On and off controls within dynein-dynactin on native cargoes.

The dynein-dynactin nanomachine transports cargoes along microtubules in cells. Why dynactin interacts separately with the dynein motor and also with microtubules is hotly debated. Here we disrupted these interactions in a targeted manner on phagosomes extracted from cells, followed by optical trapping to interrogate native dynein-dynactin teams on single phagosomes. Perturbing the dynactin-dynein interaction reduced dynein's on rate to microtubules. In contrast, perturbing the dynactin-microtubule interaction increased dynein's off rate markedly when dynein was generating force against the optical trap. The dynactin-microtubule link is therefore required for persistence against load, a finding of importance because disease-relevant mutations in dynein-dynactin are known to interfere with "high-load" functions of dynein in cells. Our findings call attention to a less studied property of dynein-dynactin, namely, its detachment against load, in understanding dynein dysfunction.

Identification of sequence determinants for the ABHD14 enzymes.

Over the course of evolution, enzymes have developed remarkable functional diversity in catalyzing important chemical reactions across various organisms, and understanding how new enzyme functions might have evolved remains an important question in modern enzymology. To systematically annotate functions, based on their protein sequences and available biochemical studies, enzymes with similar catalytic mechanisms have been clustered together into an enzyme superfamily. Typically, enzymes within a superfamily have similar overall three-dimensional structures, conserved catalytic residues, but large variations in substrate recognition sites and residues to accommodate the diverse biochemical reactions that are catalyzed within the superfamily. The serine hydrolases are an excellent example of such an enzyme superfamily. Based on known enzymatic activities and protein sequences, they are split almost equally into the serine proteases and metabolic serine hydrolases. Within the metabolic serine hydrolases, there are two outlying members, ABHD14A and ABHD14B, that have high sequence similarity, but their biological functions remained cryptic till recently. While ABHD14A still lacks any functional annotation to date, we recently showed that ABHD14B functions as a lysine deacetylase in mammals. Given their high sequence similarity, automated databases often wrongly assign ABHD14A and ABHD14B as the same enzyme, and therefore, annotating functions to them in various organisms has been problematic. In this article, we present a bioinformatics study coupled with biochemical experiments, which identifies key sequence determinants for both ABHD14A and ABHD14B, and enable better classification for them. In addition, we map these enzymes on an evolutionary timescale and provide a much-wanted resource for studying these interesting enzymes in different organisms.

Protein Interaction Z Score Assessment (PIZSA): an empirical scoring scheme for evaluation of protein-protein interactions.

Our web server, PIZSA (http://cospi.iiserpune.ac.in/pizsa), assesses the likelihood of protein-protein interactions by assigning a Z Score computed from interface residue contacts. Our score takes into account the optimal number of atoms that mediate the interaction between pairs of residues and whether these contacts emanate from the main chain or side chain. We tested the score on 174 native interactions for which 100 decoys each were constructed using ZDOCK. The native structure scored better than any of the decoys in 146 cases and was able to rank within the 95th percentile in 162 cases. This easily outperforms a competing method, CIPS. We also benchmarked our scoring scheme on 15 targets from the CAPRI dataset and found that our method had results comparable to that of CIPS. Further, our method is able to analyse higher order protein complexes without the need to explicitly identify chains as receptors or ligands. The PIZSA server is easy to use and could be used to score any input three-dimensional structure and provide a residue pair-wise break up of the results. Attractively, our server offers a platform for users to upload their own potentials and could serve as an ideal testing ground for this class of scoring schemes.

Discovering Putative Protein Targets of Small Molecules: A Study of the p53 Activator Nutlin.

Small molecule drugs bind to a pocket in disease causing target proteins based on complementarity in shape and physicochemical properties. There is a likelihood that other proteins could have binding sites that are structurally similar to the target protein. Binding to these other proteins could alter their activities leading to off target effects of the drug. One such small molecule drug Nutlin binds the protein MDM2, which is upregulated in several types of cancer and is a negative regulator of the tumor suppressor protein p53. To investigate the off target effects of Nutlin, we present here a shape-based data mining effort. We extracted the binding pocket of Nutlin from the crystal structure of Nutlin bound MDM2. We next mined the protein structural database (PDB) for putative binding pockets in other human protein structures that were similar in shape to the Nutlin pocket in MDM2 using our topology-independent structural superimposition tool CLICK. We detected 49 proteins which have binding pockets that were structurally similar to the Nutlin binding site of MDM2. All of the potential complexes were evaluated using molecular mechanics and AutoDock Vina docking scores. Further, molecular dynamics simulations were carried out on four of the predicted Nutlin-protein complexes. The binding of Nutlin to one of these proteins, gamma glutamyl hydrolase, was also experimentally validated by a thermal shift assay. These findings provide a platform for identifying potential off-target effects of existing/new drugs and also opens the possibilities for repurposing drugs/ligands.

