An intracellular hydrophobic nexus critical for hERG1 channel slow deactivation.

Slow deactivation is a critical property of voltage-gated K+ channels encoded by the human Ether-à-go-go-Related Gene 1 (hERG). hERG1 channel deactivation is modulated by interactions between intracellular N-terminal Per-Arnt-Sim (PAS) and C-terminal cyclic nucleotide-binding homology (CNBh) domains. The PAS domain is multipartite, comprising a globular domain (gPAS; residues 26-135) and an N-terminal PAS-cap that is further subdivided into an initial unstructured "tip" (residues 1-12) and an amphipathic α-helical region (residues 13-25). Although the PAS-cap tip has long been considered the effector of slow deactivation, how its position near the gating machinery is controlled has not been elucidated. Here, we show that a triad of hydrophobic interactions among the gPAS, PAS-cap α helix, and the CNBh domains is required to support slow deactivation in hERG1. The primary sequence of this "hydrophobic nexus" is highly conserved among mammalian ERG channels but shows key differences to fast-deactivating Ether-à-go-go 1 (EAG1) channels. Combining sequence analysis, structure-directed mutagenesis, electrophysiology, and molecular dynamics simulations, we demonstrate that polar serine substitutions uncover an intermediate deactivation mode that is also mimicked by deletion of the PAS-cap α helix. Molecular dynamics simulation analyses of the serine-substituted channels show an increase in distance among the residues of the hydrophobic nexus, a rotation of the intracellular gating ring, and a retraction of the PAS-cap tip from its receptor site near the voltage sensor domain and channel gate. These findings provide compelling evidence that the hydrophobic nexus coordinates the respective components of the intracellular gating ring and positions the PAS-cap tip to control hERG1 deactivation gating.

Fusion Position-Dependent Aromatic Transitions of Ligand Backbone Rings for Controlling the Redox Energetics of Photoredox Catalysts.

To reveal, quantify, and rationalize the effect of backbone π-extension on ligand redox activity, we studied the ground- and excited-state reduction potentials of eight ruthenium photoredox catalysts with the formula Ru(ppy)2L (L is the redox-active ligand of the bipyridine family) using density functional theory. Our research underlines the profound importance of the fusion position of backbone aromatic C6 rings on the redox activity of ligands in transition metal photoredox catalysts. Namely, certain fusion positions lead to the dearomatization of C6 rings in ligand-centered electron transfer events, resulting in a thermodynamic penalty equivalent to a half-volt negative shift in the reduction potential. Contrarily, the extent of backbone delocalization shows a minimal impact on redox energetics, which can be explained by the charge concentration at the nitrogen contact atoms in ligand-centered reductions. Grounded in Caulton's conceptual framework, we reaffirm the predictive potency of Lewis structures in ligand-centered redox energetics with qualitative and quantitative data. Our hypothesis regarding the effect of backbone ring dearomatization on redox energetics is further corroborated using magnetic and structure-based aromaticity indicators. Highlighting fusion-dependent dearomatization as a determining factor of ligand-centered electron transfer energetics, our findings hold implications for molecular-level design in advanced electroactive materials and catalysts.

Machine Learning-Driven Classification of Urease Inhibitors Leveraging Physicochemical Properties as Effective Filter Criteria.

