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At least 343 records · Page 19Linked to original sources
PubMed2004

The selection and design of GPCR ligands: from concept to the clinic.

Virtual screening methods using structure-based, pharmacophore-based and descriptor based protocols may be used to identify ligands for the G-protein coupled receptor target family. A complementary approach is the synthesis and screening of compound libraries designed using privileged motifs and/or based on validated hit molecules. A virtual screening approach based on molecular docking performed with GOLD using a templated homology model and a consensus scoring procedure can identify vasopressin 1a receptor antagonists. In a separate project a library design and synthesis approach based around validated hit GPCR ligands led to the identification of potent oxytocin antagonists. Subsequent optimisation of the initial library compounds has provided compounds that are now being evaluated in the clinic for the treatment of preterm labour.

Animals↗
PubMed2003

Markovian chemicals "in silico" design (MARCH-INSIDE), a promising approach for computer-aided molecular design I: discovery of anticancer compounds.

A simple stochastic approach, designed to model the movement of electrons throughout chemical bonds, is introduced. This model makes use of a Markov matrix to codify useful structural information in QSAR. The self-return probabilities of this matrix throughout time ((SR)pi(k)) are then used as molecular descriptors. Firstly, a calculation of (SR)pi(k) is made for a large series of anticancer and non-anticancer chemicals. Then, k-Means Cluster Analysis allows us to split the data series into clusters and ensure a representative design of training and predicting series. Next, we develop a classification function through Linear Discriminant Analysis (LDA). This QSAR discriminates between anticancer compounds and non-active compounds with a correct global classification of 90.5% in the training series. The model also correctly classified 86.07% of the compounds in the predicting series. This classification function is then used to perform a virtual screening of a combinatorial library of coumarins. In this connection, the biological assay of some furocoumarins, selected by virtual screening using the present model, gives good results. In particular, a tetracyclic derivative of 5-methoxypsoralen (5-MOP) has an IC50 against HL-60 tumoral line around 6 to 10 times lower than those for 8-MOP and 5-MOP (reference drugs), respectively. Finally, application of Iso-contribution Zone Analysis (IZA) provides structural interpretation of the biological activity predicted with this QSAR.

Computer Simulation↗
PubMed2002

PRO_SELECT: combining structure-based drug design and array-based chemistry for rapid lead discovery. 2. The development of a series of highly potent and selective factor Xa inhibitors.

In silico screening of combinatorial libraries prior to synthesis promises to be a valuable aid to lead discovery. PRO_SELECT, a tool for the virtual screening of libraries for fit to a protein active site, has been used to find novel leads against the serine protease factor Xa. A small seed template was built upon using three iterations of library design, virtual screening, synthesis, and biological testing. Highly potent molecules with selectivity for factor Xa over other serine proteases were rapidly obtained.

Animals↗
PubMed2004

Identification of novel estrogen receptor alpha antagonists.

We have identified novel estrogen receptor alpha (ERalpha) antagonists using both cell-based and computer-based virtual screening strategies. A mammalian two-hybrid screen was used to select compounds that disrupt the interaction between the ERalpha ligand binding domain (LBD) and the coactivator SRC-3. A virtual screen was designed to select compounds that fit onto the LxxLL peptide-binding surface of the receptor, based on the X-ray crystal structure of the ERalpha LBD complexed with a LxxLL peptide. All selected compounds effectively inhibited 17-beta-estradiol induced coactivator recruitment with potency ranging from nano-molar to micromolar. However, in contrast to classical ER antagonists, these novel inhibitors poorly displace estradiol in the ER-ligand competition assay. Nuclear magnetic resonance (NMR) suggested direct binding of these compounds to the receptors pre-complexed with estradiol and further demonstrated that no estradiol displacement occurred. Partial proteolytic enzyme digestion revealed that, when compared with 17-beta-estradiol- and 4 hydroxy-tamoxifen (4-OHT) bound receptors, at least one of these compounds might induce a unique receptor conformation. These small molecules may represent new classes of ER antagonists, and may have the potential to provide an alternative for the current anti-estrogen therapy.

