Yeah, I personally think the better biological analogue for gradient descent is the "run-and-tumble" motion of bacteria.
Take an e. coli. It has a bunch of flagella, pointing in all directions. When it rotates its flagella clockwise, each of them ends up pushing in a random direction, which results in the cell chaotically tumbling without going very far. When it rotates its flagella counterclockwise, they get tangled up with each other and all end up pointing the same direction, and the cell moves in a roughly straight line. The more attractants and fewer repellants there are, the more the cell rotates its flagella counterclockwise.
And that's it. That's the entire strategy by which e. coli navigates to food.
Here's a page with an animation of how this extremely basic behavior approximates gradient descent.
All that said, evolution looks kinda like gradient descent if you squint. For mind design, evolution would be gradient descent over the hyperparameters (and cultural evolution would be gradient descent over the training data generation process, and learning would be gradient descent over sensory data, and all of these gradients would steer in different but not entirely orthogonal directions).