From chemistry-request@ccl.net Wed Jun 8 01:53:19 2005 Received: from exmails1.chem.ucla.edu (exmails1.chem.ucla.edu [169.232.134.2]) by server.ccl.net (8.13.1/8.13.1) with ESMTP id j585rFfS007719 for ; Wed, 8 Jun 2005 01:53:16 -0400 Received: from laurence.mbi.ucla.edu (d-128-97-138-48.chem.ucla.edu [128.97.138.48]) (authenticated bits=0) by exmails1.chem.ucla.edu (8.12.8/8.12.8) with ESMTP id j585r6Kg004126; Tue, 7 Jun 2005 22:53:12 -0700 Message-Id: <6.1.2.0.2.20050607214538.038ad430.-at-.po.chem.ucla.edu> X-Sender: lavelle.-at-.po.chem.ucla.edu X-Mailer: QUALCOMM Windows Eudora Version 6.1.2.0 Date: Tue, 07 Jun 2005 22:52:00 -0700 To: amber.-at-.scripps.edu, chemistry.-at-.ccl.net From: Laurence Lavelle Subject: Protein dynamics. Cc: "David A. Case" , Konrad Hinsen Mime-Version: 1.0 Content-Type: text/plain; charset="us-ascii"; format=flowed X-Spam-Status: No, score=0.0 required=5.0 tests=none autolearn=failed version=3.0.3 X-Spam-Checker-Version: SpamAssassin 3.0.3 (2005-04-27) on server.ccl.net Both David and Konrad had several useful and thoughtful comments some of which are given below. I am still thinking about them. To a first approximation David is saying we need faster computers, while Konrad is saying we need more experiments. Even a small 100 residue protein (approx 1700 atoms) needs approximately 6000 waters (18000 atoms) to appropriately solvate (periodic box, with minimal switched cutoffs so as to avoid protein-protein interactions) the protein in an all atom Amber MD simulation for 100+ ps ... The TIP3P water model was equilibrated at 300 K and 1 atm. In the literature I see it used at temperatures below and above 300 K. In fact it is used in non-isothermal simulations. Is the TIP3P water model ok to use for (isothermal) MD at 400 K and 1 atm ? Also various numbers are used as the minimum distance between solvent and protein atoms (when adding water). I use 2.3 A. With respect to Konrad's comments. I had thought the frictional co-efficient was a constant in LD and it was chosen based on the water-protein interface. In interesting that it is (possibly) the intra-protein contacts that dominate. Although I would think this would scale with the size of the protein and therefore the frictional co-efficient would be protein dependent (or at least have two terms taking into account the water-protein and protein-protein contacts and these in turn would change during a simulation as the protein conformation changed increasing or decreasing the solvent accessible protein surface). I think the key point here ("For slow large-scale motions, you can leave out electrostatics completely, assuming no unfolding of course ...") is what is considered a structural change vs unfolding. Thanks again for your thoughtful comments. Laurence >On Mon, Jun 06, 2005, Laurence Lavelle wrote: > > > By protein motion I mean a folded protein in a constant temperature > > simulation (for example with a distance dependent dielectric, no > > electrostatic cutoffs, no periodic boundaries) and comparing the protein > > dynamics at different temperatures. > >With the above conditions (no solvent, distance dependent dielectric) there is >little reason to expect that either the average structure or the dynamics you >see in the simulation will be realistic. If you want to get any reasonable >account of protein dynamics, you need to be looking at MD simulations in >explicit solvent. If you want good results as a function of temperature, you >should take care that the water model you are using is known to produce good >dynamical results vs. temperature for pure water. > >...dac >On 06.06.2005, at 23:43, Laurence Lavelle wrote: > >>In looking at the dynamical motion of a protein, is Amber (Cornell et >>al. (1994) force field) (Amber 99 parameters) considered a reasonably >>realistic protein force field (or, as good as or better than most) ? >> >>In looking at the dynamical motion of a protein (for example using >>Amber), what are the pros and cons to doing Molecular Dynamics vs >>Langevin Dynamics vs Monte Carlo ? > >It all depends on what dynamical quantities you wish to calculate, and >on which time scales. > >If you look at long time scales for a protein that has a single stable >conformation, then you can get good results with very much simpler >models at much lower cost. See > > K. Hinsen, A.J. Petrescu, S. Dellerue, M.C. Bellissent-Funel, G.R. >Kneller > Harmonicity in slow protein dynamics > Chem. Phys. 261, 25-37 (2000) > >for an example. At the other end of the time scale spectrum, if your >study involves quantum effects, no Molecular Mechanics model will be >good enough. > >As for sampling techniques, note that Monte Carlo is not a dynamical >technique at all (it has no time scale), even though in some situations >a time scale can be assigned a posteriori. Langevin and Brownian >dynamics add an implicit source of friction and thermal energy, which >should correspond to some physical feature of the model, i.e. the >explicit modelling should be less detailed. > >In this context, it is worth pointing that the major source of friction >in a protein is not the solvent, as is frequently believed, but fast >interactions in the protein itself. See the article quoted above for a >demonstration. > >>{Some will say it depends on the details (distance dependent >>dielectric vs explicit solvent water molecules, no cutoffs vs with >>switched or shifted cutoffs, with or without periodic boundary >>conditions, etc.). However I am > >Again this depends on the time scales. For slow large-scale motions, >you can leave out electrostatics completely, assuming no unfolding of >course, because on such a coarse length scale the charge density is >practically zero. On the other hand, for localized events, a correct >representation of electrostatics is very important. > >> hoping (in addition to the above two questions) to get a general >>sense of how realistic MD, LD and MC are with respect to illustrating >>protein motion. > >We don't know that much about how realistic simulations of protein >dynamics are. Experimental information is mostly on very small time >scales or on time scales so long that they are out of reach of >simulations. In between those two extremes, there is nothing that >simulations could be tested against. > >Konrad Hinsen