Mapping the Efficiency and Physicochemical Trajectories of Successful Optimizations

Balancing Molecular Size, Activity, Permeability, and Other Properties: Drug Candidates in the Context of Their Chemical Structure Optimization

Chemical structure optimization is a vital part of early drug discovery projects. Starting with compounds that show activity on the target of interest, the chemical structures are subsequently optimized toward a development candidate (DC) molecule with the best chances of clinical success. However, the DCs in the context of such optimization programs, as well as detailed characterization of major limiting factors, have not been investigated in detail so far. Here, we report an analysis of the historical DC molecules at Novartis since 2005 in the context of their optimization projects. Mapping the DCs into their respective chemical optimization series, we find that these tend to be synthesized rather early in a substantial number of cases. Further analysis of structural properties, ADMET, and potency-related readouts revealed that DC compounds tend to be generally significantly smaller, more permeable, and have higher ligand efficiency than other compounds sent to in vivo PK studies, which we also show for compounds from the same chemical series. Although this might seem obvious to most practitioners in medicinal chemistry, for all of these properties, we could show that they tend to evolve in an undesired direction during structure optimization. This highlights the difficulty of successfully translating our knowledge to medicinal chemistry optimizations.

Modulation of the Meisenheimer complex metabolism of nitro-benzothiazinones by targeted C-6 substitution

Tuberculosis, caused by Mycobacterium tuberculosis, remains a major public health concern, demanding new antibiotics with innovative therapeutic principles due to the emergence of resistant strains. Benzothiazinones (BTZs) have been developed to address this problem. However, an unprecedented in vivo biotransformation of BTZs to hydride-Meisenheimer complexes has recently been discovered. Herein, we present a study of the influence of electron-withdrawing groups on the propensity of HMC formation in whole cells for a series of C-6-substituted BTZs obtained through reductive fluorocarbonylation as a late-stage functionalization key step. Gibbs free energy of reaction and Mulliken charges and Fukui indices on C-5 at quantum mechanics level were found as good indicators of in vitro HMC formation propensity. These results provide a first blueprint for the evaluation of HMC formation in drug development and set the stage for rational pharmacokinetic optimization of BTZs and similar drug candidates.

Unpredictable Dynamic Behaviour of Ruthenium Chelate Pyrrole Derivatives

Reaction of [Ru(H)2(CO)(PPh3)3] 1 with an equimolar amount of pyrrole-2-carboxylic acid (H2L1) leads to the homoleptic chelate derivative k2(O,O)-[RuH(CO)(HL1)(PPh3)2] 2. Prolonged acetonitrile refluxing promotes an unusual k2(O,O)- → k2(N,O)- dynamic chelate conversion, forming a neutral, stable, air- and moisture- insensitive, solvento-species k2(N,O)-[Ru(MeCN)(CO)(L1)(PPh3)2] 3. Analogously, reaction of 1 with the pyrrole-2-carboxyaldehyde (HL2) affords k2(N,O)-[RuH(CO)(HL2)(PPh3)2] 4, 5, as a couple of functional isomers. Optimized reaction conditions such as temperature and solvent polarity allow the isolation of dominant configurations. Structure 5 is a pyrrolide Ru-carbaldehyde, obtained from cyclization of the pendant CHO function, whereas species 4 can be viewed as an ethanoyl-conjugated Ru-pyrrole. Derivatives 3-5 were characterized by single crystal X-ray diffraction, ESI-Ms, IR, and NMR spectroscopy, indicating distinct features for the Ru-bonded pyrrolyl groups. DFT computational results, coplanarity, bond equalization, and electron delocalization along the fused five-membered rings support aromatic features. In accordance with the antisymbiotic trans-influence, both the isolated isomers 4 and 5 disclose CO ligands opposite to N- or O-anionic groups. The quantitative Mayer bond order evidences a stabilizing backbonding effect. Antibacterial and antifungal trials on Gram-positive (Staphylococcus aureus), Gram-negative (Escherichia coli), and Candida albicans were further carried out.

WLB-87848, a Selective σ1 Receptor Agonist, with an Unusually Positioned NH Group as Positive Ionizable Moiety and Showing Neuroprotective Activity

The synthesis and pharmacological activity of a new series of thieno[2,3-d]pyrimidin-4(3H)-one derivatives as sigma-1 receptor (σ1R) ligands are reported. A hit from a high-throughput screening program was evolved into a highly potent and selective σ1R agonist (14qR) that contains a free NH group as positive ionizable moiety, not fulfilling the usual pharmacophoric features of the σ1R. The compound shows good physicochemical and ADMET characteristics, displays an agonist profile in the binding immunoglobulin protein/σ1R association assay, induces neuron viability in an in vitro model of β-amyloid peptide intoxication, and presents positive results against recognition memory impairment induced by hippocampal injection of Aβ peptide in rats after oral treatment, altogether making 14qR (WLB-87848) an interesting candidate for neuroprotection.

Fragment-based drug discovery and biological evaluation of novel cannabinol-based inhibitors of oxytosis/ferroptosis for neurological disorders

The oxytosis/ferroptosis regulated cell death pathway is an emerging field of research owing to its pathophysiological relevance to a wide range of neurological disorders, including Alzheimer's and Parkinson's diseases and traumatic brain injury. Developing novel neurotherapeutics to inhibit oxytosis/ferroptosis offers exciting opportunities for the treatment of these and other neurological diseases. Previously, we discovered cannabinol (CBN) as a unique, potent inhibitor of oxytosis/ferroptosis by targeting mitochondria and modulating their function in neuronal cells. To further elucidate which key pharmacophores and chemical space are essential to the beneficial effects of CBN, we herein introduce a fragment-based drug discovery strategy in conjunction with cell-based phenotypic screens using oxytosis/ferroptosis to determine the structure-activity relationship of CBN. The resulting information led to the development of four new CBN analogs, CP1-CP4, that not only preserve the sub-micromolar potency of neuroprotection and mitochondria-modulating activities seen with CBN in neuronal cell models but also have better druglike properties. Moreover, compared to CBN, the analog CP1 shows improved in vivo efficacy in the Drosophila model of mild traumatic brain injury. Together these studies identify the key molecular scaffolds of cannabinoids that contribute to neuroprotection against oxytosis/ferroptosis. They also highlight the advantageous approach of combining in vitro cell-based assays and rapid in vivo studies using Drosophila models for evaluating new therapeutic compounds.

