The Experts below are selected from a list of 38718 Experts worldwide ranked by ideXlab platform
Thierry Langer - One of the best experts on this subject based on the ideXlab platform.
-
Molecule-Pharmacophore superpositioning and pattern matching in computational drug design
Drug Discovery Today, 2008Co-Authors: Gerhard Wolber, Fabian Bendix, Thomas Seidel, Thierry LangerAbstract:Three-dimensional (3D) Pharmacophore modeling is a technique for describing the interaction of a small molecule ligand with a macromolecular target. Since chemical features in a Pharmacophore model are well known and highly transparent for medicinal chemists, these models are intuitively understandable and have been increasingly successful in computational drug discovery in the past few years. The performance and applicability of Pharmacophore modeling depends on two main factors: the definition and placement of pharmacophoric features and the alignment techniques used to overlay 3D Pharmacophore models and small molecules. An overview of key technologies and latest developments in the area of 3D Pharmacophores is given and provides insight into different approaches as implemented by the 3D Pharmacophore modeling packages like Catalyst, MOE, Phase and LigandScout. © 2007 Elsevier Ltd. All rights reserved.
-
molecule Pharmacophore superpositioning and pattern matching in computational drug design
Drug Discovery Today, 2008Co-Authors: Gerhard Wolber, Fabian Bendix, Thomas Seidel, Thierry LangerAbstract:Three-dimensional (3D) Pharmacophore modeling is a technique for describing the interaction of a small molecule ligand with a macromolecular target. Since chemical features in a Pharmacophore model are well known and highly transparent for medicinal chemists, these models are intuitively understandable and have been increasingly successful in computational drug discovery in the past few years. The performance and applicability of Pharmacophore modeling depends on two main factors: the definition and placement of pharmacophoric features and the alignment techniques used to overlay 3D Pharmacophore models and small molecules. An overview of key technologies and latest developments in the area of 3D Pharmacophores is given and provides insight into different approaches as implemented by the 3D Pharmacophore modeling packages like Catalyst, MOE, Phase and LigandScout.
-
High-throughput structure-based Pharmacophore modelling as a basis for successful parallel virtual screening
Journal of Computer-Aided Molecular Design, 2006Co-Authors: Theodora M. Steindl, Gerhard Wolber, Daniela Schuster, Christian Laggner, Thierry LangerAbstract:In order to assess bioactivity profiles for small organic molecules we propose to use parallel Pharmacophore-based virtual screening. Our aim is to provide a fast, reliable and scalable system that allows for rapid in silico activity profile prediction of virtual molecules. In this proof of principle study, carried out with the new structure-based Pharmacophore modelling tool LigandScout and the high-performance database mining platform Catalyst, we present a model work for the application of parallel Pharmacophore-based virtual screening on a set of 50 structure-based Pharmacophore models built for various viral targets and 100 antiviral compounds. The latter were screened against all Pharmacophore models in order to determine if their known biological targets could be correctly predicted via an enrichment of corresponding Pharmacophores matching these ligands. The results demonstrate that the desired enrichment, i.e. a successful activity profiling, was achieved for approximately 90% of all input molecules. Additionally, we discuss descriptors for output validation, as well as various aspects influencing the analysis of the obtained activity profiles, and the effect of the searching mode utilized for screening. The results of the study presented here clearly indicate that Pharmacophore-based parallel screening comprises a reliable in silico method to predict the potential biological activities of a compound or a compound library by screening it against a series of Pharmacophore queries.
-
parallel screening a novel concept in Pharmacophore modeling and virtual screening
Journal of Chemical Information and Modeling, 2006Co-Authors: Theodora M. Steindl, Daniela Schuster, Christian Laggner, Thierry LangerAbstract:Parallel screening comprises a novel in silico method to predict the potential biological activities of a compound by screening it with a multitude of Pharmacophore models. Our aim is to provide a fast, large-scale system that allows for virtual activity profiling. In this proof of principle study, carried out with the software tools LigandScout and Catalyst, we present a model work for the application of parallel Pharmacophore-based virtual screening on a set of 50 structure-based Pharmacophore models built for various viral targets and 100 antiviral compounds. The latter were screened against all Pharmacophore models in order to determine if their biological targets could be correctly predicted via an enrichment of corresponding Pharmacophores matching these ligands. The results demonstrate that the desired enrichment, that is, successful virtual activity profiling, was achieved for approximately 90% of all input molecules. We discuss descriptors for output validation, as well as various aspects influencing the analysis of the obtained activity profiles, and the effect of the utilized search modus for screening.
