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- W1585287395 abstract "Protein-folding via numerical optimization Protein folding via divide-and-conquer optimization Ricardo Oliva collaborators Silvia Crivelli, Juan Meza Computational Sciences Division Working assumption: The “natural” conformation of a protein corresponds to a configuration that minimizes an energy potential. This premise brings the protein-folding problem into the realm of numerical optimization algorithms (e.g. LBFGS) Compute an X * that minimizes E(X), where X is the vector of atom coordinates, and E is a potential energy function (e.g. Amber). This is a challenging problem: • Potential function E is only a model. • Large-scale problem (size 10 3 --10 6 ) • Many local minima. Lawrence Berkeley National Laboratory Amber Energy Potential (Model) Movie with Cristina Siegerist (Visualization Group) E AMBER = E Bonds + E Angles + E Dihedrals + E NonBonded E Bonds = E Angles = ∑ B (r − r ) i i i Bonds Angles ∑ A ( θ i Dihedrals i − θ i ) Color ~ || Δ posn. || (speed) Two observations E Dihedrals = ∑ D ( 1+ cos(n φ i i i − δ i ) ) • atoms move in clusters. • slow “adjustment of positions” rather than large displacements E NonBonded q q = ∑ ∑ e ij ij − 2 ij + i j r r r ij ij ij i j>i" @default.
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- W1585287395 date "2004-07-11" @default.
- W1585287395 modified "2023-09-26" @default.
- W1585287395 title "Protein-folding via divide-and-conquer optimization" @default.
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