Structural Similarity Search Research Articles

The PCI domains are "winged" HEAT domains.

The HEAT domains are a family of helical hairpin repeat domains, composed of four or more hairpins. HEAT is derived from the names of four family members: huntingtin, eukaryotic translation elongation factor 3 (eEF3), protein phosphatase 2 regulatory A subunit (PP2A), and mechanistic target of rapamycin (mTOR). HEAT domain-containing proteins play roles in a wide range of cellular processes, such as protein synthesis, nuclear transport and metabolism, and cell signaling. The PCI domains are a related group of helical hairpin domains, with a “winged-helix” (WH) subdomain at their C-terminus, which is responsible for multi-subunit complex formation with other PCI domains. The name is derived from the complexes, where these domains are found: the 26S Proteasome “lid” regulatory subcomplex, the COP9 signalosome (CSN), and eukaryotic translation initiation factor 3 (eIF3). We noted that in structure similarity searches using HEAT domains, sometimes PCI domains appeared in the search results ahead of other HEAT domains, which indicated that the PCI domains could be members of the HEAT domain family, and not a related but separate group, as currently thought. Here, we report extensive structure similarity analysis of HEAT and PCI domains, both within and between the two groups of proteins. We present evidence that the PCI domains as a group have greater structural similarity with individual groups of HEAT domains than some of the HEAT domain groups have among each other. Therefore, our results indicate that the PCI domains have evolved from a HEAT domain that acquired a WH subdomain. The WH subdomain in turn mediated self-association into a multi-subunit complex, which eventually evolved into the common ancestor of the Proteasome lid/CSN/eIF3.

CBMDB: A Database for Accessing, Analyzing, and Mining CBM Information

Carbohydrate-binding modules (CBMs) are important substrate-binding domains that are mainly contained within carbohydrate-active enzymes. To elucidate the mechanism of enzyme-carbohydrate recognition and to promote the process of enzymatic engineering, it is important to explore more potential CBMs. However, the information and analytic tools of CBMs provided by current databases are limited. Here, a simple, user-friendly, and comprehensive CBM database (CBMDB) that integrates multidimensional information and analysis tools was constructed. Based on a data query function and analysis tools provided by the CBMDB, including sequence similarity searches, pairwise alignment, multiple sequence alignment, structure similarity searches, and phylogenetic visualization, information retrieval and analysis of known CBMs could be easily performed. Notably, unknown proteins with potential CBM functions could also be examined based on existing CBM data.

Identification of Novel Mutant (R132H) Isocitrate Dehydrogenase 1 Inhibitors for Glioma Therapy

Neomorphic transformations in isocitrate dehydrogenase 1 (IDH1) are the key mutations prevalently found in various cancers including glioma. Recently identified mIDH1 specific inhibitors showed modest brain penetrating potential and dose-limiting toxicity. Herein, we elucidate virtual screening strategies to discover persuasive mIDH1 inhibitors from the approved subset of the DrugBank database consisting of 2715 molecules. Initially, a structural similarity search identified a total of 1432 lead molecules. The resultant compounds were inspected by molecular docking along with MM-GBSA and ADMET analyses. Altogether, the analyses identified Abemaciclib as the hit against mIDH1. Notably, abemaciclib was able to form hydrogen bond interaction with active site residues of mIDH1 protein. In the end, the dynamic behavior of the hit complex was also examined using molecular dynamics simulation studies. The outcome of the study culminates that the hit complex was stable throughout the simulation period of 100[Formula: see text]ns. It is worth noting that benzimidazole moiety of abemaciclib was reported to show inhibitory activity against glioma cells. Overall, these findings highlight that abemaciclib has the potential as a lead molecule against glioma. Indeed, the screened hit compound could be further explored for the development of mIDH1 inhibitor with great brain penetrating ability and low toxicity.

Homology Modeling, de Novo Design of Ligands, and Molecular Docking Identify Potential Inhibitors of Leishmania donovani 24-Sterol Methyltransferase.

