Evolution of Optimal Descriptors

2016 ◽  
Vol 1 (2) ◽  
pp. 52-71
Author(s):  
Alla P. Toropova ◽  
Andrey A. Toropov
Keyword(s):  
Monte Carlo ◽  
Medicinal Chemistry ◽  
Monte Carlo Technique ◽  
Coral Software ◽  
Quantitative Structure ◽  
Structure Property ◽  
Qsar Analysis

The quantitative structure - property / activity relationships (qsprs/qsars) analysis of different substances is an important area in mathematical and medicinal chemistry. The evolution and logic of optimal descriptors which are based on the monte carlo technique in the role of a tool of the qspr/qsar analysis is discussed. A group of examples of application of the optimal descriptors which are calculated with the coral software (http://www.insilico.eu/coral) for prediction of physicochemical and biochemical endpoints of potential therapeutical agents are presented. The perspectives and limitations of the optimal descriptors are listed. The attempt of the systematization of the models calculated with the coral software is the aim of this work.

Application of the Monte Carlo Method for the Prediction of Behavior of Peptides

2019 ◽  
Vol 20 (12) ◽  
pp. 1151-1157 ◽  
Author(s):  
Alla P. Toropova ◽  
Andrey A. Toropov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Natural Sciences ◽  
Monte Carlo Technique ◽  
Quantitative Structure ◽  
Structure Property ◽  
The Monte Carlo Method ◽  
Modern Natural

Prediction of physicochemical and biochemical behavior of peptides is an important and attractive task of the modern natural sciences, since these substances have a key role in life processes. The Monte Carlo technique is a possible way to solve the above task. The Monte Carlo method is a tool with different applications relative to the study of peptides: (i) analysis of the 3D configurations (conformers); (ii) establishment of quantitative structure – property / activity relationships (QSPRs/QSARs); and (iii) development of databases on the biopolymers. Current ideas related to application of the Monte Carlo technique for studying peptides and biopolymers have been discussed in this review.

QSPR/QSAR Analyses by Means of the CORAL Software

2015 ◽  
pp. 560-585 ◽  
Author(s):  
Andrey A. Toropov ◽  
Alla P. Toropova ◽  
Emilio Benfenati ◽  
Orazio Nicolotti ◽  
Angelo Carotti ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Molecular Graph ◽  
Qsar Model ◽  
Mathematical Function ◽  
Coral Software ◽  
Structure Property ◽  
Qsar Analysis ◽  
The Monte Carlo Method ◽  
Optimal Descriptor ◽  
New Ideas

In this chapter, the methodology of building up quantitative structure—property/activity relationships (QSPRs/QSARs)—by means of the CORAL software is described. The Monte Carlo method is the basis of this approach. Simplified Molecular Input-Line Entry System (SMILES) is used as the representation of the molecular structure. The conversion of SMILES into the molecular graph is available for QSPR/QSAR analysis using the CORAL software. The model for an endpoint is a mathematical function of the correlation weights for various features of the molecular structure. Hybrid models that are based on features extracted from both SMILES and a graph also can be built up by the CORAL software. The conceptually new ideas collected and revealed through the CORAL software are: (1) any QSPR/QSAR model is a random event; and (2) optimal descriptor can be a translator of eclectic information into an endpoint prediction.

The role of the dominant descriptor in targeted quantitative structure property relationships

2007 ◽  
Vol 62 (22) ◽  
pp. 6222-6233 ◽  
Author(s):  
Mordechai Shacham ◽  
Olaf Kahrs ◽  
Georgi St. Cholakov ◽  
Roumiana P. Stateva ◽  
Wolfgang Marquardt ◽  
...  
Keyword(s):  
Quantitative Structure ◽  
Structure Property ◽  
Structure Property Relationships ◽  
Quantitative Structure Property Relationships

scholarly journals Computer Aided Drug Designing

2017 ◽  
Vol 6 (1) ◽  
pp. 1433
Author(s):  
Vijay Kumar Sehgal ◽  
Supratik Das ◽  
Anand Vardhan
Keyword(s):  
Drug Design ◽  
Medical Science ◽  
Quantitative Structure ◽  
Structure Property ◽  
Structure Based Drug Design ◽  
Safety Issues ◽  
Computer Aided ◽  
Drug Designing ◽  
Quantitative Structure Property Relationships