Water-Mediated Selenium Hydrogen-Bonding in Proteins: PDB Analysis and Gas-Phase Spectroscopy of Model Complexes.

High-resolution X-ray crystallography and two-dimensional NMR studies demonstrate that water-mediated conventional hydrogen-bonding interactions (N-H···N, O-H···N, etc.) bridging two or more amino acid residues contribute to the stability of proteins and protein-ligand complexes. In this work, we have investigated single water-mediated selenium hydrogen-bonding interactions (unconventional hydrogen-bonding) between amino acid residues in proteins through extensive protein data bank (PDB) analysis coupled with gas-phase spectroscopy and quantum chemical calculation of a model complex consisting of indole, dimethyl selenide, and water. Here, indole and dimethyl selenide represent the amino acid residues tryptophan and selenomethionine, respectively. The current investigation demonstrates that the most stable structure of the model complex observed in the IR spectroscopy mimics single water-mediated selenium hydrogen-bonded structural motifs present in the crystal structures of proteins. The present work establishes that water-mediated Se hydrogen-bonding interactions are ubiquitous in proteins and the number of these interactions observed in the PDB is more than that of direct Se hydrogen-bonds present there.

Topology independent comparison of RNA 3D structures using the CLICK algorithm.

RNA molecules are attractive therapeutic targets because non-coding RNA molecules have increasingly been found to play key regulatory roles in the cell. Comparing and classifying RNA 3D structures yields unique insights into RNA evolution and function. With the rapid increase in the number of atomic-resolution RNA structures, it is crucial to have effective tools to classify RNA structures and to investigate them for structural similarities at different resolutions. We previously developed the algorithm CLICK to superimpose a pair of protein 3D structures by clique matching and 3D least squares fitting. In this study, we extend and optimize the CLICK algorithm to superimpose pairs of RNA 3D structures and RNA-protein complexes, independent of the associated topologies. Benchmarking Rclick on four different datasets showed that it is either comparable to or better than other structural alignment methods in terms of the extent of structural overlaps. Rclick also recognizes conformational changes between RNA structures and produces complementary alignments to maximize the extent of detectable similarity. Applying Rclick to study Ribonuclease III protein correctly aligned the RNA binding sites of RNAse III with its substrate. Rclick can be further extended to identify ligand-binding pockets in RNA. A web server is developed at http://mspc.bii.a-star.edu.sg/minhn/rclick.html.

Unraveling the structural basis for the unusually rich association of human leukocyte antigen DQ2.5 with class-II-associated invariant chain peptides.

Human leukocyte antigen (HLA)-DQ2.5 (DQA1*05/DQB1*02) is a class-II major histocompatibility complex protein associated with both type 1 diabetes and celiac disease. One unusual feature of DQ2.5 is its high class-II-associated invariant chain peptide (CLIP) content. Moreover, HLA-DQ2.5 preferentially binds the non-canonical CLIP2 over the canonical CLIP1. To better understand the structural basis of HLA-DQ2.5's unusual CLIP association characteristics, better insight into the HLA-DQ2.5·CLIP complex structures is required. To this end, we determined the X-ray crystal structure of the HLA-DQ2.5· CLIP1 and HLA-DQ2.5·CLIP2 complexes at 2.73 and 2.20 Å, respectively. We found that HLA-DQ2.5 has an unusually large P4 pocket and a positively charged peptide-binding groove that together promote preferential binding of CLIP2 over CLIP1. An α9-α22-α24-α31-ß86-ß90 hydrogen bond network located at the bottom of the peptide-binding groove, spanning from the P1 to P4 pockets, renders the residues in this region relatively immobile. This hydrogen bond network, along with a deletion mutation at α53, may lead to HLA-DM insensitivity in HLA-DQ2.5. A molecular dynamics simulation experiment reported here and recent biochemical studies by others support this hypothesis. The diminished HLA-DM sensitivity is the likely reason for the CLIP-rich phenotype of HLA-DQ2.5.

