FireDock: fast interaction refinement in molecular docking

Here, we present FireDock, an efficient method for the refinement and rescoring of rigid-body docking solutions. The refinement process consists of two main steps: (1) rearrangement of the interface side-chains and (2) adjustment of the relative orientation of the molecules. Our method accounts for the observation that most interface residues that are important in recognition and binding do not change their conformation significantly upon complexation. Allowing full side-chain flexibility, a common procedure in refinement methods, often causes excessive conformational changes. These changes may distort preformed structural signatures, which have been shown to be important for binding recognition. Here, we restrict side-chain movements, and thus manage to reduce the false-positive rate noticeably. In the later stages of our procedure (orientation adjustments and scoring), we smooth the atomic radii. This allows for the minor backbone and side-chain movements and increases the sensitivity of our algorithm. FireDock succeeds in ranking a near-native structure within the top 15 predictions for 83% of the 30 enzyme-inhibitor test cases, and for 78% of the 18 semiunbound antibody-antigen complexes. Our refinement procedure significantly improves the ranking of the rigid-body PatchDock algorithm for these cases. The FireDock program is fully automated. In particular, to our knowledge, FireDock's prediction results are comparable to current state-of-the-art refinement methods while its running time is significantly lower. The method is available at http://bioinfo3d.cs.tau.ac.il/FireDock/.     

Docking analysis of transient complexes: interaction of ferredoxin-NADP+ reductase with ferredoxin and flavodoxin

Ferredoxin (Fd) interacts with ferredoxin-NADP(+) reductase (FNR) to transfer two electrons to the latter, one by one, which will finally be used to reduce NADP(+) to NADPH. The formation of a transient complex between Fd and FNR is required for the electron transfer (ET), and extensive mutational and crystallographic studies have been reported to characterize such protein-protein interaction. However, some aspects of the association mechanism still remain unclear. Moreover, in spite of their structural differences, flavodoxin (Fld) can replace Fd in its function and interact with FNR to transfer electrons with only slightly lower efficiency. Although crystallographic structures for the FNR:Fd association have been reported, experimental structural data for the FNR:Fld interaction are highly elusive. We have modeled here the interactions between FNR and both of its protein partners, Fd and Fld, using surface energy analysis, computational rigid-body docking simulations, and interface side-chain refinement. The results, consistent with previous experimental data, suggest the existence of alternative binding modes in these ET proteins.     

Principles of flexible protein-protein docking

Treating flexibility in molecular docking is a major challenge in cell biology research. Here we describe the background and the principles of existing flexible protein-protein docking methods, focusing on the algorithms and their rational. We describe how protein flexibility is treated in different stages of the docking process: in the preprocessing stage, rigid and flexible parts are identified and their possible conformations are modeled. This preprocessing provides information for the subsequent docking and refinement stages. In the docking stage, an ensemble of pre-generated conformations or the identified rigid domains may be docked separately. In the refinement stage, small-scale movements of the backbone and side-chains are modeled and the binding orientation is improved by rigid-body adjustments. For clarity of presentation, we divide the different methods into categories. This should allow the reader to focus on the most suitable method for a particular docking problem.     

Apolipoprotein E-low density lipoprotein receptor binding: study of protein-protein interaction in rationally selected docked complexes

Apolipoprotein E (apoE) is an important protein involved in lipid metabolism due to its interaction with members of the low-density lipoprotein receptor (LDLR) family. To further understand the molecular basis for this receptor-binding activity, an apoE fragment containing the receptor binding region (residues 135-151) was docked onto the fifth LDLR ligand binding repeat (LR5) by computational methods. A subset of structures generated by the docking was rationally selected on the grounds of experimental data combined with modeling and was used for further analysis. The application and comparison of two different experimental structures for the apoE fragment underlines the local structural changes occurring in apoE when switching from a receptor-inactive to a receptor-active conformation. The body of interactions occurring at the interface between the two proteins is in very good agreement with the biochemical data available for both apoE and LDLR. Charged residues are involved in numerous ionic interactions and might therefore be important for the specificity of the interaction between apoE and LR5. In addition, the interface also features a tryptophan and a stacking of histidine residues, revealing that the association between the two proteins is not entirely governed by ionic interactions. In particular, the presence of histidine residues in the interface gives a structural basis for the pH-regulated release mechanism of apoE in the endosomes. The proposed molecular basis for apoE binding to LDLR could aid the design of strategies for targeting alterations in lipid transport and metabolism.     

