The influence of the 'organizational factor' on compound quality in drug discovery

Molecular inflation, attrition and the rule of five

Physicochemical properties underlie all aspects of drug action and are critical for solubility, permeability and successful formulation. Specific physicochemical properties shown to be relevant to oral drugs are size, lipophilicity, ionisation, hydrogen bonding, polarity, aromaticity and shape. The rule of 5 (Ro5) and subsequent studies have raised awareness of the importance of compound quality amongst bioactive molecules. Lipophilicity, probably the most important physical property of oral drugs, has on average changed little over time in oral drugs, until increases in drugs published after 1990. In contrast other molecular properties such as average size have increased significantly. Factors influencing property inflation include the targets pursued, where antivirals frequently violate the Ro5, risk/benefit considerations, and variable drug discovery practices. The compounds published in patents from the pharmaceutical industry are on average larger, more lipophilic and less complex than marketed oral drugs. The variation between individual companies' patented compounds is due to different practices and not to the targets pursued. Overall, there is demonstrable physical property attrition in moving from patents to candidate drugs to marketed drugs. The pharmaceutical industry's recent poor productivity has been due, in part, to progression of molecules that are unable to unambiguously test clinical efficacy, and attrition can therefore be improved by ensuring candidate drug quality is 'fit for purpose.' The combined ligand efficiency (LE) and lipophilic ligand efficiency (LLE) values of many marketed drugs are optimised relative to other molecules acting at the same target. Application of LLE in optimisation can help identify improved leads, even with challenging targets that seem to require lipophilic ligands. Because of their targets, some projects may need to pursue 'beyond Ro5' physicochemical space; such projects will require non-standard lead generation and optimisation and should not dominate in a well-balanced portfolio. Compound quality is controllable by lead selection and optimisation and should not be a cause of clinical failure.

Prioritization of anti-malarial hits from nature: chemo-informatic profiling of natural products with in vitro antiplasmodial activities and currently registered anti-malarial drugs

BACKGROUND

A large number of natural products have shown in vitro antiplasmodial activities. Early identification and prioritization of these natural products with potential for novel mechanism of action, desirable pharmacokinetics and likelihood for development into drugs is advantageous. Chemo-informatic profiling of these natural products were conducted and compared to currently registered anti-malarial drugs (CRAD).

METHODS

Natural products with in vitro antiplasmodial activities (NAA) were compiled from various sources. These natural products were sub-divided into four groups based on inhibitory concentration (IC50). Key molecular descriptors and physicochemical properties were computed for these compounds and analysis of variance used to assess statistical significance amongst the sets of compounds. Molecular similarity analysis, estimation of drug-likeness, in silico pharmacokinetic profiling, and exploration of structure-activity landscape were also carried out on these sets of compounds.

RESULTS

A total of 1040 natural products were selected and a total of 13 molecular descriptors were analysed. Significant differences were observed among the sub-groups of NAA and CRAD for at least 11 of the molecular descriptors, including number of hydrogen bond donors and acceptors, molecular weight, polar and hydrophobic surface areas, chiral centres, oxygen and nitrogen atoms, and shape index. The remaining molecular descriptors, including clogP, number of rotatable bonds and number of aromatic rings, did not show any significant difference when comparing the two compound sets. Molecular similarity and chemical space analysis identified natural products that were structurally diverse from CRAD. Prediction of the pharmacokinetic properties and drug-likeness of these natural products identified over 50% with desirable drug-like properties. Nearly 70% of all natural products were identified as potentially promiscuous compounds. Structure-activity landscape analysis highlighted compound pairs that form 'activity cliffs'. In all, prioritization strategies for the NAA were proposed.

CONCLUSIONS

Chemo-informatic profiling of NAA and CRAD have produced a wealth of information that may guide decisions and facilitate anti-malarial drug development from natural products. Articulation of the information provided within an interactive data-mining environment led to a prioritized list of NAA.

