26 February 2018

Computationally-enabled fragment growing without a structure

Advancing fragments without high-resolution structural information remains a challenge scientists often choose not to take on, according to our poll last year. But for many appealing targets, such as membrane proteins, structural information is difficult to obtain. In a new paper in J. Med. Chem., Peter Kolb and collaborators at Philipps-University Marburg and Vrije Universiteit Brussel describe a computational strategy.

The approach, called “growing via merging”, starts with a core fragment that binds to a target, in this case the β2-adrenergic receptor (β2AR). Ideally this interaction is structurally characterized, but if not a model can suffice. Here, the researchers started with five fragments they had previously discovered. All of these had in common a lipophilic core with a primary or secondary amine appendage; this is a known pharmacophore for β2AR, so modeling could be used to orient the fragments.

Next, this core fragment is derivatized in silico with other fragments using a selection of 58 common reactions. Since all five fragments contained an amine, reductive amination was used here. A set of nearly 19,000 fragment-sized aldehydes and ketones was extracted from the ZINC database and computationally transformed into amines – as if they were reacted with one of the core fragments. These were then docked into the receptor, and those that did not overlap with the core fragments and also placed the amine near the amine of the core fragment were kept for further analysis.


The top 500-scoring fragments were then “reacted” – again in silico – with the core fragments and again docked. Eight of these were actually synthesized and tested for binding, of which four had higher affinity than the initial fragments. The best, compound 11, showed a 40-fold boost in affinity over its starting fragment.

This is an appealing approach, and it will be interesting to see how generalizable it proves. The β2AR is a somewhat forgiving test case due to prior work on the target and the fact that the ligand’s amine interaction with a critical asparate residue helps to orient the core fragment. Laudably though, the computational toolbox (called PINGUI, for Pyton in silico de novo growing utilities) is open access. Please leave a comment and share your experiences if you’ve tried it.

3 comments:

Markus Heller said...

Just wondering:

"These were then docked into the receptor, and those that did not overlap with the core fragments and also placed the amine near the amine of the core fragment were kept for further analysis."

Shouldn't it read:

"These were then docked into the receptor, and those that did overlap with the core fragments and also placed the amine near the amine of the core fragment were kept for further analysis."

Dan Erlanson said...

Hi Markus,

Good question - it's a little tricky as they actually want to make sure the fragments don't bind in the same location as the core fragment with the exception of the amine. In the example shown, the blue aldehyde would be converted to a primary amine; the hope is that the chlorophenyl moiety would not bind in the same location as the indole of compound 5. You are correct that in the following step the indole moiety of compound 11 should bind in the same location as the indole of compound 5.

Florent said...

Hi Markus and Dan,

Dan correctly described the procedure.
What I want to clarify is that we are basically doing a fragment merging procedure between the core-fragment and a given surrogate (i.e. the building block we attach). Thus we don't want them to clash against one another (we assume the merging will fail).
As you know fragments are very small, so they can bind everywhere. In computational approaches such as docking, this is translated by a high number of possible poses (i.e. predicted binding modes). In our case, a single surrogate can have up to thousands of poses. Even if we limited the binding site for docking (in this case in the SBP), some of the surrogate poses will clash with the core fragment, this is why they need to be post-filtered (figure 5 described it well: https://goo.gl/FZah2c).
A more general workflow is also available in the SI (https://goo.gl/RziBgH), fig S1.

I hope I could bring some light here. Please let me know if you need more details, I will happily provide them.

Florent

P.S: I am the main author