T
Thierry Langer
Researcher at University of Vienna
Publications - 276
Citations - 10895
Thierry Langer is an academic researcher from University of Vienna. The author has contributed to research in topics: Pharmacophore & Virtual screening. The author has an hindex of 53, co-authored 260 publications receiving 9462 citations. Previous affiliations of Thierry Langer include University of Cagliari & Slovak Academy of Sciences.
Papers
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Journal ArticleDOI
LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters.
Gerhard Wolber,Thierry Langer +1 more
TL;DR: Three-dimensional pharmacophore models are constructed, which are sufficiently selective to identify the described binding mode and are thus a useful tool for in-silico screening of large compound databases.
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Why drugs fail--a study on side effects in new chemical entities.
TL;DR: The results of this study indicate that compared with previous studies on this subject, no major improvements have been achieved in the last decade.
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Recognizing Pitfalls in Virtual Screening: A Critical Review
Thomas Scior,Andreas Bender,Gary Tresadern,José L. Medina-Franco,Karina Martinez-Mayorga,Thierry Langer,Karina Cuanalo-Contreras,Dimitris K. Agrafiotis +7 more
TL;DR: This review attempts to catalogue published and unpublished problems, shortcomings, failures, and technical traps of VS methods with the aim to avoid pitfalls by making the user aware of them in the first place.
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Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection—What can we learn from earlier mistakes?
TL;DR: This review analyzes recent literature evaluating 3D virtual screening methods, with focus on molecular docking, and highlights problematic issues and provides guidelines on how to improve the quality of computational studies.
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Efficient overlay of small organic molecules using 3D pharmacophores.
TL;DR: The presented approach identifies optimal chemical feature pairs using distance and density characteristics obtained by correlating pharmacophoric geometries and thus proves to be faster than existing combinatorial alignment methods and creates more reasonable alignments than pure atom-based methods.