Gerhard Wolber - One of the best experts on this subject based on the ideXlab platform.
-
Pharmacophore Identification and Pseudo-Receptor Modeling
The Practice of Medicinal Chemistry, 2020Co-Authors: Gerhard Wolber, Wolfgang SipplAbstract:A Pharmacophore represents a simple and intuitive concept that have been used for decades in medicinal chemistry. The use of three-dimensional chemical feature ensembles provides transparency through the ease of interpretability and at the same time allows for efficient implementation of high-throughput virtual screening methods. 3D Pharmacophores have routinely been used in combination with other molecular modelling techniques, such as quantiative structure-activity relationships or pseudo-receptor modeling. The synergistic application of different approaches in drug discovery workflows may allow to fully exploit their advantages, while compensating for some of the intrinsic limitations of each methodology. Whereas, in the past, Pharmacophore models have been mainly generated using ligand-based strategies, novel programs have been developed and applied successfully in the last few years, by combining structure-based and Pharmacophore-based approaches. This is mainly influenced by the rapidly growing number of protein-ligand 3D structures that are the basis for such combined approaches. This chapter will include a general introducion in Pharmacophore and pseudo-receptor modelling, several success stories and an outlook to future developments.
-
Strategies for 3D Pharmacophore-based virtual screening
Drug Discovery Today: Technologies, 2010Co-Authors: Thomas Seidel, Fabian Bendix, Gökhan Ibis, Gerhard WolberAbstract:3D Pharmacophore-based techniques have become one of the most important approaches for the fast and accurate virtual screening of databases with millions of compounds. The success of 3D Pharmacophores is largely based on their intuitive interpretation and creation, but the virtual screening with such three-dimensional geometric models still poses a considerable algorithmic and conceptual challenge. Most current implementations favor fast screening speed at the detriment of accuracy. This review describes the general strategies and algorithms employed for 3D Pharmacophore searching by some current Pharmacophore modeling platforms and will highlight their differences.
-
Molecule-Pharmacophore superpositioning and pattern matching in computational drug design
Drug Discovery Today, 2008Co-Authors: Gerhard Wolber, Fabian Bendix, Thomas Seidel, Thierry LangerAbstract:Three-dimensional (3D) Pharmacophore modeling is a technique for describing the interaction of a small molecule ligand with a macromolecular target. Since chemical features in a Pharmacophore model are well known and highly transparent for medicinal chemists, these models are intuitively understandable and have been increasingly successful in computational drug discovery in the past few years. The performance and applicability of Pharmacophore modeling depends on two main factors: the definition and placement of pharmacophoric features and the alignment techniques used to overlay 3D Pharmacophore models and small molecules. An overview of key technologies and latest developments in the area of 3D Pharmacophores is given and provides insight into different approaches as implemented by the 3D Pharmacophore modeling packages like Catalyst, MOE, Phase and LigandScout. © 2007 Elsevier Ltd. All rights reserved.
-
molecule Pharmacophore superpositioning and pattern matching in computational drug design
Drug Discovery Today, 2008Co-Authors: Gerhard Wolber, Fabian Bendix, Thomas Seidel, Thierry LangerAbstract:Three-dimensional (3D) Pharmacophore modeling is a technique for describing the interaction of a small molecule ligand with a macromolecular target. Since chemical features in a Pharmacophore model are well known and highly transparent for medicinal chemists, these models are intuitively understandable and have been increasingly successful in computational drug discovery in the past few years. The performance and applicability of Pharmacophore modeling depends on two main factors: the definition and placement of pharmacophoric features and the alignment techniques used to overlay 3D Pharmacophore models and small molecules. An overview of key technologies and latest developments in the area of 3D Pharmacophores is given and provides insight into different approaches as implemented by the 3D Pharmacophore modeling packages like Catalyst, MOE, Phase and LigandScout.
