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Results for “In silico screening”

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PubMed2006

In silico discovery of beta-secretase inhibitors.

Alzheimer's disease, the most common amyloid-associated disorder, accounts for the majority of the dementia diagnosed after the age of 60. The cleavage of the beta-amyloid precursor protein is initiated by beta-secretase (BACE-1), a membrane-bound aspartic protease, which has emerged as an important but difficult protein target. Here, an in silico screening approach consisting of fragment-based docking, ligand conformational search by a genetic algorithm, and evaluation of free energy of binding was used to identify low-molecular-weight inhibitors of BACE-1. More than 300,000 small molecules were docked and about 15,000 prioritized according to a linear interaction energy model with evaluation of solvation by continuum electrostatics. Eighty-eight compounds were tested in vitro, and 10 of them showed an IC(50) value lower than 100 microM in a BACE-1 enzymatic assay. Interestingly, the 10 active compounds shared a triazine scaffold. Moreover, four of them were active in an assay with mammalian cells (EC(50) < 20 microM), indicating that they are cell-permeable. Therefore, these triazine derivatives are very promising lead candidates for BACE-1 inhibition. The discoveries of this series and two other series of nonpeptidic BACE-1 inhibitors demonstrate the usefulness of our in silico high-throughput screening approach.

Amyloid Precursor Protein Secretases↗

PubMed2004

New approaches in identifying drugs to inactivate oncogene products.

With an information explosion on the molecular mechanism of oncogenesis, the completion of the human genome sequence project, and the advances in genomic and proteomic methods, many therapeutic targets for various cancers have been identified. It is timely that a number of new drug development techniques have been developed in this last decade. Candidate drug targets can now be efficiently validated with RNA interference and transgenic animals studies. Combinatorial chemistry provides large numbers of chemical compounds for drug lead discovery and optimization. High throughput assays and high content cell-based assays, in conjunction with sophisticated robotics, are now available for screening large numbers of compounds. Based on X-ray crystallographic structure data, drug leads can be discovered through in silico screening of virtual libraries. By applying these various drug discovery techniques, it is anticipated that more potent and specific anti-cancer agents will be discovered within the next decade.

Combinatorial Chemistry Techniques↗

PubMed2006

An integrated in silico 3D model-driven discovery of a novel, potent, and selective amidosulfonamide 5-HT1A agonist (PRX-00023) for the treatment of anxiety and depression.

We report the discovery of a novel, potent, and selective amidosulfonamide nonazapirone 5-HT1A agonist for the treatment of anxiety and depression, which is now in Phase III clinical trials for generalized anxiety disorder (GAD). The discovery of 20m (PRX-00023), N-{3-[4-(4-cyclohexylmethanesulfonylaminobutyl)piperazin-1-yl]phenyl}acetamide, and its backup compounds, followed a new paradigm, driving the entire discovery process with in silico methods and seamlessly integrating computational chemistry with medicinal chemistry, which led to a very rapid discovery timeline. The program reached clinical trials within less than 2 years from initiation, spending less than 6 months in lead optimization with only 31 compounds synthesized. In this paper we detail the entire discovery process, which started with modeling the 3D structure of 5-HT1A using the PREDICT methodology, and then performing in silico screening on that structure leading to the discovery of a 1 nM lead compound (8). The lead compound was optimized following a strategy devised based on in silico 3D models and realized through an in silico-driven optimization process, rapidly overcoming selectivity issues (affinity to 5-HT1A vs alpha1-adrenergic receptor) and potential cardiovascular issues (hERG binding), leading to a clinical compound. Finally we report key in vivo preclinical and Phase I clinical data for 20m tolerability, pharmacokinetics, and pharmacodynamics and show that these favorable results are a direct outcome of the properties that were ascribed to the compound during the rational structure-based discovery process. We believe that this is one of the first examples for a Phase III drug candidate that was discovered and optimized, from start to finish, using in silico model-based methods as the primary tool.

Animals↗

PubMed2006

Binding mode prediction of strand transfer HIV-1 integrase inhibitors using Tn5 transposase as a plausible surrogate model for HIV-1 integrase.

The crystal structure of Tn5 transposase-DNA complex was used in docking experiments to predict binding modes of HIV-1 integrase strand transfer inhibitors (INSTIs). In fact, the identification of HIV-1 integrase inhibitors from an in vitro screen using Tn5 transposase as the target has been recently reported. Our results suggest the utility of this protein as a useful surrogate model for IN and also for in silico screening, in the search for new potential INSTIs.

