scholarly journals VIRTUAL SCREENING OF BETA-SECRETASE 1 (BACE1) INHIBITORS IN THE INDONESIAN HERBAL DATABASE AS USING AUTODOCK AND AUTODOCK VINA

2017 ◽  
Vol 10 (17) ◽  
pp. 148
Author(s):  
Asti Anna Tanisa ◽  
Rezi Riadhi
Keyword(s):  
Binding Energy ◽  
Virtual Screening ◽  
Cellular Response ◽  
Senile Plaque ◽  
Area Under The Curve ◽  
Neuronal System ◽  
Operating Characteristics ◽  
Autodock Vina ◽  
Beta Secretase ◽  
The Brain

  Objective: Alzheimer’s is a neurodegenerative disease caused by the accumulation of senile plaque in the brain that affects neuronal system leading to a less sensitive cellular response from neurons. Previous research has found that beta-secretase 1 (BACE1) plays an important role in the senile plaque formation, become a target in Alzheimer’s medication.Methods: In this study, virtual screening of BACE1 inhibitors on the Indonesian Herbal Database was done using AutoDock and AutoDock Vina. The screening was validated using the directory of useful decoys: Enhanced database. Parameters for validation process of AutoDock and AutoDock Vina are enrichment factor (EF), receiver operating characteristics, and area under the curve (AUC).Results: The dimensions of grid boxes were 30×30×30 (AutoDock) and 11.25×11.25×11.25 (AutoDock Vina). The EF 1% and AUC values obtained from the AutoDock are 7.74 and 0.73, respectively, and in the AutoDock Vina are 4.6 and 0.77, respectively. Based on the virtual screening results, the top six compounds obtained using AutoDock (binding energy ranging from −7.84 kcal/mol to −8.79 kcal/mol) include: Azadiradione, cylindrin, lanosterol, sapogenin, simiarenol, and taraxerol. The top seven compounds (binding energy ranging from −8.8 kcal/mol to −9.4 kcal/mol) obtained using AutoDeck Vina include: Bryophyllin A, diosgenin, azadiradione, sojagol, beta-amyrin, epifriedelinol, and jasmolactone C.Conclusions: Only azadiradione was obtained from the virtual screening conducted using both types of software; it interacts with the active region in BACE1 at residue Trp 76 (AutoDock result) and Thr 232 (AutoDock Vina result).  

scholarly journals VIRTUAL SCREENING OF INDONESIAN HERBAL DATABASE FOR CP ALLOSTERIC MODULATOR OF HEPATITIS B VIRUS

2018 ◽  
Vol 10 (1) ◽  
pp. 190
Author(s):  
Ulfa Ivonie ◽  
Arry Yanuar ◽  
Firdayani .
Keyword(s):  
Virtual Screening ◽  
Core Protein ◽  
Area Under The Curve ◽  
Receiver Operating Characteristics ◽  
Screening Methods ◽  
Allosteric Modulator ◽  
Operating Characteristics ◽  
Autodock Vina ◽  
The Core ◽  
B Virus

Objective: This study performed a virtual screening of the Indonesian Herbal Database for the core protein allosteric modulator of the hepatitis Bvirus (HBV) using AutoDock and AutoDock Vina software, to discover novel safe drugs for patients.Methods: The method was validated using the parameters enrichment factor (EF), receiver operating characteristics, and area under the curve (AUC).The grid box size used in virtual screening with AutoDock was 55 × 55 × 55 with EF10% of 0.7652 and AUC of 0.6709, whereas that used in virtualscreening with AutoDock Vina was 20.625 × 20.625 × 20.625 with EF5% of 0.5075 and AUC of 0.7832.Results: The top 10 compounds from virtual screening with AutoDock at G levels −11.74–−10.31 kcal/mol were yuehchukene, lansionic acid, stigmast-4-en-3-one, myrtillin, sanggenol O, lanosterol, erycrista-gallin, alpha-spinasterol, cyanidin 3-arabinoside, and cathasterone and with AutoDock Vinaat G levels −12.1 to −10.7 kcal/mol were sanggenol O, cucumerin A, yuehchukene, palmarumycin CP1, dehydrocycloguanandin, myrtillin, liriodenine,myricetin 3-alpha-L-arabinopyranoside, myricetin 3-galactoside, and cassameridine.Conclusion: Three compounds were in top list of both virtual screening methods against Cp allosteric modulator of HBV are myrtillin, sanggenol O,and yuehchukene have a prospect to be investigated futher for anti HBV.

