A novel calcium channel Cavß2 splice variant with unique properties predominates in the retina.

Cavß subunits are essential for surface expression of voltage-gated calcium channel complexes and crucially modulate biophysical properties like voltage-dependent inactivation. Here, we describe the discovery and characterization of a novel Cavß2 variant with distinct features that predominates in the retina. We determined spliced exons in retinal transcripts of the Cacnb2 gene, coding for Cavß2, by RNA-Seq data analysis and quantitative PCR. We cloned a novel Cavß2 splice variant from mouse retina, which we are calling ß2i, and investigated biophysical properties of calcium currents with this variant in a heterologous expression system as well as its intrinsic membrane interaction when expressed alone. Our data showed that ß2i predominated in the retina with expression in photoreceptors and bipolar cells. Furthermore, we observed that the ß2i N-terminus exhibited an extraordinary concentration of hydrophobic residues, a distinct feature not seen in canonical variants. The biophysical properties resembled known membrane-associated variants, and ß2i exhibited both a strong membrane association and a propensity for clustering, which depended on hydrophobic residues in its N-terminus. We considered available Cavß structure data to elucidate potential mechanisms underlying the observed characteristics but resolved N-terminus structures were lacking and thus, precluded clear conclusions. With this description of a novel N-terminus variant of Cavß2, we expand the scope of functional variation through N-terminal splicing with a distinct form of membrane attachment. Further investigation of the molecular mechanisms underlying the features of ß2i could provide new angles on the way Cavß subunits modulate Ca2+ channels at the plasma membrane.

Development of heterodimeric estrogen receptor alpha antagonists to target simultaneously the ligand and coactivator binding site.

One-third of breast cancer patients will develop recurrent cancer within 15 years of endocrine treatment. Notably, tumor growth in a hormone-refractory state still relies on the interaction between estrogen receptor alpha (ERα) and upregulated coactivators. Herein, we suggest that simultaneous targeting of the primary ligand binding site (LBS) and the coactivator binding site (CABS) at ERα represents a promising alternative therapeutic strategy to overcome mutation-driven resistance in breast cancer. We synthesized two series of compounds that connect the LBS-binder (E)-3-{4-[8-fluoro-4-(4-hydroxyphenyl)-2,3-dihydrobenzo[b]oxepin-5-yl]phenyl}acrylic acid 8 with the coactivator binding site inhibitors (CBIs) 4,6-bis(isobutyl(methyl)amino)pyrimidine or 3-(5-methoxy-1H-benzo[d]imidazol-2-yl)propanoic acid via covalent linkage. The most active benzoxepine-pyrimidine conjugate 31 showed strong inhibition of estradiol-induced transactivation (IC50 = 18.2 nM (ERα) and 61.7 nM (ERß)) in a luciferase reporter gene assay as well as high antiproliferative effects in MCF-7 (IC50 = 65.9 nM) and tamoxifen-resistant MCF-7/TamR (IC50 = 88.9 nM) breast cancer cells. All heterodimers exhibited two- to sevenfold higher antagonism at ERα (compared with ERß) and were superior to the acrylic acid precursor 8 in terms of ER antagonism and antiproliferative activity. It was demonstrated on the example of 31 that the compounds did not influence the ERα content in MCF-7 cells and therefore act as pure antiestrogens without downregulating potency. Possible interactions of the CBI at the receptor surface, which enhanced the biological activities, were evaluated using molecular docking studies.

De Novo Missense Substitutions in the Gene Encoding CDK8, a Regulator of the Mediator Complex, Cause a Syndromic Developmental Disorder.

