Search results for: in silico approach

Authors: Adeyi Akindele Oluwatosin, Mustapha Kaosarat Keji, Ajisebiola Babafemi Siji, Adeyi Olubisi Esther, Damilohun Samuel Metibemu, Raphael Emuebie Okonji

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Envenoming by Echis ocellatus is potentially life-threatening due to severe hemorrhage, renal failure, and capillary leakage. These effects are attributed to snake venom metalloproteinases (SVMPs). Due to drawbacks in the use of antivenom, natural inhibitors from plants are of interest in studies of new antivenom treatment. Antagonizing effects of bioactive compounds of Moringa oleifera, a known antisnake plant, are yet to be tested against SVMPs of E. ocellatus (SVMP-EO). Ethanol crude extract of M. oleifera was partitioned using n-hexane and ethyl acetate. Each partition was fractionated using column chromatography and tested against SVMP-EO purified through ion-exchange chromatography with EchiTab-PLUS polyvalent anti-venom as control. Phytoconstituents of ethyl acetate fraction were screened against the catalytic site of crystal of BaP1-SVMP, while drug-likeness and ADMET toxicity of compound were equally determined. The molecular weight of isolated SVMP-EO was 43.28 kDa, with a specific activity of 245 U/ml, a percentage yield of 62.83 %, and a purification fold of 0.920. The Vmax and Km values are 2 mg/ml and 38.095 μmol/ml/min, respectively, while the optimal pH and temperature are 6.0 and 40°C, respectively. Polyvalent anti-venom, crude extract, and ethyl acetate fraction of M. oleifera exhibited a complete inhibitory effect against SVMP-EO activity. The inhibitions of the P-1 and P-II metalloprotease’s enzymes by the ethyl acetate fraction are largely due to methanol, 6, 8, 9-trimethyl-4-(2-phenylethyl)-3-oxabicyclo[3.3.1]non-6-en-1-yl)- and paroxypropione, respectively. Both compounds are potential drug candidates with little or no concern of toxicity, as revealed from the in-silico predictions. The inhibitory effects suggest that this compound might be a therapeutic candidate for further exploration for treatment of Ocellatus’ envenoming.

Keywords: Echis ocellatus, Moringa oleifera, anti-venom, metalloproteases, snakebite, molecular docking

Procedia PDF Downloads 117

Authors: Saurabh B. Ganorkar, Atul A. Shirkhedkar

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The need for investigations protecting against toxic impurities though seems to be a primary requirement; the impurities which may prove non - toxic can be explored for their therapeutic potential if any to assist advanced drug discovery. The essential role of pharmaceutical analysis can thus be extended effectively to achieve it. The present study successfully achieved these objectives with characterization of major degradation products as impurities for Zileuton which has been used for to treat asthma since years. The forced degradation studies were performed to identify the potential degradation products using Ultra-fine Liquid-chromatography. Liquid-chromatography-Mass spectrometry (Time of Flight) and Proton Nuclear Magnetic Resonance Studies were utilized effectively to characterize the drug along with five major oxidative and hydrolytic degradation products (DP’s). The mass fragments were identified for Zileuton and path for the degradation was investigated. The characterized DP’s were subjected to In-Silico studies as XP Molecular Docking to compare the gain or loss in binding affinity with 5-Lipooxygenase enzyme. One of the impurity of was found to have the binding affinity more than the drug itself indicating for its potential to be more bioactive as better Antiasthmatic. The close structural resemblance has the ability to potentiate or reduce bioactivity and or toxicity. The chances of being active biologically at other sites cannot be denied and the same is achieved to some extent by predictions for probability of being active with Prediction of Activity Spectrum for Substances (PASS) The impurities found to be bio-active as Antineoplastic, Antiallergic, and inhibitors of Complement Factor D. The toxicological abilities as Ames-Mutagenicity, Carcinogenicity, Developmental Toxicity and Skin Irritancy were evaluated using Toxicity Prediction by Komputer Assisted Technology (TOPKAT). Two of the impurities were found to be non-toxic as compared to original drug Zileuton. As the drugs are purposed and repurposed effectively the impurities can also be; as they can have more binding affinity; less toxicity and better ability to be bio-active at other biological targets.

Keywords: UFLC, LC-MS-TOF, NMR, Zileuton, impurities, toxicity, bio-activity

Procedia PDF Downloads 168

Authors: Asma Zaib, Saeed Khan, Ayaz Ahmed Noonari, Sehrish Bint-e-Mohsin

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Breast cancer is the most common cancer among females worldwide and is estimated that more than 450,000 deaths are reported each year. It accounts for about 14% of all female cancer deaths. Angiogenesis plays an essential role in Breast cancer development, invasion, and metastasis. Breast cancer predominantly begins in luminal epithelial cells lining the normal breast ducts. Breast carcinoma likely requires coordinated efforts of both increased proliferation and increased motility to progress to metastatic stages.Resveratrol: a natural stilbenoid, has anti-inflammatory and anticancer effects that inhibits proliferation of variety of human cancer cell lines, including breast, prostate, stomach, colon, pancreatic, and thyroid cancers.The objective of this study is:To investigate anti-neoangiogenesis effects of Resveratrol in breast cancer and to analyze inhibitory effects of resveratrol on aromatase, Erα, HER2/neu, and VEGFR.Docking is the computational determination of binding affinity between molecule (protein structure and ligand).We performed molecular docking using Swiss-Dock and to determine docking effects of (1) Resveratrol with Aromatase, (2) Resveratrol with ERα (3) Resveratrol with HER2/neu and (4) Resveratrol with VEGFR2.Docking results of resveratrol determined inhibitory effects on aromatase with binding energy of -7.28 kcal/mol which shows anticancerous effects on estrogen dependent breast tumors. Resveratrol also show inhibitory effects on ERα and HER2/new with binging energy -8.02, and -6.74 respectively; which revealed anti-cytoproliferative effects upon breast cancer. On the other hand resveratrol v/s VEGFR showed potential inhibitory effects on neo-angiogenesis with binding energy -7.68 kcal/mol, angiogenesis is the important phenomenon that promote tumor development and metastasis. Resveratrol is an anti-breast cancer agent conformed by in silico studies, it has been identified that resveratrol can inhibit breast cancer cells proliferation by acting as competitive inhibitor of aromatase, ERα and HER2 neo, while neo-angiogemesis is restricted by binding to VEGFR which authenticates the anti-carcinogenic effects of resveratrol against breast cancer.