Lead Molecule Prediction and Characterization for Designing MERS-CoV 3C-like Protease Inhibitors: An In silico Approach

2018 ◽  
Vol 15 (1) ◽  
pp. 82-88 ◽  
Author(s):  
Md. Mostafijur Rahman ◽  
Md. Bayejid Hosen ◽  
M. Zakir Hossain Howlader ◽  
Yearul Kabir
Keyword(s):  
Binding Energy ◽  
Middle East ◽  
Virtual Screening ◽  
In Silico ◽  
Screening Method ◽  
Middle East Respiratory Syndrome ◽  
Cytochrome P450 Enzymes ◽  
Drug Molecules ◽  
Essential Enzyme ◽  
Reduced Toxicity

Background: 3C-like protease also called the main protease is an essential enzyme for the completion of the life cycle of Middle East Respiratory Syndrome Coronavirus. In our study we predicted compounds which are capable of inhibiting 3C-like protease, and thus inhibit the lifecycle of Middle East Respiratory Syndrome Coronavirus using in silico methods. </P><P> Methods: Lead like compounds and drug molecules which are capable of inhibiting 3C-like protease was identified by structure-based virtual screening and ligand-based virtual screening method. Further, the compounds were validated through absorption, distribution, metabolism and excretion filtering. Results: Based on binding energy, ADME properties, and toxicology analysis, we finally selected 3 compounds from structure-based virtual screening (ZINC ID: 75121653, 41131653, and 67266079) having binding energy -7.12, -7.1 and -7.08 Kcal/mol, respectively and 5 compounds from ligandbased virtual screening (ZINC ID: 05576502, 47654332, 04829153, 86434515 and 25626324) having binding energy -49.8, -54.9, -65.6, -61.1 and -66.7 Kcal/mol respectively. All these compounds have good ADME profile and reduced toxicity. Among eight compounds, one is soluble in water and remaining 7 compounds are highly soluble in water. All compounds have bioavailability 0.55 on the scale of 0 to 1. Among the 5 compounds from structure-based virtual screening, 2 compounds showed leadlikeness. All the compounds showed no inhibition of cytochrome P450 enzymes, no blood-brain barrier permeability and no toxic structure in medicinal chemistry profile. All the compounds are not a substrate of P-glycoprotein. Our predicted compounds may be capable of inhibiting 3C-like protease but need some further validation in wet lab.

scholarly journals End-to-end convolutional neural network enables COVID-19 detection from breath and cough audio: a pilot study

2021 ◽  
Vol 7 (2) ◽  
pp. 356-362
Author(s):  
Harry Coppock ◽  
Alex Gaskell ◽  
Panagiotis Tzirakis ◽  
Alice Baird ◽  
Lyn Jones ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Low Cost ◽  
Area Under The Curve ◽  
Alternative Form ◽  
Economic Damage ◽  
Audio Signals ◽  
Operating Characteristics ◽  
Data Set ◽  
Empirical Performance

BackgroundSince the emergence of COVID-19 in December 2019, multidisciplinary research teams have wrestled with how best to control the pandemic in light of its considerable physical, psychological and economic damage. Mass testing has been advocated as a potential remedy; however, mass testing using physical tests is a costly and hard-to-scale solution.MethodsThis study demonstrates the feasibility of an alternative form of COVID-19 detection, harnessing digital technology through the use of audio biomarkers and deep learning. Specifically, we show that a deep neural network based model can be trained to detect symptomatic and asymptomatic COVID-19 cases using breath and cough audio recordings.ResultsOur model, a custom convolutional neural network, demonstrates strong empirical performance on a data set consisting of 355 crowdsourced participants, achieving an area under the curve of the receiver operating characteristics of 0.846 on the task of COVID-19 classification.ConclusionThis study offers a proof of concept for diagnosing COVID-19 using cough and breath audio signals and motivates a comprehensive follow-up research study on a wider data sample, given the evident advantages of a low-cost, highly scalable digital COVID-19 diagnostic tool.

scholarly journals Multi-scale characterizations of colon polyps via computed tomographic colonography

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Weiguo Cao ◽  
Marc J. Pomeroy ◽  
Yongfeng Gao ◽  
Matthew A. Barish ◽  
Almas F. Abbasi ◽  
...  
Keyword(s):  
Area Under The Curve ◽  
Texture Features ◽  
Learning Model ◽  
Colon Polyps ◽  
Texture Descriptor ◽  
Operating Characteristics ◽  
Computed Tomographic ◽  
Multi Scale ◽  
Definition Of ◽  
Occurrence Matrix

