by adaptive thresholding. The feature extraction stage comprises of three visual descriptors i.e. shape, color and texture. From shape feature we have used asymmetry index, from color feature we have used histogram of Cb component from YCbCr domain and from texture feature we have used local binary pattern. Classification was done using support vector machines and k nearest neighbors. The best performances of the system is Accuracy = 88.02% and AUROC = 90.1% was achieved by automatic segmented images. Our experiments validate that: (1). Segmentation is an imperative preprocessing step for computer assisted diagnosis of citrus greening, and (2). The combination of shape, color and texture features form a complementary set towards the identification of citrus greening disease.

Keywords: citrus greening, pattern recognition, feature extraction, classification

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Authors: Prasanna Ramachandran, Kareem Graham, Helena Kiefel, Sunit Jain, Todd DeSantis

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Microbes that reside inside the mammalian GI tract, commonly referred to as the gut microbiome, have been shown to have therapeutic effects in animal models of disease. We hypothesize that specific proteins produced by these microbes are responsible for this activity and may be used directly as therapeutics. To speed up the discovery of these key proteins from the big-data metagenomics, we have applied machine learning techniques. Using amino acid sequences of known epitopes and their corresponding binding partners, protein interaction descriptors (PID) were calculated, making a positive interaction set. A negative interaction dataset was calculated using sequences of proteins known not to interact with these same binding partners. Using Random Forest and positive and negative PID, a machine learning model was trained and used to predict interacting versus non-interacting proteins. Furthermore, the continuous variable, cosine similarity in the interaction descriptors was used to rank bacterial therapeutic candidates. Laboratory binding assays were conducted to test the candidates for their potential as therapeutics. Results from binding assays reveal the accuracy of the machine learning prediction and are subsequently used to further improve the model.

Keywords: protein-interactions, machine-learning, metagenomics, microbiome

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Authors: Mohamed Ayoub

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We perform computational investigation using density functional theory, B3LYP with aug-cc-pVTZ basis set followed by natural bond orbital analysis (NBO), which provides best single “natural Lewis structure” (NLS) representation of chosen wavefunction (Ψ) with natural resonance theory (NRT) to provide an analysis of molecular electron density in terms of resonance structures (RS) and weights (w). We selected for the study a wide range of gas phase dimers (B…HA), with hydrogen bond dissociation energies (ΔEB…H) that span more than two orders of magnitude. We demonstrate that charge transfer from a donor Lewis-type NBO (nB:) to an acceptor non-Lewis-type NBO (σHA*) is the primary cause for H-bonding not classical electrostatic (dipole-dipole or ionic). We provide a variety of structure, and spectroscopic descriptors to support the conclusion, such as IR frequency shift (ΔνHA), H-bond penetration distance (ΔRB..H), bond order (bB..H), charge-transfer (CTB→HA) and the corresponding donor-acceptor stabilization energy (ΔE(2)).

Keywords: natural bond orbital, hydrogen bonding, electron donor, electron acceptor

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Authors: Morteza Keshavarz

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In this work, using density functional theory (DFT) thermodynamic stability and quantum molecular descriptors of cyclophoshphamide (an anticancer drug)-functionalized zigzag (8,0) CNT, armchair (4,4) CNT and nanocone complexes in water, for two attachment namely the sidewall and tip, is considered. Calculation of the total electronic energy (Et) and binding energy (Eb) of all complexes indicates that the most thermodynamic stability belongs to the sidewall-attachment of cyclophosphamide into functional nanocone. On the other hand, results from chemical hardness show that drug-functionalized zigzag (8,0) and armchair (4,4) complexes in the tip-attachment configuration possess the smallest and greatest chemical hardness, respectively. By computing the solvation energy, it is found that the solution of the drug and all complexes are spontaneous in water. Furthermore, chirality, type of nanovector (nanotube or nanocone), or attachment configuration have no effects on solvation energy of complexes.

Keywords: carbon nanotube, drug delivery, cyclophosphamide drug, density functional theory (DFT)

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Authors: Sunatda Arayachukiat, Shogo Nobukawa, Masayuki Yamaguchi

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A new self-healing material was developed utilizing molecular entanglements for poly(vinyl butyral) (PVB) containing plasticizers. It was found that PVB shows autonomic self-healing behavior even below the glass transition temperature Tg because of marked molecular motion at surface. Moreover, the plasticizer addition enhances the chain mobility, leading to good healing behavior.