The therapeutic challenges pertaining to leishmaniasis due to reported chemoresistance and toxicity necessitate the need to explore novel pathways to identify plausible inhibitory molecules. Leishmania donovani 24-sterol methyltransferase (LdSMT) is vital for the synthesis of ergosterols, the main constituents of Leishmania cellular membranes. So far, mammals have not been shown to possess SMT or ergosterols, making the pathway a prime candidate for drug discovery. The structural model of LdSMT was elucidated using homology modeling to identify potential novel 24-SMT inhibitors via virtual screening, scaffold hopping, and de-novo fragment-based design. Altogether, six potential novel inhibitors were identified with binding energies ranging from −7.0 to −8.4 kcal/mol with e-LEA3D using 22,26-azasterol and S1–S4 obtained from scaffold hopping via the ChEMBL, DrugBank, PubChem, ChemSpider, and ZINC15 databases. These ligands showed comparable binding energy to 22,26-azasterol (−7.6 kcal/mol), the main inhibitor of LdSMT. Moreover, all the compounds had plausible ligand efficiency-dependent lipophilicity (LELP) scores above 3. The binding mechanism identified Tyr92 to be critical for binding, and this was corroborated via molecular dynamics simulations and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) calculations. The ligand A1 was predicted to possess antileishmanial properties with a probability of activity (Pa) of 0.362 and a probability of inactivity (Pi) of 0.066, while A5 and A6 possessed dermatological properties with Pa values of 0.205 and 0.249 and Pi values of 0.162 and 0.120, respectively. Structural similarity search via DrugBank identified vabicaserin, daledalin, zanapezil, imipramine, and cefradine with antileishmanial properties suggesting that the de-novo compounds could be explored as potential antileishmanial agents.

Discovery of potential novel CRBN modulators by virtual screening and bioassay

The incidence of malignant tumor with high mortality is increasing yearly. CRBN E3 ubiquitin ligase was proved to be an antitumor target. It was found that thalidomide and its analogs could bind to CRBN E3 ubiquitin ligase and modulate CRBN. CRBN modulators could promote the binding of CRBN to specific target proteins or block the binding of CRBN to some endogenous proteins. In this way, CRBN modulators suppress various tumor cells by modulating the interactions between CRBN and various antitumor target proteins. However, almost all CRBN modulators reported include glutarimide scaffold. Therefore, the aim of this study is to developed novel CRBN modulators. Virtual screening methods and bioassay methods, including structural similarity search, molecular docking, substructure search, antitumor evaluation and apoptosis assay were used to search novel potential CRBN modulators in Specs database. Finally, 15 compounds exhibited strong inhibition activity against A549 cells. Among these active compounds, The IC50 value against A549 of AG6033 was 0.853 ± 0.030 μM. Apoptosis assay demonstrated that AG6033 could promote apoptosis of A549 cells. Further mechanism studies suggested that AG6033 caused remarkable decrease of GSPT1 and IKZF1, the substrates of CRBN, and AG6033 induced cytotoxic effects was CRBN-dependent.

SMART v1.0: A Database for Small Molecules with Functional Implications in Plants.

We developed SMART v1.0 ( http://smart.omicstudio.cloud ), the first database for small molecules with functional implications in plants. The SMART database is devoted to providing and managing small molecules and their associated structural data, chemoinformatic data, protein targets, pathways and induced phenotype/function information. Currently, SMART v1.0 encompasses 1218 unique small molecules which are involved in multiple biological pathways. SMART v1.0 is featured with user-friendly interfaces, through which pathway-centered visualization of small molecules can be efficiently performed, and multiple types of searches (i.e., text search, structure similarity search and sequence similarity search) can be conveniently conducted. SMART v1.0 is also specifically designed to be a small molecule-sharing database, allowing users to release their newly discovered small molecules to public via the Contribute webpage. The SMART database will facilitate the comprehensive understanding of small molecules in complex biological processes in plants.

Paradoxical Pro-angiogenic Effect of Low-Dose Ellipticine Identified by In Silico Drug Repurposing.

