Discovery of Clinical Candidate AZD5462, a Selective Oral Allosteric RXFP1 Agonist for Treatment of Heart Failure.

Optimization of the highly potent and selective, yet metabolically unstable and poorly soluble hRXFP1 agonist AZ7976 led to the identification of the clinical candidate, AZD5462. Assessment of RXFP1-dependent cell signaling demonstrated that AZD5462 activates a highly similar panel of downstream pathways as relaxin H2 but does not modulate relaxin H2-mediated cAMP second messenger responsiveness. The therapeutic potential of AZD5462 was assessed in a translatable cynomolgus monkey heart failure model.

Lipid shape and packing are key for optimal design of pH-sensitive mRNA lipid nanoparticles.

The ionizable-lipid component of RNA-containing nanoparticles controls the pH-dependent behavior necessary for an efficient delivery of the cargo-the so-called endosomal escape. However, it is still an empirical exercise to identify optimally performing lipids. Here, we study two well-known ionizable lipids, DLin-MC3-DMA and DLin-DMA using a combination of experiments, multiscale computer simulations, and electrostatic theory.

Multiomics analysis of naturally efficacious lipid nanoparticle coronas reveals high-density lipoprotein is necessary for their function.

In terms of lipid nanoparticle (LNP) engineering, the relationship between particle composition, delivery efficacy, and the composition of the biocoronas that form around LNPs, is poorly understood. To explore this we analyze naturally efficacious biocorona compositions using an unbiased screening workflow. First, LNPs are complexed with plasma samples, from individual lean or obese male rats, and then functionally evaluated in vitro.

Machine learning/molecular dynamic protein structure prediction approach to investigate the protein conformational ensemble.

Proteins exist in several different conformations. These structural changes are often associated with fluctuations at the residue level. Recent findings show that co-evolutionary analysis coupled with machine-learning techniques improves the precision by providing quantitative distance predictions between pairs of residues.

Novel Chemical Series of 5-Lipoxygenase-Activating Protein Inhibitors for Treatment of Coronary Artery Disease.

5-Lipoxygenase (5-LO)-activating protein (FLAP) inhibitors have proven to attenuate 5-LO pathway activity and leukotriene production in human clinical trials. However, previous clinical candidates have been discontinued and the link between FLAP inhibition and outcome in inflammatory diseases remains to be established. We here describe a novel series of FLAP inhibitors identified from a screen of 10k compounds and the medicinal chemistry strategies undertaken to progress this series.

Discovery and Early Clinical Development of an Inhibitor of 5-Lipoxygenase Activating Protein (AZD5718) for Treatment of Coronary Artery Disease.

5-Lipoxygenase activating protein (FLAP) inhibitors attenuate 5-lipoxygenase pathway activity and reduce the production of proinflammatory and vasoactive leukotrienes. As such, they are hypothesized to have therapeutic benefit for the treatment of diseases that involve chronic inflammation including coronary artery disease. Herein, we disclose the medicinal chemistry discovery and the early clinical development of the FLAP inhibitor AZD5718 (12).

Exploring Binding Mechanisms in Nuclear Hormone Receptors by Monte Carlo and X-ray-derived Motions.

In this study, we performed an extensive exploration of the ligand entry mechanism for members of the steroid nuclear hormone receptor family (androgen receptor, estrogen receptor α, glucocorticoid receptor, mineralocorticoid receptor, and progesterone receptor) and their endogenous ligands. The exploration revealed a shared entry path through the helix 3, 7, and 11 regions. Examination of the x-ray structures of the receptor-ligand complexes further showed two distinct folds of the helix 6-7 region, classified as "open" and "closed", which could potentially affect ligand binding.

Intramolecular Hydrogen Bond Expectations in Medicinal Chemistry.

Design strategies centered on intramolecular hydrogen bonds are sometime used in drug discovery, but their general applicability has not been addressed beyond scattered examples or circumstantial evidence. A total of 1053 matched molecular pairs where only one of the two molecules is able to form an intramolecular hydrogen bond via monatomic transformations have been identified across the ChEMBL database. These pairs were used to investigate the effect of intramolecular hydrogen bonds on biological activity.

Binding thermodynamics discriminates fragments from druglike compounds: a thermodynamic description of fragment-based drug discovery.

Small is beautiful - reducing the size and complexity of chemical starting points for drug design allows better sampling of chemical space, reveals the most energetically important interactions within protein-binding sites and can lead to improvements in the physicochemical properties of the final drug. The impact of fragment-based drug discovery (FBDD) on recent drug discovery projects and our improved knowledge of the structural and thermodynamic details of ligand binding has prompted us to explore the relationships between ligand-binding thermodynamics and FBDD. Information on binding thermodynamics can give insights into the contributions to protein-ligand interactions and could therefore be used to prioritise compounds with a high degree of specificity in forming key interactions.

A comprehensive company database analysis of biological assay variability.

Analysis of data from various compounds measured in diverse biological assays is a central part of drug discovery research projects. However, no systematic overview of the variability in biological assays has been published and judgments on assay quality and robustness of data are often based on personal belief and experience within the drug discovery community. To address this we performed a reproducibility analysis of all biological assays at AstraZeneca between 2005 and 2014.

Binding Mode and Induced Fit Predictions for Prospective Computational Drug Design.

Computer-aided drug design plays an important role in medicinal chemistry to obtain insights into molecular mechanisms and to prioritize design strategies. Although significant improvement has been made in structure based design, it still remains a key challenge to accurately model and predict induced fit mechanisms. Most of the current available techniques either do not provide sufficient protein conformational sampling or are too computationally demanding to fit an industrial setting.

Ligand Binding Thermodynamics in Drug Discovery: Still a Hot Tip?

