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Predictive ADME-Tox London, UK, 27 -- 28 April 2005.

The Predictive ADME-Tox conference brought together scientists responsible for innovative in vitro and in silico screens to predict particular chemical liabilities. Oral bioavailability without adverse effects requires good absorption, distribution, metabolism and excretion (ADME) and minimal toxicity. Traditionally, these properties are measured late in development, when sufficient material is available for classical assays. Although these assays remain the gold standard, the conference focused on novel methods to predict liabilities early in the development pipeline, when a course change has less impact in the development timeline. Emerging themes from the meeting were i) integration - of data from a number of predictive assays into a 'profile' of a new class, and of safety scientists into discovery teams, in order to guide interpretation of the profile and identify tests to include in the hit-to-lead process; and ii) collaboration. As in silico predictive models are increasingly accepted, from reactivity and genetic toxicity to models for hERG inhibition, kinase crossreactivity and cytochrome P450 reactivity, increasing amounts of high-quality data will be needed to 'feed' the models. Such data will soon be beyond the capabilities of individual organisations to generate, and methods for pooling data are needed to advance the generation of predictive models for new toxicities. In addition, collaboration to apply novel methods such as metabonomics profiling to withdrawn drugs may permit the identification of new safety biomarkers to prevent such costly failures.

Biotransformation↗

The absence of TIR-type resistance gene analogues in the sugar beet (Beta vulgaris L.) genome.

The majority of known plant resistance genes encode proteins with conserved nucleotide-binding sites and leucine-rich repeats (NBS-LRR). Degenerate primers based on conserved NBS-LRR motifs were used to amplify analogues of resistance genes from the dicot sugar beet. Along with a cDNA library screen, the PCR screen identified 27 genomic and 12 expressed NBS-LRR RGAs (nlRGAs) sugar beet clones. The clones were classified into three subfamilies based on nucleotide sequence identity. Sequence analyses suggested that point mutations, such as nucleotide substitutions and insertion/deletions, are probably the primary source of diversity of sugar beet nlRGAs. A phylogenetic analysis revealed an ancestral relationship among sugar beet nlRGAs and resistance genes from various angiosperm species. One group appeared to share the same common ancestor as Prf, Rx, RPP8, and Mi, whereas the second group originated from the ancestral gene from which 12C1, Xa1, and Cre3 arose. The predicted protein products of the nlRGAs isolated in this study are all members of the non-TIR-type resistance gene subfamily and share strong sequence and structural similarities with non-TIR-type resistance proteins. No representatives of the TIR-type RGAs were detected either by PCR amplification using TIR type-specific primers or by in silico screening of more than 16,000 sugar beet ESTs. These findings suggest that TIR type of RGAs is absent from the sugar beet genome. The possible evolutionary loss of TIR type RGAs in the sugar beet is discussed.

Base Composition↗

Combining ethnopharmacology and virtual screening for lead structure discovery: COX-inhibitors as application example.

Virtual screening of large libraries of organic compounds combined with pharmacological high throughput screening is widely used for drug discovery in the pharmaceutical industry. Our aim was to explore the efficiency of using a biased 3D database comprising secondary metabolites from antiinflammatory medicinal plants as a source for the virtual screening. For this study pharmacophore models of cyclooxygenase I and II (COX-1, COX-2), key enzymes in the inflammation process, were generated with structure-based as well as common feature based modeling, resulting in three COX hypotheses. Four different multiconfomational 3D databases limited in molecular weight between 300 and 700 Da were applied to the screening in order to compare and analyze the obtained hit rates. Two of them were created in-house (DIOS, NPD). The database DIOS consists of 2752 compounds from phytochemical reports of antiinflammatory medicinal plants described by the ethnopharmacological source 'De material medica' of Pedanius Dioscorides, whereas NPD contains almost 80,000 compounds gathered arbitrarily from natural sources. In addition, two available multiconformational 3D libraries comprising marketed and development drug substances (DWI and NCI), mainly originating from synthesis, were used for comparison. As a test of the pharmacophore models' capability in natural sources, the models were used to search for known COX inhibitory natural products. This was achieved with some exceptions, which are discussed in the paper. Depending on the hypothesis used, DWI and NCI library searches produced hit rates in the range of 6.6% to 13.7%. A slight increase of the number of molecules assessed for binding was achieved with the database of natural products (NPD). Using the biased 3D database DIOS, however, the average increase of efficiency reached 77% to 133% compared to the hit rates resulting from WDI and NCI. The statistical benefit of a combination of an ethnopharmacological approach with the potential of computer aided drug discovery by in silico screening was demonstrated exemplified on the applied targets COX-1 and COX-2.

