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PubMedDate not supplied

Analysis of data fusion methods in virtual screening: similarity and group fusion.

In a recent companion paper we have related the operation of simple data fusion rules used in virtual screening to a multiple integral formalism. In this paper we extend these ideas to the analysis of data fusion methods applied to real data. We examine several cases of similarity fusion using different coefficients and different representations and consider the reasons for positive or negative results in terms of the similarity distributions. Results are obtained using the SUM-, MAX- MIN-, and CombMNZ-fusion rules. We also develop a customized fusion rule, which provides an estimate of the optimal possible result for fusing multiple searches of a specific database; this shows that similarity fusion can, in principle, achieve retrieval enhancements even if this is not achieved in practice with current fusion rules. The methods are extended to analyze the comparatively successful results of group fusion with multiple actives, and we provide a rationale for the observed superiority of the MAX-rule over the SUM-rule in this context.

Combinatorial Chemistry Techniques↗
PubMedDate not supplied

Design and evaluation of a novel class-directed 2D fingerprint to search for structurally diverse active compounds.

Recent attempts to increase similarity search performance using molecular fingerprints have mostly focused on the evaluation of alternative similarity metrics or scoring schemes, rather than the development of new types of fingerprints. Here, we introduce a novel 2D fingerprint design (property descriptor value range-derived fingerprint or PDR-FP) that involves activity-oriented selection of property descriptors and the transformation of descriptor value ranges into a binary format such that each fingerprint bit position represents a specific value interval. The design is tailored toward multiple-template similarity searching and permits training on specific activity classes. In search calculations on 15 compound classes of increasing structural diversity, the PDR fingerprint performed better than other state-of-the-art 2D fingerprints. Among the structurally diverse classes were six compound sets with peptide character, which represent a notoriously difficult chemotype for 2D similarity searching. In these cases, PDR-FP produced promising results, whereas other fingerprint methods mostly failed. PDR-FP is specifically designed for search calculations on structurally diverse compounds, and these calculations are not influenced by molecular size effects, which represent a general problem for similarity searching using bit string representations.

Algorithms↗
PubMedDate not supplied

Distributions of distances in information strings.

Distances between identical symbols in information strings (biological, language, computer programs (*.exe files) are described with a different precision with four distributions: exponential, Weibull, log-normal and negative binomial. The correlations are sometimes highly significant.

Amino Acid Sequence↗
PubMed2003

Integrated computational and experimental approach for lead optimization and design of compstatin variants with improved activity.

A novel structure-activity-based combinatorial computational optimization methodology for the design of peptides that are candidates to become therapeutics is presented. This methodology has been successfully applied in the design of a 7-fold more active analogue, among other active analogues, in the case of the complement inhibitor compstatin. The main steps of the approach involve the availability of NMR-derived structural templates, combinatorial selection of sequences based on optimization of parametrized pairwise residue interaction potentials, prediction of fold stabilities using deterministic global optimization, and experimental validation with immunological activity measurements. This work is direct evidence that an integrated experimental and theoretical approach can make the engineering of compounds with enhanced immunological properties possible.

Amino Acid Sequence↗
PubMed2002

Suitability of molecular descriptors for database mining. A comparative analysis.

Database mining methods rely on the molecular descriptors used to characterize a structural database. In the present investigation, five different types of descriptors (log P, UNITY fingerprints, ISIS keys, VolSurf, and GRIND) are applied to characterize various databases (n = 1007, 100, and 229) comprising drugs almost exclusively. The validity of the descriptors is comparatively analyzed via principal component analysis and its hierarchical variant, consensus principal component analysis. Both pharmacodynamic and pharmacokinetic aspects of database mining are treated. For pharmacodynamic aspects, clustering behavior achieved with the different descriptors is tested on the chemically homogeneous beta-blockers, benzodiazepines, and penicillins and on the chemically more diverse class I antiarrhythmics. The following ranking is observed: UNITY fingerprints > ISIS keys and GRIND > VolSurf > log P. Regarding information content, the CPCA superweight plot indicates similarity between fingerprints and ISIS keys as well as between VolSurf and log P, while GRIND differs from all the remaining descriptors. Solubility data and blood/brain barrier penetrating behavior serve as test cases for pharmacokinetic aspects. Comparison of the descriptors applied to these data reveals that VolSurf has the most realistic and consistent behavior, GRIND shows intermediate behavior, while UNITY fingerprints and ISIS keys are not well suited for pharmacokinetic profiling. From this comparative analysis, we conclude that VolSurf descriptors exhibit particular advantages in treating pharmacokinetic aspects; UNITY fingerprints, ISIS keys, and GRIND descriptors are of special value for tackling pharmacodynamic aspects of database mining. The parameter log P is of limited applicability in database mining because of rather poor reliability and lack of completeness of data.