Keywords: angiogenesis, anti-cytoproliferative, molecular docking, resveratrol

Procedia PDF Downloads 297

Authors: Arpita Roy, Navneeta Bharadvaja

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Cancer is an uncontrolled growth of abnormal cells in the body. It is one of the most serious diseases on which extensive research work has been going on all over the world. Structure-based drug designing is a computational approach which helps in the identification of potential leads that can be used for the development of a drug. Plumbagin is a naphthoquinone derivative from Plumbago zeylanica roots and belongs to one of the largest and diverse groups of plant metabolites. Anticancer and antiproliferative activities of plumbagin have been observed in animal models as well as in cell cultures. Plumbagin shows inhibitory effects on multiple cancer-signaling proteins; however, the binding mode and the molecular interactions have not yet been elucidated for most of these protein targets. In this investigation, an attempt to provide structural insights into the binding mode of plumbagin against four cancer receptors using molecular docking was performed. Plumbagin showed minimal energy against targeted cancer receptors, therefore suggested its stability and potential towards different cancers. The least binding energies of plumbagin with COX-2, TACE, and CDK6 are -5.39, -4.93, -and 4.81 kcal/mol, respectively. Comparison studies of plumbagin with different receptors showed that it is a promising compound for cancer treatment. It was also found that plumbagin obeys the Lipinski’s Rule of 5 and computed ADMET properties which showed drug likeliness and improved bioavailability. Since plumbagin is from a natural source, it has reduced side effects, and these results would be useful for cancer treatment.

Keywords: cancer, receptor, plumbagin, docking

Procedia PDF Downloads 111

Authors: Sadaf Moeez, Madiha Khalid, Zoya Khalid, Sania Shaheen, Sumbul Khalid

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Background: Inter-individual variation in response to metformin, which has been considered as a first line therapy for T2DM treatment is considerable. In the current study, it was aimed to investigate the impact of two genetic variants Leu125Phe (rs77474263) and Gly64Asp (rs77630697) in gene SLC47A1 on the clinical efficacy of metformin in T2DM Pakistani patients. Methods: The study included 800 T2DM patients (400 metformin responders and 400 metformin non-responders) along with 400 ethnically matched healthy individuals. The genotypes were determined by allele-specific polymerase chain reaction. In-silico analysis was done to confirm the effect of the two SNPs on the structure of genes. Association was statistically determined using SPSS software. Results: Minor allele frequency for rs77474263 and rs77630697 was 0.13 and 0.12. For SLC47A1 rs77474263 the homozygotes of one mutant allele ‘T’ (CT) of rs77474263 variant were fewer in metformin responders than metformin non-responders (29.2% vs. 35.5 %). Likewise, the efficacy was further reduced (7.2% vs. 4.0 %) in homozygotes of two copies of ‘T’ allele (TT). Remarkably, T2DM cases with two copies of allele ‘C’ (CC) had 2.11 times more probability to respond towards metformin monotherapy. For SLC47A1 rs77630697 the homozygotes of one mutant allele ‘A’ (GA) of rs77630697 variant were fewer in metformin responders than metformin non-responders (33.5% vs. 43.0 %). Likewise, the efficacy was further reduced (8.5% vs. 4.5%) in homozygotes of two copies of ‘A’ allele (AA). Remarkably, T2DM cases with two copies of allele ‘G’ (GG) had 2.41 times more probability to respond towards metformin monotherapy. In-silico analysis revealed that these two variants affect the structure and stability of their corresponding proteins. Conclusion: The present data suggest that SLC47A1 Leu125Phe (rs77474263) and Gly64Asp (rs77630697) polymorphisms were associated with the therapeutic response of metformin in T2DM patients of Pakistan.

Keywords: diabetes, T2DM, SLC47A1, Pakistan, polymorphism

Procedia PDF Downloads 127

Authors: Safee Chaudhary, Mahnoor Naseer Gondal, Hira Anees Awan, Abdul Rehman, Ammar Arif, Risham Hussain, Huma Khawar, Zainab Arshad, Muhammad Faizyab Ali Chaudhary, Waleed Ahmed, Muhammad Umer Sultan, Bibi Amina, Salaar Khan, Muhammad Moaz Ahmad, Osama Shiraz Shah, Hadia Hameed, Muhammad Farooq Ahmad Butt, Muhammad Ahmad, Sameer Ahmed, Fayyaz Ahmed, Omer Ishaq, Waqar Nabi, Wim Vanderbauwhede, Bilal Wajid, Huma Shehwana, Muhammad Tariq, Amir Faisal

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Cancer is a manifestation of multifactorial deregulations in biomolecular pathways. These deregulations arise from the complex multi-scale interplay between cellular and extracellular factors. Such multifactorial aberrations at gene, protein, and extracellular scales need to be investigated systematically towards decoding the underlying mechanisms and orchestrating therapeutic interventions for patient treatment. In this work, we propose ‘TISON’, a next-generation web-based multiscale modeling platform for clinical systems oncology. TISON’s unique modeling abstraction allows a seamless coupling of information from biomolecular networks, cell decision circuits, extra-cellular environments, and tissue geometries. The platform can undertake multiscale sensitivity analysis towards in silico biomarker identification and drug evaluation on cellular phenotypes in user-defined tissue geometries. Furthermore, integration of cancer expression databases such as The Cancer Genome Atlas (TCGA) and Human Proteome Atlas (HPA) facilitates in the development of personalized therapeutics. TISON is the next-evolution of multiscale cancer modeling and simulation platforms and provides a ‘zero-code’ model development, simulation, and analysis environment for application in clinical settings.