Synthesis and Anti-Trypanosoma cruzi Activity of 3-Cyanopyridine Derivatives

Chagas disease (CD) is a parasitic neglected tropical disease (NTD) caused by the protozoan Trypanosoma cruzi that affects 6 million people worldwide, often resulting in financial burden, morbidity, and mortality in endemic regions. Given a lack of highly efficient and safe treatments, new, affordable, and fit-for-purpose drugs for CD are urgently needed. In this work, we present a hit-to-lead campaign for novel cyanopyridine analogues as antichagasic agents. In a phenotypic screening against intracellular T. cruzi, hits 1 and 2 were identified and displayed promising potency combined with balanced physicochemical properties. As part of the Lead Optimization Latin America consortium, a set of 40 compounds was designed, synthesized, and tested against T. cruzi intracellular amastigotes and relevant human cell lines. The structural modifications were focused on three positions: cyanopyridine core, linker, and right-hand side. The ADME properties of selected compounds, lipophilicity, kinetic solubility, permeability, and liver microsomal stability, were evaluated. Compounds 1-9 displayed good potency (EC50T. cruzi amastigote <1 μM), and most compounds did not present significant cytotoxicity (CC50 MRC-5 = 32-64 μM). Despite the good balance between potency and selectivity, the antiparasitic activity of the series appeared to be driven by lipophilicity, making the progression of the series unfeasible due to poor ADME properties and potential promiscuity issues.

Natural Product Synthesis in the 21st Century: Beyond the Mountain Top

Research into natural products emerged from humanity's curiosity about the nature of matter and its role in the materia medica of diverse civilizations. Plants and fungi, in particular, supplied materials that altered behavior, perception, and well-being profoundly. Many active principles remain well-known today: strychnine, morphine, psilocybin, ephedrine. The potential to circumvent the constraints of natural supply and explore the properties of these materials led to the field of natural product synthesis. This research delivered new molecules with new properties, but also led to fundamental insights into the chemistry of the nonmetal elements H, C, N, O, P, S, Se, and their combinations, i.e., organic chemistry. It also led to a potent culture focused on bigger molecules and races to the finish line, perhaps at the expense of actionable next steps. About 20 years ago, the field began to contract in the United States. Research that focused solely on chemical reaction development, especially catalysis, filled the void. After all, new reactions and mechanistic insight could be immediately implemented by the chemistry community, so it became hard to justify the lengthy procurement of a complex molecule that sat in the freezer unused. This shift coincided with a divestment of natural product portfolios by pharmaceutical companies and an emphasis in academic organic chemistry on applications-driven research, perhaps at the expense of more fundamental science. However, as bioassays and the tools of chemical biology become widespread, synthesis finds a new and powerful ally that allows us to better deliver on the premise of the field. And the hard-won insights of complex synthesis can be better encoded digitally, mined by data science, and applied to new challenges, as chemists perturb and even surpass the properties of complex natural products. The 21st century promises powerful developments, both in fundamental organic chemistry and at the interface of synthesis and biology, if the community of scientists fosters its growth. This essay tries to contextualize natural product synthesis for a broad audience, looks ahead to its transformation in the coming years, and expects the future to be bright.

Novel Bidentate Amine Ligand and the Interplay between Pd(II) and Pt(II) Coordination and Biological Activity

Pt(II) and Pd(II) coordinating N-donor ligands have been extensively studied as anticancer agents after the success of cisplatin. In this work, a novel bidentate N-donor ligand, the N-[[4-(phenylmethoxy)phenyl]methyl]-2-pyridinemethanamine, was designed to explore the antiparasitic, antiviral and antitumor activity of its Pt(II) and Pd(II) complexes. Chemical and spectroscopic characterization confirm the formation of [MLCl2 ] complexes, where M=Pt(II) and Pd(II). Single crystal X-ray diffraction confirmed a square-planar geometry for the Pd(II) complex. Spectroscopic characterization of the Pt(II) complex suggests a similar structure. 1 H NMR, 195 Pt NMR and HR-ESI-MS(+) analysis of DMSO solution of complexes indicated that both compounds exchange the chloride trans to the pyridine for a solvent molecule with different reaction rates. The ligand and the two complexes were tested for in vitro antitumoral, antileishmanial, and antiviral activity. The Pt(II) complex resulted in a GI50 of 10.5 μM against the NCI/ADR-RES (multidrug-resistant ovarian carcinoma) cell line. The ligand and the Pd(II) complex showed good anti-SARS-CoV-2 activity with around 65 % reduction in viral replication at a concentration of 50 μM.

Curation and cheminformatics analysis of a Ugi-reaction derived library (URDL) of synthetically tractable small molecules for virtual screening application

Virtual screening (VS) is an important approach in drug discovery and relies on the availability of a virtual library of synthetically tractable molecules. Ugi reaction (UR) represents an important multi-component reaction (MCR) that reliably produces a peptidomimetic scaffold. Recent literature shows that a tactically assembled Ugi adduct can be subjected to further chemical modifications to yield a variety of rings and scaffolds, thus, renewing the interest in this old reaction. Given the reliability and efficiency of UR, we collated an UR derived library (URDL) of small molecules (total = 5773) for VS. The synthesis of the majority of URDL molecules may be carried out in 1-2 pots in a time and cost-effective manner. The detailed analysis of the average property and chemical space of URDL was also carried out using the open-source Datawarrior program. The comparison with FDA-approved oral drugs and inhibitors of protein-protein interactions (iPPIs) suggests URDL molecules are 'clean', drug-like, and conform to a structurally distinct space from the other two categories. The average physicochemical properties of compounds in the URDL library lie closer to iPPI molecules than oral drugs thus suggesting that the URDL resource can be applied to discover novel iPPI molecules. The URDL molecules consist of diverse ring systems, many of which have not been exploited yet for drug design. Thus, URDL represents a small virtual library of drug-like molecules with unexplored chemical space designed for VS. The structures of all molecules of URDL, oral drugs, and iPPI compounds are being made freely accessible as supplementary information for broader application.