Urease, a pivotal enzyme in nitrogen metabolism, plays a crucial role in various microorganisms, including the pathogenic Helicobacter pylori. Inhibiting urease activity offers a promising approach to combating infections and associated ailments, such as chronic kidney diseases and gastric cancer. However, identifying potent urease inhibitors remains challenging due to resistance issues that hinder traditional approaches. Recently, machine learning (ML)-based models have demonstrated the ability to predict the bioactivity of molecules rapidly and effectively. In this study, we present ML models designed to predict urease inhibitors by leveraging essential physicochemical properties. The methodological approach involved constructing a dataset of urease inhibitors through an extensive literature search. Subsequently, these inhibitors were characterized based on physicochemical properties calculations. An exploratory data analysis was then conducted to identify and analyze critical features. Ultimately, 252 classification models were trained, utilizing a combination of seven ML algorithms, three attribute selection methods, and six different strategies for categorizing inhibitory activity. The investigation unveiled discernible trends distinguishing urease inhibitors from non-inhibitors. This differentiation enabled the identification of essential features that are crucial for precise classification. Through a comprehensive comparison of ML algorithms, tree-based methods like random forest, decision tree, and XGBoost exhibited superior performance. Additionally, incorporating the "chemical family type" attribute significantly enhanced model accuracy. Strategies involving a gray-zone categorization demonstrated marked improvements in predictive precision. This research underscores the transformative potential of ML in predicting urease inhibitors. The meticulous methodology outlined herein offers actionable insights for developing robust predictive models within biochemical systems.

From Proteome to Potential Drugs: Integration of Subtractive Proteomics and Ensemble Docking for Drug Repurposing against Pseudomonas aeruginosa RND Superfamily Proteins.

Pseudomonas aeruginosa (P. aeruginosa) poses a significant threat as a nosocomial pathogen due to its robust resistance mechanisms and virulence factors. This study integrates subtractive proteomics and ensemble docking to identify and characterize essential proteins in P. aeruginosa, aiming to discover therapeutic targets and repurpose commercial existing drugs. Using subtractive proteomics, we refined the dataset to discard redundant proteins and minimize potential cross-interactions with human proteins and the microbiome proteins. We identified 12 key proteins, including a histidine kinase and members of the RND efflux pump family, known for their roles in antibiotic resistance, virulence, and antigenicity. Predictive modeling of the three-dimensional structures of these RND proteins and subsequent molecular ensemble-docking simulations led to the identification of MK-3207, R-428, and Suramin as promising inhibitor candidates. These compounds demonstrated high binding affinities and effective inhibition across multiple metrics. Further refinement using non-covalent interaction index methods provided deeper insights into the electronic effects in protein-ligand interactions, with Suramin exhibiting superior binding energies, suggesting its broad-spectrum inhibitory potential. Our findings confirm the critical role of RND efflux pumps in antibiotic resistance and suggest that MK-3207, R-428, and Suramin could be effectively repurposed to target these proteins. This approach highlights the potential of drug repurposing as a viable strategy to combat P. aeruginosa infections.

Unveiling Novel Urease Inhibitors for Helicobacter pylori: A Multi-Methodological Approach from Virtual Screening and ADME to Molecular Dynamics Simulations.

Helicobacter pylori (Hp) infections pose a global health challenge demanding innovative therapeutic strategies by which to eradicate them. Urease, a key Hp virulence factor hydrolyzes urea, facilitating bacterial survival in the acidic gastric environment. In this study, a multi-methodological approach combining pharmacophore- and structure-based virtual screening, molecular dynamics simulations, and MM-GBSA calculations was employed to identify novel inhibitors for Hp urease (HpU). A refined dataset of 8,271,505 small molecules from the ZINC15 database underwent pharmacokinetic and physicochemical filtering, resulting in 16% of compounds for pharmacophore-based virtual screening. Molecular docking simulations were performed in successive stages, utilizing HTVS, SP, and XP algorithms. Subsequent energetic re-scoring with MM-GBSA identified promising candidates interacting with distinct urease variants. Lys219, a residue critical for urea catalysis at the urease binding site, can manifest in two forms, neutral (LYN) or carbamylated (KCX). Notably, the evaluated molecules demonstrated different interaction and energetic patterns in both protein variants. Further evaluation through ADMET predictions highlighted compounds with favorable pharmacological profiles, leading to the identification of 15 candidates. Molecular dynamics simulations revealed comparable structural stability to the control DJM, with candidates 5, 8 and 12 (CA5, CA8, and CA12, respectively) exhibiting the lowest binding free energies. These inhibitors suggest a chelating capacity that is crucial for urease inhibition. The analysis underscores the potential of CA5, CA8, and CA12 as novel HpU inhibitors. Finally, we compare our candidates with the chemical space of urease inhibitors finding physicochemical similarities with potent agents such as thiourea.

