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At least 739 records · Page 41Linked to original sources
PubMed2002

The genesis of high-throughput structure-based drug discovery using protein crystallography.

Over the past 12 years, drugs have been developed using structure-based drug design relying upon traditional crystallographic methods. Established successes, such as the drugs designed against HIV-1 protease and neuraminidase, demonstrate the utility of a structure-based approach in the drug-discovery process. However, the approach has historically lacked throughput and reliability capabilities; these bottlenecks are being overcome by breakthroughs in high-throughput structural biology. Recent technological innovations such as submicroliter high-throughput crystallization, high-performance synchrotron beamlines and rapid binding-site analysis of de novo targets using virtual ligand screening and small molecule co-crystallization have resulted in a significant advance in structure-based drug discovery.

Crystallography, X-Ray↗
PubMed2005

Identification of a specific inhibitor of the dishevelled PDZ domain.

The Wnt signaling pathways are involved in embryo development as well as in tumorigenesis. Dishevelled (Dvl) transduces Wnt signals from the receptor Frizzled (Fz) to downstream components in canonical and noncanonical Wnt signaling pathways. The Dvl PDZ domain is thought to play an essential role in both pathways, and we recently demonstrated that the Dvl PDZ domain binds directly to Fz receptors. In this study, using structure-based virtual ligand screening, we identified an organic molecule (NSC668036) from the National Cancer Institute small-molecule library that can bind to the Dvl PDZ domain. We then used molecular dynamics simulation to analyze the binding between the PDZ domain and NSC668036 in detail. In addition, we showed that, in Xenopus, as expected, NSC668036 inhibited the signaling induced by Wnt3A. This compound provides a basis for rational design of high-affinity inhibitors of the PDZ domain, which can block Wnt signaling by interrupting the Fz-Dvl interaction.

Adaptor Proteins, Signal Transducing↗
PubMedDate not supplied

High-throughput screening and optimization of photoembossed relief structures.

A methodology for the rapid design, screening, and optimization of coating systems with surface relief structures, using a combination of statistical experimental design, high-throughput experimentation, data mining, and graphical and mathematical optimization routines was developed. The methodology was applied to photopolymers used in photoembossing applications. A library of 72 films was prepared by dispensing a given amount of sample onto a chemically patterned substrate consisting of hydrophilic areas separated by fluorinated hydrophobic barriers. Film composition and film processing conditions were determined using statistical experimental design. The surface topology of the films was characterized by automated AFM. Subsequently, models explaining the dependence of surface topologies on sample composition and processing parameters were developed and used for screening a virtual 4000-membered in silico library of photopolymer lacquers. Simple graphical optimization or Pareto algorithms were subsequently used to find an ensemble of formulations, which were optimal with respect to a predefined set of properties, such as aspect ratio and shape of the relief structures.

Automation↗
PubMedDate not supplied

Toward designing drug-like libraries: a novel computational approach for prediction of drug feasibility of compounds.

Prediction of the degree of drug-like character in small molecules is of great industrial interest. The major barrier, however, is the lack of a definition for drug-like character. We used the concept of the multilevel chemical compatibility (MLCC) between a compound and a drug library as a measure of the drug-like character of a compound. The rationale is that the local chemical environment of each atom or group of atoms in a compound largely contributes to the stability, toxicity, and metabolism in vivo. A systematic comparison of the local environments within a compound and those within the existing drugs provides a basis for determining whether and how much a compound is drug-like. We applied the MLCC calculations to four test sets: top selling drugs, compounds under biological testing prior to the preclinical test, anticancer drugs, and compounds known to have poor drug-like character. The following conclusions were obtained: (1) A convergent number of unique local structure types were found in the analysis of the library of the existing drugs. It suggests that the current drug library contains about 80% of all the viable types; therefore, discovery of a drug with new local structures is only an event of relatively small probability. (2) The method is highly selective in discerning drug-like compounds: most of the top drugs are predicted to be drug-like, about one-quarter of the biological testing compounds are drug-like, and about one-fifth of the anticancer drugs are drug-like. (3) The method also correctly predicted that none of the known problematic compounds are drug-like. (4) The method is fast enough for computational screening of virtual combinatorial chemistry libraries and databases of available compounds.