APLP1 and APLP2, members of the APP family of proteins,behave similarly to APP in that they associate with NMDA receptors and enhance NMDA receptor surface expression

The function of amyloid precursor protein (APP) is unknown, although the discovery that it contributes to the regulation of surface expression of N‐methyl‐d ‐aspartate (NMDA) receptors has afforded new insights into its functional significance. Since APP is a member of a gene family that contains two other members, amyloid precursor‐like proteins 1 and 2 (APLP1 and APLP2), it is important to determine if the related APP proteins possess the same properties as APP with respect to their interactions with NMDA receptors. Following expression in mammalian cells, both APLP1 and APLP2 behaved similarly to APP in that they both co‐immunoprecipitated with the two major NMDA receptor subtypes, GluN1/GluN2A and GluN1/GluN2B, via interaction with the obligatory GluN1 subunit. Immunoprecipitations from detergent extracts of adult mammalian brain showed co‐immunoprecipitation of APLP1 and APLP2 with GluN2A‐ and GluN2B‐containing NMDA receptors. Furthermore, similarly to APP, APLP1 and APLP2 both enhanced GluN1/GluN2A and GluN1/GluN2B cell surface expression. Thus, all the three members of the APP gene family behave similarly in that they each contribute to the regulation of cell surface NMDA receptor homoeostasis.

     

Characterizing the interaction between the Rab6 GTPase and Mint3 via flow cytometry based FRET analysis

In extension to previously applied techniques like yeast two-hybrid and GST pull-down assays, we successfully established a FACS-based FRET analysis to investigate the interaction of the Mint3 adaptor protein and the small Rab GTPase Rab6A in living mammalian cells. A Mint3 mutant containing only the PTB domain (Mint3Δ6) is able to interact with the constitutively active form of Rab6A. Mint3Δ4, a mutant lacking part of the PTB domain was unable to interact with Rab6A in GST pull-down analysis and did not produce FRET signals, when co-expressed with active Rab6A.We demonstrate that this FACS-based FRET analysis is a suitable method for interaction studies between two proteins in living cells.     

Combination of scoring functions improves discrimination in protein-protein docking

Two structure-based potentials are used for both filtering (i.e., selecting a subset of conformations generated by rigid-body docking), and rescoring and ranking the selected conformations. ACP (atomic contact potential) is an atom-level extension of the Miyazawa-Jernigan potential parameterized on protein structures, whereas RPScore (residue pair potential score) is a residue-level potential, based on interactions in protein-protein complexes. These potentials are combined with other energy terms and applied to 13 sets of protein decoys, as well as to the results of docking 10 pairs of unbound proteins. For both potentials, the ability to discriminate between near-native and non-native docked structures is substantially improved by refining the structures and by adding a van der Waals energy term. It is observed that ACP and RPScore complement each other in a number of ways (e.g., although RPScore yields more hits than ACP, mainly as a result of its better performance for charged complexes, ACP usually ranks the near-native complexes better). As a general solution to the protein-docking problem, we have found that the best discrimination strategies combine either an RPScore filter with an ACP-based scoring function, or an ACP-based filter with an RPScore-based scoring function. Thus, ACP and RPScore capture complementary structural information, and combining them in a multistage postprocessing protocol provides substantially better discrimination than the use of the same potential for both filtering and ranking the docked conformations.     

Gene knockout of amyloid precursor protein and amyloid precursor-like protein-2 increases cellular copper levels in primary mouse cortical neurons and embryonic fibroblasts

Alzheimer's disease is characterised by the accumulation of amyloid-beta peptide, which is cleaved from the copper-binding amyloid-beta precursor protein. Recent in vivo and in vitro studies have illustrated the importance of copper in Alzheimer's disease neuropathogenesis and suggested a role for amyloid-beta precursor protein and amyloid-beta in copper homeostasis. Amyloid-beta precursor protein is a member of a multigene family, including amyloid precursor-like proteins-1 and -2. The copper-binding domain is similar among amyloid-beta precursor protein family members, suggesting an overall conservation in its function or activity. Here, we demonstrate that double knockout of amyloid-beta precursor protein and amyloid precursor-like protein-2 expression results in significant increases in copper accumulation in mouse primary cortical neurons and embryonic fibroblasts. In contrast, over-expression of amyloid-beta precursor protein in transgenic mice results in significantly reduced copper levels in primary cortical neurons. These findings provide cellular neuronal evidence for the role of amyloid-beta precursor protein in copper homeostasis and support the existing hypothesis that amyloid-beta precursor protein and amyloid precursor-like protein-2 are copper-binding proteins with functionally interchangeable roles in copper homeostasis.     

