ProBiS-2012: web server and web services for detection of structurally similar binding sites in proteins

VirtuousPocketome: a computational tool for screening protein-ligand complexes to identify similar binding sites

Protein residues within binding pockets play a critical role in determining the range of ligands that can interact with a protein, influencing its structure and function. Identifying structural similarities in proteins offers valuable insights into their function and activation mechanisms, aiding in predicting protein-ligand interactions, anticipating off-target effects, and facilitating the development of therapeutic agents. Numerous computational methods assessing global or local similarity in protein cavities have emerged, but their utilization is impeded by complexity, impractical automation for amino acid pattern searches, and an inability to evaluate the dynamics of scrutinized protein-ligand systems. Here, we present a general, automatic and unbiased computational pipeline, named VirtuousPocketome, aimed at screening huge databases of proteins for similar binding pockets starting from an interested protein-ligand complex. We demonstrate the pipeline's potential by exploring a recently-solved human bitter taste receptor, i.e. the TAS2R46, complexed with strychnine. We pinpointed 145 proteins sharing similar binding sites compared to the analysed bitter taste receptor and the enrichment analysis highlighted the related biological processes, molecular functions and cellular components. This work represents the foundation for future studies aimed at understanding the effective role of tastants outside the gustatory system: this could pave the way towards the rationalization of the diet as a supplement to standard pharmacological treatments and the design of novel tastants-inspired compounds to target other proteins involved in specific diseases or disorders. The proposed pipeline is publicly accessible, can be applied to any protein-ligand complex, and could be expanded to screen any database of protein structures.

Identifying Metal Binding Sites in Proteins Using Homologous Structures, the MADE Approach

In order to identify the locations of metal ions in the binding sites of proteins, we have developed a method named the MADE (MAcromolecular DEnsity and Structure Analysis) approach. The MADE approach represents an evolution of our previous toolset, the ProBiS H2O (MD) methodology, for the identification of conserved water molecules. Our method uses experimental structures of proteins homologous to a query, which are subsequently superimposed upon it. Areas with a particular species present in a similar location among many homologous protein structures are identified using a clustering algorithm. Dense clusters likely represent positions containing species important to the query protein structure or function. We analyze well-characterized apo protein structures and show that the MADE approach can identify clusters corresponding to the expected positions of metal ions in their binding sites. The greatest advantage of our method lies in its generality. It can in principle be applied to any species found in protein records; it is not only limited to metal ions. We additionally demonstrate that the MADE approach can be successfully applied to predict the location of cofactors in computer-modeled structures, e.g., via AlphaFold. We also conduct a careful protein superposition method comparison and find our methodology robust and the results largely independent of the selected protein superposition algorithm. We postulate that with increasing structural data availability, additional applications of the MADE approach will be possible such as non-protein systems, water network identification, protein binding site elaboration, and analysis of binding events, all in a dynamic manner. We have implemented the MADE approach as a plugin for the PyMOL molecular visualization tool. The MADE plugin is available free of charge at https://gitlab.com/Jukic/made_software.

Inhibition of the Human Neuronal Sodium Channel Nav1.9 by Arachidonyl-2-Chloroethylamide, An Analogue of Anandamide in a hNav1.9/rNav1.4 Chimera, An Experimental and in Silico Study

Cannabinoids regulate analgesia, which has aroused much interest in identifying new pharmacological therapies in the management of refractory pain. Voltage-gated Na+ channels (Na_vs) play an important role in inflammatory and neuropathic pain. In particular, Na_v1.9 is involved in nociception and the understanding of its pharmacology has lagged behind because it is difficult to express in heterologous systems. Here, we utilized the chimeric channel hNa_v1.9_C4, that comprises the extracellular and transmembrane domains of hNa_v1.9, co-expressed with the ß1 subunit on CHO-K1 cells to characterize the electrophysiological effects of ACEA, a synthetic surrogate of the endogenous cannabinoid anandamide. ACEA induced a tonic block, decelerated the fast inactivation, markedly shifted steady-state inactivation in the hyperpolarized direction, decreasing the window current and showed use-dependent block, with a high affinity for the inactivated state (k_i = 0.84 µM). Thus, we argue that ACEA possess a local anaesthetic-like profile. To provide a mechanistic understanding of its mode of action at the molecular level, we combined induced fit docking with Monte Carlo simulations and electrostatic complementarity. In agreement with the experimental evidence, our computer simulations revealed that ACEA binds Tyr1599 of the local anaesthetics binding site of the hNa_v1.9, contacting residues that bind cannabinol (CBD) in the Na_vMs channel. ACEA adopted a conformation remarkably similar to the crystallographic conformation of anandamide on a non-homologous protein, obstructing the Na+ permeation pathway below the selectivity filter to occupy a highly conserved binding pocket at the intracellular side. These results describe a mechanism of action, possibly involved in cannabinoid analgesia.

GrAfSS: a webserver for substructure similarity searching and comparisons in the structures of proteins and RNA

The GrAfSS (Graph theoretical Applications for Substructure Searching) webserver is a platform to search for three-dimensional substructures of: (i) amino acid side chains in protein structures; and (ii) base arrangements in RNA structures. The webserver interfaces the functions of five different graph theoretical algorithms – ASSAM, SPRITE, IMAAAGINE, NASSAM and COGNAC – into a single substructure searching suite. Users will be able to identify whether a three-dimensional (3D) arrangement of interest, such as a ligand binding site or 3D motif, observed in a protein or RNA structure can be found in other structures available in the Protein Data Bank (PDB). The webserver also allows users to determine whether a protein or RNA structure of interest contains substructural arrangements that are similar to known motifs or 3D arrangements. These capabilities allow for the functional annotation of new structures that were either experimentally determined or computationally generated (such as the coordinates generated by AlphaFold2) and can provide further insights into the diversity or conservation of functional mechanisms of structures in the PDB. The computed substructural superpositions are visualized using integrated NGL viewers. The GrAfSS server is available at http://mfrlab.org/grafss/.

A Set of Experimentally Validated Decoys for the Human CC Chemokine Receptor 7 (CCR7) Obtained by Virtual Screening

We present a state-of-the-art virtual screening workflow aiming at the identification of novel CC chemokine receptor 7 (CCR7) antagonists. Although CCR7 is associated with a variety of human diseases, such as immunological disorders, inflammatory diseases, and cancer, this target is underexplored in drug discovery and there are no potent and selective CCR7 small molecule antagonists available today. Therefore, computer-aided ligand-based, structure-based, and joint virtual screening campaigns were performed. Hits from these virtual screenings were tested in a CCL19-induced calcium signaling assay. After careful evaluation, none of the in silico hits were confirmed to have an antagonistic effect on CCR7. Hence, we report here a valuable set of 287 inactive compounds that can be used as experimentally validated decoys.