Toxicology Strategies for Drug Discovery: Present and Future

Attrition due to nonclinical safety represents a major issue for the productivity of pharmaceutical research and development (R&D) organizations, especially during the compound optimization stages of drug discovery and the early stages of clinical development. Focusing on decreasing nonclinical safety-related attrition is not a new concept, and various approaches have been experimented with over the last two decades. Front-loading testing funnels in Discovery with in vitro toxicity assays designed to rapidly identify unfavorable molecules was the approach adopted by most pharmaceutical R&D organizations a few years ago. However, this approach has also a non-negligible opportunity cost. Hence, significant refinements to the "fail early, fail often" paradigm have been proposed recently to reflect the complexity of accurately categorizing compounds with early data points without taking into account other important contextual aspects, in particular efficacious systemic and tissue exposures. This review provides an overview of toxicology approaches and models that can be used in pharmaceutical Discovery at the series/lead identification and lead optimization stages to guide and inform chemistry efforts, as well as a personal view on how to best use them to meet nonclinical safety-related attrition objectives consistent with a sustainable pharmaceutical R&D model. The scope of this review is limited to small molecules, as large molecules are associated with challenges that are quite different. Finally, a perspective on how several emerging technologies may impact toxicity evaluation is also provided.

A new paradigm for navigating compound property related drug attrition

Improving the efficiency of drug discovery remains a major focus for the pharmaceutical industry. Toxicity accounts for 90% of withdrawals and major early-stage terminations relate to suboptimal efficacy and safety. Traditional oral drug space is well defined with respect to physicochemical properties and ADMET risks but increased focus on ligand-lipophilicity efficiency, maximizing enthalpy contributions and new target classes challenge this paradigm. A hybrid space has been identified that combines physical properties and key interactions attributable to drug transporters. A novel algorithm is proposed that incorporates drug-transporter interactions and its utility evaluated against popular ligand efficiency indices. Simply reducing the bulk properties of compounds can exchange one problem for another and creates high-risk areas that challenge the successful delivery from a balanced portfolio.

Molecular Property Design: Does Everyone Get It?

The principles of molecular property optimization in drug design have been understood for decades, yet much drug discovery activity today is conducted at the periphery of historical druglike property space. Lead optimization trajectories aimed at reducing physicochemical risk, assisted by ligand efficiency metrics, could help to reduce clinical attrition rates.

An analysis of the attrition of drug candidates from four major pharmaceutical companies

The pharmaceutical industry remains under huge pressure to address the high attrition rates in drug development. Attempts to reduce the number of efficacy- and safety-related failures by analysing possible links to the physicochemical properties of small-molecule drug candidates have been inconclusive because of the limited size of data sets from individual companies. Here, we describe the compilation and analysis of combined data on the attrition of drug candidates from AstraZeneca, Eli Lilly and Company, GlaxoSmithKline and Pfizer. The analysis reaffirms that control of physicochemical properties during compound optimization is beneficial in identifying compounds of candidate drug quality and indicates for the first time a link between the physicochemical properties of compounds and clinical failure due to safety issues. The results also suggest that further control of physicochemical properties is unlikely to have a significant effect on attrition rates and that additional work is required to address safety-related failures. Further cross-company collaborations will be crucial to future progress in this area.

In silico design of low molecular weight protein-protein interaction inhibitors: Overall concept and recent advances

Protein-protein interactions (PPIs) are carrying out diverse functions in living systems and are playing a major role in the health and disease states. Low molecular weight (LMW) "drug-like" inhibitors of PPIs would be very valuable not only to enhance our understanding over physiological processes but also for drug discovery endeavors. However, PPIs were deemed intractable by LMW chemicals during many years. But today, with the new experimental and in silico technologies that have been developed, about 50 PPIs have already been inhibited by LMW molecules. Here, we first focus on general concepts about protein-protein interactions, present a consensual view about ligandable pockets at the protein interfaces and the possibilities of using fast and cost effective structure-based virtual screening methods to identify PPI hits. We then discuss the design of compound collections dedicated to PPIs. Recent financial analyses of the field suggest that LMW PPI modulators could be gaining momentum over biologics in the coming years supporting further research in this area.

