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Adaptive Molecular Dynamics on the Cloud with HTMD and AceCloud

From João M. Damas

Researchers have been looking beyond traditional Molecular Dynamics (MD) for a long time now. While many have been using many forms of biased MD (for example, metadynamics), we have alternatively proposed Adaptive Molecular Dynamics 1,2 as a way to unbiasedly enhance the exploration of the phase space through on-the-fly learning of the explored space.

Since the beginning, HTMD 2 has provided an Adaptive MD protocol, which automatically manages all the process of analyzing the explored space and spawning of new MD simulations. An explanation of how Adaptive MD works and examples on how to use it can be found in the cited papers and in the online documentation of HTMD. One of the limitations of Adaptive MD has been the access to computing resources to take advantage of its high-throughput nature.

However, with the advent of cloud computing, resources are more readily available in an elastic manner that suits different needs. We have developed AceCloud 3 to run MD simulations on AWS and, together with HTMD, it can be used to run Adaptive MD simulations on the cloud. By using a system example for the generators (initial simulations), one can use the following script to quickly run an Adaptive MD job using HTMD and AceCloud:


References:
1. S. Doerr and G. De Fabritiis. On-the-fly learning and sampling of ligand binding by high-throughput molecular simulations. Journal of Chemical Theory and Computation, 10(5):2064–2069, 2014.
2. S. Doerr, M. J. Harvey, Frank Noé, and G. De Fabritiis. HTMD: High-throughput molecular dynamics for molecular discovery. Journal of Chemical Theory and Computation, 12(4):1845–1852, 2016.
3. M. J. Harvey and G. De Fabritiis. AceCloud: Molecular dynamics simulations in the cloud. Journal of Chemical Information and Modeling, 55(5):909–914,2015.

alejandroAdaptive Molecular Dynamics on the Cloud with HTMD and AceCloud
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Acellera Flows

“A command-line interface designed to perform complex workflows with few inputs”

By Alberto Cuzzolin

Nowadays, Molecular Dynamics (MD) simulation is known to be an important tool in drug discovery process. Although its potential is clearly proved, it is still not trivial to handle all the steps necessary to retrieve results. To handle all these aspects, we developed HTMD, a python framework that manages all these aspects and allows an easily scale up to an high-throughput manner.

Despite HTMD provides all the necessary functionalities, we decided to develop automated workflows, called “protocols or flows” that will ease and standardize the use of HTMD features. A command-line interface was designed to perform complex workflows with few inputs, allowing the user to customize its own protocol.

Several protocols are available with their specific options that the user can play with.
While the interface is simple and fixed (few options are available), Acellera Flows provide enhanced flexibility through template generation, meaning that the entire workflow is saved in pure python script.

At the moment, 4 protocols are available:

  • Build Flow: A protocol to build systems with amber and charmm.
  • SimpleRun Flow: A protocol to equilibrate and run MD simulation
  • RunAdaptLig Flow: A protocol to run adaptive sampling for ligand-protein recognition
  • CheckAdaptLig FLow: A protocol to analyze the ligand-protein adaptive simulation

Coming soon:

  • RunAdaptProt Flow: A protocol to run adaptive sampling for protein conformation
  • MembraneBuilder Flow: A protocol to prepare phospholipid bilayer
  •  CheckAdaptProtFlow: A protocol to analyze the protein adaptive simulations

For more details, please visit our software website.

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Acellera’s new website

As you might have noticed, Acellera’s website has experienced a few changes: Our consultancy services have been included inside the products section so it is easier to find out what fits your needs best; we have also simplified the Science section, classifying our articles in categories in order to make it easier for you to find them. At the bottom of every page, you can see the latest posts in the blog, our recent activity on Twitter -we invite you to follow us 😉 – and the subscription form to our products’ newsletters.

All our pages follow a similar architecture so that it is easier to navigate trough our contents and find what you are looking for. We have also included some videos to better illustrate some possible uses of our products and/or software. Finally, the new Partnership page includes information on how Acellera manages relationships with companies and laboratories which want to work with us.

We hope you like the new website and we will be glad to hear your feedback in the comments section.