Computational detection of the binding-site hot spot at the remodeled human growth hormone-receptor interface

A hierarchical computational approach is used to identify the engineered binding-site cavity at the remodeled intermolecular interface between the mutants of human growth hormone (hGH) and the extracellular domain of its receptor (hGHbp). Multiple docking simulations are conducted with the remodeled hGH-hGHbp complex for a panel of potent benzimidazole-containing inhibitors that can restore the binding affinity of the wild-type complex, and for a set of known nonactive small molecules that contain different heterocyclic motifs. Structural clustering of ligand-bound conformations and binding free-energy calculations, using the AMBER force field and a continuum solvation model, can rapidly locate and screen numerous ligand-binding modes on the protein surface and detect the binding-site hot spot at the intermolecular interface. Structural orientation of the benzimidazole motif in the binding-site cavity closely mimics the position of the hot spot residue W104 in the crystal structure of the wild-type complex, which is recognized as an important structural requirement for restoring binding affinity. Despite numerous pockets on the protein surface of the mutant hGH-hGHbp complex, the binding-site cavity presents the energetically favorable hot spot for the benzimidazole-containing inhibitors, whereas for a set of nonactive molecules, the lowest energy ligand conformations do not necessarily bind in the engineered cavity. The results reveal a dominant role of the intermolecular van der Waals interactions in providing favorable ligand-protein energetics in the redesigned interface, in agreement with the experimental and computational alanine scanning of the hGH-hGHbp complex.     

Characterization of the interaction between Aβ 1–42 and glyceraldehyde phosphodehydrogenase

Advances in the understanding of AD pathogenesis have recently provided strong support for a modified Aβ protein cascade hypothesis, stating that several different Aβ assemblies contribute to the triggering of a complex pathological cascade leading to neurodegeneration. Both in vitro and in vivo, Aβ rapidly forms fibrils (fAβ), which are able to interact with various molecular partners, including proteins, lipids and proteoglycans. In a previous study aimed to identify some of these molecular partners of fAβ, we demonstrated that the GAPDH was specifically coprecipitated with fAβ. The aim of this study was to characterize this interaction. First, it was shown by TEM that synthetic GAPDH directly binds fAβ 1–42. Then rat synaptosomal proteins were purified and incubated with different forms of Aβ in various conditions, and the presence of GAPDH among the proteins coprecipitated with Aβ was studied by western blotting. Results showed that the interaction between GAPDH and fAβ 1–42 is nonionic, as is not impaired by increasing salt concentrations. GAPDH is coprecipitated not only by fAβ, but also by nonfibrillar forms of Aβ 1–42. The 41–42 Aβ sequence seems to be important in the interaction of GAPDH and Aβ, as more GAPDH was coprecipitated with fAβ 1–42 than with fAβ 1–40. GAPDH extracted from various subcellular fractions including mitochondria, was shown to interact with fAβ. Our data demonstrate a direct interaction between Aβ and GAPDH and support the possibility that this interaction has an important pathogenic role in AD. Copyright © 2008 European Peptide Society and John Wiley & Sons, Ltd.     

Extension of a protein docking algorithm to membranes and applications to amyloid precursor protein dimerization

Novel adjustments are introduced to the docking algorithm, DOCK/PIERR, for the purpose of predicting structures of transmembrane protein complexes. Incorporating knowledge about the membrane environment is shown to significantly improve docking accuracy. The extended version of DOCK/PIERR is shown to perform comparably to other leading docking packages. This membrane version of DOCK/PIERR is applied to the prediction of coiled‐coil homodimer structures of the transmembrane region of the C‐terminal peptide of amyloid precursor protein (C99). Results from MD simulation of the C99 homodimer in POPC bilayer and docking are compared. Docking results are found to capture key aspects of the homodimer ensemble, including the existence of three topologically distinct conformers. Furthermore, the extended version of DOCK/PIERR is successful in capturing the effects of solvation in membrane and micelle. Specifically, DOCK/PIERR reproduces essential differences in the homodimer ensembles simulated in POPC bilayer and DPC micelle, where configurational entropy and surface curvature effects bias the handedness and topology of the homodimer ensemble. Proteins 2015; 83:2170–2185. © 2015 Wiley Periodicals, Inc.     

