Dual protein kinase and nucleoside kinase modulators for rationally designed polypharmacology

PIDiff: Physics informed diffusion model for protein pocket-specific 3D molecular generation

Designing drugs capable of binding to the structure of target proteins for treating diseases is essential in drug development. Recent remarkable advancements in geometric deep learning have led to unprecedented progress in three-dimensional (3D) generation of ligands that can bind to the protein pocket. However, most existing methods primarily focus on modeling the geometric information of ligands in 3D space. Consequently, these methods fail to consider that the binding of proteins and ligands is a phenomenon driven by intrinsic physicochemical principles. Motivated by this understanding, we propose PIDiff, a model for generating molecules by accounting in the physicochemical principles of protein-ligand binding. Our model learns not only the structural information of proteins and ligands but also to minimize the binding free energy between them. To evaluate the proposed model, we introduce an experimental framework that surpasses traditional assessment methods by encompassing various essential aspects for the practical application of generative models to actual drug development. The results confirm that our model outperforms baseline models on the CrossDocked2020 benchmark dataset, demonstrating its superiority. Through diverse experiments, we have illustrated the promising potential of the proposed model in practical drug development.

Poly-pharmacology of existing drugs: How to crack the code?

Drug development in oncology is highly challenging, with less than 5% success rate in clinical trials. This alarming figure points out the need to study in more details the multiple biological effects of drugs in specific contexts. Indeed, the comprehensive assessment of drug poly-pharmacology can provide insights into their therapeutic and adverse effects, to optimize their utilization and maximize the success rate of clinical trials. Recent technological advances have made possible in-depth investigation of drug poly-pharmacology. This review first highlights high-throughput methodologies that have been used to unveil new mechanisms of action of existing drugs. Then, we discuss how emerging chemo-proteomics strategies allow effectively dissecting the poly-pharmacology of drugs in an unsupervised manner.

Chemical Characterization, DNA-Damage Protection, Antiproliferative Activity and in Silico Studies of the Essential Oils from Perralderia coronopifolia Coss

In this study, for the first time, we analyzed the chemical composition of essential oils (EOs) steam-distilled from the flowers and leaves of Perralderia coronopifolia by GC-FID/MS. The objective was to explore new anticancer and antioxidant bioactive substances and understand their mechanisms of action through the use of plant-derived natural products. The major chemical components characterizing the EOs were cis-chrysanthenyl acetate 1, 6-oxocyclonerolidol 2, cis-8-acetoxychrysanthenyl acetate 3, and 6α-hydroxycyclonerolidol 4, respectively. Furthermore, the EOs inhibited cell proliferation in HeLa (human cervix carcinoma) and PC3 (human prostate cancer) cells and protected plasmid DNA from oxidative damage caused by UV-photolyzed H2 O2 . Employing a molecular docking study, we elucidated the main compounds' inhibition mechanisms. Consequently, the antitumor activity could be related to the inhibitory property of compound 3 against CDC25B phosphatase. The evaluation of ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties and the density functional theory (DFT) calculations of the major compounds, especially compound 3, offer potential insights for designing and developing new cancer drug candidates. In conclusion, our study provides a framework for future research and development in the field by establishing a scientific foundation for the use of Perralderia coronopifolia essential oils as a prospective source of antioxidant and anticancer agents.

