MAPPIS: Multiple 3D Alignment of Protein-Protein Interfaces
نویسندگان
چکیده
A protein-protein interface (PPI) is defined by a pair of regions of two interacting protein molecules that are linked by non-covalent bonds. Recognition of conserved 3D patterns of physico-chemical interactions may suggest their importance for the function as well as for the stability and formation of the protein-protein complex. It may assist in discovery of new drug leads that target these interactions. We present a novel method, MAPPIS, for multiple structural alignment of PPIs which allows recognition of a set of common physico-chemical properties and their interactions without the need to assume similarity of sequential patterns or backbone patterns. We show its application to several biological examples, such as alignment of interfaces of G proteins with their effectors and regulators, as well as previously created clusters of interfaces. Availability: http://bioinfo3d.cs.tau.ac.il/mappis/
منابع مشابه
MultiBind and MAPPIS: webservers for multiple alignment of protein 3D-binding sites and their interactions
Analysis of protein-ligand complexes and recognition of spatially conserved physico-chemical properties is important for the prediction of binding and function. Here, we present two webservers for multiple alignment and recognition of binding patterns shared by a set of protein structures. The first webserver, MultiBind (http://bioinfo3d.cs.tau.ac.il/MultiBind), performs multiple alignment of p...
متن کاملMAPPIS: Multiple Alignment of Protein-Protein Interfaces
Association and dissociation of protein molecules are crucial for most of the cellular processes. A protein-protein interface (PPI) is defined by a pair of regions of two interacting protein molecules that are linked by non-covalent bonds. Analysis and classification of PPIs may help to recognize certain interface binding organizations shared by different protein families, which may be importan...
متن کاملThree-dimensional cluster analysis identifies interfaces and functional residue clusters in proteins.
Three-dimensional cluster analysis offers a method for the prediction of functional residue clusters in proteins. This method requires a representative structure and a multiple sequence alignment as input data. Individual residues are represented in terms of regional alignments that reflect both their structural environment and their evolutionary variation, as defined by the alignment of homolo...
متن کاملA generalization of Profile Hidden Markov Model (PHMM) using one-by-one dependency between sequences
The Profile Hidden Markov Model (PHMM) can be poor at capturing dependency between observations because of the statistical assumptions it makes. To overcome this limitation, the dependency between residues in a multiple sequence alignment (MSA) which is the representative of a PHMM can be combined with the PHMM. Based on the fact that sequences appearing in the final MSA are written based on th...
متن کاملApplication of 3D-QSAR on a Series of Potent P38-MAP Kinase Inhibitors
One of the most applied methods in drug industry for development of new drugs is 3D-QSAR methodology. As p38-mitogen-activated protein kinase (p38-MAPK) plays a crucial role in regulating the production of such proinflammatory cytokines as tumor necrosis factor-α (TNF-α) and interleukin-1, emerging as an attractive target for new anti-inflammatory agents, we used a 3D-QSAR based method of Compa...
متن کامل