-
High-throughput structure-based Pharmacophore modelling as a basis for successful parallel virtual screening
Journal of Computer-Aided Molecular Design, 2006Co-Authors: Theodora M. Steindl, Gerhard Wolber, Daniela Schuster, Christian Laggner, Thierry LangerAbstract:In order to assess bioactivity profiles for small organic molecules we propose to use parallel Pharmacophore-based virtual screening. Our aim is to provide a fast, reliable and scalable system that allows for rapid in silico activity profile prediction of virtual molecules. In this proof of principle study, carried out with the new structure-based Pharmacophore modelling tool LigandScout and the high-performance database mining platform Catalyst, we present a model work for the application of parallel Pharmacophore-based virtual screening on a set of 50 structure-based Pharmacophore models built for various viral targets and 100 antiviral compounds. The latter were screened against all Pharmacophore models in order to determine if their known biological targets could be correctly predicted via an enrichment of corresponding Pharmacophores matching these ligands. The results demonstrate that the desired enrichment, i.e. a successful activity profiling, was achieved for approximately 90% of all input molecules. Additionally, we discuss descriptors for output validation, as well as various aspects influencing the analysis of the obtained activity profiles, and the effect of the searching mode utilized for screening. The results of the study presented here clearly indicate that Pharmacophore-based parallel screening comprises a reliable in silico method to predict the potential biological activities of a compound or a compound library by screening it against a series of Pharmacophore queries.
Renate Griffith - One of the best experts on this subject based on the ideXlab platform.
-
Combining spatial and chemical information for clustering Pharmacophores.
BMC bioinformatics, 2014Co-Authors: Lingxiao Zhou, Renate Griffith, Bruno GaetaAbstract:A Pharmacophore model consists of a group of chemical features arranged in three-dimensional space that can be used to represent the biological activities of the described molecules. Clustering of molecular interactions of ligands on the basis of their Pharmacophore similarity provides an approach for investigating how diverse ligands can bind to a specific receptor site or different receptor sites with similar or dissimilar binding affinities. However, efficient clustering of Pharmacophore models in three-dimensional space is currently a challenge. We have developed a Pharmacophore-assisted Iterative Closest Point (ICP) method that is able to group Pharmacophores in a manner relevant to their biochemical properties, such as binding specificity etc. The implementation of the method takes Pharmacophore files as input and produces distance matrices. The method integrates both alignment-dependent and alignment-independent concepts. We apply our three-dimensional Pharmacophore clustering method to two sets of experimental data, including 31 globulin-binding steroids and 4 groups of selected antibody-antigen complexes. Results are translated from distance matrices to Newick format and visualised using dendrograms. For the steroid dataset, the resulting classification of ligands shows good correspondence with existing classifications. For the antigen-antibody datasets, the classification of antigens reflects both antigen type and binding antibody. Overall the method runs quickly and accurately for classifying the data based on their binding affinities or antigens.
