Backbone alignment modeling of the structure-activity relationships of opioid ligands

Machine Learning Methods for Small Data Challenges in Molecular Science

Small data are often used in scientific and engineering research due to the presence of various constraints, such as time, cost, ethics, privacy, security, and technical limitations in data acquisition. However, big data have been the focus for the past decade, small data and their challenges have received little attention, even though they are technically more severe in machine learning (ML) and deep learning (DL) studies. Overall, the small data challenge is often compounded by issues, such as data diversity, imputation, noise, imbalance, and high-dimensionality. Fortunately, the current big data era is characterized by technological breakthroughs in ML, DL, and artificial intelligence (AI), which enable data-driven scientific discovery, and many advanced ML and DL technologies developed for big data have inadvertently provided solutions for small data problems. As a result, significant progress has been made in ML and DL for small data challenges in the past decade. In this review, we summarize and analyze several emerging potential solutions to small data challenges in molecular science, including chemical and biological sciences. We review both basic machine learning algorithms, such as linear regression, logistic regression (LR), k-nearest neighbor (KNN), support vector machine (SVM), kernel learning (KL), random forest (RF), and gradient boosting trees (GBT), and more advanced techniques, including artificial neural network (ANN), convolutional neural network (CNN), U-Net, graph neural network (GNN), Generative Adversarial Network (GAN), long short-term memory (LSTM), autoencoder, transformer, transfer learning, active learning, graph-based semi-supervised learning, combining deep learning with traditional machine learning, and physical model-based data augmentation. We also briefly discuss the latest advances in these methods. Finally, we conclude the survey with a discussion of promising trends in small data challenges in molecular science.

Exploiting Knowledge on Structure-Activity Relationships for Designing Peptidomimetics of Endogenous Peptides

Endogenous peptides are important mediators in cell communication, being consequently involved in many physiological processes. Their use as therapeutic agents is limited due to their poor pharmacokinetic profile. To circumvent this drawback, alternative diverse molecules based on the stereochemical features that confer their activity can be synthesized, using them as guidance; from peptide surrogates provided with a better pharmacokinetic profile, to small molecule peptidomimetics, through cyclic peptides. The design process requires a competent use of the structure-activity results available on individual peptides. Specifically, it requires synthesis and analysis of the activity of diverse analogs, biophysical information and computational work. In the present work, we show a general framework of the process and show its application to two specific examples: the design of selective AT1 antagonists of angiotensin and the design of selective B2 antagonists of bradykinin.

Multifunctional Enkephalin Analogs with a New Biological Profile: MOR/DOR Agonism and KOR Antagonism

In our previous studies, we developed a series of mixed MOR/DOR agonists that are enkephalin-like tetrapeptide analogs with an N-phenyl-N-piperidin-4-ylpropionamide (Ppp) moiety at the C-terminus. Further SAR study on the analogs, initiated by the findings from off-target screening, resulted in the discovery of LYS744 (6, Dmt-DNle-Gly-Phe(p-Cl)-Ppp), a multifunctional ligand with MOR/DOR agonist and KOR antagonist activity (GTPγS assay: IC₅₀ = 52 nM, I_max = 122% cf. IC₅₀ = 59 nM, I_max = 100% for naloxone) with nanomolar range of binding affinity (K_i = 1.3 nM cf. K_i = 2.4 nM for salvinorin A). Based on its unique biological profile, 6 is considered to possess high therapeutic potential for the treatment of chronic pain by modulating pathological KOR activation while retaining analgesic efficacy attributed to its MOR/DOR agonist activity.

Toward a Universal μ-Agonist Template for Template-Based Alignment Modeling of Opioid Ligands

Opioid ligands are a large group of G-protein-coupled receptor ligands possessing high structural diversity, along with complicated structure-activity relationships (SARs). To better understand their structural correlations as well as the related SARs, we developed the innovative template-based alignment modeling in our recent studies on a variety of opioid ligands. As previously reported, this approach showed promise but also with limitations, which was mainly attributed to the small size of morphine as a template. With this study, we set out to construct an artificial μ-agonist template to overcome this limitation. The newly constructed template contained a largely extended scaffold, along with a few special μ-features relevant to the μ-selectivity of opioid ligands. As demonstrated in this paper, the new template showed significantly improved efficacy in facilitating the alignment modeling of a wide variety of opioid ligands. This report comprises of two main parts. Part 1 discusses the general construction process and the structural features as well as a few typical examples of the template applications and Part 2 focuses on the template refinement and validation.

Design synthesis and structure-activity relationship of 5-substituted (tetrahydronaphthalen-2yl)methyl with N-phenyl-N-(piperidin-2-yl)propionamide derivatives as opioid ligands

Here, we report the design, synthesis and structure activity relationship of novel small molecule opioid ligands based on 5-amino substituted (tetrahydronaphthalen-2-yl)methyl moiety with N-phenyl-N-(piperidin-2-yl)propionamide derivatives. We synthesized various molecules including amino, amide and hydroxy substitution on the 5th position of the (tetrahydronaphthalen-2-yl)methyl moiety. In our further designs we replaced the (tetrahydronaphthalen-2-yl)methyl moiety with benzyl and phenethyl moiety. These N-phenyl-N-(piperidin-2-yl)propionamide analogues showed moderate to good binding affinities (850-4 nM) and were selective towards the μ opioid receptor over the δ opioid receptors. From the structure activity relationship studies, we found that a hydroxyl substitution at the 5th position of (tetrahydronapthalen-2yl)methyl group, ligands 19 and 20, showed excellent binding affinities 4 and 5 nM, respectively, and 1000 fold selectivity towards the μ opioid relative to the delta opioid receptor. The ligand 19 showed potent agonist activities 75±21 nM, and 190±42 nM in the GPI and MVD assays. Surprisingly the fluoro analogue 20 showed good agonist activities in MVD assays 170±42 nM, in contrast to its binding affinity results.

Histamine-releasing and allergenic properties of opioid analgesic drugs: resolving the two

Opioid analgesics are amongst the most commonly administered drugs in hospitals. Whether natural or synthetic, they show some common structural features, morphine-like pharmacological action and binding specificity for complementary opioid receptors. Tramadol differs from the other opioid analgesics in possessing monoaminergic activity in addition to its affinity for the µ opioid receptor. Many opioids are potent histamine releasers producing a variety of haemodynamic changes and anaphylactoid reactions, but the relationship of the appearance of these effects to the histamine plasma concentration is complex and there is no direct and invariable relationship between the two. Studies of the histamine-releasing effects, chiefly centred on morphine, reveal variable findings and conclusions often due to a range of factors including differences in technical measurements, dose, mode of administration, site of injection, the anatomical distribution of histamine receptors and heterogeneity of patient responses. Morphine itself has multiple direct effects on the vasculature and other haemodynamically-active mediators released along with histamine contribute to the variable responses to opioid drug administration. Despite their heavy use and occasional apparent anaphylactic-like side-effects, immunoglobulin E antibody-mediated immediate hypersensitivity reactions to the drugs are not often encountered. Uncertainties associated with skin testing with these known histamine-releasers, and the general unavailability of opioid drug-specific immunoglobulin E antibody tests contribute to the frequent failure to adequately investigate and establish underlying mechanisms of reactions by distinguishing anaphylactoid from true anaphylactic reactions. Clinical implications for diagnosis of reactions and some speculations on the rarity of true Type 1 allergies to these drugs are presented.