Fragment-based drug nanoaggregation reveals drivers of self-assembly

Drug nanoaggregates are particles that can deleteriously cause false positive results during drug screening efforts, but alternatively, they may be used to improve pharmacokinetics when developed for drug delivery purposes. The structural features of molecules that drive nanoaggregate formation remain elusive, however, and the prediction of intracellular aggregation and rational design of nanoaggregate-based carriers are still challenging. We investigate nanoaggregate self-assembly mechanisms using small molecule fragments to identify the critical molecular forces that contribute to self-assembly. We find that aromatic groups and hydrogen bond acceptors/donors are essential for nanoaggregate formation, suggesting that both π-π stacking and hydrogen bonding are drivers of nanoaggregation. We apply structure-assembly-relationship analysis to the drug sorafenib and discover that nanoaggregate formation can be predicted entirely using drug fragment substructures. We also find that drug nanoaggregates are stabilized in an amorphous core-shell structure. These findings demonstrate that rational design can address intracellular aggregation and pharmacologic/delivery challenges in conventional and fragment-based drug development processes.

Towards holistic Compound Quality Scores: Extending ligand efficiency indices with compound pharmacokinetic characteristics

The suitability of small molecules as oral drugs is often assessed by simple physicochemical rules, the application of ligand efficiency scores or by composite scores based on physicochemical compound properties. These rules and scores are empirical and typically lack mechanistic background, such as information on pharmacokinetics (PK). We introduce new types of Compound Quality Scores (CQS, specifically called dose scores and cmax scores), which explicitly include predicted or, when available, experimental PK parameters and combine these with on-target potency. These CQS scores are surrogates for an estimated dose and corresponding cmax and allow prioritizing of compounds within test cascades as well as before synthesis. We demonstrate the complementarity and, in most cases, superior performance relative to existing efficiency metrics by project examples.

Discovery of WLB-89462, a New Drug-like and Highly Selective σ2 Receptor Ligand with Neuroprotective Properties

The synthesis and pharmacological activity of a new series of isoxazolylpyrimidines as sigma-2 receptor (σ2R) ligands are reported. Modification of a new hit retrieved in an HTS campaign allowed the identification of the compound WLB-89462 (20c) with good σ2R affinity (Ki = 13 nM) and high selectivity vs both the σ1R (Ki = 1777 nM) and a general panel of 180 targets. It represents one of the first σ2R ligands with drug-like properties, linked to a good physicochemical and ADMET profile (good solubility, no CYP inhibition, good metabolic stability, high permeability, brain penetration, and high oral exposure in rodents). Compound 20c shows neuroprotective activity in vitro and improves short-term memory impairment induced by hippocampal injection of amyloid β peptide in rats. Together with the promising effects in the chronic models where 20c is currently being evaluated, these results pave the way toward its clinical development as a neuroprotective agent.

Antibacterial activities of anthraquinones: structure-activity relationships and action mechanisms

With the increasing prevalence of untreatable infections caused by antibiotic-resistant bacteria, the discovery of new drugs from natural products has become a hot research topic. The antibacterial activity of anthraquinones widely distributed in traditional Chinese medicine has attracted much attention. Herein, the structure and activity relationships (SARs) of anthraquinones as bacteriostatic agents are reviewed and elucidated. The substituents of anthraquinone and its derivatives are closely related to their antibacterial activities. The stronger the polarity of anthraquinone substituents is, the more potent the antibacterial effects appear. The presence of hydroxyl groups is not necessary for the antibacterial activity of hydroxyanthraquinone derivatives. Substitution of di-isopentenyl groups can improve the antibacterial activity of anthraquinone derivatives. The rigid plane structure of anthraquinone lowers its water solubility and results in the reduced activity. Meanwhile, the antibacterial mechanisms of anthraquinone and its analogs are explored, mainly including biofilm formation inhibition, destruction of the cell wall, endotoxin inhibition, inhibition of nucleic acid and protein synthesis, and blockage of energy metabolism and other substances.

Fragment expansion with NUDELs - poised DNA-encoded libraries

Optimisation of the affinity of lead compounds is a critical challenge in the identification of drug candidates and chemical probes and is a process that takes many years. Fragment-based drug discovery has become established as one of the methods of choice for drug discovery starting with small, low affinity compounds. Due to their low affinity, the evolution of fragments to desirable levels of affinity is often a key challenge. The accepted best method for increasing the potency of fragments is by iterative fragment growing, which can be very time consuming and complex. Here, we introduce a paradigm for fragment hit optimisation using poised DNA-encoded chemical libraries (DELs). The synthesis of a poised DEL, a partially constructed library that retains a reactive handle, allows the coupling of any active fragment for a specific target protein, allowing rapid discovery of potent ligands. This is illustrated for bromodomain-containing protein 4 (BRD4), in which a weakly binding fragment was coupled to a 42-member poised DEL via Suzuki-Miyaura cross coupling resulting in the identification of an inhibitor with 51 nM affinity in a single step, representing an increase in potency of several orders of magnitude from an original fragment. The potency of the compound was shown to arise from the synergistic combination of substructures, which would have been very difficult to discover by any other method and was rationalised by X-ray crystallography. The compound showed attractive lead-like properties suitable for further optimisation and demonstrated BRD4-dependent cellular pharmacology. This work demonstrates the power of poised DELs to rapidly optimise fragments, representing an attractive generic approach to drug discovery.

Today's drug discovery and the shadow of the rule of 5

INTRODUCTION

The rule of 5 developed by Lipinski et al., a landmark and prescient piece of scholarship, focused the minds of drug hunters by systematically characterizing the physical make-up of drug molecules for the first time, noting many sub-optimal compounds identified by high-throughput screening practices. Its profound influence on thinking and practices, whilst providing benefit, perhaps etched the guidelines too strongly in the minds of some drug hunters who applied the bounds too literally without understanding the implications of the underlying statistics.

AREAS COVERED

This opinion is based on recent key developments that take thinking, measurements, and standards beyond those first set out, particularly the influences of molecular weight and the understanding, measurement, and calculation of lipophilicity.

EXPERT OPINION

Techniques and technologies for physicochemical estimations set new standards. It is timely to celebrate the significance and influence of the rule of 5, whilst taking thinking to new levels with better characterizations. The shadow of the rule of 5 may be long, but it is not dark, as new measurements, predictions and principles emerge as guiding lights in the design and prioritization of higher-quality molecules redefining the meaning of beyond the rule of 5.

