Molecular Modeling Techniques Research Articles

Structural Insights into Dopamine Receptor-Ligand Interactions: From Agonists to Antagonists.

This study explores the intricacies of dopamine receptor-ligand interactions, focusing on the D1R and D5R subtypes. Using molecular modeling techniques, we investigated the binding of the pan-agonist rotigotine, revealing a universal binding mode at the orthosteric binding pocket. Additionally, we analyze the stability of antagonist-receptor complexes with SKF83566 and SCH23390. By examining the impact of specific mutations on ligand-receptor interactions through computational simulations and thermostability assays, we gain insights into binding stability. Our research also delves into the structural and energetic aspects of antagonist binding to D1R and D5R in their inactive states. These findings enhance our understanding of dopamine receptor pharmacology and hold promise for drug development in central nervous system disorders, opening doors to future research and innovation in this field.

Cheminformatics-aided discovery of potential allosteric site modulators of ubiquitin-specific protease 7

Ubiquitin-specific peptidase 7 (USP7) is a deubiquitinating enzyme that mediates the stability and activity of numerous proteins. At basal expression levels, USP7 stabilizes p53 protein, even in the presence of excess MDM2. However, its overexpression leads to the deubiquitination of MDM2 at a rate faster than p53, leading to p53 degradation and pro-tumorigenic roles. Consequently, it is an attractive target for anticancer drug discovery via the modulation of its allosteric site from which the protein is activated. In this study, molecular modeling techniques and cheminformatics approaches were employed to unravel the potential of eighty compounds to serve as its allosteric site modulators. The compounds were initially subjected to virtual screening. Subsequently, the binding free energies of the top four compounds with the highest binding affinities were calculated, and their drug-likeness, and pharmacokinetic and toxicity profiles were evaluated. Ultimately, the complexes of the protein and hit compounds were subjected to a 100 nanoseconds (ns) molecular dynamics simulation. The results of the study revealed eight compounds from the compound library with docking scores ranging from − 7.491 to -11.43 kcal/mol, compared to P217564, which exhibited a docking score of -5.671 kcal/mol. The top four compounds with the highest affinities possessed drug-like properties, and good pharmacokinetic and toxicity profiles, and their predicted inhibitory potentials showed they will be effective at minimal concentration. Also, molecular dynamics simulation confirmed the stability of the protein-ligand complexes. Conclusively, the compounds identified in this study are worthy of further evaluation for the development of allosteric site modulators of USP7.

Engineering Bacterial Chitinases for Industrial Application: From Protein Engineering to Bacterial Strains Mutation! A Comprehensive Review of Physical, Molecular, and Computational Approaches.

Bacterial chitinases are integral in breaking down chitin, the natural polymer in crustacean and insect exoskeletons. Their increasing utilization across various sectors such as agriculture, waste management, biotechnology, food processing, and pharmaceutical industries highlights their significance as biocatalysts. The current review investigates various scientific strategies to maximize the efficiency and production of bacterial chitinases for industrial use. Our goal is to optimize the heterologous production process using physical, molecular, and computational tools. Physical methods focus on isolating, purifying, and characterizing chitinases from various sources to ensure optimal conditions for maximum enzyme activity. Molecular techniques involve gene cloning, site-directed mutation, and CRISPR-Cas9 gene editing as an approach for creating chitinases with improved catalytic activity, substrate specificity, and stability. Computational approaches use molecular modeling, docking, and simulation techniques to accurately predict enzyme-substrate interactions and enhance chitinase variants' design. Integrating multidisciplinary strategies enables the development of highly efficient chitinases tailored for specific industrial applications. This review summarizes current knowledge and advances in chitinase engineering to serve as an indispensable guideline for researchers and industrialists seeking to optimize chitinase production for various uses.

Unveiling the Anticancer Potential: Computational Exploration of Nitrogenated Derivatives of (+)-Pancratistatin as Topoisomerase I Inhibitors.