Optimization of sphingosine-1-phosphate-1 receptor agonists: effects of acidic, basic, and zwitterionic chemotypes on pharmacokinetic and pharmacodynamic profiles

The efficacy of the recently approved drug fingolimod (FTY720) in multiple sclerosis patients results from the action of its phosphate metabolite on sphingosine-1-phosphate S1P1 receptors, while a variety of side effects have been ascribed to its S1P3 receptor activity. Although S1P and phospho-fingolimod share the same structural elements of a zwitterionic headgroup and lipophilic tail, a variety of chemotypes have been found to show S1P1 receptor agonism. Here we describe a study of the tolerance of the S1P1 and S1P3 receptors toward bicyclic heterocycles of systematically varied shape and connectivity incorporating acidic, basic, or zwitterionic headgroups. We compare their physicochemical properties, their performance in in vitro and in vivo pharmacokinetic models, and their efficacy in peripheral lymphocyte lowering. The campaign resulted in the identification of several potent S1P1 receptor agonists with good selectivity vs S1P3 receptors, efficacy at <1 mg/kg oral doses, and developability properties suitable for progression into preclinical development.

Novel tactics for designing water-soluble molecules in drug discovery

INTRODUCTION

Physiochemical drug properties, such as aqueous solubility are considered to be a major factor in determining the ultimate success or failure of experimental agents. Solubility is important because it determines the maximum dose which can be taken up. As the size and hydrophobicity of drug candidates has increased over the years, poor solubility has become a more prevalent issue. Recent examples from the literature show that an improved understanding of the relationship between molecular structure and solubility allows this issue to be approached using rational design.

AREAS COVERED

This review provides selected examples from the recent drug discovery literature that demonstrate various tactics, which have been applied successfully towards improving drug solubility. The examples that were selected demonstrate the underlying principles behind aqueous solubility, such as hydrophobicity and crystalline stability.

EXPERT OPINION

From a strategic point of view, improving the solubility of a compound should be straightforward because it can be accomplished by simply reducing hydrophobicity or crystalline stability. However, the structural elements and physical properties which control solubility also influence potency, pharmacokinetics and toxicity. Furthermore, there are practical aspects such as the quantity and quality of solubility-related data, which hamper the development of structure-solubility relationships. Given that poor aqueous solubility remains a primary issue in drug discovery, there is a continuous need for novel methods to overcome it.

Drug-Like Protein-Protein Interaction Modulators: Challenges and Opportunities for Drug Discovery and Chemical Biology

[Formula: see text] Fundamental processes in living cells are largely controlled by macromolecular interactions and among them, protein-protein interactions (PPIs) have a critical role while their dysregulations can contribute to the pathogenesis of numerous diseases. Although PPIs were considered as attractive pharmaceutical targets already some years ago, they have been thus far largely unexploited for therapeutic interventions with low molecular weight compounds. Several limiting factors, from technological hurdles to conceptual barriers, are known, which, taken together, explain why research in this area has been relatively slow. However, this last decade, the scientific community has challenged the dogma and became more enthusiastic about the modulation of PPIs with small drug-like molecules. In fact, several success stories were reported both, at the preclinical and clinical stages. In this review article, written for the 2014 International Summer School in Chemoinformatics (Strasbourg, France), we discuss in silico tools (essentially post 2012) and databases that can assist the design of low molecular weight PPI modulators (these tools can be found at www.vls3d.com). We first introduce the field of protein-protein interaction research, discuss key challenges and comment recently reported in silico packages, protocols and databases dedicated to PPIs. Then, we illustrate how in silico methods can be used and combined with experimental work to identify PPI modulators.

Yeast synthetic biology platform generates novel chemical structures as scaffolds for drug discovery

Synthetic biology has been heralded as a new bioengineering platform for the production of bulk and specialty chemicals, drugs, and fuels. Here, we report for the first time a series of 74 novel compounds produced using a combinatorial genetics approach in baker's yeast. Based on the concept of "coevolution" with target proteins in an intracellular primary survival assay, the identified, mostly scaffold-sized (200-350 MW) compounds, which displayed excellent biological activity, can be considered as prevalidated hits. Of the molecules found, >75% have not been described previously; 20% of the compounds exhibit novel scaffolds. Their structural and physicochemical properties comply with established rules of drug- and fragment-likeness and exhibit increased structural complexities compared to synthetically produced fragments. In summary, the synthetic biology approach described here represents a completely new, complementary strategy for hit and early lead identification that can be easily integrated into the existing drug discovery process.

