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Protein Structure Prediction: Review Inroads to Biology

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Protein Structure Prediction: Review Inroads to Biology Molecular Cell, Vol. 20, 811–819, December 22, 2005, Copyright ª2005 by Elsevier Inc. DOI 10.1016/j.molcel.2005.12.005 Protein Structure Prediction: Review Inroads to Biology Donald Petrey1 and Barry Honig1,* Structure prediction is often divided into three areas: 1 Howard Hughes Medical Institute ab initio prediction, fold recognition, and homology Department of Biochemistry and Molecular Biophysics modeling. The distinction between these areas is usually Center for Computational Biology and Bioinformatics based on the extent to which information in sequence Columbia University and structural databases is used in the construction 1130 St. Nicholas Avenue, Room 815 of a model. Ab initio prediction in its purest form makes New York, New York 10032 no use of information in databases (see e.g., Nanias et al. [2005]), and the goal is to predict the structure of a protein based entirely on the laws of physics and chemistry. The In recent years, there has been significant progress in term ab initio or de novo is also applied to the prediction the ability to predict the three-dimensional structure of the structure of proteins for which there is no similar of proteins from their amino acid sequence. Progress structure in the Protein Database (PDB) but where local has been due to new methods to extract the grow- sequence and structural relationships involving short ing amount of information in sequence and structure protein fragments, as well as secondary structure pre- databases and improved computational descriptions diction, are incorporated into the prediction process of protein energetics. This review summarizes recent (Bradley et al., 2005). Fold recognition, often referred to advances in these areas and describes a number of as ‘‘threading,’’ corresponds to the case where one or novel biological applications made possible by struc- more structures (templates) similar to a given target se- ture prediction. Despite remaining challenges, protein quence exist in the PDB but are not easily identified. Here structure prediction is becoming an extremely useful the main challenge is to find the best set of templates, tool in understanding phenomena in modern molecu- but, in general, it will be difficult to build an accurate lar and cell biology. model. At the current stage of the technology, the most accurate models are obtained when a single template can be found in the PDB that has a high level of sequence Introduction similarity to the target protein. The process of building The prediction of the three-dimensional structure of a model from such a template is referred to as homology a protein from its amino acid sequence is a challenge or comparative modeling. that has fascinated researchers in different disciplines With the exception of pure physical chemical ap- for many years. The potential impact of significant ad- proaches, essentially all protein structure prediction vances in structure prediction is enormous, since we al- methods rely on the identification of templates that may ready have ample evidence of the importance of three- range in length from relatively short fragments, as in de dimensional structure information in so many areas of novo methods, to entire proteins, as in homology mod- biology. As an example, a recent paper used predicted eling. Thus, they may all be thought of as involving ‘‘tem- structures of retroviral matrix domains, together with plate-based protein structure prediction.’’ In this review, an analysis of known structures, to establish the mode we will use the term ‘‘protein structure prediction’’ to re- of interaction of the entire matrix domain family with fer to all template-based methods. Our focus will be on membrane surfaces (Murray et al., 2005). More generally, methods that rely heavily on a small number of clearly models of members of protein families that are derived defined templates since, at this point in time, these are from experimentally determined structures make it pos- the only ones that offer a high probability of being accu- sible to deduce family-based structure-function rela- rate enough to enable the identification of biological tionships that are not evident from a small number of function. currently available representative structures of family The existence of templates that may cover only some members. The availability of such models can also reveal regions of a protein raises new questions as to the nature specificity differences within families, thus significantly of evolutionary relationships between proteins. Indeed, expanding the range of questions that can be addressed an important spin-off of structural biology has been based on the original experimentally determined struc- the discovery of new relationships between amino acid ture. Models can also be used as a basis for identifying sequences and protein structures, and among different the function of individual proteins, much in the way this protein structures. Methods to superimpose three-di- is accomplished with experimentally determined struc- mensional structures have been developed (Kolodny tures. However, despite the enormous potential impact et al., 2005b), and it has been recognized that many of protein structure prediction, the extent to which mod- proteins may have evolutionary relationships that are els that are being generated today can be used with con- evident from structure but not from sequence. Widely fidence in different applications is unclear. This review used databases such as SCOP (Lo Conte et al., 2000) will address this question in the context of a discussion and CATH (Pearl et al., 2005) divide proteins into discrete of the modeling process, with particular emphasis on families based on simple sequence relationships, super- a description of current research activity, and will also in- families based on structural and function similarity and clude a number of examples of specific biological appli- less-obvious sequence relationships, and fold based en- cations of structure prediction. tirely on structural similarity. The assumption has been that proteins in different folds evolved independently, *Correspondence: [email protected] but is this generally the case? Molecular Cell 812 Indeed, there is a great deal of ambiguity in the defini- is the subject of significant research activity, with the tion of a fold, and an argument can be made that fold problems that are being addressed ranging in nature space should be viewed as continuous (Shindyalov from the use of bioinformatics techniques to analyze se- and Bourne, 2000; Yang and Honig, 2000). A related find- quence and structure to the physical-chemical study of ing is that, given a target sequence, it is almost always the conformational energies and dynamics of proteins. possible either to find a protein that is similar to a target In the following sections, we describe the tools currently structure in overall topology (Kihara and Skolnick, 2003), used or being developed at each stage. or there is likely to be a set of proteins that have regions similar to all or part of the target (Szustakowski et al., Template Selection 2005; Zhang and Skolnick, 2005). There is also evidence The first step in structure prediction invariably involves of sequence relationships between proteins that have the use of some sequence alignment method to identify different folds (Friedberg and Godzik, 2005). Thus, the a statistically significant relationship between the tar- problem of structure prediction appears dependent in get sequence and one or more possible templates. part on the ability to identify sequence and structure re- There are a variety of methods used for this purpose lationships between proteins that, at least based on ex- that have been reviewed elsewhere (Pearson and Sierk, isting classification schemes, might not be expected to 2005). The field has evolved in clear stages, differing pri- be related. marily in the way in which the template sequences are A significantly improved ability to detect such rela- represented. Currently, the most widely used template tionships may well be one of the important by-products selection methods involve the representation of tem- of the various structural genomics initiatives that have plates as profiles, as in PsiBlast (Altschul et al., 1997) been funded in different countries around the world. or hidden Markov models (HMMs) (Eddy, 1998). In a pro- An important goal is to find a structural representative file or HMM, each position represents not a single amino for as many protein sequence families as possible, so acid, as in standard sequence alignments, but a collec- that homology models for other family members can tion of features that are obtained from the multiple se- be built, or at least so that an overall folding topology quence alignment of proteins that bear a clear evolution- can be assigned to each member. That structure predic- ary relationship. Profiles and HMMs, therefore, are a tion is an essential component of structural genomics in- more accurate representation of the variability that can itiatives implies large-scale acceptance of the value of occur at individual positions of a protein sequence. template-based structure prediction. This results in more sensitive detection of remote homo- A number of reviews of structure prediction methods logs (Marti-Renom et al., 2004). have recently been written (Ginalski et al., 2005; Marti- The set of features included in a profile or HMM varies Renom et al., 2000; Sanchez and Sali, 1997). Also, the greatly. In their simplest form, each position in a se- descriptions of the outcomes of the Critical Assessment quence is simply the probability of each amino acid ap- of Techniques for Protein Structure Prediction (CASP) pearing at that position (Altschul et al., 1997). Structural experiments are good sources of information about cur- features of the template and predicted structural fea- rent structure prediction methods (Moult et al., 2003). tures of the target, for example, the location of second- CASP is a blind test of structure prediction methods in ary structure elements, can also be included in a profile.
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