Challenges in Discovering Drugs That Target the Protein-Protein Interactions of Disordered Proteins

Drug repurposing based on the DTD-GNN graph neural network: revealing the relationships among drugs, targets and diseases

MOTIVATION

The rational modelling of the relationship among drugs, targets and diseases is crucial for drug retargeting. While significant progress has been made in studying binary relationships, further research is needed to deepen our understanding of ternary relationships. The application of graph neural networks in drug retargeting is increasing, but further research is needed to determine the appropriate modelling method for ternary relationships and how to capture their complex multi-feature structure.

RESULTS

The aim of this study was to construct relationships among drug, targets and diseases. To represent the complex relationships among these entities, we used a heterogeneous graph structure. Additionally, we propose a DTD-GNN model that combines graph convolutional networks and graph attention networks to learn feature representations and association information, facilitating a more thorough exploration of the relationships. The experimental results demonstrate that the DTD-GNN model outperforms other graph neural network models in terms of AUC, Precision, and F1-score. The study has important implications for gaining a comprehensive understanding of the relationships between drugs and diseases, as well as for further research and application in exploring the mechanisms of drug-disease interactions. The study reveals these relationships, providing possibilities for innovative therapeutic strategies in medicine.

Macrocycles and macrocyclization in anticancer drug discovery: Important pieces of the puzzle

Increasing disease-related proteins have been identified as novel therapeutic targets. Macrocycles are emerging as potential solutions, bridging the gap between conventional small molecules and biomacromolecules in drug discovery. Inspired by successful macrocyclic drugs of natural origins, macrocycles are attracting more attention for enhanced binding affinity and target selectivity. Due to the conformation constraint and structure preorganization, macrocycles can reach bioactive conformations more easily than parent acyclic compounds. Also, rational macrocyclization combined with sequent structural modification will help improve oral bioavailability and combat drug resistance. This review introduces various strategies to enhance membrane permeability in macrocyclization and subsequent modification, such as N-methylation, intramolecular hydrogen bonding modulation, isomerization, and reversible bicyclization. Several case studies highlight macrocyclic inhibitors targeting kinases, HDAC, and protein-protein interactions. Finally, some macrocyclic agents targeting tumor microenvironments are illustrated.

Investigation of steric hindrance effect on the interactions between four alkaloids and HSA by isothermal titration calorimetry and molecular docking

The binding of four alkaloids with human serum albumin (HSA) was investigated by isothermal titration calorimetry (ITC), spectroscopy and molecular docking techniques. The findings demonstrated that theophylline or caffeine can bind to HAS, respectively. The number of binding sites and binding constants are obtained. The binding mode is a static quenching process. The effects of steric hindrance, temperature, salt concentration and buffer solution on the binding indicated that theophylline and HSA have higher binding affinity than caffeine. The fluorescence and ITC results showed that the interaction between HSA and theophylline or caffeine is an entropy-driven spontaneous exothermic process. The hydrophobic force was the primary driving factor. The experimental results were consistent with the molecular docking data. Based on the molecular structures of the four alkaloids, steric hindrance might be a major factor in the binding between HSA and these four alkaloids. This study elucidates the mechanism of interactions between four alkaloids and HSA.

Advances in RNA therapeutics for modulation of 'undruggable' targets

Over the past decades, drug discovery utilizing small pharmacological compounds, fragment-based therapeutics, and antibody therapy have significantly advanced treatment options for many human diseases. However, a major bottleneck has been that>70% of human proteins/genomic regions are 'undruggable' by the above-mentioned approaches. Many of these proteins constitute essential drug targets against complex multifactorial diseases like cancer, immunological disorders, and neurological diseases. Therefore, alternative approaches are required to target these proteins or genomic regions in human cells. RNA therapeutics is a promising approach for many of the traditionally 'undruggable' targets by utilizing methods such as antisense oligonucleotides, RNA interference, CRISPR/Cas-based genome editing, aptamers, and the development of mRNA therapeutics. In the following chapter, we will put emphasis on recent advancements utilizing these approaches against challenging drug targets, such as intranuclear proteins, intrinsically disordered proteins, untranslated genomic regions, and targets expressed in inaccessible tissues.

