MATTPROB
is an updated, parameter free estimator calulating normalized
probabilities for the occurrence of multimerization states. Originally the
estimator was based on a
2003 survey of Vm (Matthews coefficient) and solvent content (Vs) distribution of about 11,000
non-redundant crystallographic PDB entries (Kantardjieff and Rupp,
Protein Science
12:1865-1871,
2003). The 2013 data set has grow to over 60000 entires and
the program can be used with the 2013 parametrized version or the
new kernel estimator, which allows any given resolution range to
be entered without the need to use binned data. The absence of
binning and a 6x larger learning test set can give more accurate
results.
Higher packing density and this lower solvent
content significantly correlate with increasing resolution and can be used to provide a more
refined probability for the occurrence of a certain oligomerization state. The
program thus accepts
resolution as additional information to select the proper probability distribution.
The assumption
is that observed resolution represents an estimate for the lower limit for crystal quality, i.e.,
crystals obviously diffract to at least this value (but could also diffract better).
It must be understood that the answers are always relative probabilities based
on our current state of knowledge and that no clear answer may result in certain
cases.
One can also enter the molecular data for
one monomer and select its known multimerization state, in case you know what
basic multimer unit you are looking for. For example, if your known molecular unit is a trimer, you may
want to look for 3-mer, 6-mer, 9-mer etc. Note that crystallographic axes coinciding with multimer axes can result in improbably
low Vm for a single multimer unit. Whenever possible, use
the correct molecular weight based on the sequnce and not
the estimated value based on residue number.
The results are represented in
tabular form at the top of the output followed by two graphs showing the
normalized probability distributions (resolution corrected and all PDB data) against Vm and Vs, respectively.
We would appreciate citation of the
two following references when using this program in published work:
The old parameterized
fit function and
parameter files from
2003 and 2013 are also available for download.
For developers, the implemenation and the link
to the data filed for the kernel estimator can be found in the
Computational
Crystallography Newsletter 15, January 2015.
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