Spinocerebellar ataxia 38: structure-function analysis shows ELOVL5 G230V is proteotoxic, conformationally altered and a mutational hotspot.

Fatty acid elongase ELOVL5 is part of a protein family of multipass transmembrane proteins that reside in the endoplasmic reticulum where they regulate long-chain fatty acid elongation. A missense variant (c.689G>T p.Gly230Val) in ELOVL5 causes Spinocerebellar Ataxia subtype 38 (SCA38), a neurodegenerative disorder characterized by autosomal dominant inheritance, cerebellar Purkinje cell demise and adult-onset ataxia. Having previously showed aberrant accumulation of p.G230V in the Golgi complex, here we further investigated the pathogenic mechanisms triggered by p.G230V, integrating functional studies with bioinformatic analyses of protein sequence and structure. Biochemical analysis showed that p.G230V enzymatic activity was normal. In contrast, SCA38-derived fibroblasts showed reduced expression of ELOVL5, Golgi complex enlargement and increased proteasomal degradation with respect to controls. By heterologous overexpression, p.G230V was significantly more active than wild-type ELOVL5 in triggering the unfolded protein response and in decreasing viability in mouse cortical neurons. By homology modelling, we generated native and p.G230V protein structures whose superposition revealed a shift in Loop 6 in p.G230V that altered a highly conserved intramolecular disulphide bond. The conformation of this bond, connecting Loop 2 and Loop 6, appears to be elongase-specific. Alteration of this intramolecular interaction was also observed when comparing wild-type ELOVL4 and the p.W246G variant which causes SCA34. We demonstrate by sequence and structure analyses that ELOVL5 p.G230V and ELOVL4 p.W246G are position-equivalent missense variants. We conclude that SCA38 is a conformational disease and propose combined loss of function by mislocalization and gain of toxic function by ER/Golgi stress as early events in SCA38 pathogenesis.

Personalized Treatment for Infantile Ascending Hereditary Spastic Paralysis Based on In Silico Strategies.

Infantile onset hereditary spastic paralysis (IAHSP) is a rare neurological disease diagnosed in less than 50 children worldwide. It is transmitted with a recessive pattern and originates from mutations of the ALS2 gene, encoding for the protein alsin and involved in differentiation and maintenance of the upper motoneuron. The exact pathogenic mechanisms of IAHSP and other neurodevelopmental diseases are still largely unknown. However, previous studies revealed that, in the cytosolic compartment, alsin is present as an active tetramer, first assembled from dimer pairs. The C-terminal VPS9 domain is a key interaction site for alsin dimerization. Here, we present an innovative drug discovery strategy, which identified a drug candidate to potentially treat a patient harboring two ALS2 mutations: one truncation at lysine 1457 (not considered) and the substitution of arginine 1611 with a tryptophan (R1611W) in the C-terminus VPS9. With a protein modeling approach, we obtained a R1611W mutant model and characterized the impact of the mutation on the stability and flexibility of VPS9. Furthermore, we showed how arginine 1611 is essential for alsin's homo-dimerization and how, when mutated to tryptophan, it leads to an abnormal dimerization pattern, disrupting the formation of active tetramers. Finally, we performed a virtual screening, individuating an already therapy-approved compound (MK4) able to mask the mutant residue and re-establishing the alsin tetramers in HeLa cells. MK4 has now been approved for compassionate use.

Targeting Long Chain Acyl-CoA Synthetases for Cancer Therapy.

The deregulation of cancer cell metabolic networks is now recognized as one of the hallmarks of cancer. Abnormal lipid synthesis and extracellular lipid uptake are advantageous modifications fueling the needs of uncontrolled cancer cell proliferation. Fatty acids are placed at the crossroads of anabolic and catabolic pathways, as they are implicated in the synthesis of phospholipids and triacylglycerols, or they can undergo ß-oxidation. Key players to these decisions are the long-chain acyl-CoA synthetases, which are enzymes that catalyze the activation of long-chain fatty acids of 12-22 carbons. Importantly, the long-chain acyl-CoA synthetases are deregulated in many types of tumors, providing a rationale for anti-tumor therapeutic opportunities. The purpose of this review is to summarize the last up-to-date findings regarding their role in cancer, and to discuss the related emerging tumor targeting opportunities.

