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At least 577 records · Page 32Linked to original sources
PubMed2006

A method for induced-fit docking, scoring, and ranking of flexible ligands. Application to peptidic and pseudopeptidic beta-secretase (BACE 1) inhibitors.

Inhibition of beta-secretase (BACE 1) has recently been investigated as a promising therapeutic approach in the treatment of Alzheimer's disease, and a growing number of BACE 1 inhibitors and crystal structures of BACE 1/inhibitors complexes have been reported. We report herein a predictive computational method and its application to potential BACE 1 inhibitors. Using a training set of 50 known highly flexible inhibitors, we developed a docking method that accounts for the flexibility of both the protein and the inhibitors. Protein flexibility is accounted for using a specifically designed genetic algorithm. We next developed a scoring function consisting of force field evaluation of the inhibitor/protein interactions and two additional terms for hydrogen bonding and entropy change upon binding. Discarding three outliers from the training set, our protocol was found to perform well with an rmsd of 1.19 kcal/mol. Evaluation of the predictive power was next carried out by virtual screening of 80 synthetic compounds. The significant enrichment at the top of the ranking list in active compounds demonstrated the ability of the docking and scoring protocol to rank the compounds relative to their activities.

Algorithms↗
PubMed2005

Autocorrelation of molecular electrostatic potential surface properties combined with partial least squares analysis as new strategy for the prediction of the activity of human A(3) adenosine receptor antagonists.

The combination of molecular electrostatic potential (MEP) surface properties (autocorrelation vectors) with the conventional partial least squares (PLS) analysis has been used for the prediction of the human A(3) receptor antagonist activities. Three-hundred-fifty-eight structurally diverse human A(3) receptor antagonists have been utilized to generate a novel ligand-based three-dimensional structure-activity relationship. Remarkably, our chemical library includes all 21 important chemical classes of human A(3) antagonists currently discovered, and it represents the largest molecular collection used to generate a general human A(3) antagonist structure-activity relationship. A robust quantitative model has been obtained as described by both cross-validated correlation coefficient (r(cv) = 0.81) and prediction capability (r(pred) = 0.82). The proposed MEP/PLS approach can be considered as an alternative hit identification tool in virtual screening applications.

Adenosine A3 Receptor Antagonists↗
PubMed2005

Pharmacophore modeling, docking, and principal component analysis based clustering: combined computer-assisted approaches to identify new inhibitors of the human rhinovirus coat protein.

The development and application of a sophisticated virtual screening and selection protocol to identify potential, novel inhibitors of the human rhinovirus coat protein employing various computer-assisted strategies are described. A large commercially available database of compounds was screened using a highly selective, structure-based pharmacophore model generated with the program Catalyst. A docking study and a principal component analysis were carried out within the software package Cerius and served to validate and further refine the obtained results. These combined efforts led to the selection of six candidate structures, for which in vitro anti-rhinoviral activity could be shown in a biological assay.

Antiviral Agents↗
PubMed2006

A critical assessment of docking programs and scoring functions.

Docking is a computational technique that samples conformations of small molecules in protein binding sites; scoring functions are used to assess which of these conformations best complements the protein binding site. An evaluation of 10 docking programs and 37 scoring functions was conducted against eight proteins of seven protein types for three tasks: binding mode prediction, virtual screening for lead identification, and rank-ordering by affinity for lead optimization. All of the docking programs were able to generate ligand conformations similar to crystallographically determined protein/ligand complex structures for at least one of the targets. However, scoring functions were less successful at distinguishing the crystallographic conformation from the set of docked poses. Docking programs identified active compounds from a pharmaceutically relevant pool of decoy compounds; however, no single program performed well for all of the targets. For prediction of compound affinity, none of the docking programs or scoring functions made a useful prediction of ligand binding affinity.

Algorithms↗
PubMed2006

Structure-based design, synthesis, and biological evaluation of novel inhibitors of human cyclophilin A.

