The emergence of the drug receptor theory

Systems pharmacology and genome medicine: a future perspective

Genome medicine uses genomic information in the diagnosis of disease and in prescribing treatment. This transdisciplinary field brings together knowledge on the relationships between genetics, pathophysiology and pharmacology. Systems pharmacology aims to understand the actions and adverse effects of drugs by considering targets in the context of the biological networks in which they exist. Genome medicine forms the base on which systems pharmacology can develop. Experimental and computational approaches enable systems pharmacology to obtain holistic, mechanistic information on disease networks and drug responses, and to identify new drug targets and specific drug combinations. Network analyses of interactions involved in pathophysiology and drug response across various scales of organization, from molecular to organismal, will allow the integration of the systems-level understanding of drug action with genome medicine. The interface of the two fields will enable drug discovery for personalized medicine. Here we provide a perspective on the questions and approaches that drive the development of these new interrelated fields.

Defining the role of pharmacology in the emerging world of translational research

Pharmacology is focused on studying the effects of endogenous agents and xenobiotics on tissue and organ function. Analysis of the concentration/response relationship is the foundation for these assessments as it provides quantifiable information on compound efficacy, potency, and, ultimately, side-effect liability and therapeutic index. Historically, pharmacology has been viewed as a unifying, hierarchically integrated, and technologically agnostic discipline. Besides being important in the development of new medications, pharmacological research has led to a better understanding of disease pathogenesis and progression. By defining the effects of compounds in vitro and in vivo, pharmacology has provided the means to validate, optimize, and advance new chemical entities (NCEs) to human testing. With the advent of molecular biology-based assay systems and a technology-driven (high-throughput screening, combinatorial chemistry, SNP mapping, systems biology) reductionistic focus, the integrated, hypothesis-driven pharmacological approach to drug discovery has been de-emphasized in recent years. This shift in research emphasis is now viewed by many as a major factor in the decline of new drug approvals and has led to various initiatives, the most notable being the Critical Path and Phase 0 clinical trial initiatives launched by the US Food and Drug Administration (FDA). These programs underscore the growing need for individuals trained in integrative pharmacology and having a background in molecular pharmacology to drive the drug discovery process and to fostering the translational research that is now considered vital for more rapidly identifying novel, more effective, and safer medications.

Design of recombinant antibody microarrays for cell surface membrane proteomics

Generating proteomic maps of membrane proteins, common targets for therapeutic interventions and disease diagnostics, has turned out to be a major challenge. Antibody-based microarrays are among the novel rapidly evolving proteomic technologies that may enable global proteome analysis to be performed. Here, we have designed the first generation of a scaleable human recombinant scFv antibody microarray technology platform for cell surface membrane proteomics as well as glycomics targeting intact cells. The results showed that rapid and multiplexed profiling of the cell surface proteome (and glycome) could be performed in a highly specific and sensitive manner and that differential expression patterns due to external stimuli could be monitored.

A short history of the rise of the molecular pharmacology of ionotropic drug receptors

Remarkably, perhaps, for many pharmacologists today, just over 25 years ago, receptors were still considered hypothetical entities. The isolation and identification of Langley's receptive substance (Ehrlich's side-chains) required efforts from diverse groups; serendipity also facilitated its purification and subsequent biochemical and molecular characterization. In this review, I consider some of the key individuals and breakthrough technical developments from the late 1950s to the early 1990s that lead to the cloning of the first receptors. I focus on the nicotinic acetylcholine receptor to illustrate the complexities in this field and because it was the first receptor to be cloned. This brief history will also touch upon the implications of the rise of molecular pharmacology for the development of new drugs.

Screening the receptorome: an efficient approach for drug discovery and target validation

The receptorome, comprising at least 5% of the human genome, encodes receptors that mediate the physiological, pathological and therapeutic responses to a vast number of exogenous and endogenous ligands. Not surprisingly, the majority of approved medications target members of the receptorome. Several in silico and physical screening approaches have been devised to mine the receptorome efficiently for the discovery and validation of molecular targets for therapeutic drug discovery. Receptorome screening has also been used to discover, and thereby avoid, the molecular targets responsible for serious and unforeseen drug side effects.