Acetyltransferases↗
PubMed2004

Strategies for the design of inhibitors of aldose reductase, an enzyme showing pronounced induced-fit adaptations.

Aldose reductase is involved in the polyol pathway, catalyzing the reduction of glucose to sorbitol. However, due to pronounced binding site adaptations, the enzyme can operate on a broad palette of structurally diverse substrates ranging from small aliphatic and aromatic aldehydes up to steroid-type ligands. A comparative analysis of the presently accessible crystal structures of aldose reductase complexes reveals four binding-competent protein conformations. Additional relevant conformers are detected through molecular dynamics simulations. They indicate an equilibrium of several conformers which is shifted towards the binding-competent geometries upon ligand binding. Such a manifold system with several alternative binding site conformers requires some tailored concepts in virtual screening. We followed two strategies, both successfully suggesting new micromolar inhibitors. In a first attempt, we concentrated on one preferred conformer and performed a virtual screening, assuming that the binding pocket of aldose reductase adopts only this conformation. In a second approach, we followed a ligand superpositioning method. Ligands were extracted in their bound conformations from three different crystal structures, all accommodating the ligands with different active site conformations. After merging these ligands into one supermolecule, mutual alignments were computed, taking candidate ligands from a screening database. The latter strategy also retrieved several structurally new inhibitors of micromolar potency.

Aldehyde Reductase↗
PubMed2006

Recent advances in computational prediction of drug absorption and permeability in drug discovery.

Approximately 40%-60% of developing drugs failed during the clinical trials because of ADME/Tox deficiencies. Virtual screening should not be restricted to optimize binding affinity and improve selectivity; and the pharmacokinetic properties should also be included as important filters in virtual screening. Here, the current development in theoretical models to predict drug absorption-related properties, such as intestinal absorption, Caco-2 permeability, and blood-brain partitioning are reviewed. The important physicochemical properties used in the prediction of drug absorption, and the relevance of predictive models in the evaluation of passive drug absorption are discussed. Recent developments in the prediction of drug absorption, especially with the application of new machine learning methods and newly developed software are also discussed. Future directions for research are outlined.

Computer Simulation↗
PubMed2001

3-D pharmacophores in drug discovery.

In this chapter we review the use of 3-D pharmacophores in drug discovery. Recent advances are highlighted, including the application of pharmacophore descriptors generated both from ligands and protein binding sites. The application of 3-D pharmacophore fingerprints as molecular descriptors for similarity and diversity applications such as virtual screening, library design and QSAR is discussed. In addition, we highlight the quantification of structure-based diversity using site-derived fingerprints, and review virtual screening methods using both single refined hypotheses and the fingerprints of multiple potential hypotheses. Further, we discuss methods that take protein flexibility and molecular shape-into account. Each of the above techniques are reviewed with particular reference to the recent advances, advantages and challenges of each methodology.

Animals↗
PubMed2005

Approach to novel functional foods for stress control: 1. Toward structure-activity relationship and data mining of food compounds by chemoinformatics.

Over the past several decades, thousands of natural organic compounds have been isolated from foods, and the information about their structures and biological activities has been accumulated. Despite the long research history of food products and their potential great promise as a medicine and functional food, the systematic research and development have not been carried out extensively. For understanding of the comprehensive structure-activity relationship, we have developed the database system of flavonoids, which are frequently found in vegetables and fruits. We also plan to execute a virtual screening of flavonoids with antidepressant activity by using the database and an advanced chemoinformatic tool. In this section, we will briefly describe (1) flavonoid database and (2) virtual screening of antidepressant compounds.

Antidepressive Agents↗
PubMed2005

Targeting drug-efflux pumps -- a pharmacoinformatic approach.