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Automated Preparation and Simulation of Membrane Proteins with HTMD

By Stefan Doerr

Molecular dynamics has matured to the point where users can simulate multiple protein systems over timescales as large as milliseconds (see reference of HTMD and ACEMD at https://www.acellera.com/science/).
However, the preparation of the protein systems remains a complex step.
Tools already exist which allow the preparation of an MD system using visual GUIs or webservers.
However few, like HTMD, are built allowing scriptable system preparation for multiple hundreds of such systems.

Adapted with permission from J. Chem. Theory Comput., 2017, 13 (9), pp 4003–4011. Copyright 2017 American Chemical Society.

 

The purpose of HTMD is to provide all tools necessary for an integrated Molecular Dynamics simulation based discovery pipeline.
Therefore, in our most recent published work (S. Doerr, T. Giorgino, G. Martinez-Rosell, J.M. Damas, G. de Fabritiis High-Throughput Automated Preparation and Simulation of Membrane Proteins with HTMD in J. Chem. Theory Comput. 2017,) we present the system building and preparation tools of HTMD and it’s application on a complex use case which is the preparation of protein-membrane systems.
We apply a single building and equilibration protocol on all eukaryotic membrane proteins of the OPM database (Orientations of Proteins in Membranes)
and perform a short equilibration runs to test for the stability of the systems.
All data from the building and equilibration runs of the OPM systems is provided to the users through a webservice which also allows direct view of the trajectories, various plots and download options for further inspection.

We believe that this and upcoming advances of HTMD will help simplifying the process of performing MD-based experiments and will further broaden the user-base and popularity of Molecular Dynamics simulations.

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Preparing a Molecular System for MD with PlayMolecule

By Gerard Martínez-Rosell

PlayMolecule Introduction

One step of the simulation workflow has typically remained relatively under addressed, namely, the preparation steps before building a molecular system. These preparation steps aim to make a protein structure, usually extracted from the PDB database, ready for system building. In particular, there’s two main points that need to be addressed: (a) titration of the residues and (b) optimization of hydrogen bond (H-bond) network. Resolved protein structures usually don’t contain hydrogen atoms and therefore need to be added by the researcher before running a molecular dynamics (MD) simulation. While most hydrogens can be easily guessed, some protein residues prove to be more challenging as they co-exist in different protonation states. While in a constant-pH simulation the residues would be free to switch among the different protonation states, in a classic MD simulation protonation states are fixed and therefore must be decided beforehand. These protonation states greatly depend on the local environment of the residue and the simulation pH.

PlayMolecule ProteinPrepare

For this reason, we devised ProteinPrepare, a protein preparation web application that allows the estimation and visualization of charge states, optimization of the hydrogen bonding network of protonated structures, thorough visual inspection of the results, and rapid iteration of changes. The application provides an evaluation of the titration states of a target protein’s residues on the basis of their local environment and the optimization of its hydrogen-bonding network through the placement of missing hydrogen atoms and flipping of side chains. Special consideration is given to residues whose pKa is close to the solvent pH because they are more prone to be misclassified by the customary binary (protonated vs unprotonated) assignments; the user can interact with the results, force their chosen titration states, and have the application reoptimize the structure. The computation is executed on the server taking advantage of High-Throughput Molecular Dynamics (HTMD) a Python framework for simple molecular-simulation-based discovery. In particular, we used the proteinPrepare() functionality of HTMD, currently based on PROPKA 3.1 and PDB2PQR 2.1. As such, in contrast to most other graphical tools, this web application also provides the short HTMD Python code required to perform the same task offline for the specific structure. The web application is publicly available at www. playmolecule.org for use on the web as part of the PlayMolecule web platform.

Conclusion

The protein preparation tool presented offers three main features: (1) help in deciding the protonation states and charges of residues while still retaining the capability to change them, (2) optimization of the hydrogen-bonding network as it might have been approximative from the crystal structure, and (3) both an interactive and scriptable way to perform these tasks. Deciding on protonation states in classical molecular dynamics is critical because a change in charge can have drastic effects and invalidate all of the results. The hydrogen-bonding network optimization is important to help the protein retain the original state of the crystal structure, especially when losing an active or inactive state can take milliseconds or more to recover. The third aspect is purely one of convenience: the use of the HTMD framework allows the reproduction of any result obtained through the ProteinPrepare web interface on local computing resources and the possibility to automate the preparation steps, e.g., repeating them for a large set of structures in a high-throughput context. Coding of HTMD based analysis on local resources takes place through the Python language and can thus take advantage of any of its numerous libraries and facilities for reproducible research.

