Defining Desirable Central Nervous System Drug Space through the Alignment of Molecular Properties, in Vitro ADME, and Safety Attributes
TL;DR: A thorough analysis of properties for 119 marketed CNS drugs and a set of 108 Pfizer CNS candidates focused on understanding the relationships between physicochemical properties, in vitro ADME attributes, primary pharmacology binding efficiencies, and in vitro safety data.
Abstract: As part of our effort to increase survival of drug candidates and to move our medicinal chemistry design to higher probability space for success in the Neuroscience therapeutic area, we embarked on a detailed study of the property space for a collection of central nervous system (CNS) molecules. We carried out a thorough analysis of properties for 119 marketed CNS drugs and a set of 108 Pfizer CNS candidates. In particular, we focused on understanding the relationships between physicochemical properties, in vitro ADME (absorption, distribution, metabolism, and elimination) attributes, primary pharmacology binding efficiencies, and in vitro safety data for these two sets of compounds. This scholarship provides guidance for the design of CNS molecules in a property space with increased probability of success and may lead to the identification of druglike candidates with favorable safety profiles that can successfully test hypotheses in the clinic.
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TL;DR: The utility of QED is extended by applying it to the problem of molecular target druggability assessment by prioritizing a large set of published bioactive compounds and may also capture the abstract notion of aesthetics in medicinal chemistry.
Abstract: Drug-likeness is a key consideration when selecting compounds during the early stages of drug discovery. However, evaluation of drug-likeness in absolute terms does not reflect adequately the whole spectrum of compound quality. More worryingly, widely used rules may inadvertently foster undesirable molecular property inflation as they permit the encroachment of rule-compliant compounds towards their boundaries. We propose a measure of drug-likeness based on the concept of desirability called the quantitative estimate of drug-likeness (QED). The empirical rationale of QED reflects the underlying distribution of molecular properties. QED is intuitive, transparent, straightforward to implement in many practical settings and allows compounds to be ranked by their relative merit. We extended the utility of QED by applying it to the problem of molecular target druggability assessment by prioritizing a large set of published bioactive compounds. The measure may also capture the abstract notion of aesthetics in medicinal chemistry.
1,161 citations
TL;DR: Optimize 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.
Abstract: 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.
797 citations
TL;DR: Based on six physicochemical properties commonly used by medicinal chemists, the CNS MPO function may be used prospectively at the design stage to accelerate the identification of compounds with increased probability of success.
Abstract: The interplay among commonly used physicochemical properties in drug design was examined and utilized to create a prospective design tool focused on the alignment of key druglike attributes. Using a set of six physicochemical parameters ((a) lipophilicity, calculated partition coefficient (ClogP); (b) calculated distribution coefficient at pH = 7.4 (ClogD); (c) molecular weight (MW); (d) topological polar surface area (TPSA); (e) number of hydrogen bond donors (HBD); (f) most basic center (pKa)), a druglikeness central nervous system multiparameter optimization (CNS MPO) algorithm was built and applied to a set of marketed CNS drugs (N = 119) and Pfizer CNS candidates (N = 108), as well as to a large diversity set of Pfizer proprietary compounds (N = 11 303). The novel CNS MPO algorithm showed that 74% of marketed CNS drugs displayed a high CNS MPO score (MPO desirability score ≥ 4, using a scale of 0−6), in comparison to 60% of the Pfizer CNS candidates. This analysis suggests that this algorithm could p...
713 citations
TL;DR: This work comprehensively analyzed drugs and clinical candidates with molecular weight (MW) > 500 Da and concluded that oral drugs are found far from the Ro5 and properties such as intramolecular hydrogen bonding, macrocyclization, dosage, and formulations can be used to improve bRo5 bioavailability.
476 citations
Cites background from "Defining Desirable Central Nervous ..."
...CNS penetration typically requires more stringent properties, for example, PSA % 90 Å2, MW % 450 Da, HBD % 3 (Ghose et al., 2012; Wager et al., 2010)....
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...…with absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters (Egan et al., 2000; Ghose et al., 2012; Gleeson, 2008; Guimarães et al., 2012; Johnson et al., 2009; Lajiness et al., 2004;Meanwell, 2011; Veber et al., 2002;Wager et al., 2010; Waring, 2009; Yang et al., 2012)....
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TL;DR: To be successful during the lead optimization phase, drug candidate identification programs will need to adopt a holistic approach that integrates multiple parameters, many of which will have unique dependencies on both the drug target and the specific chemotype under prosecution.
