Marta Filizola

@martafilizola.bsky.social

Computational biophysicist specialized in GPCRs, beta3 integrins, and other membrane proteins. Professor and Dean at Icahn School of Medicine at Mount Sinai.

We are inviting applications for a research scientist/postdoctoral associate position in the broad field of computational chemistry/biophysics/AI-driven drug discovery. Please DM your CV and 2 reference names

Ready for another poster from ⁦‪@filizolalab1‬⁩ at #BPS2026? Stop by to meet Sabina (née Dylan) and learn about new molecular insights into antibody selectivity revealed by molecular dynamics simulations and free energy calculations.

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After the most surreal peer review process we are out in the wild with BOLD-GPCRs: A Transformer-Powered App for Predicting Ligand Bioactivity and Mutational Effects across Class A GPCRs | Journal of Chemical Information and Modeling pubs.acs.org/doi/full/10....

BOLD-GPCRs: A Transformer-Powered App for Predicting Ligand Bioactivity and Mutational Effects across Class A GPCRs

G Protein-Coupled Receptors (GPCRs) are important targets for drug discovery owing to their ability to respond to a broad range of stimuli and their involvement in numerous pathologies. Although traditional ligand-based and structure-based approaches have facilitated the development of effective therapeutics for many GPCRs, these approaches often fall short when applied to receptors with limited ligand or structural data. This limitation highlights the critical need for advanced strategies capable of accurately predicting ligand bioactivity across the entire GPCR family, especially for understudied receptor subtypes. In this study, we introduce BOLD-GPCRs (BERT-Optimized Ligand Discovery for GPCRs), a deep learning framework designed to enhance the prediction of ligand bioactivity across class A GPCRs. Accessible via a user-friendly web interface, BOLD-GPCRs employs transfer learning and leverages curated data sets of known class A GPCR ligands, receptor sequences, and signaling-relevant mutations. By integrating dense neural network classifiers with transformer-based protein language models, BOLD-GPCRs captures complex relationships between receptor sequence/function and ligand activity. Our results demonstrate that BOLD-GPCRs achieves robust predictive performance for both ligand bioactivity and mutational effects across a broad range of class A GPCRs, underscoring its potential as a valuable tool for ligand discovery, especially for poorly characterized receptors.

pubs.acs.org

25 years ago, I came to Stanford on a J1 visa and worked so hard to be worthy of that privilege. Today, I lead Immunology at Mount Sinai and I am the one who feel privileged when brilliant international trainees chose to join us.

“America First” Will Destroy U.S. Science

The U.S. government has sought to restrict immigration under the “America First” doctrine. These policies severely harm American science by stripping it of talent and eliminating a major driver of its...

cell.com

Published an op-ed for @cnn.com: “Nobel laureate: I owe America my success. Today, its scientific future is in danger.” A personal reflection on what’s at stake as science funding gets slashed. I’d be grateful if you could amplify both in and beyond the science world. www.cnn.com/2025/04/09/h...

Nobel laureate: I owe America my success. Today, its scientific future is in danger | CNN

Dr. Ardem Patapoutian says he watches “with deep sadness as the United States’ remarkable scientific enterprise, which took generations of hard work and national investment to build, faces a concerted...

cnn.com

Are you aiming for leadership roles in pharmaceutical, biotech, high tech, or medical device companies? Consider applying to the revamped MSBS program @GradSchoolSinai @IcahnMountSinai, featuring 1 or 2-year tracks and non-thesis options tailored for industry professionals

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