Combinatorial Chemistry Techniques↗
PubMedDate not supplied

ADME evaluation in drug discovery. 3. Modeling blood-brain barrier partitioning using simple molecular descriptors.

In this paper, QSPR models were developed for in vivo blood-brain partitioning data (logBB) of a large data set consisting of 115 diverse organic compounds. The best model is based on three descriptors: n-octanol/water partition coefficient calculated using the SLOGP approach, logP; high-charged polar surface areas based on the Gasteiger partial charges, HCPSA, and the excessive molecular weight larger than 360, MW(360). The model bears good statistical significance, n = 78, r = 0.88, q = 0.86, s = 0.36, F = 81.5. The actual prediction potential of the model was validated through two external validation sets of 37 diverse compounds. The predicted results demonstrate that the model bears better prediction potential than many other models and can be used for logBB estimations for drug and drug-like molecules. Comparison of several logP calculation approaches suggests that logP calculated by SLOGP can be used as a significant descriptor for the prediction of molecular transport properties because SLOGP gives the most similar results with CLOGP. The QSPR model indicates that larger polar surface areas have a more negative contribution to logBB, but the absolute partial charges on the atoms surrounded by the polar surfaces should be larger than 0.10|e|. Meanwhile, tight junction membranes limit the size of hydrophilic molecules that can cross the membrane with a molecular weight of approximately 360, because when a molecule's weight is larger than 360 it shows a negative contribution to logBB. The computations of molecular surface, partial charges, logP, and logBB have been accomplished using a program called Drug-BB. Moreover, to improve the efficiency of the computations of logP, we made an extensive reparametrization of SLOGP, and the newly developed SLOGP model is only based on simple atomic addition. Further, we developed a set of parameters to calculate the topological polar surface area (TPSA), thus the high-charged topological polar surface area (HCTPSA) could be estimated from the 2D connection information of a molecule. Adopting the new strategies, the estimations of logP, HCTPSA, and logBB are only based on the topological structure of a molecule and therefore, can be used for fast screening of virtual libraries having millions of molecules.

Absorption↗
PubMedDate not supplied

Comparing ligand interactions with multiple receptors via serial docking.

Standard uses of ligand-receptor docking typically focus on the association of candidate ligands with a single targeted receptor, but actual applications increasingly require comparisons across multiple receptors. This study demonstrates that comparative docking to multiple receptors can help to select homology models for virtual compound screening and to discover ligands that bind to one set of receptors but not to another, potentially similar, set. A serial docking algorithm is furthermore described that reduces the computational costs of such calculations by testing compounds against a series of receptor structures and discarding a compound as soon as it fails to satisfy specified bind/no bind criteria for each receptor. The algorithm also realizes substantial efficiencies by taking advantage of the fact that a ligand typically binds in similar conformations to similar receptors. Thus, once detailed docking has been used to fit a ligand into the first of a series of similar receptors, much less extensive calculations can be used for the remaining structures.

Algorithms↗
PubMedDate not supplied

PEARLS: program for energetic analysis of receptor-ligand system.

Analysis of the energetics of small molecule ligand-protein, ligand-nucleic acid, and protein-nucleic acid interactions facilitates the quantitative understanding of molecular interactions that regulate the function and conformation of proteins. It has also been extensively used for ranking potential new ligands in virtual drug screening. We developed a Web-based software, PEARLS (Program for Energetic Analysis of Ligand-Receptor Systems), for computing interaction energies of ligand-protein, ligand-nucleic acid, protein-nucleic acid, and ligand-protein-nucleic acid complexes from their 3D structures. AMBER molecular force field, Morse potential, and empirical energy functions are used to compute the van der Waals, electrostatic, hydrogen bond, metal-ligand bonding, and water-mediated hydrogen bond energies between the binding molecules. The change in the solvation free energy of molecular binding is estimated by using an empirical solvation free energy model. Contribution from ligand conformational entropy change is also estimated by a simple model. The computed free energy for a number of PDB ligand-receptor complexes were studied and compared to experimental binding affinity. A substantial degree of correlation between the computed free energy and experimental binding affinity was found, which suggests that PEARLS may be useful in facilitating energetic analysis of ligand-protein, ligand-nucleic acid, and protein-nucleic acid interactions. PEARLS can be accessed at http://ang.cz3.nus.edu.sg/cgi-bin/prog/rune.pl.

