Interaction signatures stabilizing the NAD(P)-binding Rossmann fold: a structure network approach

PASS2.7: a database containing structure-based sequence alignments and associated features of protein domain superfamilies from SCOPe

Sequence alignments are models that capture the structural, functional and evolutionary relationships between proteins. Structure-guided sequence alignments are helpful in the case of distantly related proteins with poor sequence identity, thus rendering routine sequence alignment methods ineffective. Protein Alignment organized as Structural Superfamilies or PASS2 database provides such sequence alignments of protein domains within a superfamily as per the Structural Classification of Proteins extended (SCOPe) database. The current update of PASS2 (i.e. PASS2.7) is following the latest release of SCOPe (2.07) and we provide data for 14 323 protein domains that are <40% identical and are organized into 2024 superfamilies. Several useful features derived from the alignments, such as conserved secondary structural motifs, HMMs and residues conserved across the superfamily, are also reported. Protein domains that are deviant from the rest of the members of a superfamily may compromise the quality of the alignment, and we found this to be the case in ∼7% of the total superfamilies we considered. To improve the alignment by objectively identifying such ‘outliers’, in this update, we have used a k-means-based unsupervised machine learning method for clustering superfamily members, where features provided were length of domains aligned, Cα-RMSD derived from the rigid-body superposition of all members and gaps contributed to the alignment by each domain. In a few cases, we have split the superfamily as per the clusters predicted and provided complete data for each cluster. A new feature included in this update is absolutely conserved interactions (ACIs) between residue backbones and side chains, which are obtained by aligning protein structure networks using structure-guided sequence alignments of superfamilies. ACIs provide valuable information about functionally important residues and the structure–function relationships of proteins. The ACIs and the corresponding conserved networks for backbone and sidechain have been marked on the superimposed structure separately.

Database URL

The updated version of the PASS2 database is available at http://caps.ncbs.res.in/pass2/.

Identification and Functional Analysis of Two Alcohol Dehydrogenase Genes Involved in Catalyzing the Reduction of (Z)-3-Hexenal into (Z)-3-Hexenol in Tea Plants (Camellia sinensis)

Alcohol dehydrogenase (ADH) is a vital enzyme in the biosynthesis pathway of six-carbon volatiles in plants. However, little is known about its functions in tea plants. Here, we identified two ADH genes (CsADH1 and CsADH2). An in vitro protein expression assay showed that both CsADH1 and CsADH2 proteins can catalyze the reduction of (Z)-3-hexenal into (Z)-3-hexenol. Subcellular localization revealed that both CsADH1 and CsADH2 proteins were predominantly localized in the nucleus and cytosol. CsADH1 had high transcripts in young stems in autumn, while CsADH2 showed extremely high expression levels in stems and roots. The expression of CsADH2 was mainly downregulated under ABA treatment, while CsADH1 and CsADH2 transcripts were significantly lower under MeJA treatment at 12 and 24 h. Under cold treatment, CsADH1 transcripts first decreased and then increased, while CsADH2 demonstrated an almost opposite expression pattern. Notably, CsADH2 was significantly upregulated under simulated Ectropis obliqua invasion. Gene suppression by antisense oligonucleotides (AsODNs) demonstrated that AsODN_ADH2 treatment significantly reduced CsADH2 transcripts and the abundance of (Z)-3-hexenol products. The results indicate that the two CsADH genes may play an important role in response to (a)biotic stresses and in the process of (Z)-3-hexenol biosynthesis.

NAPS update: network analysis of molecular dynamics data and protein-nucleic acid complexes

Network theory is now a method of choice to gain insights in understanding protein structure, folding and function. In combination with molecular dynamics (MD) simulations, it is an invaluable tool with widespread applications such as analyzing subtle conformational changes and flexibility regions in proteins, dynamic correlation analysis across distant regions for allosteric communications, in drug design to reveal alternative binding pockets for drugs, etc. Updated version of NAPS now facilitates network analysis of the complete repertoire of these biomolecules, i.e., proteins, protein–protein/nucleic acid complexes, MD trajectories, and RNA. Various options provided for analysis of MD trajectories include individual network construction and analysis of intermediate time-steps, comparative analysis of these networks, construction and analysis of average network of the ensemble of trajectories and dynamic cross-correlations. For protein–nucleic acid complexes, networks of the whole complex as well as that of the interface can be constructed and analyzed. For analysis of proteins, protein–protein complexes and MD trajectories, network construction based on inter-residue interaction energies with realistic edge-weights obtained from standard force fields is provided to capture the atomistic details. Updated version of NAPS also provides improved visualization features, interactive plots and bulk execution. URL: http://bioinf.iiit.ac.in/NAPS/

