Current Mathematical Methods Used in QSAR/QSPR Studies

نویسندگان

  • Peixun Liu
  • Wei Long
چکیده

This paper gives an overview of the mathematical methods currently used in quantitative structure-activity/property relationship (QASR/QSPR) studies. Recently, the mathematical methods applied to the regression of QASR/QSPR models are developing very fast, and new methods, such as Gene Expression Programming (GEP), Project Pursuit Regression (PPR) and Local Lazy Regression (LLR) have appeared on the QASR/QSPR stage. At the same time, the earlier methods, including Multiple Linear Regression (MLR), Partial Least Squares (PLS), Neural Networks (NN), Support Vector Machine (SVM) and so on, are being upgraded to improve their performance in QASR/QSPR studies. These new and upgraded methods and algorithms are described in detail, and their advantages and disadvantages are evaluated and discussed, to show their application potential in QASR/QSPR studies in the future.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A novel topological descriptor based on the expanded wiener index: Applications to QSPR/QSAR studies

In this paper, a novel topological index, named M-index, is introduced based on expanded form of the Wiener matrix. For constructing this index the atomic characteristics and the interaction of the vertices in a molecule are taken into account. The usefulness of the M-index is demonstrated by several QSPR/QSAR models for different physico-chemical properties and biological activities of a large...

متن کامل

QSPR Analysis with Curvilinear Regression Modeling and Topological Indices

Topological indices are the real number of a molecular structure obtained via molecular graph G. Topological indices are used for QSPR, QSAR and structural design in chemistry, nanotechnology, and pharmacology. Moreover, physicochemical properties such as the boiling point, the enthalpy of vaporization, and stability can be estimated by QSAR/QSPR models. In this study, the QSPR (Quantitative St...

متن کامل

7 . Orthogonalization methods in QSPR - QSAR Studies

We discuss some features of the orthogonalization methods commonly applied to QSPR QSAR studies. We outline the well known multivariable linear regression analysis in vector form in order to compare mainly Randic and Gram-Schmidt orthogonalization procedures and also cast the basis for other approaches like Löwdin’s one. We expect that present review may become the starting point for future dev...

متن کامل

Yoctosecond Quantitative Structure-Activity Relationship (QSAR) and Quantitative Structure-Property Relationship (QSPR) under Synchrotron Radiations Studies for Prediction of Solubility of Anti–Cancer Nano Drugs in Aqueous Solutions Using Genetic Function Approximation (GFA) Algorithm

Yoctosecond Quantitative Structure–Activity Relationship (QSAR) and Quantitative Structure-Property Relationship (QSPR) under synchrotron radiations using Genetic Function Approximation (GFA) algorithm studies are suggested for the prediction of solubility of anti–cancer Nano drugs in aqueous solutions in yoctosecond [1-16]. Ab initio and density functional theories were used to calculate some ...

متن کامل

How the energy evaluation method used in the geometry optimization step affect the quality of the subsequent QSAR/QSPR models

The quantitative influence of the choice of energy evaluation method used in the geometry optimization step prior to the calculation of molecular descriptors in QSAR and QSPR models was investigated. A total of 11 energy evaluation methods on three molecular datasets (toxicological compounds, aromatic compounds and PPARgamma agonists) were studied. The methods employed were: MMFF94 s, MM3* with...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • International Journal of Molecular Sciences

دوره 10  شماره 

صفحات  -

تاریخ انتشار 2009