ConSurf: an algorithmic tool for the identification of functional regions in proteins by surface mapping of phylogenetic information

Evolution stings: the origin and diversification of scorpion toxin peptide scaffolds

The episodic nature of natural selection and the accumulation of extreme sequence divergence in venom-encoding genes over long periods of evolutionary time can obscure the signature of positive Darwinian selection. Recognition of the true biocomplexity is further hampered by the limited taxon selection, with easy to obtain or medically important species typically being the subject of intense venom research, relative to the actual taxonomical diversity in nature. This holds true for scorpions, which are one of the most ancient terrestrial venomous animal lineages. The family Buthidae that includes all the medically significant species has been intensely investigated around the globe, while almost completely ignoring the remaining non-buthid families. Australian scorpion lineages, for instance, have been completely neglected, with only a single scorpion species (Urodacus yaschenkoi) having its venom transcriptome sequenced. Hence, the lack of venom composition and toxin sequence information from an entire continent’s worth of scorpions has impeded our understanding of the molecular evolution of scorpion venom. The molecular origin, phylogenetic relationships and evolutionary histories of most scorpion toxin scaffolds remain enigmatic. In this study, we have sequenced venom gland transcriptomes of a wide taxonomical diversity of scorpions from Australia, including buthid and non-buthid representatives. Using state-of-art molecular evolutionary analyses, we show that a majority of CSα/β toxin scaffolds have experienced episodic influence of positive selection, while most non-CSα/β linear toxins evolve under the extreme influence of negative selection. For the first time, we have unraveled the molecular origin of the major scorpion toxin scaffolds, such as scorpion venom single von Willebrand factor C-domain peptides (SV-SVC), inhibitor cystine knot (ICK), disulphide-directed beta-hairpin (DDH), bradykinin potentiating peptides (BPP), linear non-disulphide bridged peptides and antimicrobial peptides (AMP). We have thus demonstrated that even neglected lineages of scorpions are a rich pool of novel biochemical components, which have evolved over millions of years to target specific ion channels in prey animals, and as a result, possess tremendous implications in therapeutics.

Molecular evolution of vertebrate neurotrophins: co-option of the highly conserved nerve growth factor gene into the advanced snake venom arsenalf

Neurotrophins are a diverse class of structurally related proteins, essential for neuronal development, survival, plasticity and regeneration. They are characterized by major family members, such as the nerve growth factors (NGF), brain-derived neurotrophic factors (BDNF) and neurotrophin-3 (NT-3), which have been demonstrated here to lack coding sequence variations and follow the regime of negative selection, highlighting their extremely important conserved role in vertebrate homeostasis. However, in stark contrast, venom NGF secreted as part of the chemical arsenal of the venomous advanced snake family Elapidae (and to a lesser extent Viperidae) have characteristics consistent with the typical accelerated molecular evolution of venom components. This includes a rapid rate of diversification under the significant influence of positive-selection, with the majority of positively-selected sites found in the secreted β-polypeptide chain (74%) and on the molecular surface of the protein (92%), while the core structural and functional residues remain highly constrained. Such focal mutagenesis generates active residues on the toxin molecular surface, which are capable of interacting with novel biological targets in prey to induce a myriad of pharmacological effects. We propose that caenophidian NGFs could participate in prey-envenoming by causing a massive release of chemical mediators from mast cells to mount inflammatory reactions and increase vascular permeability, thereby aiding the spread of other toxins and/or by acting as proapoptotic factors. Despite their presence in reptilian venom having been known for over 60 years, this is the first evidence that venom-secreted NGF follows the molecular evolutionary pattern of other venom components, and thus likely participates in prey-envenomation.

Three-fingered RAVERs: Rapid Accumulation of Variations in Exposed Residues of snake venom toxins

Three-finger toxins (3FTx) represent one of the most abundantly secreted and potently toxic components of colubrid (Colubridae), elapid (Elapidae) and psammophid (Psammophiinae subfamily of the Lamprophidae) snake venom arsenal. Despite their conserved structural similarity, they perform a diversity of biological functions. Although they are theorised to undergo adaptive evolution, the underlying diversification mechanisms remain elusive. Here, we report the molecular evolution of different 3FTx functional forms and show that positively selected point mutations have driven the rapid evolution and diversification of 3FTx. These diversification events not only correlate with the evolution of advanced venom delivery systems (VDS) in Caenophidia, but in particular the explosive diversification of the clade subsequent to the evolution of a high pressure, hollow-fanged VDS in elapids, highlighting the significant role of these toxins in the evolution of advanced snakes. We show that Type I, II and III α-neurotoxins have evolved with extreme rapidity under the influence of positive selection. We also show that novel Oxyuranus/Pseudonaja Type II forms lacking the apotypic loop-2 stabilising cysteine doublet characteristic of Type II forms are not phylogenetically basal in relation to other Type IIs as previously thought, but are the result of secondary loss of these apotypic cysteines on at least three separate occasions. Not all 3FTxs have evolved rapidly: κ-neurotoxins, which form non-covalently associated heterodimers, have experienced a relatively weaker influence of diversifying selection; while cytotoxic 3FTx, with their functional sites, dispersed over 40% of the molecular surface, have been extremely constrained by negative selection. We show that the a previous theory of 3FTx molecular evolution (termed ASSET) is evolutionarily implausible and cannot account for the considerable variation observed in very short segments of 3FTx. Instead, we propose a theory of Rapid Accumulation of Variations in Exposed Residues (RAVER) to illustrate the significance of point mutations, guided by focal mutagenesis and positive selection in the evolution and diversification of 3FTx.

Insights into the intra-ring subunit order of TRiC/CCT: a structural and evolutionary analysis

TRiC is an important group II chaperonin that facilitates the folding of many eukaryotic proteins. The TRiC complex consists of two stacked rings, each comprised of eight paralogous subunits with a mutual sequence identity of 30-35%. Each subunit has unique functional roles that are manifested by corresponding sequence conservation. It is generally assumed that the subunit order within each ring is fixed, but this order is still uncertain. Here we address the problem of the intra-ring subunit order by combining two sources of information: evolutionary conservation and a structural hypothesis. Specifically, we identify residues in the TRiC subunits that are likely to be part of the intra-unit interface, based on homology modeling to the solved thermosome structure. Within this set of residues, we search for a subset that shows an evolutionary conservation pattern that is indicative of the subunit order key. This pattern shows considerable conservation across species, but large variation across the eight subunits. By this approach we were able to locate two parts of the interface where complementary interactions seem to favor certain pairing of subunits. This knowledge leads to restrictions on the 5,040 (=7!) possible subunits arrangements in the ring, and limits them to just 72. Although our findings give only partial understanding of the inter-subunit interactions that determine their order, we conclude that they are comprised of complementary charged, polar and hydrophobic interactions that occur in both the equatorial and middle domains of each subunit.

