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The development of new molecules for the treatment of calmodulin related cardiovascular or neurodegenerative diseases is an interesting goal. In this work, we introduce a novel strategy with four main steps: (1) chemical synthesis of target molecules, (2) Förster Resonance Energy Transfer (FRET) biosensor development and in vitro biological assay of new derivatives, (3) Cheminformatics models development and in vivo activity prediction, and (4) Docking studies. This strategy is illustrated with a case study. Firstly, a series of 4-substituted Riluzole derivatives 1–3 were synthetized through a strategy that involves the construction of the 4-bromoriluzole framework and its further functionalization via palladium catalysis or organolithium chemistry. Next, a FRET biosensor for monitoring Ca2+-dependent CaM-ligands interactions has been developed and used for the in vitro assay of Riluzole derivatives. In particular, the best inhibition (80%) was observed for 4-methoxyphenylriluzole 2b. Besides, we trained and validated a new Networks Invariant, Information Fusion, Perturbation Theory, and Machine Learning (NIFPTML) model for predicting probability profiles of in vivo biological activity parameters in different regions of the brain. Next, we used this model to predict the in vivo activity of the compounds experimentally studied in vitro. Last, docking study conducted on Riluzole and its derivatives has provided valuable insights into their binding conformations with the target protein, involving calmodulin and the SK4 channel. This new combined strategy may be useful to reduce assay costs (animals, materials, time, and human resources) in the drug discovery process of calmodulin inhibitors.

The assessment of peptide–protein interactions is a pivotal aspect of studying the functionality and mechanisms of various bioactive peptides. In this context, it is essential to employ methods that meet specific criteria, including sensitivity, biocompatibility, versatility, simplicity, and the ability to offer real-time monitoring. In cellular contexts, only a few proteins naturally possess inherent fluorescence, specifically those containing aromatic amino acids, particularly tryptophan. Nonetheless, by covalently attaching fluorescent markers, almost all proteins can be modified for monitoring purposes. Among the early extrinsic fluorescent probes designed for this task, dansyl chloride (DNSC) is a notable option due to its versatile nature and reliable performance. DNSC has been the primary choice as a fluorogenic derivatizing reagent for analyzing amino acids in proteins and peptides for an extended period of time. In our work, we have effectively utilized the distinctive properties of dansylated-calmodulin (D-CaM) for monitoring the interaction dynamics between proteins and peptides, particularly in the context of their association with calmodulin (CaM), a calcium-dependent regulatory protein. This technique not only enables us to scrutinize the affinity of diverse ligands but also sheds light on the intricate role played by calcium in these interactions.Key features• Dynamic fluorescence and real-time monitoring: dansyl-modified CaM enables sensitive, real-time fluorescence, providing valuable insights into the dynamics of molecular interactions and ligand binding.• Selective interaction and stable fluorescent adducts: DNSC selectively interacts with primary amino groups, ensuring specific detection and forming stable fluorescent sulfonamide adducts.• Versatility in research and ease of identification: D-CaM is a versatile tool in biological research, facilitating identification, precise quantification, and drug assessment for therapeutic development.• Sensitivity to surrounding alterations: D-CaM exhibits sensitivity to its surroundings, particularly ligand-induced changes, offering subtle insights into molecular interactions and environmental influences.Graphical overviewFluorescence emission profiles of dansylated-calmodulin (D-CaM) in different states. Fluorescence emission spectra of D-CaM upon excitation at 320 nm are depicted. Conditions include apo-D-CaM (gray), holo-D-CaM (red), apo-D-CaM bound to peptide (blue), and holo-D-CaM bound to peptide (purple). Corresponding structural representations of D-CaM next to each condition are superimposed on the respective spectra along with the hydrophobicity of the dansyl environment, which increases upon binding of peptide or Ca2+ to D-CaM. Upon peptide binding to D-CaM, there is an enhancement in the fluorescent intensity of the spectra; upon Ca2+ binding, there is an enhancement of the intensity and a leftward shift of the spectra.

