Choosing an enzyme reactor theoretical background and considerations as illustrated in a case study

A short review of different types of enzyme reactors and factors of influence on the reactor choice is given. The background of their kinetic differences is discussed. The conversion of starch to maltose by use of an immobilized two-enzyme system has been chosen as a case study.     

Active learning with support vector machines in the drug discovery process

We investigate the following data mining problem from computer-aided drug design: From a large collection of compounds, find those that bind to a target molecule in as few iterations of biochemical testing as possible. In each iteration a comparatively small batch of compounds is screened for binding activity toward this target. We employed the so-called "active learning paradigm" from Machine Learning for selecting the successive batches. Our main selection strategy is based on the maximum margin hyperplane-generated by "Support Vector Machines". This hyperplane separates the current set of active from the inactive compounds and has the largest possible distance from any labeled compound. We perform a thorough comparative study of various other selection strategies on data sets provided by DuPont Pharmaceuticals and show that the strategies based on the maximum margin hyperplane clearly outperform the simpler ones.     

Natural product hybrids as new leads for drug discovery

Natural products play an important role in the development of drugs, especially for the treatment of infections and cancer, as well as immunosuppressive compounds. However, the number of natural products is limited, whereas millions of hybrids as combinations of parts of different natural products can be prepared. This new approach seems to be very promising in the development of leads for both medicinal and agrochemical applications, as the biological activity of several new hybrids exceeds that of the parent compounds. The advantage of this concept over a combinatorial chemistry approach is the high diversity and the inherent biological activity of the hybrids.     

Amperometric detection of acetylcholine and choline in a liquid chromatographic system with an immobilized enzyme reactor

Acetylcholinesterase and choline oxidase were co-immobilized by reaction with glutaraldehyde onto alkylamino-bonded silica, which was incorporated as the enzyme reactor in an h.p.l.c. system for the determination of acetylcholine and choline. The hydrogen peroxide produced enzymatically in the enzyme reactor, after the separation of acetylcholine and choline by the reverse-phase column, was monitored amperometrically. The detection limits were 1.2 pmol for choline and 1.8 pmol for acetylcholine.     

Integrated project views: decision support platform for drug discovery project teams

Drug discovery teams continuously have to decide which compounds to progress and which experiments to perform next, but the data required to make informed decisions is often scattered, inaccessible, or inconsistent. In particular, data tend to be stored and represented in a compound-centric or assay-centric manner rather than project-centric as often needed for effective use in drug discovery teams. The Integrated Project Views (IPV) system has been created to fill this gap; it integrates and consolidates data from various sources in a project-oriented manner. Its automatic gathering and updating of project data not only ensures that the information is comprehensive and available on a timely basis, but also improves the data consistency. Due to the lack of suitable off-the-shelf solutions, we were prompted to develop custom functionality and algorithms geared specifically to our drug discovery decision making process. In 10 years of usage, the resulting IPV application has become very well-accepted and appreciated, which is perhaps best evidenced by the observation that standalone Excel spreadsheets are largely eliminated from project team meetings.     

In silico fragment-mapping method: a new tool for fragment-based/structure-based drug discovery

Here, we propose an in silico fragment-mapping method as a potential tool for fragment-based/structure-based drug discovery (FBDD/SBDD). For this method, we created a database named Canonical Subsite–Fragment DataBase (CSFDB) and developed a knowledge-based fragment-mapping program, Fsubsite. CSFDB consists of various pairs of subsite–fragments derived from X-ray crystal structures of known protein–ligand complexes. Using three-dimensional similarity-matching between subsites on one protein and another, Fsubsite compares the surface of a target protein with all subsites in CSFDB. When a local topography similar to the subsite is found on the surface, Fsubsite places a fragment combined with the subsite in CSFDB on the target protein. For validation purposes, we applied the method to the apo-structure of cyclin-dependent kinase 2 (CDK2) and identified four compounds containing three mapped fragments that existed in the list of known inhibitors of CDK2. Next, the utility of our fragment-mapping method for fragment-growing was examined on the complex structure of tRNA-guanine transglycosylase with a small ligand. Fsubsite mapped appropriate fragments on the same position as the binding ligand or in the vicinity of the ligand. Finally, a 3D-pharmacophore model was constructed from the fragments mapped on the apo-structure of heat shock protein 90-α (HSP90α). Then, 3D pharmacophore-based virtual screening was carried out using a commercially available compound database. The resultant hit compounds were very similar to a known ligand of HSP90α. As a result of these findings, this in silico fragment-mapping method seems to be a useful tool for computational FBDD and SBDD.     

Choosing an equivalent replacement column for a reversed-phase liquid chromatographic assay procedure

The column selectivity parameters (H, S*, A, B and C) described in the preceding paper [L.R. Snyder, A. Maule, A. Heebsch, R. Cuellar, S. Paulson, J. Carrano, L. Wrisley C.C. Chan, N. Pearson, J.W. Dolan, J.J. Gilroy, J. Chromatogr. A 1057 (2004) 49-57] can be used to compare columns in terms of selectivity. A detailed procedure for such column comparisons is presented here, and evaluated by its use in finding suitable replacement columns for 12 different routine separations performed in five different pharmaceutical analysis laboratories.     