Cancer poses a substantial global health challenge, driving the need for innovative therapeutic solutions that offer improved effectiveness and fewer side effects. Topoisomerase I (Topo I) has emerged as a validated molecular target in the pursuit of developing anticancer drugs due to its critical role in DNA replication and transcription. (+)-Pancratistatin (PST), a naturally occurring compound found in various Amaryllidaceae plants, exhibits promising anticancer properties by inhibiting Topo I activity. However, its clinical utility is hindered by issues related to limited chemical availability and aqueous solubility. To address these challenges, molecular modelling techniques, including virtual screening, molecular docking, molecular mechanics with generalised born and surface area solvation (MM-GBSA) calculations, and molecular dynamics simulations were utilised to evaluate the binding interactions and energetics of PST analogues with Topo I, comparing them with the well-known Topo I inhibitor, Camptothecin. Among the compounds screened for this study, nitrogenated analogues emerged as the most encouraging drug candidates, exhibiting improved binding affinities, favourable interactions with the active site of Topo I, and stability of the protein-ligand complex. Structural analysis pinpointed key molecular determinants responsible for the heightened potency of nitrogenated analogues, shedding light on essential structural modifications for increased activity. Moreover, in silico absorption, distribution, metabolism, excretion, and toxicity (ADMET) predictions highlighted favourable drug-like properties and reduced toxicity profiles for the most prominent nitrogenated analogues, further supporting their potential as effective anticancer agents. In summary, this screening study underscores the significance of nitrogenation in augmenting the anticancer efficacy of PST analogues targeting Topo I. The identified lead compounds exhibit significant potential for subsequent experimental validation and optimisation, thus facilitating the development of novel and efficacious anticancer therapeutics with enhanced pharmacological profiles.

Effect of Cu2+ on the binding of catechins to zein through multi-spectral and in silico analyses

This study aimed to elucidate how Cu2+ influences the interaction between catechins and zein using multi-spectral and molecular modeling techniques. As a result, UV–vis spectra revealed characteristic changes, indicating chelation between catechins and Cu2+ at a 1:1 M ratio. Fluorescence spectra further confirmed interaction through a static quenching mechanism between catechins/catechin-Cu2+ complexes and zein. Catechins induced changes in the microenvironment and hydrophobicity surrounding the binding site of zein, whereas Cu2+ had minimal impact on these aspects. CD spectra underscored catechins' role in altering zein's secondary structure conformation, alongside Cu2+. Various types of interactions (hydrophobic, hydrogen bonding, electrostatic, and van der Waals) contributed to the binding of catechins/catechin-Cu2+ complexes with zein. Molecular modeling elucidated key residues and binding conformations, highlighting the significance of hydrophobic interactions and hydrogen bonding in their association. These findings not only deepen our understanding of catechin-Cu2+-zein interactions but also underscore their potential applications in the food industry.

Overcoming methicillin resistance by methicillin-resistant Staphylococcus aureus: Computational evaluation of napthyridine and oxadiazoles compounds for potential dual inhibition of PBP-2a and FemA proteins

Abstract The treatment of the various infections caused by Staphylococcus aureus has become challenging due to the evolving resistance against current therapeutics. In this study, the potentials of napthyridine and oxadiazole derivatives to serve as dual inhibitors of penicillin-binding protein 2a (PBP-2a) and FemA protein, which are crucial to resistance to methicillin-based drugs by S. aureus, were evaluated using molecular modeling techniques. Seventy-two compounds were subjected to molecular docking against the proteins, and the hit compounds were subjected to drug-likeness evaluation and in silico pharmacokinetics prediction. The compounds with good safety profiles were subjected to a 250-ns molecular dynamics (MD) simulation and other relevant analyses based on the MD trajectories. Five hit compounds were selected based on their high affinity for the targets as evidenced by their docking scores ranging from −8.6 to −10.1 kcal/mol for PBP-2a and −9.6 to −9.9 kcal/mol for FemA. These compounds also passed Lipinski’s rule of five evaluation with no violation and possessed high human intestinal absorption potential, showcasing their potential as orally administered therapeutic agents. However, three of the compounds were potential mutagens. MD simulation revealed that the final two compounds maintained stable interactions with the target proteins over 250 ns, with minimal deviations and fluctuations. Hydrogen bond stability and energy decomposition analysis further confirmed the strong binding affinity of the hit compounds compared to the control drug, methicillin. Conclusively, the compounds with the CID “135964525” and “44130718” are worthy of further experimental validation in the development of potential inhibitors of PBP-2a and FemA.

