Daniella Hares
Computational Chemist The Francis Crick Institute
Daniella Hares is a computational chemist specializing in molecular simulations and binding free energy calculations to support drug discovery and compound optimization. With expertise spanning Molecular Dynamics, Monte Carlo simulations, and Relative Binding Free Energy methodologies, she leverages advanced computational approaches to predict molecular behaviour, guide medicinal chemistry strategies, and accelerate the identification of promising drug candidates. Her work focuses on applying in silico techniques to improve decision-making across the drug development process, helping teams optimize compound potency, selectivity, and overall therapeutic potential.
Seminars
Are your AI-driven discovery workflows accelerating innovation, or simply generating more noise?
With AI rapidly transforming peptide discovery, how can you separate genuinely impactful technologies from overhyped solutions? Which computational approaches are delivering measurable improvements in hit identification, optimisation and candidate selection? And how can researchers overcome the limitations of current AI models when designing peptides with non-canonical amino acids and increasingly complex modalities?
This workshop will gather experts to discuss:
- Distinguish between AI tools that deliver real value versus overhyped solutions that waste resources and time
- Master co-folding methods like AlphaFold for identifying binders against challenging targets with non-canonical amino acids
- Learn how molecular dynamics simulations can test and refine co-folding predictions by capturing how peptides behave in motion
- Learn how to combine AI predictions, molecular dynamics simulations and experimental data generation with informed model training for superior hit discovery
- Discover which AI-driven design approaches work for macrocyclic peptides versus structured mini-binders.