HIV Integrase↗

PubMed2006

Virtual screening: are we there yet?

The cost of pharmaceutical development has increased dramatically in recent years, and many assorted approaches have been developed to decrease both the time and costs associated with bringing a drug to the market. Among these methods is the use of in silico screening of compound databases for potential new lead compounds, commonly referred to as virtual screening (VS). Virtual screening has become an integral part of the early discovery process in pharmaceutical development, readily observed by the large number of methodologies that have been published to date. Other reviews have been published detailing the various types of virtual screening methods in use. This work will review some of the virtual screening approaches and strategies that have been attempted to identify compounds to launch medicinal chemistry campaigns. Understanding trends and drivers in VS should help to set expectations about how and when VS could be used and what it can and cannot deliver and how it can be integrated in a successful screening campaign and used in a complementary fashion to HTS.

Computer Simulation↗

PubMed2004

Virtual screening for kinase targets.

Kinases have become a major area of drug discovery and structure-based design. Hundreds of 3D structures for more than thirty different kinases are available to the public. High structural and sequence homology within the kinase gene family makes the remaining kinases ideal targets for homology modeling and virtual screening. Somewhat surprisingly, however, the number of publications about virtual screening of kinases is very low. Therefore, rather than reviewing the field of virtual screening for kinases, we attempt here a hybrid approach of presenting what is known and common practice together with new studies on CDK2 and SRC kinase. To illustrate the challenges and pitfalls of virtual screening for kinase targets we focus on the question of how ranking is influenced by the database screened, the docking scheme, the scoring function, the activity of the compounds used for testing, and small changes in the binding pocket. In addition, a case study of finding irreversible inhibitors of ErbB2 through in silico screening is presented.

Binding Sites↗

PubMed2006

Novel human lipoxygenase inhibitors discovered using virtual screening with homology models.

We report the discovery of new, low micromolar, small molecule inhibitors of human platelet-type 12- and reticulocyte 15-lipoxygenase-1 (12-hLO and 15-hLO) using structure-based methods. Specifically, we created homology models of 12-hLO and 15-hLO, based on the structure of rabbit 15-lipoxygenase, for in silico screening of a large compound library followed by in vitro screening of 20 top scoring molecules. Eight of these compounds inhibited either 12- or 15-human lipoxygenase with lower than 100 microM affinity. Of these, we obtained IC50 values for the three best inhibitors, all of which displayed low micromolar inhibition. One compound showed specificity for 15-hLO versus 12-hLO; however, a selective inhibitor for 12-hLO was not identified. As a control we screened 20 randomly selected compounds, of which none showed low micromolar inhibition. The new low-micromolar inhibitors appear to be suitable as leads for further inhibitor development efforts against 12-hLO and 15-hLO, based on the fact their size and chemical properties are appropriate to classify them as drug-like compounds. The models of these protein-inhibitor complexes suggest strategies for future development of selective lipoxygenase inhibitors.

Animals↗

PubMed2005

Integration of virtual screening with high-throughput flow cytometry to identify novel small molecule formylpeptide receptor antagonists.

The formylpeptide receptor (FPR) family of G-protein-coupled receptors contributes to the localization and activation of tissue-damaging leukocytes at sites of chronic inflammation. We developed a FPR homology model and pharmacophore (based on the bovine rhodopsin crystal structure and known FPR ligands, respectively) for in silico screening of approximately 480,000 drug-like small molecules. A subset of 4324 compounds that matched the pharmacophore was then physically screened with the HyperCyt flow cytometry platform in high-throughput, no-wash assays that directly measure human FPR binding, with samples (each approximately 2500 cells in 2 microl) analyzed at 40/min. From 52 confirmed hits (1.2% hit rate), we identified 30 potential lead compounds (inhibition constant, Ki= 1-32 microM) representing nine distinct chemical families. Four compounds in one family were weak partial agonists. All others were antagonists. This virtual screening approach improved the physical screening hit rate by 12-fold (versus 0.1% hit-rate in a random compound collection), providing an efficient process for identifying small molecule antagonists.

Amino Acid Sequence↗

PubMed2003

Rational design, synthesis, and verification of affinity ligands to a protein surface cleft.

