Free Ligand 1D NMR Conformational Signatures To Enhance Structure Based Drug Design of a Mcl-1 Inhibitor (AZD5991) and Other Synthetic Macrocycles

AiZynth impact on medicinal chemistry practice at AstraZeneca

AstraZeneca chemists have been using the AI retrosynthesis tool AiZynth for three years. In this article, we present seven examples of how medicinal chemists using AiZynth positively impacted their drug discovery programmes. These programmes run the gamut from early-stage hit confirmation to late-stage route optimisation efforts. We also discuss the different use cases for which AI retrosynthesis tools are best suited.

Optimization of a series of novel, potent and selective Macrocyclic SYK inhibitors

Spleen tyrosine kinase (SYK) is a non-receptor cytoplasmic kinase. Due to its pivotal role in B cell receptor and Fc-receptor signalling, inhibition of SYK has been a target of interest in a variety of diseases. Herein, we report the use of structure-based drug design to discover a series of potent macrocyclic inhibitors of SYK, with excellent kinome selectivity and in vitro metabolic stability. We were able to remove hERG inhibition through the optimization of physical properties, and utilized a pro-drug strategy to address permeability challenges.

Simulation Reveals the Chameleonic Behavior of Macrocycles

Conformational analysis is central to the design of bioactive molecules. It is particularly challenging for macrocycles due to noncovalent transannular interactions, steric interactions, and ring strain that are often coupled. Herein, we simulated the conformations of five macrocycles designed to express a progression of increasing complexity in environment-dependent intramolecular interactions and verified the results against NMR measurements in chloroform and dimethyl sulfoxide. Molecular dynamics using an explicit solvent model, but not the Monte Carlo method with implicit solvation, handled both solvents correctly. Refinement of conformations at the ab initio level was fundamental to reproducing the experimental observations─standard state-of-the-art molecular mechanics force fields were insufficient. Our simulations correctly predicted the intramolecular interactions between side chains and the macrocycle and revealed an unprecedented solvent-induced conformational switch of the macrocyclic ring. Our results provide a platform for the rational, prospective design of molecular chameleons that adapt to the properties of the environment.

Insight into Thermodynamic and Kinetic Profiles in Small-Molecule Optimization

Structure-activity relationships (SARs) and structure-property relationships (SPRs) have been considered the most important factors during the drug optimization process. For medicinal chemists, improvements in the potencies and druglike properties of small molecules are regarded as their major goals. Among them, the binding affinity and selectivity of small molecules on their targets are the most important indicators. In recent years, there has been growing interest in using thermodynamic and kinetic profiles to analyze ligand-receptor interactions, which could provide not only binding affinities but also detailed binding parameters for small-molecule optimization. In this perspective, we are trying to provide an insight into thermodynamic and kinetic profiles in small-molecule optimization. Through a highlight of strategies on the small-molecule optimization with specific cases, we aim to put forward the importance of structure-thermodynamic relationships (STRs) and structure-kinetic relationships (SKRs), which could provide more guidance to find safe and effective small-molecule drugs.

Structure of human spermine oxidase in complex with a highly selective allosteric inhibitor

Human spermine oxidase (hSMOX) plays a central role in polyamine catabolism. Due to its association with several pathological processes, including inflammation and cancer, hSMOX has garnered interest as a possible therapeutic target. Therefore, determination of the structure of hSMOX is an important step to enable drug discovery and validate hSMOX as a drug target. Using insights from hydrogen/deuterium exchange mass spectrometry (HDX-MS), we engineered a hSMOX construct to obtain the first crystal structure of hSMOX bound to the known polyamine oxidase inhibitor MDL72527 at 2.4 Å resolution. While the overall fold of hSMOX is similar to its homolog, murine N1-acetylpolyamine oxidase (mPAOX), the two structures contain significant differences, notably in their substrate-binding domains and active site pockets. Subsequently, we employed a sensitive biochemical assay to conduct a high-throughput screen that identified a potent and selective hSMOX inhibitor, JNJ-1289. The co-crystal structure of hSMOX with JNJ-1289 was determined at 2.1 Å resolution, revealing that JNJ-1289 binds to an allosteric site, providing JNJ-1289 with a high degree of selectivity towards hSMOX. These results provide crucial insights into understanding the substrate specificity and enzymatic mechanism of hSMOX, and for the design of highly selective inhibitors.