Computer Simulation↗

Searching for new plastic-degrading enzymes from the plastisphere of alpine soils using a metagenomic mining approach.

Plastic materials, including microplastics, accumulate in all types of ecosystems, even in remote and cold environments such as the European Alps. This pollution poses a risk for the environment and humans and needs to be addressed. Using shotgun DNA metagenomics of soils collected in the eastern Swiss Alps at about 3,000 m a.s.l., we identified genes and their proteins that potentially can degrade plastics. We screened the metagenomes of the plastisphere and the bulk soil with a differential abundance analysis, conducted similarity-based screening with specific databases dedicated to putative plastic-degrading genes, and selected those genes with a high probability of signal peptides for extracellular export and a high confidence for functional domains. This procedure resulted in a final list of nine candidate genes. The lengths of the predicted proteins were between 425 and 845 amino acids, and the predicted genera producing these proteins belonged mainly to Caballeronia and Bradyrhizobium. We applied functional validation, using heterologous expression followed by enzymatic assays of the supernatant. Five of the nine proteins tested showed significantly increased activities when we used an esterase assay, and one of these five proteins from candidate genes, a hydrolase-type esterase, clearly had the highest activity, by more than double. We performed the fluorescence assays for plastic degradation of the plastic types BI-OPL and ecovio® only with proteins from the five candidate genes that were positively active in the esterase assay, but like the negative controls, these did not show any significantly increased activity. In contrast, the activity of the positive control, which contained a PLA-degrading gene insert known from the literature, was more than 20 times higher than that of the negative controls. These findings suggest that in silico screening followed by functional validation is suitable for finding new plastic-degrading enzymes. Although we only found one new esterase enzyme, our approach has the potential to be applied to any type of soil and to plastics in various ecosystems to search rapidly and efficiently for new plastic-degrading enzymes.

Humans↗

Expression and regulation of mouse SERDIN1, a highly conserved cardiac-specific leucine-rich repeat protein.

Despite recent progress, the precise mechanisms responsible for vertebrate cardiac development are still enigmatic. Better understanding of cardiac biology and disease necessitates identification and analysis of a full spectrum of regulatory and structural proteins specific to the developing heart. By performing an in silico screen, we identified a cardiac-specific gene we named Serdin1. The Serdin1 gene is conserved, and the message is restricted to the heart in several vertebrate species, thus implicating Serdin1 as an important gene in cardiac development. In situ hybridization confirmed that the Serdin1 message is cardiac-specific in mice as early as embryonic day 8.5. Antibody staining demonstrated predominantly nuclear staining in immortalized cardiac cell lines (P19 and HL-1) and proliferating cultured cardiomyocytes, whereas in vivo SERDIN1 localizes to I bands of the sarcomere. Seven kilobases of the upstream regulatory sequence of Serdin1 is sufficient for cardiac-specific expression. Computer analysis revealed an 80-bp homologous region between the mouse and the human Serdin genes that contains GATA, SRF, and MEF sites. Cardiac specificity and localization patterns suggest that SERDIN1 is intimately integrated with the molecular pathways controlling cardiogenesis in vertebrates.

Amino Acid Sequence↗

Predicting P-glycoprotein substrates by a quantitative structure-activity relationship model.

