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3D pharmacophore elucidation and virtual screening
Drug Discovery Today: Technologies
Vol. 7, No. 4 2010
Editors-in-Chief Kelvin Lam – Harvard University, USA Henk Timmerman – Vrije Universiteit, The Netherlands DRUG DISCOVERY
TODAY
TECHNOLOGIES
Editorial
EDITORIAL
3D pharmacophore elucidation and virtual screening Gerhard Wolber Freie Universitat Berlin, Institute of Pharmacy, Pharmaceutical Chemistry, Computer-Aided Drug Design, 14195 Berlin, Germany
The basic concept of 3D pharmacophores is simple: identify all three-dimensional molecular features, such as hydrogen bonds, charges, and hydrophobic areas that empirically characterize the binding of a ligand to its macromolecular target and use this ensemble to represent a specific binding mode. If novel compounds can be identified that are able to fulfill this interaction pattern, we assume that the found virtual hits will also bind and show comparable biological activity. Long before computers played an important role in drug discovery, medicinal chemists used to think in similar metaphors to develop and optimize their compounds, and this is potentially one of the key factors to the ongoing success of pharmacophore methods. This ease of application and understanding, however, does not mean that the underlying technology can remain simple: first, there are different views on how the complex process of ligand binding should be generalized in the correct way and second, high-throughput 3D pharmacophore screening still poses considerable algorithmic challenges related to their alignment, filtering and virtual hit ranking. Because in silico virtual screening has become a standard part of early drug discovery processes, 3D pharmacophore methods have to be seen in the context of other state-of-the-art computational drug design methods. While in the beginning, 3D pharmacophores were mainly applied in a ligand-based way, structure-based applications have recently become equally important. Therefore, much attention is devoted to comparing 3D pharmacophore methods to docking approaches, and the ability to score and prioritize hits from a virtual screening run. The series of reviews presented in this special issue on ‘3D pharmacophore elucidation and virtual screening’ provides an overview of the field, focusing on new and innovative 1740-6749/$ ß 2010 Elsevier Ltd. All rights reserved.
DOI: 10.1016/j.ddtec.2010.12.004
ways to derive meaningful 3D pharmacophores from experimental data and how to exploit this information for virtual screening. John van Drie’s article on ‘History of 3D pharmacophore searching: commercial, academic and open-source tools’, gives a general overview on the development in this field and provides a comprehensive and broad perspective on the ideas that lead to the tools nowadays used in modern drug discovery. Because all 3D searching techniques consider the ligand as flexible, conformational subsampling plays a pivotal role in pharmacophore-based virtual screening. Christof Schwab’s review on ‘Conformations and 3D pharmacophore
Gerhard Wolber is currently professor for pharmaceutical chemistry at the Freie Universita¨t Berlin, Germany. He received his Ph.D. at the University of Innsbruck in 2003 after his studies of computer science and pharmacy at the University of Innsbruck and University of Vienna, Austria, respectively. As one of the founders of the drug design company Inte:Ligand, he has been working as head of cheminformatics and research since 2003, where he has been leading the development of the two programs ilib diverse and LigandScout. In 2008, he took a position as a lecturer in pharmaceutical chemistry at the Institute of Pharmacy at the University of Innsbruck, where he headed his own research group for computational chemistry before changing to his current position at the Freie Universita¨t Berlin in 2010. His research interests include structure- and ligand-based drug design, efficient algorithms for virtual screening, 2D and 3D visualization techniques, as well as 3D pharmacophore modeling.