Expression of Cell-Adhesion Molecules in E. coli: A High Throughput Screening to Identify Paracellular Modulators

Cell-adhesion molecules (CAMs) are responsible for cell-cell, cell-extracellular matrix, and cell-pathogen interactions. Claudins (CLDNs), occludin (OCLN), and junctional adhesion molecules (JAMs) are CAMs' components of the tight junction (TJ), the single protein structure tasked with safeguarding the paracellular space. The TJ is responsible for controlling paracellular permeability according to size and charge. Currently, there are no therapeutic solutions to modulate the TJ. Here, we describe the expression of CLDN proteins in the outer membrane of E. coli and report its consequences. When the expression is induced, the unicellular behavior of E. coli is replaced with multicellular aggregations that can be quantified using Flow Cytometry (FC). Our method, called iCLASP (inspection of cell-adhesion molecules aggregation through FC protocols), allows high-throughput screening (HTS) of small-molecules for interactions with CAMs. Here, we focused on using iCLASP to identify paracellular modulators for CLDN2. Furthermore, we validated those compounds in the mammalian cell line A549 as a proof-of-concept for the iCLASP method.

Trends in oral small-molecule drug discovery and product development based on product launches before and after the Rule of Five

In 1997, the 'Rule of Five' (Ro5) suggested physicochemical limitations for orally administered drugs, based on the analysis of chemical libraries from the early 1990s. In this review, we report on the trends in oral drug product development by analyzing products launched between 1994 and 1997 and between 2013 and 2019. Our analysis confirmed that most new oral drugs are within the Ro5 descriptors; however, the number of new drug products of drugs with molecular weight (MW) and calculated partition coefficient (clogP) beyond the Ro5 has slightly increased. Analysis revealed that there is no single scientific or technological reason for this trend, but that it likely results from incremental advances are being made in molecular biology, target diversity, drug design, medicinal chemistry, predictive modeling, drug metabolism and pharmacokinetics, and drug delivery.

Sc2Mol: a scaffold-based two-step molecule generator with variational autoencoder and transformer

MOTIVATION

Finding molecules with desired pharmaceutical properties is crucial in drug discovery. Generative models can be an efficient tool to find desired molecules through the distribution learned by the model to approximate given training data. Existing generative models (i) do not consider backbone structures (scaffolds), resulting in inefficiency or (ii) need prior patterns for scaffolds, causing bias. Scaffolds are reasonable to use, and it is imperative to design a generative model without any prior scaffold patterns.

RESULTS

We propose a generative model-based molecule generator, Sc2Mol, without any prior scaffold patterns. Sc2Mol uses SMILES strings for molecules. It consists of two steps: scaffold generation and scaffold decoration, which are carried out by a variational autoencoder and a transformer, respectively. The two steps are powerful for implementing random molecule generation and scaffold optimization. Our empirical evaluation using drug-like molecule datasets confirmed the success of our model in distribution learning and molecule optimization. Also, our model could automatically learn the rules to transform coarse scaffolds into sophisticated drug candidates. These rules were consistent with those for current lead optimization.

AVAILABILITY AND IMPLEMENTATION

The code is available at https://github.com/zhiruiliao/Sc2Mol.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Impact of Software Used and the Type of Target Protein on Molecular Docking Accuracy

The modern development of computer technology and different in silico methods have had an increasing impact on the discovery and development of new drugs. Different molecular docking techniques most widely used in silico methods in drug discovery. Currently, the time and financial costs for the initial hit identification can be significantly reduced due to the ability to perform high-throughput virtual screening of large compound libraries in a short time. However, the selection of potential hit compounds still remains more of a random process, because there is still no consensus on what the binding energy and ligand efficiency (LE) of a potentially active compound should be. In the best cases, only 20-30% of compounds identified by molecular docking are active in biological tests. In this work, we evaluated the impact of the docking software used as well as the type of the target protein on the molecular docking results and their accuracy using an example of the three most popular programs and five target proteins related to neurodegenerative diseases. In addition, we attempted to determine the "reliable range" of the binding energy and LE that would allow selecting compounds with biological activity in the desired concentration range.

25 Years of Small-Molecule Optimization at Novartis: A Retrospective Analysis of Chemical Series Evolution

In the drug development process, optimization of properties and biological activities of small molecules is an important task to obtain drug candidates with optimal efficacy when first applied in subsequent clinical studies. However, despite its importance, large-scale investigations of the optimization process in early drug discovery are lacking, likely due to the absence of historical records of different chemical series used in past projects. Here, we report a retrospective reconstruction of ∼3000 chemical series from the Novartis compound database, which allows us to characterize the general properties of chemical series as well as the time evolution of structural properties, ADMET properties, and target activities. Our data-driven approach allows us to substantiate common MedChem knowledge. We find that size, fraction of sp³-hybridized carbon atoms (F_sp³), and the density of stereocenters tend to increase during optimization, while the aromaticity of the compounds decreases. On the ADMET side, solubility tends to increase and permeability decreases, while safety-related properties tend to improve. Importantly, while ligand efficiency decreases due to molecular growth over time, target activities and lipophilic efficiency tend to improve. This emphasizes the heavy-atom count and log D as important parameters to monitor, especially as we further show that the decrease in permeability can be explained with the increase in molecular size. We highlight overlaps, shortcomings, and differences of the computationally reconstructed chemical series compared to the series used in recent internal drug discovery projects and investigate the relation to historical projects.

