OPTIM is distributed free of charge under the GPL as
part of the current software image from the group.

- OPTIM test sets from the group gitlab TESTS directory.

- Example input and output for trpzip with
a one step pathway between two local minima with AMBER20.

- Example GPU and CPU input and output for ubiquitin with
a one step pathway between two local minima with AMBER20. QCI is not really needed for this initial initial interpolation,
but QCI and DNEB only examples are both provided here.

- Example for water hexamer MBPOL intermolecular potential.

Pathsample run for water hexamer including some OPTIM input and output.

- Example for QUIP Carbon GAP 20 potential.

basic minimisation for seven carbon atoms; new GAP potential.

- Example for QUIP Carbon GAP 20 potential.

basic minimisation for seven carbon atoms; old GAP potential.

- C
_{60}example for QUIP Carbon GAP 20 potential.

transition state search and pathway for buckminsterfullerene.

- Example for QUIP silicon potential.

- Example for CASTEP on nest: pentaprismane.

- Example for the Tapered ReaxFF interface; a double-ended pathway search for a C
_{24}cluster with a tiny gap on a very noisy PES.

- Another example for the Tapered ReaxFF interface; a double-ended pathway search for a C
_{24}cluster with a tiny gap on a very noisy PES.

- Example for the xtb interface; a double-ended pathway search for the water
_{21}cluster.

- Example input and output for Tryptophan Zipper 1 (PDB 1LE0) with AMBER12 and the NapShift Hybrid Potential.

- Example input and output for a 640-atom RNA with AMBER.

- Example input and output for a coarse-grained protein model.

S6 pathway for a protein bead model with 97 sites.

QCI interpolation for a protein bead model with 92 sites, avoiding chain crossings

- REDOPATH and REDOPATHXYZ examples to create complete path.xyz files for visualisation for AMBER.
REDOPATH for tau protein AMBER 12.

- Example RIGIDINIT input and output for rigidification of TRP groups in trpzip.
A two step pathway between local minima is characterised using both DNEB and QCI.

- Example VASP input from Dr Bora Karasulu. This is a test for Li ion migration pathways in a supercell with 63 Li atoms
(one vacancy) and 32 sulphur atoms.

- Example PUSHOPT runs for a machine learning example with BFGSTS and SEARCH 0 transition
state seacrhes combined with pathways calculated using LBFGS, SEARCH 0, and Page-McIver steepest-descent.

- Example MULTIJOB run for tighter minimisation of LJ
_{31}minima in either xyz or coordinate list format.

- Example MULTIJOB run for double-ended connections of LJ
_{31}minima in either xyz or coordinate list format using NEWCONNECT.

- Example connection for bulk LJ
_{864}with periodic boundary conditions.

- Examples for the LJ
_{38}cluster connecting the lowest and second-lowest minima.

These are all double-ended transition state searches and pathways using NEWCONNECT.

Parameters that produce a connected path from a single DNEB cycle.

Parameters that produce a connected path more efficiently, in six DNEB cycles.

A connected pathway where the two minima are not in the optimal permutational alignment. 56 DNEB cycles are needed and the path has 207 transition states.

- Example for the LJ
_{38}cluster calculating paths for an index 2 saddle following the two modes with negative eigenvalues.

- Example calculations for the LJ
_{38}cluster.

Double-ended transition state searches and pathways using NEWCONNECT. In each case a path.info file is produced using the DUMPALLPATHS keyword for use by the PATHSAMPLE program.

Eigenvector-following transition state searches with LBFGS energy minimisation for the pathways

Hybrid eigenvector-following transition state searches with calculation of the eigenvalue and eigenvector corresponding to the uphill direction performed using an iterative approach for the full Hessian and LBFGS energy minimisation for the pathways

Hybrid eigenvector-following transition state searches with calculation of the eigenvalue and eigenvector corresponding to the uphill direction using the DSYEVR routine and LBFGS energy minimisation for the pathways

Hybrid eigenvector-following transition state searches using a gradient-only variational approach for the eigenvalue and eigenvector corresponding to the uphill direction and LBFGS energy minimisation for the pathways

Single-ended transition state searches and pathways. In each case a path.info file is produced using the DUMPALLPATHS keyword for use by the PATHSAMPLE program, in addition to the energy as a function of integrated path length (EofS) and a movie of the complete path (points.path.xyz)

Eigenvector-following transition state search with Runge-Kutta energy minimisation for the pathway

Eigenvector-following transition state search with Page-McIver energy minimisation for the pathway

Eigenvector-following transition state search with LBFGS energy minimisation for the pathway

Eigenvector-following transition state search with eigenvector-following energy minimisation for the pathway