Keywords: systems oncology, cancer systems biology, cancer therapeutics, personalized therapeutics, cancer modelling

Procedia PDF Downloads 182

Authors: Menna Ewida, Dalal Abou El-Ella, Dina Lasheen, Huessin El-Subbagh

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Introduction: Vascular Endothelial Growth Factor receptor (VEGF) is a signal protein produced by cells that stimulates vasculogenesis to create new blood vessels. VEGF family binds to three trans-membrane tyrosine kinase receptors,Dihydrofolate reductase (DHFR) is an enzyme of crucial importance in medicinal chemistry. DHFR catalyzes the reduction 7,8 dihydro-folate to tetrahydrofolate and intimately couples with thymidylate synthase which is a pivotal enzyme that catalysis the reductive methylation of deoxyuridine monophosphate (dUMP) to deoxythymidine monophosphate (dTMP) utilizing N5,N10-methylene tetrahydrofolate as a cofactor which functions as the source of the methyl group. Purpose: Novel substituted Thiazole agents were designed as DHFR and VEGF-TK inhibitors with increased synergistic activity and decreased side effects. Methods: Five series of compounds were designed with a rational that mimic the pharmacophoric features present in the reported active compounds that target DHFR & VEGFR. These molecules were docked against Methotrexate & Sorafenib as controls. An in silico ADMET study was also performed to validate the bioavailability of the newly designed compounds. The in silico molecular docking & ADMET study were also applied to the non-classical antifolates for comparison. The interaction energy comparable to that of MTX for DHFRI and Sorafenib for VEGF-TKI activity were recorded. Results: Compound 5 exhibited the highest interaction energy when docked against Sorafenib, While Compound 9 showed the highest interaction energy when docked against MTX with the perfect binding mode. Comparable results were also obtained for the ADMET study. Most of the compounds showed absorption within (95-99) zone which varies according to the type of substituents. Conclusions: The Substituted Thiazole Analogues could be a suitable template for antitumor drugs that possess enhanced bioavailability and act as DHFR and VEGF-TK inhibitors.

Keywords: anti-tumor agents, DHFR, drug design, molecular modeling, VEGFR-TKIs

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Authors: Asif Bilal, Fouzia Tanvir, Sibtain Ahmad

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Estrogen receptor alpha, also known as estrogen receptor-1, is highly involved in risk of mammary carcinoma. The objectives of this study were to identify non-synonymous SNPs of estrogen receptor and their association with breast cancer and to identify the chemotherapeutic responses of phytochemicals against it via in-silico study design. For this purpose, different online tools. to identify pathogenic SNPs the tools were SIFT, Polyphen, Polyphen-2, fuNTRp, SNAP2, for finding disease associated SNPs the tools SNP&GO, PhD-SNP, PredictSNP, MAPP, SNAP, MetaSNP, PANTHER, and to check protein stability Mu-Pro, I-Mutant, and CONSURF were used. Post-translational modifications (PTMs) were detected by Musitedeep, Protein secondary structure by SOPMA, protein to protein interaction by STRING, molecular docking by PyRx. Seven SNPs having rsIDs (rs760766066, rs779180038, rs956399300, rs773683317, rs397509428, rs755020320, and rs1131692059) showing mutations on I229T, R243C, Y246H, P336R, Q375H, R394S, and R394H, respectively found to be completely deleterious. The PTMs found were 96 times Glycosylation; 30 times Ubiquitination, a single time Acetylation; and no Hydroxylation and Phosphorylation were found. The protein secondary structure consisted of Alpha helix (Hh) is (28%), Extended strand (Ee) is (21%), Beta turn (Tt) is 7.89% and Random coil (Cc) is (44.11%). Protein-protein interaction analysis revealed that it has strong interaction with Myeloperoxidase, Xanthine dehydrogenase, carboxylesterase 1, Glutathione S-transferase Mu 1, and with estrogen receptors. For molecular docking we used Asiaticoside, Ilekudinuside, Robustoflavone, Irinoticane, Withanolides, and 9-amin0-5 as ligands that extract from phytochemicals and docked with this protein. We found that there was great interaction (from -8.6 to -9.7) of these ligands of phytochemicals at ESR1 wild and two mutants (I229T and R394S). It is concluded that these SNPs found in ESR1 are involved in breast cancer and given phytochemicals are highly helpful against breast cancer as chemotherapeutic agents. Further in vitro and in vivo analysis should be performed to conduct these interactions.

Keywords: breast cancer, ESR1, phytochemicals, molecular docking

Procedia PDF Downloads 41

Authors: Kyle Phillips, Ndiko Ludidi

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Global climate change has resulted in altered rainfall patterns, which has resulted in annual losses in maize crop yields due to drought. Therefore it is important to produce maize cultivars that are more drought-tolerant, which is not an easily accomplished task as plants have a plethora of physical and biochemical adaptation methods. One such mechanism is the drought-induced expression of enzymatic and non-enzymatic proteins which assist plants to resist the effects of drought on their growth and development. One of these proteins is AtRD22 which has been identified in Arabidopsis thaliana. Using an in silico approach, a maize protein with 48% sequence homology to AtRD22 has been identified. This protein appears to be localized in the extracellular matrix, similarly to AtRD22. Promoter analysis of the encoding gene reveals cis-acting elements suggestive of induction of the gene’s expression by abscisic acid (ABA). Semi-quantitative transcriptomic analysis of the putative maize RD22 has revealed an increase in transcript levels after the exposure to drought. Current work elucidates the effect of up-regulation and silencing of the maize RD22 gene on the tolerance of maize to drought. The potential role of the maize RD22 gene in maize drought tolerance can be used as a tool to improve food security.

Keywords: abscisic acid, drought-responsive cis-acting elements, maize drought tolerance, RD22

Procedia PDF Downloads 425

Authors: Richa Dhingra, Monika, Manav Malhotra, Tilak Raj Bhardwaj, Neelima Dhingra

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5-Alpha-reductases (5AR), a membrane bound, NADPH dependent enzyme and convert male hormone testosterone (T) into more potent androgen dihydrotestosterone (DHT). DHT is the required for the development and function of male sex organs, but its overproduction has been found to be associated with physiological conditions like Benign Prostatic Hyperplasia (BPH). Thus the inhibition of 5ARs could be a key target for the treatment of BPH. In present study, 2D and 3D Quantitative Structure Activity Relationship (QSAR) pharmacophore models have been generated for 5AR based on known inhibitory concentration (IC₅₀) values with extensive validations. The four featured 2D pharmacophore based PLS model correlated the topological interactions (–OH group connected with one single bond) (SsOHE-index); semi-empirical (Quadrupole2) and physicochemical descriptors (Mol. wt, Bromines Count, Chlorines Count) with 5AR inhibitory activity, and has the highest correlation coefficient (r² = 0.98, q² =0.84; F = 57.87, pred r² = 0.88). Internal and external validation was carried out using test and proposed set of compounds. The contribution plot of electrostatic field effects and steric interactions generated by 3D-QSAR showed interesting results in terms of internal and external predictability. The well validated 2D Partial Least Squares (PLS) and 3D k-nearest neighbour (kNN) models were used to search novel 5AR inhibitors with different chemical scaffold. To gain more insights into the molecular mechanism of action of these steroidal derivatives, molecular docking and in silico absorption, distribution, metabolism, and excretion (ADME) studies were also performed. Studies have revealed the hydrophobic and hydrogen bonding of the ligand with residues Alanine (ALA) 63A, Threonine (THR) 60A, and Arginine (ARG) 456A of 4AT0 protein at the hinge region. The results of QSAR, molecular docking, in silico ADME studies provide guideline and mechanistic scope for the identification of more potent 5-Alpha-reductase inhibitors (5ARI).

