Computation based on molecular models is playing an increasingly important role in biology, biological chemistry, and biophysics. Since only a very limited number of properties of biomolecular systems is actually accessible to measurement by experimental means, computer simulation can complement experiment by providing not only averages, but also distributions and time series of any definable – observable or non-observable – quantity, for example conformational distributions or interactions between parts of molecular systems. Present day biomolecular modelling is limited in its application by four main problems: 1) the force-field problem, 2) the search (sampling) problem, 3) the ensemble (sampling) problem, and 4) the experimental problem. These four problems will be discussed and illustrated by practical examples. Progress over the past thirty years will be briefly reviewed. Perspectives will be outlined for pushing forward the limitations of molecular modelling.

Why Thirty Years?

…first simulations were performed in 1976..

Molecular modeling choices to make:

• Degrees of Freedom: atoms are elementary
• Forces (interactions between atoms)
• Boundary conditions
• Methods to generate configuration of atoms: Newton’s equation

Simulations can:

• explain experiment
• provoke experiment
• replace experiment
• aid in establishing intellectual property

The four problems

• Force field problem
• The search (sampling) problem
• The ensemble sampling problem
• The experimental problem

The Force Field problem

• small free energy differences
• account for entropic effects
• variety of atoms and molecules (keep it simple; transferable parameters)

…using only the PDB for force field development just doesn’t work out.

Most dominant fold is not difficult; equilibra between folds is more important.  Should be able to get melting temperatures from simulations.  Solvent viscosity drives the kinetics of folding.  Todo: Polarizable force-fields.
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The searching (sampling) problem

A. convergence
B. alleviated
C. aggrevated

Methods to compute free energy

• counting configurations
• thermodynamic integration (many simulations)
• perturbation formula (one simulation)
• One-step perturbation (few simulations)

- use “soft-core” atoms for each site where the inhibitors will interact.

Original Viagra and Levitra could have benefitted from this method (IP, patents)

The ensemble (sampling) problem

• Entropy
• Averaging
• Non-linear averaging

Coiled-coil stability has a strong entropic component.  For monomers the solute-solvent interaction decreases.  For trimers the solute-solute interaction decreases.  Entropy increases with temperature.  In trimers atomic fluctuations do not increase with temperature but solute entropy increases with temperature.

The experimental problem

• Averaging
• Insufficient data
• Insufficient accuracy

“Averages are dangerous”

Conclusions:

• Experimental data cannot determine the average structure
• Experimental data cannot determine the biomolecular structure

Artifacts of XPLOR NMR refinement disagree with simulations guided by NOE-restraints
- Two ensembles with no ensemble overlap and given same experimental data

“Experimental data is not sufficient”

Don’t rely on structural data (It’s derived; strive for primary data)

History

1957 First molecule
1964 atomic liguid (argon)
1971 molecular liquid (water)

Future

2001 –
2029 Biomolecules in water
2034 E-coli
2056 Mamallian cell (10^-9 sec)
2080 Biomolecules in water (fast as nature) 10^6
2172 Human body (10^27 atoms) 1 sec

So what if you could simulate every atom in your body for 1 second?

– There’s much better things simulation can answer; ask better questions.

Polarizable Force Field

- improves transferability between different environments
- working on these force fields
- solvation drives protein processes

Coarse-graining

- Need to switch FG/CG, back and forth
- Run simulations in parallel
- Easy to clamp 5 atoms to 1 but not easy to map 1 to 5
- FG/CG replica-exchange simulation enhances sampling
- Much faster to cross barriers in CG mode if you can switch
- Both force-fields must be thermodynamically calibrated

We need simulations to explain experiment; so we can see the numbers.  For molecular modelers, there’s still enough work to do at least until 2172!

Questions from the audience

Q: What’s the state of NMR determination
A: It depends, narrow bundles should have more motion.  Stable proteins are easy.  Averaging problem is present even in Crystallography.  Can’t get R-values.  Many many structures are not that good (XPLOR FF is simple, no solvent).  Found 20% of side-chain J-values cannot be right.  Simulation is getting to the point to correct experiment.

