Combining interface core and whole interface descriptors in postscan processing of protein-protein docking models

Conformation-Specific Inhibitory Anti-MMP-7 Monoclonal Antibody Sensitizes Pancreatic Ductal Adenocarcinoma Cells to Chemotherapeutic Cell Kill

Matrix metalloproteases (MMPs) undergo post-translational modifications including pro-domain shedding. The activated forms of these enzymes are effective drug targets, but generating potent biological inhibitors against them remains challenging. We report the generation of anti-MMP-7 inhibitory monoclonal antibody (GSM-192), using an alternating immunization strategy with an active site mimicry antigen and the activated enzyme. Our protocol yielded highly selective anti-MMP-7 monoclonal antibody, which specifically inhibits MMP-7's enzyme activity with high affinity (IC₅₀ = 132 ± 10 nM). The atomic model of the MMP-7-GSM-192 Fab complex exhibited antibody binding to unique epitopes at the rim of the enzyme active site, sterically preventing entry of substrates into the catalytic cleft. In human PDAC biopsies, tissue staining with GSM-192 showed characteristic spatial distribution of activated MMP-7. Treatment with GSM-192 in vitro induced apoptosis via stabilization of cell surface Fas ligand and retarded cell migration. Co-treatment with GSM-192 and chemotherapeutics, gemcitabine and oxaliplatin elicited a synergistic effect. Our data illustrate the advantage of precisely targeting catalytic MMP-7 mediated disease specific activity.

Determination of an effective scoring function for RNA-RNA interactions with a physics-based double-iterative method

RNA–RNA interactions play fundamental roles in gene and cell regulation. Therefore, accurate prediction of RNA–RNA interactions is critical to determine their complex structures and understand the molecular mechanism of the interactions. Here, we have developed a physics-based double-iterative strategy to determine the effective potentials for RNA–RNA interactions based on a training set of 97 diverse RNA–RNA complexes. The double-iterative strategy circumvented the reference state problem in knowledge-based scoring functions by updating the potentials through iteration and also overcame the decoy-dependent limitation in previous iterative methods by constructing the decoys iteratively. The derived scoring function, which is referred to as DITScoreRR, was evaluated on an RNA–RNA docking benchmark of 60 test cases and compared with three other scoring functions. It was shown that for bound docking, our scoring function DITScoreRR obtained the excellent success rates of 90% and 98.3% in binding mode predictions when the top 1 and 10 predictions were considered, compared to 63.3% and 71.7% for van der Waals interactions, 45.0% and 65.0% for ITScorePP, and 11.7% and 26.7% for ZDOCK 2.1, respectively. For unbound docking, DITScoreRR achieved the good success rates of 53.3% and 71.7% in binding mode predictions when the top 1 and 10 predictions were considered, compared to 13.3% and 28.3% for van der Waals interactions, 11.7% and 26.7% for our ITScorePP, and 3.3% and 6.7% for ZDOCK 2.1, respectively. DITScoreRR also performed significantly better in ranking decoys and obtained significantly higher score-RMSD correlations than the other three scoring functions. DITScoreRR will be of great value for the prediction and design of RNA structures and RNA–RNA complexes.

Great interactions: How binding incorrect partners can teach us about protein recognition and function

Protein–protein interactions play a key part in most biological processes and understanding their mechanism is a fundamental problem leading to numerous practical applications. The prediction of protein binding sites in particular is of paramount importance since proteins now represent a major class of therapeutic targets. Amongst others methods, docking simulations between two proteins known to interact can be a useful tool for the prediction of likely binding patches on a protein surface. From the analysis of the protein interfaces generated by a massive cross‐docking experiment using the 168 proteins of the Docking Benchmark 2.0, where all possible protein pairs, and not only experimental ones, have been docked together, we show that it is also possible to predict a protein's binding residues without having any prior knowledge regarding its potential interaction partners. Evaluating the performance of cross‐docking predictions using the area under the specificity‐sensitivity ROC curve (AUC) leads to an AUC value of 0.77 for the complete benchmark (compared to the 0.5 AUC value obtained for random predictions). Furthermore, a new clustering analysis performed on the binding patches that are scattered on the protein surface show that their distribution and growth will depend on the protein's functional group. Finally, in several cases, the binding‐site predictions resulting from the cross‐docking simulations will lead to the identification of an alternate interface, which corresponds to the interaction with a biomolecular partner that is not included in the original benchmark. Proteins 2016; 84:1408–1421. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Molecular Mechanisms and Kinetic Effects of FXYD1 and Phosphomimetic Mutants on Purified Human Na,K-ATPase