ProBiS-Dock: A Hybrid Multitemplate Homology Flexible Docking Algorithm Enabled by Protein Binding Site Comparison

The protein data bank (PDB) is a rich source of protein ligand structures, but ligands are not explicitly used in current docking algorithms. We have developed ProBiS-Dock, a docking algorithm complementary to the ProBiS-Dock Database (J. Chem. Inf. Model. 2021, 61, 4097-4107) that treats small molecules and proteins as fully flexible entities and allows conformational changes in both after ligand binding. A new scoring function is described that consists of a binding site-specific scoring function (ProBiS-Score) and a general statistical scoring function. ProBiS-Dock enables rapid docking of small molecules to proteins and has been successfully validated in silico against standard benchmarks. It enables rapid search for new active ligands by leveraging existing knowledge in the PDB. The potential of the software for drug development has been confirmed in vitro by the discovery of new inhibitors of human indoleamine 2,3-dioxygenase 1, an enzyme that is an attractive target for cancer therapy and catalyzes the first rate-determining step of l-tryptophan metabolism via the kynurenine pathway. The software is freely available to academic users at http://insilab.org/probisdock.

Computational Methods for Drug Repurposing

The wealth of knowledge and multi-omics data available in drug research has allowed the rise of several computational methods in the drug discovery field, resulting in a novel and exciting strategy called drug repurposing. Drug repurposing consists in finding new applications for existing drugs. Numerous computational methods perform a high-level integration of different knowledge sources to facilitate the discovery of unknown mechanisms. In this chapter, we present a survey of data resources and computational tools available for drug repositioning.

Molecular Docking Simulation Studies Identifies Potential Natural Product Derived-Antiwolbachial Compounds as Filaricides against Onchocerciasis

Onchocerciasis is the leading cause of blindness and severe skin lesions which remain a major public health problem, especially in tropical areas. The widespread use of antibiotics and the long duration required for effective treatment continues to add to the increasing global menace of multi-resistant pathogens. Onchocerca volvulus harbors the endosymbiont bacteria Wolbachia, essential for the normal development of embryos, larvae and long-term survival of the adult worm, O. volvulus. We report here results of using structure-based drug design (SBDD) approach aimed at identifying potential novel Wolbachia inhibitors from natural products against the Wolbachia surface protein (WSP). The protein sequence of the WSP with UniProtKB identifier Q0RAI4 was used to model the three-dimensional (3D) structure via homology modelling techniques using three different structure-building algorithms implemented in Modeller, I-TASSER and Robetta. Out of the 15 generated models of WSP, one was selected as the most reasonable quality model which had 82, 15.5, 1.9 and 0.5% of the amino acid residues in the most favored regions, additionally allowed regions, generously allowed regions and disallowed regions, respectively, based on the Ramachandran plot. High throughput virtual screening was performed via Autodock Vina with a library comprising 42,883 natural products from African and Chinese databases, including 23 identified anti-Onchocerca inhibitors. The top six compounds comprising ZINC000095913861, ZINC000095486235, ZINC000035941652, NANPDB4566, acetylaleuritolic acid and rhemannic acid had binding energies of −12.7, −11.1, −11.0, −11, −10.3 and −9.5 kcal/mol, respectively. Molecular dynamics simulations including molecular mechanics Poisson-Boltzmann (MMPBSA) calculations reinforced the stability of the ligand-WSP complexes and plausible binding mechanisms. The residues Arg45, Tyr135, Tyr148 and Phe195 were predicted as potential novel critical residues required for ligand binding in pocket 1. Acetylaleuritolic acid and rhemannic acid (lantedene A) have previously been shown to possess anti-onchocercal activity. This warrants the need to evaluate the anti-WSP activity of the identified molecules. The study suggests the exploitation of compounds which target both pockets 1 and 2, by investigating their potential for effective depletion of Wolbachia. These compounds were predicted to possess reasonably good pharmacological profiles with insignificant toxicity and as drug-like. The compounds were computed to possess biological activity including antibacterial, antiparasitic, anthelmintic and anti-rickettsials. The six natural products are potential novel antiwolbachial agents with insignificant toxicities which can be explored further as filaricides for onchocerciasis.

ZEAL: protein structure alignment based on shape similarity

MOTIVATION

Most protein-structure superimposition tools consider only Cartesian coordinates. Yet, much of biology happens on the surface of proteins, which is why proteins with shared ancestry and similar function often have comparable surface shapes. Superposition of proteins based on surface shape can enable comparison of highly divergent proteins, identify convergent evolution and enable detailed comparison of surface features and binding sites.

RESULTS

We present ZEAL, an interactive tool to superpose global and local protein structures based on their shape resemblance using 3D (Zernike-Canterakis) functions to represent the molecular surface. In a benchmark study of structures with the same fold, we show that ZEAL outperforms two other methods for shape-based superposition. In addition, alignments from ZEAL were of comparable quality to the coordinate-based superpositions provided by TM-align. For comparisons of proteins with limited sequence and backbone-fold similarity, where coordinate-based methods typically fail, ZEAL can often find alignments with substantial surface-shape correspondence. In combination with shape-based matching, ZEAL can be used as a general tool to study relationships between shape and protein function. We identify several categories of protein functions where global shape similarity is significantly more likely than expected by random chance, when comparing proteins with little similarity on the fold level. In particular, we find that global surface shape similarity is particular common among DNA binding proteins.

AVAILABILITY AND IMPLEMENTATION

ZEAL can be used online at https://andrelab.org/zeal or as a standalone program with command line or graphical user interface. Source files and installers are available at https://github.com/Andre-lab/ZEAL.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Immunoregulatory molecules secreted by Trichuris muris

Trichuris, whipworm nematode infections are prevalent in humans, domestic livestock and mammals. All share an epithelial dwelling niche and similar life cycle with the chronic infections that follow implying that immune evasion mechanisms are operating. Nematode excretory secretory (ES) products have been shown to be a rich source of immunomodulatory molecules for many species. The Trichuris muris model is a natural parasite of mice and has been used extensively to study host–parasite interactions and provides a tractable platform for investigation of the immunoregulatory capacity of whipworm ES. The present review details progress in identification of the composition of T. muris ES, immunomodulatory components and their potential mechanisms of action. The adult T. muris secretome is dominated by one protein with modulatory capacity although remains to be completely characterized. In addition, the secretome contains multiple other proteins and small molecules that have immunomodulatory potential, certainly by comparison to other Trichuris species. Moreover, T. muris-derived exosomes/exosome-like vesicles contain both protein and multiple miRNAs providing an alternate delivery process for molecules with the potential to modulate host immunity.

Mechanistic Insights into Side Effects of Troglitazone and Rosiglitazone Using a Novel Inverse Molecular Docking Protocol

Thiazolidinediones form drugs that treat insulin resistance in type 2 diabetes mellitus. Troglitazone represents the first drug from this family, which was removed from use by the FDA due to its hepatotoxicity. As an alternative, rosiglitazone was developed, but it was under the careful watch of FDA for a long time due to suspicion, that it causes cardiovascular diseases, such as heart failure and stroke. We applied a novel inverse molecular docking protocol to discern the potential protein targets of both drugs. Troglitazone and rosiglitazone were docked into predicted binding sites of >67,000 protein structures from the Protein Data Bank and examined. Several new potential protein targets with successfully docked troglitazone and rosiglitazone were identified. The focus was devoted to human proteins so that existing or new potential side effects could be explained or proposed. Certain targets of troglitazone such as 3-oxo-5-beta-steroid 4-dehydrogenase, neutrophil collagenase, stromelysin-1, and VLCAD were pinpointed, which could explain its hepatoxicity, with additional ones indicating that its application could lead to the treatment/development of cancer. Results for rosiglitazone discerned its interaction with members of the matrix metalloproteinase family, which could lead to cancer and neurodegenerative disorders. The concerning cardiovascular side effects of rosiglitazone could also be explained. We firmly believe that our results deepen the mechanistic understanding of the side effects of both drugs, and potentially with further development and research maybe even help to minimize them. On the other hand, the novel inverse molecular docking protocol on the other hand carries the potential to develop into a standard tool to predict possible cross-interactions of drug candidates potentially leading to adverse side effects.