A quantitative structure-activity relationship (QSAR) model has been developed to predict whether a given compound is a P-glycoprotein (Pgp) substrate or not. The training set consisted of 95 compounds classified as substrates or non-substrates based on the results from in vitro monolayer efflux assays. The two-group linear discriminant model uses 27 statistically significant, information-rich structure quantifiers to compute the probability of a given structure to be a Pgp substrate. Analysis of the descriptors revealed that the ability to partition into membranes, molecular bulk, and the counts and electrotopological values of certain isolated and bonded hydrides are important structural attributes of substrates. The model fits the data with sensitivity of 100% and specificity of 90.6% in the jackknifed cross-validation test. A prediction accuracy of 86.2% was obtained on a test set of 58 compounds. Examination of the eight "mispredicted" compounds revealed two distinct categories. Five mispredictions were explained by experimental limitations of the efflux assay; these compounds had high permeability and/or were inhibitors of calcein-AM transport. Three mispredictions were due to limitations of the chemical space covered by the current model. The Pgp QSAR model provides an in silico screen to aid in compound selection and in vitro efflux assay prioritization.

ATP Binding Cassette Transporter, Subfamily B, Mem↗

QT prolongation through hERG K(+) channel blockade: current knowledge and strategies for the early prediction during drug development.

Prolongation of the QT interval of the electrocardiogram is a typical effect of Class III antiarrhythmic drugs, achieved through blockade of potassium channels. In the past decade, evidence has accrued that several classes of drugs used for non-cardiovascular indications may prolong the QT interval with the same mechanism (namely, human ether-a-go-go-related gene (hERG) K(+) channel blockade). The great interest in QT prolongation is because of several reasons. First, drug-induced QT prolongation increases the likelihood of a polymorphous ventricular arrhythmia (namely, torsades de pointes, TdP), which may cause syncope and degenerate into ventricular fibrillation and sudden death. Second, the fact that several classes of drugs, such as antihistamines, fluoroquinolones, macrolides, and neuroleptics may cause the long QT syndrome (LQTS) raises the question whether this is a class effect (e.g., shared by all agents of a given pharmacological class) or a specific effect of single agents within a class. There is now consensus that, in most cases, only a few agents within a therapeutic class share the ability to significantly affect hERG K(+) channels. These compounds should be identified as early as possible during drug development. Third, QT prolongation and interaction with hERG K(+) channels have become surrogate markers of cardiotoxicity and have received increasing regulatory attention. This review briefly outlines the mechanisms leading to QT prolongation and the different strategies that can be followed to predict this unwanted effect. In particular, it will focus on the approaches recently proposed for the in silico screening of new compounds.

Animals↗

Reverse vaccinology and vaccines for serogroup B Neisseria meningitidis.

Whole genome sequence data are increasingly available for a wide range of human pathogens. The use of bioinformatic tools allows the comprehensive in silico screening of genome data for surface-expressed proteins, in order to identify candidate vaccine antigens. In vitro confirmation of surface location and the use of animal models to test immunogenicity further refine the list of proteins likely to be of use as vaccine antigens. This process, first applied to serogroup B Neisseria meningitidis, has been termed as reverse vaccinology. Reverse vaccinology offers the ability to undertake a rapid and comprehensive assessment of a micro-organism's surface protein repertoire, and has advantages over conventional approaches to identifying candidate antigens. Despite the advantages of the approach, development in conventional areas of vaccinology remains important to support the process of producing vaccines from genome-derived antigens.

Antigens, Bacterial↗

The role and application of in silico docking in chemical genomics research.

In silico docking techniques are being used to investigate the complementarity at the molecular level of a ligand and a protein target. As such, docking studies can be used to identify the structural features that are important for binding and for in silico screening efforts in which suitable binding partners can be identified. Here we describe a practical approach for setting up docking simulations using different docking programs. We also cover the analysis and rescoring of the obtained docking poses. Possible pitfalls in the docking studies are discussed and hints are provided to resolve commonly occurring problems.

Binding Sites↗

Organisation and structural evolution of the rice glutathione S-transferase gene family.