Spectral analysis of molecular dynamics simulations on PDZ: MD sectors

The idea of protein "sectors" posits that sparse subsets of amino acid residues form cooperative networks that are key elements of protein stability, ligand binding, and allosterism. To date, protein sectors have been calculated by the statistical coupling analysis (SCA) method of Ranganathan and co-workers via the spectral analysis of conservation-weighted evolutionary covariance matrices obtained from a multiple sequence alignments of homologous families of proteins. SCA sectors, a knowledge-based protocol, have been indentified with functional properties and allosterism for a number of systems. In this study, we investigate the utility of the sector idea for the analysis of physics-based molecular dynamics (MD) trajectories of proteins. Our test case for this procedure is PSD95- PDZ3, one of the smallest proteins for which allosterism has been observed. It has served previously as a model system for a number of prediction algorithms, and is well characterized by X-ray crystallography, NMR spectroscopy and site specific mutagenisis. All-atom MD simulations were performed for a total of 500 nanoseconds using AMBER, and MD-calculated covariance matrices for the fluctuations of residue displacements and non-bonded interaction energies were subjected to spectral analysis in a manner analogous to that of SCA. The composition of MD sectors was compared with results from SCA, site specific mutagenesis, and allosterism. The concordance indicates that MD sectors are a viable protocol for analyzing MD trajectories and provide insight into the physical origin of the phenomenon.Communicated by Ramaswamy H. Sarma.

Interconnecting Flexibility, Structural Communication, and Function in RhoGEF Oncoproteins

Dbl family Rho guanine nucleotide exchange factors (RhoGEFs) play a central role in cell biology by catalyzing the exchange of guanosine 5'-triphosphate for guanosine 5'-diphosphate (GDP) on RhoA. Insights into the oncogenic constitutive activity of the Lbc RhoGEF were gained by analyzing the structure and dynamics of the protein in different functional states and in comparison with a close homologue, leukemia-associated RhoGEF. Higher intrinsic flexibility, less dense and extended structure network, and less stable allosteric communication pathways in Lbc, compared to the nonconstitutively active homologue, emerged as major determinants of the constitutive activity. Independent of the state, the essential dynamics of the two RhoGEFs is contributed by the last 10 amino acids of Dbl homology (DH) and the whole pleckstrin homology (PH) domains and tends to be equalized by the presence of RhoA. The catalytic activity of the RhoGEF relies on the scaffolding action of the DH domain that primarily turns the switch I (SWI) of RhoA on itself through highly conserved amino acids participating in the stability core and essential for function. Changes in the conformation of SWI and disorganization of the RhoA regions deputed to nucleotide binding are among the major RhoGEF effects leading to GDP release. Binding of RhoA reorganizes the allosteric communication on RhoGEF, strengthening the communication among the canonical RhoA binding site on DH, a secondary RhoA binding site on PH, and the binding site for heterotrimeric G proteins, suggesting dual roles for RhoA as a catalysis substrate and as a regulatory protein. The structure network-based analysis tool employed in this study proved to be useful for predicting potentially druggable regulatory sites in protein structures.

Chimeric Structure of Plant Malic Enzyme Family: Different Evolutionary Scenarios for NAD- and NADP-Dependent Isoforms

Malic enzyme (ME) comprises a family of proteins with multiple isoforms located in different compartments of eukaryotic cells. In plants, cytosolic and plastidic enzymes share several characteristics such as NADP specificity (NADP-ME), oxaloacetate decarboxylase (OAD) activity, and homo-oligomeric assembly. However, mitochondrial counterparts are NAD-dependent proteins (mNAD-ME) lacking OAD activity, which can be structured as homo- and hetero-oligomers of two different subunits. In this study, we examined the molecular basis of these differences using multiple sequence analysis, structural modeling, and phylogenetic approaches. Plant mNAD-MEs show the lowest identity values when compared with other eukaryotic MEs with major differences including short amino acid insertions distributed throughout the primary sequence. Some residues in these exclusive segments are co-evolutionarily connected, suggesting that they could be important for enzymatic functionality. Phylogenetic analysis indicates that eukaryotes from different kingdoms used different strategies for acquiring the current set of NAD(P)-ME isoforms. In this sense, while the full gene family of vertebrates derives from the same ancestral gene, plant NADP-ME and NAD-ME isoforms have a distinct evolutionary history. Plant NADP-ME genes may have arisen from the α-protobacterial-like mitochondrial ancestor, a characteristic shared with major eukaryotic taxa. On the other hand, plant mNAD-ME genes were probably gained through an independent process involving the Archaeplastida ancestor. Finally, several residue signatures unique to all plant mNAD-MEs could be identified, some of which might be functionally connected to their exclusive biochemical properties. In light of these results, molecular evolutionary scenarios for these widely distributed enzymes in plants are discussed.

Biophysical and computational methods to analyze amino acid interaction networks in proteins

Globular proteins are held together by interacting networks of amino acid residues. A number of different structural and computational methods have been developed to interrogate these amino acid networks. In this review, we describe some of these methods, including analyses of X-ray crystallographic data and structures, computer simulations, NMR data, and covariation among protein sequences, and indicate the critical insights that such methods provide into protein function. This information can be leveraged towards the design of new allosteric drugs, and the engineering of new protein function and protein regulation strategies.