Structural bioinformatics and protein docking analysis of the molecular chaperone-kinase interactions: towards allosteric inhibition of protein kinases by targeting the hsp90-cdc37 chaperone machinery

A fundamental role of the Hsp90-Cdc37 chaperone system in mediating maturation of protein kinase clients and supporting kinase functional activity is essential for the integrity and viability of signaling pathways involved in cell cycle control and organism development. Despite significant advances in understanding structure and function of molecular chaperones, the molecular mechanisms and guiding principles of kinase recruitment to the chaperone system are lacking quantitative characterization. Structural and thermodynamic characterization of Hsp90-Cdc37 binding with protein kinase clients by modern experimental techniques is highly challenging, owing to a transient nature of chaperone-mediated interactions. In this work, we used experimentally-guided protein docking to probe the allosteric nature of the Hsp90-Cdc37 binding with the cyclin-dependent kinase 4 (Cdk4) kinase clients. The results of docking simulations suggest that the kinase recognition and recruitment to the chaperone system may be primarily determined by Cdc37 targeting of the N-terminal kinase lobe. The interactions of Hsp90 with the C-terminal kinase lobe may provide additional "molecular brakes" that can lock (or unlock) kinase from the system during client loading (release) stages. The results of this study support a central role of the Cdc37 chaperone in recognition and recruitment of the kinase clients. Structural analysis may have useful implications in developing strategies for allosteric inhibition of protein kinases by targeting the Hsp90-Cdc37 chaperone machinery.

Atractaspis aterrima toxins: the first insight into the molecular evolution of venom in side-stabbers

Although snake venoms have been the subject of intense research, primarily because of their tremendous potential as a bioresource for design and development of therapeutic compounds, some specific groups of snakes, such as the genus Atractaspis, have been completely neglected. To date only limited number of toxins, such as sarafotoxins have been well characterized from this lineage. In order to investigate the molecular diversity of venom from Atractaspis aterrima—the slender burrowing asp, we utilized a high-throughput transcriptomic approach completed with an original bioinformatics analysis pipeline. Surprisingly, we found that Sarafotoxins do not constitute the major ingredient of the transcriptomic cocktail; rather a large number of previously well-characterized snake venom-components were identified. Notably, we recovered a large diversity of three-finger toxins (3FTxs), which were found to have evolved under the significant influence of positive selection. From the normalized and non-normalized transcriptome libraries, we were able to evaluate the relative abundance of the different toxin groups, uncover rare transcripts, and gain new insight into the transcriptomic machinery. In addition to previously characterized toxin families, we were able to detect numerous highly-transcribed compounds that possess all the key features of venom-components and may constitute new classes of toxins.

Squeezers and leaf-cutters: differential diversification and degeneration of the venom system in toxicoferan reptiles

Although it has been established that all toxicoferan squamates share a common venomous ancestor, it has remained unclear whether the maxillary and mandibular venom glands are evolving on separate gene expression trajectories or if they remain under shared genetic control. We show that identical transcripts are simultaneously expressed not only in the mandibular and maxillary glands, but also in the enigmatic snake rictal gland. Toxin molecular frameworks recovered in this study were three-finger toxin (3FTx), CRiSP, crotamine (beta-defensin), cobra venom factor, cystatin, epididymal secretory protein, kunitz, L-amino acid oxidase, lectin, renin aspartate protease, veficolin, and vespryn. We also discovered a novel low-molecular weight disulfide bridged peptide class in pythonid snake glands. In the iguanian lizards, the most highly expressed are potentially antimicrobial in nature (crotamine (beta-defensin) and cystatin), with crotamine (beta-defensin) also the most diverse. However, a number of proteins characterized from anguimorph lizards and caenophidian snakes with hemotoxic or neurotoxic activities were recruited in the common toxicoferan ancestor and remain expressed, albeit in low levels, even in the iguanian lizards. In contrast, the henophidian snakes express 3FTx and lectin toxins as the dominant transcripts. Even in the constricting pythonid and boid snakes, where the glands are predominantly mucous-secreting, low-levels of toxin transcripts can be detected. Venom thus appears to play little role in feeding behavior of most iguanian lizards or the powerful constricting snakes, and the low levels of expression argue against a defensive role. However, clearly the incipient or secondarily atrophied venom systems of these taxa may be a source of novel compounds useful in drug design and discovery.

Designing template-free predictor for targeting protein-ligand binding sites with classifier ensemble and spatial clustering

Accurately identifying the protein-ligand binding sites or pockets is of significant importance for both protein function analysis and drug design. Although much progress has been made, challenges remain, especially when the 3D structures of target proteins are not available or no homology templates can be found in the library, where the template-based methods are hard to be applied. In this paper, we report a new ligand-specific template-free predictor called TargetS for targeting protein-ligand binding sites from primary sequences. TargetS first predicts the binding residues along the sequence with ligand-specific strategy and then further identifies the binding sites from the predicted binding residues through a recursive spatial clustering algorithm. Protein evolutionary information, predicted protein secondary structure, and ligand-specific binding propensities of residues are combined to construct discriminative features; an improved AdaBoost classifier ensemble scheme based on random undersampling is proposed to deal with the serious imbalance problem between positive (binding) and negative (nonbinding) samples. Experimental results demonstrate that TargetS achieves high performances and outperforms many existing predictors. TargetS web server and data sets are freely available at: http://www.csbio.sjtu.edu.cn/bioinf/TargetS/ for academic use.