Aldehyde oxidase mediated drug metabolism: an underpredicted obstacle in drug discovery and development

Aldehyde oxidase (AO) has garnered curiosity as a non-CYP metabolizing enzyme in drug development due to unexpected consequences such as toxic metabolite generation and high metabolic clearance resulting in the clinical failure of new drugs. Therefore, poor AO mediated clearance prediction in preclinical nonhuman species remains a significant obstacle in developing novel drugs. Various isoforms of AO, such as AOX1, AOX3, AOX3L1, and AOX4 exist across species, and different AO activity among humans influences the AO mediated drug metabolism. Therefore, carefully considering the unique challenges is essential in developing successful AO substrate drugs. The in vitro to in vivo extrapolation underpredicts AO mediated drug clearance due to the lack of reliable representative animal models, substrate-specific activity, and the discrepancy between absolute concentration and activity. An in vitro tool to extrapolate in vivo clearance using a yard-stick approach is provided to address the underprediction of AO mediated drug clearance. This approach uses a range of well-known AO drug substrates as calibrators for qualitative scaling new drugs into low, medium, or high clearance category drugs. So far, in vivo investigations on chimeric mice with humanized livers (humanized mice) have predicted AO mediated metabolism to the best extent. This review addresses the critical aspects of the drug discovery stage for AO metabolism studies, challenges faced in drug development, approaches to tackle AO mediated drug clearance's underprediction, and strategies to decrease the AO metabolism of drugs.

Development of Noncovalent Small-Molecule Keap1-Nrf2 Inhibitors by Fragment-Based Drug Discovery

Targeting the protein-protein interaction (PPI) between the transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2) and its repressor, Kelch-like ECH-associated protein 1 (Keap1), constitutes a promising strategy for treating diseases involving oxidative stress and inflammation. Here, a fragment-based drug discovery (FBDD) campaign resulted in novel, high-affinity (K_i = 280 nM), and cell-active noncovalent small-molecule Keap1-Nrf2 PPI inhibitors. We screened 2500 fragments using orthogonal assays─fluorescence polarization (FP), thermal shift assay (TSA), and surface plasmon resonance (SPR)─and validated the hits by saturation transfer difference (STD) NMR, leading to 28 high-priority hits. Thirteen co-structures showed fragments binding mainly in the P4 and P5 subpockets of Keap1's Kelch domain, and three fluorenone-based fragments featuring a novel binding mode were optimized by structure-based drug discovery. We thereby disclose several fragment hits, including their binding modes, and show how FBDD can be performed to find new small-molecule Keap1-Nrf2 PPI inhibitors.

Can We Predict Clinical Pharmacokinetics of Highly Lipophilic Compounds by Integration of Machine Learning or In Vitro Data into Physiologically Based Models? A Feasibility Study Based on 12 Development Compounds

While high lipophilicity tends to improve potency, its effects on pharmacokinetics (PK) are complex and often unfavorable. To predict clinical PK in early drug discovery, we built human physiologically based PK (PBPK) models integrating either (i) machine learning (ML)-predicted properties or (ii) discovery stage in vitro data. Our test set was composed of 12 challenging development compounds with high lipophilicity (mean calculated log P 4.2), low plasma-free fraction (50% of compounds with fu,p < 1%), and low aqueous solubility. Predictions focused on key human PK parameters, including plasma clearance (CL), volume of distribution at steady state (V_ss), and oral bioavailability (%F). For predictions of CL, the ML inputs showed acceptable accuracy and slight underprediction bias [an average absolute fold error (AAFE) of 3.55; an average fold error (AFE) of 0.95]. Surprisingly, use of measured data only slightly improved accuracy but introduced an overprediction bias (AAFE = 3.35; AFE = 2.63). Predictions of V_ss were more successful, with both ML (AAFE = 2.21; AFE = 0.90) and in vitro (AAFE = 2.24; AFE = 1.72) inputs showing good accuracy and moderate bias. The %F was poorly predicted using ML inputs [average absolute prediction error (AAPE) of 45%], and use of measured data for solubility and permeability improved this to 34%. Sensitivity analysis showed that predictions of CL limited the overall accuracy of human PK predictions, partly due to high nonspecific binding of lipophilic compounds, leading to uncertainty of unbound clearance. For accurate predictions of %F, solubility was the key factor. Despite current limitations, this work encourages further development of ML models and integration of their results within PBPK models to enable human PK prediction at the drug design stage, even before compounds are synthesized. Further evaluation of this approach with more diverse chemical types is warranted.

Forces Driving a Magic Bullet to Its Target: Revisiting the Role of Thermodynamics in Drug Design, Development, and Optimization

Drug discovery strategies have advanced significantly towards prioritizing target selectivity to achieve the longstanding goal of identifying "magic bullets" amongst thousands of chemical molecules screened for therapeutic efficacy. A myriad of emerging and existing health threats, including the SARS-CoV-2 pandemic, alarming increase in bacterial resistance, and potentially fatal chronic ailments, such as cancer, cardiovascular disease, and neurodegeneration, have incentivized the discovery of novel therapeutics in treatment regimens. The design, development, and optimization of lead compounds represent an arduous and time-consuming process that necessitates the assessment of specific criteria and metrics derived via multidisciplinary approaches incorporating functional, structural, and energetic properties. The present review focuses on specific methodologies and technologies aimed at advancing drug development with particular emphasis on the role of thermodynamics in elucidating the underlying forces governing ligand-target interaction selectivity and specificity. In the pursuit of novel therapeutics, isothermal titration calorimetry (ITC) has been utilized extensively over the past two decades to bolster drug discovery efforts, yielding information-rich thermodynamic binding signatures. A wealth of studies recognizes the need for mining thermodynamic databases to critically examine and evaluate prospective drug candidates on the basis of available metrics. The ultimate power and utility of thermodynamics within drug discovery strategies reside in the characterization and comparison of intrinsic binding signatures that facilitate the elucidation of structural-energetic correlations which assist in lead compound identification and optimization to improve overall therapeutic efficacy.