Inadequate vessel maintenance or growth causes ischemia in diseases such as myocardial infarction, stroke, and neurodegenerative disorders. Therefore, developing an effective strategy to salvage ischemic tissues using a novel compound is urgent. Drug repurposing has become a widely used method that can make drug discovery more efficient and less expensive. Additionally, computational virtual screening tools make drug discovery faster and more accurate. This study found a novel drug candidate for pro-angiogenesis by in silico virtual screening. Using Gene Expression Omnibus (GEO) microarray datasets related to angiogenesis studies, differentially expressed genes were identified and characteristic direction signatures extracted from GEO2EnrichR were used as input data on L1000CDS2 to screen pro-angiogenic molecules. After a thorough review of the candidates, a list of compounds structurally similar to TWS-119 was generated using ChemMine Tools and its clustering toolbox. ChemMine Tools and ChemminR structural similarity search tools for small-molecule analysis and clustering were used for second screening. A molecular docking simulation was conducted using AutoDock v.4 to evaluate the physicochemical effect of secondary-screened chemicals. A cell viability or toxicity test was performed to determine the proper dose of the final candidate, ellipticine. As a result, we found ellipticine, which has pro-angiogenic effects, using virtual computational methods. The noncytotoxic concentration of ellipticine was 156.25 nM. The phosphorylation of glycogen synthase kinase-3β was decreased, whereas the β-catenin expression was increased in human endothelial cells treated with ellipticine. We concluded that ellipticine at sublethal dosage could be successfully repositioned as a pro-angiogenic substance by in silico virtual screening.

Structure Based Drug Design Approach to Identify Potential SARS-CoV-2 Polymerase Inhibitors

Aims: The research work aims to apply the current virtual screening approaches for rapid screening of available compounds as inhibitors of the novel coronavirus (COVID-19). Background: The worldwide pandemic, uncontrolled spread, and lack of effective therapeutics demand novel SARS-CoV-2 inhibitory anti-viral agents. Objective: The major objectives of the present work are – i) effective utilization of open-source computer- aided drug design (CADD) tools; ii) to prepare a database according to chemical structure similarity to the reported anti-viral drug, Favipiravir; and iii) to investigate potential inhibitors of the novel coronavirus. Methods: The dataset was prepared based on the chemical structure similarity feature of ChemSpider. The virtual screening was carried out using molecular docking and ADMET properties. For performing molecular docking studies, the standard docking protocol of iGEMDOCK was used. Result: Based on chemical structure similarity search to Favipiravir, a small library of 40 compounds was designed. The docking score and ADMET properties were analyzed to prioritize the compounds. Conclusion: The virtual screening resulted in the identification of potential anti-viral compounds. Among the designed library of compounds based on structural similarity to Favipiravir, 70% of compounds were found to possess docking scores more than that of Favipiravir. The amino acid residues involved in binding at the RNA dependent RNA polymerase (RdRp) were identified. The compounds have shown acceptable ADME properties and are potentially non-toxic. Other: The study has successfully applied the open source CADD tools to investigate novel SARS-CoV-2 polymerase inhibitors.

Biochemical and structural characterization of a novel 4-O-α-l-rhamnosyl-β-d-glucuronidase from Fusarium oxysporum.

In this study, we have isolated the novel enzyme 4-O-α-l-rhamnosyl-β-d-glucuronidase(FoBGlcA), which releases α-l-rhamnosyl (1→4) glucuronic acid from gum arabic (GA), from Fusariumoxysporum 12S culture supernatant, and for the first time report an enzyme with such catalytic activity. The gene encoding FoBGlcA was cloned and expressed in Pichiapastoris. When GA was subjected to the recombinant enzyme, >95% of the l-rhamnose (Rha) and d-glucuronic acid in the substrate were released, which indicates that almost all Rha binds to the glucuronic acid at the end of the GA side chains. The crystal structure of FoBGlcA was determined using a single-wavelength anomalous dispersion at 1.51Å resolution. FoBGlcA consisted of an N-terminal (β/α)8 -barrel domain and a C-terminal antiparallel β-sheet domain. This configuration is characteristic of glycoside hydrolase (GH) family 79 proteins. A structural similarity search showed that FoBGlcA mostly resembled GH79 β-d-glucuronidase (AcGlcA79A) of Acidobacteriumcapsulatum; however, the root-mean-square deviation value was 3.2Å, indicating that FoBGlcA has a high structural divergence. FoBGlcA had a low sequence identity with AcGlcA79A (19%) and differed from other GH79 β-glucuronidases. The structures of FoBGlcA and AcGlcA79A also differed in terms of the loop structure location near subsite -2 of their catalytic sites, which may account for the unique substrate specificity of FoBGlcA. The amino acid residues involved in the catalytic activity of this enzyme were determined by evaluating the activity levels of various mutant enzymes based on the crystal structure analysis of the FoBGlcA reaction product complex. DATABASE: Atomic coordinates and structure factors (codes 7DFQ and 7DFS) have been deposited in the Protein Data Bank (http://wwpdb.org/).