AbstractTexture features have played an essential role in the field of medical imaging for computer-aided diagnosis. The gray-level co-occurrence matrix (GLCM)-based texture descriptor has emerged to become one of the most successful feature sets for these applications. This study aims to increase the potential of these features by introducing multi-scale analysis into the construction of GLCM texture descriptor. In this study, we first introduce a new parameter - stride, to explore the definition of GLCM. Then we propose three multi-scaling GLCM models according to its three parameters, (1) learning model by multiple displacements, (2) learning model by multiple strides (LMS), and (3) learning model by multiple angles. These models increase the texture information by introducing more texture patterns and mitigate direction sparsity and dense sampling problems presented in the traditional Haralick model. To further analyze the three parameters, we test the three models by performing classification on a dataset of 63 large polyp masses obtained from computed tomography colonoscopy consisting of 32 adenocarcinomas and 31 benign adenomas. Finally, the proposed methods are compared to several typical GLCM-texture descriptors and one deep learning model. LMS obtains the highest performance and enhances the prediction power to 0.9450 with standard deviation 0.0285 by area under the curve of receiver operating characteristics score which is a significant improvement.

scholarly journals Diagnostic work up of anemic patients: role of iron deficiency

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Daniela Meiser ◽  
Lale Kayikci ◽  
Matthias Orth
Keyword(s):  
Iron Deficiency ◽  
Complete Blood Count ◽  
Iron Status ◽  
Area Under The Curve ◽  
Diagnostic Value ◽  
Diagnostic Tools ◽  
Operating Characteristics ◽  
Inflammatory Conditions ◽  
Reliable Parameter ◽  
Work Up

AbstractObjectivesDiagnosing disturbances in iron metabolism can be challenging when accompanied by inflammation. New diagnostic tools such as the “Thomas-plot” (TP) (relation of soluble transferrin receptor [sTfR]/log ferritin to reticulocyte hemoglobin content [RET-He]) were established to improve classification of anemias. Aim of this retrospective study was to assess the added diagnostic value of the TP in anemia work up.MethodsPatients from December 2016 to September 2018 with a complete blood count, iron status, RET-He and sTfR were manually classified into the four quadrants of the TP on basis of conventional iron markers. Manual and algorithm-based classifications were compared using cross tabulations, Box–Whisker-Plots as well as Receiver-Operating-Characteristics (ROC) to calculate the diagnostic accuracy using Area under the Curve (AUC) analysis.ResultsA total of 3,745 patients with a conventional iron status, including 1,721 TPs, could be evaluated. In 70% of the cases the manual classification was identical to the TP, in 10% it was deviant. 20% could not clearly be classified, mostly due to inflammatory conditions. In the absence of an inflammatory condition, ferritin was a reliable parameter to define iron deficiency (ID) (AUC 0.958). In the presence of inflammation, the significance of the ferritin index (AUC 0.917) and of the RET-He (AUC 0.957) increased.ConclusionsThe TP can be useful for narrowing down the causes of anemia in complex cases. Further studies with focus on special patient groups, e.g., oncological or rheumatic patients, are desirable.

scholarly journals New screening approach to detecting congenital syphilis in China: a retrospective cohort study

2020 ◽  
pp. archdischild-2020-320549
Author(s):  
Fang Hu ◽  
Shuai-Jun Guo ◽  
Jian-Jun Lu ◽  
Ning-Xuan Hua ◽  
Yan-Yan Song ◽  
...  
Keyword(s):  
Predictive Value ◽  
Congenital Syphilis ◽  
Area Under The Curve ◽  
Diagnostic Tools ◽  
Operating Characteristics ◽  
Loss To Follow Up ◽  
Sensitivity Specificity ◽  
Mother To Child ◽  
Rule Out

BackgroundDiagnosis of congenital syphilis (CS) is not straightforward and can be challenging. This study aimed to evaluate the validity of an algorithm using timing of maternal antisyphilis treatment and titres of non-treponemal antibody as predictors of CS.MethodsConfirmed CS cases and those where CS was excluded were obtained from the Guangzhou Prevention of Mother-to-Child Transmission of syphilis programme between 2011 and 2019. We calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) using receiver operating characteristics (ROC) in two situations: (1) receiving antisyphilis treatment or no-treatment during pregnancy and (2) initiating treatment before 28 gestational weeks (GWs), initiating after 28 GWs or receiving no treatment for syphilis seropositive women.ResultsAmong 1558 syphilis-exposed children, 39 had confirmed CS. Area under the curve, sensitivity and specificity of maternal non-treponemal titres before treatment and treatment during pregnancy were 0.80, 76.9%, 78.7% and 0.79, 69.2%, 88.7%, respectively, for children with CS. For the algorithm, ROC results showed that PPV and NPV for predicting CS were 37.3% and 96.4% (non-treponemal titres cut-off value 1:8 and no antisyphilis treatment), 9.4% and 100% (non-treponemal titres cut-off value 1:16 and treatment after 28 GWs), 4.2% and 99.5% (non-treponemal titres cut-off value 1:32 and treatment before 28 GWs), respectively.ConclusionsAn algorithm using maternal non-treponemal titres and timing of treatment during pregnancy could be an effective strategy to diagnose or rule out CS, especially when the rate of loss to follow-up is high or there are no straightforward diagnostic tools.