Cyclophilin A is involved in many cellular processes, including protein folding and intracellular transports. Because cyclophilin A has been shown to interact with HIV-1 gag proteins and to enhance the viral infectivity, nonimmunosuppressive cyclophilin A ligands may represent a new class of therapeutic agents against HIV. Here, we report a virtual screening using structure- and pharmacophore-based design to identify original nonpeptidic cyclophilin ligands. Following a lead identification of compounds 1 [1-(3-benzyloxypyridin-2-yl)-3-(3-chlorophenyl)urea] and 2 [1-(3-benzyloxypyridin-2-yl)-3-(3-trifluoromethylphenyl)urea] (IC(50) = 0.3 microM), a series of molecules were synthesized from a diarylurea scaffold and evaluated for their in vitro ability to inhibit the cis-trans isomerase activity of cyclophilin A. Molecular modifications provided several more potent compounds, in particular analogues 4d and 4i with IC(50) of 14 and 20 nM, respectively. Then, we evaluated the effect of analogues 1 and 2 on HIV virion infectivity in both immortalized and primary cells. Both 1 and 2 reduced virion infectivity in the replication-defective one-round infection assay, but only 1 impaired wild-type HIV infection in human peripheral blood mononuclear cells.

Anti-HIV Agents↗
PubMed2006

Robust ligand-based modeling of the biological targets of known drugs.

Systematic annotation of the primary targets of roughly 1000 known therapeutics reveals that over 700 of these modulate approximately 85 biological targets. We report the results of three analyses. In the first analysis, drug/drug similarities and target/target similarities were computed on the basis of three-dimensional ligand structures. Drug pairs sharing a target had significantly higher similarity than drug pairs sharing no target. Also, target pairs with no overlap in annotated drug specificity shared lower similarity than target pairs with increasing overlap. Two-way agglomerative clusterings of drugs and targets were consistent with known pharmacology and suggestive that side effects and drug-drug interactions might be revealed by modeling many targets. In the second analysis, we constructed and tested ligand-based models of 22 diverse targets in virtual screens using a background of screening molecules. Greater than 100-fold enrichment of cognate versus random molecules was observed in 20/22 cases. In the third analysis, selectivity of the models was tested using a background of drug molecules, with selectivity of greater than 80-fold observed in 17/22 cases. Predicted activities derived from crossing drugs against modeled targets identified a number of known side effects, drug specificities, and drug-drug interactions that have a rational basis in molecular structure.

Computer Simulation↗
PubMed2006

Structure-based drug design and structural biology study of novel nonpeptide inhibitors of severe acute respiratory syndrome coronavirus main protease.

Severe acute respiratory syndrome coronavirus (SARS-CoV) main protease (M(pro)), a protein required for the maturation of SARS-CoV, is vital for its life cycle, making it an attractive target for structure-based drug design of anti-SARS drugs. The structure-based virtual screening of a chemical database containing 58,855 compounds followed by the testing of potential compounds for SARS-CoV M(pro) inhibition leads to two hit compounds. The core structures of these two hits, defined by the docking study, are used for further analogue search. Twenty-one analogues derived from these two hits exhibited IC50 values below 50 microM, with the most potent one showing 0.3 microM. Furthermore, the complex structures of two potent inhibitors with SARS-CoV M(pro) were solved by X-ray crystallography. They bind to the protein in a distinct manner compared to all published SARS-CoV M(pro) complex structures. They inhibit SARS-CoV M(pro) activity via intensive H-bond network and hydrophobic interactions, without the formation of a covalent bond. Interestingly, the most potent inhibitor induces protein conformational changes, and the inhibition mechanisms, particularly the disruption of catalytic dyad (His41 and Cys145), are elaborated.

Binding Sites↗
PubMed2006

Quest for the rings. In silico exploration of ring universe to identify novel bioactive heteroaromatic scaffolds.

Bioactive molecules only contain a relatively limited number of unique ring types. To identify those ring properties and structural characteristics that are necessary for biological activity, a large virtual library of nearly 600 000 heteroaromatic scaffolds was created and characterized by calculated properties, including structural features, bioavailability descriptors, and quantum chemical parameters. A self-organizing neural network was used to cluster these scaffolds and to identify properties that best characterize bioactive ring systems. The analysis shows that bioactivity is very sparsely distributed within the scaffold property and structural space, forming only several relatively small, well-defined "bioactivity islands". Various possible applications of a large database of rings with calculated properties and bioactivity scores in the drug design and discovery process are discussed, including virtual screening, support for the design of combinatorial libraries, bioisosteric design, and scaffold hopping.

Biological Availability↗
PubMed2006

Docking and three-dimensional quantitative structure-activity relationship (3D QSAR) analyses of nonsteroidal progesterone receptor ligands.