-
Combining spatial and chemical information for clustering Pharmacophores
BMC Bioinformatics, 2014Co-Authors: Lingxiao Zhou, Renate Griffith, Bruno GaetaAbstract:© 2014 Zhou et al.; licensee BioMed Central Ltd. Background: A Pharmacophore model consists of a group of chemical features arranged in three-dimensional space that can be used to represent the biological activities of the described molecules. Clustering of molecular interactions of ligands on the basis of their Pharmacophore similarity provides an approach for investigating how diverse ligands can bind to a specific receptor site or different receptor sites with similar or dissimilar binding affinities. However, efficient clustering of Pharmacophore models in three-dimensional space is currently a challenge. Results: We have developed a Pharmacophore-assisted Iterative Closest Point (ICP) method that is able to group Pharmacophores in a manner relevant to their biochemical properties, such as binding specificity etc. The implementation of the method takes Pharmacophore files as input and produces distance matrices. The method integrates both alignment-dependent and alignment-independent concepts. Conclusions: We apply our three-dimensional Pharmacophore clustering method to two sets of experimental data, including 31 globulin-binding steroids and 4 groups of selected antibody-antigen complexes. Results are translated from distance matrices to Newick format and visualised using dendrograms. For the steroid dataset, the resulting classification of ligands shows good correspondence with existing classifications. For the antigen-antibody datasets, the classification of antigens reflects both antigen type and binding antibody. Overall the method runs quickly and accurately for classifying the data based on their binding affinities or antigens
-
Development of purely structure-based Pharmacophores for the topoisomerase I-DNA-ligand binding pocket
Journal of Computer-Aided Molecular Design, 2013Co-Authors: Malgorzata N. Drwal, Keli Agama, Yves Pommier, Renate GriffithAbstract:Purely structure-based Pharmacophores (SBPs) are an alternative method to ligand-based approaches and have the advantage of describing the entire interaction capability of a binding pocket. Here, we present the development of SBPs for topoisomerase I, an anticancer target with an unusual ligand binding pocket consisting of protein and DNA atoms. Different approaches to cluster and select Pharmacophore features are investigated, including hierarchical clustering and energy calculations. In addition, the performance of SBPs is evaluated retrospectively and compared to the performance of ligand- and complex-based Pharmacophores. SBPs emerge as a valid method in virtual screening and a complementary approach to ligand-focussed methods. The study further reveals that the choice of Pharmacophore feature clustering and selection methods has a large impact on the virtual screening hit lists. A prospective application of the SBPs in virtual screening reveals that they can be used successfully to identify novel topoisomerase inhibitors.
-
Selective Pharmacophore design for α1-adrenoceptor subtypes
Journal of Molecular Graphics & Modelling, 2006Co-Authors: Iain J.a. Macdougall, Renate GriffithAbstract:Abstract α1-Adrenoceptors are G-protein coupled receptors found in a variety of vascular tissues and responsible for vasoconstriction. Selectivity for each of the three subtypes is an important consideration in drug design in order to minimise the possibility of side effects. Using Catalyst® we developed ligand-based Pharmacophores from α1a,b,d-selective antagonists available in the literature using three separate training sets. Four-feature Pharmacophores were developed for the α1a and α1b subtype-selective antagonists and a five-feature Pharmacophore was developed for the α1d subtype-selective antagonists. The α1a Pharmacophore represents both class I and II compounds with good predictivity for other compounds outside the training set as well. The α1b Pharmacophore best predicts the activity of prazosin analogues as these make up the majority of α1b-selective antagonists. Unexpectedly, no positive ionisable feature was incorporated in the α1b Pharmacophore. The α1d Pharmacophore was based primarily on one structural class of compounds, but has good predictivity for a heterogeneous test set. Preliminary docking studies using AutoDock and optimised α1-adrenoceptor homology models, conducted with the antagonists prazosin (32) and 66, showed good agreement with the findings from the Pharmacophores.
-
Combining structure-based drug design and Pharmacophores.
Journal of Molecular Graphics & Modelling, 2005Co-Authors: Renate Griffith, James Garner, Paul A. KellerAbstract:Abstract Development towards integrated computer-aided drug design methodologies is presented by utilising crystal structure complexes to produce structure-based Pharmacophores. These novel Pharmacophores represent the ligand features that are involved in interactions with the target protein, as well as the space around the ligand occupied by the protein. The protein–ligand complexes can also yield information about all interactions that ligands could potentially form with the binding site, as well as about the size of the binding cavity. Together, these describe a ‘superligand’, which can also be viewed as a Pharmacophore. Various types of novel Pharmacophores are discussed and compared, using HIV-1 reverse transcriptase (RT) as the target protein, and their application in database searching is presented.
Carlos J Camacho - One of the best experts on this subject based on the ideXlab platform.
