Researchers have introduced Vilya-1, a novel deep learning model designed for the prediction and design of macrocycle structures. This all-atom foundation model addresses limitations in current computational methods by accurately sampling relevant conformations and predicting properties like membrane permeability across diverse chemical spaces. Vilya-1 demonstrates improved geometric accuracy compared to existing physics-based and deep-learning approaches, enabling the design of new macrocycles with specific chemical and structural profiles for therapeutic development. AI
IMPACT Accelerates the design and development of novel macrocycle therapeutics by improving computational modeling accuracy and generative capabilities.
RANK_REASON The item describes a new scientific paper detailing a novel AI model for a specific scientific domain. [lever_c_demoted from research: ic=1 ai=1.0]
- alphaXiv
- arXiv
- CatalyzeX
- Connected Papers
- DagsHub
- Gotit.pub
- Hugging Face
- IArxiv
- Litmaps
- ScienceCast
- scite Smart Citations
- Vilya-1
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →
