For naturally occurring proteins, similar sequence implies similar structure. 
Consequently, multiple sequence alignments (MSAs) often are used in 
template-based modeling of protein structure and have been incorporated into 
fragment-based assembly methods. Our previous homology-free structure prediction 
study introduced an algorithm that mimics the folding pathway by coupling the 
formation of secondary and tertiary structure. Moves in the Monte Carlo 
procedure involve only a change in a single pair of phi,psi backbone dihedral 
angles that are obtained from a Protein Data Bank-based distribution appropriate 
for each amino acid, conditional on the type and conformation of the flanking 
residues. We improve this method by using MSAs to enrich the sampling 
distribution, but in a manner that does not require structural knowledge of any 
protein sequence (i.e., not homologous fragment insertion). In combination with 
other tools, including clustering and refinement, the accuracies of the 
predicted secondary and tertiary structures are substantially improved and a 
global and position-resolved measure of confidence is introduced for the 
accuracy of the predictions. Performance of the method in the Critical 
Assessment of Structure Prediction (CASP8) is discussed.