Ligand efficiency metrics in drug discovery: the pros and cons from a practical perspective

Human ether-à-go-go-related potassium channel: exploring SAR to improve drug design

hERG is best known as a primary anti-target, the inhibition of which is responsible for serious side effects. A renewed interest in hERG as a desired target, especially in oncology, was sparked because of its role in cellular proliferation and apoptosis. In this study, we survey the most recent advances regarding hERG by focusing on SAR in the attempt to elucidate, at a molecular level, off-target and on-target actions of potential hERG binders, which are highly promiscuous and largely varying in structure. Understanding the rationale behind hERG interactions and the molecular determinants of hERG activity is a real challenge and comprehension of this is of the utmost importance to prioritize compounds in early stages of drug discovery and to minimize cardiotoxicity attrition in preclinical and clinical studies.

Medicines discovery for auditory disorders: Challenges for industry

Currently, no approved medicines are available for the prevention or treatment of hearing loss. Pharmaceutical industry productivity across all therapeutic indications has historically been disappointing, with a 90% chance of failure in delivering a marketed drug after entering clinical evaluation. To address these failings, initiatives have been applied in the three cornerstones of medicine discovery: target selection, clinical candidate selection, and clinical studies. These changes aimed to enable data-informed decisions on the translation of preclinical observations into a safe, clinically effective medicine by ensuring the best biological target is selected, the most appropriate chemical entity is advanced, and that the clinical studies enroll the correct patients. The specific underlying pathologies need to be known to allow appropriate patient selection, so improved diagnostics are required, as are methodologies for measuring in the inner ear target engagement, drug delivery and pharmacokinetics. The different therapeutic strategies of protecting hearing or preventing hearing loss versus restoring hearing are reviewed along with potential treatments for tinnitus. Examples of current investigational drugs are discussed to highlight key challenges in drug discovery and the learnings being applied to improve the probability of success of launching a marketed medicine.

The Symbiotic Relationship Between Drug Discovery and Organic Chemistry

All pharmaceutical products contain organic molecules; the source may be a natural product or a fully synthetic molecule, or a combination of both. Thus, it follows that organic chemistry underpins both existing and upcoming pharmaceutical products. The reverse relationship has also affected organic synthesis, changing its landscape towards increasingly complex targets. This Review article sets out to give a concise appraisal of this symbiotic relationship between organic chemistry and drug discovery, along with a discussion of the design concepts and highlighting key milestones along the journey. In particular, criteria for a high-quality compound library design enabling efficient virtual navigation of chemical space, as well as rise and fall of concepts for its synthetic exploration (such as combinatorial chemistry; diversity-, biology-, lead-, or fragment-oriented syntheses; and DNA-encoded libraries) are critically surveyed.

KRAS Binders Hidden in Nature

Natural products have proven to be a rich source of molecular architectures for drugs. Here, an integrated approach to natural product screening is proposed, which uncovered eight new natural product scaffolds for KRAS-the most frequently mutated oncogenic driver in human cancers, which has remained thus far undrugged. The approach combines aspects of virtual screening, fragment-based screening, structure-activity relationships (SAR) by NMR, and structure-based drug discovery to overcome the limitations in traditional natural product approaches. By using our approach, a new "snugness of fit" scoring function and the first crystal-soaking system of the active form of KRASG12D , the protein-ligand X-ray structures of a tricyclic indolopyrrole fungal alkaloid and an indoloisoquinolinone have been successfully elucidated. The natural product KRAS hits discovered provide fruitful ground for the optimization of highly potent natural-product-based inhibitors of the active form of oncogenic RAS. This integrated approach for screening natural products also holds promise for other "undruggable" targets.

Pushing the Ligand Efficiency Metrics: Relative Group Contribution (RGC) Model as a Helpful Strategy to Promote a Fragment "Rescue" Effect

The ligand efficiency (LE) indexes have long been used as decision-making criteria in drug discovery and development. However, in the context of fragment-based drug design (FBDD), these metrics often exhibit a strong emphasis toward the selection of highly efficient “core” fragments for potential optimization, which are not usually considered as parts of a larger molecule with a size typical for a drug. In this study, we present a relative group contribution (RGC) model intended to predict the efficiency of a drug-sized compound in terms of its component fragments. This model could be useful not only in rapidly predicting all the possible combinations of promising fragments from an earlier hit discovery stage, but also in enabling a relatively low-LE fragment to become part of a drug-sized compound as long as it is “rescued” by other high-LE fragments.