QAUST: Protein Function Prediction Using Structure Similarity, Protein Interaction, and Functional Motifs

The number of available protein sequences in public databases is increasing exponentially. However, a significant percentage of these sequences lack functional annotation, which is essential for the understanding of how biological systems operate. Here, we propose a novel method, Quantitative Annotation of Unknown STructure (QAUST), to infer protein functions, specifically Gene Ontology (GO) terms and Enzyme Commission (EC) numbers. QAUST uses three sources of information: structure information encoded by global and local structure similarity search, biological network information inferred by protein–protein interaction data, and sequence information extracted from functionally discriminative sequence motifs. These three pieces of information are combined by consensus averaging to make the final prediction. Our approach has been tested on 500 protein targets from the Critical Assessment of Functional Annotation (CAFA) benchmark set. The results show that our method provides accurate functional annotation and outperforms other prediction methods based on sequence similarity search or threading. We further demonstrate that a previously unknown function of human tripartite motif-containing 22 (TRIM22) protein predicted by QAUST can be experimentally validated.

Phenothiazine as novel human superoxide dismutase modulators: discovery, optimization, and biological evaluation

Superoxide dismutases (SODs) are regarded as important antioxidants for protecting cells against damage arising from oxidative stress. Much research is focused on finding new chemicals with an ability to boost human SOD activity. In the research described herein a structure-based approach was used to identify new human Cu-Zn superoxide dismutase (SOD1) modulators based on previously reported plasmodium falciparum iron SOD inhibitors using induced fit docking and molecular dynamic (MD) protocols. The compound with the highest docking binding energy was selected for further structure simplification followed by structural similarity and MD in order to find a new activator/inhibitor scaffold of the SOD1 enzyme. According to the docking survey of the mentioned series, 1,4-bis(3-(1,4,8-trichloro-10Hphenothiazin-10-yl) propyl) piperazine (DS88) was the top scoring compound interacting with the SOD1 active site channel. Following structure simplification and similarity search, the most promising scaffold which is closely related to the phenothiazine antipsychotic class, was identified. Compared with the normal blood SOD1 activity, the percent of O2 production increased with trifluoperazine, while it decreased with the chlorpromazine. The molecular dynamic investigation shows that trifluoperazine exerts its SOD1 activating effect by stabilizing electrostatic loop while chlorpromazine employs SOD1 inhibition activity through repositioning of the electrostatic loop and increasing its distance from the catalytic metal site which diminished substrate specificity and catalytic activity of the SOD1 enzyme. The results identified the preferred region, orientation, and types of interaction for each activator or inhibitor compound.

Discovery of beta-lactamase CMY-10 inhibitors for combination therapy against multi-drug resistant Enterobacteriaceae.

