Optimal Descriptor Based QSPR Models for Catalytic Activity of Propylene Polymerization

2018 ◽  
Vol 3 (2) ◽  
pp. 36-48
Author(s):  
Sanija Begum ◽  
P. Ganga Raju Achary
Keyword(s):  
External Validation ◽  
Propylene Polymerization ◽  
Polymerization Process ◽  
Input Line ◽  
Qspr Model ◽  
Monte Carlo Optimization ◽  
Catalytic Activities ◽  
Optimal Descriptor ◽  
Validation Set

A heterogeneous Ziegler–Natta (ZN) catalyst is an important catalyst in the field of the polypropylene polymerization industry. The role of electron donors has been crucial in the ZN catalyzed polypropylene polymerization process. In this article, quasi-SMILES-based QSPR models are elaborated for the prediction of catalytic activities. The representations of the molecular structure by quasi-simplified molecular input line entry system were the basis to build the desired QSPR model. These models were developed by means of the Monte Carlo optimization involving the available methods classic scheme (CS), balance of correlations (BC) and balance of correlation with ideal slopes (BCIS). The best QSPR model showed r2 = 0.813 (for external validation set), rm2 (avg)=0.73 and ∆rm2= 0.03.

scholarly journals A simple 2D-QSPR model for the prediction of Setschenow constants of organic compounds

2016 ◽  
Vol 35 (1) ◽  
pp. 53 ◽  
Author(s):  
Qi Xu ◽  
Lingling Fan ◽  
Jie Xu
Keyword(s):  
Organic Compounds ◽  
External Validation ◽  
Structure Property ◽  
Training Set ◽  
Multilinear Regression ◽  
Qspr Model ◽  
Multilinear Regression Analysis ◽  
Validation Set ◽  
Reliability And Robustness ◽  
Leave One Out

A quantitative structure-property relationship (QSPR) analysis of the Setschenow constants (Ksalt) of organic compounds in a sodium chloride solution was carried out using only two-dimensional (2D) descriptors as input parameters. The whole set of 101 compounds was split into a training set of 71 compounds and a validation set of 30 compounds by means of the Kennard and Stones algorithm. A general four-parameter equation, with correlation coefficient (R) of 0.887 and standard error of estimation (s) of 0.031, was obtained by stepwise multilinear regression analysis (MLRA) on the training set. The reliability and robustness of the present model was verified with leave-one-out cross-validation, randomization tests, and the external validation set. All of the descriptors contained in this model are calculated directly from the molecular 2D structures; thus, this model can be used to easily predict the Ksalt of other compounds not involved in the present dataset.

A Comparative Study of 1D Descriptors Supported CoMFA and CoMSIA QSAR Models to Gain Novel Insights into 1,2,4-Triazoles Acting As Antitubercular Agents

2020 ◽  
Vol 16 ◽  
Author(s):  
Rajdeep Ray ◽  
Gautham Shenoy ◽  
N V Ganesh Kumar Tummalapalli
Keyword(s):  
External Validation ◽  
Antitubercular Activity ◽  
New Drugs ◽  
Rational Approach ◽  
Antitubercular Drugs ◽  
Comfa Model ◽  
Qsar Models ◽  
Structural Insights ◽  
The Way

: Tuberculosis is one of the leading cause for deaths due to infectious disease worldwide. There is an urgent need for developing new drugs due to the rising incidents of drug resistance. Triazoles have previously been reported to show antitubercular activity. Various computational tools pave the way for a rational approach in understanding the structural importance of these compounds in inhibiting Mycobacterium tuberculosis growth. The aim of this study is to develop and compare two different QSAR models based on a set of previously reported molecules and use the best one for gaining structural insights in to the Triazole molecules. In the current study, two separate models were generated with CoMFA and CoMSIA descriptors respectively based on a dataset of triazole molecules showing antitubercular activity. Several one dimensional (1D) descriptors were added to each of the models and the validation results and the contour data generated from them were compared. The best model was studied to give a detailed understanding of the triazole molecules and their role in the antitubercular activity.The r2, q2, predicted r2 and SEP (Standard error of prediction) for the CoMFA model were 0.866, 0.573, 0.119 and 0.736 respectively and for the CoMSIA model the r2, q2, predicted r2 and SEP were calculated to be 0.998, 0.634, 0.013 and 0.869 respectively. Although both the QSAR models produced acceptable internal and external validation scores but the CoMSIA results were significantly better. The CoMSIA contours also provided a better match than CoMFA with most of the features of the active compound 30b. Hence, the CoMSIA model was chosen and its contours were explored for gaining structural insights on the triazole molecules. The CoMSIA contours helped us to understand the role of several atoms and groups of the triazole molecules in their biological activity. The possibilities for substitution in the triazole compounds that would enhance the activity were also analysed. Thus, this study paves the way for designing new antitubercular drugs in future.

