Subject: rigid body summary

From: Richard Gillilan <[email-masked]>
Date: Tue, 25 Nov 1997 09:48:03 -0500

Many thanks to those who responded! I have had some very useful
conversations. (I have shortened some of the responses
in some cases as indicated by ... )

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My original post:

A number of programs (like XPLOR) have implemented the virtual
rigid body dynamics of T. Head-Gordon and C. Brooks
(Biopolymers vol 31, 77-100 (1991). I've seen a few notes
on CCL about "Moldy" that sound like it too can do this.

Does anyone have info about the program?

Also:

1. Does anyone know of recent studies using this technique,
   particularly applied to the protein-protein docking?

2. How does it compare with SHAKE type constraint methods:
   faster/slower or just different?

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From: me ([email-masked])

Moldy, XPLOR, and recent versions of CHARMM and INSIGHT
seem to support various kinds of rigid-body dynamics. 
MBO(N)D sounds particularly intriguing, see comments
>from moldyn below. Here's somthing from NASA about it too:
---
NASA Success Story (http://ntas.techtracs.org/4d.acgi$w3SuccItem(1000197))

                                  DRUG RESEARCH

NBOD2 is a computer program developed at NASA's Goddard Space Flight Center
to solve equations of the motion of systems consisting of many objects. The
program is used by DuPont to model the process of the binding between drugs
and enzymes to help develop new drugs. Enzymes are complex proteins that help
certain chemical reactions in the body. NBOD2 helps to determine what the 
properties of a new drug will be. It was supplied to DuPont by NASA's 
Computer Software Management and Information Center, or COSMIC(R).

Now on to the replies:
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From: 
        "Gustavo A. Mercier Jr" <[email-masked]>

Moldy was develope by Keith Refson in the UK and is available
by ftp. It is written in C and is highly vectorized/parallelized.
Also, it has been implemented in many machines. The code does
not implement the virtual rigid body dynamics of H-G and Brooks.
I remember browsing over their paper, but remember little of the details.
So, I will stick to describing moldy.

Moldy is intended for rigid body dynamics of molecules in liquids and
crystal systems. It also incorporates the idea of a framework. This is
like a slab of a charged crystal above which you have a
group of atoms/molecules that move in an MD simulation. I guess that
a framework could represent one face of a macromolecule above which
a ligand is trying to find the binding site. Needless to say that was
not the intended application. Moreover, I don't have experience
with frameworks.

Moldy only supports two body Van Der Waal potentials of several kinds,
in addition to the two body electrostatic terms associated with partial
charges in the molecules/atoms.

The dynamics are done using quaternions, rather than Euler angles,
and the coordinates of the center of mass. It supports the Gaussian
Thermostat and the Noose-Hover thermostat, as well as variations
of the latter for constant pressure computations. It has a few
utilities that are useful in fetching out and visualizing the results.
The integration scheme is a Beeman algorithm that is of  higher
order than the Verlet scheme commonly used in Charmm/X-Plor/AMBER.
It uses E-wald summation together with a linked-cell method
to compute the intermolecular interactions in a periodic system. ...
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From: 
           [email-masked]

I inspected Moldy's capabilities for rigid body protein docking (which I
right now do with XPLOR); it also implements the Newton-Euler equations of
motion which are used to propagate collections of rigid bodies.
 
Moldy can be downloaded from ftp.earth.ox.ac.uk using anon ftp; relevant files
are in the /pub directory (information taken from Moldy 2.12). The author
is Keith Refson ([email-masked]).

> 1. Does anyone know of recent studies using this technique,
>    particularly applied to the protein-protein docking?

The recent protein-protein docking studies that I know of seem to choose
different ways of simplifying the proteins involved: Either a simplified
energy function (which takes into account only that part of the interaction
deemed relevant by the authors) is minimized using a MonteCarlo-Simulated
Annealing-like protocol, or the minimum is found by complete enumeration
(as in the case of the Fourier-convolution based approaches). All these
approaches trade a detailed description of the dynamics for docking speed.
On the other side, some MD studies of docking have been performed (cf. Di
Nola et al., 1994). I haven't found any studies on protein-protein docking
using Head-Gordon's VRBD.

