A compound-target pairs dataset: differences between drugs, clinical candidates and other bioactive compounds.

Providing a better understanding of what makes a compound a successful drug candidate is crucial for reducing the high attrition rates in drug discovery. Analyses of the differences between active compounds, clinical candidates and drugs require high-quality datasets. However, most datasets of drug discovery programs are not openly available. This work introduces a dataset of compound-target pairs extracted from the open-source bioactivity database ChEMBL (release 32). Compound-target pairs in the dataset either have at least one measured activity or are part of the manually curated set of known interactions in ChEMBL. Known interactions between drugs or clinical candidates and targets are specifically annotated to facilitate analyses of differences between drugs, clinical candidates, and other active compounds. In total, the dataset comprises 614,594 compound-target pairs, 5,109 (3,932) of which are known interactions between drugs (clinical candidates) and targets. The extraction is performed in an automated manner and fully reproducible. We are providing not only the datasets but also the code to rerun the analyses with other ChEMBL releases.

Occurrence of "Natural Selection" in Successful Small Molecule Drug Discovery.

Published compounds from ChEMBL version 32 are used to seek evidence for the occurrence of "natural selection" in drug discovery. Three measures of natural product (NP) character were applied, to compare time- and target-matched compounds reaching the clinic (clinical compounds in phase 1-3 development and approved drugs) with background compounds (reference compounds). Pseudo-NPs (PNPs), containing NP fragments combined in ways inaccessible by nature, are increasing over time, reaching 67% of clinical compounds first disclosed since 2010. PNPs are 54% more likely to be found in post-2008 clinical versus reference compounds. The majority of target classes show increased clinical compound NP character versus their reference compounds. Only 176 NP fragments appear in >1000 clinical compounds published since 2008, yet these make up on average 63% of the clinical compound's core scaffolds. There is untapped potential awaiting exploitation, by applying nature's building blocks─"natural intelligence"─to drug design.

The Time and Place for Nature in Drug Discovery.

The case for a renewed focus on Nature in drug discovery is reviewed; not in terms of natural product screening, but how and why biomimetic molecules, especially those produced by natural processes, should deliver in the age of artificial intelligence and screening of vast collections both in vitro and in silico. The declining natural product-likeness of licensed drugs and the consequent physicochemical implications of this trend in the context of current practices are noted. To arrest these trends, the logic of seeking new bioactive agents with enhanced natural mimicry is considered; notably that molecules constructed by proteins (enzymes) are more likely to interact with other proteins (e.g., targets and transporters), a notion validated by natural products. Nature's finite number of building blocks and their interactions necessarily reduce potential numbers of structures, yet these enable expansion of chemical space with their inherent diversity of physical characteristics, pertinent to property-based design. The feasible variations on natural motifs are considered and expanded to encompass pseudo-natural products, leading to the further logical step of harnessing bioprocessing routes to access them. Together, these offer opportunities for enhancing natural mimicry, thereby bringing innovation to drug synthesis exploiting the characteristics of natural recognition processes. The potential for computational guidance to help identifying binding commonalities in the route map is a logical opportunity to enable the design of tailored molecules, with a focus on "organic/biological" rather than purely "synthetic" structures. The design and synthesis of prototype structures should pay dividends in the disposition and efficacy of the molecules, while inherently enabling greener and more sustainable manufacturing techniques.

Target-Based Evaluation of "Drug-Like" Properties and Ligand Efficiencies.

Physicochemical descriptors commonly used to define "drug-likeness" and ligand efficiency measures are assessed for their ability to differentiate marketed drugs from compounds reported to bind to their efficacious target or targets. Using ChEMBL version 26, a data set of 643 drugs acting on 271 targets was assembled, comprising 1104 drug-target pairs having ≥100 published compounds per target. Taking into account changes in their physicochemical properties over time, drugs are analyzed according to their target class, therapy area, and route of administration. Recent drugs, approved in 2010-2020, display no overall differences in molecular weight, lipophilicity, hydrogen bonding, or polar surface area from their target comparator compounds. Drugs are differentiated from target comparators by higher potency, ligand efficiency (LE), lipophilic ligand efficiency (LLE), and lower carboaromaticity. Overall, 96% of drugs have LE or LLE values, or both, greater than the median values of their target comparator compounds.

Setting Our Sights on Infectious Diseases.