In silico methods for design of biological therapeutics.

It has been twenty years since the first rationally designed small molecule drug was introduced into the market. Since then, we have progressed from designing small molecules to designing biotherapeutics. This class of therapeutics includes designed proteins, peptides and nucleic acids that could more effectively combat drug resistance and even act in cases where the disease is caused because of a molecular deficiency. Computational methods are crucial in this design exercise and this review discusses the various elements of designing biotherapeutic proteins and peptides. Many of the techniques discussed here, such as the deterministic and stochastic design methods, are generally used in protein design. We have devoted special attention to the design of antibodies and vaccines. In addition to the methods for designing these molecules, we have included a comprehensive list of all biotherapeutics approved for clinical use. Also included is an overview of methods that predict the binding affinity, cell penetration ability, half-life, solubility, immunogenicity and toxicity of the designed therapeutics. Biotherapeutics are only going to grow in clinical importance and are set to herald a new generation of disease management and cure.

Phosphoregulatory protein 14-3-3 facilitates SAC1 transport from the endoplasmic reticulum.

Most secretory cargo proteins in eukaryotes are synthesized in the endoplasmic reticulum and actively exported in membrane-bound vesicles that are formed by the cytosolic coat protein complex II (COPII). COPII proteins are assisted by a variety of cargo-specific adaptor proteins required for the concentration and export of secretory proteins from the endoplasmic reticulum (ER). Adaptor proteins are key regulators of cargo export, and defects in their function may result in disease phenotypes in mammals. Here we report the role of 14-3-3 proteins as a cytosolic adaptor in mediating SAC1 transport in COPII-coated vesicles. Sac1 is a phosphatidyl inositol-4 phosphate (PI4P) lipid phosphatase that undergoes serum dependent translocation between the endoplasmic reticulum and Golgi complex and controls cellular PI4P lipid levels. We developed a cell-free COPII vesicle budding reaction to examine SAC1 exit from the ER that requires COPII and at least one additional cytosolic factor, the 14-3-3 protein. Recombinant 14-3-3 protein stimulates the packaging of SAC1 into COPII vesicles and the sorting subunit of COPII, Sec24, interacts with 14-3-3. We identified a minimal sorting motif of SAC1 that is important for 14-3-3 binding and which controls SAC1 export from the ER. This LS motif is part of a 7-aa stretch, RLSNTSP, which is similar to the consensus 14-3-3 binding sequence. Homology models, based on the SAC1 structure from yeast, predict this region to be in the exposed exterior of the protein. Our data suggest a model in which the 14-3-3 protein mediates SAC1 traffic from the ER through direct interaction with a sorting signal and COPII.

Molecular Mechanism Underlying ATP-Induced Conformational Changes in the Nucleoprotein Filament of Mycobacterium smegmatis RecA.

RecA plays a central role in bacterial DNA repair, homologous recombination, and restoration of stalled replication forks by virtue of its active extended nucleoprotein filament. Binding of ATP and its subsequent recognition by the carboxamide group of a highly conserved glutamine (Gln196 in MsRecA) have been implicated in the formation of active RecA nucleoprotein filaments. Although the mechanism of ATP-dependent structural transitions in RecA has been proposed on the basis of low-resolution electron microscopic reconstructions, the precise sequence of events that constitute these transitions is poorly understood. On the basis of biochemical and crystallographic analyses of MsRecA variants carrying mutations in highly conserved Gln196 and Arg198 residues, we propose that the disposition of the interprotomer interface is the structural basis of allosteric activation of RecA. Furthermore, this study accounts for the contributions of several conserved amino acids to ATP hydrolysis and to the transition from collapsed to extended filament forms in Mycobacterium smegmatis RecA (MsRecA). In addition to their role in the inactive compressed state, the study reveals a role for Gln196 and Arg198 along with Phe219 in ATP hydrolysis in the active extended nucleoprotein filament. Finally, our data suggest that the primary, but not secondary, nucleotide binding site in MsRecA isomerizes into the ATP binding site present in the extended nucleoprotein filament.

