Docking Complex Research Articles

Mapping the Intersubunit Interdomain FMN-Heme Interactions in Neuronal Nitric Oxide Synthase by Targeted Quantitative Cross-Linking Mass Spectrometry.

Nitric oxide synthase (NOS) in mammals is a family of multidomain proteins in which interdomain electron transfer (IET) is controlled by domain-domain interactions. Calmodulin (CaM) binds to the canonical CaM-binding site in the linker region between the FMN and heme domains of NOS and allows tethered FMN domain motions, enabling an intersubunit FMN-heme IET in the output state for NO production. Our previous cross-linking mass spectrometric (XL MS) results demonstrated site-specific protein dynamics in the CaM-responsive regions of rat neuronal NOS (nNOS) reductase construct, a monomeric protein [Jiang et al., Biochemistry, 2023, 62, 2232-2237]. In this work, we have extended our combined approach of XL MS structural mapping and AlphaFold structural prediction to examine the homodimeric nNOS oxygenase/FMN (oxyFMN) construct, an established model of the NOS output state. We employed parallel reaction monitoring (PRM) based quantitative XL MS (qXL MS) to assess the CaM-induced changes in interdomain dynamics and interactions. Intersubunit cross-links were identified by mapping the cross-links onto top AlphaFold structural models, which was complemented by comparing their relative abundances in the cross-linked dimeric and monomeric bands. Furthermore, contrasting the CaM-free and CaM-bound nNOS samples shows that CaM enables the formation of the intersubunit FMN-heme docking complex and that CaM binding induces extensive, allosteric conformational changes across the NOS regions. Moreover, the observed cross-links sites specifically respond to changes in ionic strength. This indicates that interdomain salt bridges are responsible for stabilizing and orienting the output state for efficient FMN-heme IET. Taken together, our targeted qXL MS results have revealed that CaM and ionic strength modulate specific dynamic changes in the CaM/FMN/heme complexes, particularly in the context of intersubunit interdomain FMN-heme interactions.

Investigating the potential of Juglans regia phytoconstituents for the treatment of cervical cancer utilizing network biology and molecular docking approach.

The fourth most frequent type of cancer in women and the leading cause of mortality for females worldwide is cervical cancer. Traditionally, medicinal plants have been utilized to treat various illnesses and ailments. The molecular docking method is used in the current study to look into the phytoconstituents of Juglans regia's possible anticancer effects on cervical cancer target proteins. This work uses the microarray dataset analysis of GSE63678 from the NCBI Gene Expression Omnibus database to find differentially expressed genes. Furthermore, protein-protein interactions of differentially expressed genes were constructed using network biology techniques. The top five hub genes (IGF1, FGF2, ESR1, MYL9, and MYH11) are then determined by computing topological parameters with Cytohubba. In addition, molecular docking research was performed on Juglans regia phytocompounds that were extracted from the IMPPAT database versus hub genes that had been identified. Utilizing molecular dynamics, simulation confirmed that prioritized docked complexes with low binding energies were stable.

Unveiling the phytochemical profiles, selective bioactivity potential, and molecular docking study of bioactive compounds with target proteins using optimized bark extracts of Grewia asiatica L.

The current study aimed to explore the phytochemicals, estimate the anti-inflammatory, antioxidant, antimicrobial, and anticancer potentials of polyphenol enriched methanolic bark extract of Grewia asiatica (PEMGa), and perform molecular docking studies with identified phytocompounds. Here, we utilized response surface methodology (RSM) with a Box Behnken design (BBD) to enhance the phenolic content of the methanolic extract from G. asiatica bark by optimizing three crucial parameters like extraction time (h), temperature of extraction (°C), and solvent ratio (% v/v of methanol: water). Phytochemical quantification of PEMGa illustrated that the bark part contains a good amount of therapeutically potent phytochemical groups like phenolics, flavonoids, and tannins. Additionally, through HPLC analysis, eight compounds belonging to the phenolic and flavonoid groups have been quantified from PEMGa. By GC-MS (Gas chromatography–mass spectrometry) analysis of PEMGa, eleven phytochemicals were identified. Moreover, employing in-vitro bioactivity studies, PEMGa has unveiled its remarkable potential as an anti-inflammatory, antimicrobial, antioxidant, and anticancer agent. During the in-silico molecular docking study, out of eleven phytocompounds identified by the GC-MS study, three compounds, namely, γ-sitosterol, stigmasterol, and campesterol, formed the most stable docked complex with anti-inflammatory, antimicrobial, and antioxidant target proteins. The present study provides justification for the bark part of G. asiatica as a rich source of potent phytochemicals, and its potential against oxidative stresses, inflammations, cancer, and microbial infections.