Keywords: Poly(vinyl butyral) (PVB), rheological properties, self-healing behaviour, molecular diffusion

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Authors: Nadjib Melkemi, Salah Belaidi

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Quantitative Structure-Activity Relationship (QSAR) studies have been performed on nineteen molecules of 1,2-dithiole-3-thione analogues. The compounds used are the potent inducers of enzymes involved in the maintenance of reduced glutathione pools as well as phase-2 enzymes important to electrophile detoxication. A multiple linear regression (MLR) procedure was used to design the relationships between molecular descriptor and detoxication properties of the 1,2-dithiole-3-thione derivatives. The predictivity of the model was estimated by cross-validation with the leave-one-out method. Our results suggest a QSAR model based of the following descriptors: qS2, qC3, qC5, qS6, DM, Pol, log P, MV, SAG, HE and EHOMO for the specific activity of quinone reductase; qS1, qS2, qC3, qC4, qC5, qS6, DM, Pol, logP, MV, SAG, HE and EHOMO for the production of growth hormone. To confirm the predictive power of the models, an external set of molecules was used. High correlation between experimental and predicted activity values was observed, indicating the validation and the good quality of the derived QSAR models.

Keywords: QSAR, quinone reductase activity, production of growth hormone, MLR

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Authors: Rajandeep Kaur, Rajeev Gupta

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Background: Chronic myeloid leukemia (CML) is the most common leukaemia in India. The annual incidence of chronic myeloid leukemia in India was originally reported to be 0.8 to 2.2 per 1,00,000 population. CML is a clonal disorder that is usually easily diagnosed because the leukemic cells of more than 95% of patients have a distinctive cytogenetic abnormality, the Philadelphia chromosome (Ph1). The approval of tyrosine kinase inhibitors (TKIs), which target BCR-ABL1 kinase activity, has significantly reduced the mortality rate associated with chronic myeloid leukemia (CML) and revolutionized treatment. Material and Methods: 80 diagnosed cases of CML were taken. Investigations were done. Bone marrow and molecular studies were also done and with EUTOS, patients were stratified into low and high-risk groups and then treatment with Imatinib was given to all patients and the molecular response was evaluated at 6 months and 12 months follow up with BCR-ABL by RT-PCR quantitative assay. Results: In the study population, out of 80 patients in the study population, 40 were females and 40 were males, with M: F is 1:1. Out of total 80 patients’ maximum patients (54) were in 31-60 years age group. Our study showed a most common symptom of presentation is abdominal discomfort followed by fever. Out of the total 80 patients, 25 (31.3%) patients had high EUTOS scores and 55 (68.8%) patients had low EUTOS scores. On 6 months follow up 36.3% of patients had Complete Molecular Response, 16.3% of patients had Major Molecular Response and 47.5% of patients had No Molecular Response but on 12 months follow up 71.3% of patients had Complete Molecular Response, 16.25% of patients had Major Molecular Response and 12.5% patients had No Molecular Response. Conclusion: In this study, we found a significant correlation between EUTOS score and Molecular response at 6 months and 12 months follow up after Imatinib therapy.

Keywords: chronic myeloid leukemia, European treatment and outcome study score, hematological response, molecular response, tyrosine kinase inhibitor

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Authors: Madhusudan Purohit, Stephen Philip, Bharathkumar Inturi

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In this paper we report the quantitative structure activity relationship of novel bis-triazole derivatives for predicting the activity profile. The full model encompassed a dataset of 46 Bis- triazoles. Tripos Sybyl X 2.0 program was used to conduct CoMSIA QSAR modeling. The Partial Least-Squares (PLS) analysis method was used to conduct statistical analysis and to derive a QSAR model based on the field values of CoMSIA descriptor. The compounds were divided into test and training set. The compounds were evaluated by various CoMSIA parameters to predict the best QSAR model. An optimum numbers of components were first determined separately by cross-validation regression for CoMSIA model, which were then applied in the final analysis. A series of parameters were used for the study and the best fit model was obtained using donor, partition coefficient and steric parameters. The CoMSIA models demonstrated good statistical results with regression coefficient (r2) and the cross-validated coefficient (q2) of 0.575 and 0.830 respectively. The standard error for the predicted model was 0.16322. In the CoMSIA model, the steric descriptors make a marginally larger contribution than the electrostatic descriptors. The finding that the steric descriptor is the largest contributor for the CoMSIA QSAR models is consistent with the observation that more than half of the binding site area is occupied by steric regions.