In May 2019, the Wellcome Centre for Anti-Infectives Research (WCAIR) at the University of Dundee, UK, held an international conference with the aim of discussing some key questions around discovering new medicines for infectious diseases and a particular focus on diseases affecting Low and Middle Income Countries. There is an urgent need for new drugs to treat most infectious diseases. We were keen to see if there were lessons that we could learn across different disease areas and between the preclinical and clinical phases with the aim of exploring how we can improve and speed up the drug discovery, translational, and clinical development processes. We started with an introductory session on the current situation and then worked backward from clinical development to combination therapy, pharmacokinetic/pharmacodynamic (PK/PD) studies, drug discovery pathways, and new starting points and targets. This Viewpoint aims to capture some of the learnings.

Impact of Physicochemical Properties on Dose and Hepatotoxicity of Oral Drugs.

A database containing maximum daily doses of 1841 marketed oral drugs was used to examine the influence of physicochemical properties on dose and hepatotoxicity (drug induced liver injury, DILI). Drugs in the highest ∼20% dose range had significantly reduced mean lipophilicity and molecular weight, increased fractional surface area, increased % of acids, and decreased % of bases versus drugs in the lower ∼60% dose range. Drugs in the ∼20-40% dose range had intermediate mean properties, similar to the mean values for the full drug set. Drugs that are both large and highly lipophilic almost invariably do not have doses in the upper ∼20% range. The results show that oral druglike physicochemical properties are different according to these dose ranges, and this is consistent with maintenance of acceptable safety profiles as efficacious exposure increases. Verified DILI annotations from a compilation of >1000 approved drugs (Chen, M.; et al. Drug Discov. Today, 2016, 21, 648 ) were used. The drugs classified as "No DILI" ( n = 163) had significantly lower dose and lipophilicity, and higher Fsp3 (fraction of carbon atoms that are sp3 hybridized) versus the "Most DILI" ( n = 163) drugs. The percentages of acids were reduced and bases increased in the "No DILI" versus the "Most DILI" groups. Drugs classified as "Less DILI" or "Ambiguous DILI" had intermediate mean values of dose, lipophilicity, Fsp3, and % acids and bases. The impact of lipophilicity and Fsp3 on DILI increases in the upper 20% versus the lower 80% dose range, and a simple decision tree model predicted "No DILI" versus "Most DILI" outcomes with 82% accuracy. The model correctly classified 19 of 22 drugs (86%) that failed in development due to human hepatotoxicity. Because many oral drugs lacking DILI annotations are predicted to be "Most DILI", the model is best used preclinically in conjunction with experimental DILI mitigation.

Mapping the Efficiency and Physicochemical Trajectories of Successful Optimizations.

The practices and tactics employed in successful optimizations are examined, judged from the trajectories of ligand efficiency and property evolution. A wide range of targets is analyzed, encompassing a variety of hit finding methods (HTS, fragments, encoded library technology) and types of molecules, including those beyond the rule of five. The wider employment of efficiency metrics and lipophilicity control is evident in contemporary practice and the impact on quality demonstrable. What is clear is that while targets are different, successful molecules are almost invariably among the most efficient for their target, even at the extremes. Trajectory mapping, based on principles rather than rules, is useful in assessing quality and progress in optimizations while benchmarking against competitors and assessing property-dependent risks.

Quality guidelines for oral drug candidates: dose, solubility and lipophilicity.

In an attempt to seek increased understanding of compound attributes that influence successful drug pipeline progression, GlaxoSmithKline's portfolio of oral candidates was compared with reference sets of marketed oral drugs. The approach differs from other attrition studies by explicitly focusing on choosing 'the right compound' by applying relevant, experimentally derived properties. The analysis led to four proposed compound quality categories, created by combining specific criteria for three measures: dose, solubility and the property forecast index, a composite measure of lipophilicity using chromatographically determined LogD and aromaticity. The 'three properties' provide benchmarked guidelines for project teams to use when seeking and selecting clinical candidates, because they reflect the property distribution of marketed oral drugs.

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.

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.

Validity of ligand efficiency metrics.

A recent viewpoint article (Improving the plausibility of success with inefficient metrics. ACS Med. Chem. Lett. 2014, 5, 2-5) argued that the standard definition of ligand efficiency (LE) is mathematically invalid. In this viewpoint, we address this criticism and show categorically that the definition of LE is mathematically valid. LE and other metrics such as lipophilic ligand efficiency (LLE) can be useful during the multiparameter optimization challenge faced by medicinal chemists.

The role of ligand efficiency metrics in drug discovery.

The judicious application of ligand or binding efficiency metrics, which quantify the molecular properties required to obtain binding affinity for a drug target, is gaining traction in the selection and optimization of fragments, hits and leads. Retrospective analysis of recently marketed oral drugs shows that they frequently have highly optimized ligand efficiency values for their targets. Optimizing ligand efficiency metrics based on both molecular mass and lipophilicity, when set in the context of the specific target, has the potential to ameliorate the inflation of these properties that has been observed in current medicinal chemistry practice, and to increase the quality of drug candidates.

