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.
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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.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
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.
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.
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.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
6.
The role of ligand efficiency metrics in drug discovery Hopkins, Andrew L; Keserü, György M; Leeson, Paul D ...
Nature reviews. Drug discover/Nature reviews. Drug discovery,
02/2014, Letnik:
13, Številka:
2
Journal Article, Book Review
Recenzirano
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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.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
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.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
UK Biobank is a population-based cohort of half a million participants aged 40-69 years recruited between 2006 and 2010. In 2014, UK Biobank started the world's largest multi-modal imaging study, ...with the aim of re-inviting 100,000 participants to undergo brain, cardiac and abdominal magnetic resonance imaging, dual-energy X-ray absorptiometry and carotid ultrasound. The combination of large-scale multi-modal imaging with extensive phenotypic and genetic data offers an unprecedented resource for scientists to conduct health-related research. This article provides an in-depth overview of the imaging enhancement, including the data collected, how it is managed and processed, and future directions.
Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about individual patients. In this position paper, we ...argue that the second enabling pillar towards this vision is the increasing power of computers and algorithms to learn, reason, and build the 'digital twin' of a patient. Computational models are boosting the capacity to draw diagnosis and prognosis, and future treatments will be tailored not only to current health status and data, but also to an accurate projection of the pathways to restore health by model predictions. The early steps of the digital twin in the area of cardiovascular medicine are reviewed in this article, together with a discussion of the challenges and opportunities ahead. We emphasize the synergies between mechanistic and statistical models in accelerating cardiovascular research and enabling the vision of precision medicine.
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.
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