Abstract: The development of small molecule drug candidates from the discovery phase to a marketed product continues to be a challenging enterprise with very low success rates that have fostered the perception of poor productivity by the pharmaceutical industry. Although there have been significant advances in preclinical profiling that have improved compound triaging and altered the underlying reasons for compound attrition, the failure rates have not appreciably changed. As part of an effort to more deeply understand the reasons for candidate failure, there has been considerable interest in analyzing the physicochemical properties of marketed drugs for the purpose of comparing with drugs in discovery and development as a means capturing recent trends in drug design. The scenario that has emerged is one in which contemporary drug discovery is thought to be focused too heavily on advancing candidates with profiles that are most easily satisfied by molecules with increased molecular weight and higher overall lipophilicity. The preponderance of molecules expressing these properties is frequently a function of increased aromatic ring count when compared with that of the drugs launched in the latter half of the 20th century and may reflect a preoccupation with maximizing target affinity rather than taking a more holistic approach to drug design. These attributes not only present challenges for formulation and absorption but also may influence the manifestation of toxicity during development. By providing some definition around the optimal physicochemical properties associated with marketed drugs, guidelines for drug design have been developed that are based largely on calculated parameters and which may readily be applied by medicinal chemists as an aid to understanding candidate quality. The physicochemical properties of a molecule that are consistent with the potential for good oral absorption were initially defined by Lipinski, with additional insights allowing further refinement, while deeper analyses have explored the correlation with metabolic stability and toxicity. These insights have been augmented by careful analyses of physicochemical aspects of drug-target interactions, with thermodynamic profiling indicating that the signature of best-in-class drugs is a dependence on enthalpy to drive binding energetics rather than entropy, which is dependent on lipophilicity. Optimization of the entropic contribution to the binding energy of a ligand to its target is generally much easier than refining the enthalpic element. Consequently, in the absence of a fundamental understanding of the thermodynamic complexion of an interaction, the design of molecules with increased lipophilicity becomes almost inevitable. The application of ligand efficiency, a measure of affinity per heavy atom, group efficiency, which assesses affinity in the context of structural changes, and lipophilic ligand efficiency, which relates potency to lipophilicity, offer less sophisticated but practically useful analytical algorithms to assess the quality of drug-target interactions. These parameters are readily calculated and can be applied to lead optimization programs in a fashion that helps to maximize potency while minimizing the kind of lipophilic burden that has been dubbed "molecular obesity". Several recently described lead optimization campaigns provide illustrative, informative, and productive examples of the effect of paying close attention to carefully controlling physicochemical properties by monitoring ligand efficiency and lipophilic ligand efficiency. However, to be successful during the lead optimization phase, drug candidate identification programs will need to adopt a holistic approach that integrates multiple parameters, many of which will have unique dependencies on both the drug target and the specific chemotype under prosecution. Nevertheless, there are many important drug targets that necessitate working in space beyond that which has been defined by the retrospective analyses of marketed drugs and which will require adaptation of some of the guideposts that are useful in directing lead optimization.
426 citations
References
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TL;DR: Experimental and computational approaches to estimate solubility and permeability in discovery and development settings are described in this article, where the rule of 5 is used to predict poor absorption or permeability when there are more than 5 H-bond donors, 10 Hbond acceptors, and the calculated Log P (CLogP) is greater than 5 (or MlogP > 415).
14,026 citations
TL;DR: Reduced molecular flexibility, as measured by the number of rotatable bonds, and low polar surface area or total hydrogen bond count are found to be important predictors of good oral bioavailability, independent of molecular weight.
Abstract: Oral bioavailability measurements in rats for over 1100 drug candidates studied at SmithKline Beecham Pharmaceuticals (now GlaxoSmithKline) have allowed us to analyze the relative importance of molecular properties considered to influence that drug property. Reduced molecular flexibility, as measured by the number of rotatable bonds, and low polar surface area or total hydrogen bond count (sum of donors and acceptors) are found to be important predictors of good oral bioavailability, independent of molecular weight. That on average both the number of rotatable bonds and polar surface area or hydrogen bond count tend to increase with molecular weight may in part explain the success of the molecular weight parameter in predicting oral bioavailability. The commonly applied molecular weight cutoff at 500 does not itself significantly separate compounds with poor oral bioavailability from those with acceptable values in this extensive data set. Our observations suggest that compounds which meet only the two cr...
5,191 citations
TL;DR: The pharmaceutical industry faces considerable challenges, both politically and fiscally, and the fiscal pressures that face the industry from the perspective of R&D are dealt with.
Abstract: The pharmaceutical industry faces considerable challenges, both politically and fiscally. Politically, governments around the world are trying to contain costs and, as health care budgets constitute a very significant part of governmental spending, these costs are the subject of intense scrutiny. In the United States, drug costs are also the subject of intense political discourse. This article deals with the fiscal pressures that face the industry from the perspective of R&D. What impinges on productivity? How can we improve current reduced R&D productivity?
3,746 citations
TL;DR: The method, termed topological PSA (TPSA), provides results which are practically identical with the 3D PSA, while the computation speed is 2-3 orders of magnitude faster and may be used for fast bioavailability screening of virtual libraries having millions of molecules.
Abstract: Molecular polar surface area (PSA), i.e., surface belonging to polar atoms, is a descriptor that was shown to correlate well with passive molecular transport through membranes and, therefore, allows prediction of transport properties of drugs. The calculation of PSA, however, is rather time-consuming because of the necessity to generate a reasonable 3D molecular geometry and the calculation of the surface itself. A new approach for the calculation of the PSA is presented here, based on the summation of tabulated surface contributions of polar fragments. The method, termed topological PSA (TPSA), provides results which are practically identical with the 3D PSA (the correlation coefficient between 3D PSA and fragment-based TPSA for 34 810 molecules from the World Drug Index is 0.99), while the computation speed is 2-3 orders of magnitude faster. The new methodology may, therefore, be used for fast bioavailability screening of virtual libraries having millions of molecules. This article describes the new methodology and shows the results of validation studies based on sets of published absorption data, including intestinal absorption, Caco-2 monolayer penetration, and blood-brain barrier penetration.
2,400 citations
TL;DR: 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.
Abstract: 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.
1,954 citations