We report a docking and comparative molecular similarity indices analysis (CoMSIA) study of progesterone receptor (PR) ligands with an emphasis on nonsteroids including tanaproget. The ligand alignment generation, a critical part of model building, comprised two stages. First, thorough conformational sampling of docking poses within the PR binding pocket was made with the program GOLD. Second, a strategy to select representative poses for CoMSIA was developed utilizing the FlexX scoring function. After manual replacement of five poses where this approach had problems, a significant correlation (r(2) = 0.878) between the experimental affinities and electrostatic, hydrophobic, and hydrogen bond donor properties of the aligned ligands was found. Extensive model validation was made using random-group cross-validations, external test set predictions (r(pred)(2) = 0.833), and consistency check between the CoMSIA model and the PR binding site structure. Robustness, predictive ability, and automated alignment generation make the model a potential tool for virtual screening.

Binding Sites↗
PubMed2006

Calcium channel antagonists discovered by a multidisciplinary approach.

A multidisciplinary project has led to the discovery of novel, structurally diverse, L-type calcium entry blockers (CEBs). The absolute configuration of a recently reported CEB has been determined by vibrational circular dichroism spectroscopy, to assign the stereospecificity of the ligand-channel interaction. Thereafter, a virtual screening procedure was performed with the aim of identifying novel chemotypes for CEBs, starting from a database of purchasable compounds; 340,000 molecules were screened in silico in order to prioritize structures of interest for bioscreening. As a result, 20 compounds were tested in vitro, and functional and binding assays revealed several hits with promising behavior as CEBs.

Animals↗
PubMed2006

N,N'-Bisbenzylidenebenzene-1,4-diamines and N,N'-Bisbenzylidenenaphthalene-1,4-diamines as Sirtuin Type 2 (SIRT2) Inhibitors.

A series of N,N'-bisbenzylidenebenzene-1,4-diamine and N,N'-bisbenzylidenenaphthalene-1,4-diamine derivatives were synthesized as inhibitors for human sirtuin type 2 (SIRT2). The design of the new compounds was based on two earlier reported hits from molecular modeling and virtual screening. The most potent compound was N,N'-bis(2-hydroxybenzylidene)benzene-1,4-diamine, which was equipotent with the most potent hit compound and well-known SIRT2 inhibitor sirtinol.

Acetylation↗
PubMed2006

Discovering inhibitors of human sirtuin type 2: novel structural scaffolds.

A successful virtual screening experiment of novel SIRT2 inhibitors is described. Four out of 11 experimentally tested compounds showed in vitro inhibitory activity toward SIRT2 in a micromolar level, resulting in an experimental hit ratio of 36%. Two of these compounds inhibited SIRT2 with IC50 (microM) values of 51 and 91; moreover, one of the new inhibitors was comprised of an entirely new SIRT2-inhibiting structural scaffold.

Benzhydryl Compounds↗
PubMed2006

Contribution of conformer focusing to the uncertainty in predicting free energies for protein-ligand binding.

When a ligand binds to a protein, it is typically not in the lowest-energy conformation for the unbound ligand and there is also a loss of conformational degrees of freedom. The free-energy change for this "conformer focusing" is addressed here formally, and the associated errors with its estimation or neglect are considered in the context of scoring functions for protein-ligand docking and computation of absolute free energies of binding. Specific applications for inhibition of HIV-1 reverse transcriptase are reported. It is concluded that the uncertainties from this source alone are sufficient to preclude the viability of current docking methodology for rank-ordering of diverse compounds in high-throughput virtual screening.

Binding Sites↗
PubMedDate not supplied

Computational models for identifying potential P-glycoprotein substrates and inhibitors.

Multidrug resistance mediated by ATP binding cassette (ABC) transporters such as P-glycoprotein (P-gp) represents a serious problem for the development of effective anticancer drugs. In addition, P-gp has been shown to reduce oral absorption, modulate hepatic, renal, or intestinal elimination, and restrict blood-brain barrier penetration of several drugs. Consequently, there is a great interest in anticipating whether drug candidates are P-gp substrates or inhibitors. In this respect, two different computational models have been developed. A method for discriminating P-gp substrates and nonsubstrates has been set up based on calculated molecular descriptors and multivariate analysis using a training set of 53 diverse drugs. These compounds were previously classified as P-gp substrates or nonsubstrates on the basis of the efflux ratio from Caco-2 permeability measurements. The program Volsurf was used to compute the compounds' molecular descriptors. The descriptors were correlated to the experimental classes using partial least squares discriminant analysis (PLSD). The model was able to predict correctly the behavior of 72% of an external set of 272 proprietary compounds. Thirty of the 53 previously mentioned drugs were also evaluated for P-gp inhibition using a calcein-AM (CAM) assay. On the basis of these additional P-gp functional data, a PLSD analysis using GRIND-pharmacophore-based descriptors was performed to model P-gp substrates having poor or no inhibitory activity versus inhibitors having no evidence of significant transport. The model was able to discriminate between 69 substrates and 56 inhibitors taken from the literature with an average accuracy of 82%. The model allowed also the identification of some key molecular features that differentiate a substrate from an inhibitor, which should be taken into consideration in the design of new candidate drugs. These two models can be implemented in a virtual screening funnel.