References

Martínez-Rosell, G.; Giorgino, T.; De Fabritiis, G.; J. Chem. Inf. Model., 2017, 57 (7), pp 1511–1516
Doerr, S.; Harvey, M. J.; Noe, F.; De Fabritiis, G.; J. Chem. Theory Comput. 2016 , 12, 1845 −1852.
Søndergaard, C. R.; Olsson, M. H. M.; Rostkowski, M.; Jensen, J. H. J. Chem. Theory Comput. 2011 , 7, 2284 −2295.
Dolinsky, T. J.; Czodrowski, P.; Li, H.; Nielsen, J. E.; Jensen, J. H.; Klebe, G.; Baker, N. A. Nucleic Acids Res. 2007 , 35, W522 −W525.

alejandroPreparing a Molecular System for MD with PlayMolecule
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Crucial step in AIDS virus maturation simulated for first time

Source: IMIM

Bioinformaticians at IMIM (Hospital del Mar Medical Research Institute) and UPF (Pompeu Fabra University) have used molecular simulation techniques to explain a specific step in the maturation of the HIV virions, i.e., how newly formed inert virus particles become infectious, which is essential in understanding how the virus replicates. These results, which have been published in the latest edition of PNAS, could be crucial to the design of future antiretrovirals.

HIV virions mature and become infectious as a result of the action of a protein called HIV protease. This protein acts like a pair of scissors, cutting the long chain of connected proteins that form HIV into individual proteins that will form the infectious structure of new virions. According to the researchers of the IMIM-UPF computational biophysics group, “One of the most intriguing aspects of the whole HIV maturation process is how free HIV protease, i.e. the ‘scissors protein,’ appears for the first time, since it is also initially part of the long poly-protein chains that make up new HIV virions.

Using ACEMD a software for molecular simulations and a technology known as GPUGRID.net, Gianni De Fabritiis’ group has demonstrated that the first “scissors proteins” can cut themselves out from within the middle of these poly-protein chains. They do this by binding one of their connected ends (the N-terminus) to their own active site and then cutting the chemical bond that connects them to the rest of the chain. This is the initial step of the whole HIV maturation process. If the HIV protease can be stopped during the maturation process, it will prevent viral particles, or virions, from reaching maturity and, therefore, from becoming infectious.

This work was performed using GPUGRID.net, a voluntary distributed computing platform that harnesses the processing power of thousands of NVIDIA GPU accelerators from household computers made available by the public for research purposes. It’s akin to accessing a virtual supercomputer. One of the benefits of GPU acceleration is that it provides computing power that is around 10 times higher than that generated by computers based on CPUs alone. It reduces research costs accordingly by providing a level computational power that previously was only available on dedicated, multi-million dollar supercomputers.

Researchers use this computing power to process large numbers of data and generate highly complex molecular simulations. In this specific case, thousands of computer simulations have been carried out, each for hundreds of nanoseconds (billionths of a second) for a total of almost a millisecond.

According to researchers, this discovery in the HIV maturation process provides an alternative approach in the design of future pharmaceutical products based on the use of these new molecular mechanisms. For now, this work provides a greater understanding of a crucial step in the life cycle of HIV, a virus that directly attacks and weakens the human immune system, making it vulnerable to a wide range of infections, and which affects millions of people around the world.

Reference:

Kinetic characterization of the critical step in HIV-1 protease maturation”. S Kashif Sadiq, Frank Noe and Gianni De Fabritiis. PNAS. DOI:10.1073/pnas.1210983109.