Computer Simulation↗
PubMedDate not supplied

SHED: Shannon entropy descriptors from topological feature distributions.

A novel set of molecular descriptors called SHED (SHannon Entropy Descriptors) is presented. They are derived from distributions of atom-centered feature pairs extracted directly from the topology of molecules. The value of a SHED is then obtained by applying the information-theoretical concept of Shannon entropy to quantify the variability in a feature-pair distribution. The collection of SHED values reflecting the overall distribution of pharmacophoric features in a molecule constitutes its SHED profile. Similarity between pairs of molecules is then assessed by calculating the Euclidean distance of their SHED profiles. Under the assumption that molecules having similar pharmacological profiles should contain similar features distributed in a similar manner, examples are given to show the ability of SHED for scaffold hopping in virtual chemical screening and pharmacological profiling compared to that of substructural BCI fingerprints and three-dimensional GRIND descriptors.

Combinatorial Chemistry Techniques↗
PubMedDate not supplied

GFscore: a general nonlinear consensus scoring function for high-throughput docking.

Most of the recent published works in the field of docking and scoring protein/ligand complexes have focused on ranking true positives resulting from a Virtual Library Screening (VLS) through the use of a specified or consensus linear scoring function. In this work, we present a methodology to speed up the High Throughput Screening (HTS) process, by allowing focused screens or for hitlist triaging when a prohibitively large number of hits is identified in the primary screen, where we have extended the principle of consensus scoring in a nonlinear neural network manner. This led us to introduce a nonlinear Generalist scoring Function, GFscore, which was trained to discriminate true positives from false positives in a data set of diverse chemical compounds. This original Generalist scoring Function is a combination of the five scoring functions found in the CScore package from Tripos Inc. GFscore eliminates up to 75% of molecules, with a confidence rate of 90%. The final result is a Hit Enrichment in the list of molecules to investigate during a research campaign for biological active compounds where the remaining 25% of molecules would be sent to in vitro screening experiments. GFscore is therefore a powerful tool for the biologist, saving both time and money.

Molecular Structure↗
PubMed2000

Fast calculation of molecular polar surface area as a sum of fragment-based contributions and its application to the prediction of drug transport properties.

Molecular polar surface area (PSA), i.e., surface belonging to polar atoms, is a descriptor that was shown to correlate well with passive molecular transport through membranes and, therefore, allows prediction of transport properties of drugs. The calculation of PSA, however, is rather time-consuming because of the necessity to generate a reasonable 3D molecular geometry and the calculation of the surface itself. A new approach for the calculation of the PSA is presented here, based on the summation of tabulated surface contributions of polar fragments. The method, termed topological PSA (TPSA), provides results which are practically identical with the 3D PSA (the correlation coefficient between 3D PSA and fragment-based TPSA for 34 810 molecules from the World Drug Index is 0.99), while the computation speed is 2-3 orders of magnitude faster. The new methodology may, therefore, be used for fast bioavailability screening of virtual libraries having millions of molecules. This article describes the new methodology and shows the results of validation studies based on sets of published absorption data, including intestinal absorption, Caco-2 monolayer penetration, and blood-brain barrier penetration.

Biological Availability↗
PubMed2006

Homology modeling of the serotonin 5-HT1A receptor using automated docking of bioactive compounds with defined geometry.