Rational engineering of human spermine oxidase yields crystallizable structures and the design of an allosteric inhibitor.

An overview of kinase downregulators and recent advances in discovery approaches

Since the clinical approval of imatinib, the discovery of protein kinase downregulators entered a prosperous age. However, challenges still exist in the discovery of kinase downregulator drugs, such as the high failure rate during development, side effects, and drug-resistance problems. With the progress made through multidisciplinary efforts, an increasing number of new approaches have been applied to solve the above problems during the discovery process of kinase downregulators. In terms of in vitro and in vivo drug evaluation, progress was also made in cellular and animal model platforms for better and more clinically relevant drug assessment. Here, we review the advances in drug design strategies, drug property evaluation technologies, and efficacy evaluation models and technologies. Finally, we discuss the challenges and perspectives in the development of kinase downregulator drugs.

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.

Targeting a Novel KRAS Binding Site: Application of One-Component Stapling of Small (5-6-mer) Peptides

RAS proteins are central in the proliferation of many types of cancer, but a general approach toward the identification of pan-mutant RAS inhibitors has remained unresolved. In this work, we describe the application of a binding pharmacophore identified from analysis of known RAS binding peptides to the design of novel peptides. Using a chemically divergent approach, we generated a library of small stapled peptides from which we identified compounds with weak binding activity. Exploration of structure-activity relationships (SARs) and optimization of these early compounds led to low-micromolar binders of KRAS that block nucleotide exchange.

Generation of Quantum Configurational Ensembles Using Approximate Potentials

Conformational analysis is of paramount importance in drug design: it is crucial to determine pharmacological properties, understand molecular recognition processes, and characterize the conformations of ligands when unbound. Molecular Mechanics (MM) simulation methods, such as Monte Carlo (MC) and molecular dynamics (MD), are usually employed to generate ensembles of structures due to their ability to extensively sample the conformational space of molecules. The accuracy of these MM-based schemes strongly depends on the functional form of the force field (FF) and its parametrization, components that often hinder their performance. High-level methods, such as ab initio MD, provide reliable structural information but are still too computationally expensive to allow for extensive sampling. Therefore, to overcome these limitations, we present a multilevel MC method that is capable of generating quantum configurational ensembles while keeping the computational cost at a minimum. We show that FF reparametrization is an efficient route to generate FFs that reproduce QM results more closely, which, in turn, can be used as low-cost models to achieve the gold standard QM accuracy. We demonstrate that the MC acceptance rate is strongly correlated with various phase space overlap measurements and that it constitutes a robust metric to evaluate the similarity between the MM and QM levels of theory. As a more advanced application, we present a self-parametrizing version of the algorithm, which combines sampling and FF parametrization in one scheme, and apply the methodology to generate the QM/MM distribution of a ligand in aqueous solution.

Nuclear magnetic resonance free ligand conformations and atomic resolution dynamics

Knowledge of free ligand conformational preferences (energy minima) and conformational dynamics (rotational energy barriers) of small molecules in solution can guide drug design hypotheses and help rank ideas to bias syntheses towards more active compounds. Visualization of conformational exchange dynamics around torsion angles, by replica exchange with solute tempering molecular dynamics (REST-MD), gives results in agreement with high-resolution 1 H nuclear magnetic resonance (NMR) spectra and complements free ligand conformational analyses. Rotational energy barriers around individual bonds are comparable between calculated and experimental values, making the in-silico method relevant to ranking prospective design ideas in drug discovery programs, particularly across a series of analogs. Prioritizing design ideas, based on calculations and analysis of measurements across a series, efficiently guides rational discovery towards the "right molecules" for effective medicines.

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.

