[Show abstract][Hide abstract] ABSTRACT: 3D shape- or volume-based virtual screening is a broadly used approach in drug discovery. In recent years a large number of publications have appeared in which these tools were compared to not only competitive methods but to docking studies as well. Studies often showed that the effectiveness of docking could be highly variable due to a large number of possible confounding factors, while ligand-based, shape-based approaches were more consistent. Here, we describe a novel, fully flexible shape-based virtual screening algorithm that does not require previous 3D conformation or conformer generation. Due to its solid consistency it can easily be used on desktop computers by non-expert scientists. The algorithm is demonstrated in a study for the investigation of ß-secretase inhibitors.
Journal of Chemical Information and Modeling 02/2014; 54(4). DOI:10.1021/ci400620f · 3.74 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The linear relationship is still the most important tool for establishing connection between correlating features, properties.
The name “parameter-free linear relationship” (PFLR) stands for a new formalism, a generalized interpolation scheme, which
can be readily used for predicting biological activities or other properties in 3D QSAR manner. Our studies demonstrate the
good predictive power of PFLR even when used with a simple set of 3D molecular descriptors without constructing a grid representation
of the features. PFLR allows completing most of the computations solely in the space of descriptors, without experimental
training data, which, however, bears no importance in the case of 3D QSAR but might be advantageous in other areas where multidimensional
linear regression or partial least squares based methods are applicable.
[Show abstract][Hide abstract] ABSTRACT: Most of the drug molecules exhibit their biological activity through binding to the target protein. When the D structure of the binding site is unknown, pure ligand-based approaches are often used to perceive the 3D pharmacophore. However, dealing with conformational flexibility of ligands in such methods is still in the frontline of the current research. The special thermodynamic properties of the binding of flexible molecules, as derived here, show that the probability of the bioactive conformations in solution can determine the likelihood of binding. The binding activities can be obtained experimentally, while the probability of conformations in solution can be computed. Our present paper discusses the thermodynamic basis of performing 3D QSAR studies on molecules, with considerable conformational flexibility. In addition, we supply an algorithm to locate the bioactive conformations. The work is initiated to find the binding conformation of the therapeutically promising mucin epitope pentapeptides.
[Show abstract][Hide abstract] ABSTRACT: In the field of computational chemistry it is usual to have only a partial set of structural information about compounds, like the connectivity or the formula. Individual studies can easily be performed using ‘human interfaces’ for building input structures. However, automatic, ‘batch’ processes cannot be applied on a large number of molecules if they imply human intervention. Studies, like QSAR, pharamacophore analysis, reaction prediction might need full, complete 3D information for the compounds of interest. The widespread tools used for structure determination (force-fields or quantum chemical methods) even require a complete set of initial 3D coordinates.Our approach intends on generating globally valid set of 3D coordinates for small and medium sized molecules, based on local structural criteria. Over against iterative, backtrack based structure predicting algorithms, our method is capable of satisfying partially inconsistent requirements. Such situations are common for structures holding polycyclic, rigid details.Goals mentioned above can be achieved using coordinates interpreted in a space with a Minkowski metric. Our coordinate assignment process is divided into the following parts: (I) Automatic generation of distance criteria based on chemically relevant local properties, such as bond stretches, bond angles, dihedral angles, etc. (II) Multi-dimensional coordinate assignment which fulfills all the criteria. (III) Geometry optimization using a force field extended to the multi-dimensional Minkowski space. The optimization eliminates the over-3D components and yields the 3D coordinates.
Journal of Molecular Structure THEOCHEM 12/2003; s 666–667:51–59. DOI:10.1016/j.theochem.2003.08.013 · 1.37 Impact Factor