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Drug Discovery Today: Technologies | Editorial
searching’ provides insights into which effects different techniques will have on pharmacophore screening. He investigates and summarizes several techniques and concludes that the search for a global minimum has become less important than the search for a putative bioactive conformation or a representative subsampling of conformational space. Michael Hein, David Zilian, and Christoph Sotriffer provide a differentiated and well-balanced review ‘Docking compared to 3D-pharmacophores: The scoring function challenge’ by discussing the advantages and problems of both methods when used for prospective virtual screening. They summarize that the pharmacophore approach profits from its ability to be trained to a specific problem domain, while docking has the advantage of creating more meaningful binding poses that can be analyzed accordingly. They provide a comprehensive overview of prospective pharmacophore and docking studies, discuss the advantages and scopes of both methods and conclude that the combination of both approaches – if used in their applicability domains – provides the best results. Simon Cross’ and Gabriele Cruciani’s article ‘Grid-derived structure-based 3D pharmacophores and their performance compared to docking’ presents a different approach to pharmacophore elucidation: They illustrate how molecular interaction fields can be used to derive pharmacophores in a more generic and less heuristic way. They articulate criticism on the usefulness of scoring functions used in docking to estimate binding energy, and also come to the conclusion that the combination of both methods provides best results. Alexander Klenner, Markus Hartenfeller, Petra Schneider and Gisbert Schneider write about the ‘Fuzziness’ in pharmacophore-based virtual screening and de novo design’: They summarize their success stories resulting the application of their developed pharmacophore tools and claim that the appropriate level of ‘fuzziness’ is the key to success in
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www.drugdiscoverytoday.com
Vol. 7, No. 4 2010
pharmacophore-based virtual screening. Thomas Seidel and co-authors suggest that geometric accuracy plays a crucial role in 3D pharmacophore screening, and use pharmacophore point tolerances as a measure to balance restrictivity against sensitivity of a model. They claim that an adequate signal-tonoise ratio can only be achieved if the geometric constraints in a pharmacophore query are searched for in a geometrically accurate way, and that other screening approaches contain too many approximation steps in their screening filters and therefore loose information. Their novel pattern-matching alignment technique is able to combine this higher accuracy with state-of-the-art screening performance. The review of Gerhard Hessler and Karl-Heinz Baringhaus on ‘The scaffold hopping potential of pharmacophores’ provides a practical view on pharmacophore techniques as they are applied in industry bridging the gap between theory and practice. Various success stories and applicability guidelines are discussed giving an overview on what can be done already and what challenges still need to be addressed. Finally, Daniela Schuster provides a view on multi-target predictions with pharmacophores in her article ‘3D Pharmacophores as tools for activity profiling’. She discusses a number of different application scenarios, such as drug repositioning or natural product profiling and provides several success stories from each area. Overall, this issue offers a cross-section of new technologies in 3D pharmacophore-based virtual screening, provides a view on how this technology is applied along with best practice guidelines and gives us a roadmap on what still can be done to improve this highly successful in silico drug discovery technique. With best wishes, Gerhard Wolber
Vol. 7, No. 4 2010
Editors-in-Chief Kelvin Lam – Harvard University, USA Henk Timmerman – Vrije Universiteit, The Netherlands DRUG DISCOVERY
TODAY
TECHNOLOGIES
Editorial
EDITORIAL
3D pharmacophore elucidation and virtual screening Gerhard Wolber Freie Universitat Berlin, Institute of Pharmacy, Pharmaceutical Chemistry, Computer-Aided Drug Design, 14195 Berlin, Germany
The basic concept of 3D pharmacophores is simple: identify all three-dimensional molecular features, such as hydrogen bonds, charges, and hydrophobic areas that empirically characterize the binding of a ligand to its macromolecular target and use this ensemble to represent a specific binding mode. If novel compounds can be identified that are able to fulfill this interaction pattern, we assume that the found virtual hits will also bind and show comparable biological activity. Long before computers played an important role in drug discovery, medicinal chemists used to think in similar metaphors to develop and optimize their compounds, and this is potentially one of the key factors to the ongoing success of pharmacophore methods. This ease of application and understanding, however, does not mean that the underlying technology can remain simple: first, there are different views on how the complex process of ligand binding should be generalized in the correct way and second, high-throughput 3D pharmacophore screening still poses considerable algorithmic challenges related to their alignment, filtering and virtual hit ranking. Because in silico virtual screening has become a standard part of early drug discovery processes, 3D pharmacophore methods have to be seen in the context of other state-of-the-art computational drug design methods. While in the beginning, 3D pharmacophores were mainly applied in a ligand-based way, structure-based applications have recently become equally important. Therefore, much attention is devoted to comparing 3D pharmacophore methods to docking approaches, and the ability to score and prioritize hits from a virtual screening run. The series of reviews presented in this special issue on ‘3D pharmacophore elucidation and virtual screening’ provides an overview of the field, focusing on new and innovative 1740-6749/$ ß 2010 Elsevier Ltd. All rights reserved.
