Template based protein structure prediction (commonly referred to as homology or comparative modeling) uses knowledge of solved structures to model a protein sequence's native or true fold. First, a parent structure is found and then a template structure is built by mapping the target sequence onto the parent structure. This putative structure is refined using a combination of backbone moves, side-chain packing, and loop modeling. Template based protein structure prediction has always held great promise to produce atomically accurate models close to the native conformation based on two major assumptions. First, similar sequences exhibit similar protein folds. Second, soluble proteins populate a discrete fold space with many representatives already solved in our Protein Data Bank (PDB). Ironically, beginning so close to the native structure is also the primary source of problems confronting this method and is the reason for the lack of progress in this category of structure prediction. In this review, the general concepts and procedures for template based structure prediction are outlined based on the following topics: sequence alignment, parent structure selection, template structure building, refinement, evaluation, and final structure selection. Then, a description of established software and algorithms is provided where the advantages and limitations of the different methods will be pointed out. This is followed by a discussion of the developments in template based structure prediction up to the 7th Critical Assessment of Structure Prediction meeting. Lastly, we will address the increased difficulty in improving templates that start so close to the native structure, and discuss the improvements needed in this field.

MOTIVATION: Our focus has been on detecting topological properties that are rare in real proteins, but occur more frequently in models generated by protein structure prediction methods such as Rosetta. We previously created the Knotfind algorithm, successfully decreasing the frequency of knotted Rosetta models during CASP6. We observed an additional class of knot-like loops that appeared to be equally un-protein-like and yet do not contain a mathematical knot. These topological features are commonly referred to as slip-knots and are caused by the same mechanisms that result in knotted models. Slip-knots are undetectable by the original Knotfind algorithm. We have generalized our algorithm to detect them, and analyzed CASP6 models built using the Rosetta loop modeling method. RESULTS: After analyzing known protein structures in the PDB, we found that slip-knots do occur in certain proteins, but are rare and fall into a small number of specific classes. Our group used this new Pokefind algorithm to distinguish between these rare real slip-knots and the numerous classes of slip-knots that we discovered in Rosetta models and models submitted by the various CASP7 servers. The goal of this work is to improve future models created by protein structure prediction methods. Both algorithms are able to detect un-protein-like features that current metrics such as GDT are unable to identify, so these topological filters can also be used as additional assessment tools.

The issue of how a newly synthesized polypeptide chain folds to form a protein with a unique three-dimensional structure, otherwise known as the 'protein-folding problem', remains a fundamental question in the life sciences. Over the last few decades, much information has been gathered about the mechanisms by which proteins fold. However, despite the vast topological diversity observed in biological structures, it was thought improbable, if not impossible, that a polypeptide chain could 'knot' itself to form a functional protein. Nevertheless, such knotted structures have since been identified, raising questions about how such complex topologies can arise during folding. Their formation does not fit any current folding models or mechanisms, and therefore represents an important piece of the protein-folding puzzle. This article reviews the progress made towards discovering how nature codes for, and contends with, knots during protein folding, and examines the insights gained from both experimental and computational studies. Mechanisms to account for the formation of knotted structures that were previously thought unfeasible, and their implications for protein folding, are also discussed.

Among proteins of known three-dimensional structure, only a few possess complex topological features such as knotted or interlinked (catenated) protein backbones. Such unusual proteins offer potentially unique insights into folding pathways and stabilization mechanisms. They also present special challenges for both theorists and computational scientists interested in understanding and predicting protein-folding behavior. Here, we review complex topological features in proteins with a focus on recent progress on the identification and characterization of knotted and interlinked protein systems. Also, an approach is described for designing an expanded set of knotted proteins.

Among the thousands of known three-dimensional protein folds, only a few have been found whose backbones are in knotted configurations. The rarity of knotted proteins has important implications for how natural proteins reach their natively folded states. Proteins with such unusual features offer unique opportunities for studying the relationships between structure, folding, and stability. Here we report the identification of a unique slipknot feature in the fold of a well-known thermostable protein, alkaline phosphatase. A slipknot is created when a knot is formed by part of a protein chain, after which the backbone doubles back so that the entire structure becomes unknotted in a mathematical sense. Slipknots are therefore not detected by computational tests that look for knots in complete protein structures. A computational survey looking specifically for slipknots in the Protein Data Bank reveals a few other instances in addition to alkaline phosphatase. Unexpected similarities are noted among some of the proteins identified. In addition, two transmembrane proteins are found to contain slipknots. Finally, mutagenesis experiments on alkaline phosphatase are used to probe the contribution the slipknot feature makes to thermal stability. The trends and conserved features observed in these proteins provide new insights into mechanisms of protein folding and stability.

Transcarbamylases catalyze the transfer of the carbamyl group from carbamyl phosphate (CP) to an amino group of a second substrate such as aspartate, ornithine, or putrescine. Previously, structural determination of a transcarbamylase from Xanthomonas campestris led to the discovery of a novel N-acetylornithine transcarbamylase (AOTCase) that catalyzes the carbamylation of N-acetylornithine. Recently, a novel N-succinylornithine transcarbamylase (SOTCase) from Bacteroides fragilis was identified. Structural comparisons of AOTCase from X. campestris and SOTCase from B. fragilis revealed that residue Glu92 (X. campestris numbering) plays a critical role in distinguishing AOTCase from SOTCase. Enzymatic assays of E92P, E92S, E92V, and E92A mutants of AOTCase demonstrate that each of these mutations converts the AOTCase to an SOTCase. Similarly, the P90E mutation in B. fragilis SOTCase (equivalent to E92 in X. campestris AOTCase) converts the SOTCase to AOTCase. Hence, a single amino acid substitution is sufficient to swap the substrate specificities of AOTCase and SOTCase. X-ray crystal structures of these mutants in complexes with CP and N-acetyl-L-norvaline (an analog of N-acetyl-L-ornithine) or N-succinyl-L-norvaline (an analog of N-succinyl-L-ornithine) substantiate this conversion. In addition to Glu92 (X. campestris numbering), other residues such as Asn185 and Lys30 in AOTCase, which are involved in binding substrates through bridging water molecules, help to define the substrate specificity of AOTCase. These results provide the correct annotation (AOTCase or SOTCase) for a set of the transcarbamylase-like proteins that have been erroneously annotated as ornithine transcarbamylase (OTCase, EC 2.1.3.3).