FAMS complex: a fully automated homology modeling system for protein complex structures.

The formation of a protein-protein complex is responsible for many biological functions; therefore, three-dimensional structures of protein complexes are essential for deeper understandings of protein functions and the mechanisms of diseases at the atomic level. However, compared with individual proteins, complex structures are difficult to solve experimentally because of technical limitations. Thus a method that can predict protein complex structures would be invaluable. In this study, we developed new software, FAMS Complex; a fully automated homology modeling system for protein complex structures consisting of two or more molecules. FAMS Complex requires only sequences and alignments of the target protein as input and constructs all molecules simultaneously and automatically. FAMS Complex is likely to become an essential tool for structure-based drug design, such as in silico screening to accelerate drug discovery before an experimental structure is solved. Moreover, in this post-genomic era when huge amounts of protein sequence information are available, a major goal is the determination of protein-protein interaction networks on a genomic scale. FAMS Complex will contribute to this goal, because its procedure is fully automated and so is suited for large-scale genome wide modeling.

Protein structure prediction in structure based drug design.

The human genome and other genome sequencing projects have generated huge amounts of protein sequence information. Recently, a structural genomics project that aims to determine at least one representative three-dimensional structure from every protein family experimentally has been started. Homology modeling will play an essential role in structure based drug design such as in silico screening; because based on these representative structures the three-dimensional structures of the remaining proteins encoded in the various genomes can be predicted by homology modeling. The results of the last Critical Assessment of Techniques for Protein Structure Prediction (CASP5) demonstrated that the quality of homology modeling prediction has improved; reaching a level of reliability that biologists can now confidently use homology modeling. With improvements in modeling software and the growing number of known protein structures, homology modeling is becoming a more and more powerful and reliable tool. The present paper discusses the features and roles of homology modeling in structure based drug design, and describes the CHIMERA and FAMS modeling systems as examples. For a sample application, homology modeling of non-structural proteins of the severe acute respiratory syndrome (SARS) coronavirus is discussed. Many biological functions involve formation of protein-protein complexes; in which the protein molecules behave dynamically in the course of binding. Therefore, an understanding of protein-protein interaction will be very important for structure based drug design. To this end, normal mode analysis is useful. The present paper discusses the prediction of protein-protein interaction using normal mode analysis and examples of applications are given.