Phospholemman (FXYD1) is a single-transmembrane protein regulator of Na,K-ATPase, expressed strongly in heart, skeletal muscle, and brain and phosphorylated by protein kinases A and C at Ser-68 and Ser-63, respectively. Binding of FXYD1 reduces Na,K-ATPase activity, and phosphorylation at Ser-68 or Ser-63 relieves the inhibition. Despite the accumulated information on physiological effects, whole cell studies provide only limited information on molecular mechanisms. As a complementary approach, we utilized purified human Na,K-ATPase (α1β1 and α2β1) reconstituted with FXYD1 or mutants S63E, S68E, and S63E,S68E that mimic phosphorylation at Ser-63 and Ser-68. Compared with control α1β1, FXYD1 reduces Vmax and turnover rate and raises K0.5Na. The phosphomimetic mutants reverse these effects and reduce K0.5Na below control K0.5Na. Effects on α2β1 are similar but smaller. Experiments in proteoliposomes reconstituted with α1β1 show analogous effects of FXYD1 on K0.5Na, which are abolished by phosphomimetic mutants and also by increasing mole fractions of DOPS in the proteoliposomes. Stopped-flow experiments using the dye RH421 show that FXYD1 slows the conformational transition E2(2K)ATP → E1(3Na)ATP but does not affect 3NaE1P → E2P3Na. This regulatory effect is explained simply by molecular modeling, which indicates that a cytoplasmic helix (residues 60-70) docks between the αN and αP domains in the E2 conformation, but docking is weaker in E1 (also for phosphomimetic mutants). Taken together with previous work showing that FXYD1 also raises binding affinity for the Na(+)-selective site III, these results provide a rather comprehensive picture of the regulatory mechanism of FXYD1 that complements the physiological studies.

Systemic lupus erythematosus-associated neutrophil cytosolic factor 2 mutation affects the structure of NADPH oxidase complex

In a case-control association study with 3716 North Americans of Hispanic descent and 4867 North Americans of European descent, we show that the associations of rs17849502 (NCF2 His-389 → Gln) and rs13306575 (NCF2 Arg-395 → Trp) with systemic lupus erythematosus are independent. We have shown that His-389 → Gln disrupts the binding of NCF2 to the ZF domain of VAV1, resulting in decreased NADPH oxidase activity. With respect to Arg-395 → Trp, using protein docking and structure analyses, we provide a model for the involvement of this mutation in the structure and function of the NADPH oxidase complex. This model assigns a central role to Arg-395 in the structure and stability of the quaternary NCF2/NCF4/VAV1/RAC1 NADPH oxidase complex. Arg-395 stabilizes the C-terminal tail of NCF4 and the conformation of NCF2 loop 395-402, which in turn stabilize the evolutionarily conserved interactions of NCF2/NCF4 with the DH domain of VAV1 and RAC1 region 120-137. Our findings are consistent with the high levels of conservation of all of the residues involved in these interactions.

The autophagy protein Atg12 associates with antiapoptotic Bcl-2 family members to promote mitochondrial apoptosis

Autophagy and apoptosis constitute important determinants of cell fate and engage in a complex interplay in both physiological and pathological settings. The molecular basis of this crosstalk is poorly understood and relies, in part, on "dual-function" proteins that operate in both processes. Here, we identify the essential autophagy protein Atg12 as a positive mediator of mitochondrial apoptosis and show that Atg12 directly regulates the apoptotic pathway by binding and inactivating prosurvival Bcl-2 family members, including Bcl-2 and Mcl-1. The binding occurs independently of Atg5 or Atg3 and requires a unique BH3-like motif in Atg12, characterized by interaction studies and computational docking. In apoptotic cells, knockdown of Atg12 inhibited Bax activation and cytochrome c release, while ectopic expression of Atg12 antagonized the antiapoptotic activity of Mcl-1. The interaction between Atg12 and Bcl-2 family members may thus constitute an important point of convergence between autophagy and apoptosis in response to specific signals.

