Comparison of affinity ranking using AutoDock-GPU and MM-GBSA scores for BACE-1 inhibitors in the D3R Grand Challenge 4

Khoury, Léa El; Santos-Martins, Diogo; Sasmal, Sukanya; Eberhardt, Jérôme; Bianco, Giulia; Ambrosio, Francesca Alessandra; Solis-Vasquez, Leonardo; Koch, Andreas; Forli, Stefano; Mobley, David L.

doi:10.1007/s10822-019-00240-w

Cited by 59 publications

(47 citation statements)

References 52 publications

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“…Cloud and distributed computing resources also provide this type of completely parallel solution for high-throughput screening 35,36 . The use of GPUs has recently been made possible for the widely-used program AutoDock4 37,38 resulting in the program AutoDock-GPU, which provides up to 50X speedup over AutoDock4 (available at https://github.com/ccsb-scripts/AutoDock-GPU) [39][40][41] . Thus, the use of leadership HPC facilities for ensemble docking can provide the ability to screen billions of ligands to a full set of conformations generated with HPC-based MD simulations.…”

Section: Introductionmentioning

confidence: 99%

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19

Acharya

Agarwal

Baker

et al. 2020

J. Chem. Inf. Model.

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159

141

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We present a supercomputer-driven pipeline for in silico drug discovery using enhanced sampling molecular dynamics (MD) and ensemble docking. Ensemble docking makes use of MD results by docking compound databases into representative protein binding-site conformations, thus taking into account the dynamic properties of the binding sites. We also describe preliminary results obtained for 24 systems involving eight proteins of the proteome of SARS-CoV-2. The MD involves temperature replica exchange enhanced sampling, making use of massively parallel supercomputing to quickly sample the configurational space of protein drug targets. Using the Summit supercomputer at the Oak Ridge National Laboratory, more than 1 ms of enhanced sampling MD can be generated per day. We have ensemble docked repurposing databases to 10 configurations of each of the 24 SARS-CoV-2 systems using AutoDock Vina. Comparison to experiment demonstrates remarkably high hit rates for the top scoring tranches of compounds identified by our ensemble approach. We also demonstrate that, using Autodock-GPU on Summit, it is possible to perform exhaustive docking of one billion compounds in under 24 h. Finally, we discuss preliminary results and planned improvements to the pipeline, including the use of quantum mechanical (QM), machine learning, and artificial intelligence (AI) methods to cluster MD trajectories and rescore docking poses.

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Section: Introductionmentioning

confidence: 99%

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19

Acharya

Agarwal

Baker

et al. 2020

J. Chem. Inf. Model.

Self Cite

159

141

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“…AMBER UNITED force field electrostatic charges [ 53 ] were loaded on the protein structure, while the molcharge complement of QUACPAC [ 54 ] was used in order to achieve Marsili-Gasteiger charges for the inhibitors. Affinity maps were calculated firstly on a 0.500 Å spaced 100 × 100 × 100 Å 3 cubic box in the blind test dockings, and afterwards on 0.375 Å spaced 85 × 85 × 85 Å 3 cubic box, centered on thedonepezil crystallized structures, and the accessibility of the binding site was exploited throughout 1000 runs of Lamarckian Genetic Algorithm (LGA) implemented in AUTODOCK 4.2.6 [ 55 ] using the GPU-OpenCL algorithm version [ 56 ]. Explicit water contribution was taken into account according to the hydration force field of AUTODOCK [ 57 ], and the population size and the number of energy evaluations figures were set to 300 and 10000000, respectively.…”

