SP
Make a directory and include the following files:

• make_dirs
  
• copy_files2
  
• glide-dock_SP_0.in
  

Example of SP.in file:
USECOMPMAE YES
NREPORT 30000
RINGCONFCUT 2.500000
GRIDFILE /home/eva/Zinc_screening/SP_1MV9/1MV9_no_wat_glide-grid.zip
LIGANDFILE /home/ZINC/druglike-Zinc-library-mol2/3_p0.0.mol2
LIGFORMAT mol2

1. Run the make_dirs script --> creates 88 folders (0-87)
   
2. Run the copy_files2 script --> leave the glide-dock_SP_0.in file out of its folder to run the script and when it is finished then cut+paste it to folder_0.
   
3. Use the submit_SP_all script to run the SP on apple cluster. In my case I used to put up to 12 jobs in each node ( modify this line of the script: for (( i = 76 ; i<=87; i++   )) ). Due to the fact that the jobs were put randomly to the nodes and in order to have up to 12 jobs on each node, I was using first some "fake" gromacs runs to use 12 cores and left the other 12 free for screening runs (Evi's idea! Thank's Evi!!).
4. When the run is finished you should check all the 88 directories and see if you have outputs like: e.g. glide-dock_SP_8_pv.maegz. If something goes wrong and the run has stopped then you will see e.g. glide-dock_SP_8_raw.maegz as an output. Then you should copy your glide-dock_SP_8.in to glide-dock_SP_8_b.in and run it from the ligand that it had stopped. Finally, you will have: glide-dock_SP_8_raw.maegz and glide-dock_SP_8_b_pv.maegz. Both are useful! Don't delete the first one!
5. In order to finish the SP process you have to take the top-scored 40.000 compounds from all the directories and put them to a new file (SP_top40000_1MV9_pv.maegz) to use as an input for the XP process.

You can run the GlideSortScript_ZINC.csh script to acheive this result. The content of the script is the following: (You have to add the possible raw.maegz files,too.)
/opt/schrodinger/utilities/glide_sort -n 40000 -o SP_top40000_1MV9_pv.maegz -r  SP_top40000_1MV9.rept -hbond_cut 0.00 -cvdw_cut 0.00 -metal_cut 10.00 \ db3_p0.0/glide-dock_SP_0_pv.maegz \db3_p0.1/glide-dock_SP_1_pv.maegz \db3_p0.2/glide-dock_SP_2_pv.maegz \db3_p0.3/glide-dock_SP_3_raw.maegz \db3_p0.3/glide-dock_SP_3_b_pv.maegz \ etc.

XP
Each XP directory includes:

• grid.zip file
  
• SP_top40000_1MV9_pv.maegz (output of SP)
  
• XP.in files (I split them into 8 files in my case) 

Example of XP.in file:
WRITEREPT YES
WRITE_RES_INTERACTION YES
WRITE_XP_DESC YES
USECOMPMAE YES
POSTDOCK_NPOSE 10
LIGAND_END 10000
LIGAND_START 5001 (this line is not included in the XP_1.in file as it starts from the beginning)
MAXREF 800RINGCONFCUT 2.500000
GRIDFILE /home/eva/XP_Zinc/1MV9_XP_Zinc_2_8/1MV9_no_wat_glide-grid.zip
LIGANDFILE /home/eva/XP_Zinc/1MV9_XP_Zinc_2_8/SP_top40000_1MV9_pv.maegz
PRECISION XP

So, I split it to 8 XP directories:
0 - 5000, 5001  - 10000, 10001 - 15000, ..., 35001 - 40000

Run each one on the cluster or on our PCs manually :
/opt/schrodinger/glide 1MVC_Zinc_XP1.in -HOST xgrid-server
/opt/schrodinger/glide 1MVC_Zinc_XP2.in -HOST xgrid-server etc. 

Finally you take the top-scored 1000 compounds (as we did before for the SP process where we took the 40.000 top-scored ) using the same script (GlideSortScript_ZINC.csh):

/opt/schrodinger2012/utilities/glide_sort -n 1000 -o  file_XP_1000_pv.maegz -r  file_XP_1000_.rept -hbond_cut 0.00 -cvdw_cut 0.00 -metal_cut 10.00 glide-dock_XP_0_pv.maegz glide-dock_XP_1_pv.maegz glide-dock_XP_2_pv.maegz glide-dock_XP_3_pv.maegz glide-dock_XP_4_pv.maegz glide-dock_XP_5_pv.maegz glide-dock_XP_6_pv.maegz glide-dock_XP_7_pv.maegz glide-dock_XP_8_pv.maegz