Advantages of atmospheric pressure photoionization mass spectrometry in support of drug discovery

The performance of the atmospheric pressure photoionization (APPI) technique was evaluated against five sets of standards and drug-like compounds and compared to atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI). The APPI technique was first used to analyze a set of 86 drug standards with diverse structures and polarities with a 100% detection rate. More detailed studies were then performed for another three sets of both drug standards and proprietary drug candidates. All 60 test compounds in these three sets were detected by APPI with an overall higher ionization efficiency than either APCI or ESI. Most of the non-polar compounds in these three sets were not ionized by APCI or ESI. Analysis of a final set of 201 Wyeth proprietary drug candidates by APPI, APCI and ESI provided an additional comparison of the ionization techniques. The detection rates in positive ion mode were 94% for APPI, 84% for APCI, and 84% for ESI. Combining positive and negative ion mode detection, APPI detected 98% of the compounds, while APCI and ESI detected 91%, respectively. This analysis shows that APPI is a valuable tool for day-to-day usage in a pharmaceutical company setting because it is able to successfully ionize more compounds, with greater structural diversity, than the other two ionization techniques. Consequently, APPI could be considered a more universal ionization method, and therefore has great potential in high-throughput drug discovery especially for open access liquid chromatography/mass spectrometry (LC/MS) applications.     

Systems biology and systems chemistry: new directions for drug discovery

Improvements in drug design have historically been centered around structure-based optimization of molecule specificity for a targeted protein, in an effort to reduce unintentional binding to other proteins and off-target effects. Although the "one-to-one" drug design strategy has been successful in impairing function of targets associated with a number of diseases, recent reports of drug promiscuity, which are a potential source of adverse reactions in patients, make a case to refine the drug design strategy such that it includes an awareness of multiple interactions from both ligand and protein perspectives. Polypharmacology and chemical biology studies are amassing interaction data at rapid rates, and the integration of such data into an interpretable model requires zooming our perspective out from the single ligand-target level to the larger network-wide level. We review some of the recent developments in systems-level research for drug design and discovery, and discuss the directions that some drug design efforts are heading toward.     

Thin-layer and gas chromatographic screening programs for new drug substances.

Procedures are described for evaluation of the thin-layer and gas chromatographic properties of new raw material drug substances over a broad spectrum of conditions. Chromatographic profiles are established for each drug, and these are used as starting points for analytical procedures for the drug, its synthetic precursors, and its degradation products. Thin-layer chromatography is performed initially by use of three absorbents and a series of six solvents. Gas chromatography is performed initially by temperature programming on a series of six different columns, followed by isothermal experiments. Evaluation of resulting chromatograms from both techniques determines whether more experiments are necessary or whether an analytical method can be developed based directly on one of the results of the initial screening.     

A new enzyme immunoassay for a solid Chinese crude drug, pinellia tuber

A new immunoassay for a solid Chinese crude drug was studied. An antiserum specific for Pinellia tuber was elicited in two rabbits. Using the antiserum and powdered Pinellia tuber-coated microtiter plate as the immunological reagents, and beta-D-galactosidase-labeled goat anti-rabbit immunoglobulin G (IgG) as the tracer, a new enzyme immunoassay for a solid Pinellia tuber with a working range between 0.1 and 1000 micrograms/ml was developed. The assay was specific for a solid Pinellia tuber and showed low cross-reaction values on other Chinese crude drugs and the extract of Pinellia tuber. The specificity of the assay was compared with the selected antibody enzyme immunoassay (SAEIA) for the extract of Pinellia tuber recently developed. Both methods utilized the same immunological reagents such as the serum and the enzyme-labeled goat anti-rabbit IgG, and the only difference between them was the solid-phase antigen used. The assay results of several antigens determined by them were quite different, showing that selective measurements of different antigens, either solid or the extract of Pinellia tuber, were possible using the same antiserum, when the tracing reaction in the immunoassay was adequately selected.     

Towards a new age of virtual ADME/TOX and multidimensional drug discovery

With the continual pressure to ensure follow-up molecules to billion dollar blockbuster drugs, there is a hurdle in profitability and growth for pharmaceutical companies in the next decades. With each success and failure we increasingly appreciate that a key to the success of synthesized molecules through the research and development process is the possession of drug-like properties. These properties include an adequate bioactivity as well as adequate solubility, an ability to cross critical membranes (intestinal and sometimes blood-brain barrier), reasonable metabolic stability and of course safety in humans. Dependent on the therapeutic area being investigated it might also be desirable to avoid certain enzymes or transporters to circumvent potential drug-drug interactions. It may also be important to limit the induction of these same proteins that can result in further toxicities. We have clearly moved the assessment of in vitro absorption, distribution, metabolism, excretion and toxicity (ADME/TOX) parameters much earlier in the discovery organization than a decade ago with the inclusion of higher throughput systems. We are also now faced with huge amounts of ADME/TOX data for each molecule that need interpretation and also provide a valuable resource for generating predictive computational models for future drug discovery. The present review aims to show what tools exist today for visualizing and modeling ADME/TOX data, what tools need to be developed, and how both the present and future tools are valuable for virtual filtering using ADME/TOX and bioactivity properties in parallel as a viable addition to present practices.     

Greatly reduced amino acid alphabets in directed evolution: making the right choice for saturation mutagenesis at homologous enzyme positions

Enantioselective mutants of the thermally robust phenyl acetone monooxygenase (PAMO) as catalysts in Baeyer-Villiger reactions have been evolved by utilizing saturation mutagenesis in which drastically reduced amino acid alphabets are employed at homologous enzyme positions.     

Periodic operation of a tubular reactor: A simulation study of consecutive reactions in a chromatographic reactor

The performance of a chromatographic reactor is studied by means of computer simulations for consecutive reactions represented byA + B → RR + B → SFor square-wave pulsing it is demonstrated that a chromatographic reactor can give a higher yield than a plug-flow reactor operated at steady state if