The Mediator is an evolutionarily conserved, multi-subunit complex that regulates multiple steps of transcription. Mediator activity is regulated by the reversible association of a four-subunit module comprising CDK8 or CDK19 kinases, together with cyclin C, MED12 or MED12L, and MED13 or MED13L. Mutations in MED12, MED13, and MED13L were previously identified in syndromic developmental disorders with overlapping phenotypes. Here, we report CDK8 mutations (located at 13q12.13) that cause a phenotypically related disorder. Using whole-exome or whole-genome sequencing, and by international collaboration, we identified eight different heterozygous missense CDK8 substitutions, including 10 shown to have arisen de novo, in 12 unrelated subjects; a recurrent mutation, c.185C>T (p.Ser62Leu), was present in five individuals. All predicted substitutions localize to the ATP-binding pocket of the kinase domain. Affected individuals have overlapping phenotypes characterized by hypotonia, mild to moderate intellectual disability, behavioral disorders, and variable facial dysmorphism. Congenital heart disease occurred in six subjects; additional features present in multiple individuals included agenesis of the corpus callosum, ano-rectal malformations, seizures, and hearing or visual impairments. To evaluate the functional impact of the mutations, we measured phosphorylation at STAT1-Ser727, a known CDK8 substrate, in a CDK8 and CDK19 CRISPR double-knockout cell line transfected with wild-type (WT) or mutant CDK8 constructs. These experiments demonstrated a reduction in STAT1 phosphorylation by all mutants, in most cases to a similar extent as in a kinase-dead control. We conclude that missense mutations in CDK8 cause a developmental disorder that has phenotypic similarity to syndromes associated with mutations in other subunits of the Mediator kinase module, indicating probable overlap in pathogenic mechanisms.

Novel CACNA1A Variant p.Cys256Phe Disrupts Disulfide Bonds and Causes Spinocerebellar Ataxia.

BACKGROUND: Spinocerebellar ataxia (SCA) is a progressive, autosomal dominant neurodegenerative disorder typically associated with CAG repeat expansions. OBJECTIVE: We assessed the pathogenicity of the novel, heterozygous missense variant p.Cys256Phe (C256F) in the pore-forming α1-subunit of the Cav2.1 Ca2+ channel found in a 63-year-old woman with SCA with no CAG repeat expansion. METHODS: We examined the effect of the C256F variant on channel function using whole-cell patch-clamp recordings in transfected tsA-201 cells. RESULTS: The maximum Ca2+ current density was significantly reduced in the mutant compared to wild-type, which could not be explained by lower expression levels of mutant Cav2.1 α1- protein. Together with a significant increase in current inactivation, this is consistent with a loss of channel function. Molecular modeling predicted disruption of a conserved disulfide bond through the C256F variant. CONCLUSIONS: Our results support the pathogenicity of the C256F variant for the SCA phenotype and provide further insight into Cav2.1 structure and function.

De novo CACNA1D Ca2+ channelopathies: clinical phenotypes and molecular mechanism.

The identification of rare disease-causing variants in humans by large-scale next-generation sequencing (NGS) studies has also provided us with new insights into the pathophysiological role of de novo missense variants in the CACNA1D gene that encodes the pore-forming α1-subunit of voltage-gated Cav1.3 L-type Ca2+ channels. These CACNA1D variants have been identified somatically in aldosterone-producing adenomas as well as germline in patients with neurodevelopmental and in some cases endocrine symptoms. In vitro studies in heterologous expression systems have revealed typical gating changes that indicate enhanced Ca2+ influx through Cav1.3 channels as the underlying disease-causing mechanism. Here we summarize the clinical findings of 12 well-characterized individuals with a total of 9 high-risk pathogenic CACNA1D variants. Moreover, we propose how information from somatic mutations in aldosterone-producing adenomas could be used to predict the potential pathogenicity of novel germline variants. Since these pathogenic de novo variants can cause a channel-gain-of function, we also discuss the use of L-type Ca2+ channel blockers as a potential therapeutic option.

Correction to: De novo CACNA1D Ca2+ channelopathies: clinical phenotypes and molecular mechanism.

The above article was published online with an error in Article title. Author mispronounced the name of a gene (CACNA1D instead of CACAN1D). The correct gene is presented above.

