Preomic profile of BxPC-3 cells after treatment with BRC4

BRCA2 and RAD51 are two proteins that play a central role in homologous recombination (HR) and DNA double strand break (DSB) repair. BRCA2 assists RAD51 fibrillation and defibrillation through binding with its eight BRC repeats, with BRC4 being one of the most efficient and best characterized. RAD51 inactivation by small molecules has been proposed as a strategy to impair BRCA2/RAD51 binding and, ultimately, the HR pathway, with the aim of making cancer cells more sensitive to PARP inhibitors (PARPi). This strategy, which mimics a synthetic lethality (SL) approach, has been successfully performed in vitro by using the myristoylated derivative of BRC4 (myr-BRC4), designed for a more efficient cell entry. The present study applies a method to obtain a proteomic fingerprint after cellular treatment with the myr-BRC4 peptide using a mass spectroscopy (MS) proteomic approach. (Data are available via ProteomeXchange with identifier PXD042696.) We performed a comparative proteomic profiling of the myr-BRC4 treated vs. untreated BxPC-3 pancreatic cancer cells and evaluated the differential expression of proteins. Among the identified proteins, we focused our attention on proteins shared by both the RAD51 and the BRCA2 interactomes, and on those whose reduction showed high statistical significance. Three downregulated proteins were identified (FANCI, FANCD2, and RPA3), and protein downregulation was confirmed through immunoblotting analysis, validating the MS approach. Our results suggest that, being a direct consequence of myr-BRC4 treatment, the detection of FANCD2, FANCI, and RPA3 downregulation could be used as an indicator for monitoring HR impairment. SIGNIFICANCE: RAD51's inhibition has gained increasing attention because of its possible implications in personalized medicine through the SL approach. Chemical disruption of protein-protein interactions (PPIs) between RAD51 and BRCA2, or some of its partner proteins, could potentiate PARPi DNA damage-induced cell death. This could have application for difficult to treat cancers, such as BRCA-competent and olaparib (PARPi) resistant pancreatic adenocarcinoma. Despite RAD51 being a widely studied target, researchers still lack detailed mechanistic information. This has stifled progress in the field with only a few RAD51 inhibitors having been identified, none of which have gained regulatory approval. Nevertheless, the peptide BRC4 is one of the most specific and best characterized RAD51 binder and inhibitor reported to date. Our study is the first to report the proteomic fingerprint consequent to cellular treatment of myr-BRC4, to offer a reference for the discovery of specific protein/pathway alterations within DNA damage repair. Our results suggest that, being a direct consequence of myr-BRC4 treatment, and ultimately ofBRCA2/RAD51 disruption, the detection of FANCD2, FANCI, and RPA3 downregulation could be used as an indicator for monitoring DNA damage repair impairment and therefore be used to potentiate the development of new effective therapeutic strategies.

Multiomic analysis of HER2-enriched and AR-positive breast carcinoma with apocrine differentiation and an oligometastatic course: a case report

Breast carcinoma is the most prevalent cancer among women globally. It has variable clinical courses depending on the stage and clinical-biological features. This case report describes a 56-year-old female with invasive breast cancer without estrogen or progesterone receptor expression, with apocrine differentiation, and with no germline variants in the BRCA1 and BRCA2 genes. Throughout the clinical course, the patient exhibited discordant results for HER2 in immunohistochemistry and in situ hybridization. During the second relapse, the disease displayed apocrine microscopic features. The tumor underwent analysis for the androgen receptor, GCDFP-15, RNA-seq, and whole-genome sequencing (WGS) to identify the breast cancer subtype and to characterize the cancer genome. Our bioinformatic analysis revealed 20,323 somatic SNV/Indels, including five mutations in cancer-related genes that are believed to be responsible for the tumor's development. Two of these mutations were found in the PIK3CA and TP53 genes. Furthermore, the tumor tissue exhibited large copy number alterations to the chromosomes, which could impact gene expression through complex mechanisms and contribute to the tumor phenotype. Clustering algorithms applied on RNA-sequencing data categorized this cancer as a HER2+ subtype. The second-line capecitabine chemotherapy treatment is ongoing, and the patient is responding well. Bioinformatic results support the current treatment decision and open the way to further treatments.

