Hi Guillaume,
I think it this case it's something else. According to the Todeschini article
the smallest moment of inertia of a planar molecule like benzene should be
zero. The eigenvalues of the inertia matrix for benzene, however, are
definitely not zero (and not close enough that it's likely to be round-off
error).It would be very nice if you could run the three files I mention through
Dragon and let me know what it calculates for those descriptors.
-greg
_____________________________
From: Guillaume GODIN <guillaume.go...@firmenich.com>
Sent: Sunday, January 15, 2017 1:11 PM
Subject: RE: [Rdkit-discuss] PMI API
To: Greg Landrum <greg.land...@gmail.com>, RDKit Discuss
<rdkit-discuss@lists.sourceforge.net>, Chris Earnshaw <cgearns...@gmail.com>
Dear Greg,
I suspect that it's a precision error or eigen algorithm shift between rdkit
c++ & dragon.
To obtain good value, I suggest to try to implement a test on the eigen values
like i did in gateway.cpp implementation.
JacobiSVD<MatrixXd> getSVD(MatrixXd A) {
JacobiSVD<MatrixXd> mysvd(A, ComputeThinU | ComputeThinV);
return mysvd;
}
// get the A-1 matrix using
MatrixXd GetPinv(MatrixXd A){
JacobiSVD<MatrixXd> svd = getSVD(A);
double pinvtoler=1.e-2;// choose your tolerance wisely!
VectorXd vs=svd.singularValues();
VectorXd vsinv=svd.singularValues();
for (unsignedint i=0; i<A.cols(); ++i) {
if ( vs(i) > pinvtoler )
vsinv(i)=1.0/vs(i);
else vsinv(i)=0.0;
}
MatrixXd S = vsinv.asDiagonal();
MatrixXd Ap = svd.matrixV() * S * svd.matrixU().transpose();
return Ap;
}
If it's not solve the problem, I would like to test it in Matlab. can you
provide me the 3 (3d xyz matrix) of your example please ?
I also have Dragon 6
best regards,
Dr. Guillaume GODINPrincipal ScientistChemoinformatic &
DataminingInnovationCORPORATE R&D DIVISIONDIRECT LINE +41 (0)22 780 3645MOBILE
+41 (0)79 536 1039 Firmenich SA RUE DES JEUNES 1 | CASE
POSTALE 239 | CH-1211 GENEVE 8
De : Greg Landrum <greg.land...@gmail.com>
Envoyé : dimanche 15 janvier 2017 11:50
À : Chris Earnshaw; RDKit Discuss
Objet : Re: [Rdkit-discuss] PMI API I managed to make some time to look into
this this weekend and I've found a bug and something I don't understand.
Hopefully the community can help out here.
On Sun, Jan 8, 2017 at 11:17 AM, Chris Earnshaw <cgearns...@gmail.com> wrote:
4) The big one! The returned results look very odd. They appear to relate more
to the dimensions of the molecule than the moments of inertia. For a rod-like
molecule (dimethylacetylene) I'd expect two large and one small PMI (e.g. PMI1:
6.61651 PMI2: 150.434 PMI3: 150.434 NPR1: 0.0439828 NPR2: 0.999998) but
actually get PMI1: 0.061647 PMI2: 0.061652 PMI3: 25.3699 NPR1: 0.002430
NPR2: 0.002430.
For disk-like (benzene) the result should be one large and two medium (e.g.
PMI1: 89.1448 PMI2: 89.1495 PMI3: 178.294 NPR1: 0.499987 NPR2: 0.500013)
but get PMI1: 2.37457e-10 PMI2: 11.0844 PMI3: 11.0851 NPR1: 2.14213e-11
NPR2: 0.999933.
Finally for a roughly spherical molecule (neopentane) the NPR values look
reasonable (no great surprise) but the absolute PMI values may be too small:
old program - PMI1: 114.795 PMI2: 114.797 PMI3: 114.799
NPR1: 0.999966 NPR2: 0.999988, new program - PMI1: 6.59466 PMI2: 6.59488
PMI3: 6.59531 NPR1: 0.999902 NPR2: 0.999935
Your expectations are correct: the current RDKit implementation is wrong. The
corresponding github entry is here:
https://github.com/rdkit/rdkit/issues/1262This is due to a mistake in the way
the principal moments are calculated (which is due to the fact that I don't
spend a lot of time working with/thinking about 3D descriptors). Instead of
using the eigenvectors/eigenvalues of the inertia matrix (the tensor of
inertia) the RDKit is currently using the covariance matrix. There's some more
on the relationship between these two here:
http://number-none.com/blow/inertia/deriving_i.html
The problem is easy to fix (and I have something working here:
https://github.com/greglandrum/rdkit/tree/fix/github1262), but it screws up the
values of the descriptors that are derived from here:Todeschini and Consoni
"Descriptors from Molecular Geometry" Handbook of
Chemoinformaticshttp://dx.doi.org/10.1002/9783527618279.ch37These include the
radius of gyration, inertial shape factor, etc.Within that article they state
that Ic = 0 for planar molecules. Ignoring the inequality on page 1010, which
says that Ic is the largest moment and is contradicted by the rest of the text
(particularly the inequalities on page 1011), Ic corresponds to the smallest
principal moment : PMI1.
So now I'm confused, but I'm hoping this is obvious to someone versed in the
field: I'd like to reproduce the descriptors described in the Todeschini
article, but I clearly can't do that using the actual moments of inertia. I
could keep using the eigenvalues of the covariance matrix there, but that
doesn't match what's described in the text.
Two things that would be extremely helpful:1) an explanation of the disconnect
here from someone who knows this stuff, I would guess that it's pretty simple2)
The results of running the files github1262_1.mol, github1262_2.mol, and
github1262_3.mol from here:
https://github.com/greglandrum/rdkit/tree/fix/github1262/Code/GraphMol/MolTransforms/test_data
through Dragon and calculating the radius of gyration, inertial shape factor,
eccentricity, molecular asphericity, and spherocity index.
Best,-greg
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