2,3-Dichloronaphthoquinone derivatives: Synthesis, antimicrobial activity, molecular modelling and ADMET studies

In the present study, an intermediate namely 2-(3-bromopropylamino)-3-chloronaphthalene-1,4-dione was initially synthesized via the nucleophilic addition–elimination reaction between 2,3-dichloro-1,4-naphthoquinone and 3-bromo-1-aminopropane. Then a coupling reaction between the intermediate and piperazine derivatives yielded a number of 1,4-naphthoquinone derivatives. Spectroscopic analysis successfully characterized the products that were obtained in good yields. In vitro antibacterial properties of the compounds were examined against different bacterial strains. In vitro antibacterial properties of the compounds were examined against the bacterial strains S. Aureus, E. Faecalis, E. Coli and P. Aeruginosa. While compound 9 was found to be effective against all bacterial strains used, compound 12 was active against three strains and compounds 10 and 11 were effective against the two. None of the compounds are effective against C. albicans strain. In silico molecular docking studies revealed that all compounds had docking scores comparable to the antibacterial drugs ciprofloxacin and gentamicin and might be considered as DNA gyrase B inhibitors. Molecular dynamics simulations were also conducted for a better understanding of the stability and the selected docked complexes. Additionally, the drug similarity of the synthesized compounds and ADMET characteristics were examined in conjunction with the antibiotic ciprofloxacin, and drug potentials were then evaluated. Compatible predictions were found with the drug similarity and ADMET parameters.

Synthesis, spectroscopic analysis, and computational-based investigations on ‘azo-coumarin-Co(II)-galangin’ hybrids exhibit multipotential activities

The present study synthesized a series of cobalt (II) metal ion frame hybrid candidates (6a–6f) bearing phyto-flavonol galangin with substituted aryl diazenyl coumarins, and further structural confirmation was validated by various spectral techniques, including NMR, ATR-FTIR, UV-vis, HPLC, XRD, etc. Therapeutic potency was investigated via PASS (prediction of activity spectra for substances), molecular docking, molecular dynamics simulation, prediction of toxicity, pharmacokinetics, and drug-likeness scores, along with the highest occupied molecular orbital (HOMO), the lowest unoccupied molecular orbital (LUMO), with their energy gaps (ΔEH–L) to locate the most potential therapeutic candidates. The PASS prediction (Pa > Pi score) showed that proposed metal complexes have kinase inhibitors, antioxidative, and antischistosomal activities with potential molecular docking scores (> −7 kcal/mol) against selected targeted enzymes. Further, the MD-simulation (RMSD, RMSF, Rg, and H-bonds) of the most potential docking complex, ‘HER2-6d’, showed a minimum deviation similar to the standard drug (lapatinib) at 100 ns, indicating that 6d could be a potential noncovalent anticancer inhibitor. In addition, metal complexes possess a non-toxic and ideal drug-ability profiles, and positive electron space in an excited state increases the binding affinity towards target enzymes. Among all six ligands, 6c and 6d were the two most multipotent therapeutic agents from the above analyses. In summary, this could be a feasible approach towards the utilization of phytochemicals in mainstream therapeutic applications, where bioinformatics tools help to select a lead drug candidate at an early stage and guide for higher experimental success by proceeding with potential candidates. Communicated by Ramaswamy H. Sarma

Molecular modeling of novel 2-aminopyridine derivatives as potential JAK2 inhibitors: a rational strategy for promising anticancer agents