Q: Could you comment on CG model ‘clamping atoms’ and potential problems related to entropy
A: Take 5 atoms, make a ball, you lose entropy.  You should compensate that in the energy level?  You must balance it.

Q: Is Path integral still useful?
A: No, we’d like to remove it next version of Gromos.

Professor van Gunsteren is a big believer in using all the data you can get your hands on.

Just in case you need another -omics in your biotech vocabulary. Dynameomics is an effort by the Dagget group at the University of Washington to

characterize the native-state dynamics and folding/unfolding pathways of representatives of all known protein folds by way of molecular dynamics simulations

Three successive articles have been published in Protein Engineering Design & Selection to describe over 3000 long molecular dynamics simulations, the computational workflow, and data mining capabilities of Dynameomics. Dynameomics has applets for visual analysis and even high-quality movies of their MD trajectories!

Papers:

• Dynameomics: mass annotation of protein dynamics and unfolding in water by high-throughput atomistic molecular dynamics simulations
• Dynameomics: a multi-dimensional analysis-optimized database for dynamic protein data
• Dynameomics: design of a computational lab workflow and scientific data repository for protein simulations

Video: 4PGA unfolding movie

SC07 is in full swing in Reno. I promised some details about the PSC booth, more specifically the Wiimote controlled Molecular Dynamics demo. Some credit for this idea should go to Adam Marko, who is now a graduate student at UCSF joining the lab of Andrei Sali.

The real selling point of the Nintendo Wii video game console has been the Wiimote. For those who haven’t experienced one, the Wii Remote is very different from a typical video game controller. It has a built in accelerometer, motion sensing, and optical sensing. It communicates over bluetooth, and best of all it only costs around $50 US. These features work to enrich video games through unique human-computer interaction. The sports games that come bundled with the Wii demonstrate how previously mundane gameplay such as bowling, baseball, and tennis can be a blast with clever interaction design.

In the context of biotech, haptic interfaces could really have a big impact in how biologists, life scientists, and medical profesionals interact with computers and devices. The computer geek in me wants to believe that a keyboard and mouse is the one true way to use a computer but the success of video games consoles, Tablet PC’s, and iPhones are changing the face of computing. Imagine biosimulations which are no longer just scripts, plots, and post-process rendering but rather augmented reality. Where a scientist can use virtual instruments and interact with their simulations in real time.

Before I get ahead of myself, let me explain the demonstration you can see at the PSC booth if you’re attending SC07. It is quite simple to use a Wiimote to replace your mouse on a standard PC. Several months ago we played around with Wiimotes on our workstations, manipulating protein structures in VMD and CHIMERA which are both excellent molecular graphics and modeling programs. In this case the Wiimote just acts as a mouse, and doesn’t really offer much advantage, especially for someone who uses VMD with a mouse and keyboard. Pretty cool, but not very practical for me personally. So the Wii Remotes were left in the drawer until discussion about demos for SC07 arose. That’s when some other PSC heads got involved and the idea blossomed.

VMD is a cool program to use with a Wiimote, but a moving a single protein structure isn’t very interesting. Let’s do a NAMD simulation instead. Better yet, let’s use IMD to have an interactive NAMD simulation. And while we’re at it, let’s run it live on Big Ben (PSC’s 4,000+ processor Cray XT3). After all, Supercomputing is our middlename. The “WiiMD” demo is live at SC07 thanks to key efforts by Nathan Stone, Shawn Brown, and student Jordan Soyke. Unfortunately I could not be there to see the final result, but some work was done with PDIO, a middleware that routes data straight from the nodes of the XT3 to a remote location in real-time. There was also a rewrite of the Wiimote input driver, which Jordan talks about briefly in his blog.

Stop by the PSC booth if you get a chance. I hope to have pictures or video of the demo up sometime soon.

PSC Live! at SC07
WiiMD, interactive molecular dynamics with a wiimote?

And my two favorite blogs have noticed!
scalability.org – Coolest demo I saw today
BBGM – Finally found a reason to buy a Nintendo Wii

Wii Linux
Wiimote playing Half-life