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.

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.

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.

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.

Observation of an Unusually Large IR Red-Shift in an Unconventional S-H···S Hydrogen-Bond.

The S-H···S non-covalent interaction is generally known as an extremely unconventional weak hydrogen-bond in the literature. The present gas-phase spectroscopic investigation shows that the S-H···S hydrogen-bond can be as strong as any conventional hydrogen-bond in terms of the IR red-shift in the stretching frequency of the hydrogen-bond donor group. Herein, the strength of the S-H···S hydrogen-bond has been determined by measuring the red-shift (∼150 cm-1) of the S-H stretching frequency in a model complex of 2-chlorothiophenol and dimethyl sulfide using isolated gas-phase IR spectroscopy coupled with quantum chemistry calculations. The observation of an unusually large IR red-shift in the S-H···S hydrogen-bond is explained in terms of the presence of a significant amount of charge-transfer interactions in addition to the usual electrostatic interactions. The existence of ∼750 S-H···S interactions between the cysteine and methionine residues in 642 protein structures determined from an extensive Protein Data Bank analysis also indicates that this interaction is important for the structures of proteins.

Predicting and designing therapeutics against the Nipah virus.

Despite Nipah virus outbreaks having high mortality rates (>70% in Southeast Asia), there are no licensed drugs against it. In this study, we have considered all 9 Nipah proteins as potential therapeutic targets and computationally identified 4 putative peptide inhibitors (against G, F and M proteins) and 146 small molecule inhibitors (against F, G, M, N, and P proteins). The computations include extensive homology/ab initio modeling, peptide design and small molecule docking. An important contribution of this study is the increased structural characterization of Nipah proteins by approximately 90% of what is deposited in the PDB. In addition, we have carried out molecular dynamics simulations on all the designed protein-peptide complexes and on 13 of the top shortlisted small molecule ligands to check for stability and to estimate binding strengths. Details, including atomic coordinates of all the proteins and their ligand bound complexes, can be accessed at http://cospi.iiserpune.ac.in/Nipah. Our strategy was to tackle the development of therapeutics on a proteome wide scale and the lead compounds identified could be attractive starting points for drug development. To counter the threat of drug resistance, we have analysed the sequences of the viral strains from different outbreaks, to check whether they would be sensitive to the binding of the proposed inhibitors.

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.

Structural insights of a cellobiose dehydrogenase enzyme from the basidiomycetes fungus Termitomyces clypeatus.

Filamentous fungi secrete various oxidative enzymes to degrade the glycosidic bonds of polysaccharides. Cellobiose dehydrogenase (CDH) (E.C.1.1.99.18) is one of the important lignocellulose degrading enzymes produced by various filamentous fungi. It contains two stereo specific ligand binding domains, cytochrome and dehydrogenase - one for heme and the other for flavin adenine dinucleotide (FAD) respectively. The enzyme is of commercial importance for its use in amperometric biosensor, biofuel production, lactose determination in food, bioremediation etc. Termitomyces clypeatus, an edible fungus belonging to the basidiomycetes group, is a good producer of CDH. In this paper we have analyzed the structural properties of this enzyme from T. clypeatus and identified a distinct carbohydrate binding module (CBM) which is not present in most fungi belonging to the basidiomycetes group. In addition, the dehydrogenase domain of T. clypeatus CDH exhibited the absence of cellulose binding residues which is in contrast to the dehydrogenase domains of CDH of other basidiomycetes. Sequence analysis of cytochrome domain showed that the important residues of this domain were conserved like in other fungal CDHs. Phylogenetic tree, constructed using basidiomycetes and ascomycetes CDH sequences, has shown that very surprisingly the CDH from T. clypeatus, which is classified as a basidiomycetes fungus, is clustered with the ascomycetes group. A homology model of this protein has been constructed using the CDH enzyme of ascomycetes fungus Myricoccum thermophilum as a template since it has been found to be the best match sequence with T. clypeatus CDH. We also have modelled the protein with its substrate, cellobiose, which has helped us to identify the substrate interacting residues (L354, P606, T629, R631, Y649, N732, H733 and N781) localized within its dehydrogenase domain. Our computational investigation revealed for the first time the presence of all three domains - cytochrome, dehydrogenase and CBM - in the CDH of T. clypeatus, a basidiomycetes fungus. In addition to discovering the unique structural attributes of this enzyme from T. clypeatus, our study also discusses the possible phylogenetic status of this fungus.

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.

EZH2 promotes neoplastic transformation through VAV interaction-dependent extranuclear mechanisms.

Recently, we reported that the histone methyltransferase, EZH2, controls leukocyte migration through interaction with the cytoskeleton remodeling effector, VAV, and direct methylation of the cytoskeletal regulatory protein, Talin. However, it is unclear whether this extranuclear, epigenetic-independent function of EZH2 has a profound impact on the initiation of cellular transformation and metastasis. Here, we show that EZH2 increases Talin1 methylation and cleavage, thereby enhancing adhesion turnover and promoting accelerated tumorigenesis. This transforming capacity is abolished by targeted disruption of EZH2 interaction with VAV. Furthermore, our studies demonstrate that EZH2 in the cytoplasm is closely associated with cancer stem cell properties, and that overexpression of EZH2, a mutant EZH2 lacking its nuclear localization signal (EZH2ΔNLS), or a methyl-mimicking Talin1 mutant substantially promotes JAK2-dependent STAT3 activation and cellular transformation. Taken together, our results suggest a critical role for the VAV interaction-dependent, extranuclear action of EZH2 in neoplastic transformation.

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.

Computational modeling of protein assemblies.

Computational methods to predict the 3D structures of protein interactions fall into 3 categories-template based modeling, protein-protein docking and hybrid/integrative modeling. The two most important considerations for modeling methods are sampling and scoring conformations. Sampling has benefitted from techniques such as fast Fourier transforms (FFT), spherical harmonics and higher order manifolds. Scoring complexes to determine binding free energy is still a challenging problem. Rapid advances have been made in hybrid modeling where experimental data are amalgamated with computations. These methods have received a boost from the popularity of experimental methods such as electron microscopy (EM). While increasingly larger and complicated complexes are now getting elucidated by integrative methods, modeling conformational flexibility remains a challenge. Ongoing improvements to these techniques portend a future where organelles or even cells could be accurately modeled at a molecular level.

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.

Depth dependent amino acid substitution matrices and their use in predicting deleterious mutations.

The 20 naturally occurring amino acids have different environmental preferences of where they are likely to occur in protein structures. Environments in a protein can be classified by their proximity to solvent by the residue depth measure. Since the frequencies of amino acids are different at various depth levels, the substitution frequencies should vary according to depth. To quantify these substitution frequencies, we built depth dependent substitution matrices. The dataset used for creation of the matrices consisted of 3696 high quality, non redundant pairwise protein structural alignments. One of the applications of these matrices is to predict the tolerance of mutations in different protein environments. Using these substitution scores the prediction of deleterious mutations was done on 3500 mutations in T4 lysozyme and CcdB. The accuracy of the technique in terms of the Matthews Correlation Coefficient (MCC) is 0.48 on the CcdB testing set, while the best of the other tested methods has an MCC of 0.40. Further developments in these substitution matrices could help in improving structure-sequence alignment for protein 3D structure modeling.

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.

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.

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.

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.