This paper describes a rhodopsin-based model of 5-HT(1A) serotonin receptor. The flexibility of the receptor was considered by using large number of models for ligand dockings. Rearrangements of the heptahelical bundle were introduced, which resulted in the improvement of correlation between computational results and experimental data. The model was validated by automated docking of conformationally restricted arylpiperazines. Specific interactions, responsible for the recognition of arylpiperazine derivatives, were identified. An ionic bond was formed between the protonated amine of ligands and Asp3.32. The aromatic moiety and its substituents specifically interacted with Phe6.52 and Ser5.42, respectively, while the carbonyl groups of imide part of ligands formed hydrogen bonds with Asn7.39 and Tyr7.43. The model reproduced the binding affinity of the test group of ligands (correlation r = 0.8 between pK(i) and docking score). It also gave the enrichment in virtual screening-like experiment (100 compounds), in which 34 high-affinity compounds were found among 50 top-scored ligands.

Binding Sites↗
PubMed1998

FLEXS: a method for fast flexible ligand superposition.

If no structural information about a particular target protein is available, methods of rational drug design try to superimpose putative ligands with a given reference, e.g., an endogenous ligand. The goal of such structural alignments is, on the one hand, to approximate the binding geometry and, on the other hand, to provide a relative ranking of the ligands with respect to their similarity. An accurate superposition is the prerequisite of subsequent exploitation of ligand data by either 3D QSAR analyses, pharmacophore hypotheses, or receptor modeling. We present the automatic method FLEXS for structurally superimposing pairs of ligands, approximating their putative binding site geometry. One of the ligands is treated as flexible, while the other one, used as a reference, is kept rigid. FLEXS is an incremental construction procedure. The molecules to be superimposed are partitioned into fragments. Starting with placements of a selected anchor fragment, computed by two alternative approaches, the remaining fragments are added iteratively. At each step, flexibility is considered by allowing the respective added fragment to adopt a discrete set of conformations. The mean computing time per test case is about 1:30 min on a common-day workstation. FLEXS is fast enough to be used as a tool for virtual ligand screening. A database of typical drug molecules has been screened for potential fibrinogen receptor antagonists. FLEXS is capable of retrieving all ligands assigned to platelet aggregation properties among the first 20 hits. Furthermore, the program suggests additional interesting candidates, likely to be active at the same receptor. FLEXS proves to be superior to commonly used retrieval techniques based on 2D fingerprint similarities. The accuracy of computed superpositions determines the relevance of subsequently performed ligand analyses. In order to validate the quality of FLEXS alignments, we attempted to reproduce a set of 284 mutual superpositions derived from experimental data on 76 protein-ligand complexes of 14 proteins. The ligands considered cover the whole range of drug-size molecules from 18 to 158 atoms (PDB codes: 3ptb, 2er7). The performance of the algorithm critically depends on the sizes of the molecules to be superimposed. The limitations are clearly demonstrated with large peptidic inhibitors in the HIV and the endothiapepsin data set. Problems also occur in the presence of multiple binding modes (e.g., elastase and human rhinovirus). The most convincing results are achieved with small- and medium-sized molecules (as, e.g., the ligands of trypsin, thrombin, and dihydrofolate reductase). In more than half of the entire test set, we achieve rms deviations between computed and observed alignment of below 1.5 A. This underlines the reliability of FLEXS-generated alignments.

Algorithms↗
PubMed2000

Computational methods for the structural alignment of molecules.

In drug design, often enough, no structural information on a particular receptor protein is available. However, frequently a considerable number of different ligands is known together with their measured binding affinities towards a receptor under consideration. In such a situation, a set of plausible relative superpositions of different ligands, hopefully approximating their putative binding geometry, is usually the method of choice for preparing data for the subsequent application of 3D methods that analyze the similarity or diversity of the ligands. Examples are 3D-QSAR studies, pharmacophore elucidation, and receptor modeling. An aggravating fact is that ligands are usually quite flexible and a rigorous analysis has to incorporate molecular flexibility. We review the past six years of scientific publishing on molecular superposition. Our focus lies on automatic procedures to be performed on arbitrary molecular structures. Methodical aspects are our main concern here. Accordingly, plain application studies with few methodical elements are omitted in this presentation. While this review cannot mention every contribution to this actively developing field, we intend to provide pointers to the recent literature providing important contributions to computational methods for the structural alignment of molecules. Finally we provide a perspective on how superposition methods can effectively be used for the purpose of virtual database screening. In our opinion it is the ultimate goal to detect analogues in structure databases of nontrivial size in order to narrow down the search space for subsequent experiments.

