Predicting drug promiscuity using spherical harmonic surface shape-based similarity comparisons

Polypharmacology is becoming an increasingly important aspect in drug design. Pharmaceutical companies are discovering more and more cases in which multiple drugs bind to a given target (promiscuous targets) and in which a given drug binds to more than one target (promiscuous ligands). These phenomena are clearly of great importance when considering drug side-effects. In the last 4 years, more than 30 drugs have been tested against more than 40 novel secondary targets based on promiscuity predictions. Current methods for predicting promiscuity typically aim to relate protein receptors according to their primary sequences, the similarity of their ligands, and more recently, the similarity of their ligand binding pockets. Here, we present a spherical harmonic (SH) surface shape-based approach to predict rapidly promiscuous ligands and targets by comparing sets of SH ligand and protein shapes, respectively. We present details of our approach applied to a wide range of PDB complexes comprising ligands in a selected subset of the MDL Drug Data Report (MDDR) database which are distributed over 249 diverse pharmacological targets. The shape similarity of each ligand to each target’s ligand set is quantified and used to predict promiscuity. We also analyse the correlation between binding pocket and ligand shapes. We compare our promiscuity predictions with experimental activity values extracted from the BindingDB database.Publisher PDFPeer reviewe

Comprehensive Comparison of Ligand-Based Virtual Screening Tools Against the DUD Data set Reveals Limitations of Current 3D Methods

In recent years, many virtual screening (VS) tools have been developed that employ different molecular representations and have different speed and accuracy characteristics. In this paper, we compare ten popular ligand-based VS tools using the publicly available Directory of Useful Decoys (DUD) data set comprising over 100 000 compounds distributed across 40 protein targets. The DUD was developed initially to evaluate docking algorithms, but our results from an operational correlation analysis show that it is also well suited for comparing ligand-based VS tools. Although it is conventional wisdom that 3D molecular shape is an important determinant of biological activity, our results based on permutational significance tests of several commonly used VS metrics show that the 2D fingerprint-based methods generally give better VS performance than the 3D shape-based approaches for surprisingly many of the DUD targets. To help understand this finding, we have analyzed the nature of the scoring functions used and the composition of the DUD data set itself. We propose that to improve the VS performance of current 3D methods, it will be necessary to devise screening queries that can represent multiple possible conformations and which can exploit knowledge of known actives that span multiple scaffold families.</p

Predicting drug promiscuity using spherical harmonic surface shape-based similarity comparisons

Polypharmacology is becoming an increasingly important aspect in drug design. Pharmaceutical companies are discovering more and more cases in which multiple drugs bind to a given target (promiscuous targets) and in which a given drug binds to more than one target (promiscuous ligands). These phenomena are clearly of great importance when considering drug side-effects. In the last 4 years, more than 30 drugs have been tested against more than 40 novel secondary targets based on promiscuity predictions. Current methods for predicting promiscuity typically aim to relate protein receptors according to their primary sequences, the similarity of their ligands, and more recently, the similarity of their ligand binding pockets.Here, we present a spherical harmonic (SH) surface shape-based approach to predict rapidly promiscuous ligands and targets by comparing sets of SH ligand and protein shapes, respectively. We present details of our approach applied to a wide range of PDB complexes comprising ligands in a selected subset of the MDL Drug Data Report (MDDR) database which are distributed over 249 diverse pharmacological targets. The shape similarity of each ligand to each target’s ligand set is quantified and used to predict promiscuity. We also analyse the correlation between binding pocket and ligand shapes. We compare our promiscuity predictions with experimental activity values extracted from the BindingDB database

Using Spherical Harmonic Surface Property Representations for Ligand-Based Virtual Screening

International audienceLigand-based virtual screening (VS) techniques have become well established in the drug discovery process. However, despite their relative success, there still exists the problem of how to define the initial query compounds and which of their conformations should be used. Here, we propose a novel shape plus surface property approach using multiple local spherical harmonic (SH) functions. We also investigate the use of shape-based and shape plus property-based consensus SH queries calculated in several different ways. The utility of these approaches is compared using the 40 pharmaceutically relevant targets of the DUD database. Our results show that using a combination of SH-based properties often gives better VS performance than using simple shape-based queries. Shape-based consensus queries also perform well, but we find that explicit 3D shape-property conformations should be retained for highly flexible ligands

Using Spherical Harmonic Surface Property Representations for Ligand-Based Virtual Screening

Ligand-based virtual screening (VS) techniques have become well established in the drug discovery process. However, despite their relative success, there still exists the problem of how to define the initial query compounds and which of their conformations should be used. Here, we propose a novel shape plus surface property approach using multiple local spherical harmonic (SH) functions. We also investigate the use of shape-based and shape plus property-based consensus SH queries calculated in several different ways. The utility of these approaches is compared using the 40 pharmaceutically relevant targets of the DUD database. Our results show that using a combination of SH-based properties often gives better VS performance than using simple shape-based queries. Shape-based consensus queries also perform well, but we find that explicit 3D shape-property conformations should be retained for highly flexible ligands.</p

Computational proteomics pitfalls and challenges: HavanaBioinfo 2012 Workshop report

The workshop "Bioinformatics for Biotechnology Applications (HavanaBioinfo 2012)", held December 8-11, 2012 in Havana, aimed at exploring new bioinformatics tools and approaches for large-scale proteomics, genomics and chemoinformatics. Major conclusions of the workshop include the following: (i) development of new applications and bioinformatics tools for proteomic repository analysis is crucial; current proteomic repositories contain enough data (spectra/identifications) that can be used to increase the annotations in protein databases and to generate new tools for protein identification; (ii) spectral libraries, de novo sequencing and database search tools should be combined to increase the number of protein identifications; (iii) protein probabilities and FDR are not yet sufficiently mature; (iv) computational proteomics software needs to become more intuitive; and at the same time appropriate education and training should be provided to help in the efficient exchange of knowledge between mass spectrometrists and experimental biologists and bioinformaticians in order to increase their bioinforrnatics background, especially statistics knowledge. (c) 2013 Elsevier B.V. All rights reserved