Amber force-feild is one of the best. I think you are asking this one for performing some molecular docking or molecular dynamics study. If so each software uses their own force-feild for the purpose. Some software provides option to choose between Amber, CHARMM, OPLS etc.,

I will suggest you to go with Amber FF

Does the selection depends on nature of protein -like mono, di or trimer etc?Which software (possibly non-commercial) uses Amber ?

AutoDock uses amber force-feild.

AutoDock is available at free of cost for academics.

If your protein is dimer/trimer, I will advise you to perform the simulations with monomer (when they have similar sequence)

Dear Ajit,

Force fields and charge are two different aspects that has to be assigned to the any molecule under investigation (simulation). Amber is the FF developed exclusively for proteins and it is quite easy to parametrize 20 set of amino acids that are getting repeated in almost all the proteins available in the universe. When it comes to non-proteineous substances AMBER is of no use, MMFF is one FF that defines non-protenious small molecules-this will be of greater use for defining your small molecules that tend to interact with proteins. Even AMBER has a tool called Antechamber to define non-protineius small molecules.

Coming to assigning charges, yes you have once again options as you mentioned above. Gasteiger and kollman charges are the preferred ones for any molecules.

Assigning FF and assigning charges are two different things, without proper assignment of FF charge assignment will be inappropriate.

In relation to assignment of charges,QM may be alternative to MM in case of small molecules . But, both ligand and protein must have proper charges for docking . Can we define charges to inhibitor atoms of ligand by QM ?

Dear, it totally depends upon your aim that what you are looking for a force field application. If your concern is Model building then AMBER is best but if you are looking for a MD simulation like your protein in water then OPLS is the widely preferred force filed all over. GROMACS is the program which have many force field selection option. If you want to check a list just supply a command "pdb2gmx" to have a look.

QM and MM stands for Quantum Mechanics and Molecular Mechanics. Both uses different concept for molecular simulation. Charge assignment has to be performed before running any simulation either by QM protocol or by MM protocol.

In case of macromolecules like proteins its very computationally intensive to calculate charges using Quantum Mechanics. But in case of small molecules QM charges may provide better predictions and correlation. Specifically if metals are present in the active site then its very important to have insight about charges and also generate metal binding states.On such example may be interaction of hemoglobin with artemisinin where interaction with Fe is very important. Another approach may be taken to freeze the other parts of the protein,which is general in normal docking and treat the active site locally and calculate the energies or charges using QM method. Because we have to always admit QM is much precise and accurate than MM. In years to come with leap jump in computation power QM will be common and may even replace MM.

Molecular dynamics simulations rely on empirically parameterized force

fields that include explicit solvent. Examples are AMBER, CHARMM,

GROMOS, and OPLS. Discrepancies in simulation results due to choice of

force fields have been documented for a number of systems. Most force

fields currently avaiable are good for protein simulaton and they

problem with currently available force fields is in modeling DNA, RNA

and metal. In case of ligand amber and Charmm have their own tools to

generate the structure of ligand compatable with the macromolecuel

forec fields. I recommedne to use the most recent version of any of

these force field and also refre to the most recent publication about

the force fields from the developers so that you know the weeeknes and

strength of these force fields I have listeed some references .

Refrences

Workalemahu M. Berhanu & Artem E. Masunov (2010) Natural polyphenols

as inhibitors of amyloid aggregation. Molecular Dynamics study of

GNNQQNY heptapeptide decamer. Biophysical Chemistry 149, 12–21.

W.M. Berhanu and U.H.E. Hansmann (2012) Side-chain hydrophobicity and

the stability of Aβ(16-22) aggregates. Protein Science, DOI

10.1002/pro.2164

Case DA, Cheatham TE, Darden T, Gohlke H, Luo R, Merz KM, Onufriev A,

Simmerling C,

Wang B, Woods RJ (2005) The Amber biomolecular simulation programs. J

Comput Chem

26:1668-1688.

Van der Spoel D, Lindahl E, Hess B, Groenhof G, Mark AE, Berendsen HJC (2005)

GROMACS: Fast, flexible, and free. J Comput Chem 26:1701-1718.

Brooks BR, Brooks CL 3rd, Mackerell AD Jr, Nilsson L, Petrella RJ,

Roux B, Won Y, Archontis G, Bartels C, Boresch S, Caflisch A, Caves L,

Cui Q, Dinner AR, Feig M, Fischer S, Gao J, Hodoscek M, Im W, Kuczera

K, Lazaridis T, Ma J, Ovchinnikov V, Paci E, Pastor RW, Post CB, Pu

JZ, Schaefer M, Tidor B, Venable RM, Woodcock HL, Wu X, Yang W, York

DM, Karplus M (29 July 2009). "CHARMM: The biomolecular simulation

program". Journal of Computational Chemistry 30 (10): 1545–1614.