The structure-based design, synthesis, and screening of a glucuronic acid scaffold library of affinity ligands directed toward the catalytic cleft on porcine pancreas alpha-amylase are presented. The design was based on the simulated docking to the enzyme active site of 53 aryl glycosides from the Available Chemicals Directory (ACD) selected by in silico screening. Twenty-three compounds were selected for synthesis and screened in solution for binding toward alpha-amylase using nuclear magnetic resonance techniques. The designed molecules include a handle outside of the binding site to allow their attachment to various surfaces with minimal loss of binding activity. After initial screening in solution, one affinity ligand was selected, immobilized to Sepharose (Amersham Biosciences), and evaluated as a chromatographic probe. A column packed with ligand-coupled Sepharose specifically retained the enzyme, which could be eluted by a known inhibitor.

Animals↗

PubMed2002

Integration of virtual and high-throughput screening.

High-throughput and virtual screening are important components of modern drug discovery research. Typically, these screening technologies are considered distinct approaches, as one is experimental and the other is theoretical in nature. However, given their similar tasks and goals, these approaches are much more complementary to each other than often thought. Various statistical, informatics and filtering methods have recently been introduced to foster the integration of experimental and in silico screening and maximize their output in drug discovery. Although many of these ideas and efforts have not yet proceeded much beyond the conceptual level, there are several success stories and good indications that early-stage drug discovery will benefit greatly from a more unified and knowledge-based approach to biological screening, despite the many technical advances towards even higher throughput that are made in the screening arena.

Drug Design↗

PubMed2004

Transcriptome profiling in root nodules and arbuscular mycorrhiza identifies a collection of novel genes induced during Medicago truncatula root endosymbioses.

Transcriptome profiling based on cDNA array hybridizations and in silico screening was used to identify Medicago truncatula genes induced in both root nodules and arbuscular mycorrhiza (AM). By array hybridizations, we detected several hundred genes that were upregulated in the root nodule and the AM symbiosis, respectively, with a total of 75 genes being induced during both interactions. The second approach based on in silico data mining yielded several hundred additional candidate genes with a predicted symbiosis-enhanced expression. A subset of the genes identified by either expression profiling tool was subjected to quantitative real-time reverse-transcription polymerase chain reaction for a verification of their symbiosis-induced expression. That way, induction in root nodules and AM was confirmed for 26 genes, most of them being reported as symbiosis-induced for the first time. In addition to delivering a number of novel symbiosis-induced genes, our approach identified several genes that were induced in only one of the two root endosymbioses. The spatial expression patterns of two symbiosis-induced genes encoding an annexin and a beta-tubulin were characterized in transgenic roots using promoter-reporter gene fusions.

Annexins↗

PubMedDate not supplied

LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters.

From the historically grown archive of protein-ligand complexes in the Protein Data Bank small organic ligands are extracted and interpreted in terms of their chemical characteristics and features. Subsequently, pharmacophores representing ligand-receptor interaction are derived from each of these small molecules and its surrounding amino acids. Based on a defined set of only six types of chemical features and volume constraints, three-dimensional pharmacophore models are constructed, which are sufficiently selective to identify the described binding mode and are thus a useful tool for in-silico screening of large compound databases. The algorithms for ligand extraction and interpretation as well as the pharmacophore creation technique from the automatically interpreted data are presented and applied to a rhinovirus capsid complex as application example.

Antineoplastic Agents↗

PubMedDate not supplied

Consensus scoring criteria for improving enrichment in virtual screening.

MOTIVATION: Virtual screening of molecular compound libraries is a potentially powerful and inexpensive method for the discovery of novel lead compounds for drug development. The major weakness of virtual screening-the inability to consistently identify true positives (leads)-is likely due to our incomplete understanding of the chemistry involved in ligand binding and the subsequently imprecise scoring algorithms. It has been demonstrated that combining multiple scoring functions (consensus scoring) improves the enrichment of true positives. Previous efforts at consensus scoring have largely focused on empirical results, but they have yet to provide a theoretical analysis that gives insight into real features of combinations and data fusion for virtual screening. RESULTS: We demonstrate that combining multiple scoring functions improves the enrichment of true positives only if (a) each of the individual scoring functions has relatively high performance and (b) the individual scoring functions are distinctive. Notably, these two prediction variables are previously established criteria for the performance of data fusion approaches using either rank or score combinations. This work, thus, establishes a potential theoretical basis for the probable success of data fusion approaches to improve yields in in silico screening experiments. Furthermore, it is similarly established that the second criterion (b) can, in at least some cases, be functionally defined as the area between the rank versus score plots generated by the two (or more) algorithms. Because rank-score plots are independent of the performance of the individual scoring function, this establishes a second theoretically defined approach to determining the likely success of combining data from different predictive algorithms. This approach is, thus, useful in practical settings in the virtual screening process when the performance of at least two individual scoring functions (such as in criterion a) can be estimated as having a high likelihood of having high performance, even if no training sets are available. We provide initial validation of this theoretical approach using data from five scoring systems with two evolutionary docking algorithms on four targets, thymidine kinase, human dihydrofolate reductase, and estrogen receptors of antagonists and agonists. Our procedure is computationally efficient, able to adapt to different situations, and scalable to a large number of compounds as well as to a greater number of combinations. Results of the experiment show a fairly significant improvement (vs single algorithms) in several measures of scoring quality, specifically "goodness-of-hit" scores, false positive rates, and "enrichment". This approach (available online at http://gemdock.life. nctu.edu.tw/dock/download.php) has practical utility for cases where the basic tools are known or believed to be generally applicable, but where specific training sets are absent.