scholarly journals Insights into the molecular properties underlying antibacterial activity of prenylated (iso)flavonoids against MRSA

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sylvia Kalli ◽  
Carla Araya-Cloutier ◽  
Jos Hageman ◽  
Jean-Paul Vincken
Keyword(s):  
Prediction Models ◽  
External Validation ◽  
Qsar Model ◽  
Prediction Errors ◽  
Activity Data ◽  
Gram Positive Bacteria ◽  
Level Of Activity ◽  
Formal Charge ◽  
Validation Set

AbstractHigh resistance towards traditional antibiotics has urged the development of new, natural therapeutics against methicillin-resistant Staphylococcus aureus (MRSA). Prenylated (iso)flavonoids, present mainly in the Fabaceae, can serve as promising candidates. Herein, the anti-MRSA properties of 23 prenylated (iso)flavonoids were assessed in-vitro. The di-prenylated (iso)flavonoids, glabrol (flavanone) and 6,8-diprenyl genistein (isoflavone), together with the mono-prenylated, 4′-O-methyl glabridin (isoflavan), were the most active anti-MRSA compounds (Minimum Inhibitory Concentrations (MIC) ≤ 10 µg/mL, 30 µM). The in-house activity data was complemented with literature data to yield an extended, curated dataset of 67 molecules for the development of robust in-silico prediction models. A QSAR model having a good fit (R2adj 0.61), low average prediction errors and a good predictive power (Q2) for the training (4% and Q2LOO 0.57, respectively) and the test set (5% and Q2test 0.75, respectively) was obtained. Furthermore, the model predicted well the activity of an external validation set (on average 5% prediction errors), as well as the level of activity (low, moderate, high) of prenylated (iso)flavonoids against other Gram-positive bacteria. For the first time, the importance of formal charge, besides hydrophobic volume and hydrogen-bonding, in the anti-MRSA activity was highlighted, thereby suggesting potentially different modes of action of the different prenylated (iso)flavonoids.

Developmental venous anomaly in adult patients with diffuse glioma

Neurology ◽  
2018 ◽  
Vol 92 (1) ◽  
pp. e55-e62 ◽  
Author(s):  
Alexandre Roux ◽  
Myriam Edjlali ◽  
Sayuri Porelli ◽  
Arnault Tauziede-Espariat ◽  
Marc Zanello ◽  
...  
Keyword(s):  
External Validation ◽  
Adult Patients ◽  
World Health ◽  
Diffuse Glioma ◽  
Developmental Venous Anomaly ◽  
Venous Anomaly ◽  
Control Sets ◽  
Control Set ◽  
Validation Set ◽  
Health Organization

ObjectiveTo determine the prevalence of developmental venous anomaly in adult patients with diffuse glioma.MethodsWe performed a retrospective cohort study (2010–2016) of consecutive adult patients harboring a supratentorial diffuse glioma in 2 centers: Sainte-Anne Hospital (experimental and control sets) and Pitié-Salpêtrière Hospital (external validation set). We included 219 patients with diffuse glioma (experimental set), 252 patients with brain metastasis (control set), and 200 patients with diffuse glioma (validation set). The inclusion criteria were age ≥18 years at diagnosis, histopathologic diagnosis of diffuse glioma according to the 2016 World Health Organization classification of tumors of the CNS, surgery as first-line treatment without previous oncologic treatment, available presurgical MRI performed with similar acquisition protocol, and absence of a nodular-like or a ring-like pattern of contrast enhancement on MRI that may preclude the identification of a possible developmental venous anomaly within the glioma.ResultsWe found more developmental venous anomaly in the experimental set (21.5%) than in the control set (5.2%, p < 0.001). Similarly, we found more developmental venous anomaly in the validation set (23.5%) than in the control set (5.2%, p < 0.001). There was no difference in the developmental venous anomaly prevalence between the experimental and validation sets. The developmental venous anomaly distribution was not significantly associated with histopathologic, molecular, or imaging findings of the diffuse gliomas.ConclusionsWe report and replicate in an external cohort a high prevalence of developmental venous anomaly in adult patients with diffuse glioma, which suggests a potential underlying common predisposition or a causal relationship that requires deeper investigations.