In-silico Investigation of Ginseng Phytoconstituents as Novel Therapeutics Against MAO-A.

Ginseng (Panax ginseng) is a herb of medicinal and nutritional importance. Ginseng has been used since ancient times for the treatment of numerous ailments as it has many therapeutic properties. Several phytoconstituents are present in Panax ginseng that possess a variety of beneficial pharmacological properties. To explore the potential of phytoconstituents of Panax ginseng in the treatment of depression, a molecular modeling technique was utilized targeting monoamine oxidase-A (MAO-A). A total of sixty-one phytoconstituents of ginseng were drawn with the help of ChemBioDraw Ultra 12.0 software and PDBs for MAO-A enzyme were retrieved from the RCSB PDB database. The prepared ligands were screened for MAO-A properties using the software Molegro Virtual Docker (MVD 2010.4.1.0). All the prepared ligands were evaluated for drug-likeliness properties using Swiss ADME. Among the docking studies of 60 Ginseng phytochemicals including one standard, 15 phytoconstituents with the highest dock score and better binding interactions were selected further for absorption, distribution, metabolism and excretion (ADME) studies. Stachyose (-227.287, 17 interactions), Raffinose (-222.157, 14 interactions), and Ginsenoside Rg1 (-216.593, 10 interactions) were found to possess better interactions as compared to Clorgyline taken as a standard drug. Stachyose was found to be the most potent inhibitor of MAO-A enzyme under investigation and can be a potential lead molecule for the development of newer phytochemical-based treatment of depression.

Enantioselective Separation and Pharmacokinetics of a Chiral 1,4-Dihydropyrimidine Derivative in Rats: A Combined Chromatography and Docking Approach.

Chirality in 1,4-Dihydropyrimidines influences their pharmacological properties and synthetic strategies. Enantiomers of chiral drugs often exhibit different pharmacokinetic profiles. Therefore, separating and studying individual enantiomers is crucial to optimize drug efficacy and safety. Enantiomeric separation of ±4-(4-chlorophenyl)-6-methyl-2-oxo-N-(O-toyl)-1,2,3,4-tetrahydropyrimidine-5-carboxamide (DP-1), which is a 1,4-Dihydropyrimidine derivative is achieved on CHIRALCEL® OD-H column (particle size: 5 μm, inner diameter: 4.6 mm, length:150 mm), following by investigating the kinetic properties of (R) and (S) enantiomers. The separation was achieved with a mobile phase composed of 70% (v/v) isopropyl alcohol and 30% (v/v) n-hexane. For the bioanalytical study, acetonitrile was used to precipitate the rat plasma samples and validated the method according to USFDA guidelines. The validated bioanalytical method was then successfully applied to determine the pharmacokinetic parameters of the drug in biological samples. Molecular modeling techniques, specifically docking simulations, were employed to predict the elution order of DP-1 enantiomers. The docking results revealed moderate binding interactions between the enantiomers and the chiral stationary phase (CSP), which aligns with the theoretical expectation that stronger interactions lead to longer retention times on the column.

In-silico Molecular Docking of Two Bioactive Constituents (Quercetin 3-Glucuronide and Quercitrin) from Polygonum minus Leaves into Monoamine Oxidase-A Crystal Structure

