The bioinorganic and medicinal chemistry of carboranes: from new drug discovery to molecular imaging and therapy

The role of carboranes in medicinal chemistry has diversified in recent years and now extends into areas of drug discovery, molecular imaging, and targeted radionuclide therapy. An introduction to carborane chemistry is provided to familiarize the non-expert with some key properties of these molecules, followed by an overview of current medicinally-orientated research involving carboranes. The broad-ranging nature of this research is illustrated, with emphasis placed on recent highlights and advances in this field.     

Molecular complexity and its impact on the probability of finding leads for drug discovery.

Using a simple model of ligand-receptor interactions, the interactions between ligands and receptors of varying complexities are studied and the probabilities of binding calculated. It is observed that as the systems become more complex the chance of observing a useful interaction for a randomly chosen ligand falls dramatically. The implications of this for the design of combinatorial libraries is explored. A large set of drug leads and optimized compounds is profiled using several different properties relevant to molecular recognition. The changes observed for these properties during the drug optimization phase support the hypothesis that less complex molecules are more common starting points for the discovery of drugs. An extreme example of the use of simple molecules for directed screening against thrombin is provided.     

The application of sulfur-containing peptides in drug discovery

The purpose of the present review is to focus on the discovery of various sulfur-containing peptides with particular emphasis on their pharmacological mechanisms. This presentation is organized according to the structures of the sulfur-containing peptides.     

Expanding medicinal chemistry into 3D space: metallofragments as 3D scaffolds for fragment-based drug discovery

Fragment-based drug discovery (FBDD) is a powerful strategy for the identification of new bioactive molecules. FBDD relies on fragment libraries, generally of modest size, but of high chemical diversity. Although good chemical diversity in FBDD libraries has been achieved in many respects, achieving shape diversity – particularly fragments with three-dimensional (3D) structures – has remained challenging. A recent analysis revealed that >75% of all conventional, organic fragments are predominantly 1D or 2D in shape. However, 3D fragments are desired because molecular shape is one of the most important factors in molecular recognition by a biomolecule. To address this challenge, the use of inert metal complexes, so-called ‘metallofragments’ (mFs), to construct a 3D fragment library is introduced. A modest library of 71 compounds has been prepared with rich shape diversity as gauged by normalized principle moment of inertia (PMI) analysis. PMI analysis shows that these metallofragments occupy an area of fragment space that is unique and highly underrepresented when compared to conventional organic fragment libraries that are comprised of orders of magnitude more molecules. The potential value of this metallofragment library is demonstrated by screening against several different types of proteins, including an antiviral, an antibacterial, and an anticancer target. The suitability of the metallofragments for future hit-to-lead development was validated through the determination of IC₅₀ and thermal shift values for select fragments against several proteins. These findings demonstrate the utility of metallofragment libraries as a means of accessing underutilized 3D fragment space for FBDD against a variety of protein targets.

Fragment-based drug discovery (FBDD) using 3-dimensional metallofragments is a new strategy for the identification of bioactive molecules.     

Tautomerism in drug discovery

The influence of tautomerism on the precise structure of drugs and thus of their potential to interact with biological systems is discussed from thermodynamic and kinetic aspects. The types of tautomerism encountered in the structure of drugs in current use are surveyed together with the effect of pH, solvent polarity, and temperature.     

The future of molecular dynamics simulations in drug discovery

Molecular dynamics simulations can now track rapid processes—those occurring in less than about a millisecond—at atomic resolution for many biologically relevant systems. These simulations appear poised to exert a significant impact on how new drugs are found, perhaps even transforming the very process of drug discovery. We predict here future results we can expect from, and enhancements we need to make in, molecular dynamics simulations over the coming 25 years, and in so doing set out several Grand Challenges for the field. In the context of the problems now facing the pharmaceutical industry, we ask how we can best address drug discovery needs of the next quarter century using molecular dynamics simulations, and we suggest some possible approaches.     