Dracula's children: molecular evolution of vampire bat venom

While vampire bat oral secretions have been the subject of intense research, efforts have concentrated only on two components: DSPA (Desmodus rotundus salivary plasminogen activator) and Draculin. The molecular evolutionary history of DSPA has been elucidated, while conversely draculin has long been known from only a very small fragment and thus even the basic protein class was not even established. Despite the fact that vampire bat venom has a multitude of effects unaccounted by the documented bioactivities of DSPA and draculin, efforts have not been made to establish what other bioactive proteins are secreted by their submaxillary gland. In addition, it has remained unclear whether the anatomically distinct anterior and posterior lobes of the submaxillary gland are evolving on separate gene expression trajectories or if they remain under the shared genetic control. Using a combined proteomic and transcriptomic approach, we show that identical proteins are simultaneously expressed in both lobes. In addition to recovering the known structural classes of DSPA, we recovered a novel DSPA isoform as well as obtained a very large sequence stretch of draculin and thus established that it is a mutated version of the lactotransferrin scaffold. This study reveals a much more complex secretion profile than previously recognised. In addition to obtaining novel versions of scaffolds convergently recruited into other venoms (allergen-like, CRiSP, kallikrein, Kunitz, lysozyme), we also documented novel expression of small peptides related to calcitonin, PACAP, and statherin. Other overexpressed protein types included BPI-fold, lacritin, and secretoglobin. Further, we investigate the molecular evolution of various vampire bat venom-components and highlight the dominant role of positive selection in the evolution of these proteins. Conspicuously many of the proteins identified in the proteome were found to be homologous to proteins with known activities affecting vasodilation and platelet aggregation. We show that vampire bat venom proteins possibly evade host immune response by the mutation of the surface chemistry through focal mutagenesis under the guidance of positive Darwinian selection. These results not only contribute to the body of knowledge regarding haematophagous venoms but also provide a rich resource for novel lead compounds for use in drug design and development.

BIOLOGICAL SIGNIFICANCE

These results have direct implications in understanding the molecular evolutionary history of vampire bat venom. The unusual peptides discovered reinforce the value of studying such neglected taxon for biodiscovery.

OpenStructure: an integrated software framework for computational structural biology

Research projects in structural biology increasingly rely on combinations of heterogeneous sources of information, e.g. evolutionary information from multiple sequence alignments, experimental evidence in the form of density maps and proximity constraints from proteomics experiments. The OpenStructure software framework, which allows the seamless integration of information of different origin, has previously been introduced. The software consists of C++ libraries which are fully accessible from the Python programming language. Additionally, the framework provides a sophisticated graphics module that interactively displays molecular structures and density maps in three dimensions. In this work, the latest developments in the OpenStructure framework are outlined. The extensive capabilities of the framework will be illustrated using short code examples that show how information from molecular-structure coordinates can be combined with sequence data and/or density maps. The framework has been released under the LGPL version 3 license and is available for download from http://www.openstructure.org.

Structural and functional insight into the universal stress protein family

We present the crystal structures of two universal stress proteins (USP) from Archaeoglobus fulgidus and Nitrosomonas europaea in both apo- and ligand-bound forms. This work is the first complete synthesis of the structural properties of 26 USP available in the Protein Data Bank, over 75% of which were determined by structure genomics centers with no additional information provided. The results of bioinformatic analyses of all available USP structures and their sequence homologs revealed that these two new USP structures share overall structural similarity with structures of USPs previously determined. Clustering and cladogram analyses, however, show how they diverge from other members of the USP superfamily and show greater similarity to USPs from organisms inhabiting extreme environments. We compared them with other archaeal and bacterial USPs and discuss their similarities and differences in context of structure, sequential motifs, and potential function. We also attempted to group all analyzed USPs into families, so that assignment of the potential function to those with no experimental data available would be possible by extrapolation.

Novel targets in drug design: enzymes in the protein ubiquitylation pathway

Protein ubiquitylation is a pathway by which many proteins are selectively degraded. Its role has been shown in processes such as cell division and differentiation, oncogenesis, apoptosis, DNA repair, membrane transport and the removal of abnormal proteins. The ubiquitylation pathway enzymes are an insufficiently researched area for drug development. A genetic method has been developed (supported by computational biology) to identify potentially useful small molecules that will have a positive impact on our battle against cancer and other diseases. In silico screening is used for initial selection of drug-like compounds. This method is based on docking three-dimensional chemical libraries onto the target enzyme's functional site for initial screens using a computational scheme, followed by genetic and in vivo methods for hit optimisation. Focus has been on using the ubiquitin conjugation pathway as target for therapeutic intervention against cancer and potent inhibitors of ubiquitylation subpathways have been obtained (including those that are vital for the survival of aggressive cancer cells/tumours). Leads from the development of in vitro inhibitors provided a direction for the development of in vivo inhibitors as investigational tools, and as promising therapeutic agents.

Molecular phylogeny and evolution of the proteins encoded by coleoid (cuttlefish, octopus, and squid) posterior venom glands

In this study, we report for the first time a detailed evaluation of the phylogenetic history and molecular evolution of the major coleoid toxins: CAP, carboxypeptidase, chitinase, metalloprotease GON-domain, hyaluronidase, pacifastin, PLA2, SE-cephalotoxin and serine proteases, with the carboxypeptidase and GON-domain documented for the first time in the coleoid venom arsenal. We show that although a majority of sites in these coleoid venom-encoding genes have evolved under the regime of negative selection, a very small proportion of sites are influenced by the transient selection pressures. Moreover, nearly 70 % of these episodically adapted sites are confined to the molecular surface, highlighting the importance of variation of the toxin surface chemistry. Coleoid venoms were revealed to be as complex as other venoms that have traditionally been the recipient of the bulk of research efforts. The presence of multiple peptide/protein types in coleoids similar to those present in other animal venoms identifies a convergent strategy, revealing new information as to what characteristics make a peptide/protein type amenable for recruitment into chemical arsenals. Coleoid venoms have significant potential not only for understanding fundamental aspects of venom evolution but also as an untapped source of novel toxins for use in drug design and discovery.