Ligand-free Suzuki-Miyaura coupling with sulfur-modified gold-supported palladium in the synthesis of a conformationally-restricted cyclopropane compound library with three-dimensional diversity

A conformationally restricted privileged structure library with stereochemical diversity for a "fragment growth" methodology comprising 90 compounds was designed and systematically and efficiently synthesized using sulfur-modified Au-supported Pd (SAPd)-catalyzed ligand-free Suzuki-Miyaura coupling of vinyl iodide promoted by microwave and subsequent amidation in liquid-phase combinatorial chemistry as key reactions. Evaluation of the compounds with a 20-kinase panel indicated the usefulness of this "fragment growth" methodology for finding hit library compounds for fragment-based drug discovery.

Metabolomics and systems pharmacology: why and how to model the human metabolic network for drug discovery

Metabolism represents the 'sharp end' of systems biology, because changes in metabolite concentrations are necessarily amplified relative to changes in the transcriptome, proteome and enzyme activities, which can be modulated by drugs. To understand such behaviour, we therefore need (and increasingly have) reliable consensus (community) models of the human metabolic network that include the important transporters. Small molecule 'drug' transporters are in fact metabolite transporters, because drugs bear structural similarities to metabolites known from the network reconstructions and from measurements of the metabolome. Recon2 represents the present state-of-the-art human metabolic network reconstruction; it can predict inter alia: (i) the effects of inborn errors of metabolism; (ii) which metabolites are exometabolites, and (iii) how metabolism varies between tissues and cellular compartments. However, even these qualitative network models are not yet complete. As our understanding improves so do we recognise more clearly the need for a systems (poly)pharmacology.

Chemical predictive modelling to improve compound quality

The 'quality' of small-molecule drug candidates, encompassing aspects including their potency, selectivity and ADMET (absorption, distribution, metabolism, excretion and toxicity) characteristics, is a key factor influencing the chances of success in clinical trials. Importantly, such characteristics are under the control of chemists during the identification and optimization of lead compounds. Here, we discuss the application of computational methods, particularly quantitative structure-activity relationships (QSARs), in guiding the selection of higher-quality drug candidates, as well as cultural factors that may have affected their use and impact.

Increasing the coverage of medicinal chemistry-relevant space in commercial fragments screening

Analyzing the chemical space coverage in commercial fragment screening collections revealed the overlap between bioactive medicinal chemistry substructures and rule-of-three compliant fragments is only ∼25%. We recommend including these fragments in fragment screening libraries to maximize confidence in discovering hit matter within known bioactive chemical space, while incorporation of nonoverlapping substructures could offer novel hits in screening libraries. Using principal component analysis, polar and three-dimensional substructures display a higher-than-average enrichment of bioactive compounds, indicating increasing representation of these substructures may be beneficial in fragment screening.

Fragment-based approaches to the discovery of kinase inhibitors

Protein kinases are one of the most important families of drug targets, and aberrant kinase activity has been linked to a large number of disease areas. Although eminently targetable using small molecules, kinases present a number of challenges as drug targets, not least obtaining selectivity across such a large and relatively closely related target family. Fragment-based drug discovery involves screening simple, low-molecular weight compounds to generate initial hits against a target. These hits are then optimized to more potent compounds via medicinal chemistry, usually facilitated by structural biology. Here, we will present a number of recent examples of fragment-based approaches to the discovery of kinase inhibitors, detailing the construction of fragment-screening libraries, the identification and validation of fragment hits, and their optimization into potent and selective lead compounds. The advantages of fragment-based methodologies will be discussed, along with some of the challenges associated with using this route. Finally, we will present a number of key lessons derived both from our own experience running fragment screens against kinases and from a large number of published studies.

Synthesis of complex and diverse compounds through ring distortion of abietic acid

Many compound screening collections are populated by members that possess a low degree of structural complexity. In an effort to generate compounds that are both complex and diverse, we have developed a strategy that uses natural products as a starting point for complex molecule synthesis. Herein we apply this complexity-to-diversity approach to abietic acid, an abundant natural product used commercially in paints, varnishes, and lacquers. From abietic acid we synthesize a collection of complex (as assessed by fraction of sp(3) -hybridized carbons and number of stereogenic centers) and diverse (as assessed by Tanimoto analysis) small molecules. The 84 compounds constructed herein, and those created through similar efforts, should find utility in a variety of biological screens.