Keywords: 5α-reductase inhibitor, benign prostatic hyperplasia, ligands, molecular docking, QSAR

Procedia PDF Downloads 136

Authors: Hassan Nour, Nouh Mounadi, Oussama Abchir, Belaidi Salah, Samir Chtita

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Cholinesterase enzymes are biological catalysts essential for the transformation of acetylcholine, which is a neurotransmitter implicated in memory and learning, into acetic acid and choline, altering the neurotransmission process in Alzheimer’s disease patients. Therefore, inhibition of cholinesterase enzymes is a relevant strategy for the symptomatic treatment of Alzheimer’s disease. The current investigation aims to explore potential Cholinesterase (ChE) inhibitors through a comprehensive computational approach. Forty-nine phytoconstituents extracted from Cannabis sativa L were in-silico screened using molecular docking, pharmacokinetic and toxicological analysis to evaluate their possible inhibitory effect towards the cholinesterase enzymes. Two phytoconstituents belonging to cannabinoid derivatives were revealed to be promising candidates for Alzheimer therapy by acting as cholinesterase inhibitors. They have exhibited high binding affinities towards the cholinesterase enzymes and showed their ability to interact with key residues involved in cholinesterase enzymatic activity. In addition, they presented good ADMET profiles allowing them to be promising oral drug candidates. Furthermore, molecular dynamics (MD) simulations were executed to explore their interactions stability under mimetic biological conditions and thus support our findings. To corroborate the docking results, the binding free energy corresponding to the more stable ligand-ChE complexes was re-estimated by applying the MM-PBSA method. MD and MM-PBSA studies affirmed that the ligand-ChE recognition is spontaneous reaction leading to stable complexes. The conducted investigations have led to great findings that would strongly guide the pharmaceutical industries towards the rational development of potent anti-Alzheimer agents.

Keywords: alzheimer’s disease, molecular docking, cannabis sativa l, cholinesterase inhibitors

Procedia PDF Downloads 40

Authors: Bright Chukwunwike Uzuegbunam, Wojciech Paslawski, Hans Agren, Christer Halldin, Wolfgang Weber, Markus Luster, Thomas Arzberger, Behrooz Hooshyar Yousefi

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There is a need to develop a PET tracer that will enable to diagnosis and track the progression of Alpha-synucleinopathies (Parkinson’s disease [PD], dementia with Lewy bodies [DLB], multiple system atrophy [MSA]) in living subjects over time. Alpha-synuclein aggregates (a-syn), which are present in all the stages of disease progression, for instance, in PD, are a suitable target for in vivo PET imaging. For this reason, we have developed some promising a-syn tracers based on a disarylbisthiazole (DABTA) scaffold. The precursors are synthesized via a modified Hantzsch thiazole synthesis. The precursors were then radiolabeled via one- or two-step radiofluorination methods. The ligands were initially screened using a combination of molecular dynamics and quantum/molecular mechanics approaches in order to calculate the binding affinity to a-syn (in silico binding experiments). Experimental in vitro binding assays were also performed. The ligands were further screened in other experiments such as log D, in vitro plasma protein binding & plasma stability, biodistribution & brain metabolite analyses in healthy mice. Radiochemical yields were up to 30% - 72% in some cases. Molecular docking revealed possible binding sites in a-syn and also the free energy of binding to those sites (-28.9 - -66.9 kcal/mol), which correlated to the high binding affinity of the DABTAs to a-syn (Ki as low as 0.5 nM) and selectivity (> 100-fold) over Aβ and tau, which usually co-exist with a-synin some pathologies. The log D values range from 2.88 - 2.34, which correlated with free-protein fraction of 0.28% - 0.5%. Biodistribution experiments revealed that the tracers are taken up (5.6 %ID/g - 7.3 %ID/g) in the brain at 5 min (post-injection) p.i., and cleared out (values as low as 0.39 %ID/g were obtained at 120 min p.i. Analyses of the mice brain 20 min p.i. Revealed almost no radiometabolites in the brain in most cases. It can be concluded that in silico study presents a new venue for the rational development of radioligands with suitable features. The results obtained so far are promising and encourage us to further validate the DABTAs in autoradiography, immunohistochemistry, and in vivo imaging in non-human primates and humans.

Keywords: alpha-synuclein aggregates, alpha-synucleinopathies, PET imaging, tracer development

Procedia PDF Downloads 207

Authors: Rijnbout-St.James Willem, Lindner Volkhard, Scholand Mary Beth, Ashton M. Tillett, Di Gennaro Michael Jude, Smith Silvia Enrica

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Introduction: Fibrosing lung diseases are characterized by changes in the lung interstitium and are classified based on etiology: 1) environmental/exposure-related, 2) autoimmune-related, 3) sarcoidosis, 4) interstitial pneumonia, and 4) idiopathic. Among interstitial lung diseases (ILD) idiopathic forms, idiopathic pulmonary fibrosis (IPF) is the most severe. Pathogenesis of IPF is characterized by an increased presence of proinflammatory mediators, resulting in alveolar injury, where injury to alveolar epithelium precipitates an increase in collagen deposition, subsequently thickening the alveolar septum and decreasing gas exchange. Identifying biomarkers implicated in the pathogenesis of lung fibrosis is key to developing new therapies and improving the efficacy of existing therapies. The transforming growth factor-beta (TGF-B1), a mediator of tissue repair associated with WNT5A signaling, is partially responsible for fibroblast proliferation in ILD and is the target of Pirfenidone, one of the antifibrotic therapies used for patients with IPF. Canonical TGF-B signaling is mediated by the proteins SMAD 2/3, which are, in turn, indirectly regulated by Collagen Triple Helix Repeat Containing 1 (CTHRC1). In this study, we tested the following hypotheses: 1) CTHRC1 is more elevated in the ILD cohort compared to unaffected controls, and 2) CTHRC1 is differently expressed among ILD types. Material and Methods: CTHRC1 levels were measured by ELISA in 171 plasma samples from the deidentified University of Utah ILD cohort. Data represent a cohort of 131 ILD-affected participants and 40 unaffected controls. CTHRC1 samples were categorized by a pulmonologist based on affectation status and disease subtypes: IPF (n = 45), sarcoidosis (4), nonspecific interstitial pneumonia (16), hypersensitivity pneumonitis (n = 7), interstitial pneumonia (n=13), autoimmune (n = 15), other ILD - a category that includes undifferentiated ILD diagnoses (n = 31), and unaffected controls (n = 40). We conducted a single-factor ANOVA of plasma CTHRC1 levels to test whether CTHRC1 variance among affected and non-affected participants is statistically significantly different. In-silico analysis was performed with Ingenuity Pathway Analysis® to characterize the role of CTHRC1 in the pathway of lung fibrosis. Results: Statistical analyses of CTHRC1 in plasma samples indicate that the average CTHRC1 level is significantly higher in ILD-affected participants than controls, with the autoimmune ILD being higher than other ILD types, thus supporting our hypotheses. In-silico analyses show that CTHRC1 indirectly activates and phosphorylates SMAD3, which in turn cross-regulates TGF-B1. CTHRC1 also may regulate the expression and transcription of TGFB-1 via WNT5A and its regulatory relationship with CTNNB1. Conclusion: In-silico pathway analyses demonstrate that CTHRC1 may be an important biomarker in ILD. Analysis of plasma samples indicates that CTHRC1 expression is positively associated with ILD affectation, with autoimmune ILD having the highest average CTHRC1 values. While characterizing CTHRC1 levels in plasma can help to differentiate among ILD types and predict response to Pirfenidone, the extent to which plasma CTHRC1 level is a function of ILD severity or chronicity is unknown.