On the origins of SARS-CoV-2 main protease inhibitors

In order to address the world-wide health challenge caused by the COVID-19 pandemic, the 3CL protease/SARS-CoV-2 main protease (SARS-CoV-2-Mpro) coded by its nsp5 gene became one of the biochemical targets for the design of antiviral drugs. In less than 3 years of research, 4 inhibitors of SARS-CoV-2-Mpro have actually been authorized for COVID-19 treatment (nirmatrelvir, ensitrelvir, leritrelvir and simnotrelvir) and more such as EDP-235, FB-2001 and STI-1558/Olgotrelvir or five undisclosed compounds (CDI-988, ASC11, ALG-097558, QLS1128 and H-10517) are undergoing clinical trials. This review is an attempt to picture this quite unprecedented medicinal chemistry feat and provide insights on how these cysteine protease inhibitors were discovered. Since many series of covalent SARS-CoV-2-Mpro inhibitors owe some of their origins to previous work on other proteases, we first provided a description of various inhibitors of cysteine-bearing human caspase-1 or cathepsin K, as well as inhibitors of serine proteases such as human dipeptidyl peptidase-4 or the hepatitis C protein complex NS3/4A. This is then followed by a description of the results of the approaches adopted (repurposing, structure-based and high throughput screening) to discover coronavirus main protease inhibitors.

Death by a thousand cuts through kinase inhibitor combinations that maximize selectivity and enable rational multitargeting

Kinase inhibitors are successful therapeutics in the treatment of cancers and autoimmune diseases and are useful tools in biomedical research. However, the high sequence and structural conservation of the catalytic kinase domain complicate the development of selective kinase inhibitors. Inhibition of off-target kinases makes it difficult to study the mechanism of inhibitors in biological systems. Current efforts focus on the development of inhibitors with improved selectivity. Here, we present an alternative solution to this problem by combining inhibitors with divergent off-target effects. We develop a multicompound-multitarget scoring (MMS) method that combines inhibitors to maximize target inhibition and to minimize off-target inhibition. Additionally, this framework enables optimization of inhibitor combinations for multiple on-targets. Using MMS with published kinase inhibitor datasets we determine potent inhibitor combinations for target kinases with better selectivity than the most selective single inhibitor and validate the predicted effect and selectivity of inhibitor combinations using in vitro and in cellulo techniques. MMS greatly enhances selectivity in rational multitargeting applications. The MMS framework is generalizable to other non-kinase biological targets where compound selectivity is a challenge and diverse compound libraries are available.

Therapies from Thiopeptides

The first part of this contribution describes solutions that were developed to achieve progressively more efficient syntheses of the thiopeptide natural products, micrococcins P1 and P2 (MP1-MP2), with an eye toward exploring their potential as a source of new antibiotics. Such efforts enabled investigations on the medicinal chemistry of those antibiotics, and inspired the development of the kinase inhibitor, Masitinib®, two candidate oncology drugs, and new antibacterial agents. The studies that produced such therapeutic resources are detailed in the second part. True to the theme of this issue, "Organic Synthesis and Medicinal Chemistry: Two Inseparable Partners", an important message is that the above advances would have never materialized without the support of curiosity-driven, academic synthetic organic chemistry: a beleaguered science that nonetheless has been-and continues to be-instrumental to progress in the biomedical field.

From a drug repositioning to a structure-based drug design approach to tackle acute lymphoblastic leukemia

Cancer cells utilize the main de novo pathway and the alternative salvage pathway for deoxyribonucleotide biosynthesis to achieve adequate nucleotide pools. Deoxycytidine kinase is the rate-limiting enzyme of the salvage pathway and it has recently emerged as a target for anti-proliferative therapies for cancers where it is essential. Here, we present the development of a potent inhibitor applying an iterative multidisciplinary approach, which relies on computational design coupled with experimental evaluations. This strategy allows an acceleration of the hit-to-lead process by gradually implementing key chemical modifications to increase affinity and activity. Our lead compound, OR0642, is more than 1000 times more potent than its initial parent compound, masitinib, previously identified from a drug repositioning approach. OR0642 in combination with a physiological inhibitor of the de novo pathway doubled the survival rate in a human T-cell acute lymphoblastic leukemia patient-derived xenograft mouse model, demonstrating the proof-of-concept of this drug design strategy.