Section: Methodsmentioning

confidence: 99%

Derivatives of Tenuazonic Acid as Potential New Multi-Target Anti-Alzheimer’s Disease Agents

et al. 2021

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Alzheimer’s disease (AD) is generally recognized as a multifactorial neurodegenerative pathology with an increasing impact on society. Tenuazonic acid (TA) is a natural compound that was recently identified as a potential multitarget ligand with anti-cholinesterase, anti-amyloidogenic and antioxidant activities. Using its structure as a chemical scaffold, we synthesized and evaluated new derivatives (1–5), including tenuazonic-donepezil (TA-DNP) hybrids (4 and 5) due to the clinical importance of the anti-AD drug donepezil. These novel compounds all achieved activity in the micromolar range towards all selected targets and demonstrated to be potentially orally absorbed. Moreover, a selected compound (1) was further investigated as a chelating agent towards copper (II), zinc (II) and iron (III) and showed good chelating ability (pFe = 16.6, pCu = 11.6, pZn = 6.0 at pH 7.4). Therefore, the TA motif can be considered an interesting building block in the search for innovative multi-functional anti-neurodegenerative drugs, as exemplified by hybrid 5, a promising non-cytotoxic lead compound adequate for the early stages of AD, and capable of ameliorating the oxidative status of SH-SY5Y human neuroblastoma cells.

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“…Due to the presence of FAD in the enzyme molecular assembly, Marsili‐Gasteiger charges were applied to both the protein and ligands to normalize the electrostatic potentials in the free energy evaluation. Binding mode of each derivative was sampled with a thousand runs of Lamarckian Genetic Algorithm (LGA) implemented in AUTODOCK 4.2.6 using the GPU‐OpenCL algorithm version . To accomplish this task, affinity maps were first calculated on a 70×70×70 Å 3 box, 0.375 Å spaced, centered on the co‐crystallized coumarin, and LGA runs were issued with population size and the number of energy evaluations to 300 and 10 000 000 respectively, considering water contribution according to the hydration force field of AUTODOCK .…”

Section: Methodsmentioning

confidence: 99%

“…Binding mode of each derivative was sampled with a thousand runs of Lamarckian Genetic Algorithm (LGA) implemented in AUTODOCK 4.2.6 [29] using the GPU-OpenCL algorithm version. [30] To accomplish this task, affinity maps were first calculated on a 70 × 70 × 70 Å 3 box, 0.375 Å spaced, centered on the co-crystallized coumarin, and LGA runs were issued with population size and the number of energy evaluations to 300 and 10 000 000 respectively, considering water contribution according to the hydration force field of AUTODOCK. [31] All the docked poses were thereafter clustered, and the best free energy/most populated pose selected as representative of the binding mode.…”

Section: Molecular Modelingmentioning

confidence: 99%

Scouting around 1,2,3,4‐Tetrahydrochromeno[3,2‐c]pyridin‐10‐ones for Single‐ and Multitarget Ligands Directed towards Relevant Alzheimer's Targets

et al. 2020

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A number of 1,2,3,4-tetrahydrochromeno[3,2-c]pyridin-10-one derivatives have been synthesized and screened against different targets involved in the onset and progression of Alzheimer's disease (AD), such as acetyl-and butyrylcholinesterase (AChE and BChE), monoamine oxidases A and B (MAO A and B), aggregation of β-amyloid (Aβ) and reactive oxygen species (ROS) production. Derivatives 1 c, 3 b, 4 and 5 a showed multifaceted profiles of promising anti-AD features and returned well-balanced multitargeting inhibitory activities. Moreover, compound 1 f, a potent and selective human MAO B inhibitor (IC 50 = 0.89 μM), proved to be a safe neuroprotectant in a human neuroblastoma cell line (SH-SY5Y) by improving viability impaired by Aβ 1-42 and pro-oxidant insult. Furthermore, structure-activity relationships (SARs) and docking models were derived in order to assist further hit-to-lead optimization stage.

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Comparison of affinity ranking using AutoDock-GPU and MM-GBSA scores for BACE-1 inhibitors in the D3R Grand Challenge 4

Cited by 59 publications

References 52 publications

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19

Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19

Derivatives of Tenuazonic Acid as Potential New Multi-Target Anti-Alzheimer’s Disease Agents

Scouting around 1,2,3,4‐Tetrahydrochromeno[3,2‐c]pyridin‐10‐ones for Single‐ and Multitarget Ligands Directed towards Relevant Alzheimer's Targets

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