Janus kinase 2(JAK2) is a potential target for anticancer drugs in the treatment of numerous myeloproliferative diseases due to its central role in the JAK/STAT signaling cascade. In this study, the binding behavior of 2 amino-pyridine derivatives as JAK2 inhibitors was investigated by using multifaceted strategies including 3D-QSAR, molecular docking, Fingerprint analysis, MD simulations, and MM-PBSA calculations. A credible COMFA (q 2 = 0.606 and r 2 = 0.919) and COMSIA (q 2 = 0.641 and r 2 = 0.992) model was developed, where the internal and external validation revealed that the obtained 3D-QSAR models could be capable of predicting bioactivities of JAK2 inhibitors. The structural criteria provided by the contour maps of model were used to computationally develop more potent 100 new JAK2 inhibitors. Docking studies were conducted on the model data set and newly developed compounds (in-house library) to demonstrate their binding mechanism and highlight the key interacting residues within JAK2 active site. The selected docked complexes underwent MD simulation (100 ns), which contributed in the further study of the binding interactions. Binding free energy analyses (MMGB/PBSA) revealed that key residues such as Glu930, Leu932 (hinge region), Asp939 (solvent accessible region), Arg980, Asn981and Asp994 (catalytic site) have a significantly facilitate ligand-protein interactions through H-bonding and van der Waals interactions. The preliminary in-silico ADMET evaluation revealed encouraging results for all the modeled and in-house library compounds. The findings of this research have the potential to offer valuable recommendations for the advancement of novel, potent, and efficacious JAK2 inhibitors. Overall, this work has successfully employed a wide range of computer-based methodologies to understand the interaction dynamics between 2-amino-pyridine derivatives and the JAK2 enzyme, which is a crucial target in myeloproliferative disorders. Communicated by Ramaswamy H. Sarma

Deciphering the molecular mechanism of Bu Yang Huan Wu Decoction in interference with diabetic pulmonary fibrosis via regulating oxidative stress and lipid metabolism disorder

BackgroundDiabetes mellitus type 2 and pulmonary fibrosis have been found to be closely related in clinical practice. Diabetic pulmonary fibrosis (DPF) is a complication of diabetes mellitus, but its treatment has yet to be thoroughly investigated. Bu Yang Huan Wu Decoction (BYHWD) is a well-known traditional Chinese prescription that has shown great efficacy in treating pulmonary fibrosis with hypoglycemic and hypolipidemic effects. MethodsThe active ingredients of BYHWD and the corresponding targets were retrieved from the Traditional Chinese Medicine Systematic Pharmacology Database (TCMSP) and SymMap2. Disease-related targets were obtained from the GeneCard, OMIM and CTD databases. GO enrichment and KEGG pathway enrichment were carried out using the DAVID database. AutoDock Vina software was employed to perform molecular docking. Molecular dynamics simulations of proteinligand complexes were conducted by Gromacs. Animal experiments were further performed to validate the effects of BYHWD on the selected core targets, markers of oxidative stress, serum lipids, blood glucose and pulmonary fibrosis. ResultsA total of 84 active ingredients and 830 target genes were screened in BYHWD, among which 56 target genes intersected with DPF-related targets. Network pharmacological analysis revealed that the active ingredients can regulate target genes such as IL-6, TNF-α, VEGFA and CASP3, mainly through AGE-RAGE signaling pathway, HIF-1 signaling pathway and TNF signaling pathway. Molecular docking and molecular dynamics simulations suggested that IL6-astragaloside IV, IL6-baicalein, TNFα-astragaloside IV, and TNFα-baicalein docking complexes could bind stably. Animal experiments showed that BYHWD could reduce the expression of core targets such as VEGFA, CASP3, IL-6 and TNF-α. In addition, BYHWD could reduce blood glucose, lipid, and MDA levels in DPF while increasing the activities of SOD, CAT and GSH-Px. BYHWD attenuated the expression of HYP and collagen I, mitigating pathological damage and collagen deposition within lung tissue. ConclusionsBYHWD modulates lipid metabolism disorders and oxidative stress by targeting the core targets of IL6, TNF-α, VEGFA and CASP3 through the AGE-RAGE signaling pathway, making it a potential therapy for DPF.