IMHB-Mediated Chameleonicity in Drug Design: A Focus on Structurally Related PROTACs.

Molecular chameleonicity may enable compounds to compensate for the unfavorable ADME properties typically associated with complex molecules, such as PROTACs. Here we present a few in silico strategies to implement chameleonicity considerations in drug design. Initially, we identified six structurally related CRBN-based PROTACs targeting BET proteins and experimentally verified whether chameleonicity is needed to obtain an acceptable physicochemical profile. Then, we utilized experimental data to validate our novel computational strategies based on tools crafted to encompass a spectrum of complexities and innovative features. After confirming that the formation of IMHBs is the primary driving factor behind chameleonicity, we initially utilized conformational sampling data to define cChameCS, an IMHB-mediated, simple, and rapid chameleonicity predictor index suitable for early drug discovery. Subsequently, we identified dynamic IMHB patterns relevant to chameleonicity through molecular dynamics simulations. Finally, we proposed a workflow for designing structurally related chameleonic PROTACs of potential application in the lead optimization process.

DegraderTCM: A Computationally Sparing Approach for Predicting Ternary Degradation Complexes.

Proteolysis targeting chimeras (PROTACs or degraders) represent a novel therapeutic modality that has raised interest thanks to promising results and currently undergoing clinical testing. PROTACs induce the selective proteasomal degradation of undesired proteins by the formation of ternary complexes (TCs). Having knowledge of the 3D structure of TCs is crucial for the design of PROTAC drugs. Here, we describe DegraderTCM, a new computational method for modeling PROTAC-mediated TCs that requires low computational power and provides sound results in a short time span. We validated DegraderTCM against a selected set of experimentally determined structures and defined a method to predict the PROTAC degradation activity based on the computed TC structure. Finally, we modeled TCs of known degraders holding significance for defining the method's applicability domain. A retrospective analysis of structure-activity relationships unveiled possibilities for utilizing DegraderTCM in the initial stages of designing novel PROTAC drugs.

DNA methylation analysis in patients with neurodevelopmental disorders improves variant interpretation and reveals complexity.

Analysis of genomic DNA methylation by generating epigenetic signature profiles (episignatures) is increasingly being implemented in genetic diagnosis. Here we report our experience using episignature analysis to resolve both uncomplicated and complex cases of neurodevelopmental disorders (NDDs). We analyzed 97 NDDs divided into (1) a validation cohort of 59 patients with likely pathogenic/pathogenic variants characterized by a known episignature and (2) a test cohort of 38 patients harboring variants of unknown significance or unidentified variants. The expected episignature was obtained in most cases with likely pathogenic/pathogenic variants (53/59 [90%]), a revealing exception being the overlapping profile of two SMARCB1 pathogenic variants with ARID1A/B:c.6200, confirmed by the overlapping clinical features. In the test cohort, five cases showed the expected episignature, including (1) novel pathogenic variants in ARID1B and BRWD3; (2) a deletion in ATRX causing MRXFH1 X-linked mental retardation; and (3) confirmed the clinical diagnosis of Cornelia de Lange (CdL) syndrome in mutation-negative CdL patients. Episignatures analysis of the in BAF complex components revealed novel functional protein interactions and common episignatures affecting homologous residues in highly conserved paralogous proteins (SMARCA2 M856V and SMARCA4 M866V). Finally, we also found sex-dependent episignatures in X-linked disorders. Implementation of episignature profiling is still in its early days, but with increasing utilization comes increasing awareness of the capacity of this methodology to help resolve the complex challenges of genetic diagnoses.