Neuronal localization of the TNFα converting enzyme (TACE) in brain tissue and its correlation to amyloid plaques

The tumor necrosis factor (TNF)‐α converting enzyme (TACE) can cleave the cell‐surface ectodomain of the amyloid‐β precursor protein (APP), thus decreasing the generation of amyloid‐β (Aβ) by cultured non‐neuronal cells. While the amyloidogenic processing of APP in neurons is linked to the pathogenesis of Alzheimer's disease (AD), the expression of TACE in neurons has not yet been examined. Thus, we assessed TACE expression in a series of neuronal and non‐neuronal cell types by Western blots. We found that TACE was present in neurons and was only faintly detectable in lysates of astrocytes, oligodendrocytes, and microglial cells. Immunohistochemical analysis was used to determine the cellular localization of TACE in the human brain, and its expression was detected in distinct neuronal populations, including pyramidal neurons of the cerebral cortex and granular cell layer neurons in the hippocampus. Very low levels of TACE were seen in the cerebellum, with Purkinje cells at the granular‐molecular boundary staining faintly. Because TACE was localized predominantly in areas of the brain that are affected by amyloid plaques in AD, we examined its expression in a series of AD brains. We found that AD and control brains showed similar levels of TACE staining, as well as similar patterns of TACE expression. By double labeling for Aβ plaques and TACE, we found that TACE‐positive neurons often colocalized with amyloid plaques in AD brains. These observations support a neuronal role for TACE and suggest a mechanism for its involvement in AD pathogenesis as an antagonist of Aβ formation. © 2001 John Wiley & Sons, Inc. J Neurobiol 49: 40–46, 2001     

Protein–protein structure prediction by scoring molecular dynamics trajectories of putative poses

The prediction of protein–protein interactions and their structural configuration remains a largely unsolved problem. Most of the algorithms aimed at finding the native conformation of a protein complex starting from the structure of its monomers are based on searching the structure corresponding to the global minimum of a suitable scoring function. However, protein complexes are often highly flexible, with mobile side chains and transient contacts due to thermal fluctuations. Flexibility can be neglected if one aims at finding quickly the approximate structure of the native complex, but may play a role in structure refinement, and in discriminating solutions characterized by similar scores. We here benchmark the capability of some state‐of‐the‐art scoring functions (BACH‐SixthSense, PIE/PISA and Rosetta) in discriminating finite‐temperature ensembles of structures corresponding to the native state and to non‐native configurations. We produce the ensembles by running thousands of molecular dynamics simulations in explicit solvent starting from poses generated by rigid docking and optimized in vacuum. We find that while Rosetta outperformed the other two scoring functions in scoring the structures in vacuum, BACH‐SixthSense and PIE/PISA perform better in distinguishing near‐native ensembles of structures generated by molecular dynamics in explicit solvent. Proteins 2016; 84:1312–1320. © 2016 Wiley Periodicals, Inc.     

Impairments of long‐term depression induction and motor coordination precede Aβ accumulation in the cerebellum of APPswe/PS1dE9 double transgenic mice

Alzheimer's disease (AD) is a neurodegenerative disorder that represents the most common type of dementia among elderly people. Amyloid beta (Aβ) peptides in extracellular Aβ plaques, produced from the amyloid precursor protein (APP) via sequential processing by β‐ and γ‐secretases, impair hippocampal synaptic plasticity, and cause cognitive dysfunction in AD patients. Here, we report that Aβ peptides also impair another form of synaptic plasticity; cerebellar long‐term depression (LTD). In the cerebellum of commonly used AD mouse model, APPswe/PS1dE9 mice, Aβ plaques were detected from 8 months and profound accumulation of Aβ plaques was observed at 18 months of age. Biochemical analysis revealed relatively high levels of APP protein and Aβ in the cerebellum of APPswe/PS1dE9 mice. At pre‐Aβ accumulation stage, LTD induction, and motor coordination are disturbed. These results indicate that soluble Aβ oligomers disturb LTD induction and cerebellar function in AD mouse model.