Loop Grafting between Similar Local Environments for Fc-Silent Antibodies

Reduction of the affinity of the fragment crystallizable (Fc) region with immune receptors by substitution of one or a few amino acids, known as Fc-silencing, is an established approach to reduce the immune effector functions of monoclonal antibody therapeutics. This approach to Fc-silencing, however, is problematic as it can lead to instability and immunogenicity of the developed antibodies. We evaluated loop grafting as a novel approach to Fc-silencing in which the Fc loops responsible for immune receptor binding were replaced by loops of up to 20 amino acids from similar local environments in other human and mouse antibodies. Molecular dynamics simulations of the designed variants of an Fc region in a complex with the immune receptor FcγIIIa confirmed that loop grafting potentially leads to a significant reduction in the binding of the antibody variants to the receptor, while retaining their stability. In comparison, standard variants with less than eight substituted amino acids showed possible instability and a lower degree of Fc-silencing due to the occurrence of compensatory interactions. The presented approach to Fc-silencing is general and could be used to modulate undesirable side effects of other antibody therapeutics without affecting their stability or increasing their immunogenicity.

In Silico Laboratory: Tools for Similarity-Based Drug Discovery

Computational methods that predict and evaluate binding of ligands to receptors implicated in different pathologies have become crucial in modern drug design and discovery. Here, we describe protocols for using the recently developed package of computational tools for similarity-based drug discovery. The ProBiS stand-alone program and web server allow superimposition of protein structures against large protein databases and predict ligands based on detected binding site similarities. GenProBiS allows mapping of human somatic missense mutations related to cancer and non-synonymous single nucleotide polymorphisms and subsequent visual exploration of specific interactions in connection to these mutations. We describe protocols for using LiSiCA, a fast ligand-based virtual screening software that enables easy screening of large databases containing billions of small molecules. Finally, we show the use of BoBER, a web interface that enables user-friendly access to a large database of bioisosteric and scaffold hopping replacements.

Updates to Binding MOAD (Mother of All Databases): Polypharmacology Tools and Their Utility in Drug Repurposing

The goal of Binding MOAD is to provide users with a data set focused on high-quality x-ray crystal structures that have been solved with biologically relevant ligands bound. Where available, experimental binding affinities (K_a, K_d, K_i, IC₅₀) are provided from the primary literature of the crystal structure. The database has been updated regularly since 2005, and this most recent update has added nearly 7000 new structures (growth of 21%). MOAD currently contains 32,747 structures, composed of 9117 protein families and 16,044 unique ligands. The data are freely available on www.BindingMOAD.org. This paper outlines updates to the data in Binding MOAD as well as improvements made to both the website and its contents. The NGL viewer has been added to improve visualization of the ligands and protein structures. MarvinJS has been implemented, over the outdated MarvinView, to work with JChem for small molecule searching in the database. To add tools for predicting polypharmacology, we have added information about sequence, binding-site, and ligand similarity between entries in the database. A main premise behind polypharmacology is that similar binding sites will bind similar ligands. The large amount of protein-ligand information available in Binding MOAD allows us to compute pairwise ligand and binding-site similarities. Lists of similar ligands and similar binding sites have been added to allow users to identify potential polypharmacology pairs. To show the utility of the polypharmacology data, we detail a few examples from Binding MOAD of drug repurposing targets with their respective similarities.

Polypharmacological study of Ceritinib using a structure based in silico approach

Drug repurposing has gained mass recognition over the past few years as it has paved new therapeutic applications for already approved FDA drugs. It focuses on finding new molecular targets of drugs for medical uses different than the one originally proposed. Ceritinib, an Anaplastic Lymphoma Kinase (ALK) inhibitor is given orally in the treatment of non-small cell lung cancer (NSCLC). This treatment has been reported to be associated with a number of side effects such as hyperglycemia, convulsion, pneumonitis etc. The side effects are usually due to the unintended interaction of the drug with other protein targets. In silico polypharmacological studies of Ceritinib suggests that it binds to multiple targets other than the intended one which may largely be due to different proteins possessing similar binding sites. ProBis server was used to retrieve probable off-targets of Ceritinib based on presence of structurally similar protein binding sites as that of ALK. Ceritinib was found to bind effectively to three proteins namely Lymphocyte Cell-Specific Protein-Tyrosine Kinase, Tropomyosin receptor kinase B and Aurora kinase B having favorable binding energies and inhibition constants, with no reported side-effects as compared to their marketed drugs. Therefore, it is concluded from the present study that Ceritinib may act as an effective therapeutic target against its polypharmacological targets.

Discovery of Novel Potential Human Targets of Resveratrol by Inverse Molecular Docking

Resveratrol is a polyphenol known for its antioxidant and anti-inflammatory properties, which support its use as a treatment for variety of diseases. There are already known connections of resveratrol to chemoprevention of cancer because of its ability to prevent tumor initiation and inhibit tumor promotion and progression. Resveratrol is also believed to be important in cardiovascular diseases and neurological disorders, such as Alzheimer's disease. Using an inverse molecular docking approach, we sought to find new potential targets of resveratrol. Docking of resveratrol into each ProBiS predicted binding site of >38 000 protein structures from the Protein Data Bank was examined, and a number of novel potential targets into which resveratrol was docked successfully were found. These explain known actions or predict new effects of resveratrol. The results included three human proteins that are already known to bind resveratrol. A majority of proteins discovered however have no already described connections with resveratrol. We report new potential target human proteins and proteins connected with different organisms into which resveratrol can dock. Our results reveal previously unknown potential target human proteins, whose connection with cardiovascular and neurological disorders could lead to new potential treatments for variety of diseases. We believe that our research could help in future experimental studies on revestratol bioactivity in humans.

Repurposing Drugs Based on Evolutionary Relationships Between Targets of Approved Drugs and Proteins of Interest

Drug repurposing has garnered much interest as an effective method for drug development among biopharmaceutical companies. The availability of information on complete sequences of genomes and their associated biological data, genotype-phenotype-disease relationships, and properties of small molecules offers opportunities to explore the repurpose-able potential of existing pharmacopoeia. This method gains further importance, especially, in the context of development of drugs against infectious diseases, some of which pose serious complications due to emergence of drug-resistant pathogens. In this article, we describe computational means to achieve potential repurpose-able drug candidates that may be used against infectious diseases by exploring evolutionary relationships between established targets of FDA-approved drugs and proteins of pathogen of interest.