Conformational Sampling Deciphers the Chameleonic Properties of a VHL-Based Degrader.

Chameleonicity (the capacity of a molecule to adapt its conformations to the environment) may help to identify orally bioavailable drugs in the beyond-Rule-of-5 chemical space. Computational methods to predict the chameleonic behaviour of degraders have not yet been reported and the identification of molecular chameleons still relies on experimental evidence. Therefore, there is a need to tune predictions with experimental data. Here, we employ PROTAC-1 (a passively cell-permeable degrader), for which NMR and physicochemical data prove the chameleonic behaviour, to benchmark the capacity of two conformational sampling algorithms and selection schemes. To characterize the conformational ensembles in both polar and nonpolar environments, we compute three molecular properties proven to be essential for cell permeability: conformer shape (radius of gyration), polarity (3D PSA), and the number of intramolecular hydrogen bonds. Energetic criteria were also considered. Infographics monitored the simultaneous variation of those properties in computed and NMR conformers. Overall, we provide key points for tuning conformational sampling tools to reproduce PROTAC-1 chameleonicity according to NMR evidence. This study is expected to improve the design of PROTAC drugs and the development of computational sustainable strategies to exploit the potential of new modalities in drug discovery.

Chamelogk: A Chromatographic Chameleonicity Quantifier to Design Orally Bioavailable Beyond-Rule-of-5 Drugs.

New chemical modalities in drug discovery include molecules belonging to the bRo5 chemical space. Because of their complex and flexible structure, bRo5 compounds often suffer from a poor solubility/permeability profile. Chameleonicity describes the capacity of a molecule to adapt to the environment through conformational changes; the design of molecular chameleons is a medicinal chemistry strategy simultaneously optimizing solubility and permeability. A default method to quantify chameleonicity in early drug discovery is still missing. Here we introduce Chamelogk, an automated, fast, and cheap chromatographic descriptor of chameleonicity. Moreover, we report measurements for 55 Ro5 and bRo5 compounds and validate our method with literature data. Then, selected case studies (macrocycles, nonmacrocyclic compounds, and PROTACs) are used to illustrate the application of Chamelogk in combination with lipophilicity (BRlogD) and polarity (Δ log kwIAM) descriptors. Overall, we show how Chamelogk deserves being included in property-based drug discovery strategies to design oral bioavailable bRo5 compounds.

AI-based protein structure databases have the potential to accelerate rare diseases research: AlphaFoldDB and the case of IAHSP/Alsin.

Artificial intelligence (AI)-based protein structure databases are expected to have an impact on drug discovery. Here, we show how AlphaFold could support rare diseases research programs. We focus on Alsin, a protein responsible for rare motor neuron diseases, such as infantile-onset ascending hereditary spastic paralysis (IAHSP) and juvenile primary lateral sclerosis (JPLS), and involved in some cases of amyotrophic lateral sclerosis (ALS). First, we compared the AlphaFoldDB human Alsin model with homology models of Alsin domains. We then evaluated the flexibility profile of Alsin and of experimentally characterized mutants present in patients with IAHSP. Next, we compared preliminary models of dimeric/tetrameric Alsin responsible for its physiological action with hypothetical models reported in the literature. Finally, we suggest the best animal model for drug candidates testing. Overall, we computationally show that drug discovery efforts toward Alsin-involving diseases should be pursued.

Refinement of Computational Access to Molecular Physicochemical Properties: From Ro5 to bRo5.