A novel strategy for designing the magic shotguns for distantly related target pairs

Due to its promising capacity in improving drug efficacy, polypharmacology has emerged to be a new theme in the drug discovery of complex disease. In the process of novel multi-target drugs (MTDs) discovery, in silico strategies come to be quite essential for the advantage of high throughput and low cost. However, current researchers mostly aim at typical closely related target pairs. Because of the intricate pathogenesis networks of complex diseases, many distantly related targets are found to play crucial role in synergistic treatment. Therefore, an innovational method to develop drugs which could simultaneously target distantly related target pairs is of utmost importance. At the same time, reducing the false discovery rate in the design of MTDs remains to be the daunting technological difficulty. In this research, effective small molecule clustering in the positive dataset, together with a putative negative dataset generation strategy, was adopted in the process of model constructions. Through comprehensive assessment on 10 target pairs with hierarchical similarity-levels, the proposed strategy turned out to reduce the false discovery rate successfully. Constructed model types with much smaller numbers of inhibitor molecules gained considerable yields and showed better false-hit controllability than before. To further evaluate the generalization ability, an in-depth assessment of high-throughput virtual screening on ChEMBL database was conducted. As a result, this novel strategy could hierarchically improve the enrichment factors for each target pair (especially for those distantly related/unrelated target pairs), corresponding to target pair similarity-levels.

Is Monitoring of the Intracellular Active Metabolite Levels of Nucleobase and Nucleoside Analogs Ready for Precision Medicine Applications?

Nucleobase and nucleoside analogs (NAs) play important roles in cancer therapy. Although there are obvious individual differences in NA treatments, most NAs lack direct relationships between their plasma concentration and efficacy or adverse effects. Accumulating evidence suggests that the intracellular active metabolite levels of NAs predict patient outcomes. This article reviewed the relationships between NA intracellular active metabolite levels and their efficacy or adverse effects. The factors affecting the formation of intracellular active metabolites and combination regimens that elevate intracellular active metabolite levels were also reviewed. Given the mechanism of NA cytotoxicity, NA intracellular active metabolite levels may be predictive of clinical outcomes. Many clinical studies support this hypothesis. Therefore, the monitoring of intracellular active metabolite levels is beneficial for individualized NA treatment. However, to perform clinical monitoring in practice, well-designed studies are needed to explore the optimal threshold or range and the appropriate regimen adjustment strategies based on these parameters.

Design, synthesis and antitumor activity study of a gemcitabine prodrug conjugated with a HDAC6 inhibitor

Gemcitabine, as a first-line antitumor drug, has attracted extensive attention. However the occurrence of drug resistance limits its clinical utilization. In this paper, a gemcitabine prodrug GZ was designed and synthesized by conjugation of gemcitabine with a newly reported HDAC6 selective inhibitor pentadecanoic acid. GZ displayed high cytotoxicity to nine cancer cell lines with IC₅₀ values in the low micromolar range. In vivo, GZ displayed superior antitumor activity to gemcitabine in a 4T1 tumor xenograft model without obvious pathological damage to important organs of mice. Our study showed that compound GZ is a potential gemcitabine prodrug, which is worthy of further antitumor activity exploration.

Evolution of kinase polypharmacology across HSP90 drug discovery

Most small molecules interact with several target proteins but this polypharmacology is seldom comprehensively investigated or explicitly exploited during drug discovery. Here, we use computational and experimental methods to identify and systematically characterize the kinase cross-pharmacology of representative HSP90 inhibitors. We demonstrate that the resorcinol clinical candidates ganetespib and, to a lesser extent, luminespib, display unique off-target kinase pharmacology as compared with other HSP90 inhibitors. We also demonstrate that polypharmacology evolved during the optimization to discover luminespib and that the hit, leads, and clinical candidate all have different polypharmacological profiles. We therefore recommend the computational and experimental characterization of polypharmacology earlier in drug discovery projects to unlock new multi-target drug design opportunities.

