Thanks to everyone who joined us at #MoML2026 yesterday! We had a blast 🤩 And congrats again to @MIT PhD student Tally Portnoi on being awarded the Best Paper Prize for her work on "zPocket: Finding Pockets with Frozen Cofolding Features"! 🏆

Industry talk #2! Danaher’s Andrey Tovchigrechko talks about how his team used @boltz_bio’s BoltzGen to design beta-zipper mini binder interfaces while using agentic tools to optimize the in silico pass rate in BoltzGen. #MoML2026

How are industry experts using ML in their research? @ByteDanceSeed_’s @chengyenhsieh presents on Protein Autoregressive Modeling: Taking initiative from the hierarchical nature of proteins, PAR generates backbones by forming a global topology & performing refinements. #MoML2026

Up next, @YaleMed’s @MarkGerstein talks about building world models to predict protein folding pathways 🧬 #MoML2026

Starting now, @ISTAustria’s Alex Bronstein talks about developing a general inference time optimization framework that can maximize log-likelihood and incorporate external constraints while eliminating dependence on diffusion length and removing initialization bias. #MoML2026

How can we improve target discovery for better drugs? @omenndarlingbio’s @idmjky talks about how EVOLVEpro demonstrates the usefulness of language models in optimizing protein function. He also introduces MESSI, for immunogenicity aware binder design.

Now hearing from @FU_Berlin’s @CecClementi on the short-sightedness of GNNs and potential solutions. She introduces a framework for efficiently and accurately simulating biomolecular complexes. #MoML2026

Poster Session I is in progress! Top 4 posters will be up all day! Who do you think will win the Best Paper Prize? 👀 #MoML2026

#MoML2026 Top 4: @PaulSharoubeem presents Electro-Prot, 6.7M-parameter encoder-decoder transformer trained on 162,980 APBS calculated fields to predict Poisson-Boltzmann potentials at arbitrary points around a protein!

#MoML2026 Top 4: @Northeastern and @broadinstitute’s Yikun Zhang presents on MolSAGE, a framework that accumulates and and reuses experience across tasks to build state-of-the-art drug models efficiently!

#MoML2026 Top 4: @mit’s Tally Portnoi introduces PocketWatch, a curated dataset of biologically relevant ligand pockets, and using this dataset to develop zPocket, which trains pocket-prediction heads on top of frozen features from co-folding models.

#MoML2026 Top 4: first up is MIRAGE, presented by @UCF’s Mehdi Yazdani-Jahromi. MIRAGE is a plug-in benchmark that applies the family-support axis to affinity and pose prediction.

👀 Next up: @pas_saro and @NoahBGetz from @boltz_bio present on their approaches to maximizing performance on structure and affinity prediction in the Boltz model series, and their work on using BoltzMol-1 to identify a target inhibiting DNA damage repair. #MoML2026

How can dynamic biomarkers improve patient care? @cityofhope’s Andrea Bild shares how evolutionary models can transform cancer therapeutics.

#MoML2026 is underway! #JameelClinic faculty lead @BarzilayRegina opens the conference with a presentation on the state-of-the-art in molecular modeling.

We're excited to hear from @YaleMed's @MarkGerstein on Wednesday, Oct. 14 for #MoML2026! <20 tickets left! 🎟️ Register now before tickets are sold out: moml.mit.edu/