Development of a protease production platform for structure-based drug design

Structure-based drug design (SBDD) has played an integral role in the development of highly specific, potent protease inhibitors resulting in a number of drugs in clinical trials and on the market. Possessing biochemical assays and structural information on both the target protease and homologous family members helps ensure compound selectivity. We have redesigned the path from clone to protein eliminating many of the traditional bottlenecks associated with protein production to ensure a constant supply to feed many diverse protease drug discovery programs. The process was initiated with the design of a multi-system vector, capable of expression in both eukaryotic and prokaryotic hosts; this vector also facilitated high-throughput cloning, expression and purification. When combined into an expression screen, supplemented with salvage screens for detergent extraction and refolding, a route for protein production was established rapidly. Using this process-orientated approach we have successfully expressed and purified all mechanistic classes of active human and viral proteases for enzymatic assays and crystallization studies. While exploiting recent developments in high-throughput biochemistry, we still employ classical biophysical techniques such as light-scattering and analytical ultracentrifugation, to ensure the highest quality protein enters crystallization trials. We have drawn on examples from our own research programs to illustrate how these strategies have been successfully used in the production of proteases for SBDD.     

Fragment-based quantitative structure-activity relationship (FB-QSAR) for fragment-based drug design

In cooperation with the fragment-based design a new drug design method, the so-called "fragment-based quantitative structure-activity relationship" (FB-QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two-dimensional quantitative structure-activity relationship (2D-QSAR) is a special case, in the FB-QSAR, when the whole molecule is treated as one entity. The FB-QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB-QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus.     

GREEN: A program package for docking studies in rational drug design

Summary A program package, GREEN, has been developed that enables docking studies between ligand molecules and a protein molecule. Based on the structure of the protein molecule, the physical and chemical environment of the ligand-binding site is expressed as three-dimensional grid-point data. The grid-point data are used for the real-time evaluation of the protein-ligand interaction energy, as well as for the graphical representation of the binding-site environment. The interactive docking operation is facilitated by various built-in functions, such as energy minimization, energy contribution analysis and logging of the manipulation trajectory. Interactive modeling functions are incorporated for designing new ligand molecules while considering the binding-site environment and the protein-ligand interaction. As an example of the application of GREEN, a docking study is presented on the complex between trypsin and a synthetic trypsin inhibitor. The program package will be useful for rational drug design, based on the 3D structure of the target protein.     

XYZ,a program for modeling,validation, prediction and graphic display of data

A program for modeling, validation, prediction and graphic display of data is reported. The package is useful for dealing with responses that area function of a reduced number of variables. Implementation of user-defined models is easy and several very general equations can be selected. The structure of the program is shown and the use of the different modules is explained. Two typical, applications based on distinct mathematical models are shown.     

Development of KiBank, a database supporting structure-based drug design

KiBank is a database of inhibition constant (K_i) values with 3D structures of target proteins and chemicals. K_i values were accumulated from peer-reviewed literature searched via PubMed. The 3D structure files of target proteins were originally from Protein Data Bank (PDB), while the 2D structure files of the chemicals were collected together with the K_i values and then converted into 3D ones. In KiBank, the chemical and protein 3D structures with hydrogen atoms were optimized by energy minimization and stored in MDL MOL and PDB format, respectively.

KiBank is designed to support structure-based drug design. It provides structure files of proteins and chemicals ready for use in virtual screening through automated docking methods, while the K_i values can be applied for tests of docking/scoring combinations, program parameter settings, and calibration of empirical scoring functions. Additionally, the chemical structures and corresponding K_i values in KiBank are useful for lead optimization based on quantitative structure–activity relationship (QSAR) techniques.

KiBank is updated on a daily basis and is freely available at http://kibank.iis.u-tokyo.ac.jp/. As of August 2004, KiBank contains 8000 K_i values, over 6000 chemicals and 166 proteins covering the subtypes of receptors and enzymes.     

Molecular design of anticancer drug leads based on three-dimensional quantitative structure-activity relationship

Heat shock protein 90 (Hsp90) takes part in the developments of several cancers. Novobiocin, a typically C-terminal inhibitor for Hsp90, will probably used as an important anticancer drug in the future. In this work, we explored the valuable information and designed new novobiocin derivatives based on a three-dimensional quantitative structure-activity relationship (3D QSAR). The comparative molecular field analysis and comparative molecular similarity indices analysis models with high predictive capability were established, and their reliabilities are supported by the statistical parameters. Based on the several important influence factors obtained from these models, six new novobiocin derivatives with higher inhibitory activities were designed and confirmed by the molecular simulation with our models, which provide the potential anticancer drug leads for further research.     