Keywords: 3D QSAR, CoMSIA, triazoles, novel heterocycles

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Authors: Eisa A. Alsafran, Francis T. Edum-Fotwe, Wayne E. Lord

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The degree to which a public client actively participates in Public Private Partnership (PPP) schemes, is seen as a determinant of the success of the arrangement, and in particular, efficiency in the delivery of the assets of any infrastructure development. The asset delivery is often an early barometer for judging the overall performance of the PPP. Currently, there are no defined descriptors for the degree of such participation. The lack of defined descriptors makes the association between the degree of participation and efficiency of asset delivery, difficult to establish. This is particularly so if an optimum effect is desired. In addition, such an association is important for the strategic decision to embark on any PPP initiative. This paper presents a conceptual model of different levels of participation that characterise PPP schemes. The modelling was achieved by a systematic review of reported sources that address essential aspects and structures of PPP schemes, published from 2001 to 2015. As a precursor to the modelling, the common areas of Public Client Participation (PCP) were investigated. Equity and risk emerged as two dominant factors in the common areas of PCP, and were therefore adopted to form the foundation of the modelling. The resultant conceptual model defines the different states of combined PCP. The defined states provide a more rational basis for establishing how the degree of PCP affects the efficiency of asset delivery in PPP schemes.

Keywords: asset delivery, infrastructure development, public private partnership, public client participation

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Authors: Jannes Quer, Amir Niknejad, Marcus Weber

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Computational Drug Design is often based on Molecular Dynamics simulations of molecular systems. Molecular Dynamics can be used to simulate, e.g., the binding and unbinding event of a small drug-like molecule with regard to the active site of an enzyme or a receptor. However, the time-scale of the overall binding event is many orders of magnitude longer than the time-scale of simulation. Thus, there is a need to speed-up molecular simulations. In order to speed up simulations, the molecular dynamics trajectories have to be ”steared” out of local minimizers of the potential energy surface – the so-called metastabilities – of the molecular system. Increasing the kinetic energy (temperature) is one possibility to accelerate simulated processes. However, with temperature the entropy of the molecular system increases, too. But this kind ”stearing” is not directed enough to stear the molecule out of the minimum toward the saddle point. In this article, we give a new mathematical idea, how a potential energy surface can be changed in such a way, that entropy is kept under control while the trajectories are still steared out of the metastabilities. In order to compute the unsteared transition behaviour based on a steared simulation, we propose to use extrapolation methods. In the end we mathematically show, that our method accelerates the simulations along the direction, in which the curvature of the potential energy surface changes the most, i.e., from local minimizers towards saddle points.

Keywords: extrapolation, Eyring-Kramers, metastability, multilevel sampling

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Authors: A. Azari, S. S. K. Seyyedi

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One of the unaddressed and open challenges in the nano-networking is the characteristics of noise. The previous analysis, however, has concentrated on end-to-end communication model with no separate modelings for propagation channel and noise. By considering a separate signal propagation and noise model, the design and implementation of an optimum receiver will be much easier. In this paper, we justify consideration of a separate additive Gaussian noise model of a nano-communication system based on the molecular communication channel for which are applicable for MSK and MOSK modulation schemes. The presented noise analysis is based on the Brownian motion process, and advection molecular statistics, where the received random signal has a probability density function whose mean is equal to the mean number of the received molecules. Finally, the justification of received signal magnitude being uncorrelated with additive non-stationary white noise is provided.

Keywords: molecular, noise, diffusion, channel

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Authors: Suman Bala, Sunil Kamboj, Vipin Saini

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Quantitative Structure Activity Relationship (QSAR) analysis has been developed to relate antifungal activity of novel substituted 1,3,4-oxadiazole against Candida albicans and Aspergillus niger using computer assisted multiple regression analysis. The study has shown the better relationship between antifungal activities with respect to various descriptors established by multiple regression analysis. The analysis has shown statistically significant correlation with R² values 0.932 and 0.782 against Candida albicans and Aspergillus niger respectively. These derivatives were further subjected to molecular docking studies to investigate the interactions between the target compounds and amino acid residues present in the active site of glucosamine-6-phosphate synthase. All the synthesized compounds have better docking score as compared to standard fluconazole. Our results could be used for the further design as well as development of optimal and potential antifungal agents.