In vitro biolayer interferometry analysis of acetylcholinesterase as a potential target of aryl-organophosphorus flame-retardants

Organophosphorus flame retardants (OPFRs) have been implicated as neurotoxicants, but their potential neurotoxicity and mechanisms remain poorly understood. Herein, we investigated the neurotoxicity of selected OPFRs using zebrafish as a model organism. Environmentally relevant concentrations (3-1500 nM) of three classes of OPFRs (aryl-OPFRs, chlorinated-OPFRs, and alkyl-OPFRs) were tested in zebrafish larvae (2-144 h post-fertilisation) alongside the neurotoxic chemical chlorpyrifos (CPF) that inhibits acetylcholinesterase (AChE). Exposure to aryl-OPFRs and CPF inhibited AChE activities, while chlorinated- and alkyl-OPFRs did not inhibit these enzymes. Biolayer interferometry (BLI) was used to probe interactions between OPFRs and AChE. The association and dissociation response curves showed that, like CPF, all three selected aryl-OPFRs, triphenyl phosphate (TPHP), tricresyl phosphate (TCP) and cresyl diphenyl phosphate (CDP), bound directly to AChE. The affinity constant (K_D) for TPHP, TCP, CDP and CPF was 2.18 × 10^-4, 5.47 × 10^-5, 1.05 × 10^-4 and 1.70 × 10^-5 M, respectively. In addition, molecular docking revealed that TPHP, TCP, CDP and CPF bound to AChE with glide scores of - 7.8, - 8.3, - 8.1 and - 7.3, respectively. Furthermore, the calculated binding affinity between OPFRs and AChE correlated well with the K_D values measured by BLI. The present study revealed that aryl-OPFRs can act as potent AChE inhibitors, and may therefore present a significant ecological risk to aquatic organisms.

The high-energy transition state of the glutamate transporter homologue GltPh

Membrane transporters mediate cellular uptake of nutrients, signaling molecules, and drugs. Their overall mechanisms are often well understood, but the structural features setting their rates are mostly unknown. Earlier single-molecule fluorescence imaging of the archaeal model glutamate transporter homologue GltPh from Pyrococcus horikoshii suggested that the slow conformational transition from the outward- to the inward-facing state, when the bound substrate is translocated from the extracellular to the cytoplasmic side of the membrane, is rate limiting to transport. Here, we provide insight into the structure of the high-energy transition state of GltPh that limits the rate of the substrate translocation process. Using bioinformatics, we identified GltPh gain-of-function mutations in the flexible helical hairpin domain HP2 and applied linear free energy relationship analysis to infer that the transition state structurally resembles the inward-facing conformation. Based on these analyses, we propose an approach to search for allosteric modulators for transporters.

An up-to-date overview of computational polypharmacology in modern drug discovery

INTRODUCTION

In recent years, computational polypharmacology has gained significant attention to study the promiscuous nature of drugs. Despite tremendous challenges, community-wide efforts have led to a variety of novel approaches for predicting drug polypharmacology. In particular, some rapid advances using machine learning and artificial intelligence have been reported with great success.

AREAS COVERED

In this article, the authors provide a comprehensive update on the current state-of-the-art polypharmacology approaches and their applications, focusing on those reports published after our 2017 review article. The authors particularly discuss some novel, groundbreaking concepts, and methods that have been developed recently and applied to drug polypharmacology studies.

EXPERT OPINION

Polypharmacology is evolving and novel concepts are being introduced to counter the current challenges in the field. However, major hurdles remain including incompleteness of high-quality experimental data, lack of in vitro and in vivo assays to characterize multi-targeting agents, shortage of robust computational methods, and challenges to identify the best target combinations and design effective multi-targeting agents. Fortunately, numerous national/international efforts including multi-omics and artificial intelligence initiatives as well as most recent collaborations on addressing the COVID-19 pandemic have shown significant promise to propel the field of polypharmacology forward.