β-lactam antibiotics are the most widely used antimicrobial agents since the discovery of benzylpenicillin in the 1920s. Unfortunately, these life-saving antibiotics are vulnerable to inactivation by continuously evolving β-lactamase enzymes that are primary resistance determinants in multi-drug resistant pathogens. The current study exploits the strategy of combination therapeutics and aims at identifying novel β-lactamase inhibitors that can inactivate the β-lactamase enzyme of the pathogen while allowing the β-lactam antibiotic to act against its penicillin-binding protein target. Inhibitor discovery applied the Site-Identification by Ligand Competitive Saturation (SILCS) technology to map the functional group requirements of the β-lactamase CMY-10 and generate pharmacophore models of active site. SILCS-MC, Ligand-grid Free Energy (LGFE) analysis and Machine-learning based random-forest (RF) scoring methods were then used to screen and filter a library of 700,000 compounds. From the computational screens 74 compounds were subjected to experimental validation in which β-lactamase activity assay, in vitro susceptibility testing, and Scanning Electron Microscope (SEM) analysis were conducted to explore their antibacterial potential. Eleven compounds were identified as enhancers while 7 compounds were recognized as inhibitors of CMY-10. Of these, compound 11 showed promising activity in β-lactamase activity assay, in vitro susceptibility testing against ATCC strains (E. coli, E. cloacae, E. agglomerans, E. alvei) and MDR clinical isolates (E. cloacae, E. alvei and E. agglomerans), with synergistic assay indicating its potential as a β-lactam enhancer and β-lactamase inhibitor. Structural similarity search against the active compound 11 yielded 28 more compounds. The majority of these compounds also exhibited β-lactamase inhibition potential and antibacterial activity. The non-β-lactam-based β-lactamase inhibitors identified in the current study have the potential to be used in combination therapy with lactam-based antibiotics against MDR clinical isolates that have been found resistant against last-line antibiotics.

A computational study on hydroxychloroquine binding to target proteins related to SARS-COV-2 infection

COVID-19 disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has posed a global health emergency. Repurposing of existing drugs can be a rapid and effective strategy to fight the infection. Clinical trials have reported reduction or elimination of viral load when patients were treated with the anti-malarial drug Hydroxychloroquine (HCQ). To understand the molecular mechanism of action for effective repurposing of this drug we have carried out in silico docking and dynamics studies on complexes between HCQ and target proteins, which were identified through both literature survey and structural similarity searches in databases of small molecule – protein complexes. The proteins identified as binding HCQ are: Angiotensin Converting Enzyme 2 (ACE2), α7 nicotinic AcetylCholine Receptor (α7 nAChR), α1D-adrenergic receptor (α1D-AR), Histamine N- Methyl Transferase (HNMT) and DNA gyrase/Topoisomerase III β (Top3β). The majority of these proteins are novel and have not been used before, in docking studies. Our docking and simulation results support action of HCQ both at the entry and post-entry stages of SARS-CoV2 infection. The mechanism of action at the entry stage is through blocking the virus-binding sites on the two receptors, ACE2 & α7 nAChR, by binding directly at those sites. Our computational studies also show that the action of HCQ at the post-entry stage is to prevent both viral replication and generation of ‘cytokine storm’ by inhibiting host Top3β enzyme and α1D-AR, respectively. Binding of HCQ to HNMT is not a desired binding, and therefore this should be reduced during repurposing of HCQ.

Crystal structure and mutational analysis of the human TRIM7 B30.2 domain provide insights into the molecular basis of its binding to glycogenin-1

Tripartite motif (TRIM)7 is an E3 ubiquitin ligase that was first identified through its interaction with glycogenin-1 (GN1), the autoglucosyltransferase that initiates glycogen biosynthesis. A growing body of evidence indicates that TRIM7 plays an important role in cancer development, viral pathogenesis, and atherosclerosis and, thus, represents a potential therapeutic target. TRIM family proteins share a multidomain architecture with a conserved N-terminal TRIM and a variable C-terminal domain. Human TRIM7 contains the canonical TRIM motif and a B30.2 domain at the C terminus. To contribute to the understanding of the mechanism of action of TRIM7, we solved the X-ray crystal structure of its B30.2 domain (TRIM7B30.2) in two crystal forms at resolutions of 1.6 Å and 1.8 Å. TRIM7B30.2 exhibits the typical B30.2 domain fold, consisting of two antiparallel β-sheets of seven and six strands, arranged as a distorted β-sandwich. Furthermore, two long loops partially cover the concave face of the β-sandwich defined by the β-sheet of six strands, thus forming a positively charged cavity. We used sequence conservation and mutational analyses to provide evidence of a putative binding interface for GN1. These studies showed that Leu423, Ser499, and Cys501 of TRIM7B30.2 and the C-terminal 33 amino acids of GN1 are critical for this binding interaction. Molecular dynamics simulations also revealed that hydrogen bond and hydrophobic interactions play a major role in the stability of a modeled TRIM7B30.2-GN1 C-terminal peptide complex. These data provide useful information that could be used to target this interaction for the development of potential therapeutic agents.