Keywords: interstitial lung disease, CTHRC1, idiopathic pulmonary fibrosis, pathway analyses

Procedia PDF Downloads 163

Authors: Strahinja Z. Kovačević, Lidija R. Jevrić, Sanja O. Podunavac Kuzmanović

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The relationship between antibacterial activity of eighteen different substituted benzimidazole derivatives and their molecular characteristics was studied using chemometric QSAR (Quantitative Structure–Activity Relationships) approach. QSAR analysis has been carried out on inhibitory activity towards Staphylococcus aureus, by using molecular descriptors, as well as minimal inhibitory activity (MIC). Molecular descriptors were calculated from the optimized structures. Principal component analysis (PCA) followed by hierarchical cluster analysis (HCA) and multiple linear regression (MLR) was performed in order to select molecular descriptors that best describe the antibacterial behavior of the compounds investigated, and to determine the similarities between molecules. The HCA grouped the molecules in separated clusters which have the similar inhibitory activity. PCA showed very similar classification of molecules as the HCA, and displayed which descriptors contribute to that classification. MLR equations, that represent MIC as a function of the in silico molecular descriptors were established. The statistical significance of the estimated models was confirmed by standard statistical measures and cross-validation parameters (SD = 0.0816, F = 46.27, R = 0.9791, R2CV = 0.8266, R2adj = 0.9379, PRESS = 0.1116). These parameters indicate the possibility of application of the established chemometric models in prediction of the antibacterial behaviour of studied derivatives and structurally very similar compounds.

Keywords: antibacterial, benzimidazole, molecular descriptors, QSAR

Procedia PDF Downloads 335

Authors: Hassan Nour, Nouh Mounadi, Oussama Abchir, Belaidi Salah, Samir Chtita

Abstract:

Cholinesterase enzymes are biological catalysts essential for the transformation of acetylcholine, which is a neurotransmitter implicated in memory and learning, into acetic acid and choline, altering the neurotransmission process in Alzheimer’s disease patients. Therefore, inhibition of cholinesterase enzymes is a relevant strategy for the symptomatic treatment of Alzheimer’s disease. The current investigation aims to explore potential cholinesterase (ChE) inhibitors through a comprehensive computational approach. Forty-nine phytoconstituents extracted from Cannabis sativa L. were in-silico screened using molecular docking and pharmacokinetic and toxicological analysis to evaluate their possible inhibitory effect on the cholinesterase enzymes. Two phytoconstituents belonging to cannabinoid derivatives were revealed to be promising candidates for Alzheimer's therapy by acting as cholinesterase inhibitors. They have exhibited high binding affinities towards the cholinesterase enzymes and showed their ability to interact with key residues involved in cholinesterase enzymatic activity. In addition, they presented good ADMET profiles allowing them to be promising oral drug candidates. Furthermore, molecular dynamics (MD) simulations were executed to explore their interaction stability under mimetic biological conditions and thus support our findings. To corroborate the docking results, the binding free energy corresponding to the more stable ligand-ChE complexes was re-estimated by applying the MM-PBSA method. MD and MM-PBSA studies affirmed that the ligand-ChE recognition is a spontaneous reaction leading to stable complexes. The conducted investigations have led to great findings that would strongly guide the pharmaceutical industries toward the rational development of potent anti-Alzheimer agents.

Keywords: Alzheimer’s disease, molecular docking, Cannabis sativa L., cholinesterase inhibitors, molecular dynamics, ADMET, MM-PBSA

Procedia PDF Downloads 52

Authors: Chelali Mohammed

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In the context of the application of the competency-based approach in the system educational Algeria, the price of physical education and sport must privilege the acquisition of learning approaches and especially the approach science, which from problem situations, research and develops him information processing and application of knowledge and know-how in new situations in the words of ‘JOHN DEWEY’ ‘learning by practice’. And to achieve these goals and make teaching more EPS motivating, consistent and concrete, it is appropriate to perform a pedagogical approach freed from the constraints and open to creativity and student-centered in the light of the competency approach adopted in the formal curriculum. This approach is not unusual, but we think it is a highly professional nature requires the competence of the teacher.

Keywords: approach competencies, physical, education, teachers

Procedia PDF Downloads 569

Authors: Yu-Jen Chang, Yun Chen, Hei-Lam Wong

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The Economic Lot Scheduling Problem (ELSP) is a valuable mathematical model that can support decision-makers to make scheduling decisions. The basic period approach is effective for solving the ELSP. The assumption for applying the basic period approach is that a product must use its maximum production rate to be produced. However, a product can lower its production rate to reduce the average total cost when a facility has extra idle time. The past researches discussed how a product adjusts its production rate under the common cycle approach. To the best of our knowledge, no studies have addressed how a product lowers its production rate under the basic period approach. This research is the first paper to discuss this topic. The research develops a simple fixed rate approach that adjusts the production rate of a product under the basic period approach to solve the ELSP. Our numerical example shows our approach can find a better solution than the traditional basic period approach. Our mathematical model that applies the fixed rate approach under the basic period approach can serve as a reference for other related researches.