Tracking 20 years of compound-to-target output from literature and patents

The statistics of drug development output and declining yield of approved medicines has been the subject of many recent reviews. However, assessing research productivity that feeds development is more difficult. Here we utilise an extensive database of structure-activity relationships extracted from papers and patents. We have used this database to analyse published compounds cumulatively linked to nearly 4000 protein target identifiers from multiple species over the last 20 years. The compound output increases up to 2005 followed by a decline that parallels a fall in pharmaceutical patenting. Counts of protein targets have plateaued but not fallen. We extended these results by exploring compounds and targets for one large pharmaceutical company. In addition, we examined collective time course data for six individual protease targets, including average molecular weight of the compounds. We also tracked the PubMed profile of these targets to detect signals related to changes in compound output. Our results show that research compound output had decreased 35% by 2012. The major causative factor is likely to be a contraction in the global research base due to mergers and acquisitions across the pharmaceutical industry. However, this does not rule out an increasing stringency of compound quality filtration and/or patenting cost control. The number of proteins mapped to compounds on a yearly basis shows less decline, indicating the cumulative published target capacity of global research is being sustained in the region of 300 proteins for large companies. The tracking of six individual targets shows uniquely detailed patterns not discernible from cumulative snapshots. These are interpretable in terms of events related to validation and de-risking of targets that produce detectable follow-on surges in patenting. Further analysis of the type we present here can provide unique insights into the process of drug discovery based on the data it actually generates.

Small-molecule modulators for epigenetics targets

A capital conference: Influencing epigenetic mechanisms may be highly relevant for future therapies of various diseases such as cancer, inflammation, and metabolic disorders. Leading experts in the field gathered in Berlin on June 5-6, 2013 at a Bayer HealthCare Life Science Workshop to share recent success stories and to discuss future trends.

Phenotypic screens targeting neurodegenerative diseases

Neurodegenerative diseases affect millions of people worldwide, and the incidences increase as the population ages. Disease-modifying therapy that prevents or slows disease progression is still lacking, making neurodegenerative diseases an area of high unmet medical need. Target-based drug discovery for disease-modifying agents has been ongoing for many years, without much success due to incomplete understanding of the molecular mechanisms underlying neurodegeneration. Phenotypic screening, starting with a disease-relevant phenotype to screen for compounds that change the outcome of biological pathways rather than activities at certain specific targets, offers an alternative approach to find small molecules or targets that modulate the key characteristics of neurodegeneration. Phenotypic screens that focus on amelioration of disease-specific toxins, protection of neurons from degeneration, or promotion of neuroregeneration could be potential fertile grounds for discovering therapeutic agents for neurodegenerative diseases. In this review, we will summarize the progress of compound screening using these phenotypic-based strategies for this area, with a highlight on unique considerations for disease models, assays, and screening methodologies. We will further provide our perspectives on how best to use phenotypic screening to develop drug leads for neurodegenerative diseases.

Finding novel pharmaceuticals in the systems biology era using multiple effective drug targets, phenotypic screening and knowledge of transporters: where drug discovery went wrong and how to fix it

Despite the sequencing of the human genome, the rate of innovative and successful drug discovery in the pharmaceutical industry has continued to decrease. Leaving aside regulatory matters, the fundamental and interlinked intellectual issues proposed to be largely responsible for this are: (a) the move from 'function-first' to 'target-first' methods of screening and drug discovery; (b) the belief that successful drugs should and do interact solely with single, individual targets, despite natural evolution's selection for biochemical networks that are robust to individual parameter changes; (c) an over-reliance on the rule-of-5 to constrain biophysical and chemical properties of drug libraries; (d) the general abandoning of natural products that do not obey the rule-of-5; (e) an incorrect belief that drugs diffuse passively into (and presumably out of) cells across the bilayers portions of membranes, according to their lipophilicity; (f) a widespread failure to recognize the overwhelmingly important role of proteinaceous transporters, as well as their expression profiles, in determining drug distribution in and between different tissues and individual patients; and (g) the general failure to use engineering principles to model biology in parallel with performing 'wet' experiments, such that 'what if?' experiments can be performed in silico to assess the likely success of any strategy. These facts/ideas are illustrated with a reasonably extensive literature review. Success in turning round drug discovery consequently requires: (a) decent systems biology models of human biochemical networks; (b) the use of these (iteratively with experiments) to model how drugs need to interact with multiple targets to have substantive effects on the phenotype; (c) the adoption of polypharmacology and/or cocktails of drugs as a desirable goal in itself; (d) the incorporation of drug transporters into systems biology models, en route to full and multiscale systems biology models that incorporate drug absorption, distribution, metabolism and excretion; (e) a return to 'function-first' or phenotypic screening; and (f) novel methods for inferring modes of action by measuring the properties on system variables at all levels of the 'omes. Such a strategy offers the opportunity of achieving a state where we can hope to predict biological processes and the effect of pharmaceutical agents upon them. Consequently, this should both lower attrition rates and raise the rates of discovery of effective drugs substantially.