Intracellular Helix-Loop-Helix Domain Modulates Inactivation Kinetics of Mammalian TRPV5 and TRPV6 Channels.

TRPV5 and TRPV6 are calcium-selective ion channels expressed at the apical membrane of epithelial cells. Important for systemic calcium (Ca2+) homeostasis, these channels are considered gatekeepers of this cation transcellular transport. Intracellular Ca2+ exerts a negative control over the activity of these channels by promoting inactivation. TRPV5 and TRPV6 inactivation has been divided into fast and slow phases based on their kinetics. While slow inactivation is common to both channels, fast inactivation is characteristic of TRPV6. It has been proposed that the fast phase depends on Ca2+ binding and that the slow phase depends on the binding of the Ca2+/Calmodulin complex to the internal gate of the channels. Here, by means of structural analyses, site-directed mutagenesis, electrophysiology, and molecular dynamic simulations, we identified a specific set of amino acids and interactions that determine the inactivation kinetics of mammalian TRPV5 and TRPV6 channels. We propose that the association between the intracellular helix-loop-helix (HLH) domain and the TRP domain helix (TDh) favors the faster inactivation kinetics observed in mammalian TRPV6 channels.

Structural Insights into the Inhibition Site in the Phosphorylcholine Phosphatase Enzyme of Pseudomonas aeruginosa.

Pseudomonas aeruginosa is a highly pathogenic Gram-negative microorganism associated with high mortality levels in burned or immunosuppressed patients or individuals affected by cystic fibrosis. Studies support a colonization mechanism whereby P. aeruginosa can breakdown the host cell membrane phospholipids through the sequential action of two enzymes: (I) hemolytic phospholipase C acting upon phosphatidylcholine or sphingomyelin to produce phosphorylcholine (Pcho) and (II) phosphorylcholine phosphatase (PchP) that hydrolyzes Pcho to generate choline and inorganic phosphate. This coordinated action provides the bacteria with carbon, nitrogen, and inorganic phosphate to support growth. Furthermore, PchP exhibits a distinctive inhibition mechanism by high substrate concentration. Here, we combine kinetic assays and computational approaches such as molecular docking, molecular dynamics, and free-energy calculations to describe the inhibitory site of PchP, which shares specific residues with the enzyme's active site. Our study provides insights into a coupled inhibition mechanism by the substrate, allowing us to postulate that the integrity of the inhibition site is needed to the correct functioning of the active site. Our results allow us to gain a better understanding of PchP function and provide the basis for a rational drug design that might contribute to the treatment of infections caused by this important opportunistic pathogen.

A Novel Theoretical Probabilistic Model for Opportunistic Routing with Applications in Energy Consumption for WSNs.

This paper proposes a new theoretical stochastic model based on an abstraction of the opportunistic model for opportunistic networks. The model is capable of systematically computing the network parameters, such as the number of possible routes, the probability of successful transmission, the expected number of broadcast transmissions, and the expected number of receptions. The usual theoretical stochastic model explored in the methodologies available in the literature is based on Markov chains, and the main novelty of this paper is the employment of a percolation stochastic model, whose main benefit is to obtain the network parameters directly. Additionally, the proposed approach is capable to deal with values of probability specified by bounded intervals or by a density function. The model is validated via Monte Carlo simulations, and a computational toolbox (R-packet) is provided to make the reproduction of the results presented in the paper easier. The technique is illustrated through a numerical example where the proposed model is applied to compute the energy consumption when transmitting a packet via an opportunistic network.

Elucidating the Structural Basis of the Intracellular pH Sensing Mechanism of TASK-2 K2P Channels.