Keywords: 1, 3, 4-oxadiazole, QSAR, multiple linear regression, docking, glucosamine-6-phosphate synthase

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Authors: Paweł Stączek, Tomasz Plech, Aleksandra Strzelczyk, Katarzyna Dzitko, Monika Wujec, Edyta Kuśmierz, Piotr Paneth, Agata Paneth

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In this contribution, we will describe the inhibitory potency of nine thiosemicarbazide derivatives against bacterial type IIA topoisomerases, their antibacterial profile, and molecular modeling evaluation. We have found that one of the tested compounds, 4-benzoyl-1-(2-methyl-furan-3-ylcarbonyl) thiosemicarbazide, remarkably inhibits the activity of S. aureus DNA gyrase with the IC50 below 5 μM. Besides, this compound displays antibacterial activity on Staphylococcus spp. and E. faecalis at non-cytotoxic concentrations in mammalian cells, with minimal inhibitory concentrations (MICs) values at 25 μg/mL. Based on the enzymatic and molecular modeling studies we propose two factors, i.e. geometry of molecule and hydrophobic/hydrophilic balance as important molecular properties for developing thiosemicarbazide derivatives as potent Staphylococcus aureus DNA gyrase inhibitors.

Keywords: bioactivity, drug design, topoisomerase, molecular modeling

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Authors: Hussein Alahmer, Amr Ahmed

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Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, fuzzy c means, lesion detection, liver segmentation

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Authors: Hai Hoang, Thanh Xuan Nguyen Thi, Guillaume Galliero

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Coarse-Grained (CG) molecular simulations have shown to be an efficient way to estimate thermophysical (static and dynamic) properties of fluids. Several strategies have been developed and reported in the literature for defining CG molecular models. Among them, those based on a top-down strategy (i.e. CG molecular models related to macroscopic observables), despite being heuristic, have increasingly gained attention. This is probably due to its simplicity in implementation and its ability to provide reasonable results for not only simple but also complex systems. Regarding simple Force-Fields associated with these CG molecular models, it has been found that the four parameters Mie chain model is one of the best compromises to describe thermophysical static properties (e.g. phase diagram, saturation pressure). However, parameterization procedures of these Mie-chain GC molecular models given in literature are generally insufficient to simultaneously provide static and dynamic (e.g. viscosity) properties. To deal with such situations, we have extended the corresponding states by using a quantity associated with the liquid viscosity. Results obtained from molecular simulations have shown that our approach is able to yield good estimates for both static and dynamic thermophysical properties for various real non-associating fluids. In addition, we will show that on simple (e.g. phase diagram, saturation pressure) and complex (e.g. thermodynamic response functions, thermodynamic energy potentials) static properties, results of our scheme generally provides improved results compared to existing approaches.

Keywords: coarse-grained model, mie potential, molecular simulations, thermophysical properties, phase equilibria

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Authors: Manel Boulakoud, Abdelkader Chouaih, Fodil Hamzaoui

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In the present work we are interested in the determination of the Molecular electrostatic potential (MEP) in Z-3N(2-Ethoxyphenyl), 2-N’(2-Ethoxyphenyl) imino thiazolidin-4-one molecule by ab initio and Density Functional Theory (DFT) in the ground state. The MEP is related to the electronic density and is a very useful descriptor in understanding sites for electrophilic attack and nucleophilic reactions as well as hydrogen bonding interactions. First, geometry optimization was carried out using Hartree–Fock (HF) and DFT methods with 6-311G(d,p) basis set. In order to get more information on the molecule, its stability has been analyzed by natural bond orbital (NBO) analysis. Mulliken population analyses have been calculated. Finally, the molecular electrostatic potential (MEP) and HOMO-LUMO energy levels have been performed. The calculated HOMO and LUMO energies show also the charge transfer within the molecule. The energy gap obtained is about 4 eV which explain the stability of the studied compound. The obtained molecular electrostatic potential from the two methods confirms the nature of the electron charge transfer at the molecular shell and locate the electropositive part and the electronegative part in molecular scale of the title compound.