Biophysical properties of intrinsically disordered p130Cas substrate domain--implication in mechanosensing.

Mechanical stretch-induced tyrosine phosphorylation in the proline-rich 306-residue substrate domain (CasSD) of p130Cas (or BCAR1) has eluded an experimentally validated structural understanding. Cellular p130Cas tyrosine phosphorylation is shown to function in areas without internal actomyosin contractility, sensing force at the leading edge of cell migration. Circular dichroism shows CasSD is intrinsically disordered with dominant polyproline type II conformations. Strongly conserved in placental mammals, the proline-rich sequence exhibits a pseudo-repeat unit with variation hotspots 2-9 residues before substrate tyrosine residues. Atomic-force microscopy pulling experiments show CasSD requires minimal extension force and exhibits infrequent, random regions of weak stability. Proteolysis, light scattering and ultracentrifugation results show that a monomeric intrinsically disordered form persists for CasSD in solution with an expanded hydrodynamic radius. All-atom 3D conformer sampling with the TraDES package yields ensembles in agreement with experiment when coil-biased sampling is used, matching the experimental radius of gyration. Increasing ß-sampling propensities increases the number of prolate conformers. Combining the results, we conclude that CasSD has no stable compact structure and is unlikely to efficiently autoinhibit phosphorylation. Taking into consideration the structural propensity of CasSD and the fact that it is known to bind to LIM domains, we propose a model of how CasSD and LIM domain family of transcription factor proteins may function together to regulate phosphorylation of CasSD and effect machanosensing.

Depth: a web server to compute depth, cavity sizes, detect potential small-molecule ligand-binding cavities and predict the pKa of ionizable residues in proteins.

Residue depth accurately measures burial and parameterizes local protein environment. Depth is the distance of any atom/residue to the closest bulk water. We consider the non-bulk waters to occupy cavities, whose volumes are determined using a Voronoi procedure. Our estimation of cavity sizes is statistically superior to estimates made by CASTp and VOIDOO, and on par with McVol over a data set of 40 cavities. Our calculated cavity volumes correlated best with the experimentally determined destabilization of 34 mutants from five proteins. Some of the cavities identified are capable of binding small molecule ligands. In this study, we have enhanced our depth-based predictions of binding sites by including evolutionary information. We have demonstrated that on a database (LigASite) of ∼200 proteins, we perform on par with ConCavity and better than MetaPocket 2.0. Our predictions, while less sensitive, are more specific and precise. Finally, we use depth (and other features) to predict pKas of GLU, ASP, LYS and HIS residues. Our results produce an average error of just <1 pH unit over 60 predictions. Our simple empirical method is statistically on par with two and superior to three other methods while inferior to only one. The DEPTH server (http://mspc.bii.a-star.edu.sg/depth/) is an ideal tool for rapid yet accurate structural analyses of protein structures.

High-affinity biomolecular interactions are modulated by low-affinity binders.

The strength of molecular interactions is characterized by their dissociation constants (KD). Only high-affinity interactions (KD ≤ 10-8 M) are extensively investigated and support binary on/off switches. However, such analyses have discounted the presence of low-affinity binders (KD > 10-5 M) in the cellular environment. We assess the potential influence of low-affinity binders on high-affinity interactions. By employing Gillespie stochastic simulations and continuous methods, we demonstrate that the presence of low-affinity binders can alter the kinetics and the steady state of high-affinity interactions. We refer to this effect as 'herd regulation' and have evaluated its possible impact in two different contexts including sex determination in Drosophila melanogaster and in signalling systems that employ molecular thresholds. We have also suggested experiments to validate herd regulation in vitro. We speculate that low-affinity binders are prevalent in biological contexts where the outcomes depend on molecular thresholds impacting homoeostatic regulation.

SALIGN: a web server for alignment of multiple protein sequences and structures.