Two-pore domain potassium (K2P) channels maintain the cell's background conductance by stabilizing the resting membrane potential. They assemble as dimers possessing four transmembrane helices in each subunit. K2P channels were crystallized in "up" and "down" states. The movements of the pore-lining transmembrane TM4 helix produce the aperture or closure of side fenestrations that connect the lipid membrane with the central cavity. When the TM4 helix is in the up-state, the fenestrations are closed, while they are open in the down-state. It is thought that the fenestration states are related to the activity of K2P channels and the opening of the channels preferentially occurs from the up-state. TASK-2, a member of the TALK subfamily of K2P channels, is opened by intracellular alkalization leading the deprotonation of the K245 residue at the end of the TM4 helix. This charge neutralization of K245 could be sensitive or coupled to the fenestration state. Here, we describe the relationship between the states of the intramembrane fenestrations and K245 residue in TASK-2 channel. By using molecular modeling and simulations, we show that the protonated state of K245 (K245+) favors the open fenestration state and, symmetrically, that the open fenestration state favors the protonated state of the lysine residue. We show that the channel can be completely blocked by Prozac, which is known to induce fenestration opening in TREK-2. K245 protonation and fenestration aperture have an additive effect on the conductance of the channel. The opening of the fenestrations with K245+ increases the entrance of lipids into the selectivity filter, blocking the channel. At the same time, the protonation of K245 introduces electrostatic potential energy barriers to ion entrance. We computed the free energy profiles of ion penetration into the channel in different fenestration and K245 protonation states, to show that the effects of the two transformations are summed up, leading to maximum channel blocking. Estimated rates of ion transport are in qualitative agreement with experimental results and support the hypothesis that the most important barrier for ion transport under K245+ and open fenestration conditions is the entrance of the ions into the channel.

Correction: Concha, G., et al. The Insensitivity of TASK-3 K2P Channels to External Tetraethylammonium (TEA) Partially Depends on the Cap Structure. Int. J. Mol. Sci. 2018, 19, 2437.

We would like to submit the following correction to our published paper [...].

The Insensitivity of TASK-3 K2P Channels to External Tetraethylammonium (TEA) Partially Depends on the Cap Structure.

Two-pore domain K⁺ channels (K2P) display a characteristic extracellular cap structure formed by two M1-P1 linkers, the functional role of which is poorly understood. It has been proposed that the presence of the cap explains the insensitivity of K2P channels to several K⁺ channel blockers including tetraethylammonium (TEA). We have explored this hypothesis using mutagenesis and functional analysis, followed by molecular simulations. Our results show that the deletion of the cap structure of TASK-3 (TWIK-related acid-sensitive K⁺ channel) generates a TEA-sensitive channel with an IC50 of 11.8 ± 0.4 mM. The enhanced sensitivity to TEA displayed by the cap-less channel is also explained by the presence of an extra tyrosine residue at position 99. These results were corroborated by molecular simulation analysis, which shows an increased stability in the binding of TEA to the cap-less channel when a ring of four tyrosine is present at the external entrance of the permeation pathway. Consistently, Y99A or Y205A single-residue mutants generated in a cap-less channel backbone resulted in TASK-3 channels with low affinity to external TEA.

The Controlled Release of Abscisic Acid (ABA) Utilizing Alginate-Chitosan Gel Blends: A Synergistic Approach for an Enhanced Small-Molecule Delivery Controller.

The integration of abscisic acid (ABA) into a chitosan-alginate gel blend unveils crucial insights into the formation and stability of these two substances. ABA, a key phytohormone in plant growth and stress responses, is strategically targeted for controlled release within these complexes. This study investigates the design and characterization of this novel controlled-release system, showcasing the potential of alginate-chitosan gel blends in ABA delivery. Computational methods, including molecular dynamics simulations, are employed to analyze the structural effects of microencapsulation, offering valuable insights into complex behavior under varying conditions. This paper focuses on the controlled release of ABA from these complexes, highlighting its strategic importance in drug delivery systems and beyond. This controlled release enables targeted and regulated ABA delivery, with far-reaching implications for pharmaceuticals, agriculture, and plant stress response studies. While acknowledging context dependency, the paper suggests that the liberation or controlled release of ABA holds promise in applications, urging further research and experimentation to validate its utility across diverse fields. Overall, this work significantly contributes to understanding the characteristics and potential applications of chitosan-alginate complexes, marking a noteworthy advancement in the field of controlled-release systems.