In Silico Positional Analogue Scanning with Amber GPU-TI

Positional analogue scanning (PAS) is an accepted strategy for multiparameter lead optimization (MPO) in drug discovery. Small structural changes as introduced by PAS can lead to 10-fold changes in binding potency in ∼10-20% of cases, a significant parameter shift irrespective of other MPO objectives. Sometimes performing a complete PAS is challenging due to resource and time constraints, building block availability, or difficulty in synthesis. Calculating relative binding free energies (RBFEs) for all positions can contribute to prioritizing the most promising analogues for synthesis. We tested a well-established RBFE calculation method, Amber GPU-TI, for 20 positional analogue scans in 14 test systems (cyclin-dependent kinase 8 (CDK8), hepatitis C virus nonstructural protein 5B (HCV NS5B), tankyrase, RAC-α serine/threonine-protein kinase (Akt), phosphodiesterase 1B (PDE1B), orexin/hypocretin receptor type 1 (OX1R), orexin/hypocretin receptor type 2 (OX2R), histone acetyltransferase K (lysine) acetyltransferase 6A (KAT6A), peroxisome proliferator-activated receptor γ (PPARγ), extracellular signal-regulated kinases (ERK1/2), coactivator-associated arginine methyltransferase 1 (PRMT4), α_vβ₆, bromodomain 1 (BD1), human immunodeficiency virus-1 (HIV-1) entry) involving nitrogen, methyl, halogen, methoxy, and hydroxyl scans with at least four analogues per set. Among the 66 analogue positions explored, we found that in 18 cases Amber GPU-TI calculations predicted a more than 10-fold change in potency. In all of these cases, the experimentally observed direction of potency changes agreed with the predictions. In 16 cases, more than 10-fold changes in experimental potency were observed. Again, in all of these cases, Amber GPU-TI predicted the direction of the potency changes correctly. In none of these cases would a decision made for or against synthesis based on a 10-fold change in potency have resulted in missing an important analogue. Therefore, in silico RBFE calculations using Amber GPU-TI can meaningfully contribute to the prioritization of positional analogues before synthesis.

Identification and development of a series of disubstituted piperazines for the treatment of Chagas disease

Approximately 6-7 million people around the world are estimated to be infected with Trypanosoma cruzi, the causative agent of Chagas disease. The current treatments are inadequate and therefore new medical interventions are urgently needed. In this paper we describe the identification of a series of disubstituted piperazines which shows good potency against the target parasite but is hampered by poor metabolic stability. We outline the strategies used to mitigate this issue such as lowering logD, bioisosteric replacements of the metabolically labile piperazine ring and use of plate-based arrays for quick diversity scoping. We discuss the success of these strategies within the context of this series and highlight the challenges faced in phenotypic programs when attempting to improve the pharmacokinetic profile of compounds whilst maintaining potency against the desired target.

Developing the Cannabinoid Receptor 2 (CB2) pharmacopoeia: past, present, and future

Cannabinoid Receptor 2 (CB2) is a G protein-coupled receptor (GPCR) with considerable, though as yet unrealised, therapeutic potential. Promising preclinical data supports the applicability of CB2 activation in autoimmune and inflammatory diseases, pain, neurodegeneration, and osteoporosis. A diverse pharmacopoeia of cannabinoid ligands is available, which has led to considerable advancements in the understanding of CB2 function and extensive preclinical evaluation. However, until recently, most CB2 ligands were highly lipophilic and as such not optimal for clinical application due to unfavourable physicochemical properties. A number of strategies have been applied to develop CB2 ligands to achieve closer to 'drug-like' properties and a few such compounds have now undergone clinical trial. We review the current state of CB2 ligand development and progress in optimising physicochemical properties, understanding advanced molecular pharmacology such as functional selectivity, and clinical evaluation of CB2-targeting compounds.

Optimizing Shape Complementarity Enables the Discovery of Potent Tricyclic BCL6 Inhibitors

To identify new chemical series with enhanced binding affinity to the BTB domain of B-cell lymphoma 6 protein, we targeted a subpocket adjacent to Val18. With no opportunities for strong polar interactions, we focused on attaining close shape complementarity by ring fusion onto our quinolinone lead series. Following exploration of different sized rings, we identified a conformationally restricted core which optimally filled the available space, leading to potent BCL6 inhibitors. Through X-ray structure-guided design, combined with efficient synthetic chemistry to make the resulting novel core structures, a >300-fold improvement in activity was obtained by the addition of seven heavy atoms.

PROTAC targeted protein degraders: the past is prologue

Targeted protein degradation (TPD) is an emerging therapeutic modality with the potential to tackle disease-causing proteins that have historically been highly challenging to target with conventional small molecules. In the 20 years since the concept of a proteolysis-targeting chimera (PROTAC) molecule harnessing the ubiquitin-proteasome system to degrade a target protein was reported, TPD has moved from academia to industry, where numerous companies have disclosed programmes in preclinical and early clinical development. With clinical proof-of-concept for PROTAC molecules against two well-established cancer targets provided in 2020, the field is poised to pursue targets that were previously considered 'undruggable'. In this Review, we summarize the first two decades of PROTAC discovery and assess the current landscape, with a focus on industry activity. We then discuss key areas for the future of TPD, including establishing the target classes for which TPD is most suitable, expanding the use of ubiquitin ligases to enable precision medicine and extending the modality beyond oncology.

Relating Conformational Equilibria to Conformer-Specific Lipophilicities: New Opportunities in Drug Discovery

Efficient drug discovery is based on a concerted effort in optimizing bioactivity and compound properties such as lipophilicity, and is guided by efficiency metrics that reflect both aspects. While conformation–activity relationships and ligand conformational control are known strategies to improve bioactivity, the use of conformer‐specific lipophilicities (logp) is much less explored. Here we show how conformer‐specific logp values can be obtained from knowledge of the macroscopic logP value, and of the equilibrium constants between the individual species in water and in octanol. This is illustrated with fluorinated amide rotamers, with integration of rotamer ¹⁹F NMR signals as a facile, direct method to obtain logp values. The difference between logp and logP optimization is highlighted, giving rise to a novel avenue for lipophilicity control in drug discovery.

Bioisosteres of the Phenyl Ring: Recent Strategic Applications in Lead Optimization and Drug Design

The benzene moiety is the most prevalent ring system in marketed drugs, underscoring its historic popularity in drug design either as a pharmacophore or as a scaffold that projects pharmacophoric elements. However, introspective analyses of medicinal chemistry practices at the beginning of the 21st century highlighted the indiscriminate deployment of phenyl rings as an important contributor to the poor physicochemical properties of advanced molecules, which limited their prospects of being developed into effective drugs. This Perspective deliberates on the design and applications of bioisosteric replacements for a phenyl ring that have provided practical solutions to a range of developability problems frequently encountered in lead optimization campaigns. While the effect of phenyl ring replacements on compound properties is contextual in nature, bioisosteric substitution can lead to enhanced potency, solubility, and metabolic stability while reducing lipophilicity, plasma protein binding, phospholipidosis potential, and inhibition of cytochrome P450 enzymes and the hERG channel.

