Also for anything that is computationally expensive, I may run a serries of estimates that generate samples. And then, perhaps analysis of the samples will provide meaning.<br><br> <div class="gmail_quote">On Jan 7, 2008 9:50 AM, Jack Shultz <<a href="mailto:jackyg...@gmail.com">jackyg...@gmail.com</a>> wrote:<br> <blockquote class="gmail_quote" style="PADDING-LEFT: 1ex; MARGIN: 0px 0px 0px 0.8ex; BORDER-LEFT: #ccc 1px solid"> <div>Teo,</div> <div> </div> <div>I appreciate your comments and I am in the process of learning about molecular modeling. I am attempting to integrate these molecular modeling tools into my distributed computing project <a href="http://hydrogenathome.org/" target="_blank"> http://hydrogenathome.org</a></div> <div> </div> <div>I've hypothesized that it should be possible to identify catalysts based on structural data. Specifically I believe that it is possible to model transition state structures and their associated free energies and use that data with semi-empircal molecualr docking to model the transition state structures binding to reaction intermediates. </div> <div> </div> <div>I know that due to the induced fit model of enzymes, the active site of an enzyme goes through its own conformational changes to mold the substrate into a transition state structure. Maybe the active site in its native state is sufficiently close in structure to run a docking. Otherwise one would also have to run some kind of sampling on the different conformational changes in the protein structure. </div> <div> </div> <div>I understand that I need to start small. I will probably look at the most simple reaction with the most simple catalysts first. I may try a couple of modeling theories </div> <div>1) Parameterized DFT </div> <div>2) semi-empirical QM/MM. </div> <div> </div> <div>Perhaps treat it in a couple scenarios:</div> <div>1) Run molecular docking on transition state structures with a catalysts where the TSS model is derived in a reaction isolated from any catalysts. </div> <div>2) Then another scenario, run a molecular docking between the substrate and an enzyme. Generate a quantum box to of approximate 30 atoms and simulate a reaction within that area, ignoring external influences</div> <div> </div> <div>I don't know how realistic these ideas are, so really do appreciate having holes poked into it and an exchange of ideas. Thanks for your help.</div> <div> </div> <div>Jack</div> <div> <div></div> <div class="Wj3C7c"> <div><br><br> </div> <div class="gmail_quote">On Jan 7, 2008 1:21 AM, Teodoro Laino <<a href="mailto:teodor...@gmail.com" target="_blank">teodor...@gmail.com</a>> wrote:<br> <blockquote class="gmail_quote" style="PADDING-LEFT: 1ex; MARGIN: 0px 0px 0px 0.8ex; BORDER-LEFT: #ccc 1px solid"><br>Hi Jack,<br> <div><br>On 7 Jan 2008, at 03:12, <a href="mailto:jackyg...@gmail.com" target="_blank">jackyg...@gmail.com</a> wrote:<br><br>><br>> I am looking at semi-empirical QM/MM as way to model catalyzed water<br>> splitting hydrogen generating reactions. I've been veting this idea <br>> among researchers and there seems to be problems with many of the<br>> molecular modeling techniques such as QMC and DFT as applied to my<br>> model.<br><br></div>The information you are giving on the model are so few that i would say <br>semi-empirical can be even worst in treating water hydrogen bonds<br>compared<br>to DFT. Semi-empirical would be definitely faster but don't expect a<br>realistic<br>representation of the HB pattern for your system (few people here <br>have already<br>tried QMMM semi-empirical and can comment on that). Moreover the bond-<br>breaking<br>energies.. I would be surprised to see numbers in better agreement<br>than DFT.<br>Of course if you go for your own semi-empirical model, fully <br>reparametrized for<br>your system the situation can be different.. but that's another story..<br> <div><br>> Here is more specifically what I am proposing. I hope to run this<br>> analysis stochastically, perhaps treating the reaction in isolation,<br>> going through different energy pathways, generating a different <br>> transition state structures for each run along with associated free<br>> energy profiles. Using the results of these reaction models, I will<br>> run molecular docking analysis. So for a given reaction, we will have <br>> generated a great quantity of data. We can thus compare the<br>> theoretical vs the experimental, perhaps we can optimize these<br>> simulations with heuristic algorithms.<br><br></div>Since I don't have more details on your project I can just give <br>general comments:<br>In principle it should work.. BUT.. consider that the reaction on a<br>smaller system<br>(what you call reaction in isolation) is mainly driven by the<br>potential energy (the entropic<br>contribution can be very small). If you go on a larger system the <br>entropic contribution<br>can be pretty large and you have no information on that since there<br>are no data you<br>can extrapolate from your small cluster and your conclusions "could<br>be" wrong.<br>So be careful in making your final conclusion in the logic chain <br>(models/extrapolations<br>from cluster to larger systems).<br> <div><br>> I have just started installing the cp2k. If it is posible to build<br>> this model with cp2k, I will really need help setting up these<br>> simulations. I have not given up on DFT yet.<br><br></div>Which model? <br><br>cheers,<br>Teo<br> <div> <div></div> <div><br></blockquote></div><br>