Hi David,
Force fitting in Paramfit is experimental, so the really huge values you're
seeing are not unexpected. Which version of AmberTools do you have? I
attempted to combine the energy with the forces in later versions to help
with this issue.
Best,
Robin
On Thu, May 5, 2016 at 5:53 PM, David Poole <thepoole.ucdavis.edu> wrote:
> So.. I've been working on this automated fitting thing for some time (call
> me lazy in a way).. here is my output from trying to paramfit forces:
>
> Sum of force difference magnitudes for initial parameters =
>
> 18757139865118963232857159260735439862475445751992853261728167527242611722626830228652788754375505853551368179361932693058071312728064.0000000000
> kcal/mol-A
> R^2 value for initial parameters = 0.000010
> Calculated energy with initial parameters for structure 1 = 7724.216232
> KCal/mol
> Calculated forces with initial parameters atom 1, structure 1 = 14.6609
> -0.5663 47.6259 kcal/mol-A
>
> --------------------------GENETIC ALGORITHM MINIMISATION
> ---------------------------
> Minimising function AMBER_FORCES using the GENETIC ALGORITHM
> Running pure genetic algorithm with NO SIMPLEX REFINEMENT
>
>
> -------------------------------------------------------------------------------------
> GENERATIONS_TO_CONVERGE = 25 MAX_GENERATIONS = 5000 CONV_LIMIT =
> 1.00E+01
> OPTIMIZATIONS = 500 PARENT_PERCENT = 0.10
> SEARCH_SPACE = -1.00 MAX_GENERATIONS = 5000
> ------------------------------------ CONVERGENCE
> ------------------------------------
> Gen 0: Best=
>
> 18757139865118963232857159260735439862475445751992853261728167527242611722626830228652788754375505853551368179361932693058071312728064.00000
> Mean= 1.8757e+133 Elapsed= 0/3
> Gen 1: Best=
>
> 18757139865118963232857159260735439862475445751992853261728167527242611722626830228652788754375505853551368179361932693058071312728064.00000
> Mean= 1.8757e+133 Elapsed= 1/3
> Gen 2: Best=
>
> 18757139865118963232857159260735439862475445751992853261728167527242611722626830228652788754375505853551368179361932693058071312728064.00000
> Mean= 1.8757e+133 Elapsed= 2/3
> Gen 3: Best=
>
> 18757139865118963232857159260735439862475445751992853261728167527242611722626830228652788754375505853551368179361932693058071312728064.00000
> Mean= 1.8757e+133 Conv= 1/25
> Gen 4: Best=
>
> 18757139865118963232857159260735439862475445751992853261728167527242611722626830228652788754375505853551368179361932693058071312728064.00000
> Mean= 1.8757e+133 Conv= 2/25
> Gen 5: Best=
>
> 18757139865118963232857159260735439862475445751992853261728167527242611722626830228652788754375505853551368179361932693058071312728064.00000
> Mean= 1.8757e+133 Conv= 3/25
> Gen 6: Best=
>
> 18757139865118963232857159260735439862475445751992853261728167527242611722626830228652788754375505853551368179361932693058071312728064.00000
> Mean= 1.8757e+133 Conv= 4/25
> Gen 7: Best=
>
> 18757139865118963232857159260735439862475445751992853261728167527242611722626830228652788754375505853551368179361932693058071312728064.00000
> Mean= 1.8757e+133 Conv= 5/25
>
> Those seem like really big big values.. and it doesn't work.
>
> I am going to test tonight with a simple system etc. but anyone got an
> idea?
>
> -D
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Received on Sat May 07 2016 - 11:00:04 PDT