Inverse Molecular Docking as a Novel Approach to Study Anticarcinogenic and Anti-Neuroinflammatory Effects of Curcumin

Research efforts are placing an ever increasing emphasis on identifying signal transduction pathways related to the chemopreventive activity of curcumin. Its anticarcinogenic effects are presumably mediated by the regulation of signaling cascades, including nuclear factor κB (NF-κB), activator protein 1 (AP-1), and mitogen-activated protein kinases (MAPK). By modulating signal transduction pathways, curcumin induces apoptosis in malignant cells, thus inhibiting cancer development and progression. Due to the lack of mechanistic insight in the scientific literature, we developed a novel inverse molecular docking protocol based on the CANDOCK algorithm. For the first time, we performed inverse molecular docking of curcumin into a collection of 13,553 available human protein structures from the Protein Data Bank resulting in prioritized target proteins of curcumin. Our predictions were in agreement with the scientific literature and confirmed that curcumin binds to folate receptor β, DNA (cytosine-5)-methyltransferase 3A, metalloproteinase-2, mitogen-activated protein kinase 9, epidermal growth factor receptor and apoptosis-inducing factor 1. We also identified new potential protein targets of curcumin, namely deoxycytidine kinase, NAD-dependent protein deacetylase sirtuin-1 and -2, ecto-5'-nucleotidase, core histone macro-H2A.1, tyrosine-protein phosphatase non-receptor type 11, macrophage colony-stimulating factor 1 receptor, GTPase HRas, aflatoxin B1 aldehyde reductase member 3, aldo-keto reductase family 1 member C3, amiloride-sensitive amine oxidase, death-associated protein kinase 2 and tryptophan-tRNA ligase, that may all play a crucial role in its observed anticancer effects. Moreover, our inverse docking results showed that curcumin potentially binds also to the proteins cAMP-specific 3',5'-cyclic phosphodiesterase 4D and 17-β-hydroxysteroid dehydrogenase type 10, which provides a new explanation for its efficiency in the treatment of Alzheimer's disease. We firmly believe that our computational results will complement and direct future experimental studies on curcumin's anticancer activity as well as on its therapeutic effects against Alzheimer's disease.

Common structural and pharmacophoric features of mPGES-1 and LTC4S

Prostaglandins and leukotrienes are produced in the COX and 5-LOX pathways of the inflammatory process. The current drugs target the upstream enzymes of either of the two pathways, leading to side effects. We have attempted to target the downstream enzymes simultaneously. Two compounds 2 and 3 (10 μM), identified by virtual screening, inhibited mPGES-1 activity by 53.4 ± 4.0 and 53.9 ± 8.1%, respectively. Structural and pharmacophore studies revealed a set of common residues between LTC4S and mPGES-1 as well as four-point pharmacophore mapping onto the inhibitors of both these enzymes as well as 2 and 3. These structural and pharmacophoric features may be exploited for ligand- and structure-based screening of inhibitors and designing of dual inhibitors.

BoBER: web interface to the base of bioisosterically exchangeable replacements

We describe a novel freely available web server Base of Bioisosterically Exchangeable Replacements (BoBER), which implements an interface to a database of bioisosteric and scaffold hopping replacements. Bioisosterism and scaffold hopping are key concepts in drug design and optimization, and can be defined as replacements of biologically active compound's fragments with other fragments to improve activity, reduce toxicity, change bioavailability or to diversify the scaffold space. Our web server enables fast and user-friendly searches for bioisosteric and scaffold replacements which were obtained by mining the whole Protein Data Bank. The working of the web server is presented on an existing MurF inhibitor as example. BoBER web server enables medicinal chemists to quickly search for and get new and unique ideas about possible bioisosteric or scaffold hopping replacements that could be used to improve hit or lead drug-like compounds.

Ligand-based Modeling for the Prediction of Pharmacophore Features for Multi-targeted Inhibition of the Arachidonic Acid Cascade

The single-target drugs against the arachidonic acid inflammatory pathway are associated with serious side effects, hence, as a first step towards multi-target drugs, we have studied the pharmacophoric features common to the inhibitors of 5-lipoxygenase-activating protein (FLAP), microsomal prostaglandin E-synthase 1 (mPGES-1) and leukotriene A4 hydrolase (LTA4H). FLAP and mPGES-1 shared subfamily-specific positions (SSPs) and four mPGES-1 inhibitors binding to them mapped onto the pharmacophore derived from FLAP inhibitors (Ph-FLAP). The reactions of mPGES-1 and LTA4H had high structural similarity. The pharmacophore derived from two substrate mimic inhibitors of LTA4H (Ph-LTA4H) also mapped onto three mPGES-1 inhibitors. Screening of in-house database for Ph-FLAP and Ph-LTA4H identified one compound, C1. It inhibited the production of the mPGES-1 product, prostaglandin E2 (PGE2) by 97.8±1.6 % at 50 μM in HeLa cells and can be a starting point for designing molecules inhibiting all three targets simultaneously.

Targeting on poly(ADP-ribose) polymerase activity with DNA-damaging hybrid lactam-steroid alkylators in wild-type and BRCA1-mutated ovarian cancer cells

Conjugated lactam-steroid alkylators (LSA) have been shown to exhibit superior activity at controlling cancer models and overlap drug resistance to conventional chemjournalapy. Hybrid LSA combine two active compounds in a single molecule and incorporate modified steroids bearing lactam moiety in one or more steroid rings functioning as vectors for cytotoxic agents. We first describe a novel class of LSA that generate excellent anticancer activity against UWB1.289 and UWB1.289 + BRCA1 human ovarian cancer cell lines. Both UWB1.289 and UWB1.289 + BRCA1 cells carry mutations in the tumor suppressor gene TP53 while UWB1.289 cell line carries a germline BRCA1 mutation. In vitro, in vivo, and in silico, experimental methods were utilized to determine the poly(ADP-ribose) polymerases (PARPs) activity and mRNA transcription, DNA damage, cytostatic and cytotoxic effects, and virtual molecular interactions, in order to study the molecular mechanisms of activity of the tested LSA. LSA produce anticancer activity through dual action by combining the direct induction of cellular DNA damage with the inhibition of PARP activity and consecutive DNA repair activity. BRCA1-mutated UWB1.289 ovarian cancer cells with defective PARP-oriented repair mechanism show significantly higher sensitivity to these agents. Combined drug effect on DNA damage and repair is a novel approach in cancer therapeutics.

ProBiS tools (algorithm, database, and web servers) for predicting and modeling of biologically interesting proteins

ProBiS (Protein Binding Sites) Tools consist of algorithm, database, and web servers for prediction of binding sites and protein ligands based on the detection of structurally similar binding sites in the Protein Data Bank. In this article, we review the operations that ProBiS Tools perform, provide comments on the evolution of the tools, and give some implementation details. We review some of its applications to biologically interesting proteins. ProBiS Tools are freely available at http://probis.cmm.ki.si and http://probis.nih.gov.