Computing Methodologies↗
PubMed2002

Quantitative structure-activity relationship analysis of functionalized amino acid anticonvulsant agents using k nearest neighbor and simulated annealing PLS methods.

We report the development of rigorously validated quantitative structure-activity relationship (QSAR) models for 48 chemically diverse functionalized amino acids with anticonvulsant activity. Two variable selection approaches, simulated annealing partial least squares (SA-PLS) and k nearest neighbor (kNN), were employed. Both methods utilize multiple descriptors such as molecular connectivity indices or atom pair descriptors, which are derived from two-dimensional molecular topology. QSAR models with high internal accuracy were generated, with leave-one-out cross-validated R(2) (q(2)) values ranging between 0.6 and 0.8. The q(2) values for the actual dataset were significantly higher than those obtained for the same dataset with randomly shuffled activity values, indicating that models were statistically significant. The original dataset was further divided into several training and test sets, with highly predictive models providing q(2) values greater than 0.5 for the training sets and R(2) values greater than 0.6 for the test sets. These models were capable of predicting with reasonable accuracy the activity of 13 novel compounds not included in the original dataset. The successful development of highly predictive QSAR models affords further design and discovery of novel anticonvulsant agents.

Amino Acids↗
PubMed2002

SMall Molecule Growth 2001 (SMoG2001): an improved knowledge-based scoring function for protein-ligand interactions.

Computational lead design procedures require fast and accurate scoring functions to rank millions of generated virtual ligands for protein targets. In this article, we present an improved version of the SMoG scoring function, called SMoG2001. This function is based on a knowledge-based approach-that is, the free energy parameters are derived from the observed frequencies of atom-atom contacts in the database of three-dimensional structures of protein-ligand complexes via a procedure based on statistical mechanics. We obtained the statistics from the set of 725 complexes. SMoG2001 reproduces the experimental binding constants of the majority of 119 complexes of the testing set with good accuracy. On similar testing sets, SMoG2001 performs better than two other widely used scoring functions, PMF and SCORE1(LUDI), and comparably to DrugScore. SMoG2001 poorly predicts the affinities of ligands interacting via quantum mechanical forces with metal ions and ligands that are large and flexible. We attribute significant improvement in accuracy over previous versions of the SMoG scoring function to a better description of the reference state-that is, the state of no interactions.

Carbonic Anhydrases↗
PubMed2003

A computational model of binding thermodynamics: the design of cyclin-dependent kinase 2 inhibitors.

The cyclin-dependent protein kinases are important targets in drug discovery because of their role in cell cycle regulation. In this computational study, we have applied a continuum solvent model to study the interactions between cyclin-dependent kinase 2 (CDK2) and analogues of the clinically tested anticancer agent flavopiridol. The continuum solvent model uses Coulomb's law to account for direct electrostatic interactions, solves the Poisson equation to obtain the electrostatic contributions to solvation energy, and calculates scaled solvent-accessible surface area to account for hydrophobic interactions. The computed free energy of binding gauges the strength of protein-ligand interactions. Our model was first validated through a study on the binding of a number of flavopiridol derivatives to CDK2, and its ability to identify potent inhibitors was observed. The model was then used to aid in the design of novel CDK2 inhibitors with the aid of a computational sensitivity analysis. Some of these hypothetical structures could be significantly more potent than the lead compound flavopiridol. We applied two approaches to gain insights into designing selective inhibitors. One relied on the comparative analysis of the binding pocket for several hundred protein kinases to identify the parts of a lead compound whose modifications might lead to selective compounds. The other was based on building and using homology models for energy calculations. The homology models appear to be able to classify ligand potency into groups but cannot yet give reliable quantitative results.

Binding Sites↗
PubMed2003

Systematic surface scan of the most favorable interaction sites of magnesium ions with tetracycline.

AM1 semiempirical molecular orbital calculations have been used to probe the complexation sites for naked and hydrated magnesium ions to the different conformations and protonation states of tetracycline. The calculations reveal a wealth of possible magnesium complexation sites within a small energy range, but also indicate that magnesium complexation does not change the conformational behavior of tetracycline significantly. A hitherto unknown solvated conformation is suggested for deprotonated tetracycline.