Keywords: DFT, ab initio, HOMO-LUMO, organic compounds

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Authors: Ezgi Kaya, A. Dilek Maden

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A topological index is a number related to graph which is invariant under graph isomorphism. In theoretical chemistry, molecular structure descriptors (also called topological indices) are used for modeling physicochemical, pharmacologic, toxicologic, biological and other properties of chemical compounds. Let G be a graph with n vertices and m edges. For a given edge uv, the quantity nu(e) denotes the number of vertices closer to u than v, the quantity nv(e) is defined analogously. The vertex PI index defined as the sum of the nu(e) and nv(e). Here the sum is taken over all edges of G. The energy of a graph is defined as the sum of the eigenvalues of adjacency matrix of G and the Laplacian energy of a graph is defined as the sum of the absolute value of difference of laplacian eigenvalues and average degree of G. In theoretical chemistry, the π-electron energy of a conjugated carbon molecule, computed using the Hückel theory, coincides with the energy. Hence results on graph energy assume special significance. The Laplacian matrix of a graph G weighted by the vertex PI weighting is the Laplacian vertex PI matrix and the Laplacian vertex PI eigenvalues of a connected graph G are the eigenvalues of its Laplacian vertex PI matrix. In this study, Laplacian vertex PI energy of a graph is defined of G. We also give some bounds for the Laplacian vertex PI energy of graphs in terms of vertex PI index, the sum of the squares of entries in the Laplacian vertex PI matrix and the absolute value of the determinant of the Laplacian vertex PI matrix.

Keywords: energy, Laplacian energy, laplacian vertex PI eigenvalues, Laplacian vertex PI energy, vertex PI index

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Authors: Efendi Zaenudin, Chien-Hung Huang, Ka-Lok Ng

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Essential genes play an important role in the survival of an organism. It has been shown that cancer-associated essential genes are genes necessary for cancer cell proliferation, where these genes are potential therapeutic targets. Also, it was demonstrated that mutations of the cancer-associated essential genes give rise to the resistance of immunotherapy for patients with tumors. In the present study, we focus on studying the biological effects of the essential genes from a network perspective. We hypothesize that one can analyze a biological molecular network by decomposing it into both three-node and four-node digraphs (subgraphs). These network subgraphs encode the regulatory interaction information among the network’s genetic elements. In this study, the frequency of occurrence of the subgraph-associated essential genes in a molecular network was quantified by using the statistical parameter, odds ratio. Biological effects of subgraph-associated essential genes are discussed. In summary, the subgraph approach provides a systematic method for analyzing molecular networks and it can capture useful biological information for biomedical research.

Keywords: biological molecular networks, essential genes, graph theory, network subgraphs

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Authors: Y. Megrous, A. Chouaih, F. Hamzaoui

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The crystal structure of 4-Methyl-7-(salicylideneamino)coumarin C17H13NO3has been determined using X-ray diffraction to establish the configuration and stereochemistry of the molecule. This crystal is characterized by its nolinear activity. The molecular electron charge density distribution of the title compound is described accurately using the multipolar model of Hansen and Coppens. The net atomic charge and the molecular dipole moment in-crystal have been determined in order to understand the nature of inter-and intramolecular charge transfer. The study present the thermal motion and the structural analysis obtained from the least-square refinement on F2,this study has also allowed us to determine the electrostatic potential and therefore locate the electropositive part and the electronegative part in molecular scale of the title compound.

Keywords: electron charge density, net atomic charge, molecular dipole moment, X-ray diffraction

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Authors: I-Ling Chang, Jer-An Chen

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The elastic properties and fracture of two-dimensional graphene were calculated purely from the atomic bonding (stretching and bending) based on molecular mechanics method. Considering the representative unit cell of graphene under various loading conditions, the deformations of carbon bonds and the variations of the interlayer distance could be realized numerically under the geometry constraints and minimum energy assumption. In elastic region, it was found that graphene was in-plane isotropic. Meanwhile, the in-plane deformation of the representative unit cell is not uniform along armchair direction due to the discrete and non-uniform distributions of the atoms. The fracture of graphene could be predicted using fracture criteria based on the critical bond length, over which the bond would break. It was noticed that the fracture behavior were directional dependent, which was consistent with molecular dynamics simulation results.

