Evaluation of library ranking efficacy in virtual screening

We present the results of a comprehensive study in which we explored how the docking procedure affects the performance of a virtual screening approach. We used four docking engines and applied 10 scoring functions to the top-ranked docking solutions of seeded databases against six target proteins. The scores of the experimental poses were placed within the total set to assess whether the scoring function required an accurate pose to provide the appropriate rank for the seeded compounds. This method allows a direct comparison of library ranking efficacy. Our results indicate that the LigandFit/Ligscore1 and LigandFit/GOLD docking/scoring combinations, and to a lesser degree FlexX/FlexX, Glide/Ligscore1, DOCK/PMF (Tripos implementation), LigandFit1/Ligscore2 and LigandFit/PMF (Tripos implementation) were able to retrieve the highest number of actives at a 10% fraction of the database when all targets were looked upon collectively. We also show that the scoring functions rank the observed binding modes higher than the inaccurate poses provided that the experimental poses are available. This finding stresses the discriminatory ability of the scoring algorithms, when better poses are available, and suggests that the number of false positives can be lowered with conformers closer to bioactive ones.     

Computational validation of the importance of absolute stereochemistry in virtual screening

Consideration of stereochemistry early in the identification and optimization of lead compounds can improve the efficiency and efficacy of the drug discovery process and reduce the time spent on subsequent drug development. These improvements can result by focusing on specific enantiomers that have the desired potential therapeutic effect (eutomers), while removing from consideration enantiomers that may have no, or even undesirable, effects (distomers). A virtual screening campaign that correctly takes stereochemical information into account can, in theory, be utilized to provide information about the relative binding affinities of enantiomers. Thus, the proper enumeration of the relevant stereoisomers in general, and enantiomeric pairs in particular, of chiral compounds is crucial if one is to use virtual screening as an effective drug discovery tool. As is obvious, in cases where no stereochemical information is provided for chiral compounds in a 2D chemical database, then each possible stereoisomer should be generated for construction of the subsequent 3D database to be used for virtual screening. However, acute problems can arise in 3D database construction when relative stereochemistry is encoded in a 2D database for a chiral compound containing multiple stereogenic atoms but absolute stereochemistry is not implied. In this case, we report that generation of enantiomeric pairs is imperative in database development if one is to obtain accurate docking results. A study is described on the impact of the neglect of enantiomeric pairs on virtual screening using the human homolog of murine double minute 2 (MDM2) protein, the product of a proto-oncogene, as the target. Docking in MDM2 with GLIDE 4.0 was performed using the NCI Diversity Set 3D database and, for comparison, a set of enantiomers we created corresponding to mirror image structures of the single enantiomers of chiral compounds present in the NCI Diversity Set. Our results demonstrate that potential lead candidates may be overlooked when databases contain 3D structures representing only a single enantiomer of racemic chiral compounds.     

Evaluation of potential inhibitors of squalene synthase based on virtual screening and in vitro studies

Squalene synthase (SQS) is a potential target for hyperlipidemia treatment. To identify novel chemical scaffolds of SQS inhibitors, we generated 3D-QSAR pharmacophore models using HypoGen. The best quantitative pharmacophore model, Hypo 1, was selected for virtual screening using two chemical databases, Specs and Traditional Chinese Medicine database (TCM). The best-mapped hit compounds were then subjected to filtering by Lipinski^’s rule of five and docking studies to refine the hits. Finally, five compounds were selected from the top-ranked hit compounds for SQS inhibitory assay in vitro. Three of these compounds could inhibit SQS in vitro, and should be further evaluated pre-clinically as a treatment for hyperlipidemia.     

VinaMPI: Facilitating multiple receptor high‐throughput virtual docking on high‐performance computers

The program VinaMPI has been developed to enable massively large virtual drug screens on leadership‐class computing resources, using a large number of cores to decrease the time‐to‐completion of the screen. VinaMPI is a massively parallel Message Passing Interface (MPI) program based on the multithreaded virtual docking program AutodockVina, and is used to distribute tasks while multithreading is used to speed‐up individual docking tasks. VinaMPI uses a distribution scheme in which tasks are evenly distributed to the workers based on the complexity of each task, as defined by the number of rotatable bonds in each chemical compound investigated. VinaMPI efficiently handles multiple proteins in a ligand screen, allowing for high‐throughput inverse docking that presents new opportunities for improving the efficiency of the drug discovery pipeline. VinaMPI successfully ran on 84,672 cores with a continual decrease in job completion time with increasing core count. The ratio of the number of tasks in a screening to the number of workers should be at least around 100 in order to have a good load balance and an optimal job completion time. The code is freely available and downloadable. Instructions for downloading and using the code are provided in the Supporting Information. © 2013 Wiley Periodicals, Inc.     

