Subject: Semi-empirical parameterization...

From: [email-masked] (Joe M Leonard)
Date: Wed, 13 Apr 1994 16:04:20 -0400

Something for folks to think about...

The various SE parameter sets were all (to the best of my knowledge)
developed on VAXen about 10-ish years ago (6-ish for PM3?).  Since
that time, there's been a 2-4 orders-of-magnitude increase in
CPU horsepower, and there has to be an improvement in the quality and/or
amount of experimental data to parameterize against.

Doesn't this suggest that it's a worthwhile idea to develop an AM2/PM4
set (with or without d-orbitals) that could (a) use the extra
stuff mentioned above and (b) specifically examine the known problem
areas of the various methods?  Judging from solvation work such
as AMSOL, parameter sets can be generated in a CPU-day or a CPU-week
on the high-end stuff available now.  Several/Many sets of params can
be generated very quickly, using whatever scientific or
empirical constraints one wishes to impose...

This doesn't even take "novel" machines like SIMD/MIMD/MPP boxes into
account - these might make the process even faster.  

Folks will probably say that "we should not invalidate past results".
True, but if Allinger's allowed three different mechanics FF's (not
counting the modifications to each that have appeared over time), I think
folks will readily accept a new SE parameter set if it's properly done and
disseminated.

This way, we'll be able to get rid of any problem areas that are artifacts
of the limited capabilities and/or datasets used in the earlier
work.  It will also let folks include LARGE small molecules as opposed to
the SMALL small molecules used in the past.

Whatcha think?

Joe Leonard
[email-masked]

---

From: <[email-masked]>
Date: Wed, 13 Apr 1994 16:25:57 -0500 (CDT)

> on the high-end stuff available now.  
> 
   It is quite flattering to be held up as an example of fast, effective
semiempirical parameterization! 

   In all fairness, however, the SMx solvent models are probably
slightly more simple to develop than a full-blown semiempirical parameter
set that is designed to reproduce many different chemical properties (not
just solvation free energy). [I do not necessarily speak for our entire 
group in this matter, but I personally believe this to be true.]

   This is not to suggest that the above is not a laudable goal! It strikes
me, though, that more careful evaluation of MNDO/D, SAM1, and SINDO (Thiel et
al., Dewar et al., and Jug et al., respectively) would perhaps save some
effort in this regard. Regrettably, for a variety of reasons, there appears
to be little movement in this direction [Perhaps that should be taken as a
compliment to AM1 and PM3]. I suspect that improving on previous Hamiltonians
will require a new MODEL, as opposed to another search of parameter space.

   On another note, ab initio theories are of great value because they are
completely general, but the focus of modern chemistry is not completely
general. Rather, societal and governmental priorities dictate more pronounced
emphasis on specific topics. I wonder if another completely general
semiempirical parameterization is really worth the effort. Something that
would arguably be better received would be a particularly accurate model for
proteins, membranes, [insert your favorite chemical topic here], etc., where
the cost function used in the parameterization would be more tightly focused
than has been the case in the past. Much like molecular mechanics, such a
model would be particularly good at what it is particularly good at, and no
guarantees would be offered for distant extensions.

   Finally, work does continue on semiempirical methods -- they are called
exchange-correlation functionals . . .

CJC

-- 

Christopher J. Cramer
University of Minnesota
Department of Chemistry
207 Pleasant St. SE
Minneapolis, MN 55455-0431
(612) 624-0859
[email-masked]