The ubiquitin system,disease, and drug discovery

Abstract

The ubiquitin system of protein modification has emerged as a crucial mechanism involved in the regulation of a wide array of cellular processes. As our knowledge of the pathways in this system has grown, so have the ties between the protein ubiquitin and human disease. The power of the ubiquitin system for therapeutic benefit blossomed with the approval of the proteasome inhibitor Velcade in 2003 by the FDA. Current drug discovery activities in the ubiquitin system seek to (i) expand the development of new proteasome inhibitors with distinct mechanisms of action and improved bioavailability, and (ii) validate new targets. This review summarizes our current understanding of the role of the ubiquitin system in various human diseases ranging from cancer, viral infection and neurodegenerative disorders to muscle wasting, diabetes and inflammation. I provide an introduction to the ubiquitin system, highlight some emerging relationships between the ubiquitin system and disease, and discuss current and future efforts to harness aspects of this potentially powerful system for improving human health.

Publication history

Republished from Current BioData's Targeted Proteins database (TPdb; http://www.targetedproteinsdb.com).

     

Carbohydrate chemistry in drug discovery

The multitude of roles that carbohydrates and their glyco-conjugates play in biological processes has stimulated great interest in determining the nature of their interactions in both normal and diseased states. Manipulating such interactions will provide leads for drug discovery. Of the major classes of biomolecule, carbohydrates are the most structurally diverse. This hetereogeneity makes isolation of pure samples, and in sufficient amounts, from biological sources extremely difficult. Chemical synthesis offers the advantage of producing pure and structurally defined oligosaccharides for biological investigations. Although the complex nature of carbohydrates means that this is challenging, recent advances in the field have facilitated access to these molecules. The synthesis and isolation of oligosaccharides combined with progress in glycoarray technology have aided the identification of new carbohydrate-binding drug targets. This review aims to provide an overview of the latest advancements in carbohydrate chemistry and the role of these complex molecules in drug discovery, focusing particularly on synthetic methodologies, glycosaminoglycans, glycoprotein synthesis and vaccine development over the last few years.     

The beautiful cell: high-content screening in drug discovery

The term “high-content screening” has become synonymous with imaging screens using automated microscopes and automated image analysis. The term was coined a little over 10 years ago. Since then the technology has evolved considerably and has established itself firmly in the drug discovery and development industry. Both the instruments and the software controlling the instruments and analyzing the data have come to maturity, so the full benefits of high-content screening can now be realized. Those benefits are the capability of carrying out phenotypic multiparametric cellular assays in an unbiased, fully automated, and quantitative fashion. Automated microscopes and automated image analysis are being applied at all stages of the drug discovery and development pipeline. All major pharmaceutical companies have adopted the technology and it is in the process of being embraced broadly by the academic community. This review aims at describing the current capabilities and limits of the technology as well as highlighting necessary developments that are required to exploit fully the potential of high-content screening and analysis.     

Correction: Expanding medicinal chemistry into 3D space: metallofragments as 3D scaffolds for fragment-based drug discovery

Correction for ‘Expanding medicinal chemistry into 3D space: metallofragments as 3D scaffolds for fragment-based drug discovery’ by Christine N. Morrison et al., Chem. Sci., 2020, 11, 1216–1225, https://doi.org/10.1039/C9SC05586J.

The authors regret that in the original article, inhibitory values reported for some metallofragments were incorrect. Unfortunately, DMSO stock solutions of reportedly active ferrocene-based metallofragments were found to decompose in the presence of light, which resulted in inaccurate inhibition values. The authors maintain that the core conclusions of the paper are accurate and the utility of three-dimensional metal complexes for fragment-based drug discovery has merit.In the original article, ‘class A’ metallofragments are comprised of ferrocene derivatives (Fig. 1). Some of these ferrocene fragments (specifically those containing carbonyl groups) are reported as broadly inhibiting several protein targets. It was noted in our original report that the ferrocene scaffold was likely promiscuous due to its lipophilicity and potential redox activity, but that it might still serve as a useful metallofragment for fragment-based drug discovery (FBDD) campaigns. However, re-evaluation of these compounds against the influenza endonuclease (PA_N) failed to reproduce our original inhibition results for the class A metallofragments using freshly prepared stocks, indicating a problem with the materials used in the original study.Open in a separate windowFig. 1Chemical structures of class A metallofragments.Several compounds from class A were originally reported as having near complete (100%) inhibition against PA_N endonuclease at an inhibitor concentration of 200 μM (​and2).2). However, when re-evaluated under identical conditions, using freshly prepared DMSO stock solutions, inhibition was only observed with one fragment of this class (A22, Fig. 1), with the previously reported highly active fragments (A4, A7–A21,