Keywords: economic lot, basic period, genetic algorithm, fixed rate

Procedia PDF Downloads 538

Authors: Jingyu Hou

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This paper proposes a new teaching and learning approach-project and Module Based Teaching and Learning (PMBTL). The PMBTL approach incorporates the merits of project/problem based and module based learning methods, and overcomes the limitations of these methods. The correlation between teaching, learning, practice, and assessment is emphasized in this approach, and new methods have been proposed accordingly. The distinct features of these new methods differentiate the PMBTL approach from conventional teaching approaches. Evaluation of this approach on practical teaching and learning activities demonstrates the effectiveness and stability of the approach in improving the performance and quality of teaching and learning. The approach proposed in this paper is also intuitive to the design of other teaching units.

Keywords: computer science education, project and module based, software engineering, module based teaching and learning

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Authors: Hamzeh Alipour, Masoumeh Bagheri, Abbasali Raz, Javad Dadgar Pakdel, Kourosh Azizi, Aboozar Soltani, Mohammad Djaefar Moemenbellah-Fard

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Background: Maggot debridement therapy is an appropriate, effective, and controlled method using sterilized larvae of Luciliasericata (L.sericata) to treat wounds. Netrin-A is an enzyme in the Laminins family which secreted from salivary gland of L.sericata with a central role in neural regeneration and angiogenesis. This study aimed to production of new recombinant Netrin-A protein of Luciliasericata larvae by baculovirus expression vector system (BEVS) in SF9. Material and methods: In the first step, gene structure was subjected to the in silico studies, which were include determination of Antibacterial activity, Prion formation risk, homology modeling, Molecular docking analysis, and Optimization of recombinant protein. In the second step, the Netrin-A gene was cloned and amplified in pTG19 vector. After digestion with BamH1 and EcoR1 restriction enzymes, it was cloned in pFastBac HTA vector. It was then transformed into DH10Bac competent cells, and the recombinant Bacmid was subsequently transfected into insect Sf9 cells. The expressed recombinant Netrin-A was thus purified in the Ni-NTA agarose. This protein evaluation was done using SDS-PAGE and western blot, respectively. Finally, its concentration was calculated with the Bradford assay method. Results: The Bacmid vector structure with Netrin-A was successfully constructed and then expressed as Netrin-A protein in the Sf9 cell lane. The molecular weight of this protein was 52 kDa with 404 amino acids. In the in silico studies, fortunately, we predicted that recombinant LSNetrin-A have Antibacterial activity and without any prion formation risk.This molecule hasa high binding affinity to the Neogenin and a lower affinity to the DCC-specific receptors. Signal peptide located between amino acids 24 and 25. The concentration of Netrin-A recombinant protein was calculated to be 48.8 μg/ml. it was confirmed that the characterized gene in our previous study codes L. sericata Netrin-A enzyme. Conclusions: Successful generation of the recombinant Netrin-A, a secreted protein in L.sericata salivary glands, and because Luciliasericata larvae are used in larval therapy. Therefore, the findings of the present study could be useful to researchers in future studies on wound healing.

Keywords: blowfly, BEVS, gene, immature insect, recombinant protein, Sf9

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Authors: Majid Farsadrooh, Mehran Feizi-Dehnayebi

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Serum albumin is the most abundant protein that is present in the circulatory system of a wide variety of organisms. Although it is a significant macromolecule, it can contribute to osmotic blood pressure and also, plays a superior role in drug disposition and efficiency. Molecular docking simulation can improve in silico drug design and discovery procedures to propound a lead compound and develop it from the discovery step to the clinic. In this study, the molecular docking simulation was applied to select a lead molecule through an investigation of the interaction of the two anticancer drugs (Alitretinoin and Abemaciclib) with Human Serum Albumin (HSA). Then, a series of new compounds (a-e) were suggested using lead molecule modification. Density functional theory (DFT) including MEP map and HOMO-LUMO analysis were used for the newly proposed compounds to predict the reactivity zones on the molecules, stability, and chemical reactivity. DFT calculation illustrated that these new compounds were stable. The estimated binding free energy (ΔG) values for a-e compounds were obtained as -5.78, -5.81, -5.95, -5,98, and -6.11 kcal/mol, respectively. Finally, the pharmaceutical properties and toxicity of these new compounds were estimated through OSIRIS DataWarrior software. The results indicated no risk of tumorigenic, irritant, or reproductive effects and mutagenicity for compounds d and e. As a result, compounds d and e, could be selected for further study as potential therapeutic candidates. Moreover, employing molecular docking simulation with the prediction of pharmaceutical properties helps to discover new potential drug compounds.

Keywords: drug design, anticancer, computational studies, DFT analysis

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Authors: Lu Yang, Keng Po Lai

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Metformin, a well-known clinical drug against diabetes, is found with potential anti-diabetic and anti-obese benefits, as reported in increasing evidences. However, the current clinical and experimental investigations are not to reveal the detailed mechanisms of metformin-anti-obesity/hypertension. We have used the bioinformatics strategy, including network pharmacology and molecular docking methodology, to uncover the key targets and pathways of bioactive compounds against clinical disorders, such as cancers, coronavirus disease. Thus, in this report, the in-silico approach was utilized to identify the hug targets, pharmacological function, and mechanism of metformin against obesity and hypertension. The networking analysis identified 154 differentially expressed genes of obesity and hypertension, 21 interaction genes, and 6 hug genes of metformin treating hypertensive obesity. As a result, the molecular docking findings indicated the potent binding capability of metformin with the key proteins, including interleukin 6 (IL-6) and chemokine (C-C motif) Ligand 2 (CCL2), in hypertensive obesity. The metformin-exerted anti-hypertensive obesity action involved in metabolic regulation, inflammatory reaction. And the anti-hypertensive obesity mechanisms of metformin were revealed, including regulation of inflammatory and immunological signaling pathways for metabolic homeostasis in tissue and microenvironmental melioration in blood pressure. In conclusion, our identified findings with bioinformatics analysis have demonstrated the detailed hug and pharmacological targets, biological functions, and signaling pathways of metformin treating hypertensive obesity.