Homology models of mouse and rat estrogen receptor-α ligand-binding domain created by in silico mutagenesis of a human template: molecular docking with 17ß-estradiol, diethylstilbestrol, and paraben analogs

Crystal structures exist for human, but not rodent, estrogen receptor-α ligand-binding domain (ERα-LBD). Consequently, rodent studies involving binding of compounds to ERα-LBD are limited in their molecular-level interpretation and extrapolation to humans. Because the sequences of rodent and human ERα-LBDs are > 95% identical, we expected their 3D structures and ligand binding to be highly similar. To test this hypothesis, we used the human ERα-LBD structure (PDB 3UUD) as a template to produce rat and mouse homology models. Employing the rodent models and human structure, we generated docking poses of 23 Group A ligands (17ß-estradiol, diethylstilbestrol, and 21 paraben analogs) in AutoDock Vina for interspecies comparisons. Ligand RMSDs (Å) (median, 95% CI) were 0.49 (0.21-1.82) (human-mouse) and 1.19 (0.22-1.82) (human-rat), well below the 2.0-2.5 Å range for equivalent docking poses. Numbers of interspecies ligand-receptor residue contacts were highly similar, with Sorensen Sc (%) = 96.8 (90.0-100) (human-mouse) and 97.7 (89.5-100) (human-rat). Likewise, numbers of interspecies ligand-receptor residue contacts were highly correlated: Pearson r = 0.913 (human-mouse) and 0.925 (human-rat). Numbers of interspecies ligand-receptor atom contacts were even more tightly correlated: r = 0.979 (human-mouse) and 0.986 (human-rat). Pyramid plots of numbers of ligand-receptor atom contacts by residue exhibited high interspecies symmetry and had Spearman r s = 0.977 (human-mouse) and 0.966 (human-rat). Group B ligands included 15 ring-substituted parabens recently shown experimentally to exhibit decreased binding to human ERα and to exert increased antimicrobial activity. Ligand efficiencies calculated from docking ligands into human ERα-LBD were well correlated with those derived from published experimental data (Pearson partial r p = 0.894 and 0.918; Groups A and B, respectively). Overall, the results indicate that our constructed rodent ERα-LBDs interact with ligands in like manner to the human receptor, thus providing a high level of confidence in extrapolations of rodent to human ligand-receptor interactions.

Targeting ERK1/2 protein-serine/threonine kinases in human cancers

ERK1 and ERK2 are key protein kinases that contribute to the Ras-Raf-MEK-ERK MAP kinase signalling module. This pathway participates in the control of numerous processes including apoptosis, cell proliferation, the immune response, nervous system function, and RNA synthesis and processing. MEK1/2 activate human ERK1/2 by first catalyzing the phosphorylation of Y204/187 and then T202/185, both residues of which occur within the activation segment. The phosphorylation of both residues is required for enzyme activation. The only Raf substrates are MEK1/2 and the only MEK1/2 substrates are ERK1/2. In contrast, ERK1/2 catalyze the phosphorylation of many cytoplasmic and nuclear substrates including transcription factors and regulatory molecules. The linear MAP kinase pathway branches extensively at the ERK1/2 node. ERK1/2 are proline-directed kinases that preferentially catalyze the phosphorylation of substrates containing a PxS/TP sequence. The dephosphorylation and inactivation of ERK1/2 is catalyzed by dual specificity phosphatases, protein-tyrosine specific phosphatases, and protein-serine/threonine phosphatases. The combined functions of kinases and phosphatases make the overall process reversible. To provide an idea of the complexities involved in these reactions, somatic cell cycle progression involves the strict timing of more than 32,000 phosphorylation and dephosphorylation events as determined by mass spectrometry. The MAP kinase cascade is perhaps the most important oncogenic driver of human cancers and the blockade of this signalling module by targeted inhibitors is an important anti-tumor strategy. Although numerous cancers are driven by MAP kinase pathway activation, thus far the only orally effective approved drugs that target this signaling module are used for the treatment of BRAF-mutant melanomas. The best treatments include the combination of B-Raf and MEK inhibitors (dabrafenib and trametinib, encorafenib and binimetinib, vemurafenib and cobimetanib). However, resistance to these antagonists occurs within one year and additional treatment options are necessary. Owing to the large variety of malignancies that are driven by dysregulation of the MAP kinase pathway, additional tumor types should be amenable to MAP kinase pathway inhibitor therapy. In addition to new B-Raf and MEK inhibitors, the addition of ERK inhibitors should prove helpful. Ulixertinib, MK-8353, and GDC-0994 are orally effective, potent, and specific inhibitors of ERK1/2 that are in early clinical trials for the treatment of various advanced/metastatic solid tumors. These agents are effective against cell lines that are resistant to B-Raf and MEK1/2 inhibitor therapy. Although MK-8353 does not directly inhibit MEK1/2, it decreases the phosphorylation of ERK1/2 as well as the phosphorylation of RSK, an ERK1/2 substrate. The decrease in RSK phosphorylation appears to be a result of ERK inhibition and the decrease in ERK1/2 phosphorylation is related to the inability of MEK to catalyze the phosphorylation of the ERK-MK-8353 complex; these decreases characterize the ERK dual mechanism inhibition paradigm. Additional work will be required to determine whether ERK inhibitors will be successful in the clinic and are able to forestall the development of drug resistance of the MAP kinase pathway.

