Dear Qchem Experts,

Can I use the OPLSAA force field AND standard quantum chemical method (DFT) in a combined optimization? i.e. to have a molecule (DFT) surrounded by explicit solvent molecules (OPLAA force field)? Simple in doesn’t seem to work.

Tadeusz

Here is a very simple example of a water dimer, one molecule QM (PBE0 functional) and the other MM (OPLS force field). Works with either JANUS or ONIOM QM/MM interface. This is sample job QMMM_oniom_opt.in.

$comment

Example of an ONIOM optimization on a water dimer.

$end

$rem

exchange pbe0

basis 6-31G*

qm_mm_interface oniom ! could be janus instead

force_field oplsaa

user_connect true

jobtype opt

molden_format true

$end

$qm_atoms

4 5 6

$end

$molecule

0 1

O -0.790909 1.149780 0.907453 186 2 3 0 0

H -1.628044 1.245320 1.376372 187 1 0 0 0

H -0.669346 1.913705 0.331002 187 1 0 0 0

O 1.178001 -0.686227 0.841306 186 5 6 0 0

H 0.870001 -1.337091 1.468215 187 4 0 0 0

H 0.472696 -0.008397 0.851892 187 4 0 0 0

$end

If you have a large number of MM water molecules, then you may want to use the L-BFGS optimizer, which is turned on by adding something like

$forceman

QMMM-LBFGS

LBFGS_M 10

$end

(see sample job lbfgs_qmmm.in). By default, Q-Chem’s geometry optimizers use delocalized internal coordinates and a quasi-Newton optimization algorithm, which is a good choice for efficient location of the minimum but requires diagonalization of a Hessian-like matrix. For QM-only jobs where system size is severely limited by QM cost, that diagonalization step seldom becomes a bottleneck but that’s not true for QM/MM, where total (QM + MM) system size can be quite large. In such cases, the L-BFGS algorithm offers a limited-memory alternative, albeit at the expense of a generally much larger number of optimization steps.