Bioactive Conformational Biasing: A New Method for Focusing Conformational Ensembles on Bioactive-Like Conformers
| Autor: | Hanoch Senderowitz, Boaz Musafia |
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| Rok vydání: | 2009 |
| Předmět: |
Training set
Protein Conformation Ligand Stereochemistry Chemistry General Chemical Engineering Proteins General Chemistry Library and Information Sciences Ligands Computer Science Applications law.invention Models Chemical Multiple Models law Biological system Conformational ensembles Conformational isomerism Filtration |
| Zdroj: | Journal of Chemical Information and Modeling. 49:2469-2480 |
| ISSN: | 1549-960X 1549-9596 |
| DOI: | 10.1021/ci900163t |
| Popis: | Computational approaches that rely on ligand-based information for lead discovery and optimization are often required to spend considerable resources analyzing compounds with large conformational ensembles. In order to reduce such efforts, we have developed a new filtration tool which reduces the total number of ligand conformations while retaining in the final set a reasonable number of conformations that are similar (rmsdor = 1 A) to those observed in ligand-protein cocrystals (bioactive-like conformations). Our tool consists of the following steps: (1) Prefiltration aimed at removing ligands for which the probability of finding bioactive-like conformations is low. (2) Filtration based on a unique combination of two-/three-dimensional ligand properties. Within this paradigm, a filtration model is defined by its workflow and by the identity of the specific descriptors used for filtration. Thus, we developed multiple models based on a training set of 47 drug compounds and tested their performance on an independent test set of 24 drug compounds. For test set compounds after prefiltration, our best models have a success rate of approximately 80% and were able to reduce the total number of conformations by 36% while maintaining a sufficiently large number of bioactive-like conformations and slightly increasing their proportion in the filtered ensemble. We were also able to reduce by 39% the number of conformations that are remote (rmsd2.5 A) from the bioactive conformer (nonbioactive conformations). In accord with previous reports, prefiltration is shown to have a major effect on model performance. The role and performance of specific descriptors as filters is discussed in some detail, and future directions are proposed. |
| Databáze: | OpenAIRE |
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