The C-terminal tail of CSNAP attenuates the CSN complex

Protein degradation is one of the essential mechanisms that enables reshaping of the proteome landscape in response to various stimuli. The largest E3 ubiquitin ligase family that targets proteins to degradation by catalyzing ubiquitination is the cullin-RING ligases (CRLs). Many of the proteins that are regulated by CRLs are central to tumorigenesis and tumor progression, and dysregulation of the CRL family is frequently associated with cancer. The CRL family comprises ∼300 complexes, all of which are regulated by the COP9 signalosome complex (CSN). Therefore, CSN is considered an attractive target for therapeutic intervention. Research efforts for targeted CSN inhibition have been directed towards inhibition of the complex enzymatic subunit, CSN5. Here, we have taken a fresh approach focusing on CSNAP, the smallest CSN subunit. Our results show that the C-terminal region of CSNAP is tightly packed within the CSN complex, in a groove formed by CSN3 and CSN8. We show that a 16 amino acid C-terminal peptide, derived from this CSN-interacting region, can displace the endogenous CSNAP subunit from the complex. This, in turn, leads to a CSNAP null phenotype that attenuates CSN activity and consequently CRLs function. Overall, our findings emphasize the potential of a CSNAP-based peptide for CSN inhibition as a new therapeutic avenue.

Gibbs Energy and Gene Expression Combined as a New Technique for Selecting Drug Targets for Inhibiting Specific Protein-Protein Interactions

One of the most important aspects of successful cancer therapy is the identification of a target protein for inhibition interaction. Conventionally, this consists of screening a panel of genes to assess which is mutated and then developing a small molecule to inhibit the interaction of two proteins or to simply inhibit a specific protein from all interactions. In previous work, we have proposed computational methods that analyze protein-protein networks using both topological approaches and thermodynamic quantification provided by Gibbs free energy. In order to make these approaches both easier to implement and free of arbitrary topological filtration criteria, in the present paper, we propose a modification of the topological-thermodynamic analysis, which focuses on the selection of the most thermodynamically stable proteins and their subnetwork interaction partners with the highest expression levels. We illustrate the implementation of the new approach with two specific cases, glioblastoma (glioma brain tumors) and chronic lymphatic leukoma (CLL), based on the publicly available patient-derived datasets. We also discuss how this can be used in clinical practice in connection with the availability of approved and investigational drugs.

Focusing on oligomeric tau as a therapeutic target in Alzheimer's disease and other tauopathies

INTRODUCTION

Tau has commanded much attention as a potential therapeutic target in neurodegenerative diseases. Tau pathology is a hallmark of primary tauopathies, such as progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), and subtypes of frontotemporal dementia (FTD), as well as secondary tauopathies, such as Alzheimer's disease (AD). The development of tau therapeutics must reconcile with the structural complexity of the tau proteome, as well as an incomplete understanding of the role of tau in both physiology and disease.

AREAS COVERED

This review offers a current perspective on tau biology, discusses key barriers to the development of effective tau-based therapeutics, and promotes the idea that pathogenic (as opposed to merely pathological) tau should be at the center of drug development efforts.

EXPERT OPINION

An efficacious tau therapeutic will exhibit several primary features: 1) selectivity for pathogenic tau versus other tau species; 2) blood-brain barrier and cell membrane permeability, enabling access to intracellular tau in disease-relevant brain regions; and 3) minimal toxicity. Oligomeric tau is proposed as a major pathogenic form of tau and a compelling drug target in tauopathies.

The structure and function of YTHDF epitranscriptomic m6A readers

Specific RNA sequences modified by a methylated adenosine, N⁶-methyladenosine (m⁶A), contribute to the post-transcriptional regulation of gene expression. The quantity of m⁶A in RNA is orchestrated by enzymes that write and erase it, while its effects are mediated by proteins that bind to read this modification. Dysfunction of this post-transcriptional regulatory process has been linked to human disease. Although the initial focus has been on pharmacological targeting of the writer and eraser enzymes, interest in the reader proteins has been challenged by a lack of clear understanding of their functional roles and molecular mechanisms of action. Readers of m⁶A-modified RNA (m⁶A-RNA) - the YTH (YT521-B homology) domain-containing protein family paralogs 1-3 (YTHDF1-3, referred to here as DF1-DF3) - are emerging as therapeutic targets as their links to pathological processes such as cancer and inflammation and their roles in regulating m⁶A-RNA fate become clear. We provide an updated understanding of the modes of action of DF1-DF3 and review their structures to unlock insights into drug design approaches for DF paralog-selective inhibition.