Identification of phytocompounds as potent inhibitors of sodium/glucose cotransporter-2 leading to diabetes treatment

Type-II diabetes, a major metabolic disorder has threatened the very existence of a healthy life since long ago. Commercially available antidiabetic drugs are known for several adverse effects. The present study attempted to identify potential phytocompounds as inhibitors of sodium/glucose cotransporter-2 (SGLT2), a major protein that helps in glucose re-absorption from renal tubules. A total of 28 phytocompounds were collected based on the literature survey. 3D co-ordinates of phytocompounds were collected from PubChem database. Molecular docking was carried out with SGLT2 protein and the best 3 docking complexes were subjected to molecular dynamics simulation for 100 ns. Free energy changes were also analyzed using MM/PBSA analysis. Phytocompounds were also analyzed for their drug-likeness and ADMET properties. Docking study observed a strong binding affinity of phytocompounds (> −7.0 kcal/mol). More than 10 phytocompounds showed better binding affinity compared to reference drugs. Further analysis of three best docking complexes when analyzed by MD simulation showed better stability and compactness of the complexes compared to reference drug, empagliflozin. MM/PBSA analysis also revealed that van der Waals force and electrostatic energy are the major binding energy involved in the complex formation. Like docking energy, free energy analysis also observed stronger binding energies (ΔGGAS) in SGLT2-phytocompound complexes compared to empagliflozin complex. All the phytocompounds showed drug-likeness and considerable ADMET properties. The study, therefore, suggests that Trifolirhizin-6′-monoacetate, Aspalathin, and Quercetin-3-glucoside could be a possible inhibitor of SGLT2 protein. However, further studies need to be carried out to reveal the exact mode of activity. Communicated by Ramaswamy H. Sarma

Designing of a Novel Candidate Multi-epitope Vaccine to boost Immune Responses against SARS‐COV‐2 using Immunoinformatics and Machine Learning based Approach

Background: The fast development of an effective vaccine is the major demand for protection against the SARS-COV-2 virus outbreak. With the vast volume of data and the requirement for automatic abstract property learning, machine learning (ML) as a branch of artificial intelligence (AI) has a significant contribution in areas of vaccine discovery. The rise of ML has greatly accelerated the often lengthy vaccine approval process. ML models for COVID-19 vaccine development focus on the prediction of potential epitopes by using a variety of techniques, such as artificial neural networks, gradient boosting decision trees and deep neural networks. : In this regard, immuno-informatics tools are time-saving and cost-effective methods to hasten the design and establishment of a proficient multi-peptide candidate vaccine. The utilization of multi-epitope-based vaccines has been demonstrated to be a promising immunization approach against viruses due to the induction of long-term protective immunity. Methods: In the present study, a comprehensive computational and machine learning based approach was conducted to design a multi-epitope-based potential candidate vaccine composed of cytotoxic T lymphocyte (CTL) and helper T lymphocyte (HTL) epitopes of conserved regions of Spike and Nucleocapsid proteins. The potential viral peptides as the candidate vaccine were screened regarding convenient features like hydrophilicity, flexibility, antigenicity, and charging properties. In the next step, the vaccine efficacy needs to be improved by an immune adjuvant. For this purpose, the C-terminal domain of the heat shock protein gp96 (CT-GP96) was applied as a potent adjuvant for enhancing immunity. The five assembled constructs with different peptide orders were generated and fused with the assistance of suitable linkers. All five assembled candidate vaccine constructs were modeled and their 3D structures were assessed in terms of strong immune responses stimulation and their structural stability and immune processing for response induction. Finally, the best refined model was docked to toll-like receptor 4 (TLR4). Furthermore, Molecular Dynamics (MD) simulation of the vaccine-receptor complex was done to assess the stability and related physical movements of the vaccine-TLR4 docking complex. The final candidate vaccine was computationally cloned in E. coli expression host to guarantee its high level of production. Results: Following a comprehensive immune-informatics and machine learning-based approach, the best conserved CTL and HTL immune stimulant epitopes were selected and assembled in different orders to build five different constructs. The final validated candidate vaccine construct was selected according to its efficacy, stability, and exposure ability, molecular docking analysis with TLR4. The molecular simulations by iMODS software also confirmed the stability of the binding interface. Additionally, the computational cloning of the final assembled candidate vaccine with pET28a plasmid showed the possibility of high level production of the vaccine construct post transformation in an E. coli host. Conclusion: The computational analysis indicated that this construct can be proposed as a potent prophylactic and therapeutic candidate multi-epitope vaccine against SARS-COV-2 once its effectiveness is verified by experimental and animal studies.