Targeting Casein Kinase 1 Delta Sensitizes Pancreatic and Bladder Cancer Cells to Gemcitabine Treatment by Upregulating Deoxycytidine Kinase

Although gemcitabine is the cornerstone of care for pancreatic ductal adenocarcinoma (PDA), patients lack durable responses and relapse is inevitable. While the underlying mechanisms leading to gemcitabine resistance are likely to be multifactorial, there is a strong association between activating gemcitabine metabolism pathways and clinical outcome. This study evaluated casein kinase 1 delta (CK1δ) as a potential therapeutic target for PDA and bladder cancer, in which CK1δ is frequently overexpressed. We assessed the antitumor effects of genetically silencing or pharmacologically inhibiting CK1δ using our in-house CK1δ small-molecule inhibitor SR-3029, either alone or in combination with gemcitabine, on the proliferation and survival of pancreatic and bladder cancer cell lines and orthotopic mouse models. Genetic studies confirmed that silencing CK1δ or treatment with SR-3029 induced a significant upregulation of deoxycytidine kinase (dCK), a rate-limiting enzyme in gemcitabine metabolite activation. The combination of SR-3029 with gemcitabine induced synergistic antiproliferative activity and enhanced apoptosis in both pancreatic and bladder cancer cells. Furthermore, in an orthotopic pancreatic tumor model, we observed improved efficacy with combination treatment concomitant with increased dCK expression. This study demonstrates that CK1δ plays a role in gemcitabine metabolism, and that the combination of CK1δ inhibition with gemcitabine holds promise as a future therapeutic option for metastatic PDA as well as other cancers with upregulated CK1δ expression.

From basic research to the clinic: innovative therapies for ALS and FTD in the pipeline

Amyotrophic lateral sclerosis (ALS) and Frontotemporal Degeneration (FTD) are neurodegenerative disorders, related by deterioration of motor and cognitive functions and short survival. Aside from cases with an inherited pathogenic mutation, the causes of the disorders are still largely unknown and no effective treatment currently exists. It has been shown that FTD may coexist with ALS and this overlap occurs at clinical, genetic, and molecular levels. In this work, we review the main pathological aspects of these complex diseases and discuss how the integration of the novel pathogenic molecular insights and the analysis of molecular interaction networks among all the genetic players represents a critical step to shed light on discovering novel therapeutic strategies and possibly tailoring personalized medicine approaches to specific ALS and FTD patients.

Molecular Mechanisms of TDP-43 Misfolding and Pathology in Amyotrophic Lateral Sclerosis

TAR DNA binding protein 43 (TDP-43) is a versatile RNA/DNA binding protein involved in RNA-related metabolism. Hyper-phosphorylated and ubiquitinated TDP-43 deposits act as inclusion bodies in the brain and spinal cord of patients with the motor neuron diseases: amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). While the majority of ALS cases (90-95%) are sporadic (sALS), among familial ALS cases 5-10% involve the inheritance of mutations in the TARDBP gene and the remaining (90-95%) are due to mutations in other genes such as: C9ORF72, SOD1, FUS, and NEK1 etc. Strikingly however, the majority of sporadic ALS patients (up to 97%) also contain the TDP-43 protein deposited in the neuronal inclusions, which suggests of its pivotal role in the ALS pathology. Thus, unraveling the molecular mechanisms of the TDP-43 pathology seems central to the ALS therapeutics, hence, we comprehensively review the current understanding of the TDP-43's pathology in ALS. We discuss the roles of TDP-43's mutations, its cytoplasmic mis-localization and aberrant post-translational modifications in ALS. Also, we evaluate TDP-43's amyloid-like in vitro aggregation, its physiological vs. pathological oligomerization in vivo, liquid-liquid phase separation (LLPS), and potential prion-like propagation propensity of the TDP-43 inclusions. Finally, we describe the various evolving TDP-43-induced toxicity mechanisms, such as the impairment of endocytosis and mitotoxicity etc. and also discuss the emerging strategies toward TDP-43 disaggregation and ALS therapeutics.