Locating sweet spots for screening hits and evaluating pan-assay interference filters from the performance analysis of two lead-like libraries

The efficiency of automated compound screening is heavily influenced by the design and the quality of the screening libraries used. We recently reported on the assembly of one diverse and one target-focused lead-like screening library. Using data from 15 enzyme-based screenings conducted using these libraries, their performance was investigated. Both libraries delivered screening hits across a range of targets, with the hits distributed across the entire chemical space represented by both libraries. On closer inspection, however, hit distribution was uneven across the chemical space, with enrichments observed in octants characterized by compounds at the higher end of the molecular weight and lipophilicity spectrum for lead-like compounds, while polar and sp³-carbon atom rich compounds were underrepresented among the screening hits. Based on these observations, we propose that screening libraries should not be evenly distributed in lead-like chemical space but be enriched in polar, aliphatic compounds. In conjunction with variable concentration screening, this could lead to more balanced hit rates across the chemical space and screening hits of higher ligand efficiency will be captured. Apart from chemical diversity, both screening libraries were shown to be clean from any pan-assay interference (PAINS) behavior. Even though some compounds were flagged to contain PAINS structural motifs, some of these motifs were demonstrated to be less problematic than previously suggested. To maximize the diversity of the chemical space sampled in a screening campaign, we therefore consider it justifiable to retain compounds containing PAINS structural motifs that were apparently clean in this analysis when assembling screening libraries.

Physicochemical and DMPK in silico models: facilitating their use by medicinal chemists

It is known that the developability of drugs is related to their physicochemical and DMPK properties. Given the time and expense involved in discovering and developing new drugs, maximizing the chance of success by calculating properties ahead of chemical synthesis and testing, and only acting on those candidates whose properties fall into a desired range, would seem to make sense. This paper provides an overview of calculable physicochemical and DMPK properties, an assessment of their relative difficulty of their calculation and accuracy, and available software. Methods companies have employed to communicate results will be discussed, including the use of composite scoring functions and ranking schemes. Calculations do no good if chemists will not use them to prioritize synthesis decisions. Strategies are presented for facilitating model usage. An approach adopted at Genentech for presenting results that involves the close coupling of property calculations with 3D structure based drug design is described.

Targeting Plasmodium falciparum Hsp90: Towards Reversing Antimalarial Resistance

Malaria continues to exact a great human toll in tropical settings. Antimalarial resistance is rife and the parasite inexorably develops mechanisms to outwit our best drugs, including the now first-line choice, artesunate. Novel strategies to circumvent resistance are needed. Here we detail drug development focusing on heat shock protein 90 and its central role as a chaperone. A growing body of evidence supports the role for Hsp90 inhibitors as adjunctive drugs able to restore susceptibility to traditionally efficacious compounds like chloroquine.

