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gradient descent != molecular dynamics; the latter is simulating forces on atoms, not attempting to optimize a target function. You can use molecular dynamics for optimization too - it can be very powerful, just slow - but I don't think that's what they're describing here.

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I read it as they are using a molecular dynamics package to define a function (potential energy of the protein structure) and are using gradient descent to (slowly) reach stable extrema (static configurations of the protein).

That makes more sense, but the energy function isn't really a feature of molecular dynamics, anything that does molecular optimization or modeling will have this information built in.

You're absolutely right. My bad, mixed too many ideas at once :). Gradient descent (or similar techniques) can be used for structural optimization with the same atomistic models used in molecular dynamics.

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