TargetATPsite: a template-free method for ATP-binding sites prediction with residue evolution image sparse representation and classifier ensemble

Understanding the interactions between proteins and ligands is critical for protein function annotations and drug discovery. We report a new sequence-based template-free predictor (TargetATPsite) to identify the Adenosine-5'-triphosphate (ATP) binding sites with machine-learning approaches. Two steps are implemented in TargetATPsite: binding residues and pockets predictions, respectively. To predict the binding residues, a novel image sparse representation technique is proposed to encode residue evolution information treated as the input features. An ensemble classifier constructed based on support vector machines (SVM) from multiple random under-samplings is used as the prediction model, which is effective for dealing with imbalance phenomenon between the positive and negative training samples. Compared with the existing ATP-specific sequence-based predictors, TargetATPsite is featured by the second step of possessing the capability of further identifying the binding pockets from the predicted binding residues through a spatial clustering algorithm. Experimental results on three benchmark datasets demonstrate the efficacy of TargetATPsite.

Structural, evolutionary, and assembly principles of protein oligomerization

In the protein universe, 30-50% of proteins self-assemble to form symmetrical complexes consisting of multiple copies of themselves, called homomers. The prevalence of homomers motivates us to review many of their properties. In Section 1, we describe the methods and challenges associated with quaternary structure inference-these methods are indeed at the basis of any analysis on homomers. In Section 2, we describe the morphological properties of homomers, as well as the database 3DComplex, which provides a taxonomy for both homomeric and heteromeric protein complexes. In Section 3, we review interface properties of homomeric complexes. In Section 4, we then present recent findings on the evolution of homomer interfaces, which we link in Section 5 to the evolution of homomers as entire entities. In Section 6, we discuss mechanisms involved in their assembly and how these mechanisms can be linked to evolution.

Differential evolution and neofunctionalization of snake venom metalloprotease domains

Snake venom metalloproteases (SVMP) are composed of five domains: signal peptide, propeptide, metalloprotease, disintegrin, and cysteine-rich. Secreted toxins are typically combinatorial variations of the latter three domains. The SVMP-encoding genes of Psammophis mossambicus venom are unique in containing only the signal and propeptide domains. We show that the Psammophis SVMP propeptide evolves rapidly and is subject to a high degree of positive selection. Unlike Psammophis, some species of Echis express both the typical multidomain and the unusual monodomain (propeptide only) SVMP, with the result that a lower level of variation is exerted upon the latter. We showed that most mutations in the multidomain Echis SVMP occurred in the protease domain responsible for proteolytic and hemorrhagic activities. The cysteine-rich and disintegrin-like domains, which are putatively responsible for making the P-III SVMPs more potent than the P-I and P-II forms, accumulate the remaining variation. Thus, the binding sites on the molecule's surface are evolving rapidly whereas the core remains relatively conserved. Bioassays conducted on two post-translationally cleaved novel proline-rich peptides from the P. mossambicus propeptide domain showed them to have been neofunctionalized for specific inhibition of mammalian a7 neuronal nicotinic acetylcholine receptors. We show that the proline rich postsynaptic specific neurotoxic peptides from Azemiops feae are the result of convergent evolution within the precursor region of the C-type natriuretic peptide instead of the SVMP. The results of this study reinforce the value of studying obscure venoms for biodiscovery of novel investigational ligands.

Protein fragments: functional and structural roles of their coevolution networks

Small protein fragments, and not just residues, can be used as basic building blocks to reconstruct networks of coevolved amino acids in proteins. Fragments often enter in physical contact one with the other and play a major biological role in the protein. The nature of these interactions might be multiple and spans beyond binding specificity, allosteric regulation and folding constraints. Indeed, coevolving fragments are indicators of important information explaining folding intermediates, peptide assembly, key mutations with known roles in genetic diseases, distinguished subfamily-dependent motifs and differentiated evolutionary pressures on protein regions. Coevolution analysis detects networks of fragments interaction and highlights a high order organization of fragments demonstrating the importance of studying at a deeper level this structure. We demonstrate that it can be applied to protein families that are highly conserved or represented by few sequences, enlarging in this manner, the class of proteins where coevolution analysis can be performed and making large-scale coevolution studies a feasible goal.

Improving the thermostability of alpha-amylase by combinatorial coevolving-site saturation mutagenesis

Background

The generation of focused mutant libraries at hotspot residues is an important strategy in directed protein evolution. Existing methods, such as combinatorial active site testing and residual coupling analysis, depend primarily on the evolutionary conserved information to find the hotspot residues. Hardly any attention has been paid to another important functional and structural determinants, the functionally correlated variation information--coevolution.

Results

In this paper, we suggest a new method, named combinatorial coevolving-site saturation mutagenesis (CCSM), in which the functionally correlated variation sites of proteins are chosen as the hotspot sites to construct focused mutant libraries. The CCSM approach was used to improve the thermal stability of α-amylase from Bacillus subtilis CN7 (Amy7C). The results indicate that the CCSM can identify novel beneficial mutation sites, and enhance the thermal stability of wild-type Amy7C by 8°C ( T5030), which could not be achieved with the ordinarily rational introduction of single or a double point mutation.

Conclusions

Our method is able to produce more thermostable mutant α-amylases with novel beneficial mutations at new sites. It is also verified that the coevolving sites can be used as the hotspots to construct focused mutant libraries in protein engineering. This study throws new light on the active researches of the molecular coevolution.

Identification of a novel IVD mutation in a consanguineous family with isovaleric acidemia

Isovaleric acidemia (IVA) is a rare autosomal recessive disorder caused by a deficiency of isovaleryl-CoA dehydrogenase encoded by IVD gene. In this case study we report the first Saudi IVA patients from a consanguineous family with a novel transversion (p.G362V) and briefly discuss likely phenotype-genotype correlation of the disease in the Saudi population. We explored the functional consequences of the mutation by using various bioinformatics prediction algorithms and discussed the likely mechanism of the disease caused by the mutation.

Structures of 5'-3' Exoribonucleases

5'-3' Exoribonucleases (XRNs) have important functions in RNA processing, RNA turnover and decay, RNA interference, RNA polymerase transcription, and other cellular processes. Their sequences share two highly conserved regions, CR1 and CR2. The cytoplasmic Xrn1 and the nuclear Xrn2/Rat1 are found in yeast and animals, and XRNs are found in most other eukaryotes. Crystal structures of Xrn1 and Rat1 have been reported recently, offering the first detailed information on these enzymes. The two conserved regions of XRNs form a single, large domain. CR1 has structural homology with the FEN superfamily of nucleases, while CR2 restricts access to the active site, ensuring that XRNs are exclusive exoribonucleases. The structure of Rai1, the protein partner of Rat1, revealed the presence of an active site, and further studies demonstrated that this activity is a novel mechanism for mRNA 5'-end capping quality surveillance.

