diff --git a/Project.toml b/Project.toml
index 2042474..e1173bd 100644
--- a/Project.toml
+++ b/Project.toml
@@ -13,7 +13,7 @@ Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [compat]
 AssigningSecondaryStructure = "0.2"
-Distances = "0"
+Distances = "^0.10"
 LinearAlgebra = "1"
 PDBTools = "^0.15"
 Rotations = "1"
diff --git a/src/protein/idealize.jl b/src/protein/idealize.jl
new file mode 100644
index 0000000..2dc2e6d
--- /dev/null
+++ b/src/protein/idealize.jl
@@ -0,0 +1,67 @@
+# This algorithm is presented in a paper by Cui et al.: https://almob.biomedcentral.com/articles/10.1186/1748-7188-8-5
+
+import Distances: euclidean, sqeuclidean
+import Statistics: mean
+
+# written as D(P_i, P_j) in the paper
+bottleneck_distance(P_i::Backbone, P_j::Backbone) = sqrt(maximum(sqeuclidean, zip(P_i, P_j)))
+ 
+# the root-mean-square deviation of atomic positions: https://en.wikipedia.org/wiki/Root-mean-square_deviation_of_atomic_positions
+RMSD(m1::M, m2::M) where M <: AbstractMatrix{<:Real} = sqrt(mean(_pairwise_column_distances(m1, m2, sqeuclidean)))
+RMSD(v1::V, v2::V) where V <: AbstractVector{<:Real} = sqrt(mean(x -> x^2, v1 .- v2)) # should be same as reshaping into matrix
+
+# written as S_f(P_i) in the paper
+function free_energy_score(P_i::Backbone) # pass Chain instead (or amino acid vector)
+    return 0 # TODO
+end
+
+function D_α(P_i::Backbone, P_j::Backbone)
+    return RMSD(alphacarbon_coords(P_i), alphacarbon_coords(P_j))
+end
+
+angle_D(a, b) = min(abs(a - b), 2π - abs(a - b))
+
+function D_φψ(P_i::Backbone, P_j::Backbone)
+    bonds_i = ChainedBonds(P_i)
+    bonds_j = ChainedBonds(P_j)
+    φ_i, ψ_i = phi_angles(bonds_i), psi_angles(bonds_i)
+    φ_j, ψ_j = phi_angles(bonds_j), psi_angles(bonds_j)
+    return sqrt(mean(angle_D.(φ_i, φ_j).^2 .+ angle_D.(ψ_i, ψ_j).^2))
+end
+
+function D_O(P_i::Backbone, P_j::Backbone)
+    return sqrt(RMSD(oxygen_coords(P_i)^2, oxygen_coords(P_j))^2)
+end
+
+# TODO: add beta and hydrogen terms
+# TODO: precomputed bonds_0
+# written as S_{BB}(P_i) in the paper
+# evaluates not only the similarity between idealized and target structure,
+# but also evaluates the free energy to ensure it's protein-like
+function score_function(P_0::Backbone, P_i::Backbone, w1=1, w2=1, w3=1)
+    - w1*D_α(P_0, P_i) +
+    - w2*D_O(P_0, P_i) +
+    - w3*D_φψ(P_0, P_i)
+end
+
+# Main Dynamic Programming Algorithm
+function idealize_protein_structure(P_0::Backbone, r=1, ϵ=r/5)
+    
+end
+
+
+
+
+"""
+    idealize(backbone, idealized_lengths, idealized_angles)
+
+`idealized_lengths` and `idealized_angles` will be *repeated* indefinitely to fill the backbone.
+Thus, for protein chains, 3 elements will suffice for each vector.
+"""
+function idealize(
+    backbone::Backbone{T},
+    idealized_lengths::AbstractVector{T},
+    idealized_angles::AbstractVector{T},
+)
+
+end
\ No newline at end of file