Surviving the deluge of biosimulation data

Hospital, Adam; Battistini, Federica; Soliva, Robert; Gelpí, Josep Lluís; Orozco, Modesto

doi:10.1002/wcms.1449

Cited by 31 publications

(35 citation statements)

References 88 publications

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“…Consequently, the call for public availability and conservation of data has extended to molecular dynamics (MD) simulation trajectories of biomolecules, 20 − 22 and the discussion on how and by whom such databanks for dynamic structures would be set up is currently active. 23 − 26 While there are currently no general MD databanks in operation, individual databanks are accepting contributions on nucleic acid, 27 protein/DNA/RNA, 28 cyclodextrin, 29 G-protein-coupled receptor, 30 and lipid bilayer 31 simulations.…”

Section: Introductionmentioning

confidence: 99%

Using Open Data to Rapidly Benchmark Biomolecular Simulations: Phospholipid Conformational Dynamics

Antila

Ferreira

Ollila

et al. 2021

J. Chem. Inf. Model.

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Molecular dynamics (MD) simulations are widely used to monitor time-resolved motions of biomacromolecules, although it often remains unknown how closely the conformational dynamics correspond to those occurring in real life. Here, we used a large set of open-access MD trajectories of phosphatidylcholine (PC) lipid bilayers to benchmark the conformational dynamics in several contemporary MD models (force fields) against nuclear magnetic resonance (NMR) data available in the literature: effective correlation times and spin–lattice relaxation rates. We found none of the tested MD models to fully reproduce the conformational dynamics. That said, the dynamics in CHARMM36 and Slipids are more realistic than in the Amber Lipid14, OPLS-based MacRog, and GROMOS-based Berger force fields, whose sampling of the glycerol backbone conformations is too slow. The performance of CHARMM36 persists when cholesterol is added to the bilayer, and when the hydration level is reduced. However, for conformational dynamics of the PC headgroup, both with and without cholesterol, Slipids provides the most realistic description because CHARMM36 overestimates the relative weight of ∼1 ns processes in the headgroup dynamics. We stress that not a single new simulation was run for the present work. This demonstrates the worth of open-access MD trajectory databanks for the indispensable step of any serious MD study: benchmarking the available force fields. We believe this proof of principle will inspire other novel applications of MD trajectory databanks and thus aid in developing biomolecular MD simulations into a true computational microscope—not only for lipid membranes but for all biomacromolecular systems.

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Section: Introductionmentioning

confidence: 99%

Using Open Data to Rapidly Benchmark Biomolecular Simulations: Phospholipid Conformational Dynamics

Antila

Ferreira

Ollila

et al. 2021

J. Chem. Inf. Model.

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“…All data is available at the Bioactive Conformational Ensemble (BCE) server http://mmb.irbbarcelona.org/BCE/ (see companion paper ct-2020-00305q). Trajectories were stored for further analysis using MD database recommendations 50 .…”

Section: Figure 2 Scheme Of the Automatic Pipelinementioning

confidence: 99%

Exploring the Conformational Landscape of Bioactive Small Molecules

Zivanovic

Colizzi

Moreno

et al. 2020

J. Chem. Theory Comput.

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By using a combination of classical Hamiltonian Replica Exchange with high-level quantum mechanical calculations on more than one hundred drug-like molecules we explored here the energy cost associated with binding of drug-like molecules to target macromolecules. We found that, in general, the drug-like molecules present bound to proteins in the Protein Data Bank (PDB) can access easily the bioactive conformation and in fact for 73% of the studied molecules the "bioactive" conformation is within 3kbT from the most stable conformation in solution as determined by DFT/SCRF calculations. Cases with large differences between the most stable and the "bioactive" conformations appear in ligands recognized by ionic contacts, or very large structures establishing many favorable interactions with the protein. There are also a few cases where we observed a non-negligible uncertainty related to the experimental structure deposited in PDB. Remarkably, the rough automatic force-field used here provides reasonable estimates of the conformational ensemble of drugs in solution. The outlined protocol can be used to better estimate the cost of adopting the bioactive conformation.

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“…At present time, the database contains data for around 1000 conformers of ~115 compounds and occupies around 1 Tb of disk. All trajectories were stored for further analysis using MD database recommendations 23 .…”

Section: Bce Database Structure and Associated Tools Database Contentmentioning

confidence: 99%

Bioactive Conformational Ensemble Server and Database. A Public Framework to Speed Up In Silico Drug Discovery

Zivanovic

Bayarri

Colizzi

et al. 2020

J. Chem. Theory Comput.

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Modern high-throughput structure-based drug discovery algorithms consider ligand flexibility, but typically with low accuracy, which results in a loss of performance in the derived models. Here we present the Bioactive Conformational Ensemble (BCE) server and its associated database. The server creates conformational ensembles of drug-like ligands and stores them in the BCE database, where a variety of analyses are offered to the user. The workflow implemented in the BCE server combines enhanced sampling molecular dynamics with self-consistent reaction field quantum mechanics (SCRF/QM) calculations. The server automatizes all the steps to transform 1D or 2D representation of drugs into three dimensional molecules, which are then titrated, parametrized, hydrated and optimized before being subjected to Hamiltonian replica-exchange (HREX) molecular dynamics simulations. Ensembles are collected and subjected to a clustering procedure to derive representative conformers, which are then analyzed at the SCRF/QM level of theory. All structural data is organized in a noSQL database accessible through a graphical interface and in a programmatic manner through a REST API. The server allows the user to define a private workspace and offers a deposition protocol as well as input files for "in house" calculations in those cases where confidentiality is a must. The database and the associated server are available at https://mmb.irbbarcelona.org/BCE

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Surviving the deluge of biosimulation data

Cited by 31 publications

References 88 publications

Using Open Data to Rapidly Benchmark Biomolecular Simulations: Phospholipid Conformational Dynamics

Using Open Data to Rapidly Benchmark Biomolecular Simulations: Phospholipid Conformational Dynamics

Exploring the Conformational Landscape of Bioactive Small Molecules

Bioactive Conformational Ensemble Server and Database. A Public Framework to Speed Up In Silico Drug Discovery

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