Two-Dimensional Barriers for Probing Conformational Shifts in Macrocycles

We describe the development and use of composite two-dimensional barriers in macrocyclic backbones. These tunable constructs derive their mode of action from heterocyclic rearrangements. The Boulton-Katritzky reaction has been identified as a particularly versatile means to effect a composite barrier, allowing the examination of the influence of heterocycle translocation on conformation. Kinetic studies using ¹H NMR have revealed that the in-plane atom movement is fast in 17, 18, 19-membered rings but slows down in 16-membered rings. The analysis by NMR and MD simulation experiments is consistent with the maintenance of rare cis-amide motifs during conformational interconversion. Taken together, our investigation demonstrates that heterocyclic rearrangement reactions can be used to control macrocyclic backbones and provides fundamental insights that may be applicable to the development of a wide range of other conformational control elements.

Modulation of the Passive Permeability of Semipeptidic Macrocycles: N- and C-Methylations Fine-Tune Conformation and Properties

Incorporating small modifications to peptidic macrocycles can have a major influence on their properties. For instance, N-methylation has been shown to impact permeability. A better understanding of the relationship between permeability and structure is of key importance as peptidic drugs are often associated with unfavorable pharmacokinetic profiles. Starting from a semipeptidic macrocycle backbone composed of a tripeptide tethered head-to-tail with an alkyl linker, we investigated two small changes: peptide-to-peptoid substitution and various methyl placements on the nonpeptidic linker. Implementing these changes in parallel, we created a collection of 36 compounds. Their permeability was then assessed in parallel artificial membrane permeability assay (PAMPA) and Caco-2 assays. Our results show a systematic improvement in permeability associated with one peptoid position in the cycle, while the influence of methyl substitution varies on a case-by-case basis. Using a combination of molecular dynamics simulations and NMR measurements, we offer hypotheses to explain such behavior.

Diversity-orientated synthesis of macrocyclic heterocycles using a double SNAr approach

An efficient macrocyclisation approach based on the double aromatic nucleophilic substitution (SNACK) was developed. This methodology allows a facile incorporation of heterocyclic motifs into macrocyclic rings and rapid synthesis of a significant number of structurally diverse macrocycles. SNACK macrocyclisation enables preparation of stable diastereoisomers of conformationally restricted macrocycles (atropisomers). Practical application of SNACK macrocyclisation in a drug discovery project was exemplified by the identification of high affinity macrocyclic binders of B-cell lymphoma 6 (BCL6).

NMR spectroscopy: the swiss army knife of drug discovery

Nuclear magnetic resonance (NMR) spectroscopy has evolved into a powerful tool within drug discovery over the last two decades. While traditionally being used by medicinal chemists for small molecule structure elucidation, it can also be a valuable tool for the identification of small molecules that bind to drug targets, for the characterization of target-ligand interactions and for hit-to-lead optimization. Here, we describe how NMR spectroscopy is integrated into the Pfizer drug discovery pipeline and how we utilize this approach to identify and validate initial hits and generate leads.

The role of NMR in leveraging dynamics and entropy in drug design

Nuclear magnetic resonance (NMR) spectroscopy has contributed to structure-based drug development (SBDD) in a unique way compared to the other biophysical methods. The potency of a ligand binding to a protein is dictated by the binding free energy, which is an intricate interplay between entropy and enthalpy. In addition to providing the atomic resolution structural information, NMR can help to identify protein-ligand interactions that potentially contribute to the enthalpic component of the free energy. NMR can also illuminate dynamic aspects of the interaction, which correspond to the entropic term of the free energy. The ability of NMR to access both terms in the free energy equation stems from the suite of experiments developed to shed light on various aspects that contribute to both entropy and enthalpy, deepening our understanding of the biological function of macromolecules and assisting to target them in physiological conditions. Here we provide a brief account of the contribution of NMR to SBDD, highlighting hallmark examples and discussing the challenges that demand further method development. In the era of integrated biology, the unique ability of NMR to directly ascertain structural and dynamical aspects of macromolecule and monitor changes in these properties upon engaging a ligand can be combined with computational and other structural and biophysical methods to provide a more complete picture of the energetics of drug engagement with the target. Such efforts can be used to engineer better drugs.