Some useful tips:

Run faster with the -LOCAL flag:
/opt/schrodinger/glide -LOCAL file.in

path for ZINC on apple:
/Network/Servers/xgrid-Server.xgrid/Volumes/RAID/NetUsers/pgkeka/PI3K/Screening/ZINC/druglike-Zinc-library-mol2/

Apple cluster run-command:
/opt/schrodinger/glide your_XP_file.in -HOST xgrid-server

Schrodinger's March 2013 seminar series begin next Tuesday, March 5. This seminar series will include presentations on Phase Shape for ligand-based shape screening and new ensemble docking practices to account for protein flexibility.

Schrodinger is also debuting a Materials Science Suite this year - Dr. Vyacheslav S. Bryantsev of Liox Power will also be presenting on computational modeling of rechargeable Li-air battery materials on March 7. Please feel free to invite your colleagues in the materials industries to join us for this materials-focused presentation!

Here is the full webinar list with dates:

Accounting for protein flexibility in virtual screening using ensemble docking

Dr. Woody Sherman
Schrödinger's Vice President, Applications Science
Abstract March 5, 2013
10 am ET Register
1pm ET Register

Computational Modeling of Rechargeable Li-Air Battery Materials
Dr. Vyacheslav S. Bryantsev
Liox Power, Senior Scientist
Abstract March 7, 2013
10 am ET Register

Using Phase Shape for rapid ligand alignment and virtual screening
Dr. Woody Sherman
Schrödinger's Vice President, Applications Science
Abstract March 12, 2013
10 am ET Register
1pm ET Register

Before docking with Glide and during receptor Grid generation, you have the possibility to select which hydroxyl and thiol groups around your ligand will be rotating in order to form hydrogen bonds.

After performing Glide docking you have to save your project file so that for each ligand the correct Ser/Thr/Cys rotamer is displayed in the pose viewer file. In order to include this information in your saved files, you have to follow this procedure:

1) Import the *_pv.maegz with your top-scored compounds in Maestro

2) In another Maestro window import the *.sdf file containing the exemplar compounds of each of the initial clusters.

3) In the Project Table of the first Maestro window, select (Control and right mouse click on the entry) AND include (Control and right mouse click on the box of the table entry so that it turns from empty full (black): the displayed atoms (i.e. the protein) plus each of the exemplar compounds that we see in the second Maestro window.

4) Export the selected/included entries into a *maegz file that MUST end with "_pv", e.g. "exemp1_pv.maegz", making also sure that the option "All properties" in the Export pop-up window is selected.

George

When looking for diversity in protein structures, the volume-based or the shape-based analysis of a binding side through SiteMap is more meaningful  than looking at the RMSD metric alone, as mentioned in a recent protein preparation Schrodinger webinar by Dr Woody Sherman, which can be found here:
http://www.schrodinger.com/seminarprior/19/38/

To evaluate protein structure diversity with SiteMap you can perform the following steps:
1. Run SiteMap on each structure -- Computes shape of binding pocket for each structure
3.Generate pairwise volume overlap matrix with the Python script from Script Center "trajectory_binding_site_volumes.py"
4.Perform hierarchical clustering to get diverse binding sites with "volume_cluster.py"
5. Choose desired structures

See also:
Halgren T (2007) Chem Biol Drug Des 69(2):146 title: "New method for fast and accurate binding-site identification and analysis."

Halgren T (2009) J Chem Inf Model 49:377 title: "Identifying and characterizing binding sites and assessing druggability."

Eva

In Maestro when visualizing a structure file, you can  select Tools -> Measurements -> Contacts panel in order to see Good contacts and Bad&Ugly contacts. When contacts are displayed, good contacts are green by default, bad ones are orange, and ugly ones are red. These criteria whether a contact is defined as good, bad or ugly are based on the following formula:

C = D12 / ( R1 + R2 )

where D12 is the distance between atomic centers 1 and 2, and R1 and R2 are the radii of atomic centers 1 and 2. C is defined as the "contact cutoff ratio" in Maestro and has default values of 0.85 for "Bad" contacts and 0.70 for "Ugly" contacts. C must be monotonically increasing for each of the contact types, that is C(ugly) < C(bad) < C(good). These three values then provide 4 ranges. Distances greater than C(good) are not marked, less than C(good) but greater than C(bad) are marked as "good", etc.

This answer was provided by the Schrodinger help team.

Zoe