ACEMD Simulation details.

alejandroCrucial step in AIDS virus maturation simulated for first time
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Penguin Computing Showcases Acellera’s ACEMD at SC2012

PENGUIN COMPUTING SHOWCASES ACELLERA’S ACEMD AT SC2012 LONDON, UK – 10 November 2012

Acellera today announced that Penguin Computing will showcase Acellera’s ACEMD on POD (Penguin Computing ON Demand) at Supercomputing 2012 in Salt Lake City, Utah, booth 3866. ACEMD is the world’s fastest and most efficient bio-molecular dynamics (MD) engine for GPU nodes and workstations. Specifically optimized to run on NVIDIA graphics cards, ACEMD enables on a single GPU performance equivalent to more than 100 CPUs while maintaining microsecond trajectories. In combination with POD, ACEMD aims to facilitate the transition of MD from a multi-node, single-trajectory science to high-throughput MD (HT-MD), a new paradigm in computational biophysics.

Matt Jacobs, Sr. Vice President of Corporate Development for Penguin Computing states, “As we approach the clock cycle limits on traditional CPU architectures, multicore and GPU technologies are moving to the forefront to reshape the way our customers conceptualize their research. Acellera’s ACEMD package demonstrates the true capabilities that this new level of parallelism offers and Penguin Computing is pleased to be able to showcase this package on our POD environment at this year’s Supercomputing conference.”

Molecular Dynamics simulation is a powerful technique for investigating biological systems with atomic resolution. Prior to the introduction of Acellera’s ACEMD, the cost of bio-MD simulations for R&D was prohibitive, requiring hundreds of CPU cores for a single run on dedicated HPC clusters. ACEMD transformed the bio-MD field by introducing highly optimized bio-MD simulation on comparatively low-cost GPUs, enabling supercomputing class simulations on a small GPU cluster. ACEMD enables new kinds of analyses, such as the complete reconstruction of protein–ligand interactions in terms of thermodynamics and kinetics, or MD based fragment-based drug discovery. Such studies open new avenues in pharmaceutical research, and illuminate ligand binding site and pose, as well as specific kinetic signatures that can be associated with the quality of small molecules during drug development.

“We are pleased to have this opportunity to work with such a reputable provider of world-class HPC solutions. Penguin’s POD technology combined with Acellera’s ACEMD provides an unbeatable platform for on-demand, highly-efficiency bio-MD simulation for all scientists, from those just beginning to explore its huge potential to established MD users” states Gianni De Fabritiis, Founder and Chief Science Officer at Acellera.

ACEMD is the engine behind GPUGRID, one of the largest distributed computing projects worldwide. ACEMD is stable, scalable, robust, and can handle thousands of highly demanding MD simulations daily. ACEMD simulations have helped researchers push our understanding of protein-ligand interactions, ion channel dynamics, membrane protein behavior, and mechanisms for drug resistance.

Penguin Computing and Acellera are looking to expand their partnership to include turn-key solutions which integrate Acellera and Penguin technology. This would mark Penguin Computing as the first U.S. Value Added Reseller and provider of L1 system support for Metrocubo, Acellera’s MD appliance.

To experience a demonstration of ACEMD at SC2012, visit Penguin Computing booth 1217 November 12-15th where ACEMD simulations will use POD, an HPC cloud that provides instant availability on-demand. Interested parties will be offered the opportunity during those same dates to challenge ACEMD with their own systems on POD. Contact David Soriano at info@acellera.com for more information.

About Penguin Computing
For well over a decade Penguin Computing has been dedicated to delivering complete, integrated High Performance Computing (HPC) solutions that are innovative, cost effective and easy to use. Penguin offers a complete end-to-end portfolio of products and solutions ranging from Linux servers and workstations to integrated, turn-key HPC clusters and cluster management software. For users that want to use supercomputing capabilities on-demand and pay as they go, Penguin offers ‘Penguin Computing on Demand’ (POD), a public HPC cloud that is available instantly and as needed. With its broad portfolio of solutions Penguin is the one-stop shop for HPC and enterprise customers and counts some of the world’s most demanding HPC users as its customers, including Caterpillar, Life Technologies, Dolby, Lockheed Martin, the U.S. Air Force, and the U.S. Navy.
To learn more, visit http://www.penguincomputing.com