Glutathione S-transferases (GSTs) comprise a large family of key defence enzymes against xenobiotic toxicity. Here we describe the comprehensive characterisation of this important multigene family in the model monocot species rice [ Oryza sativa(L.)]. Furthermore, we investigate the molecular evolution of the family based on the analysis of (1) the patterns of within-genome duplication, and (2) the phylogenetic relationships and evolutionary divergence among rice, Arabidopsis, maize and soybean GSTs. By in-silico screening of the EST and genome divisions of the Genbank/EMBL/DDBJ database we have isolated 59 putative genes and two pseudogenes, making this the largest plant GST family characterised to date. Of these, 38 (62%) are represented by genomic and EST sequences and 23 (38%) are known only from their genomic sequences. A preliminary survey of EST collections shows a large degree of variability in gene expression between different tissues and environmental conditions, with a small number of genes (13) accounting for 80% of all ESTs. Rice GSTs are organised in four main phylogenetic classes, with 91% of all rice genes belonging to the two plant-specific classes Tau (40 genes) and Phi (16 genes). Pairwise identity scores range between 17 and 98% for proteins of the same class, and 7 and 21% for interclass comparisons. Rapid evolution by gene duplication is suggested by the discovery of two large clusters of 7 and 23 closely related genes on chromosomes 1 and 10, respectively. A comparison of the complete GST families in two monocot and two dicot species suggests a monophyletic origin for all Theta and Zeta GSTs, and no more than three common ancestors for all Phi and Tau genes.

Arabidopsis↗

Variable selection and specification of robust QSAR models from multicollinear data: arylpiperazinyl derivatives with affinity and selectivity for alpha2-adrenoceptors.

Two QSAR models have been identified that predict the affinity and selectivity of arylpiperazinyl derivatives for alpha1 and alpha2 adrenoceptors (ARs). The models have been specified and validated using 108 compounds whose structures and inhibition constants (Ki) are available in the literature [Barbaro et al., J. Med. Chem., 44 (2001) 2118; Betti et al., J. Med. Chem., 45 (2002) 3603; Barbaro et al., Bioorg. Med. Chem., 10 (2002) 361; Betti et al., J. Med. Chem., 46 (2003) 3555]. One hundred and forty-seven predictors have been calculated using the Cerius 2 software available from Accelrys. This set of variables exhibited redundancy and severe multicollinearity, which had to be identified and removed as appropriate in order to obtain robust regression models free of inflated errors for the beta estimates - so-called bouncing betas. Those predictors that contained information relevant to the alpha2 response were identified on the basis of their pairwise linear correlations with affinity (-log Ki) for alpha2 adrenoceptors; the remaining variables were discarded. Subsequent variable selection made use of Factor Analysis (FA) and Unsupervised Variable Selection (UzFS). The data was divided into test and training sets using cluster analysis. These two sets were characterised by similar and consistent distributions of compounds in a high dimensional, but relevant predictor space. Multiple regression was then used to determine a subset of predictors from which to determine QSAR models for affinity to alpha2-ARs. Two multivariate procedures, Continuum Regression (the Portsmouth formulation) and Canonical Correlation Analysis (CCA), have been used to specify models for affinity and selectivity, respectively. Reasonable predictions were obtained using these in silico screening tools.

Models, Molecular↗

Free energy perturbation approach to the critical assessment of selective cyclooxygenase-2 inhibitors.

The discovery of selective cyclooxygenase-2 (COX-2) inhibitors represents a major achievement of the efforts over the past few decades to develop therapeutic treatments for inflammation. To gain insights into designing new COX-2-selective inhibitors, we address the energetic and structural basis for the selective inhibition of COX isozymes by means of a combined computational protocol involving docking experiment, force field design for the heme prothetic group, and free energy perturbation (FEP) simulation. We consider both COX-2- and COX-1-selective inhibitors taking the V523I mutant of COX-2 to be a relevant structural model for COX-1 as confirmed by a variety of experimental and theoretical evidences. For all COX-2-selective inhibitors under consideration, we find that free energies of binding become less favorable as the receptor changes from COX-2 to COX-1, due to the weakening and/or loss of hydrogen bond and hydrophobic interactions that stabilize the inhibitors in the COX-2 active site. On the other hand, COX-1-selective oxicam inhibitors gain extra stabilization energy with the change of residue 523 from valine to isoleucine because of the formations of new hydrogen bonds in the enzyme-inhibitor complexes. The utility of the combined computational approach, as a valuable tool for in silico screening of COX-2-selective inhibitors, is further exemplified by identifying the physicochemical origins of the enantiospecific selective inhibition of COX-2 by alpha-substituted indomethacin ethanolamide inhibitors.

Amino Acid Sequence↗

VolSurf analysis of pharmacokinetic properties for several antifungal sesquiterpene lactones isolated from Greek Centaurea sp.

Sesquiterpene lactones are terpenoid compounds characteristic of the Asteraceae (Compositae) possessing a variety of biological activities, such as cytotoxic, antitumor, antibacterial, and antifungal. The prediction of the pharmacokinetic profile of several antifungal sesquiterpene lactones, isolated from Greek taxa of Centaurea sp., was undertaken in this study using the VolSurf procedure. The molecules were projected on the following pre-calculated ADME models: Caco-2 cell permeability, plasma protein affinity, blood-brain barrier permeation and thermodynamic solubility. The in silico projection revealed a non optimal pharmacokinetic profile for the studied compounds. ADME in silico screening of a semi-synthetic derivatives virtual library has been performed in order to optimize the pharmacokinetic properties. A number of derivatives were proposed as it was predicted to have higher Caco-2 cell permeability, while the pharmacokinetic behaviour regarding BBB penetration, protein binding and solubility was mainly preserved.

Antifungal Agents↗

Comparison of a homology model and the crystallographic structure of human 11beta-hydroxysteroid dehydrogenase type 1 (11betaHSD1) in a structure-based identification of inhibitors.

Human 11beta-hydroxysteroid dehydrogenase type 1 (11betaHSD1) catalyzes the interconversion of cortisone into active cortisol. 11betaHSD1 inhibition is a tempting target for the treatment of a host of human disorders that might benefit from blockade of glucocorticoid action, such as obesity, metabolic syndrome, and diabetes type 2. Here, we report an in silico screening study aimed at identifying new selective inhibitors of human 11betaHSD1 enzyme. In the first step, homology modeling was employed to build the 3D structure of 11betaHSD1. Further, molecular docking was used to validate the predicted model by showing that it was able to discriminate between known 11betaHSD1 inhibitors or substrates and non-inhibitors. The homology model was found to reproduce closely the crystal structure that became publicly available in the final stages of this work. Finally, we carried out structure-based virtual screening experiments on both the homology model and the crystallographic structure with a database of 114,000 natural molecules. Among these, 15 molecules were consistently selected as inhibitors based on both the model and crystal structures of the enzyme, implying a good quality for the homology model. Among these putative 11betaHSD1 inhibitors, two were flavonone derivatives that have already been shown to be potent inhibitors of the enzyme.

11-beta-Hydroxysteroid Dehydrogenase Type 1↗

Identification and validation of natural dengue virus NS1 inhibitors with promising antiviral potential.

Dengue infection remains a major global public health challenge, with no specific antiviral therapy currently available. The dengue virus non-structural protein 1 (NS1) exists in both intracellular and secreted forms playing a pivotal role in viral replication, immune evasion, and pathogenesis, particularly by contributing to endothelial disruption and vascular leakage during severe disease, thereby making it a promising therapeutic target. In silico screening identified berberine, betulinic acid, and ursolic acid as top candidates, exhibiting high binding affinities and stable interactions within the NS1 binding pocket. These computational predictions were further validated by biophysical assays, which demonstrated strong and specific binding interactions between the purified NS1 protein and the selected compounds. All three compounds significantly reduced viral genome levels, with the highest inhibition observed for berberine (60%), and followed by betulinic acid (40%) and ursolic acid (28%). Consistently, berberine showed the most potent inhibition of both intracellular and extracellular NS1. Overall, these findings highlight the inhibitory potential of natural compounds against DENV NS1 and provide a strong foundation for the development of NS1-targeted antivirals as a novel therapeutic strategy against dengue infection.

Antiviral Agents↗

Integrated Genome Mining and Bioactivity-Guided Isolation of Antimicrobial Peptides from Bacillus amyloliquefaciens BS4.