Algorithms↗

PubMedDate not supplied

A new strategy for improved secondary screening and lead optimization using high-resolution SPR characterization of compound-target interactions.

Biophysical label-free assays such as those based on SPR are essential tools in generating high-quality data on affinity, kinetic, mechanistic and thermodynamic aspects of interactions between target proteins and potential drug candidates. Here we show examples of the integration of SPR with bioinformatic approaches and mutation studies in the early drug discovery process. We call this combination 'structure-based biophysical analysis'. Binding sites are identified on target proteins using information that is either extracted from three-dimensional structural analysis (X-ray crystallography or NMR), or derived from a pharmacore model based on known binders. The binding site information is used for in silico screening of a large substance library (e.g. available chemical directory), providing virtual hits. The three-dimensional structure is also used for the design of mutants where the binding site has been impaired. The wild-type target and the impaired mutant are then immobilized on different spots of the sensor chip and the interactions of compounds with the wild-type and mutant are compared in order to identify selective binders for the binding site of the target protein. This method can be used as a cost-effective alternative to high-throughput screening methods in cases when detailed binding site information is available. Here, we present three examples of how this technique can be applied to provide invaluable data during different phases of the drug discovery process.

Adenosine Deaminase↗

PubMed2005

Evidence for a dispersed Hox gene cluster in the platyhelminth parasite Schistosoma mansoni.

In most bilaterian organisms so far studied, Hox genes are organized in genomic clusters and determine development along the anteroposterior axis. It has been suggested that this clustering, together with spatial and temporal colinearity of gene expression, represents the ancestral condition. However, in organisms with derived modes of embryogenesis and lineage-dependent mechanisms for the determination of cell fate, temporal colinearity of expression can be lost and Hox cluster organization disrupted, as is the case for the ecdysozoans Drosophila melanogaster and Caenorhabditis elegans and the urochordates Ciona intestinalis and Oikopleura dioica. We sought to determine whether a lophotrochozoan, the platyhelminth parasite Schistosoma mansoni, possesses a conserved or disrupted Hox cluster. Using a polymerase chain reaction (PCR)-based strategy, we have cloned and characterized three novel S. mansoni genes encoding orthologues of Drosophila labial (SmHox1), deformed (SmHox4), and abdominal A (SmHox8), as well as the full-length coding sequence of the previously described Smox1, which we identify as an orthologue of fushi tarazu. Quantitative reverse transcriptase-PCR showed that the four genes were expressed at all life-cycle stages but that levels of expression were differentially regulated. Phylogenetic analysis and the conservation of "parapeptide" sequences C-terminal to the homeodomains of SmHox8 and Smox1 support the grouping of platyhelminths within the lophotrochozoan clade. However, Bacterial Artificial Chromosome (BAC) library screening followed by genome walking failed to reconstitute a cluster. The BAC clones containing Hox genes were sequenced, and in no case were other Hox genes found on the same clone. Moreover, the SmHox4 and SmHox8 genes contained single very large introns (>40 kbp) further indicating that the schistosome Hox cluster is highly extended. Localization of the Hox genes to chromosomes using fluorescence in situ hybridization showed that SmHox4 and SmHox8 are on the long arm of chromosome 4, whereas SmHox1 and Smox1 are on chromosome 3. In silico screening of the available genome sequences corroborated results of Southern blotting and BAC library screening that indicate that there are no paralogues of SmHox1, SmHox4, or SmHox8. The schistosome Hox cluster is therefore not duplicated, but is both dispersed and disintegrated in the genome.

Amino Acid Sequence↗

PubMed2000

Characterization of a novel gene, C21orf6, mapping to a critical region of chromosome 21q22.1 involved in the monosomy 21 phenotype and of its murine ortholog, orf5.