There is a need of computational tools to rank bRo5 drug candidates in the very early phases of drug discovery when chemical matter is unavailable. In this study, we selected three compounds: (a) a Ro5 drug (Pomalidomide), (b) a bRo5 orally available drug (Saquinavir), and (c) a polar PROTAC (CMP 98) to focus on computational access to physicochemical properties. To provide a benchmark, the three compounds were first experimentally characterized for their lipophilicity, polarity, IMHBs, and chameleonicity. To reproduce the experimental information content, we generated conformer ensembles with conformational sampling and molecular dynamics in both water and nonpolar solvents. Then we calculated Rgyr, 3D PSA, and IMHB number. An innovative pool of strategies for data analysis was then provided. Overall, we report a contribution to close the gap between experimental and computational methods for characterizing bRo5 physicochemical properties.

Designing Soluble PROTACs: Strategies and Preliminary Guidelines.

Solubility optimization is a crucial step to obtaining oral PROTACs. Here we measured the thermodynamic solubilities (log S) of 21 commercial PROTACs. Next, we measured BRlogD and log kwIAM (lipophilicity), EPSA, and Δ log kwIAM (polarity) and showed that lipophilicity plays a major role in governing log S, but a contribution of polarity cannot be neglected. Two-/three-dimensional descriptors calculated on conformers arising from conformational sampling and steered molecular dynamics failed in modeling solubility. Infographic tools were used to identify a privileged region of soluble PROTACs in a chemical space defined by BRlogD, log kwIAM and topological polar surface area, while machine learning provided a log S classification model. Finally, for three pairs of PROTACs we measured the solubility, lipophilicity, and polarity of the building blocks and identified the limits of estimating PROTAC solubility from the synthetic components. Overall, this paper provides promising guidelines for optimizing PROTAC solubility in early drug discovery programs.

Rational Control of Molecular Properties Is Mandatory to Exploit the Potential of PROTACs as Oral Drugs.

To obtain new oral drugs in the beyond rule of five space, PROTACs among others, molecular properties should be optimized in early drug discovery. Degraders call for design strategies which focus on intramolecular interaction and chameleonicity. In parallel, tailored revalidation of permeability assessment and prediction methods becomes fundamental in this innovative chemical space.

The ACSL3-LPIAT1 signaling drives prostaglandin synthesis in non-small cell lung cancer.

Enhanced prostaglandin production promotes the development and progression of cancer. Prostaglandins are generated from arachidonic acid (AA) by the action of cyclooxygenase (COX) isoenzymes. However, how cancer cells are able to maintain an elevated supply of AA for prostaglandin production remains unclear. Here, by using lung cancer cell lines and clinically relevant KrasG12D-driven mouse models, we show that the long-chain acyl-CoA synthetase (ACSL3) channels AA into phosphatidylinositols to provide the lysophosphatidylinositol-acyltransferase 1 (LPIAT1) with a pool of AA to sustain high prostaglandin synthesis. LPIAT1 knockdown suppresses proliferation and anchorage-independent growth of lung cancer cell lines, and hinders in vivo tumorigenesis. In primary human lung tumors, the expression of LPIAT1 is elevated compared with healthy tissue, and predicts poor patient survival. This study uncovers the ACSL3-LPIAT1 axis as a requirement for the sustained prostaglandin synthesis in lung cancer with potential therapeutic value.

ACSL3-PAI-1 signaling axis mediates tumor-stroma cross-talk promoting pancreatic cancer progression.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by marked fibrosis and low immunogenicity, features that are linked to treatment resistance and poor clinical outcomes. Therefore, understanding how PDAC regulates the desmoplastic and immune stromal components is of great clinical importance. We found that acyl-CoA synthetase long-chain 3 (ACSL3) is up-regulated in PDAC and correlates with increased fibrosis. Our in vivo results show that Acsl3 knockout hinders PDAC progression, markedly reduces tumor fibrosis and tumor-infiltrating immunosuppressive cells, and increases cytotoxic T cell infiltration. This effect is, at least in part, due to decreased plasminogen activator inhibitor-1 (PAI-1) secretion from tumor cells. Accordingly, PAI-1 expression in PDAC positively correlates with markers of fibrosis and immunosuppression and predicts poor patient survival. We found that PAI-1 pharmacological inhibition strongly enhances chemo- and immunotherapeutic response against PDAC, increasing survival of mice. Thus, our results unveil ACSL3-PAI-1 signaling as a requirement for PDAC progression with druggable attributes.

