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This is a summary of my issue raised in the openFE developers channel on 05/02/2022:
My original message: 3:00 PM
"There is an issue with the LOMAP similarity scoring that I wanted to bring up as you all work on incorporating it into OpenFE.
On Friday, I found a bug/limitation in the existing LOMAP similarity metric. I ran my planner for the PLBenchmark sets and saw abnormally low similarity scores in a particular use case, which I will describe. The attached example is from the PLBenchmarks bace_hunt ligand set, and the ligands are shown in optimization_inputs.pdf. In output.pdf, you can see the similarity scores are all near zero in the heatmap where Distance = 1 - similarity(LOMAP). These ligands shouldn’t all have zero or near zero similarity.
I have also attached bace_hunt.zip, which includes sdf files and the LOMAP generated similarity scores (strict_numpy.csv) for your reference.
In this case, LOMAP produces poor similarities due to chirality. MCSS in LOMAP is 2D and doesn’t handle chirality properly, so it deletes chiral centers. In the bace_hunt set, the whole ring system attached to the chiral center is not considered in the similarity scoring. What remains is the aromatic ring at the top left. Since there is no variation in chirality across the rings in the series, the ring should not be deleted.
It looks like the similarity metric should be refined then to better handle MCSS and chirality."
"...Basically, as originally implemented LOMAP had to delete chiral centers when computing MCS because I only had 2D graphs without chirality and there was no way to ensure the mapping worked out correctly.
When Mary applied this to the real sets, it turns out deleting chiral centers in several systems results in essentially no similarity so things will basically fail.
This was never intended to be a long-term solution when I first whipped this together back in maybe 2010 in like a week (LOL), more of a “I’ll just delete these until I come up with a better solution, because this is just a proof-of-concept…” and… here we are a dozen years later.
(I know OpenEye has done something better in theirs, but that’s proprietary.)"
Clara Christ provided a solution she implemented:
"...here is what I did at the time to handle stereo atoms when mapping (see below). In short, I chose the MCS of the many possible MCSs with the minimum atom-to-atom distances AND distances greater than 0.5A and atoms differing in stereochemistry were removed from the MCS (the code is with BI). https://pubs.acs.org/doi/pdf/10.1021/ci4004199 "
The text was updated successfully, but these errors were encountered:
This is a summary of my issue raised in the openFE developers channel on 05/02/2022:
My original message:
3:00 PM
"There is an issue with the LOMAP similarity scoring that I wanted to bring up as you all work on incorporating it into OpenFE.
On Friday, I found a bug/limitation in the existing LOMAP similarity metric. I ran my planner for the PLBenchmark sets and saw abnormally low similarity scores in a particular use case, which I will describe. The attached example is from the PLBenchmarks bace_hunt ligand set, and the ligands are shown in optimization_inputs.pdf. In output.pdf, you can see the similarity scores are all near zero in the heatmap where Distance = 1 - similarity(LOMAP). These ligands shouldn’t all have zero or near zero similarity.
I have also attached bace_hunt.zip, which includes sdf files and the LOMAP generated similarity scores (strict_numpy.csv) for your reference.
In this case, LOMAP produces poor similarities due to chirality. MCSS in LOMAP is 2D and doesn’t handle chirality properly, so it deletes chiral centers. In the bace_hunt set, the whole ring system attached to the chiral center is not considered in the similarity scoring. What remains is the aromatic ring at the top left. Since there is no variation in chirality across the rings in the series, the ring should not be deleted.
It looks like the similarity metric should be refined then to better handle MCSS and chirality."
optimization_inputs.pdf
output.pdf
bace_hunt.zip
David Mobley responded with added detail:
"...Basically, as originally implemented LOMAP had to delete chiral centers when computing MCS because I only had 2D graphs without chirality and there was no way to ensure the mapping worked out correctly.
When Mary applied this to the real sets, it turns out deleting chiral centers in several systems results in essentially no similarity so things will basically fail.
This was never intended to be a long-term solution when I first whipped this together back in maybe 2010 in like a week (LOL), more of a “I’ll just delete these until I come up with a better solution, because this is just a proof-of-concept…” and… here we are a dozen years later.
(I know OpenEye has done something better in theirs, but that’s proprietary.)"
Clara Christ provided a solution she implemented:
"...here is what I did at the time to handle stereo atoms when mapping (see below). In short, I chose the MCS of the many possible MCSs with the minimum atom-to-atom distances AND distances greater than 0.5A and atoms differing in stereochemistry were removed from the MCS (the code is with BI). https://pubs.acs.org/doi/pdf/10.1021/ci4004199 "
The text was updated successfully, but these errors were encountered: