Boltz-2: Towards Accurate and Efficient Binding Affinity Prediction
PulseAugur coverage of Boltz-2: Towards Accurate and Efficient Binding Affinity Prediction — every cluster mentioning Boltz-2: Towards Accurate and Efficient Binding Affinity Prediction across labs, papers, and developer communities, ranked by signal.
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New PIT-GCL framework uses topology for protein interaction prediction
Researchers have developed PIT-GCL, a novel framework for predicting protein interactions that leverages topological graph contrastive learning. This dual-tower system encodes proteins independently using sequence embed…
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New method ensures physical validity in biomolecular structure prediction
Researchers have developed a novel method to improve the physical validity of biomolecular structures predicted by diffusion models like AlphaFold 3. The approach introduces two projection operators that are applied at …
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NVIDIA BioNeMo Inference Runtime accelerates protein structure prediction
NVIDIA has introduced the BioNeMo Inference Runtime (BioIR), a Python library designed to accelerate biomolecular structure prediction models on NVIDIA GPUs. BioIR optimizes specific operations within models like Pairfo…
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NVIDIA BioNeMo and Claude Science partner for AI-driven protein prediction
NVIDIA has introduced a new workflow integrating its BioNeMo platform with Claude Science, designed to improve protein structure prediction. This system utilizes agentic AI to orchestrate multiple protein-folding models…
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AI framework DBMol designs drug molecules using structure prediction models
Researchers have developed DBMol, a novel framework for designing small molecules with high affinity for specific protein targets, a crucial step in drug discovery. This method leverages advanced structure prediction mo…
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NVIDIA BioNeMo Agent Toolkit empowers AI agents in life sciences research
NVIDIA has launched the BioNeMo Agent Toolkit, designed to integrate its accelerated AI capabilities into life sciences research workflows. This toolkit allows AI agents, such as those used in Anthropic's Claude Science…
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PairSAE method enhances interpretability in protein co-folding models
Researchers have developed PairSAE, a novel method for achieving mechanistic interpretability in protein co-folding foundation models. Unlike standard sparse autoencoders that struggle with the quadratic feature explosi…