Novel Insights into RAD52’s Structure, Function, and Druggability for Synthetic Lethality and Innovative Anticancer Therapies

In recent years, the RAD52 protein has been highlighted as a mediator of many DNA repair mechanisms. While RAD52 was initially considered to be a non-essential auxiliary factor, its inhibition has more recently been demonstrated to be synthetically lethal in cancer cells bearing mutations and inactivation of specific intracellular pathways, such as homologous recombination. RAD52 is now recognized as a novel and critical pharmacological target. In this review, we comprehensively describe the available structural and functional information on RAD52. The review highlights the pathways in which RAD52 is involved and the approaches to RAD52 inhibition. We discuss the multifaceted role of this protein, which has a complex, dynamic, and functional 3D superstructural arrangement. This complexity reinforces the need to further investigate and characterize RAD52 to solve a challenging mechanistic puzzle and pave the way for a robust drug discovery campaign.

Identification of Novel GSK-3β Hits Using Competitive Biophysical Assays

Glycogen synthase kinase 3 beta (GSK-3β) is an evolutionarily conserved serine-threonine kinase dysregulated in numerous pathologies, such as Alzheimer’s disease and cancer. Even though GSK-3β is a validated pharmacological target most of its inhibitors have two main limitations: the lack of selectivity due to the high homology that characterizes the ATP binding site of most kinases, and the toxicity that emerges from GSK-3β complete inhibition which translates into the impairment of the plethora of pathways GSK-3β is involved in. Starting from a 1D ¹⁹F NMR fragment screening, we set up several biophysical assays for the identification of GSK-3β inhibitors capable of binding protein hotspots other than the ATP binding pocket or to the ATP binding pocket, but with an affinity able of competing with a reference binder. A phosphorylation activity assay on a panel of several kinases provided selectivity data that were further rationalized and corroborated by structural information on GSK-3β in complex with the hit compounds. In this study, we identified promising fragments, inhibitors of GSK-3β, while proposing an alternative screening workflow that allows facing the flaws that characterize the most common GSK-3β inhibitors through the identification of selective inhibitors and/or inhibitors able to modulate GSK-3β activity without leading to its complete inhibition.

ARN25068, a versatile starting point towards triple GSK-3β/FYN/DYRK1A inhibitors to tackle tau-related neurological disorders

The human kinome plays a crucial role in several pathways. Its dysregulation has been linked to diverse central nervous system (CNS)-related disorders with a drastic impact on the aging population. Among them, tauopathies, such as Alzheimer's Disease (AD) and Frontotemporal Lobar degeneration (FTLD-tau), are neurodegenerative disorders pathologically defined by the presence of hyperphosphorylated tau-positive intracellular inclusions known as neurofibrillary tangles (NFTs). Compelling evidence has reported the great potential of the simultaneous modulation of multiple protein kinases (PKs) involved in abnormal tau phosphorylation through a concerted pharmacological approach to achieve a superior therapeutic effect relative to classic "one target, one drug" approaches. Here, we report on the identification and characterization of ARN25068 (4), a low nanomolar and well-balanced dual GSK-3β and FYN inhibitor, which also shows inhibitory activity against DYRK1A, an emerging target in AD and tauopathies. Computational and X-Ray studies highlight compound 4's typical H-bonding pattern of ATP-competitive inhibitors at the binding sites of all three PKs. In a tau phosphorylation assay on Tau0N4R-TM-tGFP U2OS cell line, 4 reduces the extent of tau phosphorylation, promoting tau-stabilized microtubule bundles. In conclusion, this compound emerges as a promising prototype for further SAR explorations to develop potent and well-balanced triple GSK-3β/FYN/DYRK1A inhibitors to tackle tau hyperphosphorylation.

Probing Interplays between Human XBP1u Translational Arrest Peptide and 80S Ribosome

The ribosome stalling mechanism is a crucial biological process, yet its atomistic underpinning is still elusive. In this framework, the human XBP1u translational arrest peptide (AP) plays a central role in regulating the unfolded protein response (UPR) in eukaryotic cells. Here, we report multimicrosecond all-atom molecular dynamics simulations designed to probe the interactions between the XBP1u AP and the mammalian ribosome exit tunnel, both for the wild type AP and for four mutant variants of different arrest potencies. Enhanced sampling simulations allow investigating the AP release process of the different variants, shedding light on this complex mechanism. The present outcomes are in qualitative/quantitative agreement with available experimental data. In conclusion, we provide an unprecedented atomistic picture of this biological process and clear-cut insights into the key AP–ribosome interactions.