The yeast regulator of transcription protein Rtr1 lacks an active site and phosphatase activity

The activity of RNA polymerase II (Pol II) is controlled in part by the phosphorylation state of the C-terminal domain (CTD) of its largest subunit. Recent reports have suggested that yeast regulator of transcription protein, Rtr1, and its human homologue RPAP2, possess Pol II CTD Ser5 phosphatase activity. Here we report the crystal structure of Kluyveromyces lactis Rtr1, which reveals a new type of zinc finger protein and does not have any close structural homologues. Importantly, the structure does not show evidence of an active site, and extensive experiments to demonstrate its CTD phosphatase activity have been unsuccessful, suggesting that Rtr1 has a non-catalytic role in CTD dephosphorylation.

Structure-based rebuilding of coevolutionary information reveals functional modules in rhodopsin structure

Correlated mutation analysis (CMA) has been used to investigate protein functional sites. However, CMA has suffered from low signal-to-noise ratio caused by meaningless phylogenetic signals or structural constraints. We present a new method, Structure-based Correlated Mutation Analysis (SCMA), which encodes coevolution scores into a protein structure network. A path-based network model is adapted to describe information transfer between residues, and the statistical significance is estimated by network shuffling. This model intrinsically assumes that residues in physical contact have a more reliable coevolution score than distant residues, and that coevolution in distant residues likely arises from a series of contacting and coevolving residues. In addition, coevolutionary coupling is statistically controlled to remove the structural effects. When applied to the rhodopsin structure, the SCMA method identified a much higher percentage of functional residues than the typical coevolution score (61% vs. 22%). In addition, statistically significant residues are used to construct the coevolved residue-residue subnetwork. The network has one highly connected node (retinal bound Lys296), indicating that Lys296 can induce and regulate most other coevolved residues in a variety of locations. The coevolved network consists of a few modular clusters which have distinct functional roles. This article is part of a Special Issue entitled: Computational Methods for Protein Interaction and Structural Prediction.

L1pred: a sequence-based prediction tool for catalytic residues in enzymes with the L1-logreg classifier

To understand enzyme functions, identifying the catalytic residues is a usual first step. Moreover, knowledge about catalytic residues is also useful for protein engineering and drug-design. However, to experimentally identify catalytic residues remains challenging for reasons of time and cost. Therefore, computational methods have been explored to predict catalytic residues. Here, we developed a new algorithm, L1pred, for catalytic residue prediction, by using the L1-logreg classifier to integrate eight sequence-based scoring functions. We tested L1pred and compared it against several existing sequence-based methods on carefully designed datasets Data604 and Data63. With ten-fold cross-validation, L1pred showed the area under precision-recall curve (AUPR) and the area under ROC curve (AUC) of 0.2198 and 0.9494 on the training dataset, Data604, respectively. In addition, on the independent test dataset, Data63, it showed the AUPR and AUC values of 0.2636 and 0.9375, respectively. Compared with other sequence-based methods, L1pred showed the best performance on both datasets. We also analyzed the importance of each attribute in the algorithm, and found that all the scores contributed more or less equally to the L1pred performance.

The statistical significance of selected sense-antisense peptide interactions

Sense and antisense peptides, encoded by sense and corresponding antisense DNA strands, are capable of specific interactions that could be a driving force to mediate protein-protein or protein-peptide binding associations. The complementary residue hypothesis suggests that these interactions are founded upon the sum of pairwise interactions between amino acids encoded by corresponding sense and antisense codons. Despite many successful experimental results obtained with the hypothesis, however, the physicochemical basis for these interactions is poorly understood. We examined the potential of the hypothesis for general identification of protein-protein interaction sites, and the possible role of the hypothesis in determining folding in a broad set of protein structures. In addition, we performed a structural study to investigate the binding of a complementary peptide to IL-1F2. Our results suggest that complementary residue pairs are no more frequent or conserved than average in protein-protein interfaces, and are statistically under-represented amongst contacting residue pairs in folded protein structures. Although our structural results matched experimental observations of binding between the peptide and IL-1F2, complementary residue interactions do not appear to be dominant in the bound structure. Overall, our data do not allow us to conclude that the complementary residue hypothesis accounts for specific sense-antisense peptide interactions.

Protein-protein interactions and substrate channeling in orthologous and chimeric aldolase-dehydrogenase complexes

Bacterial aldolase-dehydrogenase complexes catalyze the last steps in the meta cleavage pathway of aromatic hydrocarbon degradation. The aldolase (TTHB246) and dehydrogenase (TTHB247) from Thermus thermophilus were separately expressed and purified from recombinant Escherichia coli. The aldolase forms a dimer, while the dehydrogenase is a monomer; these enzymes can form a stable tetrameric complex in vitro, consisting of two aldolase and two dehydrogenase subunits. Upon complex formation, the K(m) value of 4-hydroxy-2-oxopentanoate, the substrate of TTHB246, is decreased 4-fold while the K(m) of acetaldehyde, the substrate of TTHB247, is increased 3-fold. The k(cat) values of each enzyme were reduced by ~2-fold when they were in a complex. The half-life of TTHB247 at 50 °C increased by ~4-fold when it was in a complex with TTHB246. The acetaldehyde product from TTHB246 could be efficiently channelled directly to TTHB247, but the channeling efficiency for the larger propionaldehyde was ~40% lower. A single A324G substitution in TTHB246 increased the channeling efficiency of propionaldehyde to a value comparable to that of acetaldehyde. Stable and catalytically competent chimeric complexes could be formed between the T. thermophilus enzymes and the orthologous aldolase (BphI) and dehydrogenase (BphJ) from the biphenyl degradation pathway of Burkholderia xenovorans LB400. However, channeling efficiencies for acetaldehyde in these chimeric complexes were ~10%. Structural and sequence analysis suggests that interacting residues in the interface of the aldolase-dehydrogenase complex are highly conserved among homologues, but coevolution of partner enzymes is required to fine-tune this interaction to allow for efficient substrate channeling.