A systematic molecular and pharmacologic evaluation of AKT inhibitors reveals new insight into their biological activity.

BACKGROUND: AKT, a critical effector of the phosphoinositide 3-kinase (PI3K) signalling cascade, is an intensely pursued therapeutic target in oncology. Two distinct classes of AKT inhibitors have been in clinical development, ATP-competitive and allosteric. Class-specific differences in drug activity are likely the result of differential structural and conformational requirements governing efficient target binding, which ultimately determine isoform-specific potency, selectivity profiles and activity against clinically relevant AKT mutant variants. METHODS: We have carried out a systematic evaluation of clinical AKT inhibitors using in vitro pharmacology, molecular profiling and biochemical assays together with structural modelling to better understand the context of drug-specific and drug-class-specific cell-killing activity. RESULTS: Our data demonstrate clear differences between ATP-competitive and allosteric AKT inhibitors, including differential effects on non-catalytic activity as measured by a novel functional readout. Surprisingly, we found that some mutations can cause drug resistance in an isoform-selective manner despite high structural conservation across AKT isoforms. Finally, we have derived drug-class-specific phosphoproteomic signatures and used them to identify effective drug combinations. CONCLUSIONS: These findings illustrate the utility of individual AKT inhibitors, both as drugs and as chemical probes, and the benefit of AKT inhibitor pharmacological diversity in providing a repertoire of context-specific therapeutic options.

Steroid sulfatase inhibiting lanostane triterpenes - Structure activity relationship and in silico insights.

Steroid sulfatase (STS) transforms hormone precursors into active steroids. Thus, it represents a target of intense research regarding hormone-dependent cancers. In this study, three ligand-based pharmacophore models were developed to identify STS inhibitors from natural sources. In a pharmacophore-based virtual screening of a curated molecular TCM database, lanostane-type triterpenes (LTTs) were predicted as STS ligands. Three traditionally used polypores rich in LTTs, i.e., Ganoderma lucidum Karst., Gloeophyllum odoratum Imazeki, and Fomitopsis pinicola Karst., were selected as starting materials. Based on eighteen thereof isolated LTTs a structure activity relationship for this compound class was established with piptolinic acid D (1), pinicolic acid B (2), and ganoderol A (3) being the most pronounced and first natural product STS inhibitors with IC50 values between 10 and 16 µM. Molecular docking studies proposed crucial ligand target interactions and a prediction tool for these natural compounds correlating with experimental findings.

Interference of Paraben Compounds with Estrogen Metabolism by Inhibition of 17ß-Hydroxysteroid Dehydrogenases.

Parabens are effective preservatives widely used in cosmetic products and processed food, with high human exposure. Recent evidence suggests that parabens exert estrogenic effects. This work investigated the potential interference of parabens with the estrogen-activating enzyme 17ß-hydroxysteroid dehydrogenase (17ß-HSD) 1 and the estrogen-inactivating 17ß-HSD2. A ligand-based 17ß-HSD2 pharmacophore model was applied to screen a cosmetic chemicals database, followed by in vitro testing of selected paraben compounds for inhibition of 17ß-HSD1 and 17ß-HSD2 activities. All tested parabens and paraben-like compounds, except their common metabolite p-hydroxybenzoic acid, inhibited 17ß-HSD2. Ethylparaben and ethyl vanillate inhibited 17ß-HSD2 with IC50 values of 4.6 ± 0.8 and 1.3 ± 0.3 µM, respectively. Additionally, parabens size-dependently inhibited 17ß-HSD1, whereby hexyl- and heptylparaben were most active with IC50 values of 2.6 ± 0.6 and 1.8 ± 0.3 µM. Low micromolar concentrations of hexyl- and heptylparaben decreased 17ß-HSD1 activity, and ethylparaben and ethyl vanillate decreased 17ß-HSD2 activity. However, regarding the very rapid metabolism of these compounds to the inactive p-hydroxybenzoic acid by esterases, it needs to be determined under which conditions low micromolar concentrations of these parabens or their mixtures can occur in target cells to effectively disturb estrogen effects in vivo.