Keywords: metformin, obesity, hypertension, bioinformatics findings

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Authors: Jineetkumar Gawad, Chandrakant Bonde

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Tuberculosis (TB) is a major worldwide concern whose control has been exacerbated by HIV, the rise of multidrug-resistance (MDR-TB) and extensively drug resistance (XDR-TB) strains of Mycobacterium tuberculosis. The interest for newer and faster acting antitubercular drugs are more remarkable than any time. To search potent compounds is need and challenge for researchers. Here, we tried to design lead for inhibition of Decaprenyl phosphoryl-β-D-ribose 2′-epimerase (DprE1) enzyme. Arabinose is an essential constituent of mycobacterial cell wall. DprE1 is a flavoenzyme that converts decaprenylphosphoryl-D-ribose into decaprenylphosphoryl-2-keto-ribose, which is intermediate in biosynthetic pathway of arabinose. Latter, DprE2 converts keto-ribose into decaprenylphosphoryl-D-arabinose. We had a selection of 23 compounds from azaindole series for computational study, and they were drawn using marvisketch. Ligands were prepared using Maestro molecular modeling interface, Schrodinger, v10.5. Common pharmacophore hypotheses were developed by applying dataset thresholds to yield active and inactive set of compounds. There were 326 hypotheses were developed. On the basis of survival score, ADRRR (Survival Score: 5.453) was selected. Selected pharmacophore hypotheses were subjected to virtual screening results into 1000 hits. Hits were prepared and docked with protein 4KW5 (oxydoreductase inhibitor) was downloaded in .pdb format from RCSB Protein Data Bank. Protein was prepared using protein preparation wizard. Protein was preprocessed, the workspace was analyzed using force field OPLS 2005. Glide grid was generated by picking single atom in molecule. Prepared ligands were docked with prepared protein 4KW5 using Glide docking. After docking, on the basis of glide score top-five compounds were selected, (5223, 5812, 0661, 0662, and 2945) and the glide docking score (-8.928, -8.534, -8.412, -8.411, -8.351) respectively. There were interactions of ligand and protein, specifically HIS 132, LYS 418, TRY 230, ASN 385. Pi-pi stacking was observed in few compounds with basic Imidazo [4,5-b] pyridine ring. We had basic azaindole ring in parent compounds, but after glide docking, we received compounds with Imidazo [4,5-b] pyridine as a basic ring. That might be the new lead in the process of drug discovery.

Keywords: DprE1 inhibitors, in silico drug designing, imidazo [4, 5-b] pyridine, lead, tuberculosis

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Authors: Muhammad Naweed, Usman Tariq Murtaza, Waseem Siddique

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A pallet body approach is a finite element-based computational approach used for the modeling and assessment of a three-dimensional surface crack. The approach is capable of inserting the crack in an engineering structure and generating high-quality hexahedral mesh in the cracked region of the structure. The approach is capable of computing the stress intensity factors along a semi-elliptical surface crack numerically. The objective of this work is to present that the stress intensity factors produced by the approach can be used with confidence for capturing the parameters during the fatigue crack growth.

Keywords: pallet body approach, semi-elliptical surface crack, stress intensity factors, fatigue crack growth

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Authors: Aussara Panya, Nunghathai Sawasdee, Mutita Junking, Chatchawan Srisawat, Kiattawee Choowongkomon, Pa-Thai Yenchitsomanus

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Dengue virus (DENV) infection is a global public health problem with approximately 100 million infected cases a year. Presently, there is no approved vaccine or effective drug available; therefore, the development of anti-DENV drug is urgently needed. The clinical reports revealing the positive association between the disease severity and viral titer has been reported previously suggesting that the anti-DENV drug therapy can possibly ameliorate the disease severity. Although several anti-DENV agents showed inhibitory activities against DENV infection, to date none of them accomplishes clinical use in the patients. The surface envelope (E) protein of DENV is critical for the viral entry step, which includes attachment and membrane fusion; thus, the blocking of envelope protein is an attractive strategy for anti-DENV drug development. To search the safe anti-DENV agent, this study aimed to search for novel peptide inhibitors to counter DENV infection through the targeting of E protein using a structure-based in silico design. Two selected strategies has been used including to identify the peptide inhibitor which interfere the membrane fusion process whereby the hydrophobic pocket on the E protein was the target, the destabilization of virion structure organization through the disruption of the interaction between the envelope and membrane proteins, respectively. The molecular docking technique has been used in the first strategy to search for the peptide inhibitors that specifically bind to the hydrophobic pocket. The second strategy, the peptide inhibitor has been designed to mimic the ectodomain portion of membrane protein to disrupt the protein-protein interaction. The designed peptides were tested for the effects on cell viability to measure the toxic to peptide to the cells and their inhibitory assay to inhibit the DENV infection in Vero cells. Furthermore, their antiviral effects on viral replication, intracellular protein level and viral production have been observed by using the qPCR, cell-based flavivirus immunodetection and immunofluorescence assay. None of tested peptides showed the significant effect on cell viability. The small peptide inhibitors achieved from molecular docking, Glu-Phe (EF), effectively inhibited DENV infection in cell culture system. Its most potential effect was observed for DENV2 with a half maximal inhibition concentration (IC50) of 96 μM, but it partially inhibited other serotypes. Treatment of EF at 200 µM on infected cells also significantly reduced the viral genome and protein to 83.47% and 84.15%, respectively, corresponding to the reduction of infected cell numbers. An additional approach was carried out by using peptide mimicking membrane (M) protein, namely MLH40. Treatment of MLH40 caused the reduction of foci formation in four individual DENV serotype (DENV1-4) with IC50 of 24-31 μM. Further characterization suggested that the MLH40 specifically blocked viral attachment to host membrane, and treatment with 100 μM could diminish 80% of viral attachment. In summary, targeting the hydrophobic pocket and M-binding site on the E protein by using the peptide inhibitors could inhibit DENV infection. The results provide proof of-concept for the development of antiviral therapeutic peptide inhibitors to counter DENV infection through the use of a structure-based design targeting conserved viral protein.

Keywords: dengue virus, dengue virus infection, drug design, peptide inhibitor

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

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The present paper deals with chromatographic lipophilicity prediction of newly synthesized steroid derivatives. The prediction was achieved using in silico generated molecular descriptors and quantitative structure-retention relationship (QSRR) methodology with the artificial neural networks (ANN) approach. Chromatographic lipophilicity of the investigated compounds was expressed as retention factor value logk. For QSRR modeling, a feedforward back-propagation ANN with gradient descent learning algorithm was applied. Using the novel sum of ranking differences (SRD) method generated ANN models were ranked. The aim was to distinguish the most consistent QSRR model that can be found, and similarity or dissimilarity between the models that could be noticed. In this study, SRD was performed with average values of retention factor value logk as reference values. An excellent correlation between experimentally observed retention factor value logk and values predicted by the ANN was obtained with a correlation coefficient higher than 0.9890. Statistical results show that the established ANN models can be applied for required purpose. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation in Science and Technology).