scholarly journals Exhaustive laccase-catalysed oxidation of a lignin model compound (vanillyl glycol) produces methanol and polymeric quinoid products

1985 ◽  
Vol 229 (1) ◽  
pp. 277-279 ◽  
Author(s):  
K Lundquist ◽  
P Kristersson
Keyword(s):  
Model Compound ◽  
Polymerization Process ◽  
Lignin Biodegradation ◽  
Simultaneous Formation ◽  
Initial Formation ◽  
Lignin Model Compound ◽  
Catalysed Oxidation ◽  
Visible Spectra ◽  
Lignin Model

Laccase-catalysed oxidation of the lignin-related phenol vanillyl glycol results in the initial formation of dimers and subsequent polymerization. The polymerization is accompanied by a liberation of methanol corresponding to 15-20% demethylation. Visible spectra together with reduction experiments suggest the simultaneous formation of o-quinones. The participation of quinone formation in the polymerization process and the possible role of such intermediates in lignin biodegradation is discussed.

scholarly journals Predicting Survival for Nasopharyngeal Carcinoma: Development and Validation of Nomograms With Routine Hematological Biomarkers Based on the 8th Edition of AJCC/UICC Staging System

2020 ◽  
Author(s):  
Yu Liang ◽  
Kaihua Chen ◽  
Jie Yang ◽  
Jing Zhang ◽  
Rurong Peng ◽  
...  
Keyword(s):  
Validation Cohort ◽  
External Validation ◽  
Progression Free Survival ◽  
Staging System ◽  
Tnm Staging ◽  
Prognostic Role ◽  
Tnm System ◽  
Ebv Dna ◽  
8Th Edition

Abstract BackgroundThe 8th edition of AJCC/UICC TNM staging system (TNM system) and the previous nomograms have limitations, therefore we aimed to develop and validate nomograms incorporating routine hematological biomarkers with or without EBV DNA for overall survival (OS) and progression-free survival (PFS). We also evaluated the prognostic role of EBV DNA.Material and Methods1203 patients at our hospital from 2013 to 2016 were retrospectively reviewed and divided into two parts (922 patients for primary cohort and 281 for validation cohort). Nomograms (nomogram with or without EBV DNA) were developed and compared with other models (TNM system alone, TNM system with EBV DNA), via comparison the prognostic role of EBV DNA was evaluated. Internal and external validation were performed. Risk stratification were conducted with recursive partitioning analysis.ResultsThe nomograms with EBV DNA for OS and PFS included sex, age, T category, N category, EBV DNA, albumin, neutrophil to lymphocyte ratio and lactate dehydrogenase. The nomograms without EBV DNA for OS and PFS included the same variables but without EBV DNA. The C-index for nomogram with EBV DNA was 0.715 for OS and 0.705 for PFS. For nomogram without EBV DNA, it was 0.709 and 0.700, respectively. It was 0.639 and 0.636 for TNM system alone and 0.648, 0.646 respectively for TNM system with EBV DNA. The nomograms with or without EBV DNA had better performance than both the TNM system alone and TNM system with EBV DNA, while the TNM system with EBV DNA were better than TNM system alone. The validation cohort indicates great applicability of nomograms. The patients were stratified into 4 risk groups.ConclusionThe nomograms with or without EBV DNA provide better prognostication than the TNM system and also the TNM system with EBV DNA. EBV DNA is valuable in predicting survival, but it is not suggested to incorporate EBV DNA alone to TNM system.