Optimized Virtual Screening Workflow for the Identification of Novel G-Quadruplex Ligands.

G-quadruplexes, alternative DNA secondary structures present in telomeres, emerge as promising targets for the treatment of cancer, because they prevent telomere elongation and accordingly cell proliferation. Within this study, theoretically validated pharmacophore- and shape-based models as well as a theoretically validated docking protocol were generated and applied in parallel for virtual screening and the identification of novel G-quadruplex ligands. Top-ranked hits retrieved with all methods independently and in addition in a consensus approach were selected for biological testing. Of the 32 tested virtual hits seven selectively stabilized G-quadruplexes over duplex DNA in the fluorescence melting assay. For the five most active compounds, chemically closely related analogues were collected and subjected to in vitro analysis. Thereby, seven further novel G-quadruplex ligands could be identified. These molecules do not only represent novel scaffolds, but some of them are in addition even more potent G-quadruplex stabilizers than the established reference compound berberine. This study proposes an optimized in silico workflow for the identification of novel G-quadruplex stabilizers, which can also be applied in future studies. In addition, structurally novel and promising lead candidates with strong and selective G-quadruplex stabilizing properties are reported.

Pharmacophore Models and Pharmacophore-Based Virtual Screening: Concepts and Applications Exemplified on Hydroxysteroid Dehydrogenases.

Computational methods are well-established tools in the drug discovery process and can be employed for a variety of tasks. Common applications include lead identification and scaffold hopping, as well as lead optimization by structure-activity relationship analysis and selectivity profiling. In addition, compound-target interactions associated with potentially harmful effects can be identified and investigated. This review focuses on pharmacophore-based virtual screening campaigns specifically addressing the target class of hydroxysteroid dehydrogenases. Many members of this enzyme family are associated with specific pathological conditions, and pharmacological modulation of their activity may represent promising therapeutic strategies. On the other hand, unintended interference with their biological functions, e.g., upon inhibition by xenobiotics, can disrupt steroid hormone-mediated effects, thereby contributing to the development and progression of major diseases. Besides a general introduction to pharmacophore modeling and pharmacophore-based virtual screening, exemplary case studies from the field of short-chain dehydrogenase/reductase (SDR) research are presented. These success stories highlight the suitability of pharmacophore modeling for the various application fields and suggest its application also in futures studies.

Study of key residues in MERS-CoV and SARS-CoV-2 main proteases for resistance against clinically applied inhibitors nirmatrelvir and ensitrelvir.

The Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is an epidemic, zoonotically emerging pathogen initially reported in Saudi Arabia in 2012. MERS-CoV has the potential to mutate or recombine with other coronaviruses, thus acquiring the ability to efficiently spread among humans and become pandemic. Its high mortality rate of up to 35% and the absence of effective targeted therapies call for the development of antiviral drugs for this pathogen. Since the beginning of the SARS-CoV-2 pandemic, extensive research has focused on identifying protease inhibitors for the treatment of SARS-CoV-2. Our intention was therefore to assess whether these protease inhibitors are viable options for combating MERS-CoV. To that end, we used previously established protease assays to quantify inhibition of SARS-CoV-2, MERS-CoV and other main proteases. Nirmatrelvir inhibited several of these proteases, whereas ensitrelvir was less broadly active. To simulate nirmatrelvir's clinical use against MERS-CoV and subsequent resistance development, we applied a safe, surrogate virus-based system. Using the surrogate virus, we previously selected hallmark mutations of SARS-CoV-2-Mpro, such as T21I, M49L, S144A, E166A/K/V and L167F. In the current study, we selected a pool of MERS-CoV-Mpro mutants, characterized the resistance and modelled the steric effect of catalytic site mutants S142G, S142R, S147Y and A171S.

