Hologram QSAR models

In 2007, Moda et al. [60] developed a set of Hologram QSAR models for a much smaller data set of 250 molecules in comparison to the above-discussed models. They found that using all atoms, bonds, connections, and chirality to define molecular fragments led to a set of encouraging models and the best one was achieved when the fragment size was from 4 to 7, which had q2 of 0.7 and r2 of 0.93. This model was too good to be true since the standard error was only 7.60, much smaller than the average experimental error, which is 14.5 based on 367 experimental data [55]. 

Moda, T.L., Montanari, C.A., Andricopulo, A.D. Hologram QSAR model for the prediction of human oral bioavailability. Bioorg. Med. Chem. 2007, 15, 7738-45. 

We have evaluated three different techniques to generate QSAR models, namely Comparative Molecular Field Analysis (CoMFA), Comprehensive Descriptors for Structural and Statistical Analysis (CODESSA), and Hologram QSAR (HQSAR). More specifically they were evaluated for their utility (predictivity, speed, accuracy, and reproducibility) to predict ER binding activity quantitatively (Tong et al., 1998 Shi et al., 2001). Common to the three QSAR methods is the... 

The methods applied in recent years by various groups to construct QSAR models for ART and analogues include docking calculations to heme [104, 105], CoMFA [106-109] and hologram QSAR [108] as well as the hypothetical active-site lattice (HASL) approach [107], self-organizing maps of the molecular electrostatic potential [110], quantum-similarity measures [111] and topological molecular connectivity descriptors [112]. 

---