Hasup Lee

Community-wide assessment of protein-interface modeling suggests improvements to design methodology

The CAPRI (Critical Assessment of Predicted Interactions) and CASP (Critical Assessment of protein Structure Prediction) experiments have demonstrated the power of community-wide tests of methodology in assessing the current state of the art and spurring progress in the very challenging areas of protein docking and structure prediction. We sought to bring the power of community-wide experiments to bear on a very challenging protein design problem that provides a complementary but equally fundamental test of current understanding of protein-binding thermodynamics. We have generated a number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments, suggesting that there may be important physical chemistry missing in the energy calculations. A total of 28 research groups took up the challenge of determining what is missing: we provided structures of 87 designed complexes and 120 naturally occurring complexes and asked participants to identify energetic contributions and/or structural features that distinguish between the two sets. The community found that electrostatics and solvation terms partially distinguish the designs from the natural complexes, largely due to the nonpolar character of the designed interactions. Beyond this polarity difference, the community found that the designed binding surfaces were, on average, structurally less embedded in the designed monomers, suggesting that backbone conformational rigidity at the designed surface is important for realization of the designed function. These results can be used to improve computational design strategies, but there is still much to be learned; for example, one designed complex, which does form in experiments, was classified by all metrics as a nonbinder.

Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions

Community‐wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community‐wide assessment of methods to predict the effects of mutations on protein–protein interactions. Twenty‐two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side‐chain sampling and backbone relaxation, evaluated packing, electrostatic, and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large‐scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies. Proteins 2013; 81:1980–1987.

GalaxyPepDock: a protein–peptide docking tool based on interaction similarity and energy optimization

Protein–peptide interactions are involved in a wide range of biological processes and are attractive targets for therapeutic purposes because of their small interfaces. Therefore, effective protein–peptide docking techniques can provide the basis for potential therapeutic applications by enabling an atomic-level understanding of protein interactions. With the increasing number of protein–peptide structures deposited in the protein data bank, the prediction accuracy of protein-peptide docking can be enhanced by utilizing the information provided by the database. The GalaxyPepDock web server, which is freely accessible at http://galaxy.seoklab.org/pepdock, performs similarity-based docking by finding templates from the database of experimentally determined structures and building models using energy-based optimization that allows for structural flexibility. The server can therefore effectively model the structural differences between the template and target protein–peptide complexes. The performance of GalaxyPepDock is superior to those of the other currently available web servers when tested on the PeptiDB set and on recently released complex structures. When tested on the CAPRI target 67, GalaxyPepDock generates models that are more accurate than the best server models submitted during the CAPRI blind prediction experiment.

Blind prediction of interfacial water positions in CAPRI.

We report the first assessment of blind predictions of water positions at protein–protein interfaces, performed as part of the critical assessment of predicted interactions (CAPRI) community‐wide experiment. Groups submitting docking predictions for the complex of the DNase domain of colicin E2 and Im2 immunity protein (CAPRI Target 47), were invited to predict the positions of interfacial water molecules using the method of their choice. The predictions—20 groups submitted a total of 195 models—were assessed by measuring the recall fraction of water‐mediated protein contacts. Of the 176 high‐ or medium‐quality docking models—a very good docking performance per se—only 44% had a recall fraction above 0.3, and a mere 6% above 0.5. The actual water positions were in general predicted to an accuracy level no better than 1.5 Å, and even in good models about half of the contacts represented false positives. This notwithstanding, three hotspot interface water positions were quite well predicted, and so was one of the water positions that is believed to stabilize the loop that confers specificity in these complexes. Overall the best interface water predictions was achieved by groups that also produced high‐quality docking models, indicating that accurate modelling of the protein portion is a determinant factor. The use of established molecular mechanics force fields, coupled to sampling and optimization procedures also seemed to confer an advantage. Insights gained from this analysis should help improve the prediction of protein–water interactions and their role in stabilizing protein complexes. Proteins 2014; 82:620–632.

GalaxyGemini: a web server for protein homo-oligomer structure prediction based on similarity

SUMMARY A large number of proteins function as homo-oligomers; therefore, predicting homo-oligomeric structure of proteins is of primary importance for understanding protein function at the molecular level. Here, we introduce a web server for prediction of protein homo-oligomer structure. The server takes a protein monomer structure as input and predicts its homo-oligomer structure from oligomer templates selected based on sequence and tertiary/quaternary structure similarity. Using protein model structures as input, the server shows clear improvement over the best methods of CASP9 in predicting oligomeric structures from amino acid sequences. AVAILABILITY http://galaxy.seoklab.org/gemini. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

High-resolution protein–protein docking by global optimization: recent advances and future challenges

A computational protein-protein docking method that predicts atomic details of protein-protein interactions from protein monomer structures is an invaluable tool for understanding the molecular mechanisms of protein interactions and for designing molecules that control such interactions. Compared to low-resolution docking, high-resolution docking explores the conformational space in atomic resolution to provide predictions with atomic details. This allows for applications to more challenging docking problems that involve conformational changes induced by binding. Recently, high-resolution methods have become more promising as additional information such as global shapes or residue contacts are now available from experiments or sequence/structure data. In this review article, we highlight developments in high-resolution docking made during the last decade, specifically regarding global optimization methods employed by the docking methods. We also discuss two major challenges in high-resolution docking: prediction of backbone flexibility and water-mediated interactions.