SUMMARY: Accurate alignment of protein sequences and/or structures is crucial for many biological analyses, including functional annotation of proteins, classifying protein sequences into families, and comparative protein structure modeling. Described here is a web interface to SALIGN, the versatile protein multiple sequence/structure alignment module of MODELLER. The web server automatically determines the best alignment procedure based on the inputs, while allowing the user to override default parameter values. Multiple alignments are guided by a dendrogram computed from a matrix of all pairwise alignment scores. When aligning sequences to structures, SALIGN uses structural environment information to place gaps optimally. If two multiple sequence alignments of related proteins are input to the server, a profile-profile alignment is performed. All features of the server have been previously optimized for accuracy, especially in the contexts of comparative modeling and identification of interacting protein partners. AVAILABILITY: The SALIGN web server is freely accessible to the academic community at http://salilab.org/salign. SALIGN is a module of the MODELLER software, also freely available to academic users (http://salilab.org/modeller). CONTACT: sali@salilab.org; madhusudhan@bii.a-star.edu.sg.

Biological insights from topology independent comparison of protein 3D structures.

Comparing and classifying the three-dimensional (3D) structures of proteins is of crucial importance to molecular biology, from helping to determine the function of a protein to determining its evolutionary relationships. Traditionally, 3D structures are classified into groups of families that closely resemble the grouping according to their primary sequence. However, significant structural similarities exist at multiple levels between proteins that belong to these different structural families. In this study, we propose a new algorithm, CLICK, to capture such similarities. The method optimally superimposes a pair of protein structures independent of topology. Amino acid residues are represented by the Cartesian coordinates of a representative point (usually the C(α) atom), side chain solvent accessibility, and secondary structure. Structural comparison is effected by matching cliques of points. CLICK was extensively benchmarked for alignment accuracy on four different sets: (i) 9537 pair-wise alignments between two structures with the same topology; (ii) 64 alignments from set (i) that were considered to constitute difficult alignment cases; (iii) 199 pair-wise alignments between proteins with similar structure but different topology; and (iv) 1275 pair-wise alignments of RNA structures. The accuracy of CLICK alignments was measured by the average structure overlap score and compared with other alignment methods, including HOMSTRAD, MUSTANG, Geometric Hashing, SALIGN, DALI, GANGSTA(+), FATCAT, ARTS and SARA. On average, CLICK produces pair-wise alignments that are either comparable or statistically significantly more accurate than all of these other methods. We have used CLICK to uncover relationships between (previously) unrelated proteins. These new biological insights include: (i) detecting hinge regions in proteins where domain or sub-domains show flexibility; (ii) discovering similar small molecule binding sites from proteins of different folds and (iii) discovering topological variants of known structural/sequence motifs. Our method can generally be applied to compare any pair of molecular structures represented in Cartesian coordinates as exemplified by the RNA structure superimposition benchmark.

CLICK--topology-independent comparison of biomolecular 3D structures.

Our server, CLICK: http://mspc.bii.a-star.edu.sg/click, is capable of superimposing the 3D structures of any pair of biomolecules (proteins, DNA, RNA, etc.). The server makes use of the Cartesian coordinates of the molecules with the option of using other structural features such as secondary structure, solvent accessible surface area and residue depth to guide the alignment. CLICK first looks for cliques of points (3-7 residues) that are structurally similar in the pair of structures to be aligned. Using these local similarities, a one-to-one equivalence is charted between the residues of the two structures. A least square fit then superimposes the two structures. Our method is especially powerful in establishing protein relationships by detecting similarities in structural subdomains, domains and topological variants. CLICK has been extensively benchmarked and compared with other popular methods for protein and RNA structural alignments. In most cases, CLICK alignments were statistically significantly better in terms of structure overlap. The method also recognizes conformational changes that may have occurred in structural domains or subdomains in one structure with respect to the other. For this purpose, the server produces complementary alignments to maximize the extent of detectable similarity. Various examples showcase the utility of our web server.

DEPTH: a web server to compute depth and predict small-molecule binding cavities in proteins.