scholarly journals Identification of Novel Cathepsin B Inhibitors with Implications in Alzheimer’s Disease: Computational Refining and Biochemical Evaluation

Cells ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1946
Author(s):  
Nitin Chitranshi ◽  
Ashutosh Kumar ◽  
Samran Sheriff ◽  
Veer Gupta ◽  
Angela Godinez ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Hydrogen Bond ◽  
Virtual Screening ◽  
Cathepsin B ◽  
Amyloid Β ◽  
Proteolytic Degradation ◽  
Hydrogen Bond Acceptor ◽  
Starting Point ◽  
The Brain

Amyloid precursor protein (APP), upon proteolytic degradation, forms aggregates of amyloid β (Aβ) and plaques in the brain, which are pathological hallmarks of Alzheimer’s disease (AD). Cathepsin B is a cysteine protease enzyme that catalyzes the proteolytic degradation of APP in the brain. Thus, cathepsin B inhibition is a crucial therapeutic aspect for the discovery of new anti-Alzheimer’s drugs. In this study, we have employed mixed-feature ligand-based virtual screening (LBVS) by integrating pharmacophore mapping, docking, and molecular dynamics to detect small, potent molecules that act as cathepsin B inhibitors. The LBVS model was generated by using hydrophobic (HY), hydrogen bond acceptor (HBA), and hydrogen bond donor (HBD) features, using a dataset of 24 known cathepsin B inhibitors of both natural and synthetic origins. A validated eight-feature pharmacophore hypothesis (Hypo III) was utilized to screen the Maybridge chemical database. The docking score, MM-PBSA, and MM-GBSA methodology was applied to prioritize the lead compounds as virtual screening hits. These compounds share a common amide scaffold, and showed important interactions with Gln23, Cys29, His110, His111, Glu122, His199, and Trp221. The identified inhibitors were further evaluated for cathepsin-B-inhibitory activity. Our study suggests that pyridine, acetamide, and benzohydrazide compounds could be used as a starting point for the development of novel therapeutics.

First trimester prediction of maternal glycemic status

2015 ◽  
Vol 43 (3) ◽  
Author(s):  
Rinat Gabbay-Benziv ◽  
Lauren E. Doyle ◽  
Miriam Blitzer ◽  
Ahmet A. Baschat
Keyword(s):  
Risk Score ◽  
Predictive Value ◽  
Challenge Test ◽  
Area Under The Curve ◽  
First Trimester ◽  
Tolerance Test ◽  
Oral Glucose ◽  
Operating Characteristics ◽  
Maternal Characteristics ◽  
Predictive Algorithm

AbstractTo predict gestational diabetes mellitus (GDM) or normoglycemic status using first trimester maternal characteristics.We used data from a prospective cohort study. First trimester maternal characteristics were compared between women with and without GDM. Association of these variables with sugar values at glucose challenge test (GCT) and subsequent GDM was tested to identify key parameters. A predictive algorithm for GDM was developed and receiver operating characteristics (ROC) statistics was used to derive the optimal risk score. We defined normoglycemic state, when GCT and all four sugar values at oral glucose tolerance test, whenever obtained, were normal. Using same statistical approach, we developed an algorithm to predict the normoglycemic state.Maternal age, race, prior GDM, first trimester BMI, and systolic blood pressure (SBP) were all significantly associated with GDM. Age, BMI, and SBP were also associated with GCT values. The logistic regression analysis constructed equation and the calculated risk score yielded sensitivity, specificity, positive predictive value, and negative predictive value of 85%, 62%, 13.8%, and 98.3% for a cut-off value of 0.042, respectively (ROC-AUC – area under the curve 0.819, CI – confidence interval 0.769–0.868). The model constructed for normoglycemia prediction demonstrated lower performance (ROC-AUC 0.707, CI 0.668–0.746).GDM prediction can be achieved during the first trimester encounter by integration of maternal characteristics and basic measurements while normoglycemic status prediction is less effective.