Fall and rise of behavioural pharmacology

Since the 1970s, a fortunate ensemble of technological and scientific developments has radically changed pharmacology, both in practice and imaginative thinking, towards a predominantly molecular science. Economic and political forces contributed to the undervaluation of in vivo experiments. The present generation of bioscientists, undertrained in whole animal, particularly behavioural pharmacology, now faces the challenge to interpret and translate an interminable hoard of molecular data into understandable and applicable medicine. The article provides a retrospection in four decades of progress.:

General Linearized Biexponential Model for QSAR Data Showing Bilinear-Type Distribution

A major impediment of many QSAR-type analyses is that the data show a maximum or minimum and can no longer be adequately described by linear functions that provide unrivaled simplicity and usually give good description over more restricted ranges. Here, a general linearized biexponential (LinBiExp) model is proposed that can adequately describe data showing bilinear-type distribution as a function of not just often-employed lipophilicity descriptors (e.g., log P) but as a function of any descriptor (e.g., molecular volume). Contrary to Hansch-type parabolic models, LinBiExp allows the natural extension of linear models and fitting of asymmetrical data. It is also more general and intuitive than Kubinyi's model as it has a more natural functional form. It was obtained by a differential equation-based approach starting from very general assumptions that cover both static equilibria and first-order kinetic processes and that involve abstract processes through which the concentration of the compound of interest in an assumed "effect" compartment is connected to its "external" concentration. Physicochemical aspects placing LinBiExp within the framework of linear free energy relationship (LFER) approaches are presented together with illustrative applications in various fields such as toxicity, antimicrobial activity, anticholinergic activity, and glucocorticoid receptor binding.

Molecular modelling of drug targets: the past, the present and the future

Most currently used therapeutic drugs have an enzyme or a membrane-bound receptor as site of action. The sequencing of the human and other genomes has provided a potential to identify many hitherto unknown proteins that might serve as new drug targets. To achieve this, knowledge about three-dimensional protein structures is crucial for the understanding of their functional mechanisms, and for a rational drug design. Over the last decade atomic resolution crystal structures of soluble proteins have been reported in a rapidly increasing number, but the detailed three-dimensional structures are still unknown for the majority of membrane proteins since their membrane association makes experimental structure determinations complicated. Computerized modelling of protein structures, based on experimentally determined structures of homologue proteins, may be a useful methodological alternative, especially for membrane proteins. In the past, molecular modelling of transporters and G-protein-coupled receptors was based on low-resolution structural data obtained by cryo-electron microscopy. Recent high-resolution crystal structure determinations of a G-protein-coupled receptor, rhodopsin, and several different transporter proteins and ion channels have enabled construction of more accurate receptor and transporter models. For the future, collaborative structural genomics initiatives aim at determining the three-dimensional structure of all known proteins, based on a combination of experimental structure determination and molecular modelling. Development of still more powerful computer hardware and software will enable extensive studies of the protein structure and dynamics of new potential drug targets, but raises a new challenge in the validation and calibration of computerized methods of biosimulations.

Principles: receptor theory in pharmacology

Pharmacological receptor theory is discussed with special reference to advances made during the past 25 years. Thus, the operational model has supplanted analysis of drug-receptor interaction in functional systems whereas the extended ternary complex model is used routinely to simulate quantitatively G-protein-coupled receptor (GPCR) behavior. Six new behaviors for GPCRs, centered on spontaneous production of receptor active states, ligand-selective receptor active states, oligomerization with other proteins (receptor and non-receptor) and allosteric mechanisms, have been characterized and each holds the potential for new drug discovery for therapeutic benefit.

Rediscovering the sweet spot in drug discovery

Advances over the past decade in drug discovery technologies have not yet led to an increase in productivity. We analyzed the reasons that have led to this juncture and identify the selection of the right target and the right lead as crucial. New approaches are required to take full advantage of the genomics revolution. For targets, methods are becoming available for high-throughput proteome analysis and pathway characterization that synergize with studies of disease association and differential expression. For leads, methods are being developed that 'reverse' the high-throughput screening paradigm by mapping drugs and drug-like compounds back onto the proteome. The synergy between pathway mapping and compound mapping could allow the pharmaceutical and biotechnology industries to rediscover the sweet spot of research productivity.

Discovering risperidone: the LSD model of psychopathology

In the 1970s and 1980s, Janssen Pharmaceutica Research, which had a broad interest in central nervous system disorders and nurtured intellectual freedom, developed original, and at times heretical, concepts. It took decades for the scientific community to endorse some of these concepts. Among them were such notions as an elementary particle of behaviour, the introduction of response quality in receptor theory, and the idea that tolerance does not develop to opioids. These concepts enabled the discovery of the antipsychotic risperidone, a unique full antagonist of the interoceptive effects of LSD.