Evaluation and application of multiple scoring functions for a virtual screening experiment

In order to identify novel chemical classes of factor Xa inhibitors, five scoring functions (FlexX, DOCK, GOLD, ChemScore and PMF) were engaged to evaluate the multiple docking poses generated by FlexX. The compound collection was composed of confirmed potent factor Xa inhibitors and a subset of the LeadQuest screening compound library. Except for PMF the other four scoring functions succeeded in reproducing the crystal complex (PDB code: 1FAX). During virtual screening the highest hit rate (80%) was demonstrated by FlexX at an energy cutoff of -40 kJ/mol, which is about 40-fold over random screening (2.06%). Limited results suggest that presenting more poses of a single molecule to the scoring functions could deteriorate their enrichment factors. A series of promising scaffolds with favorable binding scores was retrieved from LeadQuest. Consensus scoring by pair-wise intersection failed to enrich the hit rate yielded by single scorings (i.e. FlexX). We note that reported successes of consensus scoring in hit rate enrichment could be artificial because their comparisons were based on a selected subset of single scoring and a markedly reduced subset of double or triple scoring. The findings presented in this report are based upon a single biological system and support further studies.     

Pharmacophore modelling,virtual screening and molecular docking studies on PLD1 inhibitors

Lipid metabolism plays a significant role in influenza virus replication and subsequent infection. The regulatory mechanism governing lipid metabolism and viral replication is not properly understood to date, but both Phospholipase D (PLD1 and PLD2) activities are stimulated in viral infection. In vitro studies indicate that chemical inhibition of PLD1 delays viral entry and reduction of viral loads. The current study reports a three-dimensional pharmacophore model based on 35 known PLD1 inhibitors. A sub-set of 25 compounds was selected as the training set and the remaining 10 compounds were kept in the test set. One hundred and twelve pharmacophore models were generated; a six-featured pharmacophore model (AADDHR.57) with survival score (2.69) produced a statistically significant three-dimensional quantitative structure–activity relationship model with r² = 0.97 (internal training set), r² = 0.71 (internal test set) and Q² = 0.64. The predictive power of the pharmacophore model was validated with an external test set (r² = 0.73) and a systematic virtual screening work-flow was employed showing an enrichment factor of 23.68 at the top 2% of the dataset (active and decoys). Finally, the model was used for screening of the filtered PubChem database to fetch molecules which can be proposed as potential PLD1 inhibitors for blocking influenza infection.     

Validation of multivariate screening methodology. Case study: Detection of food fraud

Multivariate screening methods are increasingly being implemented but there is no worldwide harmonized criterion for their validation. This study contributes to establish protocols for validating these methodologies. We propose the following strategy: (1) Establish the multivariate classification model and use receiver operating characteristic (ROC) curves to optimize the significance level (α) for setting the model’s boundaries. (2) Evaluate the performance parameter from the contingency table results and performance characteristic curves (PCC curves). The adulteration of hazelnut paste with almond paste and chickpea flour has been used as a case study. Samples were analyzed by infrared (IR) spectroscopy and the multivariate classification technique used was soft independent modeling of class analogies (SIMCA). The ROC study showed that the optimal α value for setting the SIMCA boundaries was 0.03 in both cases. The sensitivity value was 93%, specificity 100% for almond and 98% for chickpea, and efficiency 97% for almond and 93% for chickpea.     

The identification of new ATAD2 bromodomain inhibitors: the application of combined ligand and structure-based virtual screening

Ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS) approaches were used to identify new inhibitors for ATAD2 bromodomain. The LBVS approach was used to search 23,129,083 clean compounds to identify compounds similar to an active compound with reported pIC₅₀ equal to 7.2. Based on LBVS results, 19 compounds were selected. To perform SBVS, by applying nine filters on 23,129,083 clean compounds, 1,057,060 compounds were selected. After performing SBVS on these selected compounds with idock software, 16 compounds with the lowest binding energies were selected. More accurate molecular docking analysis was performed on these 35 selected compounds by using iGEMDOCK software and six of them with the lowest binding energies were selected as hit compounds. These compounds were zinc36647229, zinc77969074, zinc13637358, zinc77971540, zinc12991296 and zinc19374204.     

Novel metal complexes of 3-acetylcoumarin-2-hydrazinobenzothiazole Schiff base: Design,structural characterizations,DNA binding,DFT calculations,molecular docking and biological studies