-
zincpharmer Pharmacophore search of the zinc database
Nucleic Acids Research, 2012Co-Authors: David Ryan Koes, Carlos J CamachoAbstract:ZINCPharmer (http://zincpharmer.csb.pitt.edu) is an online interface for searching the purchasable compounds of the ZINC database using the Pharmer Pharmacophore search technology. A Pharmacophore describes the spatial arrangement of the essential features of an interaction. Compounds that match a well-defined Pharmacophore serve as potential lead compounds for drug discovery. ZINCPharmer provides tools for constructing and refining Pharmacophore hypotheses directly from molecular structure. A search of 176 million conformers of 18.3 million compounds typically takes less than a minute. The results can be immediately viewed, or the aligned structures may be downloaded for off-line analysis. ZINCPharmer enables the rapid and interactive search of purchasable chemical space.
-
pharmer efficient and exact Pharmacophore search
Journal of Chemical Information and Modeling, 2011Co-Authors: David Ryan Koes, Carlos J CamachoAbstract:Pharmacophore search is a key component of many drug discovery efforts. Pharmer is a new computational approach to Pharmacophore search that scales with the breadth and complexity of the query, not the size of the compound library being screened. Two novel methods for organizing Pharmacophore data, the Pharmer KDB-tree and Bloom fingerprints, enable Pharmer to perform an exact Pharmacophore search of almost two million structures in less than a minute. In general, Pharmer is more than an order of magnitude faster than existing technologies. The complete source code is available under an open-source license at http://pharmer.sourceforge.net.
Theodora M. Steindl - One of the best experts on this subject based on the ideXlab platform.
-
High-throughput structure-based Pharmacophore modelling as a basis for successful parallel virtual screening
Journal of Computer-Aided Molecular Design, 2006Co-Authors: Theodora M. Steindl, Gerhard Wolber, Daniela Schuster, Christian Laggner, Thierry LangerAbstract:In order to assess bioactivity profiles for small organic molecules we propose to use parallel Pharmacophore-based virtual screening. Our aim is to provide a fast, reliable and scalable system that allows for rapid in silico activity profile prediction of virtual molecules. In this proof of principle study, carried out with the new structure-based Pharmacophore modelling tool LigandScout and the high-performance database mining platform Catalyst, we present a model work for the application of parallel Pharmacophore-based virtual screening on a set of 50 structure-based Pharmacophore models built for various viral targets and 100 antiviral compounds. The latter were screened against all Pharmacophore models in order to determine if their known biological targets could be correctly predicted via an enrichment of corresponding Pharmacophores matching these ligands. The results demonstrate that the desired enrichment, i.e. a successful activity profiling, was achieved for approximately 90% of all input molecules. Additionally, we discuss descriptors for output validation, as well as various aspects influencing the analysis of the obtained activity profiles, and the effect of the searching mode utilized for screening. The results of the study presented here clearly indicate that Pharmacophore-based parallel screening comprises a reliable in silico method to predict the potential biological activities of a compound or a compound library by screening it against a series of Pharmacophore queries.
-
parallel screening a novel concept in Pharmacophore modeling and virtual screening
Journal of Chemical Information and Modeling, 2006Co-Authors: Theodora M. Steindl, Daniela Schuster, Christian Laggner, Thierry LangerAbstract:Parallel screening comprises a novel in silico method to predict the potential biological activities of a compound by screening it with a multitude of Pharmacophore models. Our aim is to provide a fast, large-scale system that allows for virtual activity profiling. In this proof of principle study, carried out with the software tools LigandScout and Catalyst, we present a model work for the application of parallel Pharmacophore-based virtual screening on a set of 50 structure-based Pharmacophore models built for various viral targets and 100 antiviral compounds. The latter were screened against all Pharmacophore models in order to determine if their biological targets could be correctly predicted via an enrichment of corresponding Pharmacophores matching these ligands. The results demonstrate that the desired enrichment, that is, successful virtual activity profiling, was achieved for approximately 90% of all input molecules. We discuss descriptors for output validation, as well as various aspects influencing the analysis of the obtained activity profiles, and the effect of the utilized search modus for screening.