Keywords: energy minimization, fracture, graphene, molecular mechanics

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Authors: Jing Zhao, Yongqing Bai, Qiaofang Shi, Huaihao Zhang

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Advances in software technology enable computational chemistry to be commonly applied in various research fields, especially in pedagogy. Thus, in order to expand and improve experimental instructions of computational chemistry for undergraduates, we designed an introductory experiment—research on acrylamide molecular structure and physicochemical properties. Initially, students construct molecular models of acrylamide and polyacrylamide in Gaussian and Materials Studio software respectively. Then, the infrared spectral data, atomic charge and molecular orbitals of acrylamide as well as solvation effect of polyacrylamide are calculated to predict their physicochemical performance. At last, rheological experiments are used to validate these predictions. Through the combination of molecular simulation (performed on Gaussian, Materials Studio) with experimental verification (rheology experiment), learners have deeply comprehended the chemical nature of acrylamide and polyacrylamide, achieving good learning outcomes.

Keywords: upper-division undergraduate, computer-based learning, laboratory instruction, molecular modeling

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Authors: Sakina Fatima, Joseph-Patrick W. E. Clarke, Patricia A. Thibault, Subha Kalyaanamoorthy, Michael Levin, Aravindhan Ganesan

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Heteronuclear ribonucleoprotein (hnRNPA1 or A1) is associated with the pathology of different diseases, including neurological disorders and cancers. In particular, the aggregation and dysfunction of A1 have been identified as a critical driver for neurodegeneration (NDG) in Multiple Sclerosis (MS). Structurally, A1 includes a low-complexity domain (LCD) and two RNA-recognition motifs (RRMs), and their interdomain coordination may play a crucial role in A1 aggregation. Previous studies propose that RNA-inhibitors or nucleoside analogs that bind to RRMs can potentially prevent A1 self-association. Therefore, molecular-level understanding of the structures, dynamics, and nucleotide interactions with A1 RRMs can be useful for developing therapeutics for NDG in MS. In this work, a combination of computational modelling and biochemical experiments were employed to analyze a set of RNA-A1 RRM complexes. Initially, the atomistic models of RNA-RRM complexes were constructed by modifying known crystal structures (e.g., PDBs: 4YOE and 5MPG), and through molecular docking calculations. The complexes were optimized using molecular dynamics simulations (200-400 ns), and their binding free energies were computed. The binding affinities of the selected complexes were validated using a thermal shift assay. Further, the most important molecular interactions that contributed to the overall stability of the RNA-A1 RRM complexes were deduced. The results highlight that adenine and guanine are the most suitable nucleotides for high-affinity binding with A1. These insights will be useful in the rational design of nucleotide-analogs for targeting A1 RRMs.

Keywords: hnRNPA1, molecular docking, molecular dynamics, RNA-binding proteins

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Authors: Salem El-Tohami Ashoor

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Here we show that the reduction of [Cr(ArN(CH2)3NAr)2Cl2] (1) where (Ar = 2,6-Pri2C6H3) and in presence of NaCp (2) (Cp= C5H5 = cyclopentadien), with a center coordination η5 interaction between Cp as co-ligand and chromium metal center, this was optimization by using density functional theory (DFT) and then was comparing with experimental data, also other possibility of Cp interacted with ion metal were tested like η1 ,η2 ,η3 and η4 under optimization system. These were carried out under investigation of density functional theory (DFT) calculation, and comparing together. Other methods, explicitly including electron correlation, are necessary for more accurate calculations; MB3LYP ( Becke)( Lee–Yang–Parr ) level of theory often being used to obtain more exact results. These complexes were estimated of electronic energy for molecular system, because it accounts for all electron correlation interactions. The optimised of [Cr(ArN(CH2)3NAr)2(η5-Cp)] (Ar = 2,6-Pri2C6H3 and Cp= C5H5) was found to be thermally more stable than others of chromium cyclopentadienyl. By using Dewar-Chatt-Duncanson model, as a basis of the molecular orbital (MO) analysis and showed the highest occupied molecular orbital (HOMO) and lowest occupied molecular orbital LUMO.