Structure network analysis to gain insights into GPCR function

G protein coupled receptors (GPCRs) are allosteric proteins whose functioning fundamentals are the communication between the two poles of the helix bundle. Protein structure network (PSN) analysis is one of the graph theory-based approaches currently used to investigate the structural communication in biomolecular systems. Information on system's dynamics can be provided by atomistic molecular dynamics (MD) simulations or coarse grained elastic network models paired with normal mode analysis (ENM–NMA). The present review article describes the application of PSN analysis to uncover the structural communication in G protein coupled receptors (GPCRs). Strategies to highlight changes in structural communication upon misfolding, dimerization and activation are described. Focus is put on the ENM–NMA-based strategy applied to the crystallographic structures of rhodopsin in its inactive (dark) and signalling active (meta II (MII)) states, highlighting changes in structure network and centrality of the retinal chromophore in differentiating the inactive and active states of the receptor.

The Unfolding MD Simulations of Cyclophilin: Analyzed by Surface Contact Networks and Their Associated Metrics

Currently, considerable interest exists with regard to the dissociation of close packed aminoacids within proteins, in the course of unfolding, which could result in either wet or dry moltenglobules. The progressive disjuncture of residues constituting the hydrophobic core ofcyclophilin from L. donovani (LdCyp) has been studied during the thermal unfolding of the molecule, by molecular dynamics simulations. LdCyp has been represented as a surface contactnetwork (SCN) based on the surface complementarity (Sm) of interacting residues within themolecular interior. The application of Sm to side chain packing within proteins make it a very sensitive indicator of subtle perturbations in packing, in the thermal unfolding of the protein. Network based metrics have been defined to track the sequential changes in the disintegration ofthe SCN spanning the hydrophobic core of LdCyp and these metrics prove to be highly sensitive compared to traditional metrics in indicating the increased conformational (and dynamical) flexibility in the network. These metrics have been applied to suggest criteria distinguishing DMG, WMG and transition state ensembles and to identify key residues involved in crucial conformational/topological events during the unfolding process.

Catching Functional Modes and Structural Communication in Dbl Family Rho Guanine Nucleotide Exchange Factors

Computational approaches such as Principal Component Analysis (PCA) and Elastic Network Model-Normal Mode Analysis (ENM-NMA) are proving to be of great value in investigating relevant biological problems linked to slow motions with no demand in computer power. In this study, these approaches have been coupled to the graph theory-based Protein Structure Network (PSN) analysis to dissect functional dynamics and structural communication in the Dbl family of Rho Guanine Nucleotide Exchange Factors (RhoGEFs). They are multidomain proteins whose common structural feature is a DH-PH tandem domain deputed to the GEF activity that makes them play a central role in cell and cancer biology. While their common GEF action is accomplished by the DH domain, their regulatory mechanisms are highly variegate and depend on the PH and the additional domains as well as on interacting proteins. Major evolutionary-driven deformations as inferred from PCA concern the α6 helix of DH that dictates the orientation of the PH domain. Such deformations seem to depend on the mechanisms adopted by the GEF to prevent Rho binding, i.e. functional specialization linked to autoinhibition. In line with PCA, ENM-NMA indicates α6 and the linked PH domain as the portions of the tandem domain holding almost the totality of intrinsic and functional dynamics, with the α6/β1 junction acting as a hinge point for the collective motions of PH. In contrast, the DH domain holds a static scaffolding and hub behavior, with structural communication playing a central role in the regulatory actions by other domains/proteins. Possible allosteric communication pathways involving essentially DH were indeed found in those RhoGEFs acting as effectors of small or heterotrimeric RasGTPases. The employed methodology is suitable for deciphering structure/dynamics relationships in large sets of homologous or analogous proteins.

An automated approach to network features of protein structure ensembles

Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of β2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html.

Comparison of leaf proteomes of cassava (Manihot esculenta Crantz) cultivar NZ199 diploid and autotetraploid genotypes

Cassava polyploid breeding has drastically improved our knowledge on increasing root yield and its significant tolerance to stresses. In polyploid cassava plants, increases in DNA content highly affect cell volumes and anatomical structures. However, the mechanism of this effect is poorly understood. The purpose of the present study was to compare and validate the changes between cassava cultivar NZ199 diploid and autotetraploid at proteomic levels. The results showed that leaf proteome of cassava cultivar NZ199 diploid was clearly differentiated from its autotetraploid genotype using 2-DE combined MS technique. Sixty-five differential protein spots were seen in 2-DE image of autotetraploid genotype in comparison with that of diploid. Fifty-two proteins were identified by MALDI-TOF-MS/MS, of which 47 were up-regulated and 5 were down-regulated in autotetraploid genotype compared with diploid genotype. The classified functions of 32 up-regulated proteins were associated with photosynthesis, defense system, hydrocyanic acid (HCN) metabolism, protein biosynthesis, chaperones, amino acid metabolism and signal transduction. The remarkable variation in photosynthetic activity, HCN content and resistance to salt stress between diploid and autotetraploid genotypes is closely linked with expression levels of proteomic profiles. The analysis of protein interaction networks indicated there are direct interactions between the 15 up-regulation proteins involved in the pathways described above. This work provides an insight into understanding the protein regulation mechanism of cassava polyploid genotype, and gives a clue to improve cassava polyploidy breeding in increasing photosynthesis and resistance efficiencies.