Designing of drugs and their development are a time and resource consuming process. There is an increasing effort to introduce the role of computational approach to chemical and biological space in order to organise the design and development of drugs and their optimisation. The role of Computer Aided Drug Designing (CADD) are nowadays expressed in Nanotechnology, Molecular biology, Biochemistry etc. It is a diverse discipline where various forms of applied and basic researches are interlinked with each other. Computer aided or in Silico drug designing is required to detect hits and leads. Optimise/ alter the absorption, distribution, metabolism, excretion and toxicity profile and prevent safety issues. Some commonly used computational approaches include ligand-based drug design, structure-based drug design, and quantitative structure-activity and quantitative structure-property relationships. In today's world, due to an avid interest of regulatory agencies and, even pharmaceutical companies in advancing drug discovery and development process by computational means, it is expected that its power will grow as technology continues to evolve. The main purpose of this review article is to give a brief glimpse about the role Computer Aided Drug Design has played in modern medical science and the scope it carries in the near future, in the service of designing newer drugs along with lesser expenditure of time and money.

scholarly journals QSPR/QSAR Analyses by Means of the CORAL Software

2017 ◽  
pp. 929-955
Author(s):  
Andrey A. Toropov ◽  
Alla P. Toropova ◽  
Emilio Benfenati ◽  
Orazio Nicolotti ◽  
Angelo Carotti ◽  
...  
Keyword(s):  
Molecular Structure ◽  
Molecular Graph ◽  
Qsar Model ◽  
Mathematical Function ◽  
Coral Software ◽  
Structure Property ◽  
Qsar Analysis ◽  
The Monte Carlo Method ◽  
Optimal Descriptor ◽  
New Ideas

In this chapter, the methodology of building up quantitative structure—property/activity relationships (QSPRs/QSARs)—by means of the CORAL software is described. The Monte Carlo method is the basis of this approach. Simplified Molecular Input-Line Entry System (SMILES) is used as the representation of the molecular structure. The conversion of SMILES into the molecular graph is available for QSPR/QSAR analysis using the CORAL software. The model for an endpoint is a mathematical function of the correlation weights for various features of the molecular structure. Hybrid models that are based on features extracted from both SMILES and a graph also can be built up by the CORAL software. The conceptually new ideas collected and revealed through the CORAL software are: (1) any QSPR/QSAR model is a random event; and (2) optimal descriptor can be a translator of eclectic information into an endpoint prediction.

scholarly journals The Monte Carlo approach to model and predict the melting point of imidazolium ionic liquids using hybrid optimal descriptors

RSC Advances ◽  
2021 ◽  
Vol 11 (54) ◽  
pp. 33849-33857
Author(s):  
Shahram Lotfi ◽  
Shahin Ahmadi ◽  
Parvin Kumar
Keyword(s):  
Monte Carlo ◽  
Ionic Liquids ◽  
Melting Point ◽  
Quantitative Structure ◽  
Structure Property ◽  
Melting Points ◽  
Data Set ◽  
Imidazolium Ionic Liquids ◽  
Monte Carlo Approach ◽  
Structure Property Relationship

The melting points of imidazolium ILs are studied employing a quantitative structure–property relationship (QSPR) approach to develop a model for predicting the melting points of a data set of imidazolium ILs.

The Monte Carlo Method as a Tool to Build up Predictive QSPR/QSAR

2020 ◽  
Vol 16 (3) ◽  
pp. 197-206 ◽  
Author(s):  
Andrey A. Toropov ◽  
Alla P. Toropova
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Target Function ◽  
Statistical Characteristics ◽  
Mathematical Function ◽  
Coral Software ◽  
Structure Property ◽  
Molecular Features ◽  
The Monte Carlo Method ◽  
Correlation Weights

Background: The Monte Carlo method has a wide application in various scientific researches. For the development of predictive models in a form of the quantitative structure-property / activity relationships (QSPRs/QSARs), the Monte Carlo approach also can be useful. The CORAL software provides the Monte Carlo calculations aimed to build up QSPR/QSAR models for different endpoints. Methods: Molecular descriptors are a mathematical function of so-called correlation weights of various molecular features. The numerical values of the correlation weights give the maximal value of a target function. The target function leads to a correlation between endpoint and optimal descriptor for the visible training set. The predictive potential of the model is estimated with the validation set, i.e. compounds that are not involved in the process of building up the model. Results: The approach gave quite good models for a large number of various physicochemical, biochemical, ecological, and medicinal endpoints. Bibliography and basic statistical characteristics of several CORAL models are collected in the present review. In addition, the extended version of the approach for more complex systems (nanomaterials and peptides), where behaviour of systems is defined by a group of conditions besides the molecular structure is demonstrated. Conclusion: The Monte Carlo technique available via the CORAL software can be a useful and convenient tool for the QSPR/QSAR analysis.

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