Ameya Harmalkar
@ameyaharmalkar.bsky.social
PhD w/ Jeff Gray on protein docking/design @JHU ChemBE | Tweaking generative models for protein design @Generate Biomedicines | Runner | (chaotic) Protein geek (he/him/his)
So much to process and be excited about! Massive respect to the organizers and speakers for an incredible Keystone experience! 🚀 #KSMLStructure2025
March 27, 2025 at 7:14 PM
So much to process and be excited about! Massive respect to the organizers and speakers for an incredible Keystone experience! 🚀 #KSMLStructure2025
Also learnt a lot from @elanasimon.bsky.social talk on interpretable features in LLMs, and @possuhuanglab.bsky.social and Bruno Correia’s talks on de novo protein design and the long term vision of ProteinML!
March 27, 2025 at 7:13 PM
Also learnt a lot from @elanasimon.bsky.social talk on interpretable features in LLMs, and @possuhuanglab.bsky.social and Bruno Correia’s talks on de novo protein design and the long term vision of ProteinML!
Finally, a wonderful closing keynote by Charlotte Deane highlighted that “AI Is Not Magic”
Charlotte reminded us that structures tell stories—and that understanding beats leaderboard chasing.
She also demoed MolSnapper, a tool to tailor plausible molecules into binding sites.
Charlotte reminded us that structures tell stories—and that understanding beats leaderboard chasing.
She also demoed MolSnapper, a tool to tailor plausible molecules into binding sites.
March 27, 2025 at 7:10 PM
Finally, a wonderful closing keynote by Charlotte Deane highlighted that “AI Is Not Magic”
Charlotte reminded us that structures tell stories—and that understanding beats leaderboard chasing.
She also demoed MolSnapper, a tool to tailor plausible molecules into binding sites.
Charlotte reminded us that structures tell stories—and that understanding beats leaderboard chasing.
She also demoed MolSnapper, a tool to tailor plausible molecules into binding sites.
In two separate talks, @moalquraishi.bsky.social and @sokrypton.org unpacked what AlphaFold has learnt and how it learns, as well as, how to hack it for protein design tasks! (s/o to BindCraft by @martinpacesa.bsky.social et al.)
March 27, 2025 at 7:09 PM
In two separate talks, @moalquraishi.bsky.social and @sokrypton.org unpacked what AlphaFold has learnt and how it learns, as well as, how to hack it for protein design tasks! (s/o to BindCraft by @martinpacesa.bsky.social et al.)
“ML Methods for Protein–Peptide Interactions” by Amy Keating!
A killer comparison of structure predictors (AF3, Boltz, Chai-1) on 631 protein–peptide complexes! We also got a preview of COORdinator2, a new coordinate-based Potts model that maps sequence landscapes on fixed backbones.
A killer comparison of structure predictors (AF3, Boltz, Chai-1) on 631 protein–peptide complexes! We also got a preview of COORdinator2, a new coordinate-based Potts model that maps sequence landscapes on fixed backbones.
March 27, 2025 at 7:07 PM
“ML Methods for Protein–Peptide Interactions” by Amy Keating!
A killer comparison of structure predictors (AF3, Boltz, Chai-1) on 631 protein–peptide complexes! We also got a preview of COORdinator2, a new coordinate-based Potts model that maps sequence landscapes on fixed backbones.
A killer comparison of structure predictors (AF3, Boltz, Chai-1) on 631 protein–peptide complexes! We also got a preview of COORdinator2, a new coordinate-based Potts model that maps sequence landscapes on fixed backbones.
“Decoding Binding Entropy Through Structural Biology” by @stephanieaw.bsky.social
Brilliant exploration of entropy’s role in binding thermodynamics.
Key insight: While binding sites lose entropy, distal sites compensate by becoming more flexible. Very curious how this plays out in Ab–Ag binding!
Brilliant exploration of entropy’s role in binding thermodynamics.
Key insight: While binding sites lose entropy, distal sites compensate by becoming more flexible. Very curious how this plays out in Ab–Ag binding!
March 27, 2025 at 7:05 PM
“Decoding Binding Entropy Through Structural Biology” by @stephanieaw.bsky.social
Brilliant exploration of entropy’s role in binding thermodynamics.
Key insight: While binding sites lose entropy, distal sites compensate by becoming more flexible. Very curious how this plays out in Ab–Ag binding!
Brilliant exploration of entropy’s role in binding thermodynamics.
Key insight: While binding sites lose entropy, distal sites compensate by becoming more flexible. Very curious how this plays out in Ab–Ag binding!
“Have Protein Language Models Learned Dynamics?” by @hkws.bsky.social As someone whose PhD focused on conformational dynamics, I loved this talk. Hannah showcased the Dyna-1 model that uses NMR data + PLMs to extract the ground truth of protein dynamics!
March 27, 2025 at 7:03 PM
“Have Protein Language Models Learned Dynamics?” by @hkws.bsky.social As someone whose PhD focused on conformational dynamics, I loved this talk. Hannah showcased the Dyna-1 model that uses NMR data + PLMs to extract the ground truth of protein dynamics!
+1 to the first part of the statement; maybe with the caveat that if it is templated off a single sequence, the designed sequence has a novel structural fold. Also, what about trastuzumab with redesigned CDRs?
January 5, 2025 at 6:13 AM
+1 to the first part of the statement; maybe with the caveat that if it is templated off a single sequence, the designed sequence has a novel structural fold. Also, what about trastuzumab with redesigned CDRs?