The nature of ligand efficiency

Ligand efficiency is a widely used design parameter in drug discovery. It is calculated by scaling affinity by molecular size and has a nontrivial dependency on the concentration unit used to express affinity that stems from the inability of the logarithm function to take dimensioned arguments. Consequently, perception of efficiency varies with the choice of concentration unit and it is argued that the ligand efficiency metric is not physically meaningful nor should it be considered to be a metric. The dependence of ligand efficiency on the concentration unit can be eliminated by defining efficiency in terms of sensitivity of affinity to molecular size and this is illustrated with reference to fragment-to-lead optimizations. Group efficiency and fit quality are also examined in detail from a physicochemical perspective. The importance of examining relationships between affinity and molecular size directly is stressed throughout this study and an alternative to ligand efficiency for normalization of affinity with respect to molecular size is presented.

Synthesis, In Silico, and In Vitro Evaluation of Long Chain Alkyl Amides from 2-Amino-4-Quinolone Derivatives as Biofilm Inhibitors

Infection from multidrug resistant bacteria has become a growing health concern worldwide, increasing the need for developing new antibacterial agents. Among the strategies that have been studied, biofilm inhibitors have acquired relevance as a potential source of drugs that could act as a complement for current and new antibacterial therapies. Based on the structure of 2-alkyl-3-hydroxy-4-quinolone and N-acylhomoserine lactone, molecules that act as mediators of quorum sensing and biofilm formation in Pseudomonas aeruginosa, we designed, prepared, and evaluated the biofilm inhibition properties of long chain amide derivatives of 2-amino-4-quinolone in Staphylococcus aureus and P. aeruginosa. All compounds had higher biofilm inhibition activity in P. aeruginosa than in S. aureus. Particularly, compounds with an alkyl chain of 12 carbons exhibited the highest inhibition of biofilm formation. Docking scores and molecular dynamics simulations of the complexes of the tested compounds within the active sites of proteins related to quorum sensing had good correlation with the experimental results, suggesting the diminution of biofilm formation induced by these compounds could be related to the inhibition of these proteins.

(Chlorosulfonyl)benzenesulfonyl Fluorides-Versatile Building Blocks for Combinatorial Chemistry: Design, Synthesis and Evaluation of a Covalent Inhibitor Library

Multigram synthesis of (chlorosulfonyl)benzenesulfonyl fluorides is described. Selective modification of these building blocks at the sulfonyl chloride function under parallel synthesis conditions is achieved. It is shown that the reaction scope includes the use of (hetero)aromatic and electron-poor aliphatic amines (e.g., amino nitriles). Utility of the method is demonstrated by preparation of the sulfonyl fluoride library for potential use as covalent fragments, which is demonstrated by a combination of in silico and in vitro screening against trypsin as a model enzyme. As a result, several inhibitors were identified with activity on par with that of the known inhibitor.

Synthesis of Jacaranone-Derived Nitrogenous Cyclohexadienones and Their Antiproliferative and Antiprotozoal Activities

The cytotoxic and antiprotozoal activities of the phytoquinoide, jacaranone, and related compounds have been an ongoing topic in recent drug discovery. Starting from the natural product-derived cyclohexadienone scaffold, a series of nitrogen-containing derivatives were synthesized and subsequently evaluated for their antiproliferative and antiprotozoal activity. Anticancer potency was analyzed using different types of cancer cell lines: MDA-MB-231 breast cancer, CCRF-CEM leukemia, HCT-116 colon cancer, U251 glioblastoma, and, in addition, non-tumorigenic MRC-5 lung fibroblasts. Antiproliferative activities at micromolar concentrations could be shown. Antiprotozoal activity was assessed against Plasmodium falciparum NF54 and Trypanosoma brucei rhodesiense STIB900. For all compounds, selectivity indices (SI) were calculated based on assessed cytotoxicity towards L6 cells. In addition, the structure-activity-relationships and physicochemical parameters of these compounds are discussed.