The Transcriptome of the Zoanthid Protopalythoa variabilis (Cnidaria, Anthozoa) Predicts a Basal Repertoire of Toxin-like and Venom-Auxiliary Polypeptides

Protopalythoa is a zoanthid that, together with thousands of predominantly marine species, such as hydra, jellyfish, and sea anemones, composes the oldest eumetazoan phylum, i.e., the Cnidaria. Some of these species, such as sea wasps and sea anemones, are highly venomous organisms that can produce deadly toxins for preying, for defense or for territorial disputes. Despite the fact that hundreds of organic and polypeptide toxins have been characterized from sea anemones and jellyfish, practically nothing is known about the toxin repertoire in zoanthids. Here, based on a transcriptome analysis of the zoanthid Protopalythoa variabilis, numerous predicted polypeptides with canonical venom protein features are identified. These polypeptides comprise putative proteins from different toxin families: neurotoxic peptides, hemostatic and hemorrhagic toxins, membrane-active (pore-forming) proteins, protease inhibitors, mixed-function venom enzymes, and venom auxiliary proteins. The synthesis and functional analysis of two of these predicted toxin products, one related to the ShK/Aurelin family and the other to a recently discovered anthozoan toxin, displayed potent in vivo neurotoxicity that impaired swimming in larval zebrafish. Altogether, the complex array of venom-related transcripts that are identified in P. variabilis, some of which are first reported in Cnidaria, provides novel insight into the toxin distribution among species and might contribute to the understanding of composition and evolution of venom polypeptides in toxiferous animals.

Linker-switch approach towards new ATP binding site inhibitors of DNA gyrase B

Due to increasing emergence of bacterial resistance, compounds with new mechanisms of action are of paramount importance. One of modestly researched therapeutic targets in the field of antibacterial discovery is DNA gyrase B. In the present work we synthesized a focused library of potential DNA gyrase B inhibitors composed of two key pharmacophoric moieties linked by three types of sp³-rich linkers to obtain three structural classes of compounds. Using molecular docking, molecular dynamics and analysis of conserved waters in the binding site, we identified a favourable binding mode for piperidin-4-yl and 4-cyclohexyl pyrrole-2-carboxamides while predicting unfavourable interactions with the active site for piperazine pyrrole-2-carboxamides. Biological evaluation of prepared compounds on isolated enzyme DNA gyrase B confirmed our predictions and afforded multiple moderately potent inhibitors of DNA gyrase B. Namely trans-4-(4,5-dibromo-1H-pyrrole-2-carboxamide)cyclohexyl)glycine and 4-(4-(3,4-dichloro-5-methyl-1H-pyrrole-2-carboxamido)piperidin-1-yl)-4-oxobutanoic acid with an IC₅₀ value of 16 and 0.5 μM respectively.

Landscape of protein-small ligand binding modes

Elucidating the mechanisms of specific small-molecule (ligand) recognition by proteins is a long-standing conundrum. While the structures of these molecules, proteins and ligands, have been extensively studied, protein-ligand interactions, or binding modes, have not been comprehensively analyzed. Although methods for assessing similarities of binding site structures have been extensively developed, the methods for the computational treatment of binding modes have not been well established. Here, we developed a computational method for encoding the information about binding modes as graphs, and assessing their similarities. An all-against-all comparison of 20,040 protein-ligand complexes provided the landscape of the protein-ligand binding modes and its relationships with protein- and chemical spaces. While similar proteins in the same SCOP Family tend to bind relatively similar ligands with similar binding modes, the correlation between ligand and binding similarities was not very high (R(2)  = 0.443). We found many pairs with novel relationships, in which two evolutionally distant proteins recognize dissimilar ligands by similar binding modes (757,474 pairs out of 200,790,780 pairs were categorized into this relationship, in our dataset). In addition, there were an abundance of pairs of homologous proteins binding to similar ligands with different binding modes (68,217 pairs). Our results showed that many interesting relationships between protein-ligand complexes are still hidden in the structure database, and our new method for assessing binding mode similarities is effective to find them.

Similarity Search of Flexible 3D Molecules Combining Local and Global Shape Descriptors

In this paper, a framework for shape-based similarity search of 3D molecular structures is presented. The proposed framework exploits simultaneously the discriminative capabilities of a global, a local, and a hybrid local-global shape feature to produce a geometric descriptor that achieves higher retrieval accuracy than each feature does separately. Global and hybrid features are extracted using pairwise computations of diffusion distances between the points of the molecular surface, while the local feature is based on accumulating pairwise relations among oriented surface points into local histograms. The local features are integrated into a global descriptor vector using the bag-of-features approach. Due to the intrinsic property of its constituting shape features to be invariant to articulations of the 3D objects, the framework is appropriate for similarity search of flexible 3D molecules, while at the same time it is also accurate in retrieving rigid 3D molecules. The proposed framework is evaluated in flexible and rigid shape matching of 3D protein structures as well as in shape-based virtual screening of large ligand databases with quite promising results.

Role of magnesium ions in the reaction mechanism at the interface between Tm1631 protein and its DNA ligand

A protein, Tm1631 from the hyperthermophilic organism Thermotoga maritima belongs to a domain of unknown function protein family. It was predicted that Tm1631 binds with the DNA and that the Tm1631–DNA complex is an endonuclease repair system with a DNA repair function (Konc et al. PLoS Comput Biol 9(11): e1003341, 2013). We observed that the severely bent, strained DNA binds to the protein for the entire 90 ns of classical molecular dynamics (MD) performed; we could observe no significant changes in the most distorted region of the DNA, where the cleavage of phosphodiester bond occurs. In this article, we modeled the reaction mechanism at the interface between Tm1631 and its proposed ligand, the DNA molecule, focusing on cleavage of the phosphodiester bond. After addition of two Mg²⁺ ions to the reaction center and extension of classical MD by 50 ns (totaling 140 ns), the DNA ligand stayed bolted to the protein. Results from density functional theory quantum mechanics/molecular mechanics (QM/MM) calculations suggest that the reaction is analogous to known endonuclease mechanisms: an enzyme reaction mechanism with two Mg²⁺ ions in the reaction center and a pentacovalent intermediate. The minimum energy pathway profile shows that the phosphodiester bond cleavage step of the reaction is kinetically controlled and not thermodynamically because of a lack of any energy barrier above the accuracy of the energy profile calculation. The role of ions is shown by comparing the results with the reaction mechanisms in the absence of the Mg²⁺ ions where there is a significantly higher reaction barrier than in the presence of the Mg²⁺ ions.Graphical abstract

Comparison of in silico tools for binding site prediction applied for structure-based design of autolysin inhibitors

Autolysin E (AtlE) is a bacteriolytic enzyme which plays an important role in division and growth of bacterial cells and therefore represents a promising potential drug target. Its 3D structure has been recently elucidated. We used in silico prediction tools to study substrate or ligand (inhibitor) binding regions of AtlE. We applied several freely available tools and a commercial tool for binding site identification and compared results of the prediction. Calculation time, number of predictions and output data provided by specific software vary according to the different approaches utilized by specific method categories. Despite different approaches, binding sites in similar locations on the protein were predicted. Specific amino acid residues that form these binding sites were predicted as binding residues. The predicted residues, especially those with predicted highest conservation score, could theoretically have catalytic and binding properties. According to our results, we assume that E138, which has the highest conservation score, is the catalytic residue and F161, G162 and Y224, which are also highly conserved, are responsible for substrate binding. Ligands developed with binding specificity towards these residues could inhibit the catalysis and binding of the substrate of AtlE. The molecules with inhibitory potency could therefore represent potential new antibacterial agents.

Polypharmacology in Drug Development: A Minireview of Current Technologies

Polypharmacology, the process in which a single drug is able to bind to multiple targets specifically and simultaneously, is an emerging paradigm in drug development. The potency of a given drug can be increased through the engagement of multiple targets involved in a certain disease. Polypharmacology may also help identify novel applications of existing drugs through drug repositioning. However, many problems and challenges remain in this field. Rather than covering all aspects of polypharmacology, this Minireview is focused primarily on recently reported techniques, from bioinformatics technologies to cheminformatics approaches as well as text-mining-based methods, all of which have made significant contributions to the research of polypharmacology.