Despite the increasing availability of genomic data and enhanced data analysis procedures, predicting the severity of associated diseases remains elusive in the absence of clinical descriptors. To address this challenge, we have focused on the KV7.2 voltage-gated potassium channel gene (KCNQ2), known for its link to developmental delays and various epilepsies, including self-limited benign familial neonatal epilepsy and epileptic encephalopathy. Genome-wide tools often exhibit a tendency to overestimate deleterious mutations, frequently overlooking tolerated variants, and lack the capacity to discriminate variant severity. This study introduces a novel approach by evaluating multiple machine learning (ML) protocols and descriptors. The combination of genomic information with a novel Variant Frequency Index (VFI) builds a robust foundation for constructing reliable gene-specific ML models. The ensemble model, MLe-KCNQ2, formed through logistic regression, support vector machine, random forest and gradient boosting algorithms, achieves specificity and sensitivity values surpassing 0.95 (AUC-ROC > 0.98). The ensemble MLe-KCNQ2 model also categorizes pathogenic mutations as benign or severe, with an area under the receiver operating characteristic curve (AUC-ROC) above 0.67. This study not only presents a transferable methodology for accurately classifying KCNQ2 missense variants, but also provides valuable insights for clinical counseling and aids in the determination of variant severity. The research context emphasizes the necessity of precise variant classification, especially for genes like KCNQ2, contributing to the broader understanding of gene-specific challenges in the field of genomic research. The MLe-KCNQ2 model stands as a promising tool for enhancing clinical decision making and prognosis in the realm of KCNQ2-related pathologies.

Neuronal KV7 channels, important regulators of cell excitability, are among the most sensitive proteins to reactive oxygen species. The S2S3 linker of the voltage sensor was reported as a site-mediating redox modulation of the channels. Recent structural insights reveal potential interactions between this linker and the Ca2+-binding loop of the third EF-hand of calmodulin (CaM), which embraces an antiparallel fork formed by the C-terminal helices A and B, constituting the calcium responsive domain (CRD). We found that precluding Ca2+ binding to the EF3 hand, but not to EF1, EF2, or EF4 hands, abolishes oxidation-induced enhancement of KV7.4 currents. Monitoring FRET (Fluorescence Resonance Energy Transfer) between helices A and B using purified CRDs tagged with fluorescent proteins, we observed that S2S3 peptides cause a reversal of the signal in the presence of Ca2+ but have no effect in the absence of this cation or if the peptide is oxidized. The capacity of loading EF3 with Ca2+ is essential for this reversal of the FRET signal, whereas the consequences of obliterating Ca2+ binding to EF1, EF2, or EF4 are negligible. Furthermore, we show that EF3 is critical for translating Ca2+ signals to reorient the AB fork. Our data are consistent with the proposal that oxidation of cysteine residues in the S2S3 loop relieves KV7 channels from a constitutive inhibition imposed by interactions between the EF3 hand of CaM which is crucial for this signaling.

Abstract Background The amino acid sequence of proteins generally carries all the necessary information for acquisition of native conformations, but the vectorial nature of translation can additionally determine the folding outcome. Such consideration is particularly relevant in human diseases associated to inherited mutations leading to structural instability, aggregation, and degradation. Mutations in the KCNQ2 gene associated with human epilepsy have been suggested to cause misfolding of the encoded Kv7.2 channel. Although the effect on folding of mutations in some domains has been studied, little is known of the way pathogenic variants located in the calcium responsive domain (CRD) affect folding. Here, we explore how a Kv7.2 mutation (W344R) located in helix A of the CRD and associated with hereditary epilepsy interferes with channel function. Results We report that the epilepsy W344R mutation within the IQ motif of CRD decreases channel function, but contrary to other mutations at this site, it does not impair the interaction with Calmodulin (CaM) in vitro, as monitored by multiple in vitro binding assays. We find negligible impact of the mutation on the structure of the complex by molecular dynamic computations. In silico studies revealed two orientations of the side chain, which are differentially populated by WT and W344R variants. Binding to CaM is impaired when the mutated protein is produced in cellulo but not in vitro, suggesting that this mutation impedes proper folding during translation within the cell by forcing the nascent chain to follow a folding route that leads to a non-native configuration, and thereby generating non-functional ion channels that fail to traffic to proper neuronal compartments. Conclusions Our data suggest that the key pathogenic mechanism of Kv7.2 W344R mutation involves the failure to adopt a configuration that can be recognized by CaM in vivo but not in vitro.