Cations, Divalent↗
PubMed2004

Synthesis, biological evaluation, and molecular modeling studies of a novel, peripherally selective inhibitor of catechol-O-methyltransferase.

A novel series of potent, peripherally selective, and long-acting inhibitors of catechol-O-methyltransferase (COMT) has been synthesized. The introduction and nature of heteroatom-containing substituents to the side-chain of the nitrocatechol pharmacophore was found to have a profound effect on both peripheral selectivity and duration of COMT inhibition in the mouse. This approach led to the discovery of 1-(3,4-dihydroxy-5-nitrophenyl)-3-[4-[3-(trifluoromethyl)phenyl]-1-piperazinyl]-1-propanone hydrochloride 35 (BIA 3-335), which was found to possess a superior inhibitory profile in vivo over both the nonselective inhibitor tolcapone 1 and the peripherally selective but short-acting entacapone 2. In this model, 35 retained 75% inhibition of peripheral COMT at 6 h after oral administration, yet significantly, only a minor reduction of central (cerebral) COMT activity was observed. Molecular modeling techniques were applied to review the analysis of the ternary enzyme-inhibitor complex previously determined by X-ray crystallography and to provide a deeper understanding of the structure-activity relationships within this novel series. Furthermore, a computational approach was applied in an effort to elucidate the particular structural factors relevant to the poor blood-brain permeability of 35. In conclusion, the improved biological properties herein reported reveal 35 as a candidate for clinical studies as an adjunct to L-DOPA therapy for Parkinson's disease.

Animals↗
PubMed2004

Ph4Dock: pharmacophore-based protein-ligand docking.

The development and validation of the program Ph4Dock is presented. Ph4Dock is a novel automated ligand docking program that makes best use of pharmacophoric features both in a ligand and at concave portions of a protein. By mapping of pharmacophores of the ligand to the pharmacophoric features that represent the concaves of the target protein, Ph4Dock realizes an efficient and accurate prediction of the binding modes between the ligand and the protein. To validate the potential of this unique docking algorithm, we have selected 43 reliable crystal structures of protein-ligand complexes. All of the ligands are druglike, and they are varied in nature. The diffraction-component precision index (DPI) originally used in crystallography was applied in this study in order to evaluate the docking results quantitatively. The root-mean-square deviation (rmsd) between non-hydrogen atoms of the ligand in the prediction and experimental results were analyzed using DPI. The rmsd values for 25 structures, consisting of almost 60% of the dataset, are less than three times of the corresponding DPI values. It means that the precision of docking results obtained by Ph4Dock is mostly equivalent to the experimental error in these cases. The present study has demonstrated that Ph4Dock can accurately reproduce the experimentally determined docking modes if the reliable crystal structures are used. Normally the success rate of the docking is judged using rmsd < or = 2.0 A as the criterion. The Ph4Dock marked an appreciably good success rate of 86% based on this criterion.

Binding Sites↗
PubMed2004

"Lead hopping". Validation of topomer similarity as a superior predictor of similar biological activities.

Two extensive studies quantifying the ability of topomer shape similarity to forecast a variety of biological similarities are described. In a prospective trial of "lead hopping", using topomer similarity for virtual screening and queries from the patent literature, biological assays of 308 selected compounds (representing 0.03% of those available, per assay type) yielded 11 successful "lead hops" in the 13 assays attempted. The hit rate averaged over all assays was 39% ("activity"defined as inhibition > or =20% at 10 microM), significantly greater than an unexpectedly high negative control hit rate of 15%. The average "Tanimoto 2D fingerprint similarity" between query and "lead hop" structures (0.36) was little more than the Tanimoto similarity between random drug-like structures. Topomer shape and Tanimoto 2D fingerprint similarities were also compared retrospectively, in their tendencies to concentrate together potential and actual drugs reported to belong to the same "activity class", for twenty classes. Among the most similar 3% of structures (corresponding to "> or =0.85 Tanimoto" for these structures), an average of 62% of the topomer similar selection possessed a near neighbor belonging to the same activity class, roughly a one-third superiority over the "Tanimoto > or = 0.85" selection containing 48% actives in avoiding false positives. Conversely, the least similar 75% of structures contained 0.3% actives for topomer similarity vs 1.0% actives for Tanimoto 2D fingerprint similarity, a 3-fold superiority for topomers in avoiding false negatives.

