Proteins perform their functions mainly via active sites, whereas other parts of the proteins comprise the scaffolds, which support the active sites. One strategy for protein functional design is transplanting active sites, such as catalytic sites for enzyme or binding hot spots for protein-protein interactions, onto a new scaffold. AutoMatch is a new program designed for efficiently elucidating suitable scaffolds and potential sites on the scaffolds. Backrub motions are used to treat backbone flexibility during the design process. A step-by-step checking strategy and cluster-representation examination strategy were developed to solve the large combinatorial problem for the matching of active-site conformations. In addition, a grid-based binding energy scoring method was used to filter the solutions. An enzyme design benchmark and a protein-protein interaction design benchmark were built to test the algorithm. AutoMatch could identify the hot spots in the nonbinding protein and rank them within the top five results for 8 of 10 target-binding protein design cases. In addition, among the 15 enzymes tested, AutoMatch can identify the catalytic active sites in the apoprotein and rank them within the top five results for 13 cases. AutoMatch was also tested for screening scaffold library in designing binding proteins targeting influenza hemagglutinin, HIV gp120, and epidermal growth factor receptor kinase, respectively. AutoMatch, and the two test sets, ActApo and ActFree, are available for noncommercial applications at http://mdl.ipc.pku.edu.cn/cgi-bin/down.cgi.
"Graph theory-based pattern matching approaches or set reduction algorithms may be employed in spotting scaffolds that can accommodate desired hot spot patterns (Liang et al., 2000). Lai and his coworkers developed such algorithms (Liang et al., 2000; Zhang and Lai, 2012) and they successfully designed a protein to bind the human EPO receptor (Liu et al., 2007). Fleishman et al. (Fleishman et al., 2011) suggested another approach to design protein drugs with predetermined hot spot patterns. "
[Show abstract][Hide abstract] ABSTRACT: Identification of drug-like small molecules that alter protein-protein interactions might be a key step in drug discovery. However, it is very challenging to find such molecules that target interface regions in protein complexes. Recent findings indicate that such molecules usually target specifically energetically favored residues (hot spots) in protein-protein interfaces. These residues contribute to the stability of protein-protein complexes. Computational prediction of hot spots on bound and unbound structures might be useful to find druggable sites on target interfaces. We review the recent advances in computational hot spot prediction methods in the first part of the review and then provide examples on how hot spots might be crucial in drug design.
Progress in Biophysics and Molecular Biology 07/2014; 116(2-3). DOI:10.1016/j.pbiomolbio.2014.06.003 · 2.27 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Protein design or redesign generate an amino acid sequence that folds to a stable protein and performs a desired
function. In other words, designer proteins are modified versions of naturally occurring proteins. The engineering,
design and selection of proteins for use in therapy and biotechnology is essential. Protein design has become a
powerful approach for understanding the relationship between amino acid sequence and 3-dimensional structure.
Moreover, protein design challenges have direct relevance for biomedicine. Designer proteins may help produce
more drugs with longer shelf-life. Researchers are developing new methods to create ‘tailor-made’ peptides and
proteins with improved pharmacological properties
[Show abstract][Hide abstract] ABSTRACT: RNA-protein interactions play key roles in many biological processes. The three dimensional (3D) structure of protein-RNA complexes can be determined experimentally by structural biologists. The recognition between protein and RNA can be understood from the 3D atomic structure. However, the structure determination of protein-RNA complexes by experimental methods is often difficult and costly, and limited to the binding strength. Thus, the prediction and design of protein-RNA complex structures is important in biological medical research. In this review, we will discuss the recent progress in protein-RNA interface prediction and design, which includes the following aspects: (1) protein-RNA docking and the conformational change on binding; (2) the recognition mechanism of protein-RNA binding; (3) the molecular design based on the protein-RNA interface. Improvement of the protein-RNA docking algorithm will help us annotate a large number of proteins and RNA with unknown function, and molecular design based on macromolecular interactions will be useful in drug design.
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