Eigenvector-following transition state search with Bulirsch-Stoer energy minimisation for the pathway

Hybrid eigenvector-following transition state search with calculation of the eigenvalue and eigenvector corresponding to the uphill direction using the DSYEVR routine then Bulirsch-Stoer energy minimisation for the pathway

Hybrid eigenvector-following transition state search with calculation of the eigenvalue and eigenvector corresponding to the uphill direction using the DSYEVR routine then Runge-Kutta energy minimisation for the pathway

Hybrid eigenvector-following transition state search with calculation of the eigenvalue and eigenvector corresponding to the uphill direction using the DSYEVR routine then Page-McIver energy minimisation for the pathway

Hybrid eigenvector-following transition state search with calculation of the eigenvalue and eigenvector corresponding to the uphill direction using the DSYEVR routine then LBFGS energy minimisation for the pathway

Hybrid eigenvector-following transition state search with calculation of the eigenvalue and eigenvector corresponding to the uphill direction using the DSYEVR routine then eigenvector-following energy minimisation for the pathway

Hybrid eigenvector-following transition state search using a gradient-only variational approach for the eigenvalue and eigenvector corresponding to the uphill direction then Bulirsch-Stoer energy minimisation for the pathway

Hybrid eigenvector-following transition state search using a gradient-only variational approach for the eigenvalue and eigenvector corresponding to the uphill direction then Runge-Kutta energy minimisation for the pathway

Hybrid eigenvector-following transition state search using a gradient-only variational approach for the eigenvalue and eigenvector corresponding to the uphill direction then Page-McIver energy minimisation for the pathway

Hybrid eigenvector-following transition state search using a gradient-only variational approach for the eigenvalue and eigenvector corresponding to the uphill direction then LBFGS energy minimisation for the pathway

Hybrid eigenvector-following transition state search using a gradient-only variational approach for the eigenvalue and eigenvector corresponding to the uphill direction then eigenvector-following energy minimisation for the pathway

Hybrid eigenvector-following transition state search with calculation of the eigenvalue and eigenvector corresponding to the uphill direction performed using an iterative approach for the full Hessian and LBFGS energy minimisation for the pathways

Hybrid eigenvector-following transition state search with calculation of the eigenvalue and eigenvector corresponding to the uphill direction performed using an iterative approach for the full Hessian and Bulirsch-Stoer energy minimisation for the pathways

Hybrid eigenvector-following transition state search with calculation of the eigenvalue and eigenvector corresponding to the uphill direction performed using an iterative approach for the full Hessian and Runge-Kutta energy minimisation for the pathways

Hybrid eigenvector-following transition state search with calculation of the eigenvalue and eigenvector corresponding to the uphill direction performed using an iterative approach for the full Hessian and Page-McIver energy minimisation for the pathways

Hybrid eigenvector-following transition state search with calculation of the eigenvalue and eigenvector corresponding to the uphill direction performed using an iterative approach for the full Hessian and eigenvector-following energy minimisation for the pathways

- Factorised superposition approach (FSA) for computing binding free energies (AMBER9)
- REDOPATH movie-making run for a trapped ion cluster
- NEWCONNECT run for TIP4P water octamer
- NEWCONNECT run for TIP4P water octamer using the angle-axis scheme
- Harmonic normal mode analysis on a folded conformation of the met-enkephalin peptide (AMBER9)
- Harmonic normal mode analysis on a folded conformation of the met-enkephalin peptide (CHARMM19)
- Transition state benchmark for a amyloidogenic GNNQQNY peptide rearrangement (CHARMM19)
- Transition state benchmark for a tryptophan zipper 1 rearrangement (AMBER9)
- The MSB test sets for pathways in trpzip1 and GNNQQNY with CHARMM and AMBER. These compressed tar files contain a total
of 2100 pathways, including OPTIM input and output. Each double-ended connection attempt is performed with
quasi-continuous interpolation (QCI), DNEB interpolation, and the seven interpolation schemes described in
M.S. Bauer, B. Strodel, S.N. Fejer, E.F. Koslover and D.J. Wales, J. Chem. Phys., 132, 054101 (2010).
AMBER/GNNQQNY/TS1

AMBER/GNNQQNY/TS2

AMBER/GNNQQNY/TS3

AMBER/trpzip/TS1

AMBER/trpzip/TS2

AMBER/trpzip/TS3

CHARMM/GNNQQNY/TS1

CHARMM/GNNQQNY/TS2

CHARMM/GNNQQNY/TS3

CHARMM/trpzip/TS1

CHARMM/trpzip/TS2

CHARMM/trpzip/TS3