In line with our studies on propafenone-type inhibitors of P-glycoprotein (P-gp), we applied several methods to approach virtual screening tools for identification of new P-gp inhibitors on one hand and the molecular basis of ligand-protein interaction on the other hand. For virtual screening, a combination of autocorrelation vectors and selforganising artificial neural networks proved extremely valuable in identifying P-gp inhibitors with structurally new scaffolds. For a closer view on the binding region for propafenone-type ligands we applied a combination of pharmacophore-driven photoaffinity labeling and protein homology modeling. On LmrA, a bacterial homologue of P-gp, we were able to identify distinct regions on transmembrane helices 3, 5 and 6 which show significant changes in the labeling pattern during different steps of the catalytic cycle.

ATP Binding Cassette Transporter, Subfamily B, Mem↗
PubMed2004

Identification of non-phosphate-containing small molecular weight inhibitors of the tyrosine kinase p56 Lck SH2 domain via in silico screening against the pY + 3 binding site.

The protein p56 lymphoid T cell tyrosine kinase (Lck) is predominantly expressed in T lymphocytes where it plays a critical role in T-cell-mediated immune response. Lck participates in phosphotyrosine-dependent protein-protein interactions through its modular binding unit, the Src homology-2 (SH2) domain. Accordingly, virtual screening methods combined with experimental assays were used to identify small molecular weight nonpeptidic compounds that block Lck SH2 domain-dependent interactions. Virtual screening included scoring normalization procedures and postdocking structural clustering that is shown to facilitate the selection of active compounds. By targeting the well-defined hydrophobic binding pocket known to impart specificity on Lck-protein interactions (i.e., pY + 3 site), inhibitors of the Lck SH2 domain were discovered that omit the phosphotyrosine (pY) or related moieties. The 34 out of 196 computationally selected compounds were shown to inhibit Lck SH2 domain association with phosphorylated immunoreceptor tyrosine based activation motifs peptide. Twenty-four of the active compounds were further tested for their ability to modulate biological function. Thirteen of these compounds showed inhibitory activity in mixed lymphocyte culture assay. Fluorescence titration experiments on four of these active compounds further verified their binding to the SH2 domain. Because of their simple chemical structures, these small organic compounds have the potential to act as lead compounds for the development of novel immunosuppressant drugs.

Animals↗
PubMed2003

Chemical feature-based pharmacophores and virtual library screening for discovery of new leads.

During the past years, efforts in the pharmaceutical industry have focused on optimizing the early phase hit-to-lead development of the drug discovery process. In silico-based high-throughput screening (HTS) approaches emerged, with a number of issues arising, such as the need for efficient search algorithms, library design, diversity, drug- and/or lead-likeness. These problems were addressed in numerous publications. This review focuses on the generation and use of virtual compound libraries, and on studies in which chemical feature-based pharmacophore models are used in combination with in silico screening. These procedures are generally used to obtain hits (or leads) that are more likely to give successful clinical candidates.

Combinatorial Chemistry Techniques↗
PubMed2006

Improved lead-finding for kinase targets using high-throughput docking.

Protein kinases represent a major class of drug targets for the pharmaceutical industry, and the identification of kinase inhibitors with novel and diverse chemotypes is therefore a high priority. Virtual screening methods are a primary source for the discovery of lead molecules for drug development, with high-throughput docking algorithms being among the most extensively used of these methods. A number of developments in virtual screening technologies have resulted in more effective computer-based compound screening of potential kinase inhibitors. These developments include the following: (i) conformational search methods for pose generation; (ii) improvements in the prediction of protein-ligand binding energy through the use of scoring functions; (iii) the use of interaction filters for identifying ligand poses with known binding determinants; and (iv) the impact of binding site flexibility upon high-throughput docking success. This review discusses the application of these methods in the context of the discovery of kinase adenosine triphosphate antagonists.

Animals↗
PubMed2001

A virtual high throughput screen for high affinity cytochrome P450cam substrates. Implications for in silico prediction of drug metabolism.