Phenotypic and molecular analyses of patients with partial chromosome 21 monosomy enabled us to define a region, spanning 2.4 Mb between D21S190 and D21S226, associated with arthrogryposis, mental retardation, hypertonia, and several facial anomalies. The markers of the region were used to screen a total human PAC library (Ioannou, RZPD). We isolated 57 PACs, which formed primary contigs. EST clusters (UNIGENE collection) located in a 6-Mb interval, between D21S260 and D21S263, were mapped in individual bacterial clones. We mapped the WI-17843 cluster to the PAC clone J12100, which contains the two anchor markers LB10T and LA329. The open reading frame extends over 960 bp, with three putative start codons. The 1695-bp cDNA containing a polyadenylation signal should correspond to the full-length cDNA. From the genomic sequence, we deduced that the gene contained five exons and that there was a putative promoter sequence upstream from exon 1. In silico screening of DNA databases revealed similarity with a murine EST. The corresponding cDNA (1757 bp) sequence was very similar (>85%) to the human cDNA and had an open reading frame of 876 nucleotides. Somatic hybrid mapping localized the cDNA to mouse chromosome 16. EST analyses and RT-PCR indicated that the third exon in the human gene (exon 2 in the mouse) undergoes alternative splicing. Northern blot hybridization showed that the gene was ubiquitously expressed in humans and mice. The longest mouse clone was used to generate riboprobes, which were hybridized to murine embryos at stages E-9.5, E-10.5, E-12.5, E-13.5, and E-14.5-15, to study the pattern of expression during development. Ubiquitous labeling was observed, with strong signals restricted to limited areas of the telencephalon, the mesencephalon, and the interrhombomeric regions in the central nervous system, and other regions of the body such as the limb buds, branchial arches, and somites.

Amino Acid Sequence↗

PubMed2003

Conferring thermostability to mesophilic proteins through optimized electrostatic surfaces.

Recently, there have been several experimental reports of proteins displaying appreciable stability gains through mutation of one or two amino acid residues. Here, we employ a simple theoretical model to quickly screen mutant structures for increased thermostability through optimization of the protein's electrostatic surface. Our results are able to reproduce the experimental observation that elimination of like-charge repulsions and creation of opposite-charge attractions on the protein surface is an efficient method to confer thermostability to a mesophilic protein. Using Poisson-Boltzmann electrostatics, we calculate relative protein stabilities for the exhaustive surface mutagenesis of the cold shock, RNase T1, and CheY proteins. Comparison with 25 experimentally characterized cold shock protein mutants reveals an average correlation of 0.86. The model is also quantitatively accurate when reproducing the experimental D49A and D49H mutant stabilities of RNase T1. This work represents the first comprehensive in silico screening of mutant candidates likely to confer thermostability to mesophilic proteins through optimization of surface electrostatics. Systematic single mutant, followed by double mutant, screening yields a limited number of mutant structures displaying significant stability gains suitable for subsequent experimental characterization.

Amino Acid Sequence↗

PubMed2005

Atom, atom-type and total molecular linear indices as a promising approach for bioorganic and medicinal chemistry: theoretical and experimental assessment of a novel method for virtual screening and rational design of new lead anthelmintic.

Helminth infections are a medical problem in the world nowadays. In this paper a novel atom-level chemical descriptor has been applied to estimate the anthelmintic activity. Total and local linear indices and linear discriminant analysis were used to obtain a quantitative model that discriminates between anthelmintic and non-anthelmintic drug-like compounds. The discriminant model has an accuracy of 90.11% in the training set, with a high Matthews' correlation coefficient (MCC=0.80). To assess the robustness and predictive power of the obtained model, internal (leave-n-out) and external validation process was performed. The QSAR model correctly classified 88.55% of compounds in this external prediction set, yielding a MCC of 0.77. Another LDA model was carried out to outline some conclusions about the possible modes of action of anthelmintic drugs. It has an accuracy of 93.50% in the training set, and 80.00% in the external prediction set. After that, the developed model was used in the virtual--in silico--screening and several compounds from the Merck Index, Negwer's Handbook and Goodman and Gilman were identified by the model as anthelmintic. Finally, the experimental assay of an organic chemical (a furylethylene derivative) by an in vivo test permits us to carry out an assessment of the model. An accuracy of 100% with the theoretical predictions was observed. These results suggest that the proposed method will be a good tool for studying the biological properties of drug candidates during the early state of the drug-development process.

Anthelmintics↗