Targeting Olokizumab-Interleukin 6 interaction interface to discover novel IL-6 inhibitors

The IL-6/IL-6R or IL-6/GP130 protein-protein interactions play a significant role in controlling the development of chronic inflammatory diseases, such as rheumatoid arthritis, Castleman disease, psoriasis, and, most recently, COVID-19. Modulating or antagonizing protein-protein interactions of IL6 binding to its receptors by oral drugs promises similar efficacy to biological therapy in patients, namely monoclonal antibodies. In this study, we used a crystal structure of the Fab part of olokizumab in a complex with IL-6 (PDB ID: 4CNI) to uncover starting points for small molecule IL-6 antagonist discovery. Firstly, a structure‑based pharmacophore model of the protein active site cavity was generated to identify possible candidates, followed by virtual screening with a significant database Drugbank. After the docking protocol validation, a virtual screening by molecular docking was carried out and a total of 11 top hits were reported. Detailed analysis of the best scoring molecules was performed with ADME/T analysis and molecular dynamics simulation. Furthermore, the Molecular Mechanics-Generalized Born Surface Area (MM/GBSA) technique has been utilized to evaluate the free binding energy. Based on the finding, one newly obtained compound in this study, namely DB15187, may serve as a lead compound for the discovery of IL-6 inhibitors.Communicated by Ramaswamy H. Sarma.

Structural Adaptation of the Single-Stranded DNA-Binding Protein C-Terminal to DNA Metabolizing Partners Guides Inhibitor Design

Single-stranded DNA-binding protein (SSB) is a bacterial interaction hub and an appealing target for antimicrobial therapy. Understanding the structural adaptation of the disordered SSB C-terminus (SSB-Ct) to DNA metabolizing enzymes (e.g., ExoI and RecO) is essential for designing high-affinity SSB mimetic inhibitors. Molecular dynamics simulations revealed the transient interactions of SSB-Ct with two hot spots on ExoI and RecO. The residual flexibility of the peptide-protein complexes allows adaptive molecular recognition. Scanning with non-canonical amino acids revealed that modifications at both termini of SSB-Ct could increase the affinity, supporting the two-hot-spot binding model. Combining unnatural amino acid substitutions on both segments of the peptide resulted in enthalpy-enhanced affinity, accompanied by enthalpy-entropy compensation, as determined by isothermal calorimetry. NMR data and molecular modeling confirmed the reduced flexibility of the improved affinity complexes. Our results highlight that the SSB-Ct mimetics bind to the DNA metabolizing targets through the hot spots, interacting with both of segments of the ligands.

Targeting peptide-mediated interactions in omics

Peptide-mediated interactions (PMIs) play a crucial role in cell signaling network, which are responsible for about half of cellular protein-protein associations in the human interactome and have recently been recognized as a new kind of promising druggable target for drug development and disease therapy. In this article, we give a systematic review regarding the proteome-wide discovery of PMIs and targeting druggable PMIs (dPMIs) with chemical drugs, self-inhibitory peptides (SIPs) and protein agents, particularly focusing on their implications and applications for therapeutic purpose in omics. We also introduce computational peptidology strategies used to model, analyze, and design PMI-targeted molecular entities and further extend the concepts of protein context, direct/indirect readout, and enthalpy/entropy effect involved in PMIs. Current issues and future perspective on this topic are discussed. There is still a long way to go before establishment of efficient therapeutic strategies to target PMIs on the omics scale.

Investigating the Effect of Tyrosine Kinase Inhibitors on the Interaction between Human Serum Albumin by Atomic Force Microscopy

It is important for elucidating the regulation mechanism of life activities, as well as for the prevention, diagnosis, and drug design of diseases, to study protein–protein interactions (PPIs). Here, we investigated the interactions of human serum albumin (HSA) in the presence of tyrosine kinase inhibitors (TKIs: imatinib, nilotinib, dasatinib, bosutinib, and ponatinib) using atomic force microscopy (AFM). The distribution of rupture events including the specific interaction force F_i and the non-specific interaction force F₀ between HSA pairs was analyzed. Based on the force measurements, F_i and F₀ between HSA pairs in the control experiment were calculated to be 47 ± 1.5 and 116.1 ± 1.3 pN. However, F_i was significantly decreased in TKIs, while F₀ was slightly decreased. By measuring the rupture forces at various loading rates and according to the Bell equation, the kinetic parameters of the complexes were investigated in greater detail. Molecular docking was used as a complementary means by which to explore the force of this effect. The whole measurements indicated that TKIs influenced PPIs in a variety of ways, among which hydrogen bonding and hydrophobic interactions were the most important. In conclusion, these outcomes give us a better insight into the mechanisms of PPIs when there are exogenous compounds present as well as in different liquid environments.