Prioritization of Molecular Targets for Antimalarial Drug Discovery

There is a shift in antimalarial drug discovery from phenotypic screening toward target-based approaches, as more potential drug targets are being validated in Plasmodium species. Given the high attrition rate and high cost of drug discovery, it is important to select the targets most likely to deliver progressible drug candidates. In this paper, we describe the criteria that we consider important for selecting targets for antimalarial drug discovery. We describe the analysis of a number of drug targets in the Malaria Drug Accelerator (MalDA) pipeline, which has allowed us to prioritize targets that are ready to enter the drug discovery process. This selection process has also highlighted where additional data are required to inform target progression or deprioritization of other targets. Finally, we comment on how additional drug targets may be identified.

A Retrospective Look at the Impact of Binding Site Environment on the Optimization of TRPA1 Antagonists

Transient receptor potential ankyrin 1 (TRPA1) antagonists have generated broad interest in the pharmaceutical industry for the treatment of both pain and asthma. Over the past decade, multiple antagonist classes have been reported in the literature with a wide range of structural diversity. Our own work has focused on the development of proline sulfonamide and hypoxanthine-based antagonists, two antagonist classes with distinct physicochemical properties and pharmacokinetic (PK) trends. Late in our discovery program, cryogenic electron microscopy (cryoEM) studies revealed two different antagonist binding sites: a membrane-exposed proline sulfonamide transmembrane site and an intracellular hypoxanthine site near the membrane interface. A retrospective look at the discovery program reveals how the different binding sites, and their location relative to the cell membrane, influenced the optimization trajectories and overall drug profiles of each antagonist class.

An Alkynylpyrimidine-Based Covalent Inhibitor That Targets a Unique Cysteine in NF-κB-Inducing Kinase

NF-κB-inducing kinase (NIK) is a key enzyme in the noncanonical NF-κB pathway, of interest in the treatment of a variety of diseases including cancer. Validation of NIK as a drug target requires potent and selective inhibitors. The protein contains a cysteine residue at position 444 in the back pocket of the active site, unique within the kinome. Analysis of existing inhibitor scaffolds and early structure-activity relationships (SARs) led to the design of C444-targeting covalent inhibitors based on alkynyl heterocycle warheads. Mass spectrometry provided proof of the covalent mechanism, and the SAR was rationalized by computational modeling. Profiling of more potent analogues in tumor cell lines with constitutively activated NIK signaling induced a weak antiproliferative effect, suggesting that kinase inhibition may have limited impact on cancer cell growth. This study shows that alkynyl heterocycles are potential cysteine traps, which may be employed where common Michael acceptors, such as acrylamides, are not tolerated.

Fezolinetant in the treatment of vasomotor symptoms associated with menopause

Introduction: Although international clinical practice guidelines recognize a continued role for menopausal hormone therapy (HT), particularly for symptomatic women <60 years of age or within 10 years of menopause, safety and tolerability concerns have discouraged HT use due to potential links with a perceived increased risk of hormone-dependent cancers, and an established risk of stroke and venous thromboembolism. There is therefore a need for safe, effective non-hormonal therapy for relief of menopausal vasomotor symptoms (VMS).Areas covered: This narrative review summarizes the dataset accrued for fezolinetant, a neurokinin-3 receptor (NK3R) antagonist in clinical development for menopause-associated VMS.Expert opinion: Altered signaling in neuroendocrine circuits at menopause leads to VMS wherein NK3R activity plays a key role to modulate the thermoregulatory center in a manner conducive to triggering the 'hot flash' response. Thus, a new generation of NK3R antagonists has entered clinical development to specifically target the mechanistic basis of VMS. Fezolinetant is the most advanced NK3R antagonist in terms of stage of clinical development. Results to date have demonstrated rapid and substantial reduction in VMS frequency and severity and associated improvements in health-related quality of life. NK3R antagonists offer a non-hormonal alternative to HT for the treatment of menopause-related VMS.

Synthesis and Physicochemical Properties of 2-SF5-(Aza)Indoles, a New Family of SF5 Heterocycles

Structural diversity in heterocyclic chemistry is key to unlocking new properties and modes of action. In this regard, heterocycles embedding emerging fluorinated substituents hold great promise. Herein is described a strategy to access 2-SF₅-(aza)indoles for the first time. The sequence relies on the radical addition of SF₅Cl to the alkynyl π-system of 2-ethynyl anilines followed by a cyclization reaction. A telescoped sequence is proposed, making this strategy very appealing and reproducible on a gram scale. Downstream functionalizations are also demonstrated, allowing an easy diversification of N- and C3-positions. Ames test, pK _a, log P, and differential scanning calorimetry measurements of several fluorinated 2-Rf-indoles are also disclosed. These studies highlight the strategic advantages that a C2-pentafluorosulfanylated motif impart to a privileged scaffold such as an indole.

Fragment-Based Optimization of Dihydropyrazino-Benzimidazolones as Metabotropic Glutamate Receptor-2 Positive Allosteric Modulators against Migraine

Our previous scaffold-hopping attempts resulted in dihydropyrazino-benzimidazoles as metabotropic glutamate receptor-2 (mGluR2) positive allosteric modulators (PAMs) with suboptimal drug-like profiles. Here, we report an alternative fragment-based optimization strategy applied on the new dihydropyrazino-benzimidazolone scaffold. Analyzing published high-affinity mGluR2 PAMs, we used a pharmacophore-guided approach to identify suitable growing vectors and optimize the scaffold in these directions. This strategy resulted in a new fragment like lead (34) with improved druglike properties that were translated to sufficient pharmacokinetics and validated proof-of-concept studies in migraine. Gratifyingly, compound 34 showed reasonable activity in the partial infraorbital nerve ligation, a migraine disease model that might open this indication for mGluR2 PAMs.