GSK-3β, FYN, and DYRK1A: Master Regulators in Neurodegenerative Pathways

Protein kinases (PKs) have been recognized as central nervous system (CNS)-disease-relevant targets due to their master regulatory role in different signal transduction cascades in the neuroscience space. Among them, GSK-3β, FYN, and DYRK1A play a crucial role in the neurodegeneration context, and the deregulation of all three PKs has been linked to different CNS disorders with unmet medical needs, including Alzheimer’s disease (AD), Parkinson’s disease (PD), frontotemporal lobar degeneration (FTLD), and several neuromuscular disorders. The multifactorial nature of these diseases, along with the failure of many advanced CNS clinical trials, and the lengthy approval process of a novel CNS drug have strongly limited the CNS drug discovery. However, in the near-decade from 2010 to 2020, several computer-assisted drug design strategies have been combined with synthetic efforts to develop potent and selective GSK-3β, FYN, and DYRK1A inhibitors as disease-modifying agents. In this review, we described both structural and functional aspects of GSK-3β, FYN, and DYRK1A and their involvement and crosstalk in different CNS pathological signaling pathways. Moreover, we outlined attractive medicinal chemistry approaches including multi-target drug design strategies applied to overcome some limitations of known PKs inhibitors and discover improved modulators with suitable blood–brain barrier (BBB) permeability and drug-like properties.

Comprehensive Analysis of Binding Sites in Tubulin

Tubulin plays essential roles in vital cellular activities and is the target of a wide range of proteins and ligands. Here, using a combined computational and crystallographic fragment screening approach, we addressed the question of how many binding sites exist in tubulin. We identified 27 distinct sites, of which 11 have not been described previously, and analyzed their relationship to known tubulin-protein and tubulin-ligand interactions. We further observed an intricate pocket communication network and identified 56 chemically diverse fragments that bound to 10 distinct tubulin sites. Our results offer a unique structural basis for the development of novel small molecules for use as tubulin modulators in basic research applications or as drugs. Furthermore, our method lays down a framework that may help to discover new pockets in other pharmaceutically important targets and characterize them in terms of chemical tractability and allosteric modulation.

How Genetics Might Explain the Unusual Link Between Malaria and COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-associated coronavirus disease 2019 (COVID-19) pandemic has been the subject of a large number of studies in recent times. Here, starting from the evidence that in Italy, the areas with the lowest number of COVID-19 cases were those with the highest incidence of malaria in the early 1900's, we explore possible inverse relationships between malaria and COVID-19. Indeed, some genetic variants, which have been demonstrated to give an advantage against malaria, can also play a role in the incidence and severity of SARS-CoV-2 infections (e.g., the ACE2 receptor). To verify this scientific hypothesis, we here use public data from whole-genome sequencing (WGS) experiments to extrapolate the genetic information of 46 world populations with matched COVID-19 data. In particular, we focus on 47 genes, including ACE2 and genes which have previously been reported to play a role in malaria. Only common variants (>5%) in at least 30% of the selected populations were considered, and, for this subset, we correlate the intra-population allele frequency with the COVID-19 data (cases/million inhabitants), eventually pinpointing meaningful variants in 6 genes. This study allows us to distinguish between positive and negative correlations, i.e., variants whose frequency significantly increases with increasing or decreasing COVID-19 cases. Finally, we discuss the possible molecular mechanisms associated with these variants and advance potential therapeutic options, which may help fight and/or prevent COVID-19.

Synthetic Lethality through the Lens of Medicinal Chemistry

Personalized medicine and therapies represent the goal of modern medicine, as drug discovery strives to move away from one-cure-for-all and makes use of the various targets and biomarkers within differing disease areas. This approach, especially in oncology, is often undermined when the cells make use of alternative survival pathways. As such, acquired resistance is unfortunately common. In order to combat this phenomenon, synthetic lethality is being investigated, making use of existing genetic fragilities within the cancer cell. This Perspective highlights exciting targets within synthetic lethality, (PARP, ATR, ATM, DNA-PKcs, WEE1, CDK12, RAD51, RAD52, and PD-1) and discusses the medicinal chemistry programs being used to interrogate them, the challenges these programs face, and what the future holds for this promising field.