Lupus-associated causal mutation in neutrophil cytosolic factor 2 (NCF2) brings unique insights to the structure and function of NADPH oxidase

Systemic lupus erythematosus (SLE), the prototypic systemic autoimmune disease, is a debilitating multisystem autoimmune disorder characterized by chronic inflammation and extensive immune dysregulation in multiple organ systems, resulting in significant morbidity and mortality. Here, we present a multidisciplinary approach resulting in the identification of neutrophil cytosolic factor 2 (NCF2) as an important risk factor for SLE and the detailed characterization of its causal variant. We show that NCF2 is strongly associated with increased SLE risk in two independent populations: childhood-onset SLE and adult-onset SLE. The association between NCF2 and SLE can be attributed to a single nonsynonymous coding mutation in exon 12, the effect of which is the substitution of histidine-389 with glutamine (H389Q) in the PB1 domain of the NCF2 protein, with glutamine being the risk allele. Computational modeling suggests that the NCF2 H389Q mutation reduces the binding efficiency of NCF2 with the guanine nucleotide exchange factor Vav1. The model predicts that NCF2/H389 residue interacts with Vav1 residues E509, N510, E556, and G559 in the ZF domain of Vav1. Furthermore, replacing H389 with Q results in 1.5 kcal/mol weaker binding. To examine the effect of the NCF2 H389Q mutation on NADPH oxidase function, site-specific mutations at the 389 position in NCF2 were tested. Results show that an H389Q mutation causes a twofold decrease in reactive oxygen species production induced by the activation of the Vav-dependent Fcγ receptor-elicited NADPH oxidase activity. Our study completes the chain of evidence from genetic association to specific molecular function.

Integrating atom-based and residue-based scoring functions for protein-protein docking

Most scoring functions for protein-protein docking algorithms are either atom-based or residue-based, with the former being able to produce higher quality structures and latter more tolerant to conformational changes upon binding. Earlier, we developed the ZRANK algorithm for reranking docking predictions, with a scoring function that contained only atom-based terms. Here we combine ZRANK's atom-based potentials with five residue-based potentials published by other labs, as well as an atom-based potential IFACE that we published after ZRANK. We simultaneously optimized the weights for selected combinations of terms in the scoring function, using decoys generated with the protein-protein docking algorithm ZDOCK. We performed rigorous cross validation of the combinations using 96 test cases from a docking benchmark. Judged by the integrative success rate of making 1000 predictions per complex, addition of IFACE and the best residue-based pair potential reduced the number of cases without a correct prediction by 38 and 27% relative to ZDOCK and ZRANK, respectively. Thus combination of residue-based and atom-based potentials into a scoring function can improve performance for protein-protein docking. The resulting scoring function is called IRAD (integration of residue- and atom-based potentials for docking) and is available at http://zlab.umassmed.edu.

CAPRI targets T29-T42: proving ground for new docking procedures

The critical assessment of protein interactions (CAPRI) experiment provides a unique opportunity for unbiased assessment of docking procedures. The recent CAPRI targets T29-T42 entailed docking of bound, unbound, and modeled structures, presenting a wide range of prediction difficulty. We submitted accurate predictions for targets T40, T41, and T42, a good prediction for T32 and acceptable predictions for T29 and T34. The accuracy of our docking results generally matched the prediction difficulty; hence, docking of modeled proteins produced less accurate results. However, there were interesting exceptions: an accurate prediction was submitted for the dimer of modeled tetratricopeptide repeat (T42) and only an acceptable prediction for the bound/unbound case T29. The ensembles of docking models produced in the scans included an acceptable or better prediction for every target. We show here that our recently developed postscan reevaluation procedure, which tests propensity and solvation measures of the whole interface and the interface core, successfully distinguished these predictions from false docking models. For enzyme-inhibitor targets, we show that the distance of the interface from the enzyme's centroid ranked high native like docking models. Also, for one case we demonstrate that docking of an ensemble of conformers produced by normal modes analysis can improve the accuracy of the prediction.