Have a read of our new article now out in Neuron!
www.sciencedirect.com/science/arti...
We used Cryo EM, electrophysiology and MD simulations to determine the structure of S-(+)-Ketamine at its most pharmacologically important NMDA receptor subtype, and show the basis for DQP subtype selectivity!
www.sciencedirect.com/science/arti...
We used Cryo EM, electrophysiology and MD simulations to determine the structure of S-(+)-Ketamine at its most pharmacologically important NMDA receptor subtype, and show the basis for DQP subtype selectivity!
Structural basis for channel gating and blockade in tri-heteromeric GluN1-2B-2D NMDA receptor
Discrete activation of N-methyl-D-aspartate receptor (NMDAR) subtypes by glutamate and the co-agonist glycine is fundamental to neuroplasticity. A dis…
www.sciencedirect.com
February 14, 2025 at 8:52 PM
Have a read of our new article now out in Neuron!
www.sciencedirect.com/science/arti...
We used Cryo EM, electrophysiology and MD simulations to determine the structure of S-(+)-Ketamine at its most pharmacologically important NMDA receptor subtype, and show the basis for DQP subtype selectivity!
www.sciencedirect.com/science/arti...
We used Cryo EM, electrophysiology and MD simulations to determine the structure of S-(+)-Ketamine at its most pharmacologically important NMDA receptor subtype, and show the basis for DQP subtype selectivity!
Reposted by Max Epstein
Very nice to see the work of Matt Warren and Isak Valsson just out with Charlotte Deane, Aniket Magarkar and @garrettmm.bsky.social where we show how augementation can dramatically improve ML affinity predictions to close to FEP accuracy.
rdcu.be/d88Wm
rdcu.be/d88Wm
Narrowing the gap between machine learning scoring functions and free energy perturbation using augmented data
Communications Chemistry - Machine learning offers great promise for fast and accurate binding affinity predictions, however, current models lack robust evaluation and fail on tasks encountered in...
rdcu.be
February 8, 2025 at 8:12 PM
Very nice to see the work of Matt Warren and Isak Valsson just out with Charlotte Deane, Aniket Magarkar and @garrettmm.bsky.social where we show how augementation can dramatically improve ML affinity predictions to close to FEP accuracy.
rdcu.be/d88Wm
rdcu.be/d88Wm
Reposted by Max Epstein
I’ve seen some posts recently, about the value of basic research, in light of funding cuts and demands that research have immediate economic justification.
Let me collect some info here, in a thread, about why it’s a bad idea to attach those sorts of demands to funding. 🧵 🧪 ⚛️
Let me collect some info here, in a thread, about why it’s a bad idea to attach those sorts of demands to funding. 🧵 🧪 ⚛️
December 4, 2024 at 4:13 AM
I’ve seen some posts recently, about the value of basic research, in light of funding cuts and demands that research have immediate economic justification.
Let me collect some info here, in a thread, about why it’s a bad idea to attach those sorts of demands to funding. 🧵 🧪 ⚛️
Let me collect some info here, in a thread, about why it’s a bad idea to attach those sorts of demands to funding. 🧵 🧪 ⚛️