Unraveling the key step in the aroma puzzle: Insights into alcohol acyltransferases in strawberries.

Alcohol acyltransferases (AATs) play a crucial role in catalyzing the transfer of acyl groups, contributing to the diverse aroma of fruits, including strawberries. In this research we identified nine AAT genes in strawberries through a comprehensive analysis involving phylogenetics, gene structure, conserved motifs, and structural protein model examinations. The study used the 'Camarosa' strawberry genome database, and experiments were conducted with fruits harvested at different developmental and ripening stages. The transcriptional analysis revealed differential expression patterns among the AAT genes during fruit ripening, with only four genes (SAAT, FaAAT2, FaAAT7, and FaAAT9) showing increased transcript accumulation correlated with total AAT enzyme activity. Additionally, the study employed in silico methods, including sequence alignment, phylogenetic analysis, and structural modeling, to gain insights into the AAT protein model structures with increase expression pattern during fruit ripening. The four modeled AAT proteins exhibited structural similarities, including conserved catalytic sites and solvent channels. Furthermore, the research investigated the interaction of AAT proteins with different substrates, highlighting the enzymes' promiscuity in substrate preferences. The study contributes with valuable information to unveil AAT gene family members in strawberries, providing scientific background for further exploration of their biological characteristics and their role in aroma biosynthesis during fruit ripening.

Structural and transcriptional characterization of pyruvate decarboxylase (PDC) gene family during strawberry fruit ripening process.

Strawberry is one of the most popular fruits in the world, because their high fruit quality, especially with respect to the combination of aroma, flavor, color, and nutritional compounds. Pyruvate decarboxylase (PDC) is the first of two enzymes specifically required for ethanolic fermentation and catalyzes the decarboxylation of pyruvate to yield acetaldehyde and CO2. The ethanol, an important alcohol which acts as a precursor for the ester and other alcohols formation in strawberry, is produced by the PDC. The objective was found all different PDCs genes present in the strawberry genome and investigate PDC gene expression and ligand-protein interactions in strawberry fruit. Volatile organic compounds were evaluated during the development of the fruit. After this, eight FaPDC were identified with four genes that increase the relative expression during fruit ripening process. Molecular dynamics simulations were performed to analyze the behavior of Pyr and TPP ligands within the catalytic and regulatory sites of the PDC proteins. Results indicated that energy-restrained simulations exhibited minor fluctuations in ligand-protein interactions, while unrestrained simulations revealed crucial insights into ligand affinity. TPP consistently displayed strong interactions with the catalytic site, emphasizing its pivotal role in enzymatic activity. However, FaPDC6 and FaPDC9 exhibited decreased pyruvate affinity initially, suggesting unique binding characteristics requiring further investigation. Finally, the present study contributes significantly to understanding PDC gene expression and the intricate molecular dynamics underlying strawberry fruit ripening, shedding light on potential targets for further research in this critical biological pathway.

Cost-Effective Pipeline for a Rational Design and Selection of Capsaicin Analogues Targeting TRPV1 Channels.

