Journal ArticleDOI
Beware of q2
Reads0
Chats0
TLDR
It is argued that the high value of LOO q2 appears to be the necessary but not the sufficient condition for the model to have a high predictive power, which is the general property of QSAR models developed using LOO cross-validation.Abstract:
Validation is a crucial aspect of any quantitative structure-activity relationship (QSAR) modeling. This paper examines one of the most popular validation criteria, leave-one-out cross-validated R2 (LOO q2). Often, a high value of this statistical characteristic (q2 > 0.5) is considered as a proof of the high predictive ability of the model. In this paper, we show that this assumption is generally incorrect. In the case of 3D QSAR, the lack of the correlation between the high LOO q2 and the high predictive ability of a QSAR model has been established earlier [Pharm. Acta Helv. 70 (1995) 149; J. Chemomet. 10(1996)95; J. Med. Chem. 41 (1998) 2553]. In this paper, we use two-dimensional (2D) molecular descriptors and k nearest neighbors (kNN) QSAR method for the analysis of several datasets. No correlation between the values of q2 for the training set and predictive ability for the test set was found for any of the datasets. Thus, the high value of LOO q2 appears to be the necessary but not the sufficient condition for the model to have a high predictive power. We argue that this is the general property of QSAR models developed using LOO cross-validation. We emphasize that the external validation is the only way to establish a reliable QSAR model. We formulate a set of criteria for evaluation of predictive ability of QSAR models.read more
Citations
More filters
Journal ArticleDOI
Prediction of dielectric constant of ionic liquids
TL;DR: In this paper, a new approach based on the quantitative structure-property relationship (QSPR) method is presented to find relationship between structural features and dielectric constant value.
Journal ArticleDOI
Mutatomics analysis of the systematic thermostability profile of Bacillus subtilis lipase A.
TL;DR: In this paper, a new characterization method was proposed to describe structural variations upon protein residue mutation, and the generated descriptors were then statistically correlated with protein thermostability change associated with the mutation based on a large panel of structure-solved, melting temperature known protein mutation data.
Journal ArticleDOI
Data Science Meets Physical Organic Chemistry.
TL;DR: In this article, the authors investigated whether enantioselectivity data from a reaction can be quantitatively connected to the attributes of reaction components, such as catalyst and substrate structural features, to harness data for asymmetric catalyst design.
Journal ArticleDOI
Perturbation-Theory and Machine Learning (PTML) Model for High-Throughput Screening of Parham Reactions: Experimental and Theoretical Studies.
Lorena Simón-Vidal,Oihane Garcia-Calvo,Uxue Oteo,Sonia Arrasate,Esther Lete,Nuria Sotomayor,Humberto González-Díaz,Humberto González-Díaz +7 more
TL;DR: This work has developed a perturbation-theory and machine learning (PTML) model combining perturbations theory (PT) and ML algorithms for predicting the yield of a given reaction, and reports a comparative study of linear versus nonlinear PTML models based on artificial neural network (ANN) algorithms.
Journal ArticleDOI
Development of Prediction Models on Base-Catalyzed Hydrolysis Kinetics of Phthalate Esters with Density Functional Theory Calculation.
TL;DR: Qualitative structure-activity relationship models were developed that can differentiate PAEs with the departure of the leaving group as the rate-determining step in the hydrolysis and estimate kB values, which provides a promising way to predict hydrolytic kinetics of PAEs.
References
More filters
Journal ArticleDOI
Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins.
TL;DR: The main features of the CoMFA approach, exemplified by analyses of the affinities of 21 varied steroids to corticosteroid and testosterone-binding globulins, and a number of advances in the methodology of molecular graphics are described.
Book
Substituent constants for correlation analysis in chemistry and biology
Corwin Hansch,Albert J. Leo +1 more
TL;DR: In this paper, the book is the window to get in the world and you can open the world easily, and these wise words are really familiar with you, so bring home now the book enPDFd substituent constants for correlation analysis in chemistry and biology to be your sources when going to read.