Prediction of protein function from protein sequence and structure

Abstract

1. Introduction 3082. Plan of this article 3123. Natural mechanisms of development of novel protein functions 3133.1 Divergence 3133.2 Recruitment 3163.3 ‘Mixing and matching’ of domains, including duplication/oligomerization, and domain swapping or fusion 3164. Classification schemes for protein functions 3174.1 General schemes 3174.2 The EC classification 3184.3 Combined classification schemes 3194.4 The Gene Ontology Consortium 3215. Methods for assigning protein function 3215.1 Detection of protein homology from sequence, and its application to function assignment 3215.2 Detection of structural similarity, protein structure classifications, and structure/function correlations 3265.3 Function prediction from amino-acid sequence 3275.3.1 Databases of single motifs 3285.3.2 Databases of profiles 3295.3.3 Databases of multiple motifs 3305.3.4 Precompiled families 3315.3.5 Function identification from sequence by feature extraction 3315.4 Methods making use of structural data 3326. Applications of full-organism information: inferences from genomic context and protein interaction patterns 3347. Conclusions 3358. Acknowledgements 3359. References 335The sequence of a genome contains the plans of the possible life of an organism, but implementation of genetic information depends on the functions of the proteins and nucleic acids that it encodes. Many individual proteins of known sequence and structure present challenges to the understanding of their function. In particular, a number of genes responsible for diseases have been identified but their specific functions are unknown. Whole-genome sequencing projects are a major source of proteins of unknown function. Annotation of a genome involves assignment of functions to gene products, in most cases on the basis of amino-acid sequence alone. 3D structure can aid the assignment of function, motivating the challenge of structural genomics projects to make structural information available for novel uncharacterized proteins. Structure-based identification of homologues often succeeds where sequence-alone-based methods fail, because in many cases evolution retains the folding pattern long after sequence similarity becomes undetectable. Nevertheless, prediction of protein function from sequence and structure is a difficult problem, because homologous proteins often have different functions. Many methods of function prediction rely on identifying similarity in sequence and/or structure between a protein of unknown function and one or more well-understood proteins. Alternative methods include inferring conservation patterns in members of a functionally uncharacterized family for which many sequences and structures are known. However, these inferences are tenuous. Such methods provide reasonable guesses at function, but are far from foolproof. It is therefore fortunate that the development of whole-organism approaches and comparative genomics permits other approaches to function prediction when the data are available. These include the use of protein–protein interaction patterns, and correlations between occurrences of related proteins in different organisms, as indicators of functional properties. Even if it is possible to ascribe a particular function to a gene product, the protein may have multiple functions. A fundamental problem is that function is in many cases an ill-defined concept. In this article we review the state of the art in function prediction and describe some of the underlying difficulties and successes.