Keywords: Chromium(III) cyclopentadienyl complexes, DFT, MO, HOMO, LUMO

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Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Sinisa Markov, Aleksandar Okljesa, Andrea Nikolic, Marija Sakac, Katarina Penov Gasi

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This study considered the microbiological activity determination and molecular docking study for selected steroid derivatives of biomedical importance. Minimal inhibitory concentration (MIC) was determined for steroid derivatives against Staphylococcus aureus using macrodilution method. Some of the investigated steroid derivatives express bacteriostatic effect against Staphylococcus aureus. Molecular docking approaches are the most widely used techniques for predicting the binding mode of a ligand. Molecular docking study was done for steroid derivatives for androgen receptor negative prostate cancer cell line (PC-3) toward Human Cytochrome P450 CYP17A1. The molecules that had the smallest experimental IC50 values confirmed their ability to dock into active place using suitable molecular docking procedure. The binding disposition of those molecules was thoroughly investigated. Microbiological analysis and molecular docking study were conducted with aim to additionally characterize selected steroid derivatives for future investigation regarding their biological activity and to estimate the binding-affinities of investigated derivatives. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation and Science and Technology).

Keywords: binding affinity, minimal inhibitory concentration, molecular docking, pc-3 cell line, staphylococcus aureus, steroids

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Authors: José Manue Carvalho Vieira, Mariana Magalhães, Elizabeth Serra

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The Port Wine industry is essential to Portugal because it carries a tangible cultural heritage and for social and economic reasons. Positioned as a luxury product, brands need to pay more attention to the new generation's habits, preferences, languages, and sensory perceptions. Healthy lifestyles, anti-alcohol campaigns, and digitalisation of their buying decision process need to be better understood to understand the wine market in the future. The purpose of this study is to clarify the sensory perception gap between Port Wine descriptors promotion and the new generation's perceptions to help wineries to align their strategies. Based on the interpretivist approach - multiple methods and techniques (mixed-methods), different world views and different assumptions, and different data collection methods and analysis, this research integrated qualitative semi-structured interviews, Port Wine promotion contents, and social media perceptions mined by Sentiment Analysis Enginius algorithm. Findings confirm that Port Wine CEOs' strategies, brands' promotional content, and social perceptions are not sufficiently aligned. The central insight for Port Wine brands' managers is that there is a long and continuous work of understanding and associating their descriptors with the most relevant perceptual values and criteria of their targets to reposition (when necessary) and sustainably revitalise their brands. Finally, this study hypothesised a sensory gap that leads to a decrease in consumption, trying to find recommendations on how to transform it into an advantage for a better attraction towards the young age group (18-25).

Keywords: port wine, consumer habits, sensory gap analysis, wine marketing

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Authors: Jayanthi Sivaraman

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Claudins are the important components of the tight junctions that play a key role in paracellular permeability. Among various members of Claudin family, Claudin 4 (CLDN4) is found to be overexpressed in ovarian, pancreatic carcinomas and other epithelial malignancies. Therefore, in this study, an attempt has been made to identify potent inhibitors for CLDN4 from the ZINC database using virtual screening, molecular docking and molecular dynamics simulations. A well refined molecular model of CLDN4 was built using Prime of Schrodinger v10.2(Template- PDB ID: 4P79). Approximately, 6 million compounds from ZINC database are subjected to high-throughput virtual screening (HTVS) against the active site of CLDN4. Molecular docking using GLIDE predicted ARG31, ASN142, ASP146 and ARG158 as critically important residues. Furthermore, three compounds from ZINC database (ZINC96331839, ZINC36533519 and ZINC75819394) showed highly promising ADME properties and binding affinity with stable conformation. The therapeutic efficiency of these lead compounds is evaluated and confirmed by in-vitro and in-vivo studies which leads to the development of novel anti-cancer drugs.

Keywords: ADME property, inhibitors, molecular docking, virtual screening

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Authors: Guohua Cao, Xu Dong

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X-ray Fluorescence Molecular Imaging (XFMI) holds great promise as a low-cost molecular imaging modality for biomedical applications with high chemical sensitivity. However, for in vivo biomedical applications, a key technical bottleneck is the relatively low chemical sensitivity of XFMI, especially at a reasonably low radiation dose. In laboratory x-ray source based XFMI, one of the main factors that limits the chemical sensitivity of XFMI is the scattered x-rays. We will present our latest findings on improving the chemical sensitivity of XFMI using excitation beam spectrum optimization. XFMI imaging experiments on two mouse-sized phantoms were conducted at three different excitation beam spectra. Our results show that the minimum detectable concentration (MDC) of iodine can be readily increased by five times via excitation spectrum optimization. Findings from this investigation could find use for in vivo pre-clinical small-animal XFMI in the future.

