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The influence of lead discovery strategies on the properties of drug candidates

Key Points

  • For several years, the pharmaceutical industry has been suffering from a shortfall of approved new chemical entities. Differences in the physicochemical properties of recent leads and clinical candidates compared with those of historical leads and approved drugs are thought to have a major impact on compound-related attrition in clinical trials.

  • In this article, the physicochemical profiles of hits are compared with the profiles of the corresponding leads that have evolved from them via hit-to-lead optimization. The hit–lead pairs are classified by the hit discovery strategy such as high-throughput screening (HTS), fragment-based hit discovery, virtual screening and natural product based screening.

  • On average, HTS, fragment and natural product hits have similar ligand efficiency but HTS hits achieve this primarily via lipophilicity, whereas fragment and natural product hits achieve this via good complementarity and balanced properties. Therefore, fragment-based and natural product hits could be considered to be the preferred starting points over HTS hits.

  • Our data suggest that it is highly challenging to progress HTS hits while maintaining or reducing logP, and that non-HTS hits become lipophilic leads, indicating that most of the gain in potency during hit-to-lead optimization is reached via extending the molecules with hydrophobic moieties.

  • Fragment-derived leads seem similar to those derived from HTS, suggesting that the hit-to-lead optimization process has a major role in the poor physicochemical properties of candidates.

  • The statistical data suggest that the benefits of using HTS alternatives for hit discovery do not include improved leads or more efficient leads, but only novel starting points by accessing uncharted chemical space.

  • We propose that a paradigm shift towards giving more resources to interdisciplinary hit-to-lead optimization teams may bring about a more productive hit evolution process starting from hit discovery to the clinic.

Abstract

Despite the widespread acceptance of guidelines related to desirable physicochemical properties of potential small-molecule drugs, key properties — such as lipophilicity — of recently developed clinical candidates and advanced lead compounds have been shown to differ significantly from those of historical leads and drugs. By analysing the physicochemical properties of a large database of hits and corresponding leads identified in the past decade, we show that this undesirable phenomenon can be traced back to the nature of high-throughput screening hits and hit-to-lead optimization practices. Conceptual and organizational adjustments may be required to enable a smooth lead-evolution process that reduces the chance of high compound-related attrition in clinical trials.

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Figure 1: Averaged properties of hits and leads.
Figure 2: Lead classes (bottom) originated and developed from screening hits (top) against β-site amyloid precursor protein cleaving enzyme 1 (BACE1).
Figure 3: Distribution of hits and leads developed against β-site amyloid precursor protein cleaving enzyme 1 (BACE1) in property space defined by logP and ligand efficiency (LE).
Figure 4: LELP of hits and leads.
Figure 5: Distribution of ligand efficiency (LE) versus number of heavy atoms (Nheavy) for the different hit and lead classes.
Figure 6: Distribution of average hits and leads classified by the different lead identification methods.

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Acknowledgements

The authors are grateful to R. Kiss and L. Molnár for their help with compiling the hit-to-lead database, and to M. Hann (GlaxoSmithKline) and T. Oprea (University of New Mexico, USA) for kindly providing their lead-to-drug databases for comparison.

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Correspondence to György M. Keserü.

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Glossary

Cluster

A hit cluster includes molecules that are related by either visual inspection or a computed similarity measure.

Singleton

A small-molecule hit that is unique (that is, a cluster of one) by either visual inspection or a computed similarity measure.

Drug-like

Similar to drugs. A term typically used for small molecules that resemble oral drugs (that is, do not have undesirable moieties) and have properties that do not violate Lipinski's rules.

pPotency

pPotency is −log(potency), in which potency is either a measure of binding (Kd) or biological activity (Ki, IC50 or EC50).

Andrews' binding energy

An estimated binding energy a small molecule would establish with a hypothetical macromolecule partner if all functional groups contributed to binding. Average functional group contributions to binding were calculated by Andrews (applying a training set of 200 drugs) using a formula that includes correction for entropy.

Heavy atom

An atom other than hydrogen in small molecules that are relevant for drug discovery.

Polar surface area

Usually defined as the surface sum over all polar atoms (usually oxygen and nitrogen), which also includes attached hydrogens.

Rotors

Rotatable bonds in molecules: acyclic single bonds that do not have significantly restricted rotational freedom (that is, a secondary amide bond is not a rotatable bond). Different software packages have various levels of sophistication in identifying rotatable bonds, and often the number of rotors simply equals the number of acyclic single bonds.

Veber's criteria

GlaxoSmithKline's database of 1,100 molecules with oral bioavailability measurements in rats was used by Veber et al. to find that a polar surface area of ≤140 Å2 (or the sum of hydrogen-bond donors and acceptors of ≤12) and a number of rotatable bonds of ≤10 is sufficient to predict oral bioavailability.

Lipinski's rules

Four criteria identified by Lipinski et al. to be relevant for oral bioavailability: molecular mass <500 Da, number of hydrogen-bond acceptors <10, number of hydrogen-bond donors <5 and clogP <5.

Lead-like

Similar to leads. A term typically used for small molecules that resemble leads that could historically be developed into oral drugs. Actual criteria vary but typically lead-like molecules do not have undesirable moieties and have properties that do not violate a stricter version of Lipinski's rules such as molecular mass <350 Da and logP <3.

Rule-of-three

Criteria proposed to describe fragments suitable for biophysical screening: molecular mass <300 Da, logP ≤3, the number of hydrogen-bond acceptors ≤3 and the number of hydrogen-bond donors ≤3.

Ligand efficiency

A measure proposed to quantify the average contribution of a heavy atom to binding (Gibb's free energy divided by the number of heavy atoms). Originally intended to be used with Kd but since has often been applied to any measure of potency.

Tanimoto distance

Molecular similarity as measured by the Tanimoto coefficient: T = c/(a + b + c), where c is the number of common bits, and a and b are the number of unique bits in molecule_a and molecule_b using a molecular fingerprint. The more similar two molecules are, the closer the Tanimoto distance is to 1. Typically, a Tanimoto coefficient >0.85 is considered highly similar and coefficient >0.75 is considered similar for the purpose of clustering molecules that may have similar biological activity profiles.

Hit-to-lead programmes

Viable leads delivered by successful hit-to-lead programmes fulfil a set of programme-dependent predefined criteria that typically include, but are not limited to, potency, selectivity, structure–activity relationships, physicochemical properties, metabolic stability, pharmacokinetics, and cytochrome P450 and hERG profiles.

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Keserü, G., Makara, G. The influence of lead discovery strategies on the properties of drug candidates. Nat Rev Drug Discov 8, 203–212 (2009). https://doi.org/10.1038/nrd2796

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