Multiple-step virtual screening using VSM-G: overview and validation of fast geometrical matching enrichment

Beautrait, Alexandre; Leroux, Vincent; Chavent, Matthieu; Ghemtio, Léo; Devignes, Marie‐Dominique; Smaïl-Tabbone, Malika; Cai, Wensheng; Shao, Xuegang; Moreau, Gilles; Bladon, Peter; Yao, Jianhua; Maigret, Bernard

doi:10.1007/s00894-007-0257-9

Cited by 17 publications

(26 citation statements)

References 57 publications

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“…We used the VMS-G software platform [31] to perform virtual screening (VS). The docking program used within the platform was GOLD [32], which has been recognized as among the best docking software [33].…”

Section: Virtual Screeningmentioning

confidence: 99%

Structure-based virtual screening of hypothetical inhibitors of the enzyme longiborneol synthase—a potential target to reduce Fusarium head blight disease

Bresso

Leroux²,

Urban

et al. 2016

J Mol Model

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Fusarium head blight (FHB) is one of the most destructive diseases of wheat and other cereals worldwide. During infection, the Fusarium fungi produce mycotoxins that represent a high risk to human and animal health. Developing small-molecule inhibitors to specifically reduce mycotoxin levels would be highly beneficial since current treatments unspecifically target the Fusarium pathogen. Culmorin possesses a well-known important synergistically virulence role among mycotoxins, and longiborneol synthase appears to be a key enzyme for its synthesis, thus making longiborneol synthase a particularly interesting target. This study aims to discover potent and less toxic agrochemicals against FHB. These compounds would hamper culmorin synthesis by inhibiting longiborneol synthase. In order to select starting molecules for further investigation, we have conducted a structure-based virtual screening investigation. A longiborneol synthase structural model is first built using homology modeling, followed by molecular dynamics simulations that provided the required input for a protein-ligand ensemble docking procedure. From this strategy, the three most interesting compounds (hits) were selected among the 25 top-ranked docked compounds from a library of 15,000 drug-like compounds. These putative inhibitors of longiborneol synthase provide a sound starting point for further studies involving molecular modeling coupled to biochemical experiments. This process could eventually lead to the development of novel approaches to reduce mycotoxin contamination in harvested grain.

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Section: Virtual Screeningmentioning

confidence: 99%

Structure-based virtual screening of hypothetical inhibitors of the enzyme longiborneol synthase—a potential target to reduce Fusarium head blight disease

Bresso

Leroux²,

Urban

et al. 2016

J Mol Model

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show abstract

“…47 We used this molecular database as it has been already used as a reference set in proof-of-concept studies of virtual screening techniques. 17 A preliminary filtering procedure was performed on the whole ZINC library, using Lipinski's rule-of-five 48 allowing a single violation for each structure. This gave a total of 598,375 unique molecules that was stored into the VSM-G working database.…”

Section: Ligand Databasesmentioning

confidence: 99%

“…This number of 8,000 was retained according to previous studies as containing most of the molecules of interest. 17 This new set of putative ligands was screened using the semi-flexible GOLD docking method which performs more accurate, but more computationally expensive dockings. The molecules and the LXR β target binding sites were 33 A) interface to select the grid computing resources for job submission.…”

Section: Screening Processmentioning

confidence: 99%

“…[13][14][15][16] Basically, there are two approaches to speed up the structure-based high-throughput virtual screening (HTVS) process, and to significantly reduce the constraint of required time and resources addressing the performance bottleneck. 1,3,4,[10][11][12]17,18 The first is to run the calculations on massively parallel supercomputers. This requires the docking programs to be modified; the code is parallelized and optimized for the particular machine configuration.…”

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confidence: 99%

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Efficiency of a hierarchical protocol for high throughput structure-based virtual screening on GRID5000 cluster grid

Ghemtio¹,

Jeannot²,

Maigret³

2010

OAB

Self Cite

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Most modern computational techniques in the drug discovery areas put demands on large computer resources. Grid computing offers a powerful alternative way of running computationally intensive applications. One field of the drug innovation process that can benefit greatly from the use of grid resources is the high-throughput virtual screening approach for docking huge chemical compound libraries into known protein-binding sites. The use of computational grids is the combination of computer resources from multiple administrative domains, heterogeneous, and geographically dispersed applications to a common task that requires a great number of computer-processing cycles or the need to process large amounts of data. This study detailed a screening campaign, on Grid5000 cluster grid computing infrastructure, concerning the ZINC database, from which a subset of ∼600,000 "drug-like" molecules was extracted, against three structures of the liver-X receptor β (LXR β). A funnel strategy was used for that purpose, starting from a fast but simple shape matching procedure and achieved with more complex molecular dynamics simulations. From a total of ∼91 million three-dimensional conformations which were generated at the beginning of the funnel and after intermediate filtering steps, the process ended with 45 putative hits. The GRID5000 is a highly reconfigurable, controllable, and monitorable experimental cluster grid, connecting nine sites geographically distributed in France, and featuring more than 3,200 processors and 5,700 cores. To hide the complexity of the grid system from the user, the GRID5000 has been used through the virtual screening manager for grid computing (VSM-G) platform, dedicated to in silico screening and to provide maximum computing power by using grid resources efficiently. The whole screening process required around 82 days (78 days of pre-processing and 3.6 days for the docking funnel itself) and utilized 3,144 nodes over nine sites. The use of grid infrastructures and hierarchical filtering protocol enable us to perform evaluations of the binding capabilities of millions of compounds on several conformations of a given target and propose that, with a low cost, most promising compounds for in vitro tests.

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“…We use the PARASURF and PARAFIT modules [41] to calculate and superpose SH molecular surfaces, and the MSSH [42] program to calculate the SH shapes of protein pockets. PARASURF calculates molecular shape and electronic properties from semi-empirical quantum mechanics theory and encodes these properties as SH expansions [35,36].…”

Section: Calculating Sh Shapesmentioning

confidence: 99%

Predicting Drug Promiscuity Using Spherical Harmonic Surface Shape-Based Similarity Comparisons

Pérez‐Nueno¹

2011

TOPROCJ

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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.Consensus shapes, drug promiscuity, ligand shape space, protein pocket space, protein sequence space, shape similarity, spherical harmonic shapes.

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Multiple-step virtual screening using VSM-G: overview and validation of fast geometrical matching enrichment

Cited by 17 publications

References 57 publications

Structure-based virtual screening of hypothetical inhibitors of the enzyme longiborneol synthase—a potential target to reduce Fusarium head blight disease

Structure-based virtual screening of hypothetical inhibitors of the enzyme longiborneol synthase—a potential target to reduce Fusarium head blight disease

Efficiency of a hierarchical protocol for high throughput structure-based virtual screening on GRID5000 cluster grid

Predicting Drug Promiscuity Using Spherical Harmonic Surface Shape-Based Similarity Comparisons

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