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

Physicochemical properties such as lipophilicity and molecular mass are known to have an important influence on the absorption, distribution, metabolism, excretion and toxicity (ADMET) profile of small-molecule drug candidates. To assess the use of this knowledge in reducing the likelihood of compound-related attrition, the molecular properties of compounds acting at specific drug targets described in patents from leading pharmaceutical companies during the 2000-2010 period were analysed. Over the past decade, there has been little overall change in properties that influence ADMET outcomes, but there are marked differences in molecular properties between organizations, which are maintained when the targets pursued are taken into account. The target-unbiased molecular property differences, which are attributable to divergent corporate drug design strategies, are comparable to the differences between the major drug target classes. On the basis of our analysis, we conclude that a substantial sector of the pharmaceutical industry has not modified its drug design practices and is still producing compounds with suboptimal physicochemical profiles.

Strategies to improve in vivo toxicology outcomes for basic candidate drug molecules.

A valid PLS-DA model to predict attrition in pre-clinical toxicology for basic oral candidate drugs was built. A combination of aromatic/aliphatic balance, flatness, charge distribution and size descriptors helped predict the successful progression of compounds through a wide range of toxicity testing. Eighty percent of an independent test set of marketed post-2000 basic drugs could be successfully classified using the model, indicating useful forward predictivity. The themes within this work provide additional guidance for medicinal design chemists and complement other literature property guidelines.

The discovery of novel, potent and highly selective inhibitors of inducible nitric oxide synthase (iNOS).

By careful analysis of experimental X-ray ligand crystallographic protein data across several inhibitor series we have discovered a novel, potent and selective series of iNOS inhibitors exemplified by compound 8.

Lessons learned from candidate drug attrition.

Rising expenditure in pharmaceutical R&D has not been matched by increased productivity. There is an urgent need to solve the current high levels of pipeline attrition. Changing the current failed model of drug discovery and development, in which high numbers of candidate drugs are produced and high attrition is accepted, is essential. A different model is needed, in which the focus shifts to identifying better-quality candidate drugs that allow scientifically robust testing of disease and targets in humans. Lowering the risks of compound-based attrition in small-molecule drug discovery and development (ie, addressing toxicity, specificity, potency, duration and exposure) is achievable by improved control of physical properties and by setting more demanding candidate criteria. Separating the key scientific experiment--proof-of-concept clinical trials in humans--from commercial development imperatives is a necessary step for the industry.

The influence of drug-like concepts on decision-making in medicinal chemistry.

The application of guidelines linked to the concept of drug-likeness, such as the 'rule of five', has gained wide acceptance as an approach to reduce attrition in drug discovery and development. However, despite this acceptance, analysis of recent trends reveals that the physical properties of molecules that are currently being synthesized in leading drug discovery companies differ significantly from those of recently discovered oral drugs and compounds in clinical development. The consequences of the marked increase in lipophilicity--the most important drug-like physical property--include a greater likelihood of lack of selectivity and attrition in drug development. Tackling the threat of compound-related toxicological attrition needs to move to the mainstream of medicinal chemistry decision-making.

From ATP to AZD6140: the discovery of an orally active reversible P2Y12 receptor antagonist for the prevention of thrombosis.

Starting from adenosine triphosphate (ATP), the identification of a novel series of P2Y(12) receptor antagonists and exploitation of their SAR is described. Modifications of the acidic side chain and the purine core and investigation of hydrophobic substituents led to a series of neutral molecules. The leading compound, 17 (AZD6140), is currently in a large phase III clinical trial for the treatment of acute coronary syndromes and prevention of thromboembolic clinical sequelae.

Time-related differences in the physical property profiles of oral drugs.

Comparisons of the calculated physicochemical properties of oral drugs launched prior to 1983 (864 drugs) and between 1983 and 2002 (329 drugs) show that mean values of lipophilicity, percent polar surface area and H-bond donor count are the same, suggesting that these are the most important oral druglike physical properties. In contrast, mean values of molecular weight and the numbers of O + N atoms, H-bond acceptors, and rotatable bonds and rings have increased in 1983-2002 drugs (by 13-29%). Analysis of the 1983-2002 oral drugs by therapy area shows that antiinfectives and nervous system drugs have the most extreme physical property profiles. Cardiovascular drugs show increasing molecular weight with year of publication, primarily a consequence of focusing on clinically proven mechanisms, with limited chemical diversity. Drug classes other than antiinfectives show comparable distributions of lipophilicity, suggesting that this property in oral drugs is important irrespective of the drug's target. The results suggest that the balance between polar and nonpolar drug properties is an important, unchanging feature of oral drug molecules.