About Acellera
Acellera is a UK based company focused on providing new technologies in the field of research and development. Since 2006, Acellera has innovated in the field of molecular dynamics simulation software for accelerator processors. Its current flagship product, ACEMD, delivers cluster-computer levels of performance for MD simulations on personal GPU workstations. Computational throughput is also optimized through the joined development of software and hardware. Recently, Acellera designed and patented a new enclosure for GPU optimized calculations for these purposes.
One mission of Acellera is to develop high-throughput molecular dynamics techniques that deliver solutions for estimating common physical chemistry properties as binding affinities, kinetics, poses and pathways with experimental accuracy. The development of new methods for molecular data analysis allows us to understand binding processes to a new level of insight. In this field, the Binding Assay solution by Acellera provides a level of details on the binding process that is unique worldwide.
Acellera is the owner and unique provider of the intellectual property behind all these technologies and the software, hardware infrastructure.
To learn more, visit http://www.acellera.com

Penguin Computing is a registered trademark of Penguin Computing, Inc. Penguin Computing on Demand is a pending trademark in the U.S. ACEMD is a trademark of Acellera. All other trademarks are property of their respective owners. Other product or company names mentioned may be trademarks or trade names of their respective companies.

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Acellera will be at SC12 in Salt Lake City NOV 12-15

We will be with Penguin Computing at booth 3866. We will be showcasing ACEMD on POD (Penguin on demand) and also Metrocubo, and the Metrocubo Chassis (Patent Pending). Come see us! Have a system you want to test? Bring the files to the booth and we will benchmark it right there.

alejandroAcellera will be at SC12 in Salt Lake City NOV 12-15
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New paper in JACS on conformational characterization of HIV-1 RT

A new paper using ACEMD has been published in JACS under the title Thumbs Down for HIV: Domain Level Rearrangements Do Occur in the NNRTI-Bound HIV-1 Reverse Transcriptase stemming from a collaboration between University College London (UK) and Universitat Pompeu Fabra (Spain) researchers.

In this work researchers unveiled previously undescribed closed conformations in drug-bound HIV-1 RT which suggesting that “allosteric modulation is effected via the alteration of the kinetic landscape of conformational transitions upon drug-binding”. In the publication researchers also state that “a more detailed understanding of the mechanism of NNRTI inhibition and the effect of binding upon domain motion could aid the design of more effective inhibitors and help identify novel allosteric sites.”

The work was performed through an ensemble molecular dynamics strategy using ACEMD and aggregate simulation time of ~0.6 µs.

Reference:
D. W. Wright, S. K. Sadiq, G. De Fabritiis, P. V. Coveney, Thumbs Down for HIV: Domain Level Rearrangements Do Occur in the NNRTI-Bound HIV-1 Reverse Transcriptase, J. Am. Chem. Soc., 2012, 134 (31), 12885–12888. http://pubs.acs.org/doi/abs/10.1021/ja301565k

alejandroNew paper in JACS on conformational characterization of HIV-1 RT
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Science paper confirms ACEMD results

A Science paper titled “Structural Basis for Allosteric Regulation of GPCRs by Sodium Ions” by the group of Professor R. C. Stevens at The Scripps Research Institute in La Jolla, CA (USA) has confirmed the role of sodium ions in the allosteric regulation of GPCRs as it had been modeled by Selent et al. in 2010 using high-throughput MD simulations on ACEMD.

Results by Stevens Group shed on the importance of endogenous small molecules at specific binding sites as control mechanisms of membrane proteins. Such concept exceeds the common view of allostery via pharmacological ligands. The results have profound effects on the current understanding of the functional mechanisms of GPCRs, a broad family of proteins that comprises many of today’s pharmacological targets.

In that regard, computational modeling of small molecule-protein interactions using ACEMD has proven powerful tool to predict unknown solvent-derived effects on protein function.

References:

– Liu W., et al., Structural Basis for Allosteric Regulation of GPCRs by Sodium Ions, Science 2012: 337 (6091), 232-236. DOI:10.1126/science.1219218

– Selent J., et al., Induced Effects of Sodium Ions on Dopaminergic G-Protein Coupled Receptors, PLOS Computational Biology 2010, 6, e1000884. DOI:10.1371/journal.pcbi.1000884

– Source: The Scripps Research Institute

alejandroScience paper confirms ACEMD results
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