Impact of protein and small molecule interactions on kinase conformations.

Protein kinases act as central molecular switches in the control of cellular functions. Alterations in the regulation and function of protein kinases may provoke diseases including cancer. In this study we investigate the conformational states of such disease-associated kinases using the high sensitivity of the kinase conformation (KinCon) reporter system. We first track BRAF kinase activity conformational changes upon melanoma drug binding. Second, we also use the KinCon reporter technology to examine the impact of regulatory protein interactions on LKB1 kinase tumor suppressor functions. Third, we explore the conformational dynamics of RIP kinases in response to TNF pathway activation and small molecule interactions. Finally, we show that CDK4/6 interactions with regulatory proteins alter conformations which remain unaffected in the presence of clinically applied inhibitors. Apart from its predictive value, the KinCon technology helps to identify cellular factors that impact drug efficacies. The understanding of the structural dynamics of full-length protein kinases when interacting with small molecule inhibitors or regulatory proteins is crucial for designing more effective therapeutic strategies.

Highly specific SARS-CoV-2 main protease (Mpro) mutations against the clinical antiviral ensitrelvir selected in a safe, VSV-based system.

In the SARS-CoV-2 pandemic, the so far two most effective approved antivirals are the protease inhibitors nirmatrelvir, in combination with ritonavir (Paxlovid) and ensitrelvir (Xocova). However, antivirals and indeed all antimicrobial drugs are sooner or later challenged by resistance mutations. Studying such mutations is essential for treatment decisions and pandemic preparedness. At the same time, generating resistant viruses to assess mutants is controversial, especially with pathogens of pandemic potential like SARS-CoV-2. To circumvent gain-of-function research with non-attenuated SARS-CoV-2, a previously developed safe system based on a chimeric vesicular stomatitis virus dependent on the SARS-CoV-2 main protease (VSV-Mpro) was used to select mutations against ensitrelvir. Ensitrelvir is clinically especially relevant due to its single-substance formulation, avoiding drug-drug interactions by the co-formulated CYP3A4 inhibitor ritonavir in Paxlovid. By treating VSV-Mpro with ensitrelvir, several highly-specific resistant mutants against this inhibitor were selected, while being still fully or largely susceptible to nirmatrelvir. We then confirmed several ensitrelvir-specific mutants in gold standard enzymatic assays and SARS-CoV-2 replicons. These findings indicate that the two inhibitors can have distinct viral resistance profiles, which could determine treatment decisions.

Cav 1.3-selective inhibitors of voltage-gated L-type Ca2+ channels: Fact or (still) fiction?

Voltage-gated L-type Ca2+ -channels (LTCCs) are the target of Ca2+ -channel blockers (CCBs), which are in clinical use for the evidence-based treatment of hypertension and angina. Their cardiovascular effects are largely mediated by the Cav 1.2-subtype. However, based on our current understanding of their physiological and pathophysiological roles, Cav 1.3 LTCCs also appear as attractive drug targets for the therapy of various diseases, including treatment-resistant hypertension, spasticity after spinal cord injury and neuroprotection in Parkinson's disease. Since CCBs inhibit both Cav 1.2 and Cav 1.3, Cav 1.3-selective inhibitors would be valuable tools to validate the therapeutic potential of Cav 1.3 channel inhibition in preclinical models. Despite a number of publications reporting the discovery of Cav 1.3-selective blockers, their selectivity remains controversial. We conclude that at present no pharmacological tools exist that are suitable to confirm or refute a role of Cav 1.3 channels in cellular responses. We also suggest essential criteria for a small molecule to be considered Cav 1.3-selective.

Protocol for predicting drug-resistant protein mutations to an ERK2 inhibitor using RESISTOR.