The aim of the current research was to dock the two abundant bioactive constituents of Polygonum minus leaf extract, in1cluding Quercetin 3-Glucuronide (Miquelianin) and Quercitrin (Quercetin-3-rhamnoside). In-silico Molecular modelling technique was used to predict about a protein (enzyme) interacts with molecules (ligands). Monoamine oxidase-A (MAO-A) is the key enzyme that is involved in the breakdown of neurotransmitters like serotonin and noradrenaline. Drugs that are involved in its inhibition, are considered to be antidepressant agents. This molecular docking study observed the binding energy of selected ligands and their interactions with amino acid residue along with bond types in the MAO-A structure. Molecular docking was done using Molecular Operating Environment (MOE) software, whereas visualization and expression of results were carried out using Discovery Studio (DS) visualizer. Clorgyline was used in this study as a co-crystal ligand, whereas moclobemide was used as a standard MAO-A inhibitor, and Amitriptyline was used as a common antidepressant which also has some MAO-A inhibitory effect. Quercetin 3-glucuronide (Miquelianin) and Quercitrin (Quercetin-3-rhamnoside) have more binding affinities with MAO-A structure as compared to all other drugs. Its interaction pattern was most likely moclobemide and Clorgyline, which are considered standard MAO-A inhibitors in this study. Based on these results, it is concluded that Quercetin 3-Glucuronide (Miquelianin) and Quercitrin (Quercetin-3-rhamnoside) have the potential to become potent MAO-A inhibitors in future.

The Potential of Molecular Docking for Predictive Toxicology.

Molecular modeling techniques are widely used in medicinal chemistry for the study of biological targets, the rational design of new drugs, or the investigation of their mechanism of action.They are also applied in toxicology to identify chemical potential harmful effects.Molecular docking is a computational technique to predict the ligand binding mode and evaluate the interaction energy with a biological target.This chapter describes a computational workflow to predict possible endocrine disruptors on peroxisome proliferator-activated receptor alpha (PPARα), a nuclear receptor involved in glucose and lipid metabolism. The analyzed compounds are food contact chemicals, natural or synthetic substances intentionally added to food or released from the package or during production or technological processes.

Molecular Mechanisms Underlying the Spectral Shift in Zebrafish Cone Opsins.

Visual pigments are essential for converting light into electrical signals during vision. Composed of an opsin protein and a retinal-based chromophore, pigments in vertebrate rods (Rh1) and cones (Rh2) have different spectral sensitivities, with distinct peak absorption wavelengths determined by the shape and composition of the chromophore binding pocket. Despite advances in understanding Rh1 pigments such as bovine rhodopsin, the molecular basis of spectral shifts in Rh2 cone opsins has been less studied, particularly the E122Q mutation, which accounts for about half of the observed spectral shift in these pigments. In this study, we employed molecular modeling and quantum mechanical techniques to investigate the molecular mechanisms behind the spectral difference in blue-shifted Rh2-1 (absorption peak = 467 nm, 122Q) and green-shifted Rh2-4 (absorption peak = 505 nm, 122E) zebrafish cone opsins. We modeled the pigments 3D structures based on their sequences and conducted all-atom molecular dynamics simulations totaling 2 microseconds. Distance analysis of the trajectories identified three key sites: E113, E181, and E122. The E122Q mutation, previously known, validates our findings, while E181 and E113 are newly identified contributors. Structural analysis revealed key features with differing values that explain the divergent spectral sensitivities of Rh2-1 and Rh2-4: 1) chromophore atom fluctuations and C5-C6 torsion angle, 2) binding pocket volume, 3) hydration patterns, and 4) E113-chromophore interaction stability. Quantum mechanics further confirms the critical role of residue E181 in Rh2-1 and E122 in Rh2-4 for their spectral behavior. Our study provides new insights into the molecular determinants of spectral shifts in cone opsins, and we anticipate that it will serve as a starting point for a broader understanding of the functional diversity of visual pigments.

Exploring protein structural ensembles: Integration of sparse experimental data from electron paramagnetic resonance spectroscopy with molecular modeling methods.

Under physiological conditions, proteins continuously undergo structural fluctuations on different timescales. Some conformations are only sparsely populated, but still play a key role in protein function. Thus, meaningful structure-function frameworks must include structural ensembles rather than only the most populated protein conformations. To detail protein plasticity, modern structural biology combines complementary experimental and computational approaches. In this review, we survey available computational approaches that integrate sparse experimental data from electron paramagnetic resonance spectroscopy with molecular modeling techniques to derive all-atom structural models of rare protein conformations. We also propose strategies to increase the reliability and improve efficiency using deep learning approaches, thus advancing the field of integrative structural biology.