Structure-based virtual screening techniques require reliable scoring functions to discriminate potential substrates effectively. In this study we compared the performance of GOLD, PMF, DOCK and FlexX scoring functions in FlexX flexible docking to cytochrome P450cam binding site. Crystal structures of protein-substrate complexes were most effectively reproduced by the FlexX/PMF method. On the other hand, the FlexX/GOLD approach provided the best correlation between experimental binding constants and predicted scores. Binding modes selected by the FlexX/PMF approach were rescored by GOLD to obtain a reliable measure of binding energetics. The effectiveness of the FlexX/PMF/GOLD method was demonstrated by the correct classification of 32 out of the 33 experimentally studied compounds and also in a virtual HTS test on a library of 10,000 compounds. Although almost all the available functions were developed to be general, our study on cytochrome P450cam substrates suggests that careful selection or even tailoring the scoring function might increase the prediction power of virtual screens significantly. The FlexX/PMF/GOLD methodology was tested on cytochrome P450 3A4 substrates and inhibitors. This preliminary study revealed that the combined function was able to recognise 334 out of the 345 compounds bound to 3A4.

Binding Sites↗
PubMed2001

Combinatorial networks.

A novel approach for the analysis and virtual screening of large combinatorial libraries is presented. The method attempts to relieve the computational burden by computing the properties of the products in a way that does not require their explicit enumeration. In particular, a small subset of compounds from the virtual library is identified and their descriptors are calculated in a conventional manner. The resulting data is used as input to a multilayer perceptron, which is trained to predict the descriptors of the products from the descriptors of their respective building blocks. Once trained, the neural network is able to estimate the descriptors of the remaining members of the virtual library with remarkable accuracy, without ever, generating their connection tables. This method eliminates the two most time-consuming steps in virtual screening and allows the processing of very large combinatorial libraries that are intractable with conventional techniques.

Chemistry Techniques, Analytical↗
PubMedDate not supplied

Ensemble docking into flexible active sites. Critical evaluation of FlexE against JNK-3 and beta-secretase.

One of the main complicating factors in structure-based drug design is the conformational rearrangement of the receptor upon ligand binding implicating protein flexibility as a crucial component in virtual screening. The FlexE approach allows flexibility through discrete alternative conformations of varying parts of the protein taken from structures having similar backbone traces. Here the performance of FlexE was tested against that of FlexX and FlexX-Pharm, by carrying out virtual screening experiments on two sets of structurally distinct complexes, for the enzymes beta-secretase (BACE), and c-jun N-terminal kinase 3 (JNK-3). A large number of incompatible instances occurred between structural elements of the proteins thus loop movements could not be studied in JNK-3 as well as in BACE. The investigation of the side-chain flexibility revealed that at the most FlexE could achieve the enrichment yielded by FlexX in JNK-3 but not in BACE. Although limited side-chain variations (e.g. different protonation states) can be treated by FlexE, docking into protein ensembles remains a practical tool that decreases the average run time for a ligand.

Amyloid Precursor Protein Secretases↗
PubMed2004

High-throughput docking as a source of novel drug leads.

Receptor-based virtual screening has become a viable source of novel leads in the pharmaceutical industry. The rapidly growing availability of structural information across protein families, the accessibility to increased computational power at affordable cost, as well as an improved understanding on how to effectively apply virtual screening technologies has contributed to their emergence. Nonetheless, continued improvement in the accuracy of scoring functions and a greater understanding of protein mobility is critical to advance the technology further.

Binding Sites↗
PubMed2005

New inhibitors of the Tat-TAR RNA interaction found with a "fuzzy" pharmacophore model.

TAR RNA is a potential target for AIDS therapy. Ligand-based virtual screening was performed to retrieve novel scaffolds for RNA-binding molecules capable of inhibiting the Tat-TAR interaction, which is essential for HIV replication. We used a "fuzzy" pharmacophore approach (SQUID) and an alignment-free pharmacophore method (CATS3D) to carry out virtual screening of a vendor database of small molecules and to perform "scaffold-hopping". A small subset of 19 candidate molecules were experimentally tested for TAR RNA binding in a fluorescence resonance energy transfer (FRET) assay. Both methods retrieved molecules that exhibited activities comparable to those of the reference molecules acetylpromazine and chlorpromazine, with the best molecule showing ten times better binding behavior (IC50 = 46 microM). The hits had molecular scaffolds different from those of the reference molecules.

Acepromazine↗