A chemogenomic analysis of ionization constants--implications for drug discovery

Chemogenomics methods seek to characterize the interaction between drugs and biological systems and are an important guide for the selection of screening compounds. The acid/base character of drugs has a profound influence on their affinity for the receptor, on their absorption, distribution, metabolism, excretion and toxicity (ADMET) profile and the way the drug can be formulated. In particular, the charge state of a molecule greatly influences its lipophilicity and biopharmaceutical characteristics. This study investigates the acid/base profile of human small-molecule drugs, chemogenomics datasets and screening compounds including a natural products set. We estimate the acid-ionization constant (pK(a)) values of these compounds and determine the identity of the ionizable functional groups in each set. We find substantial differences in acid/base profiles of the chemogenomic classes. In many cases, these differences can be linked to the nature of the target binding site and the corresponding functional groups needed for recognition of the ligand. Clear differences are also observed between the acid/base characteristics of drugs and screening compounds. For example, the proportion of drugs containing a carboxylic acid was 20 %, in stark contrast to a value of 2.4 % for the screening set sample. The proportion of aliphatic amines was 27 % for drugs and only 3.4 % for screening compounds. This suggests that there is a mismatch between commercially available screening compounds and the compounds that are likely to interact with a given chemogenomic target family. Our analysis provides a guide for the selection of screening compounds to better target specific chemogenomic families with regard to the overall balance of acids, bases and pK(a) distributions.

The significance of acid/base properties in drug discovery

While drug discovery scientists take heed of various guidelines concerning drug-like character, the influence of acid/base properties often remains under-scrutinised. Ionisation constants (pK(a) values) are fundamental to the variability of the biopharmaceutical characteristics of drugs and to underlying parameters such as logD and solubility. pK(a) values affect physicochemical properties such as aqueous solubility, which in turn influences drug formulation approaches. More importantly, absorption, distribution, metabolism, excretion and toxicity (ADMET) are profoundly affected by the charge state of compounds under varying pH conditions. Consideration of pK(a) values in conjunction with other molecular properties is of great significance and has the potential to be used to further improve the efficiency of drug discovery. Given the recent low annual output of new drugs from pharmaceutical companies, this review will provide a timely reminder of an important molecular property that influences clinical success.

A ring-distortion strategy to construct stereochemically complex and structurally diverse compounds from natural products

High-throughput screening is the dominant method used to identify lead compounds in drug discovery. As such, the makeup of screening libraries largely dictates the biological targets that can be modulated and the therapeutics that can be developed. Unfortunately, most compound-screening collections consist principally of planar molecules with little structural or stereochemical complexity, compounds that do not offer the arrangement of chemical functionality necessary for the modulation of many drug targets. Here we describe a novel, general and facile strategy for the creation of diverse compounds with high structural and stereochemical complexity using readily available natural products as synthetic starting points. We show through the evaluation of chemical properties (which include fraction of sp(3) carbons, ClogP and the number of stereogenic centres) that these compounds are significantly more complex and diverse than those in standard screening collections, and we give guidelines for the application of this strategy to any suitable natural product.

2P2Ichem: focused chemical libraries dedicated to orthosteric modulation of protein–protein interactions

Design of focused chemical libraries dedicated to protein–protein interaction targets.

What can we learn from the evolution of protein-ligand interactions to aid the design of new therapeutics?

Efforts to increase affinity in the design of new therapeutic molecules have tended to lead to greater lipophilicity, a factor that is generally agreed to be contributing to the low success rate of new drug candidates. Our aim is to provide a structural perspective to the study of lipophilic efficiency and to compare molecular interactions created over evolutionary time with those designed by humans. We show that natural complexes typically engage in more polar contacts than synthetic molecules bound to proteins. The synthetic molecules also have a higher proportion of unmatched heteroatoms at the interface than the natural sets. These observations suggest that there are lessons to be learnt from Nature, which could help us to improve the characteristics of man-made molecules. In particular, it is possible to increase the density of polar contacts without increasing lipophilicity and this is best achieved early in discovery while molecules remain relatively small.

The promiscuous binding of pharmaceutical drugs and their transporter-mediated uptake into cells: what we (need to) know and how we can do so

A recent paper in this journal sought to counter evidence for the role of transport proteins in effecting drug uptake into cells, and questions that transporters can recognize drug molecules in addition to their endogenous substrates. However, there is abundant evidence that both drugs and proteins are highly promiscuous. Most proteins bind to many drugs and most drugs bind to multiple proteins (on average more than six), including transporters (mutations in these can determine resistance); most drugs are known to recognise at least one transporter. In this response, we alert readers to the relevant evidence that exists or is required. This needs to be acquired in cells that contain the relevant proteins, and we highlight an experimental system for simultaneous genome-wide assessment of carrier-mediated uptake in a eukaryotic cell (yeast).