Exploring the binding characteristics between lorlatinib and human alpha-1-acid glycoprotein: Multispectral and molecular modeling techniques

Approval in 2019 was granted for the highly selective, targeted agent lorlatinib, which primary target is ROS1 and ALK. The purpose of this work was to examine the binding mechanism between lorlatinib (LOR) and HAG employing multispectral and molecular modeling techniques. Fluorescence data demonstrated that LOR quenched HAG fluorescence as a static quenching, interecalated into the hydrophobic cavity of HAG with a moderate affinity. Thermodynamic and competitive experiments pointed out that LOR bound with HAG primarily through hydrogen bonding, hydrophobic, and van der Waals forces. Circular dichroism, three-dimensional and synchronous fluorescence spectroscopic studies noted that the secondary structure of HAG and microenvironments around tyrosine (Tyr) and tryptophan (Trp) residues were altered due to binding with LOR. The contribution of each energy involved in binding process of LOR and HAG has been analyzed by molecular simulation techniques. Besides, the environmental conditions with metal ions have also been studied. The present study is expected to provide a theoretical basis for further studying the metabolism of LOR in vivo, which may help to gain a deeper understanding of the general pharmacological activity of the drug.

Molecular insight into binding affinities and blockade effects of selected flavonoid compounds on the PD-1/PD-L1 pathway.

This study investigated the binding mechanisms of the flavonoids apigenin (Api), kaempferol (Kmp), and quercetin (Que) to the PD-L1 dimer using a combination of molecular modeling and experimental techniques. The binding free energy results demonstrated that the flavonoids could tightly bind to the PD-L1 dimer, with the binding abilities following the trend Que > Kmp > Api. Key residues Ile54, Tyr56, Met115, Ala121, and Tyr123 were identified as important for binding. The flavonoids primarily bind to the C-, F-, and G-sheet domains. The spontaneous formation of the complex systems was mainly driven by hydrophobic forces. Dynamic cross-correlation matrix and secondary structure analyses further indicated that the studied flavonoids could stably interact with the binding sites. ELISA results showed that the flavonoids could effectively block PD-1/PD-L1 interactions, although the inhibitory activity of Api was weaker. Therefore, flavonols might be more effective inhibitors compared to flavones. The findings of this study are expected to contribute to the development of novel flavonoids targeting the PD-1/PD-L1 pathway.

Unveiling the potential of novel 5α-reductase inhibitors via ligand based drug design, molecular docking and ADME predictions to manage BPH

Benign prostatic hyperplasia (BPH), a prevalent condition among elderly males characterized by the non-cancerous enlargement of the prostate gland is due to the increased stromal and epithelial cell numbers. The enlargement is driven by an active dihydrotestosterone (DHT), synthesized from its prohormone testosterone under the catalytic effect of 5α-reductase Type-II (5-AR2) enzyme. To reduce the increased DHT levels and ultimately to control prostate growth, inhibition of the 5-AR represent an interesting therapeutic target. The 3D crystallography structure 5-AR2, a member of the steroid 5-AR family belonging to the class of oxidoreductase has been resolved recently and opened the door to develop selective novel inhibitors of 5-AR Type-II isoform using molecular modeling techniques. The Force field and Gaussian-field three-dimensional quantitative structure–activity relationship (3D-QSAR) models have been developed using 42 selective 5-AR2 inhibitors belonging to chemical class of steroidal androstene. Partial least squares analysis produced statistically significant model with R2training = 0.9367, 0.9459 and predictability Q2test = 0.7233, 0.8595. Developed 3D-QSAR model include steric, electrostatic, hydrophobic, and hydrogen bond acceptor and donor field indicators, whereas the potential field contributions indicated the importance of steric feature in governing their biological activity. Protein-ligand interaction pattern analysis revealed that amino acid residues GLU57, ARG114, TYR91 present in the active site of 5-AR2 are crucial for lower energy complexes with good binding affinity. Identified hits were finally adjudged for their druggability by determining in-silico pharmacokinetic parameters. Further, RMSD, binding free energy calculations and post MD analysis demonstrated the enhanced binding affinity with better ΔGbind value (-79.6 ± 3.9 kcal/mol) of identified ligand A-10 than the reference molecule finasteride (-69.13 ± 4.69 kcal/mol). Combined approach of ligand-based and structure-based models have provided an improved understanding of the structural properties of androstene class that may be further used to develop novel 5-AR2 inhibitors to be useful in BPH.