Computing Methodologies↗
PubMed2005

Enhancing the effectiveness of similarity-based virtual screening using nearest-neighbor information.

We test the hypothesis that fusing the outputs of similarity searches based on a single bioactive reference structure and on its nearest neighbors (of unknown activity) is more effective (in terms of numbers of high-ranked active structures) than a similarity search involving just the reference structure. This turbo similarity searching approach provides a simple way to enhance the effectiveness of simulated virtual screening searches of the MDL Drug Data Report database.

Computing Methodologies↗
PubMed2006

Theoretical and experimental investigation of morphology and temperature effects on adsorption of organic vapors in single-walled carbon nanotubes.

Hexane adsorption on single-walled carbon nanotube (SWNT) bundles is studied by both simulation and experimentally using a previously developed computer-aided methodology, which employed a smaller physisorbed probe molecule, nitrogen, to explore the porosity of nanotube samples. Configurational-bias grand canonical Monte Carlo simulation of hexane adsorption on localized sites of the bundles is carried out to predict adsorption on their external surface and in their internal sites. These localized isotherms are then combined into a global isotherm for a given sample by using knowledge of its tube-diameter distribution and structural parameters, such as the fraction of open-ended nanotubes and the external surface area of bundles in samples, which have been independently determined from the standard nitrogen adsorption isotherm. The near-perfect replication of experimental isotherms demonstrates the validity of our method for structural characterization of SWNT samples. The effect of temperature on adsorption is also studied and the simulation results are extrapolated to predict the limiting hexane adsorption capacity of the samples. The similarity between the hexane adsorption isotherms and those of other organic molecules demonstrates that the adsorption mechanisms explored here are not specific to hexane, and that the proposed methodology can be potentially applicable to other sorbates with equal success.

Journal Article↗
PubMed2006

Hydride affinities of some substituted alkynes: prediction by DFT calculations and rationalization by triadic formula.

Hydride affinities (HAs) of the ethynes substituted by a wide range of different substituents are considered by using the B3LYP methodology. The computed values are in fair agreement with available experimental data, which are unfortunately scarce. The trend of changes of the HAs is rationalized by trichotomy formula. One of the important results of this analysis is a finding that similar HA values might result from completely different effects. Alternative sites of the H- attack are examined and the difference in energies relative to the most susceptible positions is interpreted. Structural features of substituted ethyne hydrides are briefly discussed.

Journal Article↗
PubMed2006

Medium scale integration of molecular logic gates in an automaton.

The assembly of molecular automata that perform increasingly complex tasks, such as game playing, presents an unbiased test of molecular computation. We now report a second-generation deoxyribozyme-based automaton, MAYA-II, which plays a complete game of tic-tac-toe according to a perfect strategy. In silicon terminology, MAYA-II represents the first "medium-scale integrated molecular circuit", integrating 128 deoxyribozyme-based logic gates, 32 input DNA molecules, and 8 two-channel fluorescent outputs across 8 wells.

Algorithms↗
PubMed2001

Data-based modeling of the failure rate of repairable equipment.

A database of failures of many types of medical equipment was analysed, to study the dependence of failure rate on equipment age and on time since repair. The intention was to use this large dataset to assess the validity of some widely-used models of failure rate, such as the power-law and loglinear Poisson processes, and so to recommend simple and adequate models to those practitioners having little data to discriminate between rival models. The aim is also to illustrate a methodology for computing policy costs from failure databases. The power-law process model was found to fit slightly better overall than did the loglinear and linear processes. Some related models were created to fit an observed peaking of failure rate. The data showed a decreasing hazard of (first) failure after repair for some equipment types. This can be due to imperfect or hazardous repair, and also to differing failure rates among a population of machines. Two simple models of imperfect repair were used to fit the data, and an Empirical Bayes method was used to fit a model of variable failure rate between machines. Neglect of such variation can lead to an over-estimate of the hazardousness of repair.

Bayes Theorem↗
PubMed1997

Educational implications of analogy. A view from case-based reasoning.

Case-based reasoning (CBR) focuses on analogy in the context of solving real-world problems. Its research methodology of computational modeling is aimed at deriving hypotheses about cognition. CBR's computational models show the roles of encoding, retrieval, and adaptation in analogical reasoning processes. In addition, its algorithms provide insight into what it might take to enhance human cognition. CBR as a plausible cognitive model can thus advise on educational philosophy, educational practice, and design of educational software.

Association Learning↗