Untitled

The Flexible Ligand Unified Force Field (FLUFF) is a molecular mechanistic superposition algorithm utilizing a template structure, on top of which the ligand(s) are superimposed. FLUFF enables a flexible semiautomatic superimposition in which the ligand and the template are allowed to seek the best common conformation, which can then be used to predict the biological activity by Boundless Adaptive Localized Ligand (BALL). In BALL, the similarity of the electrostatic and van der Waals volumes of the template and ligand is evaluated using the template-based coordinate system which makes the FLUFF-BALL invariant as to the rotations and translations of the global coordinate system. When tested using the CBG (corticosteroid binding globulin) affinities of 31 benchmark steroids, the FLUFF-BALL technique produced results comparable to standard 3D-QSAR methods. Supplementary test calculations were performed with five additional data sets. Due to its high level of automation and high throughput, the FLUFF-BALL is highly suitable for use in drug design and in scanning of large molecular libraries.

Section: Introductionmentioning

confidence: 99%

FLUFF-BALL, A Template-Based Grid-Independent Superposition and QSAR Technique: Validation Using a Benchmark Steroid Data Set

Korhonen

Tuppurainen

Laatikainen

et al. 2003

“…That is the price that one must pay by requiring the detailed characterization of a three-dimensional molecular property field, whether it is steric, electrostatic, or hydrophobic. There have, however, been a number of characterizations − dependent upon three-dimensional structure that capture molecular features in ways not requiring an alignment or superposition step for the assignment of molecular similarity. The alignment-free procedures also generate a relatively small set of three-dimensional descriptors, thus enabling greater ease of statistical analysis.…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Moments of Molecular Property Fields

Silverman

2000

Descriptors that capture certain three-dimensional molecular features and do not require molecular superposition or alignment for the assignment of molecular similarity have recently been proposed and investigated. Among these, moments of molecular features have been utilized in the QSAR of several molecular series. The present work examines certain formal aspects of the use of moment expansions for which the zero-order moment of a property field is nonvanishing. The first-order term of such moment expansion is then dependent upon the origin of expansion, and it is pointed out that expansion about the molecular centroid is descriptive of first-order differences about the property-field mean. For a hydrophobic property field, this first-order term is just the Eisenberg hydrophobic moment. Second-order moments about the centroid can be written as components of the WHIM covariant matrix. Moment expansions are also performed about the property-field center in analogy with expansions about the center of mass. For such expansion, a set of descriptors consisting of moments of the molecular density and of a molecular hydrophobic property field as well as of related quantities are used in a QSAR of the binding of 74 polyhalogenated aromatic molecules to the Ah cystolic receptor. This QSAR has been named CoMMA2 to distinguish it from CoMMA, for which the zero-order moment of the expansion vanishes.

“…Spectroscopic QSAR Methods. A set of QSAR methods have recently been put forward in which vibration frequencies (EVA, eigenvalue, i.e., vibrational normal mode in this context), − MO energies (EEVA, electronic eigenvalue), − and NMR chemical shifts (CoSA, comparative spectra analysis and its modifications − ) are used to derive QSAR descriptors. It has been shown that spectroscopic methods can provide robust, predictive QSAR models for a large number of biological data sets.…”

Section: Introductionmentioning

confidence: 99%

Spectroscopic QSAR Methods and Self-Organizing Molecular Field Analysis for Relating Molecular Structure and Estrogenic Activity

Asikainen

Ruuskanen

Tuppurainen

2003

The performance of three "spectroscopic" quantitative structure-activity relationship (QSAR) methods (eigenvalue (EVA), electronic eigenvalue (EEVA), and comparative spectra analysis (CoSA)) for relating molecular structure and estrogenic activity are critically evaluated. The methods were tested with respect to the relative binding affinities (RBA) of a diverse set of 36 estrogens previously examined in detail by the comparative molecular field analysis method. The CoSA method with (13)C chemical shifts appears to provide a predictive QSAR model for this data set. EEVA (i.e., molecular orbital energy in this context) is a borderline case, whereas the performances of EVA (i.e., vibrational normal mode) and CoSA with (1)H shifts are substandard and only semiquantitative. The CoSA method with (13)C chemical shifts provides an alternative and supplement to conventional 3D QSAR methods for rationalizing and predicting the estrogenic activity of molecules. If CoSA is to be applied to large data sets, however, it is desirable that the chemical shifts are available from common databases or, alternatively, that they can be estimated with sufficient accuracy using fast prediction schemes. Calculations of NMR chemical shifts by quantum mechanical methods, as in this case study, seem to be too time-consuming at this moment, but the situation is changing rapidly. An inherent shortcoming common to all spectroscopic QSAR methods is that they cannot take the chirality of molecules into account, at least as formulated at present. Moreover, the symmetry of molecules may cause additional problems. There are three pairs of enantiomers and nine symmetric (C(2) or C(2)(v)) molecules present in the data set, so that the predictive ability of full 3D QSAR methods is expected to be better than that of spectroscopic methods. This is demonstrated with SOMFA (self-organizing molecular field analysis). In general, the use of external test sets with randomized data is encouraged as a validation tool in QSAR studies.