MS3ALIGN: an efficient molecular surface aligner using the topology of surface curvature

Background

Aligning similar molecular structures is an important step in the process of bio-molecular structure and function analysis. Molecular surfaces are simple representations of molecular structure that are easily constructed from various forms of molecular data such as 3D atomic coordinates (PDB) and Electron Microscopy (EM) data.

Methods

We present a Multi-Scale Morse-Smale Molecular-Surface Alignment tool, MS3ALIGN, which aligns molecular surfaces based on significant protrusions on the molecular surface. The input is a pair of molecular surfaces represented as triangle meshes. A key advantage of MS3ALIGN is computational efficiency that is achieved because it processes only a few carefully chosen protrusions on the molecular surface. Furthermore, the alignments are partial in nature and therefore allows for inexact surfaces to be aligned.

Results

The method is evaluated in four settings. First, we establish performance using known alignments with varying overlap and noise values. Second, we compare the method with SurfComp, an existing surface alignment method. We show that we are able to determine alignments reported by SurfComp, as well as report relevant alignments not found by SurfComp. Third, we validate the ability of MS3ALIGN to determine alignments in the case of structurally dissimilar binding sites. Fourth, we demonstrate the ability of MS3ALIGN to align iso-surfaces derived from cryo-electron microscopy scans.

Conclusions

We have presented an algorithm that aligns Molecular Surfaces based on the topology of surface curvature. A webserver and standalone software implementation of the algorithm available at http://vgl.serc.iisc.ernet.in/ms3align.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0874-8) contains supplementary material, which is available to authorized users.

Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods

Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein-ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein-ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein-ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

Different combinations of atomic interactions predict protein-small molecule and protein-DNA/RNA affinities with similar accuracy

Interactions between proteins and other molecules play essential roles in all biological processes. Although it is widely held that a protein's ligand specificity is determined primarily by its three‐dimensional structure, the general principles by which structure determines ligand binding remain poorly understood. Here we use statistical analyses of a large number of protein−ligand complexes with associated binding‐affinity measurements to quantitatively characterize how combinations of atomic interactions contribute to ligand affinity. We find that there are significant differences in how atomic interactions determine ligand affinity for proteins that bind small chemical ligands, those that bind DNA/RNA and those that interact with other proteins. Although protein‐small molecule and protein‐DNA/RNA binding affinities can be accurately predicted from structural data, models predicting one type of interaction perform poorly on the others. Additionally, the particular combinations of atomic interactions required to predict binding affinity differed between small‐molecule and DNA/RNA data sets, consistent with the conclusion that the structural bases determining ligand affinity differ among interaction types. In contrast to what we observed for small‐molecule and DNA/RNA interactions, no statistical models were capable of predicting protein−protein affinity with >60% correlation. We demonstrate the potential usefulness of protein‐DNA/RNA binding prediction as a possible tool for high‐throughput virtual screening to guide laboratory investigations, suggesting that quantitative characterization of diverse molecular interactions may have practical applications as well as fundamentally advancing our understanding of how molecular structure translates into function. Proteins 2015; 83:2100–2114. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Considerations of Protein Subpockets in Fragment-Based Drug Design

While the fragment-based drug design approach continues to gain importance, gaps in the tools and methods available in the identification and accurate utilization of protein subpockets have limited the scope. The importance of these features of small molecule-protein recognition is highlighted with several examples. A generalized solution for the identification of subpockets and corresponding chemical fragments remains elusive, but there are numerous advancements in methods that can be used in combination to address subpockets. Finally, additional examples of approaches that consider the relative importance of small-molecule co-dependence of protein conformations are highlighted to emphasize an increased significance of subpockets, especially at protein interfaces.

Evolution of Macromolecular Docking Techniques: The Case Study of Nickel and Iron Metabolism in Pathogenic Bacteria

The interaction between macromolecules is a fundamental aspect of most biological processes. The computational techniques used to study protein-protein and protein-nucleic acid interactions have evolved in the last few years because of the development of new algorithms that allow the a priori incorporation, in the docking process, of experimentally derived information, together with the possibility of accounting for the flexibility of the interacting molecules. Here we review the results and the evolution of the techniques used to study the interaction between metallo-proteins and DNA operators, all involved in the nickel and iron metabolism of pathogenic bacteria, focusing in particular on Helicobacter pylori (Hp). In the first part of the article we discuss the methods used to calculate the structure of complexes of proteins involved in the activation of the nickel-dependent enzyme urease. In the second part of the article, we concentrate on two applications of protein-DNA docking conducted on the transcription factors HpFur (ferric uptake regulator) and HpNikR (nickel regulator). In both cases we discuss the technical expedients used to take into account the conformational variability of the multi-domain proteins involved in the calculations.

A Novel Antiviral Target Structure Involved in the RNA Binding, Dimerization, and Nuclear Export Functions of the Influenza A Virus Nucleoprotein

Developing antiviral therapies for influenza A virus (IAV) infection is an ongoing process because of the rapid rate of antigenic mutation and the emergence of drug-resistant viruses. The ideal strategy is to develop drugs that target well-conserved, functionally restricted, and unique surface structures without affecting host cell function. We recently identified the antiviral compound, RK424, by screening a library of 50,000 compounds using cell-based infection assays. RK424 showed potent antiviral activity against many different subtypes of IAV in vitro and partially protected mice from a lethal dose of A/WSN/1933 (H1N1) virus in vivo. Here, we show that RK424 inhibits viral ribonucleoprotein complex (vRNP) activity, causing the viral nucleoprotein (NP) to accumulate in the cell nucleus. In silico docking analysis revealed that RK424 bound to a small pocket in the viral NP. This pocket was surrounded by three functionally important domains: the RNA binding groove, the NP dimer interface, and nuclear export signal (NES) 3, indicating that it may be involved in the RNA binding, oligomerization, and nuclear export functions of NP. The accuracy of this binding model was confirmed in a NP-RK424 binding assay incorporating photo-cross-linked RK424 affinity beads and in a plaque assay evaluating the structure-activity relationship of RK424. Surface plasmon resonance (SPR) and pull-down assays showed that RK424 inhibited both the NP-RNA and NP-NP interactions, whereas size exclusion chromatography showed that RK424 disrupted viral RNA-induced NP oligomerization. In addition, in vitro nuclear export assays confirmed that RK424 inhibited nuclear export of NP. The amino acid residues comprising the NP pocket play a crucial role in viral replication and are highly conserved in more than 7,000 NP sequences from avian, human, and swine influenza viruses. Furthermore, we found that the NP pocket has a surface structure different from that of the pocket in host molecules. Taken together, these results describe a promising new approach to developing influenza virus drugs that target a novel pocket structure within NP.