Transient receptor potential (TRP) channels constitute a large group of membrane receptors associated with sensory pathways in vertebrates. One of the most studied is TRPV1, a polymodal receptor tuned for detecting heat and pungent compounds. Specific inhibition of the nociceptive transduction at the peripheral nerve represents a convenient approach to pain relief. While acting as a chemoreceptor, TRPV1 shows high sensitivity and selectivity for capsaicin. In contrast to the drugs available on the market that target the inflammatory system, TRPV1 antagonists act as negative modulators of nociceptive transduction. Therefore, the development of compounds modulating TRPV1 activity has expanded dramatically over time. Experimental data suggest that most agonist and antagonist drugs interact at or near capsaicin's binding site. In particular, the properties of capsaicin's head play an essential role in modulating potency and affinity. Here, we explored a cost-efficient pipeline to predict the effects of introducing chemical modifications into capsaicin's head region. An extensive set of molecules was selected by first considering the geometrical properties of capsaicin's binding site and then molecular docking. Finally, the novel ligands were ranked by combining molecular and pharmacokinetic predictions.

Development and Evaluation of Cross-Linked Alginate-Chitosan-Abscisic Acid Blend Gel.

Abscisic acid (ABA) has been proposed to play a significant role in the ripening of nonclimacteric fruit, stomatal opening, and response to abiotic stresses in plants, which can adversely affect crop growth and productivity. The biological effects of ABA are dependent on its concentration and signal transduction pathways. However, due to its susceptibility to the environment, it is essential to find a suitable biotechnological approach to coat ABA for its application. One promising approach is to utilize alginate and chitosan, two natural polysaccharides known for their strong affinity for water and their ability to act as coating agents. In this study, an alginate-chitosan blend was employed to develop an ABA cover. To achieve this, an alginate-chitosan-abscisic acid (ALG-CS-ABA) blend was prepared by forming ionic bonds or complexes with calcium ions, or through dual cross-linking. This was done by dripping a homogeneous solution of alginate-chitosan and ABA into a calcium chloride solution, resulting in the formation of the blend. By combining the unique properties of alginate, chitosan, and ABA, the resulting ALG-CS-ABA blend can potentially offer enhanced stability, controlled release, and improved protection of ABA. These characteristics make it a promising biotechnological approach for various applications, including the targeted delivery of ABA in agricultural practices or in the development of innovative plant-based products. Further evaluation and characterization of the ALG-CS-ABA blend will provide valuable insights into its potential applications in the fields of biomedicine, agriculture, and tissue engineering.

A journey from molecule to physiology and in silico tools for drug discovery targeting the transient receptor potential vanilloid type 1 (TRPV1) channel.

The heat and capsaicin receptor TRPV1 channel is widely expressed in nerve terminals of dorsal root ganglia (DRGs) and trigeminal ganglia innervating the body and face, respectively, as well as in other tissues and organs including central nervous system. The TRPV1 channel is a versatile receptor that detects harmful heat, pain, and various internal and external ligands. Hence, it operates as a polymodal sensory channel. Many pathological conditions including neuroinflammation, cancer, psychiatric disorders, and pathological pain, are linked to the abnormal functioning of the TRPV1 in peripheral tissues. Intense biomedical research is underway to discover compounds that can modulate the channel and provide pain relief. The molecular mechanisms underlying temperature sensing remain largely unknown, although they are closely linked to pain transduction. Prolonged exposure to capsaicin generates analgesia, hence numerous capsaicin analogs have been developed to discover efficient analgesics for pain relief. The emergence of in silico tools offered significant techniques for molecular modeling and machine learning algorithms to indentify druggable sites in the channel and for repositioning of current drugs aimed at TRPV1. Here we recapitulate the physiological and pathophysiological functions of the TRPV1 channel, including structural models obtained through cryo-EM, pharmacological compounds tested on TRPV1, and the in silico tools for drug discovery and repositioning.

Role of Liraglutide Use in Patients With Heart Failure.

