AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Here we use a large language model for the exploration of chemical space of transition metal complexes (TMCs), fine-tuning the open-source Llama-3.2-1B model with a variation of the SMILES string...
LinkLlama is presented, a fine-tuned Meta Llama 3 model that bridges the gap between text-based generation and 3D spatial awareness, offering a highly controllable and chemically robust framework to accelerate linker design and drug discovery in general.
Full‐length atomistic conformational ensembles generated by IDPConformerGenerator and optimized by X‐EISDv2 workflow support a model of translation regulation in which the dynamic 4E‐BP2:eIF4E complex facilitates accessibility of regulatory sites of 4E‐BP2 when bound.
Molecular dynamics (MD) and the development of next-generation force fields increasingly rely on automatic differentiation for efficient simulated property prediction and parameter optimization. However, standard FFs and machine learning frameworks often suffer from significant performance bottlenecks-such as kernel la...
KinConfBench is introduced, a curated benchmark of 2225 high-quality human kinase chains to evaluate the ability of four state-of-the-art cofolding models—Boltz-2, Chai-1, Protenix, and RoseTTAFold-All-Atom—to recover both canonical and rare conformational states.
Co-folding models hold immense potential for allosteric drug discovery, but have been severely hampered by their systematic bias toward orthosteric ligand binding. While fragment screening has been proposed for allosteric binding site discovery, we show that co-folding models still suffer from memorization in which che...
It is shown that enhancing an LLMs capabilities for robust prediction of small molecule geometries still retains nearly all of its pre-trained language abilities by randomly mixing in small quantities of natural language prompt-response pairs into the fine-tuning.
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