Bacterial resistance remains a critical global health challenge, driving the continuous search for novel antimicrobial agents. Bacillus amyloliquefaciens is a recognized repository of bioactive metabolites; however, its full biosynthetic potential requires integrated genomic and experimental validation. This study characterized the antimicrobial profile of B. amyloliquefaciens BS4 through a hybrid pipeline. Genome sequencing and de novo assembly revealed a 3.9 Mb chromosome with a G + C content of 46.14%. Functional annotation identified 3,887 coding sequences, including pathways for siderophore biosynthesis and a complete bacilysin biosynthetic cluster. BGC analysis using antiSMASH v7.1.0 and BAGEL4 identified 18 biosynthetic gene clusters, while similarity network analysis via BiG-SCAPE highlighted unique singleton BGCs, indicating untapped biosynthetic diversity. Although in silico screening via Macrel predicted two putative cationic antimicrobial peptides (AMPs), bioactivity-guided purification utilizing sequential RP-HPLC, and de novo sequencing revealed a distinct set of four active peptides. Notably, three of these sequences were identified as fragments derived from the BclA exosporium protein family, highlighting the structural proteome as a non-canonical source of antimicrobials. The purified fractions exhibited activity against M. luteus and E. coli, while displaying no significant hemolytic activity or cytotoxicity, even above the MIC values. Molecular docking further supported the interaction of these candidates with bacterial targets. Overall, this hybrid strategy effectively uncovers the antimicrobial complexity of BS4, revealing 'cryptic' peptide candidates with therapeutic potential.

Bacillus amyloliquefaciens BS4↗

A retinoic acid binding cytochrome P450: CYP120A1 from Synechocystis sp. PCC 6803.

At least 35 cytochrome P450 (P450, CYP) or cytochrome P450-like genes have been identified in 10 cyanobacterial genomes yet none have been functionally characterized. CYP110 and CYP120 represent the two largest cyanobacterial P450 families with 16 and four members, respectively, identified to date. The Synechocystis sp. PCC 6803 CYP120A1 protein sequence shares high degrees of conservation with CYP120A2 from Trichodesmium erythraeum IMS101 and CYP120B1 and CYP120C1 from Nostoc punctiforme PCC 73102. In this communication, we report the cloning, expression, purification, and characterization of CYP120A1 from Synechocystis. Homology modeling predictions of the three-dimensional structure of CYP120A1 coupled with in silico screening for potential substrates and experimental spectroscopic analyses have identified retinoic acid as a compound binding with high affinity to this P450's catalytic site. These characterizations of Synechocystis CYP120A1 lay the initial foundations for understanding the basic role of cytochrome P450s in cyanobacteria and related organisms.

Bacterial Proteins↗

Identification of BCOX1, a novel gene overexpressed in breast cancer.

The identification of tumor-associated antigens, which are specifically expressed in cancer tissues, is of utmost important for immunotherapy of breast cancer. We have combined in silico screening and experimental expression analysis to identify genes that are differentially expressed in breast carcinomas compared with their corresponding normal tissues. Using these approaches, we identified a novel gene, BCOX1, with overexpression in breast carcinoma. BCOX1 was highly homologous to KIAA0100, a hypothetical gene located on chromosome 17q11.2. RNA in situ hybridization shows that BCOX1 mRNA signal is mainly located in the cytoplasm of breast carcinoma epithelial cells, but not in those of normal epithelial cells, stroma cells and lymphocytes. Furthermore, mRNA expression of BCOX1 was moderately elevated in ductal in situ carcinoma (DCIS), peaked in invasive breast carcinoma (IBC) and metastatic breast carcinoma cells (MET) whereas absent in benign ductal epithelial cells. The predicted BCOX1 open reading frame of 666 bp encodes a putative protein of 222 amino acid residues with a calculated molecular weight of 2,4920 Da and a PI of 5.86. Computational analyses predict that the putative BCOX1 protein is a cytoplasmic protein. The functional relevance of this novel gene is yet to be determined. This study warrants further investigations to explore the molecular functions of BCOX1, and to determine its potential diagnostic and therapeutic applications for breast cancer.

Antigens, Neoplasm↗