Monte Carlo Method Based QSAR Studies of Mer Kinase Inhibitors in Compliance with OECD Principles

Drug Research ◽  
2017 ◽  
Vol 68 (04) ◽  
pp. 189-195 ◽  
Author(s):  
Parvin Kumar ◽  
Ashwani Kumar
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Kinase Inhibitors ◽  
Structural Characteristics ◽  
Predictive Ability ◽  
Qsar Model ◽  
Correlation Technique ◽  
Qsar Studies ◽  
Oecd Principles ◽  
Qsar Models

AbstractMonte Carlo method based QSAR studies for inhibitors of Mer kinase, a potential novel target for cancer treatment, has been carried out using balance of correlation technique. The data was divided into three random and dissimilar splits and hybrid optimal descriptors derived from SMILES and hydrogen filled graphs based notations were used for construction of QSAR models. The generated models have good fitting ability, robustness, generalizability and internal predictive ability. The external predictive ability has been tested using multiple criteria and described models exhibited good performance in all of these tests. The values of R2, Q2, R2 test, Q2 test, R2 m and ∆R2 m for the best model are 0.9502, 0.9388, 0.9469, 0.9083, 0.7534 and 0.0894 respectively. Also, the structural characteristics responsible for enhancement and reduction of activity have been extracted. Further, the agreement with the OECD rules for QSAR model has been discussed.

scholarly journals QSAR Models for Nitrogen Containing Monophosphonate and Bisphosphonate Derivatives as Human Farnesyl Pyrophosphate Synthase Inhibitors Based on Monte Carlo Method

Drug Research ◽  
2018 ◽  
Vol 69 (03) ◽  
pp. 159-167 ◽  
Author(s):  
Parvin Kumar ◽  
Ashwani Kumar ◽  
Jayant Sindhu ◽  
Sohan Lal
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Mevalonate Pathway ◽  
Predictive Ability ◽  
Correlation Technique ◽  
Farnesyl Pyrophosphate ◽  
Farnesyl Pyrophosphate Synthase ◽  
End Point ◽  
Qsar Models ◽  
Human Farnesyl Pyrophosphate Synthase

AbstractHuman farnesyl pyrophosphate synthase (hFPPS) is a well-settled therapeutic target and it is an enzyme of the mevalonate pathway which catalyzes the biosynthesis of the C-15 isoprenoid farnesyl pyrophosphate. QSAR studies by using Monte Carlo method for human farnesyl pyrophosphate synthase inhibitors has been carried out using balance of correlation technique with Index of ideality correlation. For construction of QSAR models, six random splits were prepared from the data of 73 phosphonates and hybrid optimal descriptors procured from graph (HFG) and SMILES based notations were employed. The developed QSAR models have robustness, good fitting ability, generalizability and internal predictive ability. The external predictive ability has been certified by testing various precedents. The values of R2, IIC, Q2 and ∆R2 m for the best model are 0.9304, 0.9614, 0.9061 and 0.0861 respectively. The developed QSAR models met with the specified standards given in OECD guideline and applicability domain. The structural feature promoters for the end point increase and promoters for end point decrease have been extracted. The predicted pIC50 for the new proposed compounds have also been reported.

Interpretable SMILES-based QSAR model of inhibitory activity of sirtuins 1 and 2

2020 ◽  
Vol 23 ◽  
Author(s):  
Apilak Worachartcheewan ◽  
Alla P. Toropova ◽  
Andrey A. Toropov ◽  
Reny Pratiwi ◽  
Virapong Prachayasittikul ◽  
...  
Keyword(s):  
Histone Deacetylases ◽  
Rational Design ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Sirtuin 1 ◽  
Data Set ◽  
Functional Roles ◽  
Molecular Features ◽  
Oecd Principles ◽  
Qsar Models