AstexViewer: a visualisation aid for structure-based drug design

AstexViewer is a Java molecular graphics program that can be used for visualisation in many aspects of structure-based drug design. This paper describes its functionality, implementation and examples of its use. The program can run as an Applet in a web browser allowing structures to be displayed without installing additional software. Applications of its use are described for visualisation and as part of a structure based design platform. The software is being made freely available to the community and may be downloaded from http://www.astex-technology.com/AstexViewer.     

Development of quantitative imaging mass spectrometry (q-IMS) for drug visualization using animal tissues

Quantitative imaging mass spectrometry (q-IMS) is a frontier topic of research in drug analysis. Although many q-IMS methodologies have been reported, validation of the method is insufficient. We have investigated the feasibility of coupling q-IMS with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to develop a verifiable method. The approach combines quantitative LC-MS/MS information with the spatial distribution information obtained by IMS. This paper compares measured drug quantities with those estimated using IMS. The target drug, erlotinib, is a tyrosine kinase inhibitor of non-small-cell lung cancer. The quantitative accuracy of our q-IMS method in an animal model study is approximately 17%. Measurements were conducted on mouse liver and brain tissues before and after erlotinib administration. Erlotinib is delivered to the brain, although the concentration is 10⁴ times smaller than that found in the liver.     

SERAPhiC: a benchmark for in silico fragment-based drug design

Our main objective was to compile a data set of high-quality protein-fragment complexes and make it publicly available. Once assembled, the data set was challenged using docking procedures to address the following questions: (i) Can molecular docking correctly reproduce the experimentally solved structures? (ii) How thorough must the sampling be to replicate the experimental data? (iii) Can commonly used scoring functions discriminate between the native pose and other energy minima? The data set, named SERAPhiC (Selected Fragment Protein Complexes), is publicly available in a ready-to-dock format ( http://www.iit.it/en/drug-discovery-and-development/seraphic.html ). It offers computational medicinal chemists a reliable test set for both in silico protocol assessment and software development.     

Hydrogel design strategies for drug delivery

Hydrogels are water-swollen three-dimensional networks made of polymers, proteins, small molecules or colloids. They constitute a versatile platform for drug delivery because of their capacity to encapsulate and protect drugs and provide sustained and/or remotely programmable spatial and temporal release and have thus generated a substantial amount of research for the delivery of either small active compounds or biopharmaceuticals. This article discusses the features that make hydrogels attractive as matrices for delivery and reviews a range of designs, focussing on studies from recent years, in particular: ‘smart’ hydrogels (responding to temperature, light, magnetic fields, ultrasounds or combined stimuli); recent technologies: 3D printing and microneedles; and closes by discussing polymer-free drug delivery systems: peptides, small molecules and colloids.     

Modeling chemical reactions for drug design

Chemical reactions are involved at many stages of the drug design process. This starts with the analysis of biochemical pathways that are controlled by enzymes that might be downregulated in certain diseases. In the lead discovery and lead optimization process compounds have to be synthesized in order to test them for their biological activity. And finally, the metabolism of a drug has to be established. A better understanding of chemical reactions could strongly help in making the drug design process more efficient. We have developed methods for quantifying the concepts an organic chemist is using in rationalizing reaction mechanisms. These methods allow a comprehensive modeling of chemical reactivity and thus are applicable to a wide variety of chemical reactions, from gas phase reactions to biochemical pathways. They are empirical in nature and therefore allow the rapid processing of large sets of structures and reactions. We will show here how methods have been developed for the prediction of acidity values and of the regioselectivity in organic reactions, for designing the synthesis of organic molecules and of combinatorial libraries, and for furthering our understanding of enzyme-catalyzed reactions and of the metabolism of drugs.     

Development of a manufacturing process for the drug fenleuton

A new strategy for a large scale synthesis is developed and evaluated by the improvement of the current synthesis for fenleuton, a drug with important applications in leukotriene-mediated inflammatory diseases that acts through inhibition of the 5-lipoxygenase enzyme.     