Keywords: molecular imaging, X-ray fluorescence, chemical sensitivity, X-ray scattering

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Authors: Begüm Terzi, Özlem Ateş Sönmezoğlu, Ahmet Yildirim

Abstract:

Drought is the most important factor that limiting the production and productivity of wheat in the world. The yield of wheat, which is one of the most important crop in the world, reduced depend on drought. Researches to minimize effects of drought are one of the most important about breeding of drought resistant varieties. In recent years, benefiting from the drought resistance wild species and rapid advances in molecular biology studies, researches about drought have been accelerated and number of studies were made on molecular plant breeding which included the molecular mechanisms related to drought resistance. The aim of the present study was characterization of some bread wheat lines for drought tolerance which commonly cultivated in different location of Turkey. In this study, registered 9 bread wheat varieties which on the physiological tests about drought tolerance and 10 bread wheat line has been developed by Transitional Zone Agricultural Research Institute were used. SSR, STS, RAPD and SNP markers that associated with drought tolerance were used. The polymorphisms of the markers were determined by screening of two control varieties. For these purpose 40 molecular markers were used and 12 markers of them were polymorphic among the drought tolerance and the drought sensitive varieties. Control varieties were screened using polymorphic markers. All the DNAs on the genotypes will be searched for the presence of QTLs mapped to different chromosomes. Result of the research, the studied genotypes will be grouped according to drought tolerance and will be detected drought tolerance varieties by molecular markers. In addition, the results will be compared also with physiological tests. The drought tolerant wheat genotypes may be used in breeding studies related to drought stress.

Keywords: bread wheat, drought, molecular marker, Triticum aestivum

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Authors: Asli Faiza, Khamouli Saida

Abstract:

With the development of computer tools over the past 20 years. Molecular modeling and, more precisely, molecular docking has very quickly entered field of pharmaceutical research. EGFR enzyme involved in cancer disease.Our work consists of studying the inhibition of EGFR (1M17) with deferent inhibitors derived from quinazoline and quinoline by molecular docking. The values of ligands L148 and L177 are the best ligands for inhibit the activity of 1M17 since it forms a stable complex with this enzyme by better binding to the active site. The results obtained show that the ligands L148 and L177 give weak interactions with the active site residues EGFR (1M17), which stabilize the complexes formed of this ligands, which gives a better binding at the level of the active site, and an RMSD of L148 [1,9563 Å] and of L177 [ 1,2483 Å]. [1, 9563, 1.2483] Å

Keywords: docking, EGFR, quinazoline, quinoliène, MOE

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Authors: Mohamad Mohsen Yavarizadeh

Abstract:

Polystyrene (PS) and related homopolymers are brittle materials that typically fail in tensile tests at very low strains. These polymers can be toughened by the addition of rubbery particles which initiate a large number of crazes that produce substantial plastic strain at relatively low stresses. Considerable energy is dissipated in the formation of these crazes, producing a relatively tough material that shows an impact toughness of more than 5 times of pure PS. While cross linking of rubbery phase is necessary in aforementioned mechanism of toughening, another mechanism of toughening was also introduced in which low molecular weight liquid rubbers can also toughen PS when dispersed in the form of small pools in the glassy matrix without any cross linking. However, this new mechanism which is based on local plasticization, fails to act properly at high strain rate deformations, i.e. impact tests. In this work, the idea of combination of these two mechanisms was tried. To do so, Polybutadiene rubbers (PB) with bimodal distribution of molecular weight were prepared in which, comparable fractions of very high and very low molecular weight rubbers were mixed. Incorporation of these materials in PS matrix in a reactive process resulted in more significant increases in toughness of PS. In other words, although low molecular weight PB is ineffective in high strain rate impact test by itself, it showed a significant synergistic effect when combined with high molecular weight PB. Surprisingly, incorporation of just 10% of low molecular weight PB doubled the impact toughness of regular high impact PS (HIPS). It was observed that most of rubbery particles could initiate crazes. The effectiveness of low molecular weight PB in impact test was attributed to low strain rate deformation of each individual craze as a result of producing a large number of crazes in this material. In other words, high molecular weight PB chains make it possible to have an appropriate dispersion of rubbery phase in order to create a large number of crazes in the PS matrix and consequently decrease the velocity of each craze. Low molecular weight PB, in turn, would have enough time to locally plasticize craze fibrils and enhance the energy dissipation.

Keywords: molecular weight distribution, polystyrene, toughness, homopolymer

Procedia PDF Downloads 411