Geometricus represents protein structures as shape-mers derived from moment invariants.

As the number of experimentally solved protein structures rises, it becomes increasingly appealing to use structural information for predictive tasks involving proteins. Due to the large variation in protein sizes, folds and topologies, an attractive approach is to embed protein structures into fixed-length vectors, which can be used in machine learning algorithms aimed at predicting and understanding functional and physical properties. Many existing embedding approaches are alignment based, which is both time-consuming and ineffective for distantly related proteins. On the other hand, library- or model-based approaches depend on a small library of fragments or require the use of a trained model, both of which may not generalize well. We present Geometricus, a novel and universally applicable approach to embedding proteins in a fixed-dimensional space. The approach is fast, accurate, and interpretable. Geometricus uses a set of 3D moment invariants to discretize fragments of protein structures into shape-mers, which are then counted to describe the full structure as a vector of counts. We demonstrate the applicability of this approach in various tasks, ranging from fast structure similarity search, unsupervised clustering and structure classification across proteins from different superfamilies as well as within the same family. Python code available at https://git.wur.nl/durai001/geometricus.

Molecular modeling approach to identify inhibitors of Rv2004c (rough morphology and virulent strain gene), a DosR (dormancy survival regulator) regulon protein from Mycobacterium tuberculosis

Being a part of dormancy survival regulator (DosR) regulon, Rv2004c (rough morphology and virulent strain gene) has been identified in earlier experimental studies as an indispensable protein required for the growth and survival of Mycobacterium tuberculosis. This protein was predicted to have a role in inhibition of phospholipase A2 activity related to immuno-defence and other membrane-related events. Thus, considering significance of Rv2004c protein, a structure-based drug designing strategy was followed to identify potential inhibitors to this novel target. Initially, to validate the target, absence of homologous proteins in the host was verified through sequence and structure similarity search against human proteome. Then, a potential ligand binding site on the target was identified and virtual screening against Zinc database molecules was carried out. The top scoring hits along with their analogs were taken for docking studies with Glide. The binding free energy of the docked complexes of the Glide hits were predicted by Prime program from Schrodinger and molecules ZINC57990006, ZINC33605742, ZINC71773467 and ZINC34198774 were recognized as potential hits against this target. Analyzing the predicted pharmacokinetic properties of the molecules from QikProp and admetSAR tool, ZINC34198774 was identified as a valid molecule. Molecular dynamics simulation studies ascertained that ZINC34198774 could be a potential inhibitor against Rv2004c. Thus, results acquired from this study could be of use to design new therapeutics against tuberculosis. Communicated by Ramaswamy H. Sarma.

Discovery of potentially biased agonists of mu-opioid receptor (MOR) through molecular docking, pharmacophore modeling, and MD simulation

Opioids are well known for their potent analgesic efficacy and severe side effects. Studies have shown that analgesic effects are mediated by the downstream G-protein-dependent pathway of the μ-opioid receptor (MOR), and another β-arrestin-dependent pathway mediates side effects such as respiratory depression, constipation and tolerance etc. TRV130 is a biased ligand for G-protein-dependent pathway, which has high analgesia and has fewer side effects than morphine. In this study, the structure similarity search was performed on the IBSSC database using Oliceridine (TRV130) and PZM21 as templates. The 3D structure-based pharmacophore model was built and combined molecular docking prediction mode was selected to filter out small molecules, Finally, based on affinity prediction, four candidate molecules were obtained. Molecular dynamics simulations explored the detailed interaction mechanism of proteins with small molecules under dynamics. These results suggest that these candidate molecules are potential MOR agonists.

