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Journal ArticleDOI

New developments in PEST shape/property hybrid descriptors

01 Feb 2003-Journal of Computer-aided Molecular Design (Kluwer Academic Publishers)-Vol. 17, Iss: 2, pp 231-240
TL;DR: The use of the RECON/PEST methodology in a virtual high-throughput mode, as well as the use of TAE properties for molecular surface autocorrelation analysis are discussed.
Abstract: Recent investigations have shown that the inclusion of hybrid shape/property descriptors together with 2D topological descriptors increases the predictive capability of QSAR and QSPR models. Property-Encoded Surface Translator (PEST) descriptors may be computed using ab initio or semi-empirical electron density surfaces and/or electronic properties, as well as atomic fragment-based TAE/RECON property-encoded surface reconstructions. The RECON and PEST algorithms also include rapid fragment-based wavelet coefficient descriptor (WCD) computation. These descriptors enable a compact encoding of chemical information. We also briefly discuss the use of the RECON/PEST methodology in a virtual high-throughput mode, as well as the use of TAE properties for molecular surface autocorrelation analysis.

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Citations
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Journal ArticleDOI
TL;DR: Results show that the method can reliably extract compounds of shape similar to the query molecules, and initial results for a receptor-based strategy using shape signatures are presented, with application to the design of new inhibitors predicted to be active against HIV protease.
Abstract: A unifying principle of rational drug design is the use of either shape similarity or complementarity to identify compounds expected to be active against a given target. Shape similarity is the underlying foundation of ligand-based methods, which seek compounds with structure similar to known actives, while shape complementarity is the basis of most receptor-based design, where the goal is to identify compounds complementary in shape to a given receptor. These approaches can be extended to include molecular descriptors in addition to shape, such as lipophilicity or electrostatic potential. Here we introduce a new technique, which we call shape signatures, for describing the shape of ligand molecules and of receptor sites. The method uses a technique akin to ray-tracing to explore the volume enclosed by a ligand molecule, or the volume exterior to the active site of a protein. Probability distributions are derived from the ray-trace, and can be based solely on the geometry of the reflecting ray, or may include joint dependence on properties, such as the molecular electrostatic potential, computed over the surface. Our shape signatures are just these probability distributions, stored as histograms. They converge rapidly with the length of the ray-trace, are independent of molecular orientation, and can be compared quickly using simple metrics. Shape signatures can be used to test for both shape similarity between compounds and for shape complementarity between compounds and receptors and thus can be applied to problems in both ligand- and receptor-based molecular design. We present results for comparisons between small molecules of biological interest and the NCI Database using shape signatures under two different metrics. Our results show that the method can reliably extract compounds of shape (and polarity) similar to the query molecules. We also present initial results for a receptor-based strategy using shape signatures, with application to the design of new inhibitors predicted to be active against HIV protease.

126 citations

Journal ArticleDOI
TL;DR: The results from recently published studies show that shape and shape-based descriptors are at least as useful as other traditional molecular descriptors in drug discovery, virtual screening and predictive toxicology.

103 citations

Journal ArticleDOI
TL;DR: The development of a diversity-oriented synthesis strategy for the generation of diverse small molecules based around a common macrocyclic peptidomimetic framework, containing structural motifs present in many naturally occurring bioactive compounds is reported.
Abstract: Structurally diverse libraries of novel small molecules represent important sources of biologically active agents. In this paper we report the development of a diversity-oriented synthesis strategy for the generation of diverse small molecules based around a common macrocyclic peptidomimetic framework, containing structural motifs present in many naturally occurring bioactive compounds. Macrocyclic peptidomimetics are largely underrepresented in current small-molecule screening collections owing primarily to synthetic intractability; thus novel molecules based around these structures represent targets of significant interest, both from a biological and a synthetic perspective. In a proof-of-concept study, the synthesis of a library of 14 such compounds was achieved. Analysis of chemical space coverage confirmed that the compound structures indeed occupy underrepresented areas of chemistry in screening collections. Crucial to the success of this approach was the development of novel methodologies for the macrocyclic ring closure of chiral α-azido acids and for the synthesis of diketopiperazines using solid-supported N methylmorpholine. Owing to their robust and flexible natures, it is envisaged that both new methodologies will prove to be valuable in a wider synthetic context.

102 citations


Cites methods from "New developments in PEST shape/prop..."

  • ...For all structures TAE/RECON electrostatic potential and electrostatic potential autocorrelation descriptors (75) were calculated as implemented in the molecular operating environment and the resulting variables were subject to principal component analysis in the same program....

