The Klem Lab at LSU is hiring a postdoctoral researcher in computational biochemistry!
Application info: klem-research-group.github.io/join/
♻️ Please share with anyone who might be interested! #chemjobs #postdoc #compchem #biochemistry #enzymes

💻🧪 CompMotifs: Hack the Sciences (lu.ma/apsqlxlj) is wrapped!

70+ hackers, 12 projects, £1.5k worth of prizes, 5 great speakers (incl. @petar-v.bsky.social!) and epic ideas.

Powered by @aria-research.bsky.social and friends.

👉 compmotifs.com and lu.ma/compmotifs.

Spaces at our hackathon are filling up. Join us! lu.ma/apsqlxlj

Reposts will be much appreciated.

​Following our successful SF event, we (www.compmotifs.com) are running another hackathon!

When? 7-8 June.
Where? London, UK.
Who? Builders and researchers from academia and industry.
What? Develop innovative computational tools to advance the natural sciences.

Join us: lu.ma/apsqlxlj?utm....

We (www.compmotifs.com) are coming to SF!

Together with Pebblebed, we’re hosting a 2-day hackathon on 26-27 March for builders and scientists across disciplines to build new methods and tools for the computational and natural sciences. Join us: lu.ma/t5yik06g.

Reposts will be much appreciated!

🚀 By virtue of its simplicity, QuickBind can serve as both an effective virtual screening tool and a minimal test bed for exploring new model architectures and innovations.

🚀 By virtue of its simplicity, QuickBind can serve as both an effective virtual screening tool and a minimal test bed for exploring new model architectures and innovations.

🔍 We investigated the mechanistic basis by which QuickBind makes predictions and found that it has learned key physicochemical properties of molecular docking.

💊 To facilitate high-throughput virtual screening applications, we augmented QuickBind with a binding affinity module and demonstrate its capabilities for multiple clinically-relevant drug targets.

🔬 QuickBind predicts how a small molecule will bind to a target protein, a key component of early-stage computational drug discovery.
⚖️ We assessed QuickBind on widely used benchmarks and found that it provides an attractive trade-off between model accuracy and runtime.

I presented QuickBind in a Spotlight Presentation at MLCB 2024 in Seattle, and it's now been published in the corresponding volume of PMLR (proceedings.mlr.press/v261/treyde2...).

Excited to share my master's thesis work with Chris Kim, Nazim Bouatta, and @moalquraishi.bsky.social: QuickBind, a light-weight and interpretable molecular docking model (arxiv.org/abs/2410.16474).