Virtual Screening Data Fusion Using Both Structure- and Ligand-Based Methods

Svensson, Fredrik; Karlén, Anders; Sköld, Christian

doi:10.1021/ci2004835

Cited by 80 publications

(93 citation statements)

References 41 publications

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“…43,44 Using the consensus molecular shape pattern derived from compounds 1 and 2 avoided the need to screen large databases using several different queries and then to rank the ligands using time-consuming, data-fusion methods that in the past often produced false positives. 35 …”

Section: Resultsmentioning

confidence: 99%

Novel Mycosin Protease MycP₁ Inhibitors Identified by Virtual Screening and 4D Fingerprints

Hamza

Wagner

Evans

et al. 2014

J. Chem. Inf. Model.

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The rise of drug-resistant Mycobacterium tuberculosis lends urgency to the need for new drugs for the treatment of tuberculosis (TB). The identification of a serine protease, mycosin protease-1 (MycP1), as the crucial agent in hydrolyzing the virulence factor, ESX-secretion-associated protein B (EspB), potentially opens the door to new tuberculosis treatment options. Using the crystal structure of mycobacterial MycP1 in the apo form, we performed an iterative ligand- and structure-based virtual screening (VS) strategy to identify novel, nonpeptide, small-molecule inhibitors against MycP1 protease. Screening of ∼485 000 ligands from databases at the Genomics Research Institute (GRI) at the University of Cincinnati and the National Cancer Institute (NCI) using our VS approach, which integrated a pharmacophore model and consensus molecular shape patterns of active ligands (4D fingerprints), identified 81 putative inhibitors, and in vitro testing subsequently confirmed two of them as active inhibitors. Thereafter, the lead structures of each VS round were used to generate a new 4D fingerprint that enabled virtual rescreening of the chemical libraries. Finally, the iterative process identified a number of diverse scaffolds as lead compounds that were tested and found to have micromolar IC50 values against the MycP1 target. This study validated the efficiency of the SABRE 4D fingerprints as a means of identifying novel lead compounds in each screening round of the databases. Together, these results underscored the value of using a combination of in silico iterative ligand- and structure-based virtual screening of chemical libraries with experimental validation for the identification of promising structural scaffolds, such as the MycP1 inhibitors.

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Section: Resultsmentioning

confidence: 99%

Novel Mycosin Protease MycP₁ Inhibitors Identified by Virtual Screening and 4D Fingerprints

Hamza

Wagner

Evans

et al. 2014

J. Chem. Inf. Model.

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“…e Results for GOLD were calculated with ChemScore. 41 f Data was not available from Svensson et al 44 their Tanimoto coefficient was below the threshold T c . The previous subsection assumed the maximal Tanimoto coefficient T c = 1; by reducing the T c , we selected ligands that were less similar to the actives.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

VS-APPLE: A Virtual Screening Algorithm Using Promiscuous Protein–Ligand Complexes

Okuno

Kato

Terada

et al. 2015

J. Chem. Inf. Model.

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As the number of structurally resolved protein-ligand complexes increases, the ligand-binding pockets of many proteins have been found to accommodate multiple different compounds. Effective use of these structural data is important for developing virtual screening (VS) methods that identify bioactive compounds. Here, we introduce a VS method, VS-APPLE (Virtual Screening Algorithm using Promiscuous Protein-Ligand complExes), based on promiscuous protein-ligand binding structures. In VS-APPLE, multiple ligands bound to a pocket are combined into a query template for screening. Both the structural match between a test compound and the multiple-ligand template and the possible collisions between the test compound and the target protein are evaluated by an efficient geometric hashing method. The performance of VS-APPLE was examined on a filtered, clustered version of the Directory of Useful Decoys data set. In Area Under the Curve analyses of this data set, VS-APPLE outperformed several popular screening programs. Judging from the performance of VS-APPLE, the structural data of promiscuous protein-ligand bindings could be further analyzed and exploited for developing VS methods.

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“…This stance is further strengthened through a very recent retrospective study in which a multipronged virtual screening approach very similar to the one employed here was one of the best performing “consensus” approaches. 43 …”

Section: Discussionmentioning

confidence: 99%

Identification of Novel Antimalarial Chemotypes via Chemoinformatic Compound Selection Methods for a High-Throughput Screening Program against the Novel Malarial Target, PfNDH2: Increasing Hit Rate via Virtual Screening Methods

et al. 2012

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Malaria is responsible for approximately 1 million deaths annually; thus, continued efforts to discover new antimalarials are required. A HTS screen was established to identify novel inhibitors of the parasite's mitochondrial enzyme NADH:quinone oxidoreductase (PfNDH2). On the basis of only one known inhibitor of this enzyme, the challenge was to discover novel inhibitors of PfNDH2 with diverse chemical scaffolds. To this end, using a range of ligand-based chemoinformatics methods, ∼17000 compounds were selected from a commercial library of ∼750000 compounds. Forty-eight compounds were identified with PfNDH2 enzyme inhibition IC50 values ranging from 100 nM to 40 μM and also displayed exciting whole cell antimalarial activity. These novel inhibitors were identified through sampling 16% of the available chemical space, while only screening 2% of the library. This study confirms the added value of using multiple ligand-based chemoinformatic approaches and has successfully identified novel distinct chemotypes primed for development as new agents against malaria.

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Virtual Screening Data Fusion Using Both Structure- and Ligand-Based Methods

Cited by 80 publications

References 41 publications

Novel Mycosin Protease MycP₁ Inhibitors Identified by Virtual Screening and 4D Fingerprints

Novel Mycosin Protease MycP₁ Inhibitors Identified by Virtual Screening and 4D Fingerprints

VS-APPLE: A Virtual Screening Algorithm Using Promiscuous Protein–Ligand Complexes

Identification of Novel Antimalarial Chemotypes via Chemoinformatic Compound Selection Methods for a High-Throughput Screening Program against the Novel Malarial Target, PfNDH2: Increasing Hit Rate via Virtual Screening Methods

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Virtual Screening Data Fusion Using Both Structure- and Ligand-Based Methods

Cited by 80 publications

References 41 publications

Novel Mycosin Protease MycP1 Inhibitors Identified by Virtual Screening and 4D Fingerprints

Novel Mycosin Protease MycP1 Inhibitors Identified by Virtual Screening and 4D Fingerprints

VS-APPLE: A Virtual Screening Algorithm Using Promiscuous Protein–Ligand Complexes

Identification of Novel Antimalarial Chemotypes via Chemoinformatic Compound Selection Methods for a High-Throughput Screening Program against the Novel Malarial Target, PfNDH2: Increasing Hit Rate via Virtual Screening Methods

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Novel Mycosin Protease MycP₁ Inhibitors Identified by Virtual Screening and 4D Fingerprints

Novel Mycosin Protease MycP₁ Inhibitors Identified by Virtual Screening and 4D Fingerprints