Re: [phenixbb] ligand fitting

Hi Sneha, Easier option would be to superpose homolog-protein+peptide coordinates onto your "apo" structure (using SSM for example within coot), which might get the peptide closer to the binding-site of your protein, and then tweak it for better fit. OR if the peptide is not too long, and its electron density is clear one might be able to build it manually from scratch. Hope this helps, Partha On Thu, Oct 9, 2014 at 12:56 PM, Sneha Rangarajan wrote:

Hello everyone,

I have a question about ligand fitting into density.

At this point my maps look quite good with decent density for the peptide (ligand)[Rfactprs 26/31].

I tried using ligandfit by giving it the pdb and mtz of the ligand free model along with peptide.pdb (peptide stripped from a pdb where it was complexed with a homologous protein).

However the output was a ligand.pdb file with a CC of 0.49. I am not sure how to interpret this. Does this mean it could not find the density for the ligand?

Is there a better way to fit the peptide into density?

Thanks,

S

*From:* [email protected] [mailto: [email protected]] *On Behalf Of *Sneha Rangarajan *Sent:* Wednesday, October 08, 2014 10:30 AM *To:* Nathaniel Echols *Cc:* [email protected] *Subject:* Re: [phenixbb] (no subject)

This was a great idea. My Rfactors after a second round of autobuild are now 25/32. I think it might be getting there afterall J

S

*From:* Nathaniel Echols [mailto:[email protected] ] *Sent:* Friday, October 03, 2014 3:08 PM *To:* Sneha Rangarajan *Cc:* Pavel Afonine; [email protected] *Subject:* Re: [phenixbb] (no subject)

On Fri, Oct 3, 2014 at 11:58 AM, Sneha Rangarajan wrote:

I did another round of refinement with default settings (XYZ,realsp, IndB and occ) with and without weight optimization.

Without weight opt, the Rfactors are 23/36 with RMSbonds-0.0108 and RMSangles-1.750

One idea would be to run AutoBuild again. I've seen cases before where it didn't converge using the default settings, and feeding a previous result back into the program for a second run produced significantly better models. It might help get rid of the overfitting.

-Nat

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