A computer program for use in quantitative electron probe microanalysis

Summary A computer program for use in the conversion of electron probe X-ray intensity ratios into chemical compositions has been written. The inclusion of several of the more successful correction procedures facilitates the comparison of these procedures and allows an investigator to select the correction procedure which will give the best results for the system being studied. Theoretical calibration calculations of the intensity ratio versus composition can be performed and these results can be plotted by machine. The program has been designed to be as versatile as possible and still retain simple experimental input requirements. Some results obtained using recently published correction procedure are discussed.

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Zusammenfassung Ein Computerprogramm wurde geschrieben, um Intensitätsverhältnisse der Elektronenstrahlmikroanalyse in chemische Zusammensetzungen umzurechnen. Die Einfügung einiger besonders erfolgversprechender Korrekturverfahren erleichtert den Vergleich dieser Verfahren und ermöglicht dem Bearbeiter, jenes Korrekturverfahren auszuwählen, das für das eben untersuchte System die besten Ergebnisse liefert. Die theoretischen Berechnungen des Intensitätsverhältnisses in Abhängigkeit von der Zusammensetzung können als Eichung durchgeführt werden und diese Ergebnisse kann die Maschine ausdrucken. Das Programm wurde so vielseitig wie möglich erstellt, beinhaltet aber dennoch einfache experimentelle Eingabemöglichkeiten. Einige Ergebnisse, die durch den Gebrauch kürzlich veröffentlichter Korrekturverfahren erhalten wurden, werden diskutiert.

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Résumé Un programme d'ordinateur servant à convertir les rapports d'intensité de rayons X de sonde électronique en compositions chimiques a été rédigé. L'inclusion de plusieurs procédures de correction parmi celles qui ont obtenu le plus de succès facilite la comparaison de ces procédures et permet à l'investigateur de choisir la procédure de correction qui, à son avis, donnera les meilleurs résultats pour lè système étudié. Des calculs théoriques de calibrage entre le rapport d'intensité et la composition peuvent être faits et ces résultats peuvent être rapportés sur graphique mécaniquement. De par sa conception, le programme jouit du maximum de souplesse tout en gardant le plus de simplicité possible aux données expérimentales nécessaires à l'entrée. Certains résultats obtenus à l'aide de procédures de correction récemment publiés, font l'objet de discussions.

     

EUDOC: a computer program for identification of drug interaction sites in macromolecules and drug leads from chemical databases

The completion of the Human Genome Project, the growing effort on proteomics, and the Structural Genomics Initiative have recently intensified the attention being paid to reliable computer docking programs able to identify molecules that can affect the function of a macromolecule through molecular complexation. We report herein an automated computer docking program, EUDOC, for prediction of ligand-receptor complexes from 3D receptor structures, including metalloproteins, and for identification of a subset enriched in drug leads from chemical databases. This program was evaluated from the standpoints of force field and sampling issues using 154 experimentally determined ligand-receptor complexes and four "real-life" applications of the EUDOC program. The results provide evidence for the reliability and accuracy of the EUDOC program. In addition, key principles underlying molecular recognition, and the effects of structural water molecules in the active site and different atomic charge models on docking results are discussed. Copyright 2001 John Wiley & Sons, Inc. J Comput Chem 22: 1750-1771, 2001     

NMR spectroscopy tools for structure-aided drug design

Biomolecular NMR spectroscopy has expanded dramatically in recent years and is now a powerful tool for the study of structure, dynamics, and interactions of biomolecules. Previous limitations with respect to molecular size are no longer a primary barrier, and systems as large as 900 kDa were recently studied. NMR spectroscopy is already well-established as an efficient method for ligand screening. A number of recently developed techniques show promise as aids in structure-based drug design, for example, in the rapid determination of global protein folds, the structural characterization of ligand-protein complexes, and the derivation of thermodynamic parameters. An advantage of the method is that all these interactions can be studied in solution--time-consuming crystallization is not necessary. This Review focuses on recent developments in NMR spectroscopy and how they might be of value in removing some of the current "bottlenecks" in structure-based drug discovery.     

Rational design of nanocarriers for mitochondria-targeted drug delivery

Well-developed mitochondria-targeted nanocarriers for function regulation are highly desirable. Numerous studies have been conducted on the treatment of mitochondria-related diseases; however, further improvements are required to develop more effective drug delivery methods. Herein, we comprehensively introduce recent developments progress in rational design of mitochondria-targeted nanocarriers, and discuss the different strategies of available nanocarriers for targeting mitochondria. We also highlight the advantages and disadvantages of various carrier systems that are currently in use. Finally, perspective on new generation for mitochondria-targeted delivery systems in the emerging area of drug-based therapeutics is also discussed.