Background: Sirtuin 1 (Sirt1) and sirtuin 2 (Sirt2) are NAD+ -dependent histone deacetylases which play important functional roles in removal of the acetyl group of acetyl-lysine substrates. Considering the dysregulation of Sirt1 and Sirt2 as etiological causes of diseases, Sirt1 and Sirt2 are lucrative target proteins for treatment, thus there has been great interest in the development of Sirt1 and Sirt2 inhibitors. Objective: This study compiled the bioactivity data of Sirt1 and Sirt2 for the construction of quantitative structure-activity relationship (QSAR) models in accordance with the OECD principles. Method: Simplified molecular input line entry system (SMILES)-based molecular descriptors were used to characterize the molecular features of inhibitors while the Monte Carlo method of the CORAL software was employed for multivariate analysis. The data set was subjected to 3 random splits in which each split separated the data into 4 subsets consisting of training, invisible training, calibration and external sets. Results: Statistical indices for the evaluation of QSAR models suggested good statistical quality for models of Sirt1 and Sirt2 inhibitors. Furthermore, mechanistic interpretation of molecular substructures that are responsible for modulating the bioactivity (i.e. promoters of increase or decrease of bioactivity) was extracted via the analysis of correlation weights. It exhibited molecular features involved Sirt1 and Sirt2 inhibitors. Conclusion: It is anticipated that QSAR models presented herein can be useful as guidelines in the rational design of potential Sirt1 and Sirt2 inhibitors for the treatment of Sirtuin-related diseases.

scholarly journals Monte-Carlo method-based QSAR model to discover phytochemical urease inhibitors using SMILES and GRAPH descriptors

2021 ◽  
pp. 1-10
Author(s):  
Kumar Sambhav Chopdar ◽  
Ganesh Chandra Dash ◽  
Pranab Kishor Mohapatra ◽  
Binata Nayak ◽  
Mukesh Kumar Raval
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Qsar Model ◽  
Urease Inhibitors

2D and 3D QSAR Studies on a Series of Antichagasic Fenarimol Derivatives

2017 ◽  
Vol 2 (1) ◽  
pp. 44-63
Author(s):  
Anacleto S. de Souza ◽  
Leonardo G. Ferreira ◽  
Adriano D. Andricopulo
Keyword(s):  
Neglected Tropical Diseases ◽  
Public Health Problem ◽  
Predictive Ability ◽  
3D Qsar ◽  
Structural Features ◽  
Field Analysis ◽  
Global Public Health ◽  
Qsar Studies ◽  
Qsar Models ◽  
2D And 3D

Chagas disease is one of the most important neglected tropical diseases. Endemic in Latin America, the disease is a global public health problem, affecting several countries in North America, Europe, Asia and Oceania. The disease affects around 8-10 million people worldwide and the limited treatments available present low efficacy and severe side effects, highlighting the urgent need for new therapeutic options. In this work, the authors developed QSAR models for a series of fenarimol derivatives exhibiting anti-T. cruzi activity. The models were constructed using the Hologram QSAR (HQSAR), Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods. The QSAR models presented substantial predictive ability for a series of test set compounds (HQSAR, r2pred = 0.66; CoMFA, r2pred = 0.82; and CoMSIA, r2pred = 0.76), and were valuable to identify key structural features related to the observed trypanocidal activity. The results reported herein are useful for the design of novel derivatives having improved antichagasic properties.

scholarly journals 2D and 3D QSAR Studies on a Series of Antichagasic Fenarimol Derivatives

2017 ◽  
pp. 956-977
Author(s):  
Anacleto S. de Souza ◽  
Leonardo G. Ferreira ◽  
Adriano D. Andricopulo
Keyword(s):  
Neglected Tropical Diseases ◽  
Public Health Problem ◽  
Predictive Ability ◽  
3D Qsar ◽  
Structural Features ◽  
Field Analysis ◽  
Global Public Health ◽  
Qsar Studies ◽  
Qsar Models ◽  
2D And 3D

Chagas disease is one of the most important neglected tropical diseases. Endemic in Latin America, the disease is a global public health problem, affecting several countries in North America, Europe, Asia and Oceania. The disease affects around 8-10 million people worldwide and the limited treatments available present low efficacy and severe side effects, highlighting the urgent need for new therapeutic options. In this work, the authors developed QSAR models for a series of fenarimol derivatives exhibiting anti-T. cruzi activity. The models were constructed using the Hologram QSAR (HQSAR), Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods. The QSAR models presented substantial predictive ability for a series of test set compounds (HQSAR, r2pred = 0.66; CoMFA, r2pred = 0.82; and CoMSIA, r2pred = 0.76), and were valuable to identify key structural features related to the observed trypanocidal activity. The results reported herein are useful for the design of novel derivatives having improved antichagasic properties.