Influenza A virus nucleoprotein (NP) is a highly conserved multifunctional protein that plays an essential role in infection by all subtypes of influenza A virus, making it an attractive target for new antiviral drugs. NP regulates viral polymerase activity and transport of the viral genome into/from the host cell nucleus by forming the viral ribonucleoprotein complex (vRNP). Because NP regulates replication and transcription of the viral genome in addition to its role in nuclear export (all of which are essential for the production of viral progeny), it is a promising drug target. Here, we used the antiviral compound RK424 to identify a novel pocket structure within NP. This structure encompassed three different functional domains that are involved in the above-mentioned replication steps. RK424 inhibits viral genome replication/transcription and nuclear export of NP by destabilizing the NP oligomer and inhibiting the binding of chromosome region maintenance 1 (CRM1) to NP via nuclear export signal (NES) 3, which is located in close proximity to the NP pocket. Taken together, these findings suggest that this small NP pocket is a novel antiviral target.

N-Phenyl-4,5-dibromopyrrolamides and N-Phenylindolamides as ATP Competitive DNA Gyrase B Inhibitors: Design, Synthesis, and Evaluation

Bacterial DNA gyrase is a well-known and validated target in the design of antibacterial drugs. However, inhibitors of its ATP binding subunit, DNA gyrase B (GyrB), have so far not reached clinical use. In the present study, three different series of N-phenyl-4,5-dibromopyrrolamides and N-phenylindolamides were designed and prepared as potential DNA gyrase B inhibitors. The IC50 values of compounds on DNA gyrase from Escherichia coli were in the low micromolar range, with the best compound, (4-(4,5-dibromo-1H-pyrrole-2-carboxamido)benzoyl)glycine (18a), displaying an IC50 of 450 nM. For this compound, a high-resolution crystal structure in complex with E. coli DNA gyrase B was obtained, revealing details of its binding mode within the active site. The binding affinities of three compounds with GyrB were additionally evaluated by surface plasmon resonance, and the results were in good agreement with the determined enzymatic activities. For the most promising compounds, the inhibitory activities against DNA gyrase from Staphylococcus aureus and topoisomerases IV from E. coli and S. aureus were determined. Antibacterial activities of the most potent compounds of each series were evaluated against two Gram-positive and two Gram-negative bacterial strains. The results obtained in this study provide valuable information on the binding mode and structure-activity relationship of N-phenyl-4,5-dibromopyrrolamides and N-phenylindolamides as promising classes of ATP competitive GyrB inhibitors.

Comparative interactions of withanolides and sterols with two members of sterol glycosyltransferases from Withania somnifera

Background

Sterol glycosyltransferases (SGTs) are ubiquitous but one of the most diverse group of enzymes of glycosyltransferases family. Members of this family modulate physical and chemical properties of secondary plant products important for various physiological processes. The role of SGTs has been demonstrated in the biosynthesis of pharmaceutically important molecules of medicinal plants like Withania somnifera.

Results

Analysis suggested conserved behaviour and high similarity in active sites of WsSGTs with other plant GTs. Substrate specificity of WsSGTs were analysed through docking performance of WsSGTs with different substrates (sterols and withanolides). Best docking results of WsSGTL1 in the form of stable enzyme-substrate complex having lowest binding energies were obtained with brassicasterol, transandrosteron and WsSGTL4 with solasodine, stigmasterol and 24-methylene cholesterol.

Conclusion

This study reveals topological characters and conserved nature of two SGTs from W. somnifera (WsSGTs) i.e. WsSGTL1 and WsSGTL4. However, besides being ubiquitous in nature and with broad substrate specificity, difference between WsSGTL1 and WsSGTL4 is briefly described by difference in stability (binding energy) of enzyme-substrate complexes through comparative docking.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0563-7) contains supplementary material, which is available to authorized users.

Combined rational design and a high throughput screening platform for identifying chemical inhibitors of a Ras-activating enzyme

The Ras family small GTPases regulate multiple cellular processes, including cell growth, survival, movement, and gene expression, and are intimately involved in cancer pathogenesis. Activation of these small GTPases is catalyzed by a special class of enzymes, termed guanine nucleotide exchange factors (GEFs). Herein, we developed a small molecule screening platform for identifying lead hits targeting a Ras GEF enzyme, SOS1. We employed an ensemble structure-based virtual screening approach in combination with a multiple tier high throughput experimental screen utilizing two complementary fluorescent guanine nucleotide exchange assays to identify small molecule inhibitors of GEF catalytic activity toward Ras. From a library of 350,000 compounds, we selected a set of 418 candidate compounds predicted to disrupt the GEF-Ras interaction, of which dual wavelength GDP dissociation and GTP-loading experimental screening identified two chemically distinct small molecule inhibitors. Subsequent biochemical validations indicate that they are capable of dose-dependently inhibiting GEF catalytic activity, binding to SOS1 with micromolar affinity, and disrupting GEF-Ras interaction. Mutagenesis studies in conjunction with structure-activity relationship studies mapped both compounds to different sites in the catalytic pocket, and both inhibited Ras signaling in cells. The unique screening platform established here for targeting Ras GEF enzymes could be broadly useful for identifying lead inhibitors for a variety of small GTPase-activating GEF reactions.

A Novel Algorithm for Enhanced Structural Motif Matching in Proteins

As widely discussed in literature, spatial patterns of amino acids, so-called structural motifs, play an important role in protein function. The functionally responsible part of proteins often lies in an evolutionarily highly conserved spatial arrangement of only a few amino acids, which are held in place tightly by the rest of the structure. Those recurring amino acid arrangements can be seen as patterns in the three-dimensional space and are known as structural motifs. In general, these motifs can mediate various functional interactions, such as DNA/RNA targeting and binding, ligand interactions, substrate catalysis, and stabilization of the protein structure. Hence, characterizing and identifying such conserved structural motifs can contribute to the understanding of structure-function relationships. Therefore, and because of the rapidly increasing number of solved protein structures, it is highly desirable to identify, understand, and moreover to search for structurally scattered amino acid motifs. This work aims at the development and the implementation of a novel and robust matching algorithm to detect structural motifs in large sets of target structures. The proposed methods were combined and implemented to a feature-rich and easy-to-use command line software tool written in Java.

Biochemical functional predictions for protein structures of unknown or uncertain function

With the exponential growth in the determination of protein sequences and structures via genome sequencing and structural genomics efforts, there is a growing need for reliable computational methods to determine the biochemical function of these proteins. This paper reviews the efforts to address the challenge of annotating the function at the molecular level of uncharacterized proteins. While sequence- and three-dimensional-structure-based methods for protein function prediction have been reviewed previously, the recent trends in local structure-based methods have received less attention. These local structure-based methods are the primary focus of this review. Computational methods have been developed to predict the residues important for catalysis and the local spatial arrangements of these residues can be used to identify protein function. In addition, the combination of different types of methods can help obtain more information and better predictions of function for proteins of unknown function. Global initiatives, including the Enzyme Function Initiative (EFI), COMputational BRidges to EXperiments (COMBREX), and the Critical Assessment of Function Annotation (CAFA), are evaluating and testing the different approaches to predicting the function of proteins of unknown function. These initiatives and global collaborations will increase the capability and reliability of methods to predict biochemical function computationally and will add substantial value to the current volume of structural genomics data by reducing the number of absent or inaccurate functional annotations.