Scabies: important clinical consequences explained by new molecular studies

In 2004, we reviewed the status of disease caused by the scabies mite Sarcoptes scabiei at the time and pointed out that very little basic research had ever been done. The reason for this was largely the lack of availability of mites for experimental purposes and, to a degree, a consequent lack of understanding of its importance, resulting in the trivial name 'itch mite'. Scabies is responsible for major morbidity in disadvantaged communities and immunocompromised patients worldwide. In addition to the physical discomfort caused by the disease, scabies infestations facilitate infection by bacterial pathogens such as Streptococcus pyogenes and Staphylococcus aureus via skin lesions, resulting in severe downstream disease such as in a high prevalence of rheumatic fever/heart disease in affected communities. We now have further evidence that in disadvantaged populations living in tropical climates, scabies rather than 'Strep throat' is an important source of S. pyogenes causing rheumatic fever and eventually rheumatic heart disease. In addition, our work has resulted in two fundamental research tools that facilitate much of the current biomedical research efforts on scabies, namely a public database containing ~45,000 scabies mite expressed sequence tags and a porcine in vivo model. Here we will discuss novel and unexpected proteins encountered in the database that appear crucial to mite survival with regard to digestion and evasion of host defence. The mode(s) of action of some of these have been at least partially revealed. Further, newly discovered molecules that may well have a similar role, such as a family of inactivated cysteine proteases, are yet to be investigated. Hence, there are now whole families of potential targets for chemical inhibitors of S. scabiei. These efforts put today's scabies research in a unique position to design and test small molecules that may specifically interfere with mite-derived molecules, such as digestive proteases and mite complement inhibitors. The porcine scabies model will be available to trial in vivo treatment with potential inhibitors. New therapies for scabies may be developed from these studies and may contribute to reduce the spread of scabies and the subsequent prevalence of bacterial skin infections and their devastating sequelae in the community.

Smolign: a spatial motifs-based protein multiple structural alignment method

Availability of an effective tool for protein multiple structural alignment (MSTA) is essential for discovery and analysis of biologically significant structural motifs that can help solve functional annotation and drug design problems. Existing MSTA methods collect residue correspondences mostly through pairwise comparison of consecutive fragments, which can lead to suboptimal alignments, especially when the similarity among the proteins is low. We introduce a novel strategy based on: building a contact-window based motif library from the protein structural data, discovery and extension of common alignment seeds from this library, and optimal superimposition of multiple structures according to these alignment seeds by an enhanced partial order curve comparison method. The ability of our strategy to detect multiple correspondences simultaneously, to catch alignments globally, and to support flexible alignments, endorse a sensitive and robust automated algorithm that can expose similarities among protein structures even under low similarity conditions. Our method yields better alignment results compared to other popular MSTA methods, on several protein structure data sets that span various structural folds and represent different protein similarity levels. A web-based alignment tool, a downloadable executable, and detailed alignment results for the data sets used here are available at http://sacan.biomed. drexel.edu/Smolign and http://bio.cse.ohio-state.edu/Smolign.

Selection on the protein-coding genome

Populations evolve as mutations arise in individual organisms and, through hereditary transmission, may become "fixed" (shared by all individuals) in the population. Most mutations are lethal or have negative fitness consequences for the organism. Others have essentially no effect on organismal fitness and can become fixed through the neutral stochastic process known as random drift. However, mutations may also produce a selective advantage that boosts their chances of reaching fixation. Regions of genes where new mutations are beneficial, rather than neutral or deleterious, tend to evolve more rapidly due to positive selection. Genes involved in immunity and defense are a well-known example; rapid evolution in these genes presumably occurs because new mutations help organisms to prevail in evolutionary "arms races" with pathogens. In recent years, genome-wide scans for selection have enlarged our understanding of the evolution of the protein-coding regions of the various species. In this chapter, we focus on the methods to detect selection in protein-coding genes. In particular, we discuss probabilistic models and how they have changed with the advent of new genome-wide data now available.

A knowledge-based potential highlights unique features of membrane α-helical and β-barrel protein insertion and folding

Outer membrane β-barrel proteins differ from α-helical inner membrane proteins in lipid environment, secondary structure, and the proposed processes of folding and insertion. It is reasonable to expect that outer membrane proteins may contain primary sequence information specific for their folding and insertion behavior. In previous work, a depth-dependent insertion potential, E(z) , was derived for α-helical inner membrane proteins. We have generated an equivalent potential for TM β-barrel proteins. The similarities and differences between these two potentials provide insight into unique aspects of the folding and insertion of β-barrel membrane proteins. This potential can predict orientation within the membrane and identify functional residues involved in intermolecular interactions.

HotRegion: a database of predicted hot spot clusters

Hot spots are energetically important residues at protein interfaces and they are not randomly distributed across the interface but rather clustered. These clustered hot spots form hot regions. Hot regions are important for the stability of protein complexes, as well as providing specificity to binding sites. We propose a database called HotRegion, which provides the hot region information of the interfaces by using predicted hot spot residues, and structural properties of these interface residues such as pair potentials of interface residues, accessible surface area (ASA) and relative ASA values of interface residues of both monomer and complex forms of proteins. Also, the 3D visualization of the interface and interactions among hot spot residues are provided. HotRegion is accessible at http://prism.ccbb.ku.edu.tr/hotregion.

AADS--an automated active site identification, docking, and scoring protocol for protein targets based on physicochemical descriptors

We report here a robust automated active site detection, docking, and scoring (AADS) protocol for proteins with known structures. The active site finder identifies all cavities in a protein and scores them based on the physicochemical properties of functional groups lining the cavities in the protein. The accuracy realized on 620 proteins with sizes ranging from 100 to 600 amino acids with known drug active sites is 100% when the top ten cavity points are considered. These top ten cavity points identified are then submitted for an automated docking of an input ligand/candidate molecule. The docking protocol uses an all atom energy based Monte Carlo method. Eight low energy docked structures corresponding to different locations and orientations of the candidate molecule are stored at each cavity point giving 80 docked structures overall which are then ranked using an effective free energy function and top five structures are selected. The predicted structure and energetics of the complexes agree quite well with experiment when tested on a data set of 170 protein-ligand complexes with known structures and binding affinities. The AADS methodology is implemented on an 80 processor cluster and presented as a freely accessible, easy to use tool at http://www.scfbio-iitd.res.in/dock/ActiveSite_new.jsp .