Thermodynamics and Kinetics of Drug-Target Binding by Molecular Simulation

Computational studies play an increasingly important role in chemistry and biophysics, mainly thanks to improvements in hardware and algorithms. In drug discovery and development, computational studies can reduce the costs and risks of bringing a new medicine to market. Computational simulations are mainly used to optimize promising new compounds by estimating their binding affinity to proteins. This is challenging due to the complexity of the simulated system. To assess the present and future value of simulation for drug discovery, we review key applications of advanced methods for sampling complex free-energy landscapes at near nonergodicity conditions and for estimating the rate coefficients of very slow processes of pharmacological interest. We outline the statistical mechanics and computational background behind this research, including methods such as steered molecular dynamics and metadynamics. We review recent applications to pharmacology and drug discovery and discuss possible guidelines for the practitioner. Recent trends in machine learning are also briefly discussed. Thanks to the rapid development of methods for characterizing and quantifying rare events, simulation's role in drug discovery is likely to expand, making it a valuable complement to experimental and clinical approaches.

Enhanced Molecular Dynamics Simulations of Intrinsically Disordered Proteins

Molecular dynamics simulations represent a powerful tool to gain insights into structural and dynamical features of biomolecular systems. Nevertheless, their recognized limitation in terms of achievable timescales becomes particularly severe when dealing with slow processes. In such cases, the employment of enhanced sampling methods, which allow accelerating the characterization of rare events in a timeframe consistent with conventional computational resources, results as crucial. In particular, such advanced techniques have proven highly valuable in the context of protein folding and, specifically, to explore the conformational ensemble spanned by intrinsically disordered proteins (IDPs). Here, we describe how to set up molecular dynamics simulations with one of these enhanced sampling approaches (namely, Parallel Tempering Metadynamics in the Well-Tempered Ensemble) using the N_TAIL peptide as a test case.

Multi-target dopamine D3 receptor modulators: Actionable knowledge for drug design from molecular dynamics and machine learning

Local changes in the structure of G-protein coupled receptors (GPCR) binders largely affect their pharmacological profile. While the sought efficacy can be empirically obtained by introducing local modifications, the underlining structural explanation can remain elusive. Here, molecular dynamics (MD) simulations of the eticlopride-bound inactive state of the Dopamine D3 Receptor (D3DR) have been clustered using a machine learning-based approach in the attempt to rationalize the efficacy change in four congeneric modulators. Accumulating extended MD trajectories of receptor-ligand complexes, we observed how the increase in ligand flexibility progressively destabilized the crystal structure of the inactivated receptor. To prospectively validate this model, a partial agonist was rationally designed based on structural insights and computational modeling, and eventually synthesized and tested. Results turned out to be in line with the predictions. This case study suggests that the investigation of ligand flexibility in the framework of extended MD simulations can assist and inform drug design strategies, highlighting its potential role as a powerful in silico counterpart to functional assays.

Dynamic Docking: A Paradigm Shift in Computational Drug Discovery

Molecular docking is the methodology of choice for studying in silico protein-ligand binding and for prioritizing compounds to discover new lead candidates. Traditional docking simulations suffer from major limitations, mostly related to the static or semi-flexible treatment of ligands and targets. They also neglect solvation and entropic effects, which strongly limits their predictive power. During the last decade, methods based on full atomistic molecular dynamics (MD) have emerged as a valid alternative for simulating macromolecular complexes. In principle, compared to traditional docking, MD allows the full exploration of drug-target recognition and binding from both the mechanistic and energetic points of view (dynamic docking). Binding and unbinding kinetic constants can also be determined. While dynamic docking is still too computationally expensive to be routinely used in fast-paced drug discovery programs, the advent of faster computing architectures and advanced simulation methodologies are changing this scenario. It is feasible that dynamic docking will replace static docking approaches in the near future, leading to a major paradigm shift in in silico drug discovery. Against this background, we review the key achievements that have paved the way for this progress.

