Comments (4)
Hey!
-
I am not sure how a one-to-tone correspondence between Keypoints and pocketpoints could be possible considering that the sets have different cardinality. This is the reason why the ot formulation is used.
-
The ot loss indeed encourages keypoints to be similar to pocket points.
-
The kabsch algorithm is used to align protein keypoints with ligand keypoints. These are of the same cardinality, but their one-to-one correspondence is not enforced. There is only a soft correspondence between the keypoints coming from the ot_loss that is taken to the same set of pocket points.
from equidock_public.
@HannesStark
I know you are not the author of this paper, but our team is planning to read your EquiBind work so that we have to understand EquiDock first.
Considering the sad news of Octavian, we are not sure who can answer this question, could you please help us to clarify this point?
from equidock_public.
Hi!
The OT matrix was used in computing the returned ot_dist.
The model then receives the ot_dist as additional loss and is "encouraged" to decrease it by producing keypoints that closely match the pocket points.
from equidock_public.
Hi Hannes, thanks so much for your kind & quick response! Please allow me to discuss this point further.
As far as our team understand, by using ot_dist
as loss only, the keypoints are encouraged to match pocket points as a set, but no one-to-one correspondence between each set. (except if we use ot_matrix
explicitly to specify one-to-one correspondence)
Since Kabsch algorithm seems to assume perfect-aligned points (i.e. one-to-one correspondence between two sets), I still not quite clear that ot_loss
alone is enough for Kabsch ?
from equidock_public.
Related Issues (20)
- Question about the Fig.12 HOT 4
- inference script has no docs HOT 1
- Hyperparameters HOT 2
- Installation problems HOT 1
- Matrix Product Error in Kabsh Model HOT 1
- How to run inference on custom PDB + Problems with Installation HOT 5
- best validation score & some other variations
- Source code for DIPS split HOT 6
- Thank you for your generous open source work, salute your work, and wish your soul peace
- what is the difference between rigid protein docking and protein-protein docking?
- can not achieve the performance which mentioned in the original paper HOT 8
- cuda and dgl version
- Code is not usable or documented HOT 2
- Dependencies typo ? HOT 1
- How to get the complex pose? HOT 13
- to speed up rsync
- deallock in make_dataset HOT 3
- DIPS dataset HOT 2
- about preprocess_raw_data.py HOT 5
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from equidock_public.