Heart failure is a clinical condition in which the heart is unable to maintain adequate cardiac output. Liraglutide is a glucagon-like peptide 1 (GLP-1) analogue that is used for the treatment of type 2 diabetes mellitus, but recent evidence suggests that it might have a beneficial role in treating heart failure. We conducted a review of existing literature and found five relevant studies. Data from these studies were extracted and then extrapolated into results following analysis. Four of the five studies found an increase in heart rate in heart failure patients. All five studies reported an increased rate of hospitalization. The five studies also showed an increased risk of adverse effects such as arrhythmia, ventricular tachycardia, atrial fibrillation, and worsening of heart failure. Given the scarcity of evidence in the available literature on liraglutide in heart failure, more research on this population is required.

Rational Design of Hydrogels for Cationic Antimicrobial Peptide Delivery: A Molecular Modeling Approach.

In light of the growing bacterial resistance to antibiotics and in the absence of the development of new antimicrobial agents, numerous antimicrobial delivery systems over the past decades have been developed with the aim to provide new alternatives to the antimicrobial treatment of infections. However, there are few studies that focus on the development of a rational design that is accurate based on a set of theoretical-computational methods that permit the prediction and the understanding of hydrogels regarding their interaction with cationic antimicrobial peptides (cAMPs) as potential sustained and localized delivery nanoplatforms of cAMP. To this aim, we employed docking and Molecular Dynamics simulations (MDs) that allowed us to propose a rational selection of hydrogel candidates based on the propensity to form intermolecular interactions with two types of cAMPs (MP-L and NCP-3a). For the design of the hydrogels, specific building blocks were considered, named monomers (MN), co-monomers (CM), and cross-linkers (CL). These building blocks were ranked by considering the interaction with two peptides (MP-L and NCP-3a) as receptors. The better proposed hydrogel candidates were composed of MN3-CM7-CL1 and MN4-CM5-CL1 termed HG1 and HG2, respectively. The results obtained by MDs show that the biggest differences between the hydrogels are in the CM, where HG2 has two carboxylic acids that allow the forming of greater amounts of hydrogen bonds (HBs) and salt bridges (SBs) with both cAMPs. Therefore, using theoretical-computational methods allowed for the obtaining of the best virtual hydrogel candidates according to affinity with the specific cAMP. In conclusion, this study showed that HG2 is the better candidate for future in vitro or in vivo experiments due to its possible capacity as a depot system and its potential sustained and localized delivery system of cAMP.

Calcium-Alginate-Chitosan Nanoparticle as a Potential Solution for Pesticide Removal, a Computational Approach.

Pesticides have a significant negative impact on the environment, non-target organisms, and human health. To address these issues, sustainable pest management practices and government regulations are necessary. However, biotechnology can provide additional solutions, such as the use of polyelectrolyte complexes to encapsulate and remove pesticides from water sources. We introduce a computational methodology to evaluate the capture capabilities of Calcium-Alginate-Chitosan (CAC) nanoparticles for a broad range of pesticides. By employing ensemble-docking and molecular dynamics simulations, we investigate the intermolecular interactions and absorption/adsorption characteristics between the CAC nanoparticles and selected pesticides. Our findings reveal that charged pesticide molecules exhibit more than double capture rates compared to neutral counterparts, owing to their stronger affinity for the CAC nanoparticles. Non-covalent interactions, such as van der Waals forces, π-π stacking, and hydrogen bonds, are identified as key factors which stabilized the capture and physisorption of pesticides. Density profile analysis confirms the localization of pesticides adsorbed onto the surface or absorbed into the polymer matrix, depending on their chemical nature. The mobility and diffusion behavior of captured compounds within the nanoparticle matrix is assessed using mean square displacement and diffusion coefficients. Compounds with high capture levels exhibit limited mobility, indicative of effective absorption and adsorption. Intermolecular interaction analysis highlights the significance of hydrogen bonds and electrostatic interactions in the pesticide-polymer association. Notably, two promising candidates, an antibiotic derived from tetracycline and a rodenticide, demonstrate a strong affinity for CAC nanoparticles. This computational methodology offers a reliable and efficient screening approach for identifying effective pesticide capture agents, contributing to the development of eco-friendly strategies for pesticide removal.