PoSSuM v.2.0: data update and a new function for investigating ligand analogs and target proteins of small-molecule drugs

PoSSuM (http://possum.cbrc.jp/PoSSuM/) is a database for detecting similar small-molecule binding sites on proteins. Since its initial release in 2011, PoSSuM has grown to provide information related to 49 million pairs of similar binding sites discovered among 5.5 million known and putative binding sites. This enlargement of the database is expected to enhance opportunities for biological and pharmaceutical applications, such as predictions of new functions and drug discovery. In this release, we have provided a new service named PoSSuM drug search (PoSSuMds) at http://possum.cbrc.jp/PoSSuM/drug_search/, in which we selected 194 approved drug compounds retrieved from ChEMBL, and detected their known binding pockets and pockets that are similar to them. Users can access and download all of the search results via a new web interface, which is useful for finding ligand analogs as well as potential target proteins. Furthermore, PoSSuMds enables users to explore the binding pocket universe within PoSSuM. Additionally, we have improved the web interface with new functions, including sortable tables and a viewer for visualizing and downloading superimposed pockets.

The crystal structure of archaeal serine hydroxymethyltransferase reveals idiosyncratic features likely required to withstand high temperatures

Serine hydroxymethyltransferases (SHMTs) play an essential role in one-carbon unit metabolism and are used in biomimetic reactions. We determined the crystal structure of free (apo) and pyridoxal-5'-phosphate-bound (holo) SHMT from Methanocaldococcus jannaschii, the first from a hyperthermophile, from the archaea domain of life and that uses H₄MPT as a cofactor, at 2.83 and 3.0 Å resolution, respectively. Idiosyncratic features were observed that are likely to contribute to structure stabilization. At the dimer interface, the C-terminal region folds in a unique fashion with respect to SHMTs from eubacteria and eukarya. At the active site, the conserved tyrosine does not make a cation-π interaction with an arginine like that observed in all other SHMT structures, but establishes an amide-aromatic interaction with Asn257, at a different sequence position. This asparagine residue is conserved and occurs almost exclusively in (hyper)thermophile SHMTs. This led us to formulate the hypothesis that removal of frustrated interactions (such as the Arg-Tyr cation-π interaction occurring in mesophile SHMTs) is an additional strategy of adaptation to high temperature. Both peculiar features may be tested by designing enzyme variants potentially endowed with improved stability for applications in biomimetic processes.

Proteins comparison through probabilistic optimal structure local alignment

Multiple local structure comparison helps to identify common structural motifs or conserved binding sites in 3D structures in distantly related proteins. Since there is no best way to compare structures and evaluate the alignment, a wide variety of techniques and different similarity scoring schemes have been proposed. Existing algorithms usually compute the best superposition of two structures or attempt to solve it as an optimization problem in a simpler setting (e.g., considering contact maps or distance matrices). Here, we present PROPOSAL (PROteins comparison through Probabilistic Optimal Structure local ALignment), a stochastic algorithm based on iterative sampling for multiple local alignment of protein structures. Our method can efficiently find conserved motifs across a set of protein structures. Only the distances between all pairs of residues in the structures are computed. To show the accuracy and the effectiveness of PROPOSAL we tested it on a few families of protein structures. We also compared PROPOSAL with two state-of-the-art tools for pairwise local alignment on a dataset of manually annotated motifs. PROPOSAL is available as a Java 2D standalone application or a command line program at http://ferrolab.dmi.unict.it/proposal/proposal.html.

Structural basis for the recognition in an idiotype-anti-idiotype antibody complex related to celiac disease

Anti-idiotype antibodies have potential therapeutic applications in many fields, including autoimmune diseases. Herein we report the isolation and characterization of AIM2, an anti-idiotype antibody elicited in a mouse model upon expression of the celiac disease-specific autoantibody MB2.8 (directed against the main disease autoantigen type 2 transglutaminase, TG2). To characterize the interaction between the two antibodies, a 3D model of the MB2.8-AIM2 complex has been obtained by molecular docking. Analysis and selection of the different obtained docking solutions was based on the conservation within them of the inter-residue contacts. The selected model is very well representative of the different solutions found and its stability is confirmed by molecular dynamics simulations. Furthermore, the binding mode it adopts is very similar to that observed in most of the experimental structures available for idiotype-anti-idiotype antibody complexes. In the obtained model, AIM2 is directed against the MB2.8 CDR region, especially on its variable light chain. This makes the concurrent formation of the MB2.8-AIM2 complex and of the MB2.8-TG2 complex incompatible, thus explaining the experimentally observed inhibitory effect on the MB2.8 binding to TG2.

The structure and dynamics of BmR1 protein from Brugia malayi: in silico approaches

Brugia malayi is a filarial nematode, which causes lymphatic filariasis in humans. In 1995, the disease has been identified by the World Health Organization (WHO) as one of the second leading causes of permanent and long-term disability and thus it is targeted for elimination by year 2020. Therefore, accurate filariasis diagnosis is important for management and elimination programs. A recombinant antigen (BmR1) from the Bm17DIII gene product was used for antibody-based filariasis diagnosis in "Brugia Rapid". However, the structure and dynamics of BmR1 protein is yet to be elucidated. Here we study the three dimensional structure and dynamics of BmR1 protein using comparative modeling, threading and ab initio protein structure prediction. The best predicted structure obtained via an ab initio method (Rosetta) was further refined and minimized. A total of 5 ns molecular dynamics simulation were performed to investigate the packing of the protein. Here we also identified three epitopes as potential antibody binding sites from the molecular dynamics average structure. The structure and epitopes obtained from this study can be used to design a binder specific against BmR1, thus aiding future development of antigen-based filariasis diagnostics to complement the current diagnostics.

Simple Ligand-Receptor Interaction Descriptor (SILIRID) for alignment-free binding site comparison

We describe SILIRID (Simple Ligand–Receptor Interaction Descriptor), a novel fixed size descriptor characterizing protein–ligand interactions. SILIRID can be obtained from the binary interaction fingerprints (IFPs) by summing up the bits corresponding to identical amino acids. This results in a vector of 168 integer numbers corresponding to the product of the number of entries (20 amino acids and one cofactor) and 8 interaction types per amino acid (hydrophobic, aromatic face to face, aromatic edge to face, H-bond donated by the protein, H-bond donated by the ligand, ionic bond with protein cation and protein anion, and interaction with metal ion). Efficiency of SILIRID to distinguish different protein binding sites has been examined in similarity search in sc-PDB database, a druggable portion of the Protein Data Bank, using various protein–ligand complexes as queries. The performance of retrieval of structurally and evolutionary related classes of proteins was comparable to that of state-of-the-art approaches (ROC AUC ≈ 0.91). SILIRID can efficiently be used to visualize chemogenomic space covered by sc-PDB using Generative Topographic Mapping (GTM): sc-PDB SILIRID data form clusters corresponding to different protein types.

ProBiS-ligands: a web server for prediction of ligands by examination of protein binding sites

The ProBiS-ligands web server predicts binding of ligands to a protein structure. Starting with a protein structure or binding site, ProBiS-ligands first identifies template proteins in the Protein Data Bank that share similar binding sites. Based on the superimpositions of the query protein and the similar binding sites found, the server then transposes the ligand structures from those sites to the query protein. Such ligand prediction supports many activities, e.g. drug repurposing. The ProBiS-ligands web server, an extension of the ProBiS web server, is open and free to all users at http://probis.cmm.ki.si/ligands.