Directing on-surface polymerization via substrate-directed molecular template

2021 ◽  
Author(s):  
Siyi Gu ◽  
Shizhang Fu ◽  
Caimei Gong ◽  
Sihao Li ◽  
Xiaoqing Liu ◽  
...  
Keyword(s):  
Polymerization Process ◽  
Surface Polymerization ◽  
Molecular Nanostructures

Using template to control on-surface polymerization process is valuable for building functional molecular nanostructures. Here, the role of the symmetric matching between a halogen-ligand component (H2TBrPP) and substrate on the...

CDK5RAP3 as a Novel Biomarker Signature Predicting Survival and Adjuvant Chemotherapeutic benefit in Gastric Cancer

2020 ◽  
Author(s):  
Jia-Bin Wang ◽  
You-Xin Gao ◽  
Ning-Zi Lian ◽  
Yu-Bin Ma ◽  
Ping Li ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Adjuvant Chemotherapy ◽  
Cancer Patients ◽  
Cox Model ◽  
External Validation ◽  
Tumour Tissue ◽  
Tissue Samples ◽  
Significant Difference ◽  
Validation Set ◽  
Gastric Cancer Patients

Abstract Background: We previously demonstrated that CDK5RAP3 acts as a tumour suppressor in gastric cancer through negative regulation of the Wnt/β-catenin signalling pathway, but its function in chemotherapeutic responsiveness of gastric cancer has not been investigated. In this study, we aimed to examine the clinical significance of CDK5RAP3 to predict chemotherapeutic responsiveness in gastric cancer.Methods: A collection of 188 pairs of tumour tissue microarray specimens from Fujian Medical University were employed for the discovery set, and 310 tumour tissue samples of gastric cancer patients were employed for the internal validation set. Eight-five tumour tissue samples from Qinghai University Hospital were used as the external validation set 1. Transcriptomic and clinical data of 299 gastric cancer patients from TCGA were used as the external validation set 2. CDK5RAP3 expression, microsatellite instability (MSI) status, and tumour-infiltrating lymphocytes (TIL) were examined with immunohistochemistry. Clinical outcomes of patients were compared with Kaplan-Meier curves and the Cox model.Results: In a multi-centre evaluation, increased CDK5RAP3 indication of better prognosis depends mainly on MSI-L/MSS status or TILhigh. High CDK5RAP3 expression predicts sensitive therapeutic responsiveness to postoperative adjuvant chemotherapy in gastric cancer. In a stratification analysis based on CDK5RAP3 combined with TIL or MSI status, patients with CKD5RAP3low TILlow showed no significant difference in prognosis after receiving chemotherapy, whereas patients with CKD5RAP3low TILhigh, CKD5RAP3high TILlow, and CKD5RAP3high TILhigh had better responsiveness to chemotherapy. In addition, patients with CKD5RAP3high MSI-L/MSS status benefitted the most from adjuvant chemotherapy among all patients evaluated. Conclusions: CKD5RAP3 can be used as an effective marker to evaluate individualized chemotherapy regimens in gastric cancer patients dependent on their TIL and MSI status.

Retrained Classification of Tyrosinase Inhibitors and “In Silico” Potency Estimation by Using Atom-Type Linear Indices

2013 ◽  
pp. 322-427
Keyword(s):  
External Validation ◽  
Correlation Coefficients ◽  
Classification Models ◽  
Training Set ◽  
Linear Discriminant ◽  
Oecd Principles ◽  
Qsar Models ◽  
Validation Set ◽  
Global Accuracy

In this paper, the authors present an effort to increase the applicability domain (AD) by means of retraining models using a database of 701 great dissimilar molecules presenting anti-tyrosinase activity and 728 drugs with other uses. Atom-based linear indices and best subset linear discriminant analysis (LDA) were used to develop individual classification models. Eighteen individual classification-based QSAR models for the tyrosinase inhibitory activity were obtained with global accuracy varying from 88.15-91.60% in the training set and values of Matthews correlation coefficients (C) varying from 0.76-0.82. The external validation set shows globally classifications above 85.99% and 0.72 for C. All individual models were validated and fulfilled by OECD principles. A brief analysis of AD for the training set of 478 compounds and the new active compounds included in the re-training was carried out. Various assembled multiclassifier systems contained eighteen models using different selection criterions were obtained, which provide possibility of select the best strategy for particular problem. The various assembled multiclassifier systems also estimated the potency of active identified compounds. Eighteen validated potency models by OECD principles were used.

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