Understanding the Role of Layered Minerals in the Emergence and Preservation of Proto-Proteins and Detection of Traces of Early Life.

ConspectusThe origin of life remains one of the most profound mysteries in science. Over millennia, theories have evolved, yet the question persists: How did life emerge from inanimate matter? At its core, the study of life's origin offers insights into our place in the universe and the nature of life itself. By delving into the chemical and geological processes that led to life's emergence, scientists gain a deeper understanding of the fundamental principles that govern living systems. This knowledge not only expands our scientific understanding but also has profound implications for fields ranging from astrobiology to synthetic biology.This research employs a multidisciplinary approach, combining a diverse array of techniques, from space missions to wet laboratory experiments to theoretical modeling. Investigations into the formation of the first proto-biomolecules are tailored to explore both the complex molecular processes that underpin life and the geological contexts in which these processes may have occurred. While laboratory experiments are aimed at mimicking the processes of early planets, not every process and sample is attainable. To this end, we demonstrate the use of molecular modeling techniques to complement experimental efforts and extraterrestrial missions. The simulations enable researchers to test hypotheses and explore scenarios that are difficult or impossible to replicate in the laboratory, bridging gaps in our understanding of prebiotic processes across vast time and space scales.Minerals, particularly layered structures like clays and hydrotalcites, play diverse and pivotal roles in the origin of life. They concentrate organic species, catalyze polymerization reactions (such as peptide formation), and provide protective environments for the molecules. Minerals have also been suggested to have acted as primitive genetic materials. Nevertheless, they may lack the ability for long-term information replication. Instead, we suggest that minerals may act as transcribers of information encoded in environmental cyclic phenomena, such as tidal or seasonal changes. We argue that extensive protection of the produced polymer will immobilize it, making it inactive for any further function. Therefore, in order to generate a functional polymer, it is essential that it remains mobile and chemically active. Furthermore, we suggest a route to the identification of pseudobiosignatures, a polymer that was polymerized on the same mineral surface and consequently retained through overprotection.This Account presents a comprehensive evaluation of the current understanding of the role of layered mineral surfaces on life's origin and biosignature preservation. It highlights the complexity of mineral-organic interactions and proposes pathways for proto-biomolecule emergence and methods for identifying and interpreting potential biosignatures. Ultimately, the quest to uncover the origin of life continues to drive scientific exploration and innovation, offering profound insights into the fundamental nature of existence and our place in the universe.

Enzymatically Mediated In Situ Generation of Z-Scheme Bi2S3/Bi2MoO6 Heterojunction-Based Organic Photoelectrochemical Transistor for METTL3/METTL14 Detection.

The OPECT biosensing platform, which connects optoelectronics and biological systems, offers significant amplification and more possibilities for research in biological applications. In this work, a homogeneous organic photoelectrochemical transistor (OPECT) biosensor based on a Bi2S3/Bi2MoO6 heterojunction was constructed to detect METTL3/METTL14 protein activity. The METTL3/METTL14 complex enzyme was used to catalyze adenine (A) on an RNA strand to m6A, protecting m6A-RNA from being cleaved by an E. coli toxin (MazF). Alkaline phosphatase (ALP) catalyzed the conversion of Na3SPO3 to H2S through an enzymatic reaction. Due to the adoption of the strategy of no fixation on the electrode, the generated H2S was easy to diffuse to the surface of the ITO electrode. The Bi2S3/Bi2MoO6 heterojunction was formed in situ through a chemical replacement reaction with Bi2MoO6, improving photoelectric conversion efficiency and realizing signal amplification. Based on this "signal on" mode, METTL3/METTL14 exhibited a wide linear range (0.00001-25 ng/μL) between protein concentration and photocurrent intensity with a limit of detection (LOD) of 7.8 fg/μL under optimal experimental conditions. The applicability of the developed method was evaluated by investigating the effect of four plasticizers on the activity of the METTL3/METTL14 protein, and the molecular modeling technique was employed to investigate the interaction between plasticizers and the protein.