Five new Cu (II), Zn (II), Pd (II), Ru (III) and Ag(I) complexes, derived from the 3-acetylcoumarin-2-hydrazinobenzothiazole Schiff base (Hachbt), have been synthesized and characterized. The structures were established with the aid of elemental analyses (C, H, N), FT-IR, ¹H-NMR, ESR, UV–visible and ESI-mass spectra. The complexes were also investigated by magnetic susceptibility, thermal gravimetric analysis (TG-DTA) and cyclic voltammetry measurements. The results suggest that the Schiff base ligand behaves in two different ways: neutral mono/bidentate or mono-negative bi/tridentate. The calf thymus DNA (CT DNA) binding affinities of Hachbt and its complexes have been examined by UV–visible spectroscopy. The antifungal activity of the compounds was also screened against two fungal species of wood-decay basidiomycetes using the agar dilution method. Different complexes caused a reduction in the fungal colony diameters at a media concentration of 100 μg/ml. The best antifungal activity was observed for the Pd (II) and Ag(I) complexes with a 60% and 79% reduction, respectively. The effect of the complexes on the ability of the same fungi to decolorize poly-R dye on agar plates was also tested. All of the complexes showed an enhanced effect on the decolorization ability and the Cu (II) and Ru (III) complexes exhibited the strongest effect at a media concentration of 5 μg/ml. Theoretical studies were performed for all the complexes using the DFT/B3LYP/6–31 + g(d) basis set for calculations on the ligand atoms and LAN2DZ for the Pd (II) complex. The optimized geometries were found to be in a good agreement with the proposed structures. The molecular docking calculations show that the binding affinity of the Pd (II) complex is −309.170-309.2 kcal/mol, which suggests complexation with the DNA minor groove.     

Practical uses of proficiency testing as valuable tools for validation and performance assessment in environmental analysis

Besides their role as an external quality control tool, PT results or samples could be used as an alternative to fulfil some of the quality assurance requirements such as analytical precision, uncertainty assessment, and internal quality control. This additional use of proficiency testing could help laboratories to reduce the financial impact of their quality assurance process. The purpose of this paper is to highlight some practical uses of PT results or samples in the environmental analytical field, which have been implemented at ISSeP (Institut Scientifique de Service Public), either for method validation or for internal quality control.Presented at the Eurachem PT Workshop September 2005, Portorož, Slovenia     

Reducing false-positive rates in virtual screening via cancellation of systematic errors in the scoring function

Here we propose an over-the-hood docking method that compensates for systematic errors in the docking force fields. This method explicitly estimates the interaction energy of the ligand with the protein surface and uses it as a baseline to estimate the actual binding energy in the active site. It improves the accuracy of virtual screening in the LeadFinder package by up to 48%.     

Multiple protein structures and multiple ligands: effects on the apparent goodness of virtual screening results

As an extension to a previous published study (McGaughey et al., J Chem Inf Model 47:1504–1519, 2007) comparing 2D and 3D similarity methods to docking, we apply a subset of those virtual screening methods (TOPOSIM, SQW, ROCS-color, and Glide) to a set of protein/ligand pairs where the protein is the target for docking and the cocrystallized ligand is the target for the similarity methods. Each protein is represented by a maximum of five crystal structures. We search a diverse subset of the MDDR as well as a diverse small subset of the MCIDB, Merck’s proprietary database. It is seen that the relative effectiveness of virtual screening methods, as measured by the enrichment factor, is highly dependent on the particular crystal structure or ligand, and on the database being searched. 2D similarity methods appear very good for the MDDR, but poor for the MCIDB. However, ROCS-color (a 3D similarity method) does well for both databases. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Discovery of novel indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors by virtual screening

In this study, a combination of virtual screening methods were utilized to identify novel potential indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors. A series of IDO1 potential inhibitors were identified by a combination of following steps: Lipinski's Rule of Five, Veber rules filter, molecular docking, HipHop pharmacophores, 3D-Quantitative structure activity relationship (3D-QSAR) studies and Pan-assay Interference Compounds (PAINS) filter. Three known categories of IDO1 inhibitors were used to constructed pharmacophores and 3D-QSAR models. Four point pharmacophores (RHDA) of IDO1 inhibitors were generated from the training set. The 3D-QSAR models were obtained using partial least squares (PLS) analyze based on the docking conformation alignment from the training set. The leave-one-out correlation (q²) and non-cross-validated correlation coefficient (r²_pred) of the best CoMFA model were 0.601 and 0.546, and the ones from the best CoMSIA model were 0.506 and 0.541, respectively. Six hits from Specs database were identified and analyzed to confirm their binding modes and key interactions to the amino acid residues in the protein. This work may provide novel backbones for new generation of inhibitors of IDO1.     

Evaluation of docking performance in a blinded virtual screening of fragment-like trypsin inhibitors

In this study, we have "blindly" assessed the ability of several combinations of docking software and scoring functions to predict the binding of a fragment-like library of bovine trypsine inhibitors. The most suitable protocols (involving Gold software and GoldScore scoring function, with or without rescoring) were selected for this purpose using a training set of compounds with known biological activities. The selected virtual screening protocols provided good results with the SAMPL3-VS dataset, showing enrichment factors of about 10 for Top 20 compounds. This methodology should be useful in difficult cases of docking, with a special emphasis on the fragment-based virtual screening campaigns.