Algorithms↗
PubMed2004

Crystal structure of transglutaminase 3 in complex with GMP: structural basis for nucleotide specificity.

Epidermal-type Transglutaminase 3 (TGase 3) is a Ca(2+)-dependent enzyme involved in the cross-linking of structural proteins required in the assembly of the cell envelope. We have recently shown that calcium-activated TGase 3, like TGase 2, can bind, hydrolyze, and is inhibited by GTP despite lacking structural homology with other GTP-binding proteins. Here we report the crystal structure determined at 2.0 A resolution of TGase 3 in complex with GMP to elucidate the structural features required for nucleotide recognition. Binding affinities for various nucleotides were found by fluorescence displacement to be as follows: guanosine 5'-3-O-(thio)triphosphate (GTPgammaS) (0.4 microm), GTP (0.6 microm), GDP (1.0 microm), GMP (0.4 microm), and ATP (28.0 microm). Furthermore, we found that GMP binds as a reversible, noncompetitive inhibitor of TGase 3 transamidation activity, similar to GTPgammaS and GDP. A genetic algorithm similarity program (GASP) approach (virtual ligand screening) identified three compounds from the Lead Quest trade mark data base (Tripos Inc.) based on superimposition of GTPgammaS, GDP, and GMP guanine nucleotides from our crystal structures to generate the minimum align flexible fragment. These three were nucleotide analogs without a phosphate group containing the minimal binding motif for TGase 3 that includes a nucleoside recognition groove. Binding affinities were measured as follows: TP349915 (K(d) = 4.1 microm), TP395289 (K(d) = 38.5 microm), TP394305 (K(d) = 1.0 mm). Remarkably, these compounds do not inhibit but instead activate TGase 3 transamidation by about 10-fold. These results suggest that the nucleotide binding pocket in TGase 3 may be exploited to either enhance or inhibit the enzymatic activity as required for different therapeutic approaches.

Adenosine Triphosphate↗
PubMed2006

Real-time electromagnetic navigation bronchoscopy to peripheral lung lesions using overlaid CT images: the first human study.

STUDY OBJECTIVES: To characterize the feasibility, accuracy, and safety of the superDimension/Bronchus system (SDBS) [superDimension, Ltd; Hertzliya, Israel] in navigating to previously unreachable peripheral lung lesions and obtaining biopsy specimens. DESIGN: Open-label, prospective, controlled clinical study. SETTING: Pulmonary institute of a university-affiliated municipal hospital. PATIENTS: Thirteen adult candidates for nonemergency bronchoscopy who gave informed consent to participate. INTERVENTIONS: The patients underwent flexible bronchoscopy using the SDBS, which is based on real-time CT-guided electromagnetic navigation and is capable of reaching peripheral lung masses beyond the reach of the bronchoscope. A position sensor was used to navigate to and sample the various target lesions for biopsy. MEASUREMENTS AND RESULTS: Three-dimensional chest CT was followed by SDBS methodology for marking anatomic landmarks and the target lesion on a virtual bronchoscopy screen and for sampling the lesion. The SDBS assisted in obtaining positive biopsy diagnoses in 9 of 13 cases (69%), with an average navigation accuracy of 5.7 mm. There were no SDBS-related adverse events. CONCLUSIONS: The SDBS is safe and effective in navigating to peripheral lung lesions located beyond the optic limits of a standard flexible bronchoscope.

Adult↗
PubMed2006

eHiTS: an innovative approach to the docking and scoring function problems.

Virtual Ligand Screening (VLS) has become an integral part of the drug design process for many pharmaceutical companies. In protein structure based VLS the aim is to find a ligand that has a high binding affinity to the target receptor whose 3D structure is known. This review will describe the docking tool eHiTS. eHiTS is an exhaustive and systematic docking tool which contains many automated features that simplify the drug design workflow. A description of the unique docking algorithm and novel approach to scoring used within eHiTS is presented. In addition a validation study is presented that demonstrates the accuracy and wide applicability of eHiTS in re-docking bound ligands into their receptors.

Algorithms↗