Maria A. Castellanos
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mariacastel.bsky.social
Maria A. Castellanos
@mariacastel.bsky.social
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Computational Chemist | Postdoc with @jchodera.bsky.social at MSKCC | Antiviral discovery for pandemic prevention with ASAP | PhD with Adam Willard, MIT Chemistry

https://sites.google.com/view/mariaacastellanos
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Reposted by Maria A. Castellanos
achira-ai.bsky.social
Achira is growing! We’re looking for talented software engineers, ML research engineers, and AI/ML scientists to join our team in building foundation simulation models to power the future of drug discovery.

Apply at achira.ai
Achira
Building foundation simulation models for drug discovery
achira.ai
October 24, 2025 at 12:20 PM
Reposted by Maria A. Castellanos
mskeducation.bsky.social
Kicking off the #MSKPostdoc Research Symposium: @mariacastel.bsky.social, Andrew S. Gordon MERIT Fellow from the @jchodera.bsky.social lab, presents a computational pipeline to design antivirals that target conserved protein sites - arming us against future pandemics. 🧬💻🦠 #NPAW2025 #VirusResearch
September 18, 2025 at 7:08 PM
Reposted by Maria A. Castellanos
sukritsingh92.bsky.social
Happy Holi, from the @jchodera.bsky.social lab!!
Five people, covered in bright Holi powder, stand arm-in-arm in front of a waterfront railing with a cityscape in the background. They’re all smiling and wearing colorful, powder-stained clothes.
March 14, 2025 at 9:51 PM
Reposted by Maria A. Castellanos
jchodera.bsky.social
Everything is chaos, but I wanted to share some awesome recent science from the lab that hints at where the future of biomolecular simulation is headed:

Foundation simulation models that can be fine-tuned to experimental free energy data to produce systematically more accurate predictions.
Figure 1 from arXiv preprint https://doi.org/10.1101/2025.01.06.631610 Fig. 1 Espaloma is an end-to-end differentiable molecular mechanics parameter assignment scheme for arbitrary organic molecules. Espaloma (extensible surrogate potential optimized by message-passing) is a modular approach for directly computing molecular mechanics force field parameters FFF from a chemical graph G such as a small molecule or biopolymer via a process that is fully differentiable in the model parameters FNN. In Stage 1, a graph neural network is used to generate continuous latent atom embeddings describing local chemical environments from the chemical graph. In Stage 2, these atom embeddings are transformed into feature vectors that preserve appropriate symmetries for atom, bond, angle, and proper/improper torsion inference via Janossy pooling.54 In Stage 3, molecular mechanics parameters are directly predicted from these feature vectors using feed-forward neural networks. This parameter assignment process is performed once per molecular species, allowing the potential energy to be rapidly computed using standard molecular mechanics or molecular dynamics frameworks thereafter. The collection of parameters FNN describing the espaloma model can be considered as the equivalent complete specification of a traditional molecular mechanics force field such as GAFF38,39/AM1-BCC55,56 in that it encodes the equivalent of traditional typing rules, parameter assignment tables, and even partial charge models. Reproduced from ref. 49 with permission from the Royal Society of Chemistry.
February 19, 2025 at 7:30 PM
Reposted by Maria A. Castellanos
polarishub.io
🦠 We’re excited to announce our first competition in partnership with @asapdiscovery.bsky.social and @omsf.io!

Test your skills across three sub-challenges revolving around SARS-CoV-2 and MERS-CoV Mpro🧵

Full details: polarishub.io/competitions
Blog: polarishub.io/blog/antivir...
December 3, 2024 at 3:13 PM
Reposted by Maria A. Castellanos
jchodera.bsky.social
Resharing in the Good Place:

Super proud of superstar postdoc Maria A. Castellanos (@mariacastel.bsky.social) winning a poster prize at the Computational Med Chem School for her work with @asapdiscovery.bsky.social on predicting broad-spectrum antiviral activity!

www.choderalab.org/news/maria-p...
Postdoctoral Fellow Maria A. Castellanos wins poster prize at Computational Medicinal Chemistry School for AlphaFold-based prediction of antiviral spectrum — Chodera lab // MSKCC
Chodera lab Postdoctoral Fellow Maria A. Castellanos was awarded a poster prize at the Computational Medicinal Chemistry School held Oct 28-30, 2024 at the Novartis Institutes for Biomedical Resea...
www.choderalab.org
November 21, 2024 at 7:52 PM