ATP Binding Cassette Transporter, Subfamily B, Mem↗
PubMed2000

Fast prediction and visualization of protein binding pockets with PASS.

PASS (Putative Active Sites with Spheres) is a simple computational tool that uses geometry to characterize regions of buried volume in proteins and to identify positions likely to represent binding sites based upon the size, shape, and burial extent of these volumes. Its utility as a predictive tool for binding site identification is tested by predicting known binding sites of proteins in the PDB using both complexed macromolecules and their corresponding apoprotein structures. The results indicate that PASS can serve as a front-end to fast docking. The main utility of PASS lies in the fact that it can analyze a moderate-size protein (approximately 30 kDa) in under 20 s, which makes it suitable for interactive molecular modeling, protein database analysis, and aggressive virtual screening efforts. As a modeling tool, PASS (i) rapidly identifies favorable regions of the protein surface, (ii) simplifies visualization of residues modulating binding in these regions, and (iii) provides a means of directly visualizing buried volume, which is often inferred indirectly from curvature in a surface representation. PASS produces output in the form of standard PDB files, which are suitable for any modeling package, and provides script files to simplify visualization in Cerius2, InsightII, MOE, Quanta, RasMol, and Sybyl. PASS is freely available to all.

Algorithms↗
PubMed1999

Prediction of the intestinal absorption of endothelin receptor antagonists using three theoretical methods of increasing complexity.

PURPOSE: Three new computational strategies have been evaluated for their ability to predict intestinal membrane permeability to a series of endothelin receptor antagonists. METHODS: The three methods were evaluated using a set of ten nonpeptide endothelin receptor antagonists. The simplest method, "the rule of five", is based on 2D parameters such as the number of potential hydrogen bonds, molecular weight and calculated lipophilicity. A method based on molecular mechanics calculations is used to calculate 3D parameters such as polar and non-polar parts of the molecular surface area. The third method uses quantum mechanics to calculate molecular properties related to the valence region. RESULTS: Descriptors derived by the latter two methods correlated well with permeability coefficients of the endothelin receptor antagonists. On the other hand, the rule of five failed to discriminate between drugs with high and low permeability. CONCLUSIONS: Molecular surface descriptors and descriptors derived from quantum mechanics are potentially useful for the virtual screening of the permeability of the intestinal membrane to endothelin receptor antagonists.

Animals↗
PubMed2002

Q-fit: a probabilistic method for docking molecular fragments by sampling low energy conformational space.

A new method is presented that docks molecular fragments to a rigid protein receptor. It uses a probabilistic procedure based on statistical thermodynamic principles to place ligand atom triplets at the lowest energy sites. The probabilistic method ranks receptor binding modes so that the lowest energy ones are sampled first. This allows constraints to be introduced to limit the depth of the search leading to a computationally efficient method of sampling low energy conformational space. This is combined with energy minimization of the initial fragment placement to arrive at a low energy conformation for the molecular fragment. Two different search methods are tested involving (i) geometric hashing and (ii) pose clustering methods. Ten molecular fragments were docked that have commonly been used to test docking methods. The success rate was 8/10 and 10/10 for generating a close solution ranked first using the two different sampling procedures. In general, all five of the top ranked solutions reproduce the observed binding mode, which increases confidence in the predictions. A set of ten molecular fragments that have previously been identified as problematic were docked. Success was achieved in 3/10 and 4/10 using the two different methods. Again there is a high level of agreement between the two methods and again in the successful cases the top ranked solutions are correct whilst in the case of the failures none are. The geometric hashing and pose clustering methods are fast averaging approximately 13 and approximately 11 s per placement respectively using conservative parameters. The results are very encouraging and will facilitate the process of finding novel small molecule lead compounds by virtual screening of chemical databases.

Algorithms↗
PubMed2002

A review of protein-small molecule docking methods.

The binding of small molecule ligands to large protein targets is central to numerous biological processes. The accurate prediction of the binding modes between the ligand and protein, (the docking problem) is of fundamental importance in modern structure-based drug design. An overview of current docking techniques is presented with a description of applications including single docking experiments and the virtual screening of databases.

Algorithms↗