Galantamine potentiates the neuroprotective effect of memantine against NMDA-induced excitotoxicity

The combination of memantine, an N-methyl-d-aspartate (NMDA) receptor antagonist, with an acetylcholinesterase inhibitor (AChEI) is the current standard of care in Alzheimer's disease (AD). Galantamine, an AChEI currently marketed for the treatment of AD, exerts memory-enhancing and neuroprotective effects via activation of nicotinic acetylcholine receptors (nAChRs). Here, we investigated the neuroprotective properties of galantamine in primary cultures of rat cortical neurons when given alone or in combination with memantine. In agreement with previous findings, we found that memantine was fully effective in reversing NMDA toxicity at concentrations of 2.5 and 5 μmol/L. Galantamine also completely reversed NMDA toxicity at a concentration of 5 μmol/L. The α7 and α4β2 nAChR antagonists, methyllycaconitine, and dihydro-β-erythroidine blocked the neuroprotective effect of galantamine, demonstrating the involvement of nAChRs. The combination of memantine with galantamine produced synergistic actions, such that full neuroprotective efficacy, was obtained at inactive concentrations of memantine (0.1 μmol/L) and galantamine (1 μmol/L). A similar potentiation was also observed when memantine was replaced with ifenprodil, suggesting a possible involvement of the NR2B subunit of the NMDA receptor. In summary, our study reports for the first time at a cellular level that memantine and galantamine interact on the same excitotoxic cascade and that the combination of these two drugs can result in a remarkable neuroprotective effect.

Pharmacological characterization of memoquin, a multi-target compound for the treatment of Alzheimer's disease

Alzheimer's disease (AD) is characterized by progressive loss of cognitive function, dementia and altered behavior. Over 30 million people worldwide suffer from AD and available therapies are still palliative rather than curative. Recently, Memoquin (MQ), a quinone-bearing polyamine compound, has emerged as a promising anti-AD lead candidate, mainly thanks to its multi-target profile. MQ acts as an acetylcholinesterase and β-secretase-1 inhibitor, and also possesses anti-amyloid and anti-oxidant properties. Despite this potential interest, in vivo behavioral studies with MQ have been limited. Here, we report on in vivo studies with MQ (acute and sub-chronic treatments; 7–15 mg/kg per os) carried out using two different mouse models: i) scopolamine- and ii) beta-amyloid peptide- (Aβ-) induced amnesia. Several aspects related to memory were examined using the T-maze, the Morris water maze, the novel object recognition, and the passive avoidance tasks. At the dose of 15 mg/kg, MQ was able to rescue all tested aspects of cognitive impairment including spatial, episodic, aversive, short and long-term memory in both scopolamine- and Aβ-induced amnesia models. Furthermore, when tested in primary cortical neurons, MQ was able to fully prevent the Aβ-induced neurotoxicity mediated by oxidative stress. The results support the effectiveness of MQ as a cognitive enhancer, and highlight the value of a multi-target strategy to address the complex nature of cognitive dysfunction in AD.

A catalytic mechanism for cysteine N-terminal nucleophile hydrolases, as revealed by free energy simulations

The N-terminal nucleophile (Ntn) hydrolases are a superfamily of enzymes specialized in the hydrolytic cleavage of amide bonds. Even though several members of this family are emerging as innovative drug targets for cancer, inflammation, and pain, the processes through which they catalyze amide hydrolysis remains poorly understood. In particular, the catalytic reactions of cysteine Ntn-hydrolases have never been investigated from a mechanistic point of view. In the present study, we used free energy simulations in the quantum mechanics/molecular mechanics framework to determine the reaction mechanism of amide hydrolysis catalyzed by the prototypical cysteine Ntn-hydrolase, conjugated bile acid hydrolase (CBAH). The computational analyses, which were confirmed in water and using different CBAH mutants, revealed the existence of a chair-like transition state, which might be one of the specific features of the catalytic cycle of Ntn-hydrolases. Our results offer new insights on Ntn-mediated hydrolysis and suggest possible strategies for the creation of therapeutically useful inhibitors.

Systematic exploitation of multiple receptor conformations for virtual ligand screening

The role of virtual ligand screening in modern drug discovery is to mine large chemical collections and to prioritize for experimental testing a comparatively small and diverse set of compounds with expected activity against a target. Several studies have pointed out that the performance of virtual ligand screening can be improved by taking into account receptor flexibility. Here, we systematically assess how multiple crystallographic receptor conformations, a powerful way of discretely representing protein plasticity, can be exploited in screening protocols to separate binders from non-binders. Our analyses encompass 36 targets of pharmaceutical relevance and are based on actual molecules with reported activity against those targets. The results suggest that an ensemble receptor-based protocol displays a stronger discriminating power between active and inactive molecules as compared to its standard single rigid receptor counterpart. Moreover, such a protocol can be engineered not only to enrich a higher number of active compounds, but also to enhance their chemical diversity. Finally, some clear indications can be gathered on how to select a subset of receptor conformations that is most likely to provide the best performance in a real life scenario.