Structural and biochemical analysis of nuclease domain of clustered regularly interspaced short palindromic repeat (CRISPR)-associated protein 3 (Cas3)

RNA transcribed from clustered regularly interspaced short palindromic repeats (CRISPRs) protects many prokaryotes from invasion by foreign DNA such as viruses, conjugative plasmids, and transposable elements. Cas3 (CRISPR-associated protein 3) is essential for this CRISPR protection and is thought to mediate cleavage of the foreign DNA through its N-terminal histidine-aspartate (HD) domain. We report here the 1.8 Å crystal structure of the HD domain of Cas3 from Thermus thermophilus HB8. Structural and biochemical studies predict that this enzyme binds two metal ions at its active site. We also demonstrate that the single-stranded DNA endonuclease activity of this T. thermophilus domain is activated not by magnesium but by transition metal ions such as manganese and nickel. Structure-guided mutagenesis confirms the importance of the metal-binding residues for the nuclease activity and identifies other active site residues. Overall, these results provide a framework for understanding the role of Cas3 in the CRISPR system.

Characterization of protein-protein interaction interfaces from a single species

Most proteins attain their biological functions through specific interactions with other proteins. Thus, the study of protein-protein interactions and the interfaces that mediate these interactions is of prime importance for the understanding of biological function. In particular the precise determinants of binding specificity and their contributions to binding energy within protein interfaces are not well understood. In order to better understand these determinants an appropriate description of the interaction surface is needed. Available data from the yeast Saccharomyces cerevisiae allow us to focus on a single species and to use all the available structures, correcting for redundancy, instead of using structural representatives. This allows us to control for potentially confounding factors that may affect sequence propensities. We find a significant contribution of main-chain atoms to protein-protein interactions. These include interactions both with other main-chain and side-chain atoms on the interacting chain. We find that the type of interaction depends on both amino acid and secondary structure type involved in the contact. For example, residues in α-helices and large amino acids are the most likely to be involved in interactions through their side-chain atoms. We find an intriguing homogeneity when calculating the average solvation energy of different areas of the protein surface. Unexpectedly, homo- and hetero-complexes have quite similar results for all analyses. Our findings demonstrate that the manner in which protein-protein interactions are formed is determined by the residue type and the secondary structure found in the interface. However the homogeneity of the desolvation energy despite heterogeneity of interface properties suggests a complex relationship between interface composition and binding energy.

HomPPI: a class of sequence homology based protein-protein interface prediction methods

BACKGROUND

Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate.

RESULTS

We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence.Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i) NPS-HomPPI (Non partner-specific HomPPI), which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii) PS-HomPPI (Partner-specific HomPPI), which can be used to predict the interface residues of a query protein with a specific target protein.Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC) of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of both the query and the target can be reliably identified. The HomPPI web server is available at http://homppi.cs.iastate.edu/.

CONCLUSIONS

Sequence homology-based methods offer a class of computationally efficient and reliable approaches for predicting the protein-protein interface residues that participate in either obligate or transient interactions. For query proteins involved in transient interactions, the reliability of interface residue prediction can be improved by exploiting knowledge of putative interaction partners.

HemeBIND: a novel method for heme binding residue prediction by combining structural and sequence information

BACKGROUND

Accurate prediction of binding residues involved in the interactions between proteins and small ligands is one of the major challenges in structural bioinformatics. Heme is an essential and commonly used ligand that plays critical roles in electron transfer, catalysis, signal transduction and gene expression. Although much effort has been devoted to the development of various generic algorithms for ligand binding site prediction over the last decade, no algorithm has been specifically designed to complement experimental techniques for identification of heme binding residues. Consequently, an urgent need is to develop a computational method for recognizing these important residues.

RESULTS

Here we introduced an efficient algorithm HemeBIND for predicting heme binding residues by integrating structural and sequence information. We systematically investigated the characteristics of binding interfaces based on a non-redundant dataset of heme-protein complexes. It was found that several sequence and structural attributes such as evolutionary conservation, solvent accessibility, depth and protrusion clearly illustrate the differences between heme binding and non-binding residues. These features can then be separately used or combined to build the structure-based classifiers using support vector machine (SVM). The results showed that the information contained in these features is largely complementary and their combination achieved the best performance. To further improve the performance, an attempt has been made to develop a post-processing procedure to reduce the number of false positives. In addition, we built a sequence-based classifier based on SVM and sequence profile as an alternative when only sequence information can be used. Finally, we employed a voting method to combine the outputs of structure-based and sequence-based classifiers, which demonstrated remarkably better performance than the individual classifier alone.

CONCLUSIONS

HemeBIND is the first specialized algorithm used to predict binding residues in protein structures for heme ligands. Extensive experiments indicated that both the structure-based and sequence-based methods have effectively identified heme binding residues while the complementary relationship between them can result in a significant improvement in prediction performance. The value of our method is highlighted through the development of HemeBIND web server that is freely accessible at http://mleg.cse.sc.edu/hemeBIND/.

The expanding view of protein-protein interactions: complexes involving intrinsically disordered proteins

A frequently neglected aspect of protein-protein interactions is flexibility. Small-scale fluctuations are present even in globular proteins, and alternative conformations can have a significant influence on the binding process. However, flexibility becomes highly prominent in complexes involving intrinsically disordered proteins. The importance of disordered regions in protein interactions has been recognized only relatively recently. In this survey we examine the basic properties of the complexes of disordered and ordered proteins from three different directions. The comparison of the interface properties shows that although disordered proteins can also adopt well-defined conformations in their bound form, their inherently dynamic nature is cast into their complexes. Furthermore, an overview of prediction methods indicates that disordered proteins as well as their binding regions can be recognized from the amino acid sequence by capturing the basic biophysical properties of these segments. Finally, we propose the generalization of the 'energy landscape model' for the description of complex formation that can help to put the various types of protein associations on a common ground.