Keywords: artificial neural networks, liquid chromatography, molecular descriptors, steroids, sum of ranking differences

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Authors: Janneth Gonzalez, Andrés Pinzon Velasco, Maria Angarita

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Astrocytes play an important role in various processes in the brain, including pathological conditions such as neurodegenerative diseases. Recent studies have shown that the increase in saturated fatty acids such as palmitic acid (PA) triggers pro-inflammatorypathways in the brain. The use of synthetic neurosteroids such as tibolone has demonstrated neuro-protective mechanisms. However, broad studies with a systemic point of view on the neurodegenerative role of PA and the neuro-protective mechanisms of tibolone are lacking. In this study, we performed the integration of multi-omic data (transcriptome and proteome) into a human astrocyte genomic scale metabolic model to study the astrocytic response during palmitate treatment. We evaluated metabolic fluxes in three scenarios (healthy, induced inflammation by PA, and tibolone treatment under PA inflammation). We also applied a control theory approach to identify those reactions that exert more control in the astrocytic system. Our results suggest that PA generates a modulation of central and secondary metabolism, showing a switch in energy source use through inhibition of folate cycle and fatty acid β‐oxidation and upregulation of ketone bodies formation. We found 25 metabolic switches under PA‐mediated cellular regulation, 9 of which were critical only in the inflammatory scenario but not in the protective tibolone one. Within these reactions, inhibitory, total, and directional coupling profiles were key findings, playing a fundamental role in the (de)regulation of metabolic pathways that may increase neurotoxicity and represent potential treatment targets. Finally, the overall framework of our approach facilitates the understanding of complex metabolic regulation, and it can be used for in silico exploration of the mechanisms of astrocytic cell regulation, directing a more complex future experimental work in neurodegenerative diseases.

Keywords: astrocytes, data integration, palmitic acid, computational model, multi-omics

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Authors: Md. Fazlul Karim, Ashik Sharfaraz, Aysha Ferdoushi

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Background: Computational medicinal chemistry approaches are used for designing and identifying new drug-like molecules, predicting properties and pharmacological activities, and optimizing lead compounds in drug development. SIRT7, a nicotinamide adenine dinucleotide (NAD+)-dependent deacylase which regulates aging, is an emerging target for cancer therapy with mounting evidence that SIRT7 downregulation plays important roles in reversing cancer phenotypes and suppressing tumor growth. Activation or altered expression of SIRT7 is associated with the progression and invasion of various cancers, including liver, breast, gastric, prostate, and non-small cell lung cancer. Objectives: The goal of this work was to identify potent and selective bioactive candidate inhibitors of SIRT7 by in silico screening of small molecule compounds obtained from Nigella sativa (N. sativa). Methods: SIRT7 structure was retrieved from The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), and its active site was identified using CASTp and metaPocket. Molecular docking simulation was performed with PyRx 0.8 virtual screening software. Drug-likeness properties were tested using SwissADME and pkCSM. In silico toxicity was evaluated by Osiris Property Explorer. Bioactivity was predicted by Molinspiration software. Antitumor activity was screened for Prediction of Activity Spectra for Substances (PASS) using Way2Drug web server. Molecular dynamics (MD) simulation was carried out by Desmond v3.6 package. Results: A total of 159 bioactive compounds from the N. Sativa were screened against the SIRT7 enzyme. Five bioactive compounds: chrysin (CID:5281607), pinocembrin (CID:68071), nigellidine (CID:136828302), nigellicine (CID:11402337), and epicatechin (CID:72276) were identified as potent SIRT7 anti-cancer candidates after docking score evaluation and applying Lipinski's Rule of Five. Finally, MD simulation identified Chrysin as the top SIRT7 anti-cancer candidate molecule. Conclusion: Chrysin, which shows a potential inhibitory effect against SIRT7, can act as a possible anti-cancer drug candidate. This inhibitor warrants further evaluation to check its pharmacokinetics and pharmacodynamics properties both in vitro and in vivo.

Keywords: SIRT7, antitumor, molecular docking, molecular dynamics simulation

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Authors: Y. Tiamaz, N. Souissi

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The purpose of this paper is to present a classification of Lean models which aims to capture all the concepts related to this approach and thus facilitate its implementation. This classification allows the identification of the most relevant models according to several dimensions. From this perspective, we present a review and an analysis of Lean models literature and we propose dimensions for the classification of the current proposals while respecting among others the axes of the Lean approach, the maturity of the models as well as their application domains. This classification allowed us to conclude that researchers essentially consider the Lean approach as a toolbox also they design their models to solve problems related to a specific environment. Since Lean approach is no longer intended only for the automotive sector where it was invented, but to all fields (IT, Hospital, ...), we consider that this approach requires a generic model that is capable of being implemented in all areas.

Keywords: lean approach, lean models, classification, dimensions, holistic view

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Authors: Alessandro Marano

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Aim: The author describes a strategy for choosing between two different rhinoplasty approaches for outcomes treatment. Methods: Series of the case study. There are advantages and disadvantages on both approaches for rhinoplasty. On the side of the open approach, we are be able to better manage the techniques for shaping and restoring nasal structures in rhinoplasty outcomes; on the other side, the closed approach requires more practice and experience to achieve good results. Results: Author’s choice is the closed approach on rhinoplasty outcomes. Anyway, the open approach is most commonly preferred due to superior management and better vision on nasal structures. Conclusions: Both approaches are valid for the treatment of rhinoplasty outcomes, author's preferred approach is closed, with minimally invasive modification focused on restoring outcomes in nasal function and aesthetics.

Keywords: rhinoplasty, aesthetic, face, outcomes

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Authors: Wang Xingbo

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Computation of determinant in the form |I-X| is primary and fundamental because it can help to compute many other determinants. This article puts forward a time-reducible approach to compute determinant |I-X|. The approach is derived from the Newton’s identity and its time complexity is no more than that to compute the eigenvalues of the square matrix X. Mathematical deductions and numerical example are presented in detail for the approach. By comparison with classical approaches the new approach is proved to be superior to the classical ones and it can naturally reduce the computational time with the improvement of efficiency to compute eigenvalues of the square matrix.

Keywords: algorithm, determinant, computation, eigenvalue, time complexity

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