Design, Synthesis, and Structural Analysis of Cladosporin-Based Inhibitors of Malaria Parasites

Here we have described a systematic structure activity relationship (SAR) of a set of compounds inspired from cladosporin, a tool compound that targets parasite (Plasmodium falciparum) lysyl tRNA synthetase (KRS). Four sets of analogues, synthesized based on point changes in the chemical scaffold of cladosporin and other logical modifications and hybridizations, were assessed using high throughput enzymatic and parasitic assays along with in vitro pharmacokinetics. Co-crystallization of the most potent compound in our series (CL-2) with PfKRS revealed its structural basis of enzymatic binding and potency. Further, we report that CL-2 has performed better than cladosporin in terms of metabolic stability. It thus represents a new lead for further optimization toward the development of antimalarial drugs. Collectively, along with a lead compound, the series offers insights on how even the slightest chemical modification might play an important role in enhancing or decreasing the potency of a chemical scaffold.

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.

Trends in Hit-to-Lead Optimization Following DNA-Encoded Library Screens

DNA-encoded library (DEL) screens have emerged as a powerful hit-finding tool for a number of biological targets. In this Innovations article, we review published hit-to-lead optimization studies following DEL screens. Trends in molecular property changes from hit to lead are identified, and specific optimization tactics are exemplified in case studies. Across the studies, physicochemical property and structural changes post-DEL screening are similar to those which occur during hit-to-lead optimization following high throughputscreens (HTS). However, unique aspects of DEL-the combinatorial synthetic methods which enable DEL synthesis and the linker effects at the DNA attachment point-impact the strategies and outcomes of hit-to-lead optimizations.

Physicochemical Profiling and Comparison of Research Antiplasmodials and Advanced Stage Antimalarials with Oral Drugs

To understand the property space of antimalarials, we collated a large dataset of research antiplasmodial (RAP) molecules with known in vitro potencies and advanced stage antimalarials (ASAMs) with established oral bioavailability. While RAP molecules are "non-druglike", ASAM molecules display properties closer to Lipinski's and Veber's thresholds. Comparison within the different potency groups of RAP molecules indicates that the in vitro potency is positively correlated to the molecular weight, the calculated octanol-water partition coefficient (clog P), aromatic ring counts (#Ar), and hydrogen bond acceptors. Despite both categories being bioavailable, the ASAM molecules are relatively larger and more lipophilic, have a lower polar surface area, and possess a higher count of heteroaromatic rings than oral drugs. Also, antimalarials are found to have a higher proportion of aromatic (#ArN) and basic nitrogen (#BaN) counts, features implicitly used in the design of antimalarial molecules but not well studied hitherto. We also propose using descriptors scaled by the sum of #ArN and #BaN (SBAN) to define an antimalarial property space. Together, these results may have important applications in the identification and optimization of future antimalarials.

A Decade of FDA-Approved Drugs (2010-2019): Trends and Future Directions

A total of 378 novel drugs and 27 biosimilars approved by the U.S. Food and Drug Administration (FDA) between 2010 and 2019 were evaluated according to approval numbers by year, therapeutic areas, modalities, route of administration, first-in-class designation, approval times, and expedited review categories. From this review, oncology remains the top therapy area (25%), followed by infection (15%) and central nervous system disorders (11%). Regulatory incentives have been effective as evidenced by an increase in orphan drugs as well as antibacterial drugs approved under the GAIN act. Clinical development times may be increasing, perhaps as a result of the increase in orphan drug indications. Small molecules continue to mostly adhere to "Rule of 5" (Ro5) parameters, but innovation in new modalities is rapidly progressing with approvals for antisense oligonucleotides (ASO), small-interfering RNA (siRNAs), and antibody-directed conjugates (ADCs). Finally, novel targets and scientific breakthroughs that address areas of unmet clinical need are discussed in detail.

Mapping major SARS-CoV-2 drug targets and assessment of druggability using computational fragment screening: Identification of an allosteric small-molecule binding site on the Nsp13 helicase

The 2019 emergence of, SARS-CoV-2 has tragically taken an immense toll on human life and far reaching impacts on society. There is a need to identify effective antivirals with diverse mechanisms of action in order to accelerate preclinical development. This study focused on five of the most established drug target proteins for direct acting small molecule antivirals: Nsp5 Main Protease, Nsp12 RNA-dependent RNA polymerase, Nsp13 Helicase, Nsp16 2'-O methyltransferase and the S2 subunit of the Spike protein. A workflow of solvent mapping and free energy calculations was used to identify and characterize favorable small-molecule binding sites for an aromatic pharmacophore (benzene). After identifying the most favorable sites, calculated ligand efficiencies were compared utilizing computational fragment screening. The most favorable sites overall were located on Nsp12 and Nsp16, whereas the most favorable sites for Nsp13 and S2 Spike had comparatively lower ligand efficiencies relative to Nsp12 and Nsp16. Utilizing fragment screening on numerous possible sites on Nsp13 helicase, we identified a favorable allosteric site on the N-terminal zinc binding domain (ZBD) that may be amenable to virtual or biophysical fragment screening efforts. Recent structural studies of the Nsp12:Nsp13 replication-transcription complex experimentally corroborates ligand binding at this site, which is revealed to be a functional Nsp8:Nsp13 protein-protein interaction site in the complex. Detailed structural analysis of Nsp13 ZBD conformations show the role of induced-fit flexibility in this ligand binding site and identify which conformational states are associated with efficient ligand binding. We hope that this map of over 200 possible small-molecule binding sites for these drug targets may be of use for ongoing discovery, design, and drug repurposing efforts. This information may be used to prioritize screening efforts or aid in the process of deciphering how a screening hit may bind to a specific target protein.

Into the Fray! A Beginner's Guide to Medicinal Chemistry

Modern medicinal chemistry is a complex, multidimensional discipline that operates at the interface of the chemical and biological sciences. The medicinal chemistry contribution to drug discovery is typically described in the context of the well-recited linear progression of the drug discovery pipeline. However, compound optimization is idiosyncratic to each project, and clear definitions of hit and lead molecules and the subsequent progress along the pipeline becomes easily blurred. In addition, this description lacks insight into the entangled relationship between chemical and pharmacological properties, and thus provides limited guidance on how innovative medicinal chemistry strategies can be applied to solve optimization problems, regardless of the stage in the pipeline. Through discussion and illustrative examples, this article seeks to provide insights into the finesse of medicinal chemistry and the subtlety of balancing chemical properties pharmacology. In so doing, it aims to serve as an accessible and simple-to-digest guide for anyone who wishes to learn about the underlying principles of medicinal chemistry, in a context that has been decoupled from the pipeline description.