DOI: 10.1016/j.ddtec.2010.12.004
ways to derive meaningful 3D pharmacophores from experimental data and how to exploit this information for virtual screening. John van Drie’s article on ‘History of 3D pharmacophore searching: commercial, academic and open-source tools’, gives a general overview on the development in this field and provides a comprehensive and broad perspective on the ideas that lead to the tools nowadays used in modern drug discovery. Because all 3D searching techniques consider the ligand as flexible, conformational subsampling plays a pivotal role in pharmacophore-based virtual screening. Christof Schwab’s review on ‘Conformations and 3D pharmacophore
Gerhard Wolber is currently professor for pharmaceutical chemistry at the Freie Universita¨t Berlin, Germany. He received his Ph.D. at the University of Innsbruck in 2003 after his studies of computer science and pharmacy at the University of Innsbruck and University of Vienna, Austria, respectively. As one of the founders of the drug design company Inte:Ligand, he has been working as head of cheminformatics and research since 2003, where he has been leading the development of the two programs ilib diverse and LigandScout. In 2008, he took a position as a lecturer in pharmaceutical chemistry at the Institute of Pharmacy at the University of Innsbruck, where he headed his own research group for computational chemistry before changing to his current position at the Freie Universita¨t Berlin in 2010. His research interests include structure- and ligand-based drug design, efficient algorithms for virtual screening, 2D and 3D visualization techniques, as well as 3D pharmacophore modeling.
e203
Drug Discovery Today: Technologies | Editorial
searching’ provides insights into which effects different techniques will have on pharmacophore screening. He investigates and summarizes several techniques and concludes that the search for a global minimum has become less important than the search for a putative bioactive conformation or a representative subsampling of conformational space. Michael Hein, David Zilian, and Christoph Sotriffer provide a differentiated and well-balanced review ‘Docking compared to 3D-pharmacophores: The scoring function challenge’ by discussing the advantages and problems of both methods when used for prospective virtual screening. They summarize that the pharmacophore approach profits from its ability to be trained to a specific problem domain, while docking has the advantage of creating more meaningful binding poses that can be analyzed accordingly. They provide a comprehensive overview of prospective pharmacophore and docking studies, discuss the advantages and scopes of both methods and conclude that the combination of both approaches – if used in their applicability domains – provides the best results. Simon Cross’ and Gabriele Cruciani’s article ‘Grid-derived structure-based 3D pharmacophores and their performance compared to docking’ presents a different approach to pharmacophore elucidation: They illustrate how molecular interaction fields can be used to derive pharmacophores in a more generic and less heuristic way. They articulate criticism on the usefulness of scoring functions used in docking to estimate binding energy, and also come to the conclusion that the combination of both methods provides best results. Alexander Klenner, Markus Hartenfeller, Petra Schneider and Gisbert Schneider write about the ‘Fuzziness’ in pharmacophore-based virtual screening and de novo design’: They summarize their success stories resulting the application of their developed pharmacophore tools and claim that the appropriate level of ‘fuzziness’ is the key to success in
e204
www.drugdiscoverytoday.com
Vol. 7, No. 4 2010
pharmacophore-based virtual screening. Thomas Seidel and co-authors suggest that geometric accuracy plays a crucial role in 3D pharmacophore screening, and use pharmacophore point tolerances as a measure to balance restrictivity against sensitivity of a model. They claim that an adequate signal-tonoise ratio can only be achieved if the geometric constraints in a pharmacophore query are searched for in a geometrically accurate way, and that other screening approaches contain too many approximation steps in their screening filters and therefore loose information. Their novel pattern-matching alignment technique is able to combine this higher accuracy with state-of-the-art screening performance. The review of Gerhard Hessler and Karl-Heinz Baringhaus on ‘The scaffold hopping potential of pharmacophores’ provides a practical view on pharmacophore techniques as they are applied in industry bridging the gap between theory and practice. Various success stories and applicability guidelines are discussed giving an overview on what can be done already and what challenges still need to be addressed. Finally, Daniela Schuster provides a view on multi-target predictions with pharmacophores in her article ‘3D Pharmacophores as tools for activity profiling’. She discusses a number of different application scenarios, such as drug repositioning or natural product profiling and provides several success stories from each area. Overall, this issue offers a cross-section of new technologies in 3D pharmacophore-based virtual screening, provides a view on how this technology is applied along with best practice guidelines and gives us a roadmap on what still can be done to improve this highly successful in silico drug discovery technique. With best wishes, Gerhard Wolber