Structural Characterization of Heat Shock Protein 90β and Molecular Interactions with Geldanamycin and Ritonavir: A Computational Study.

Drug repositioning is an important therapeutic strategy for treating breast cancer. Hsp90β chaperone is an attractive target for inhibiting cell progression. Its structure has a disordered and flexible linker region between the N-terminal and central domains. Geldanamycin was the first Hsp90β inhibitor to interact specifically at the N-terminal site. Owing to the toxicity of geldanamycin, we investigated the repositioning of ritonavir as an Hsp90β inhibitor, taking advantage of its proven efficacy against cancer. In this study, we used molecular modeling techniques to analyze the contribution of the Hsp90β linker region to the flexibility and interaction between the ligands geldanamycin, ritonavir, and Hsp90β. Our findings indicate that the linker region is responsible for the fluctuation and overall protein motion without disturbing the interaction between the inhibitors and the N-terminus. We also found that ritonavir established similar interactions with the substrate ATP triphosphate, filling the same pharmacophore zone.

(Invited) Advances in Modeling Ion Transport in Micropores and Charging Behavior of Porous Electrodes: Merging Molecular Insights with Machine Learning for Energy Storage

Electric double layer (EDL) charging is a complex process coupling electro-osmotic flow, surface reactions, and ion concentration gradients. The charging dynamics depends on the properties of electrolyte and electrode structure, as well as initial and boundary conditions. While molecular dynamics (MD) simulations and first-principles calculations can encompass all factors, their computational demands are substantial even for simple electrochemical systems such as electrolytes near a planar surface. This presentation explores recent advancements in modeling ion transport in micropores and the charging behavior of porous electrodes with different theoretical and simulation methods. Illustrative examples will be discussed on the integration of molecular modeling and machine-learning techniques to enhance our understanding of complex electrochemical processes and improve the design of energy storage devices.

Identification of Selective JAK3/STAT1 and CYP34A from Pyrazolopyrimidine Derivatives: A Search for Potential Drug Targets for Rheumatoid Arthritis using In-silico Drug Discovery Techniques

Objective: This study aimed to discover a novel active compound capable of effectively inhibiting JAK3/STAT1 and CYP3A4 using molecular modelling techniques, with the goal of treating autoimmune diseases such as cancer and specifically rheumatoid arthritis. The study involved modelling compounds derived from pyrazolopyrimidine, followed by screening methods to identify the most promising compounds. Moreover, this study seeks to identify potential compounds that can inhibit JAK3/STAT through molecular modelling techniques and validate the stability and affinity of the predicted molecule. Methods: Various molecular modelling techniques were employed to identify potential compounds and assess the stability and affinity of the predicted molecule. A pharmacophore hypothesis was developed to obtain crucial information about the experimental series of pyrazolopyrimidine studied, which served as the basis for designing new molecules. Additionally, ADMET was utilized to predict and evaluate the pharmacokinetic properties and potential toxicity of the compound prior to synthesis or utilization. To determine the essential residues involved in the interaction between the molecule and the target JAK3 protein, the covalent docking method was applied. We further validated the binding stability of the JAK3 protein with the ligands ZINC62162141 and Tofacitinib, both of which have been approved by the FDA for JAK3/STAT inhibition., using DFT/B3LYP/6-31G molecular dynamics simulations lasting 1000 ns and MM/GBSA. Results: During the study, we identified compounds that displayed notable activity against JAK3/STAT, specifically those containing thiadiazol, oxadiazol, and chlorophenyl groups. Additionally, the pharmacophore model, ADRRR_1, exhibited promising potential for predicting new molecules. The predicted compound, ZINC62162141, demonstrated favourable ADMET properties, including inhibition of CYP3A4. Furthermore, we assessed its binding stability to the target protein and determined its affinity for the protein-ligand complex using MMGBSA. Conclusion: The results of this study suggest that the compounds identified have the potential to be promising candidates for inhibiting JAK3/STAT and CYP3A4, offering potential therapeutic benefits for the treatment of rheumatoid arthritis. These findings provide a foundation for subsequent experimental validation and the development of novel drugs in this field.