QSAR STUDIES ON PYRAZOLO [1, 5-A] PYRIMIDINE-BASED PIM-1 KINASE INHIBITORS

INDIAN DRUGS ◽  
2016 ◽  
Vol 53 (11) ◽  
pp. 12-19
Author(s):  
M. C Sharma ◽  
Keyword(s):  
Predictive Power ◽  
Kinase Inhibitors ◽  
Kinase Inhibitor ◽  
Qsar Model ◽  
Pyrimidine Derivatives ◽  
Structural Requirements ◽  
Qsar Studies ◽  
Structure Activity ◽  
Quantitative Structure Activity Relationships ◽  
External Test

Quantitative structure-activity relationships (QSAR) have been applied in order to explain the structural requirements of Pim-1 kinase activity of pyrazolo [1, 5-a] pyrimidine derivatives. The QSAR model was an internal predictive power (q2 = 0.7866) of 78% and a predictivity for the external test set (pred_r2 = 0.7742) of about 77%. The developed significant QSAR model indicates that HUMO energy, SsOHcount, SsNH2Count and T_O_O_4 potential of whole molecule play an important role in Pim-1 kinase inhibitor of pyrimidine. Consequently, these results can be useful in identifying the structural requirements of pyrazolo [1, 5-a] pyrimidine derivatives and helpful for better understanding the Pim-1 kinase. Eventually, they provide a beneficial basis to design new and more potent inhibitors of Pim-1 kinase.

On Strain-Induced Grain Growth Using Modified Monte Carlo Method and Digital Image Correlation Technique

2007 ◽  
Vol 558-559 ◽  
pp. 1121-1126 ◽  
Author(s):  
Wei Ling Lin ◽  
Jui Chao Kuo
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Digital Image Correlation ◽  
Grain Growth ◽  
Digital Image ◽  
Image Correlation ◽  
Correlation Technique ◽  
Strain Mapping ◽  
2D Strain ◽  
Dic Technique

In this study the strain-induced grain growth was simulated on an aluminum bicrystal by using channel-die compression. After compression of the bicrystal up to 5% deformation the strain mapping were characterized by using digital image correlation (DIC) technique and the 2D strain filed provided data to simulate grain growth using a modified Monte Carlo method. The strain-induced grain growth on grain boundary was simulated and compared with experiment after annealing at 450°C for 4 hours. The relation between the deformation heterogeneity and the grain growth was discussed in this work.

Molecular Docking and 3D-QSAR Studies of 4-Phenylpiperidine Derivatives as μ-Opioid Agonists

2011 ◽  
Vol 361-363 ◽  
pp. 263-267 ◽  
Author(s):  
Ming Liu ◽  
Wen Xiang Hu ◽  
Xiao Li Liu
Keyword(s):  
Electrostatic Interactions ◽  
Biological Activities ◽  
3D Qsar ◽  
Qsar Model ◽  
Field Analysis ◽  
Qsar Studies ◽  
Chemical Structures ◽  
Opioid Agonists ◽  
Qsar Models ◽  
Leave One Out

A predictive 3D-QSAR model which correlates the biological activities with the chemical structures of a series of 4-phenylpiperidine derivatives as μ opioid agonists was developed by means of comparative molecular field analysis (CoMFA). The stabilities of the 3D-QSAR models were verified by the leave-one-out cross-validation method. Moreover, the predictive capabilities of the models were validated by an external test set. Best predictions were obtained with CoMFA standard model(q2=0.504, N=6, r2=0.968) which revealed how steric and electrostatic interactions contribute to agonists bioactivities, and provided us with important information to understand the interaction of agonists and μ opioid receptor .

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