Activity-based profiling for drug discovery

Activity-based protein profiling (ABPP) is emerging as a game-changing tool for drug discovery, target validation, and basic biology. In this issue, Chang et?al. (2011) report the ABPP-facilitated discovery of JW480, a highly selective potent and orally bioavailable inhibitor of monoalkylglycerol ether hydrolase KIAA1363 that dramatically impairs in?vivo growth of human prostate cancer cell lines.     

A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases

The discovery of various protein/receptor targets from genomic research is expanding rapidly. Along with the automation of organic synthesis and biochemical screening, this is bringing a major change in the whole field of drug discovery research. In the traditional drug discovery process, the industry tests compounds in the thousands. With automated synthesis, the number of compounds to be tested could be in the millions. This two-dimensional expansion will lead to a major demand for resources, unless the chemical libraries are made wisely. The objective of this work is to provide both quantitative and qualitative characterization of known drugs which will help to generate "drug-like" libraries. In this work we analyzed the Comprehensive Medicinal Chemistry (CMC) database and seven different subsets belonging to different classes of drug molecules. These include some central nervous system active drugs and cardiovascular, cancer, inflammation, and infection disease states. A quantitative characterization based on computed physicochemical property profiles such as log P, molar refractivity, molecular weight, and number of atoms as well as a qualitative characterization based on the occurrence of functional groups and important substructures are developed here. For the CMC database, the qualifying range (covering more than 80% of the compounds) of the calculated log P is between -0.4 and 5.6, with an average value of 2.52. For molecular weight, the qualifying range is between 160 and 480, with an average value of 357. For molar refractivity, the qualifying range is between 40 and 130, with an average value of 97. For the total number of atoms, the qualifying range is between 20 and 70, with an average value of 48. Benzene is by far the most abundant substructure in this drug database, slightly more abundant than all the heterocyclic rings combined. Nonaromatic heterocyclic rings are twice as abundant as the aromatic heterocycles. Tertiary aliphatic amines, alcoholic OH and carboxamides are the most abundant functional groups in the drug database. The effective range of physicochemical properties presented here can be used in the design of drug-like combinatorial libraries as well as in developing a more efficient corporate medicinal chemistry library.     

The discovery of isotactic polypropylene and its impact on pure and applied science

This article recalls some aspects of the fascinating history of the discovery by Giulio Natta and his research group of the stereoselective polymerization of propylene and the understanding of the relationships between structure and properties of semicrystalline polymers. The impact of the discovery of isotactic polypropylene and stereoregular polymers on pure and applied science is briefly outlined. © 2003 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 42: 391–395, 2004     

WinDock: structure-based drug discovery on Windows-based PCs

In recent years, virtual database screening using high-throughput docking (HTD) has emerged as a very important tool and a well-established method for finding new lead compounds in the drug discovery process. With the advent of powerful personal computers (PCs), it is now plausible to perform HTD investigations on these inexpensive PCs. To make HTD more accessible to a broad community, we present here WinDock, an integrated application designed to help researchers perform structure-based drug discovery tasks under a uniform, user friendly graphical interface for Windows-based PCs. WinDock combines existing small molecule searchable three-dimensional (3D) libraries, homology modeling tools, and ligand-protein docking programs in a semi-automatic, interactive manner, which guides the user through the use of each integrated software component. WinDock is coded in C++.