As part of my current project, I'm studied protein-protein docking using
VRBD within XPLOR. Let me know if you're interested in my experiences.

> 2. How does it compare with SHAKE type constraint methods:
>    faster/slower or just different?

Just different would be a better description, as you constrain the bond
angles and dihedrals as well (dependent of course, on the way you choose
your rigid bodies).
Second, in the SHAKE approach, each atom still experiences the force due to
it's interaction with the rest of the  system. In VRDB (as proposed by
Head-Gordon) , a force/torque acting on a  rigid body is derived from the
forces acting on it's constitutive atoms.
Third, Head-Gordon in her work enforces planarity of the peptide bond by
turning it into a rigid body. Thus,  your dynamics will differ
>from a plain bond-length SHAKE simulation.

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From: 
        Konrad Hinsen <[email-masked]>

I have no practical experience with VRBD, but with other treatments
of rigid-body and constrained systems, which may be of interest.

First of all it is necessary to distinguish between the consequence of
applying certain constraints and the limitations/efficiency of particular
methods to do so. Obviously keeping a peptide group rigid is a stronger
constraint than fixing just the bond length, but it also comes with a
higher reduction of fast degrees of freedom, which is after all the
reason for applying mechanical constraints. For a discussion and an
explicit comparison for helix dynamics, see

    K. Hinsen, G.R. Kneller
    Influence of constraints on the dynamics of polypeptide chains
    Phys. Rev. E 52, 6868 (1995)

Once you have chosen the constraints you want to apply (that's a
physical choice), you must then pick a method to implement them (that's
an algorithmic choice). In this choice you must consider the limitations
and efficiency criteria for each method. For SHAKE these are

- limitation: no rigid groups of more than three atoms (planar)
  or four atoms (non-planar)  (at least for the commonly implemented
  original version of SHAKE, a generalization has been published,
  but is not in general use)
- efficiency problem: strongly interdependent constraint cause
  a long iteration

For VRBD:

- limitation: no constraints between rigid units
- efficiency consideration: most efficient for large rigid units

Note that many other techniques for implementing constraints have
been proposed and/or tested.

In principle, the results for a given set of constraints should be
identical irrespective of the method used, but I am not aware of any
practical comparison.

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From: 
        [email-masked] (Hon M Chun)

        There is a new modeling approach called MBO(N)D (for Multibody
Order (n) Dynamics) that has more capabilities than the original
Head-Gordon and Brooks work.  It was developed at Moldyn as a result
of application of flexible spacecraft simulation techniques to
molecular dynamics modeling.  The main difference is that, in addition
to providing rigid body dynamics capabilities, MBO(N)D allows the
bodies to be flexible, using body-based mode vectors to describe the
allowed deformational motions.  Another difference is that bond length
constraints can be optionally applied across bonds connecting adjacent
bodies.  Bodies can be defined to be as small as rings and peptide
planes, or as large as whole residues, secondary structures, or
domains.  Individual atoms can be modeled as particles.  Of course,
the user needs to decide what level of grouping is appropriate for the
problem at hand.  A multiple time scale integrator allows the
efficient simulation of models where there co-exist bodies of various
sizes, and even individual atoms.

        The code is interfaced to CHARMM, and uses a slightly extended
set of keywords for the input script file.  The combined code is also
interfaced with INSIGHT 97.0, and is currently available from
Molecular Simulations, Inc, which distributes CHARMM and MBO(N)D to
commercial, academic, and government organizations.  (The contact
person at MSI is Mary Donlan; her e-mail address is [email-masked].)

        A paper on MBO(N)D is being prepared for journal submission.
I will be happy to send you a pre-print when it is ready.

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