Depth measures the extent of atom/residue burial within a protein. It correlates with properties such as protein stability, hydrogen exchange rate, protein-protein interaction hot spots, post-translational modification sites and sequence variability. Our server, DEPTH, accurately computes depth and solvent-accessible surface area (SASA) values. We show that depth can be used to predict small molecule ligand binding cavities in proteins. Often, some of the residues lining a ligand binding cavity are both deep and solvent exposed. Using the depth-SASA pair values for a residue, its likelihood to form part of a small molecule binding cavity is estimated. The parameters of the method were calibrated over a training set of 900 high-resolution X-ray crystal structures of single-domain proteins bound to small molecules (molecular weight <1.5 KDa). The prediction accuracy of DEPTH is comparable to that of other geometry-based prediction methods including LIGSITE, SURFNET and Pocket-Finder (all with Matthew's correlation coefficient of ∼0.4) over a testing set of 225 single and multi-chain protein structures. Users have the option of tuning several parameters to detect cavities of different sizes, for example, geometrically flat binding sites. The input to the server is a protein 3D structure in PDB format. The users have the option of tuning the values of four parameters associated with the computation of residue depth and the prediction of binding cavities. The computed depths, SASA and binding cavity predictions are displayed in 2D plots and mapped onto 3D representations of the protein structure using Jmol. Links are provided to download the outputs. Our server is useful for all structural analysis based on residue depth and SASA, such as guiding site-directed mutagenesis experiments and small molecule docking exercises, in the context of protein functional annotation and drug discovery.

Structure-guided fragment-based in silico drug design of dengue protease inhibitors.

An in silico fragment-based drug design approach was devised and applied towards the identification of small molecule inhibitors of the dengue virus (DENV) NS2B-NS3 protease. Currently, no DENV protease co-crystal structure with bound inhibitor and fully formed substrate binding site is available. Therefore a homology model of DENV NS2B-NS3 protease was generated employing a multiple template spatial restraints method and used for structure-based design. A library of molecular fragments was derived from the ZINC screening database with help of the retrosynthetic combinatorial analysis procedure (RECAP). 150,000 molecular fragments were docked to the DENV protease homology model and the docking poses were rescored using a target-specific scoring function. High scoring fragments were assembled to small molecule candidates by an implicit linking cascade. The cascade included substructure searching and structural filters focusing on interactions with the S1 and S2 pockets of the protease. The chemical space adjacent to the promising candidates was further explored by neighborhood searching. A total of 23 compounds were tested experimentally and two compounds were discovered to inhibit dengue protease (IC(50) = 7.7 µM and 37.9 µM, respectively) and the related West Nile virus protease (IC(50) = 6.3 µM and 39.0 µM, respectively). This study demonstrates the successful application of a structure-guided fragment-based in silico drug design approach for dengue protease inhibitors providing straightforward hit generation using a combination of homology modeling, fragment docking, chemical similarity and structural filters.

Peptide bond planarity constrains hydrogen bond geometry and influences secondary structure conformations.

An extensive database study of hydrogen bonds in different protein environments showed systematic variations in donor-acceptor-acceptor antecedent angle (H) and donor-acceptor distance. Protein environments were characterized by depth (distance of amino acids from bulk solvent), secondary structure, and whether the donor/acceptor belongs to the main chain (MC) or side chain (SC) of amino acids. The MC-MC hydrogen bonds (whether in secondary structures or not) have H angles tightly restricted to a value of around 155°, which was distinctly different from other H angles. Quantum chemical calculations attribute this characteristic MC-MC H angle to the nature of the electron density distribution around the planar peptide bond. Additional classical simulations suggest a causal link between MC-MC H angle and the conformation of secondary structures in proteins. We also showed that donor-acceptor distances are environment dependent, which has implications on protein stability. Our results redefine hydrogen bond geometries in proteins and suggest useful refinements to existing molecular mechanics force fields.

Methods for Molecular Modelling of Protein Complexes.

Biological processes are often mediated by complexes formed between proteins and various biomolecules. The 3D structures of such protein-biomolecule complexes provide insights into the molecular mechanism of their action. The structure of these complexes can be predicted by various computational methods. Choosing an appropriate method for modelling depends on the category of biomolecule that a protein interacts with and the availability of structural information about the protein and its interacting partner. We intend for the contents of this chapter to serve as a guide as to what software would be the most appropriate for the type of data at hand and the kind of 3D complex structure required. Particularly, we have dealt with protein-small molecule ligand, protein-peptide, protein-protein, and protein-nucleic acid interactions.Most, if not all, model building protocols perform some sampling and scoring. Typically, several alternate conformations and configurations of the interactors are sampled. Each such sample is then scored for optimization. To boost the confidence in these predicted models, their assessment using other independent scoring schemes besides the inbuilt/default ones would prove to be helpful. This chapter also lists such software and serves as a guide to gauge the fidelity of modelled structures of biomolecular complexes.