Crystal Structure of Streptococcus pyogenes Cas1 and Its Interaction with Csn2 in the Type II CRISPR-Cas System

CRISPRs and Cas proteins constitute an RNA-guided microbial immune system against invading nucleic acids. Cas1 is a universal Cas protein found in all three types of CRISPR-Cas systems, and its role is implicated in new spacer acquisition during CRISPR-mediated adaptive immunity. Here, we report the crystal structure of Streptococcus pyogenes Cas1 (SpCas1) in a type II CRISPR-Cas system and characterize its interaction with S. pyogenes Csn2 (SpCsn2). The SpCas1 structure reveals a unique conformational state distinct from type I Cas1 structures, resulting in a more extensive dimerization interface, a more globular overall structure, and a disruption of potential metal-binding sites for catalysis. We demonstrate that SpCas1 directly interacts with SpCsn2, and identify the binding interface and key residues for Cas complex formation. These results provide structural information for a type II Cas1 protein, and lay a foundation for studying multiprotein Cas complexes functioning in type II CRISPR-Cas systems.

Structure of vaccinia virus A46, an inhibitor of TLR4 signaling pathway, shows the conformation of VIPER motif

Vaccinia virus (VACV) encodes many proteins that interfere with the host immune system. Vaccinia virus A46 protein specifically targets the BB‐loop motif of TIR‐domain‐containing proteins to disrupt receptor:adaptor (e.g., TLR4:MAL and TLR4:TRAM) interactions of the toll‐like receptor signaling. The crystal structure of A46 (75–227) determined at 2.58 Å resolution showed that A46 formed a homodimer and adopted a Bcl‐2‐like fold similar to other VACV proteins such as A52, B14, and K7. Our structure also revealed that VIPER (viral inhibitory peptide of TLR4) motif resides in the α1‐helix and six residues of the VIPER region were exposed to surface for binding to target proteins. In vitro binding assays between wild type and six mutants A46 (75–227) and full‐length MAL identified critical residues in the VIPER motif. Computational modeling of the A46:MAL complex structure showed that the VIPER region of A46 and AB loop of MAL protein formed a major binding interface. In summary, A46 is a homodimer with a Bcl‐2‐like fold and VIPER motif is believed to be involved in the interaction with MAL protein based on our binding assays.

GalaxyRefineComplex: Refinement of protein-protein complex model structures driven by interface repacking.

Protein-protein docking methods have been widely used to gain an atomic-level understanding of protein interactions. However, docking methods that employ low-resolution energy functions are popular because of computational efficiency. Low-resolution docking tends to generate protein complex structures that are not fully optimized. GalaxyRefineComplex takes such low-resolution docking structures and refines them to improve model accuracy in terms of both interface contact and inter-protein orientation. This refinement method allows flexibility at the protein interface and in the overall docking structure to capture conformational changes that occur upon binding. Symmetric refinement is also provided for symmetric homo-complexes. This method was validated by refining models produced by available docking programs, including ZDOCK and M-ZDOCK, and was successfully applied to CAPRI targets in a blind fashion. An example of using the refinement method with an existing docking method for ligand binding mode prediction of a drug target is also presented. A web server that implements the method is freely available at http://galaxy.seoklab.org/refinecomplex.

Binding Site Prediction of Proteins with Organic Compounds or Peptides Using GALAXY Web Servers.

We introduce two GALAXY web servers called GalaxySite and GalaxyPepDock that predict protein complex structures with small organic compounds and peptides, respectively. GalaxySite predicts ligands that may bind the input protein and generates complex structures of the protein with the predicted ligands from the protein structure given as input or predicted from the input sequence. GalaxyPepDock takes a protein structure and a peptide sequence as input and predicts structures for the protein-peptide complex. Both GalaxySite and GalaxyPepDock rely on available experimentally resolved structures of protein-ligand complexes evolutionarily related to the target. With the continuously increasing size of the protein structure database, the probability of finding related proteins in the database is increasing. The servers further relax the complex structures to refine the structural aspects that are missing in the available structures or that are not compatible with the given protein by optimizing physicochemical interactions. GalaxyPepDock allows conformational change of the protein receptor induced by peptide binding. The atomistic interactions with ligands predicted by the GALAXY servers may offer important clues for designing new molecules or proteins with desired binding properties.