The use of ligand binding thermodynamics has been proposed as a potential success factor to accelerate drug discovery. However, despite the intuitive appeal of optimizing binding enthalpy, a number of factors complicate routine use of thermodynamic data. On a macroscopic level, a range of experimental parameters including temperature and buffer choice significantly influence the observed thermodynamic signatures.

Discovery of AZD6642, an inhibitor of 5-lipoxygenase activating protein (FLAP) for the treatment of inflammatory diseases.

A drug discovery program in search of novel 5-lipoxygenase activating protein (FLAP) inhibitors focused on driving a reduction in lipophilicity with maintained or increased ligand lipophilic efficiency (LLE) compared to previously reported compounds led to the discovery of AZD6642 (15b). Introduction of a hydrophilic tetrahydrofuran (THF) ring at the stereogenic central carbon atom led to a significant shift in physicochemical property space. The structure-activity relationship exploration and optimization of DMPK properties leading to this compound are described in addition to pharmacokinetic analysis and an investigation of the pharmacokinetic (PK)-pharmacodynamic (PD) relationship based on ex vivo leukotriene B4 (LTB4) levels in dog.

Computational prediction of drug solubility in fasted simulated and aspirated human intestinal fluid.

Purpose: To develop predictive models of apparent solubility (Sapp) of lipophilic drugs in fasted state simulated intestinal fluid (FaSSIF) and aspirated human intestinal fluid (HIF).

Methods: Measured Sapp values in FaSSIF, HIF and phosphate buffer pH 6.5 (PhBpH6.

A serendipitously identified novel small molecule procoagulant compound giving rise to a high-throughput screening assay based on human plasma.

Introduction: Oral treatment is lacking for haemophilia, the rare bleeding disorders, and some severe forms of von Willebrand's disease. We have serendipitously identified a small molecule procoagulant compound (AZ10047130). This publication describes some characteristics of AZ10047130 and a systematic search for novel hits using a, human plasma-based, high-throughput screening (HTS) assay.

Discovery of agonists of cannabinoid receptor 1 with restricted central nervous system penetration aimed for treatment of gastroesophageal reflux disease.

Agonists of the cannabinoid receptor 1 (CB1) have been suggested as possible treatments for a range of medical disorders including gastroesophageal reflux disease (GERD). While centrally acting cannabinoid agonists are known to produce psychotropic effects, it has been suggested that the CB1 receptors in the periphery could play a significant role in reducing reflux. A moderately potent and highly lipophilic series of 2-aminobenzamides was identified through focused screening of GPCR libraries.

Pharmacodynamic-pharmacokinetic integration as a guide to medicinal chemistry.

A primary objective of pharmacokinetic-pharmacodynamic (PKPD) reasoning is to identify key in vivo drug and system proper¬ties, enabling prediction of the magnitude and time course of drug responses under physiological and pathological conditions in animals and man. Since the pharmacological response generated by a drug is highly dependent on the actual system used to study its action, knowledge about its potency and efficacy at a given concentration or dose is insufficient to obtain a proper understanding of its pharmacodynamic profile. Hence, the output of PKPD activities extends beyond the provision of quantitative measures (models) of results, to the design of future protocols.

Impact of input parameters on the prediction of hepatic plasma clearance using the well-stirred model.

The in vitro metabolic stability assays are indispensable for screening the metabolic liability of new chemical entities (NCEs) in drug discovery. Intrinsic clearance (CL(int)) values from liver microsomes and/or hepatocytes are frequently used to assess metabolic stability as well as to quantitatively predict in vivo hepatic plasma clearance (CL(H)). An often used approximation is the so called well-stirred model which has gained widespread use.

High-throughput pKa screening and prediction amenable for ADME profiling.

Recent technological advances have made it possible for several new pK(a) assays to be used in drug screening. In this review, a critical overview is provided of current new methodologies for high-throughput screening and prediction of pK(a). Typical applications of using pK(a )constants and charge state for absorption, distribution, metabolism and excretion (ADME) profiling and quantitative structure-activity relationship modelling complements the methodological comparisons and discussions.

Role of topology, nonadditivity, and water-mediated interactions in predicting the structures of alpha/beta proteins.

The folding of alpha/beta proteins involves most of the commonly known structural and dynamic complexities of the protein energy landscapes. Thus, the interplay among different structural components, taking into account the cooperative interactions, is important in determining the success of protein structure prediction. In this work we present further developments of our knowledge-based force field for alpha/beta proteins, introducing more realistic modeling of many-body interactions governing the folding of beta-sheets.

Dressed ion theory of size-asymmetric electrolytes: effective ionic charges and the decay length of screened Coulomb potential and pair correlations.

The effects of ionic size asymmetry on long-range electrostatic interactions in electrolyte solutions are investigated within the primitive model. Using the formalism of dressed ion theory we analyze correlation functions from Monte Carlo simulations and the hypernetted chain approximation for size asymmetric 1:1 electrolytes. We obtain decay lengths of the screened Coulomb potential, effective charges of ions, and effective permittivity of the solution.

Role of water mediated interactions in protein-protein recognition landscapes.

The energy landscape picture of protein folding and binding is employed to optimize a number of pair potentials for direct and water-mediated interactions in protein complex interfaces. We find that water-mediated interactions greatly complement direct interactions in discriminating against various types of trap interactions that model those present in the cell. We highlight the context dependent nature of knowledge-based binding potentials, as contrasted with the situation for autonomous folding.

Water in protein structure prediction.

Proteins have evolved to use water to help guide folding. A physically motivated, nonpairwise-additive model of water-mediated interactions added to a protein structure prediction Hamiltonian yields marked improvement in the quality of structure prediction for larger proteins. Free energy profile analysis suggests that long-range water-mediated potentials guide folding and smooth the underlying folding funnel.