     

Computational model for the IGF-II/IGF2r complex that is predictive of mutational and surface plasmon resonance data

Insulin-like growth factors (IGFs) are key regulators of cell proliferation, differentiation, and transformation, and are thus pivotal in cancer, especially breast, prostate, and colon neoplasm. Their potent mitogenic and anti-apoptotic actions depend primarily on their availability to bind to the signaling IGF cell surface receptors. One mechanism by which IGF-II availability is thought to be modulated is by binding to the nonsignaling IGF-II receptor (IGF2R). This binding is essentially mediated by domain 11 in the multidomain IGF2R extracellular region. The crystal structure of domain 11 of the human IGF-II receptor (IGF2R-d11) has identified a putative IGF-II binding site, and a nuclear magnetic resonance (NMR) solution structure for the IGF-II ligand has also been characterized. These structures have now been used to model in silico the protein-protein interaction between IGF-II and IGF2R-d11 using the program 3D-Dock. Because the IGF-II data comprise an ensemble of 20 structures, all of which satisfy the NMR constraints, the docking procedure was applied to each member of the ensemble. Only those models in which residue Ile1572 of IGF2R-d11, known to be essential for the binding of IGF-II, was at the interface were considered further. These plausible complexes were then critically assessed using an array of analysis techniques including consideration of additional mutagenesis data. One model was strongly supported by these analyses and is discussed here in detail. Furthermore, we demonstrate in vitro experimental support for this model by studying the binding of chimeras of IGF-I and IGF-II to IGF2R fragments.     

The key role of atom types, reference states, and interaction cutoff radii in the knowledge-based method: new variational approach

We present a variational method to derive knowledge-based potentials. The method is based on an optimization procedure of objective variables: atom types, reference states, and interaction cutoff radii. We suggest and apply new unsymmetrical reference states. The cutoff radii and atom types are optimized to improve docking accuracy of the corresponding potentials. The atom types are varied along an atom type tree, with 6 root and 49 top atom types, and the set of 18 optimal atom types is obtained. We demonstrate strong dependence between the choice of atom types and the docking accuracy of the potentials derived with these atom types. The averaged root-mean square deviations (RMSDs) of the ligand docked positions relative to the experimentally determined positions decrease when the elements C, N, O are split into the optimal types.     

Evolutionary conserved N-terminal region of human muscle fructose 1,6-bisphosphatase regulates its activity and the interaction with aldolase

N-terminal residues of muscle fructose 1,6-bisphosphatase (FBPase) are highly conserved among vertebrates. In this article, we present evidence that the conservation is responsible for the unique properties of the muscle FBPase isozyme: high sensitivity to AMP and Ca(2+) inhibition and the high affinity to muscle aldolase, which is a factor desensitizing muscle FBPase toward AMP and Ca(2+). The first N-terminal residue affecting the affinity of muscle FBPase to aldolase is arginine 3. On the other hand, the first residue significantly influencing the kinetics of muscle FBPase is proline 5. Truncation from 5-7 N-terminal residues of the enzyme not only decreases its affinity to aldolase but also reduces its k-(cat) and activation by Mg(2+), and desensitizes FBPase to inhibition by AMP and calcium ions. Deletion of the first 10 amino acids of muscle FBPase abolishes cooperativity of Mg(2+) activation and results in biphasic inhibition of the enzyme by AMP. Moreover, this truncation lowers affinity of muscle FBPase to aldolase about 14 times, making it resemble the liver isozyme. We suggest that the existence of highly AMP-sensitive muscle-like FBPase, activity of which is regulated by metabolite-dependent interaction with aldolase enables the precise regulation of muscle energy expenditures and might contributed to the evolutionary success of vertebrates.     

Critical analysis of the successes and failures of homology models of G protein‐coupled receptors

We present a critical assessment of the performance of our homology model refinement method for G protein‐coupled receptors (GPCRs), called LITICon that led to top ranking structures in a recent structure prediction assessment GPCRDOCK2010. GPCRs form the largest class of drug targets for which only a few crystal structures are currently available. Therefore, accurate homology models are essential for drug design in these receptors. We submitted five models each for human chemokine CXCR4 (bound to small molecule IT1t and peptide CVX15) and dopamine D3DR (bound to small molecule eticlopride) before the crystal structures were published. Our models in both CXCR4/IT1t and D3/eticlopride assessments were ranked first and second, respectively, by ligand RMSD to the crystal structures. For both receptors, we developed two types of protein models: homology models based on known GPCR crystal structures, and ab initio models based on the prediction method MembStruk. The homology‐based models compared better to the crystal structures than the ab initio models. However, a robust refinement procedure for obtaining high accuracy structures is needed. We demonstrate that optimization of the helical tilt, rotation, and translation is vital for GPCR homology model refinement. As a proof of concept, our in‐house refinement program LITiCon captured the distinct orientation of TM2 in CXCR4, which differs from that of adrenoreceptors. These findings would be critical for refining GPCR homology models in future. Proteins 2013. © 2012 Wiley Periodicals, Inc.