PLCγ1 suppression promotes the adaptation of KRAS-mutant lung adenocarcinomas to hypoxia.

Mutant KRAS modulates the metabolic plasticity of cancer cells to confer a growth advantage during hypoxia, but the molecular underpinnings are largely unknown. Using a lipidomic screen, we found that PLCγ1 is suppressed during hypoxia in KRAS-mutant human lung adenocarcinoma cancer cell lines. Suppression of PLCγ1 in hypoxia promotes a less oxidative cancer cell metabolism state, reduces the formation of mitochondrial reactive oxygen species and switches tumour bioenergetics towards glycolysis by impairing Ca2+ entry into the mitochondria. This event prevents lipid peroxidation, antagonizes apoptosis and increases cancer cell proliferation. Accordingly, loss of function of Plcg1 in a mouse model of KrasG12D-driven lung adenocarcinoma increased the expression of glycolytic genes, boosted tumour growth and reduced survival. In patients with KRAS-mutant lung adenocarcinomas, low PLCγ1 expression correlates with increased expression of hypoxia markers and predicts poor patient survival. Thus, our work reveals a mechanism of cancer cell adaptation to hypoxia with potential therapeutic value.

Modeling ErbB2-p130Cas interaction to design new potential anticancer agents.

The ErbB2 receptor tyrosine kinase is overexpressed in approximately 15-20% of breast tumors and associated with aggressive disease and poor clinical outcome. p130Cas represents a nodal scaffold protein regulating cell survival, migration and proliferation in normal and pathological contexts. p130Cas overexpression in ErbB2 human breast cancer correlates with poor prognosis and metastasis formation. Recent data indicate that p130Cas association to ErbB2 protects ErbB2 from degradation, thus enhancing tumorigenesis. Therefore, inhibiting p130Cas/ErbB2 interaction might represent a new therapeutic strategy to target breast cancer. Here we demonstrate by performing Molecular Modeling, Molecular Dynamics, dot blot, ELISA and fluorescence quenching experiments, that p130Cas binds directly to ErbB2. Then, by structure-based virtual screening, we identified two potential inhibitors of p130Cas/ErbB2 interaction. Their experimental validation was performed in vitro and in ErbB2-positive breast cancer cellular models. The results highlight that both compounds interfere with p130Cas/ErbB2 binding and significantly affect cell proliferation and sensitivity to Trastuzumab. Overall, this study identifies p130Cas/ErbB2 complex as a potential breast cancer target revealing new therapeutic perspectives for protein-protein interaction (PPI).

Author Correction: Modeling ErbB2-p130Cas interaction to design new potential anticancer agents.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Impact of Dynamically Exposed Polarity on Permeability and Solubility of Chameleonic Drugs Beyond the Rule of 5.

Conformational flexibility has been proposed to significantly affect drug properties outside rule-of-5 (Ro5) chemical space. Here, we investigated the influence of dynamically exposed polarity on cell permeability and aqueous solubility for a structurally diverse set of drugs and clinical candidates far beyond the Ro5, all of which populated multiple distinct conformations as revealed by X-ray crystallography. Efflux-inhibited (passive) Caco-2 cell permeability correlated strongly with the compounds' minimum solvent-accessible 3D polar surface areas (PSA), whereas aqueous solubility depended less on the specific 3D conformation. Inspection of the crystal structures highlighted flexibly linked aromatic side chains and dynamically forming intramolecular hydrogen bonds as particularly effective in providing "chameleonic" properties that allow compounds to display both high cell permeability and aqueous solubility. These structural features, in combination with permeability predictions based on the correlation to solvent-accessible 3D PSA, should inspire drug design in the challenging chemical space far beyond the Ro5.