Abstract WP5: Outcomes Are Not Different Between Patients With Intermediate and High Dwi-aspects After Stent-retriever Thrombectomy

Stroke ◽  
2016 ◽  
Vol 47 (suppl_1) ◽  
Author(s):  
Woong Yoon ◽  
Seul Kee Kim ◽  
Tae Wook Heo ◽  
Byung Hyun Baek ◽  
Jaechan Park
Keyword(s):  
Functional Outcome ◽  
Time Window ◽  
Multivariate Logistic Regression Analysis ◽  
Area Under The Curve ◽  
Stent Retriever ◽  
Operating Characteristics ◽  
Anterior Circulation ◽  
Good Outcome ◽  
Characteristics Analysis ◽  
The Impact

Introduction: Few studies have investigated the association between pretreatment DWI-ASPECTS and functional outcome after stent-retriever thrombectomy in patients with acute anterior circulation stroke. Hypothesis: Patients with acute stroke and DWI-ASPECTS <7 might have a similar chance of a good outcome compared to those with a higher DWI-ASPECTS, if they are treated with a stent-retriever thrombectomy in a short time window. However, this hypothesis has not been tested. Thus, this study aimed to investigate the impact of DWI-ASPECTS on functional outcome in patients with acute anterior circulation stroke who received a stent-retriever thrombectomy. Methods: We retrospectively analyzed the clinical and DWI data from 171 patients with acute anterior circulation stroke who were treated with stent-retriever thrombectomy within 6 hours of symptom onset. The DWI-ASPECTS was assessed by two readers. A good outcome was defined as a modified Rankin Scale score of 0-2 at 3 months. Results: The median DWI-ASPECTS was 7 (interquartile range, 6-8). Receiver operating characteristics analysis revealed an ASPECTS ≥ 7 was the optimal cut-off to predict a good outcome at 3 months (area under the curve=0.57; sensitivity, 75.3%; specificity, 34.4%). The rates of good outcome, symptomatic hemorrhage, and mortality were not different between high DWI-ASPECTS (scores of 7-10) and intermediate (scores of 4-6) groups. In patients with an intermediate DWI-ASPECTS, good outcome was achieved in 46.5% (20/43) of patients with successful revascularization (modified TICI 2b or 3), whereas no patients without successful revascularization had a good outcome ( P =0.016). In multivariate logistic regression analysis, independent predictors of good outcome were age and successful revascularization. Conclusions: Our study suggested that treatment outcomes were not different between patients with a high DWI-ASPECTS and those with an intermediate DWI-ASPECTS who underwent stent-retriever thrombectomy for acute anterior circulation stroke. Thus, patients with an intermediate DWI-ASPECTS otherwise eligible for endovascular therapy should not be excluded for stent-retriever thrombectomy or stroke trials.

scholarly journals MicroRNAs Which Can Prognosticate Aggressiveness of Bladder Cancer

Cancers ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1551 ◽  
Author(s):  
Edyta Marta Borkowska ◽  
Tomasz Konecki ◽  
Michał Pietrusiński ◽  
Maciej Borowiec ◽  
Zbigniew Jabłonowski
Keyword(s):  
Bladder Cancer ◽  
Area Under The Curve ◽  
Roc Curves ◽  
Control Group ◽  
Low Grade ◽  
Operating Characteristics ◽  
High Death Rate ◽  
Biological Potential ◽  
High Death ◽  
Muscle Invasive

Bladder cancer (BC) is still characterized by a very high death rate in patients with this disease. One of the reasons for this is the lack of adequate markers which could help determine the biological potential of the tumor to develop into its invasive stage. It has been found that some microRNAs (miRNAs) correlate with disease progression. The purpose of this study was to identify which miRNAs can accurately predict the presence of BC and can differentiate low grade (LG) tumors from high grade (HG) tumors. The study included 55 patients with diagnosed bladder cancer and 30 persons belonging to the control group. The expression of seven selected miRNAs was estimated with the real-time PCR technique according to miR-103-5p (for the normalization of the results). Receiver operating characteristics (ROC) curves and the area under the curve (AUC) were used to evaluate the feasibility of using selected markers as biomarkers for detecting BC and discriminating non-muscle invasive BC (NMIBC) from muscle invasive BC (MIBC). For HG tumors, the relevant classifiers are miR-205-5p and miR-20a-5p, whereas miR-205-5p and miR-182-5p are for LG (AUC = 0.964 and AUC = 0.992, respectively). NMIBC patients with LG disease are characterized by significantly higher miR-130b-3p expression values compared to patients in HG tumors.

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