Semi-supervised Co-Clustering on Attributed Heterogeneous Information Networks

Node clustering on heterogeneous information networks (HINs) plays an important role in many real-world applications. While previous research mainly clusters same-type nodes independently via exploiting structural similarity search, they ignore the correlations of different-type nodes. In this paper, we focus on the problem of co-clustering heterogeneous nodes where the goal is to mine the latent relevance of heterogeneous nodes and simultaneously partition them into the corresponding type-aware clusters. This problem is challenging in two aspects. First, the similarity or relevance of nodes is not only associated with multiple meta-path-based structures but also related to numerical and categorical attributes. Second, clusters and similarity/relevance searches usually promote each other.To address this problem, we first design a learnable overall relevance measure that integrates the structural and attributed relevance by employing meta-paths and attribute projection. We then propose a novel approach, called SCCAIN, to co-cluster heterogeneous nodes based on constrained orthogonal non-negative matrix tri-factorization. Furthermore, an end-to-end framework is developed to jointly optimize the relevance measures and co-clustering. Extensive experiments on real-world datasets not only demonstrate that SCCAIN consistently outperforms state-of-the-art methods but also validate the effectiveness of integrating attributed and structural information for co-clustering.

Designing, Cytotoxic Evaluation, Molecular Docking and in Silico Pharmacokinetic Prediction of New Hydrocortisone Derivatives as Anti-Asthmatics Drugs

A series of new 20 corticosteroids were subjected to molecular property prediction. The Molecular, Physicochemical, and Biological properties were determined using Molinspiration Cheminformatics software. These compounds were further subjected to Toxicity Predictions using the Osiris Software. The calculated drug-related properties of the designed molecules were similar to those found in most marketed drugs. Amongst the proposed molecules, fourteen promising candidates can be considered as promising structures for the synthesis of new and more effective anti-asthmatic drugs. Result indicates that the derivatives are orally active molecules. In-silico ADME and toxicity prediction was accomplished with the help of Swiss-ADMET tool provides the latest and most inclusive for diverse chemicals associated with known Absorption, Distribution, Metabolism, Excretion and Toxicity profiles. furthermore, BBB (Blood brain barrier) penetration, HIA (Human intestinal absorption), Caco-2 cell permeability and Ames test were calculated using ADMET web-based query tools incorporating a molecular build in interface enable the database to be queried by Smiles and structural similarity search. According to molecular docking results, derivatives No 4, 10 and 11 showed better docking Scores values compared to other derivatives and also dexamethasone and hydrocortisone.
 Keywords: Corticosteroids, Drug-likeness, Lipophilicity, Anti-asthmatic, ADME.

Structural insights into phosphopantetheinyl hydrolase PptH from Mycobacterium tuberculosis.

The amidinourea 8918 was recently reported to inhibit the type II phosphopantetheinyl transferase (PPTase) of Mycobacterium tuberculosis (Mtb), PptT, a potential drug-target that activates synthases and synthetases involved in cell wall biosynthesis and secondary metabolism. Surprisingly, high-level resistance to 8918 occurred in Mtb harboring mutations within the gene adjacent to pptT, rv2795c, highlighting the role of the encoded protein as a potentiator of the bactericidal action of the amidinourea. Those studies revealed that Rv2795c (PptH) is a phosphopantetheinyl (PpT) hydrolase, possessing activity antagonistic with respect to PptT. We have solved the crystal structure of Mtb's phosphopantetheinyl hydrolase, making it the first phosphopantetheinyl (carrier protein) hydrolase structurally characterized. The 2.5 Å structure revealed the hydrolases' four-layer (α/β/β/α) sandwich fold featuring a Mn-Fe binuclear center within the active site. A structural similarity search confirmed that PptH most closely resembles previously characterized metallophosphoesterases (MPEs), particularly within the vicinity of the active site, suggesting that it may utilize a similar catalytic mechanism. In addition, analysis of the structure has allowed for the rationalization of the previously reported PptH mutations associated with 8918-resistance. Notably, differences in the sequences and predicted structural characteristics of the PpT hydrolases PptH of Mtb and E. coli's acyl carrier protein hydrolase (AcpH) indicate that the two enzymes evolved convergently and therefore are representative of two distinct PpT hydrolase families.