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Journal ArticleDOI
TL;DR: The development and early application of major components of MetaDrugTM (GeneGo, Inc.) software will be described, which includes rule-based metabolite prediction, quantitative structure–activity relationship models for major drug metabolising enzymes, and an extensive database of human protein–xenobiotic interactions, which represents a combined approach to predicting drug metabolism.
Abstract: There is an urgent requirement within the pharmaceutical and biotechnology industries, regulatory authorities and academia to improve the success of molecules that are selected for clinical trials. Although absorption, distribution, metabolism, excretion and toxicity (ADME/Tox) properties are some of the many components that contribute to successful drug discovery and development, they represent factors for which we currently have in vitro and in vivo data that can be modelled computationally. Understanding the possible toxicity and the metabolic fate of xenobiotics in the human body is particularly important in early drug discovery. There is, therefore, a need for computational methodologies for uncovering the relationships between the structure and the biological activity of novel molecules. The convergence of numerous technologies, including high-throughput techniques, databases, ADME/Tox modelling and systems biology modelling, is leading to the foundation of systems-ADME/Tox. Results from experiments can be integrated with predictions to globally simulate and understand the likely complete effects of a molecule in humans. The development and early application of major components of MetaDrug (GeneGo, Inc.) software will be described, which includes rule-based metabolite prediction, quantitative structure-activity relationship models for major drug metabolising enzymes, and an extensive database of human protein-xenobiotic interactions. This represents a combined approach to predicting drug metabolism. MetaDrug can be readily used for visualising Phase I and II metabolic pathways, as well as interpreting high-throughput data derived from microarrays as networks of interacting objects. This will ultimately aid in hypothesis generation and the early triaging of molecules likely to have undesirable predicted properties or measured effects on key proteins and cellular functions.

85 citations


Cites methods from "New developments in PEST shape/prop..."

  • ...This suggests that generic types of QSAR models can be used to generate predictions for metabolic stability, and it is certainly likely that other computational algorithms will be applied in this area, such as Kernel-based methods; for example, support vector machines [98] and Kernel-partial least squares [106-108], which have started to be used in drug discovery [109-112] alongside new types of molecular descriptors [113]....

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Journal ArticleDOI
TL;DR: Shape Signatures descriptors can be used with SVM and Kohonen SOM and perform better in classification problems related to the analysis of highly clustered and heterogeneous property spaces and may have utility for predicting the potential for cardiotoxicity in drug discovery mediated by the 5-HT(2B) receptor and hERG.
Abstract: Shape Signatures is a new computational tool that is being evaluated for applications in computational toxicology and drug discovery. The method employs a customized ray-tracing algorithm to explore the volume enclosed by the surface of a molecule and then uses the output to construct compact histograms (i.e., signatures) that encode for molecular shape and polarity. In the present study, we extend the application of the Shape Signatures methodology to the domain of computational models for cardiotoxicity. The Shape Signatures method is used to generate molecular descriptors that are then utilized with widely used classification techniques such as k nearest neighbors (k-NN), support vector machines (SVM), and Kohonen self-organizing maps (SOM). The performances of these approaches were assessed by applying them to a data set of compounds with varying affinity toward the 5-HT2B receptor as well as a set of human ether-a-go-go-related gene (hERG) potassium channel inhibitors. Our classification models for 5...

70 citations

References
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Book
01 May 1992
TL;DR: This paper presents a meta-analyses of the wavelet transforms of Coxeter’s inequality and its applications to multiresolutional analysis and orthonormal bases.
Abstract: Introduction Preliminaries and notation The what, why, and how of wavelets The continuous wavelet transform Discrete wavelet transforms: Frames Time-frequency density and orthonormal bases Orthonormal bases of wavelets and multiresolutional analysis Orthonormal bases of compactly supported wavelets More about the regularity of compactly supported wavelets Symmetry for compactly supported wavelet bases Characterization of functional spaces by means of wavelets Generalizations and tricks for orthonormal wavelet bases References Indexes.

16,073 citations

Journal ArticleDOI
TL;DR: In this article, the regularity of compactly supported wavelets and symmetry of wavelet bases are discussed. But the authors focus on the orthonormal bases of wavelets, rather than the continuous wavelet transform.
Abstract: Introduction Preliminaries and notation The what, why, and how of wavelets The continuous wavelet transform Discrete wavelet transforms: Frames Time-frequency density and orthonormal bases Orthonormal bases of wavelets and multiresolutional analysis Orthonormal bases of compactly supported wavelets More about the regularity of compactly supported wavelets Symmetry for compactly supported wavelet bases Characterization of functional spaces by means of wavelets Generalizations and tricks for orthonormal wavelet bases References Indexes.

14,157 citations

Book
01 Jan 1996

312 citations

Journal ArticleDOI
TL;DR: In this paper, a set of molecular surface property descriptors were used to construct HPLC column capacity factor PLS models for a series of high-energy materials, and the most useful new indices were found to correspond to histogram bin data computed for K and G surface kinetic energy densities.
Abstract: The new transferable atom equivalent TAE method for rapid molecular electron density reconstruction was used to compute a set of molecular surface property descriptors. These descriptors were then used to construct HPLC column capacity factor PLS models for a series of high-energy materials. The new TAE-derived surface property indices are also available from ab initio or semiempirical wave functions, but the speed and accuracy of TAE reconstruction make it the method of choice for obtaining these indices. The new QSPR indices are based upon the extrema, distributions, and surface integrals of the electronic kinetic energy . density, the Politzer average local ionization potential pip , and the electrostatic potential, as well as the rates at which these properties change normal to the 0.002-erau 3 molecular surface. The distribution of the properties were recorded as surface histograms. While property extrema and surface integral averages proved to be descriptive, the most useful new indices were found to correspond to histogram bin data computed for K and G surface kinetic energy densities.

82 citations