A single zinc ion is sufficient for an active Trypanosoma brucei tRNA editing deaminase

Editing of adenosine (A) to inosine (I) at the first anticodon position in tRNA is catalyzed by adenosine deaminases acting on tRNA (ADATs). This essential reaction in bacteria and eukarya permits a single tRNA to decode multiple codons. Bacterial ADATa is a homodimer with two bound essential Zn(2+). The ADATa crystal structure revealed residues important for substrate binding and catalysis; however, such high resolution structural information is not available for eukaryotic tRNA deaminases. Despite significant sequence similarity among deaminases, we continue to uncover unexpected functional differences between Trypanosoma brucei ADAT2/3 (TbADAT2/3) and its bacterial counterpart. Previously, we demonstrated that TbADAT2/3 is unique in catalyzing two different deamination reactions. Here we show by kinetic analyses and inductively coupled plasma emission spectrometry that wild type TbADAT2/3 coordinates two Zn(2+) per heterodimer, but unlike any other tRNA deaminase, mutation of one of the key Zn(2+)-coordinating cysteines in TbADAT2 yields a functional enzyme with a single-bound zinc. These data suggest that, at least, TbADAT3 may play a role in catalysis via direct coordination of the catalytic Zn(2+). These observations raise the possibility of an unusual Zn(2+) coordination interface with important implications for the function and evolution of editing deaminases.

Alternative allosteric mechanisms can regulate the substrate and E2 in SUMO conjugation

Sumoylation is the covalent attachment of small ubiquitin-like modifier (SUMO) to a target protein. Similar to other ubiquitin-like pathways, three enzyme types are involved that act in succession: an activating enzyme (E1), a conjugating enzyme (E2), and a ligase (E3). To date, unlike other ubiquitin-like mechanisms, sumoylation of the target RanGAP1 (Target(RanGAP1)) does not absolutely require the E3 of the system, RanBP2 (E3(RanBP2)), since the presence of E2 (E2(Ubc9)) is enough to sumoylate Target(RanGAP1). However, in the presence of E3, sumoylation is more efficient. To understand the role of the target specificity of E3(RanBP2) and E2(Ubc9), we carried out molecular dynamics simulations for the structure of E2(Ubc9)-SUMO-Target(RanGAP1) with and without the E3(RanBP2) ligase. Analysis of the dynamics of E2(Ubc9)-SUMO-Target(RanGAP1) in the absence and presence of E3(RanBP2) revealed that two different allosteric sites regulate the ligase activity: (i) in the presence of E3(RanBP2), the E2(Ubc9)'s loop 2; (ii) in the absence of E3(RanBP2), the Leu65-Arg70 region of SUMO. These results provide a first insight into the question of how E3(RanBP2) can act as an intrinsic E3 for E2(Ubc9) and why, in its absence, the activity of E2(Ubc9)-SUMO-Target(RanGAP1) could still be maintained, albeit at lower efficiency.

Crystal structure of a truncated urease accessory protein UreF from Helicobacter pylori

Urease plays a central role in the pathogenesis of Helicobacter pylori in humans. Maturation of this nickel metalloenzyme in bacteria requires the participation of the accessory proteins UreD (termed UreH in H. pylori), UreF, and UreG, which form sequential complexes with the urease apoprotein as well as UreE, a metallochaperone. Here, we describe the crystal structure of C-terminal truncated UreF from H. pylori (residues 1-233), the first UreF structure to be determined, at 1.55 A resolution using SAD methods. UreF forms a dimer in vitro and adopts an all-helical fold congruent with secondary structure prediction. On the basis of evolutionary conservation analysis, the structure reveals a probable binding surface for interaction with other urease components as well as key conserved residues of potential functional relevance.

Structural and biochemical studies of the 5'→3' exoribonuclease Xrn1

The 5′→ 3′ exoribonucleases (XRNs) have important functions in transcription, RNA metabolism, and RNA interference. The recent structure of Rat1 (Xrn2) showed that the two highly conserved regions of XRNs form a single, large domain, defining the active site of the enzyme. Xrn1 has a 510-residue segment following the conserved regions that is required for activity but is absent in Rat1. We report here the crystal structures at 2.9 Å resolution of Kluyveromyces lactis Xrn1 (residues 1–1245, E178Q mutant), alone and in complex with a Mn²⁺ ion in the active site. The 510-residue segment contains four domains (D1–D4), located far from the active site. Our mutagenesis and biochemical studies demonstrate that their functional importance is due to their stabilization of the conformation of the N-terminal segment of Xrn1. These domains may also constitute a platform for interacting with protein partners of Xrn1.

Catalytic residues in hydrolases: analysis of methods designed for ligand-binding site prediction

The comparison of eight tools applicable to ligand-binding site prediction is presented. The methods examined cover three types of approaches: the geometrical (CASTp, PASS, Pocket-Finder), the physicochemical (Q-SiteFinder, FOD) and the knowledge-based (ConSurf, SuMo, WebFEATURE). The accuracy of predictions was measured in reference to the catalytic residues documented in the Catalytic Site Atlas. The test was performed on a set comprising selected chains of hydrolases. The results were analysed with regard to size, polarity, secondary structure, accessible solvent area of predicted sites as well as parameters commonly used in machine learning (F-measure, MCC). The relative accuracies of predictions are presented in the ROC space, allowing determination of the optimal methods by means of the ROC convex hull. Additionally the minimum expected cost analysis was performed. Both advantages and disadvantages of the eight methods are presented. Characterization of protein chains in respect to the level of difficulty in the active site prediction is introduced. The main reasons for failures are discussed. Overall, the best performance offers SuMo followed by FOD, while Pocket-Finder is the best method among the geometrical approaches.

Prediction of active site cleft using support vector machines

Computational tools are available today for the detection and delineation of the clefts and cavities in protein 3D structure and ranking them on the basis of probable binding site clefts. There is a need to improve the ranking of clefts and accuracy of predicting catalytic site clefts. Our results show that the distance of the clefts from protein centroid and sequence entropy of the lining residues, when used in conjunction with the volume, are valuable descriptors for predicting the catalytic site. We have applied the SVM approach for recognizing and ranking the active site clefts and tested its performance using different combinations of attributes. In both the ligand-bound and the unbound forms of structures, our method correctly predicts the active site clefts in 73% of cases at rank one. If we consider the results at rank 3 (i.e., the correct solution is among one of the top three solutions), the correctly predicted cases are 94% and 90% for the bound and the unbound forms of structures, respectively. Our approach improves the ranking of binding site clefts in comparison with CASTp and is comparable to other existing methods like Fpocket. Although the data set for training the SVM approach is rather small in size, the results are encouraging for the method to be used as complementary to other existing tools.