In silico fragment-based drug design with SEED

We report on two fragment-based drug design protocols, SEED2XR and ALTA, which start by high-throughput docking. SEED2XR is a two-stage protocol for fragment-based drug design. The first stage is in silico and consists of the automatic docking of 10³-10⁴ fragments using SEED, which requires about 1 s per fragment. SEED is a docking software developed specifically for fragment docking and binding energy evaluation by a force field with implicit solvent. In the second stage of SEED2XR, the 10-10² fragments with the most favorable predicted binding energies are validated by protein X-ray crystallography. The recent applications of SEED2XR to bromodomains demonstrate that the whole SEED2XR protocol can be carried out in about a week of working time, with hit rates ranging from 10% to 40%. Information on fragment-target interactions generated by the SEED2XR protocol or directly from SEED docking has been used for the discovery of hundreds of hits. ALTA is a computational protocol for screening which identifies candidate ligands that preserve the interactions between the optimal SEED fragments and the protein target. Medicinal chemistry optimization of ligands predicted by ALTA has resulted in pre-clinical candidates for protein kinases and bromodomains. The high-throughput, very low cost, sustainability, and high hit rate of the SEED-based protocols, unreachable by purely experimental techniques, make them perfectly suitable for both academic and industrial drug discovery research.

Aromatic Rings Commonly Used in Medicinal Chemistry: Force Fields Comparison and Interactions With Water Toward the Design of New Chemical Entities

The identification of lead compounds usually includes a step of chemical diversity generation. Its rationale may be supported by both qualitative (SAR) and quantitative (QSAR) approaches, offering models of the putative ligand-receptor interactions. In both scenarios, our understanding of which interactions functional groups can perform is mostly based on their chemical nature (such as electronegativity, volume, melting point, lipophilicity etc.) instead of their dynamics in aqueous, biological solutions (solvent accessibility, lifetime of hydrogen bonds, solvent structure etc.). As a consequence, it is challenging to predict from 2D structures which functional groups will be able to perform interactions with the target receptor, at which intensity and relative abundance in the biological environment, all of which will contribute to ligand potency and intrinsic activity. With this in mind, the aim of this work is to assess properties of aromatic rings, commonly used for drug design, in aqueous solution through molecular dynamics simulations in order to characterize their chemical features and infer their impact in complexation dynamics. For this, common aromatic and heteroaromatic rings were selected and received new atomic charge set based on the direction and module of the dipole moment from MP2/6-31G^* calculations, while other topological terms were taken from GROMOS53A6 force field. Afterwards, liquid physicochemical properties were simulated for a calibration set composed by nearly 40 molecules and compared to their respective experimental data, in order to validate each topology. Based on the reliance of the employed strategy, we expanded the dataset to more than 100 aromatic rings. Properties in aqueous solution such as solvent accessible surface area, H-bonds availability, H-bonds residence time, and water structure around heteroatoms were calculated for each ring, creating a database of potential interactions, shedding light on features of drugs in biological solutions, on the structural basis for bioisosterism and on the enthalpic/entropic costs for ligand-receptor complexation dynamics.

Practical application of ligand efficiency metrics in lead optimisation

The use of composite metrics that normalise biological potency values in relation to markers of physicochemical properties, such as size or lipophilicity, has gained a significant amount of traction with many medicinal chemists in recent years. However, there is no consensus on best practice in the area and their application has attracted some criticism. Here we present our approach to their application in lead optimisation projects, provide an objective discussion of the principles we consider important and illustrate how our use of lipophilic ligand efficiency enabled the progression of a number of our successful drug discovery projects. We derive, from this and some recent literature highlights, a set of heuristic guidelines for lipophilicity based optimisation that we believe are generally applicable across chemical series and protein targets.

Present drug-likeness filters in medicinal chemistry during the hit and lead optimization process: how far can they be simplified?

During the past decade, decreasing the attrition rate of drug development candidates reaching the market has become one of the major challenges in pharmaceutical research and drug development (R&D). To facilitate the decision-making process, and to increase the probability of rapidly finding and developing high-quality compounds, a variety of multiparametric guidelines, also known as rules and ligand efficiency (LE) metrics, have been developed. However, what are the 'best' descriptors and how far can we simplify these drug-likeness prediction tools in terms of the numerous, complex properties that they relate to?