ReSCoSS: a flexible quantum chemistry workflow identifying relevant solution conformers of drug-like molecules

Conformational equilibria are at the heart of drug design, yet their energetic description is often hampered by the insufficient accuracy of low-cost methods. Here we present a flexible and semi-automatic workflow based on quantum chemistry, ReSCoSS, designed to identify relevant conformers and predict their equilibria across different solvent environments in the Conductor-like Screening Model for Real Solvents (COSMO-RS) framework. We demonstrate the utility and accuracy of the workflow through conformational case studies on several drug-like molecules from literature where relevant conformations are known. We further show that including ReSCoSS conformers significantly improves COSMO-RS based predictions of physicochemical properties over single-conformation approaches. ReSCoSS has found broad adoption in the in-house drug discovery and development work streams and has contributed to establishing quantum-chemistry methods as a strategic pillar in ligand discovery.

Anaplastic lymphoma kinase inhibitors: an updated patent review (2014-2018)

Introduction: Anaplastic lymphoma kinase (ALK), a receptor tyrosine kinase, has been discovered in several cancers, including anaplastic large-cell lymphoma, non-small cell lung cancer, and inflammatory myofibroblastic tumors. The deregulation of ALK activities, such as translocation and point mutation, results in human carcinogenesis. The use of ALK inhibitors in clinical cancer treatment has been shown to be efficacious, and the issue of resistance to ALK inhibitors has been reported. Consequently, the development of a new generation of ALK inhibitors is necessary.Areas covered: This paper provides a comprehensive review of the patent literature from 2014 to 2018 including small molecule ALK inhibitors and their use as anticancer agents. The approved and developing ALK inhibitors are described.Expert commentary: The available three generations of ALK inhibitors have shown a good anticancer effect in ALK-positive non-small cell lung cancer. An urgent issue in this field is ALK resistance development. The development of new ALK inhibitors through structure modification of currently available ALK inhibitors is proceeding, such as the synthesis of macrocyclic compounds. This article arranges the ALK inhibitors that have published in the patent in recent years. It may help in the investigation of a new generation of ALK inhibitors, which can overcome the resistance issue and development of novel drug candidates in the future.

Modelling the binding mode of macrocycles: Docking and conformational sampling

Drug discovery is increasingly tackling challenging protein binding sites regarding molecular recognition and druggability, including shallow and solvent-exposed protein-protein interaction interfaces. Macrocycles are emerging as promising chemotypes to modulate such sites. Despite their chemical complexity, macrocycles comprise important drugs and offer advantages compared to non-cyclic analogs, hence the recent impetus in the medicinal chemistry of macrocycles. Elaboration of macrocycles, or constituent fragments, can strongly benefit from knowledge of their binding mode to a target. When such information from X-ray crystallography is elusive, computational docking can provide working models. However, few studies have explored docking protocols for macrocycles, since conventional docking methods struggle with the conformational complexity of macrocycles, and also potentially with the shallower topology of their binding sites. Indeed, macrocycle binding mode prediction with the mainstream docking software GOLD has hardly been explored. Here, we present an in-depth study of macrocycle docking with GOLD and the ChemPLP scores. First, we summarize the thorough curation of a test set of 41 protein-macrocycle X-ray structures, raising the issue of lattice contacts with such systems. Rigid docking of the known bioactive conformers was successful (three top ranked poses) for 92.7% of the systems, in absence of crystallographic waters. Thus, without conformational search issues, scoring performed well. However, docking success dropped to 29.3% with the GOLD built-in conformational search. Yet, the success rate doubled to 58.5% when GOLD was supplied with extensive conformer ensembles docked rigidly. The reasons for failure, sampling or scoring, were analyzed, exemplified with particular cases. Overall, binding mode prediction of macrocycles remains challenging, but can be much improved with tailored protocols. The analysis of the interplay between conformational sampling and docking will be relevant to the prospective modelling of macrocycles in general.