Prospective predictions of drug-resistant protein mutants could improve the design of therapeutics less prone to resistance. Here, we describe RESISTOR, an algorithm that uses structure- and sequence-based criteria to predict resistance mutations. We demonstrate the process of using RESISTOR to predict ERK2 mutants likely to arise in melanoma ablating the efficacy of the ERK1/2 inhibitor SCH779284. RESISTOR is included in the free and open-source computational protein design software OSPREY. For complete details on the use and execution of this protocol, please refer to Guerin et al..1.

Disruptor: Computational identification of oncogenic mutants disrupting protein-protein and protein-DNA interactions.

We report an Osprey-based computational protocol to prospectively identify oncogenic mutations that act via disruption of molecular interactions. It is applicable to analyse both protein-protein and protein-DNA interfaces and it is validated on a dataset of clinically relevant mutations. In addition, it is used to predict previously uncharacterised patient mutations in CDK6 and p16 genes, which are experimentally confirmed to impair complex formation.

A comprehensive study of SARS-CoV-2 main protease (Mpro) inhibitor-resistant mutants selected in a VSV-based system.

Nirmatrelvir was the first protease inhibitor (PI) specifically developed against the SARS-CoV-2 main protease (3CLpro/Mpro) and licensed for clinical use. As SARS-CoV-2 continues to spread, variants resistant to nirmatrelvir and other currently available treatments are likely to arise. This study aimed to identify and characterize mutations that confer resistance to nirmatrelvir. To safely generate Mpro resistance mutations, we passaged a previously developed, chimeric vesicular stomatitis virus (VSV-Mpro) with increasing, yet suboptimal concentrations of nirmatrelvir. Using Wuhan-1 and Omicron Mpro variants, we selected a large set of mutants. Some mutations are frequently present in GISAID, suggesting their relevance in SARS-CoV-2. The resistance phenotype of a subset of mutations was characterized against clinically available PIs (nirmatrelvir and ensitrelvir) with cell-based and biochemical assays. Moreover, we showed the putative molecular mechanism of resistance based on in silico molecular modelling. These findings have implications on the development of future generation Mpro inhibitors, will help to understand SARS-CoV-2 protease-inhibitor-resistance mechanisms and show the relevance of specific mutations in the clinic, thereby informing treatment decisions.

RESISTOR: A New OSPREY Module to Predict Resistance Mutations.

Computational, in silico prediction of resistance-conferring escape mutations could accelerate the design of therapeutics less prone to resistance. This article describes how to use the Resistor algorithm to predict escape mutations. Resistor employs Pareto optimization on four resistance-conferring criteria-positive and negative design, mutational probability, and hotspot cardinality-to assign a Pareto rank to each prospective mutant. It also predicts the mechanism of resistance, that is, whether a mutant ablates binding to a drug, strengthens binding to the endogenous ligand, or a combination of these two factors, and provides structural models of the mutants. Resistor is part of the free and open-source computational protein design software OSPREY.

Resistor: An algorithm for predicting resistance mutations via Pareto optimization over multistate protein design and mutational signatures.

Resistance to pharmacological treatments is a major public health challenge. Here, we introduce Resistor-a structure- and sequence-based algorithm that prospectively predicts resistance mutations for drug design. Resistor computes the Pareto frontier of four resistance-causing criteria: the change in binding affinity (ΔKa) of the (1) drug and (2) endogenous ligand upon a protein's mutation; (3) the probability a mutation will occur based on empirically derived mutational signatures; and (4) the cardinality of mutations comprising a hotspot. For validation, we applied Resistor to EGFR and BRAF kinase inhibitors treating lung adenocarcinoma and melanoma. Resistor correctly identified eight clinically significant EGFR resistance mutations, including the erlotinib and gefitinib "gatekeeper" T790M mutation and five known osimertinib resistance mutations. Furthermore, Resistor predictions are consistent with BRAF inhibitor sensitivity data from both retrospective and prospective experiments using KinCon biosensors. Resistor is available in the open-source protein design software OSPREY.