Discovery of multitarget-directed small molecule inhibitors from Andrographis paniculata for Nipah virus disease therapy: Molecular docking, molecular dynamics simulation and ADME-Tox profiling

Nipah virus (NiV), an emerging highly infectious agent, causes fatal infection to humans through zoonosis, particularly in Asian countries including India. No specific treatment or vaccine is available to cure or combat the NiV infection. Targetable plant-based computer-assisted drug discovery is a novel approach to combat NiV disease. The purpose of the current in silico study was to evaluate the potential of Andrographis paniculata phytochemicals to act as drug molecules to combat NiV disease by targeting multiple NiV proteins: attachment glycoprotein (NiV-G), nucleoprotein (NiV-N) and phosphoprotein (NiV-P). Six phytochemicals from A. paniculata: andrograpanin (AGNN), andrographidine E (AGDN), andrographin (AGPN), andrographolide (AGLD), deoxyandrographolide (DGLD) and neoandrographolide (NGLD) were docked against NiV-G, NiV-N and NiV-P. Outcomes of molecular docking approved the anti-NiV capacity of A. paniculata compounds with top binding affinity of NGLD against all the targets NiV-G, NiV-N and NiV-P with binding energies -8.1, -7.7 and -6.0 kcal/mol, respectively. The molecular dynamic simulation results further validated the protein-ligand docked complexes’ stability. Compared to the A. paniculata phytochemicals, standard antivirals, favipiravir and ribavirin, had low efficacy against all the target proteins. Furthermore, the A. paniculata phytocompounds displayed acceptable drug-likeness and ADME-Tox (absorption, distribution, metabolism, excretion, and toxicity) profiles. Overall, the present findings can be translated into preclinical and clinical investigations to inspect A. paniculata phytochemicals as mainstream drugs for NiV disease.

Insights from in silico exploration of major curcumin analogs targeting human dipeptidyl peptidase IV

The goal of this work is to use a variety of in-silico techniques to identify anti-diabetic agents against DPP-IV enzyme from five main curcumin analogues. To produce the successful molecules, five main curcumin analogues were docked into the active site of DPP-IV enzyme. In comparison to the control molecule (Saxagliptin, −6.9 kcal/mol), all the compounds have the highest binding affinity (-7.6 to −7.7 kcal/mol) for the DPP-IV enzyme. These compounds underwent further testing for studies on drug-likeness, pharmacokinetics, and acute toxicity to see the efficacy and safety of compounds. To assess the stability of the docking complex and the binding posture identified during the docking experiment, our study got THC as the lead compound, which was then exposed to 200 ns of molecular dynamic simulation and PCA analysis. Additionally, DFT calculations were conducted to determine the thermodynamic, molecular orbital, and electrostatic potential characteristics of lead compound. Overall, the lead chemical has shown strong drug-like properties, is non-toxic, and has a sizable affinity for the DPP-IV enzyme. Communicated by Ramaswamy H. Sarma

Rational design for novel heterocyclic based Donepezil analogs for Alzheimer’s disease: an in silico approach

Alzheimer’s disease (AD) is a progressive neurodegenerative disease and has devastating impacts on the elderly population. During the last two decades, there has been a significant focus on developing effective and safe treatments for AD. Acetylcholinesterase (AChE) has been identified as one of the primary therapeutic targets for developing drug candidates for AD. However, there is still a need for more efficient therapies. In this study, our aim is to design a new series of heterocyclic-based AChE inhibitors inspired by a standard drug. Here, we carried out molecular docking, drug-likeliness characteristics, and molecular dynamics (MD) to predict important pharmacophore features and understand the inhibitory mechanism of the designed inhibitors towards the AChE. We have designed 112 new derivatives by replacing the piperidine moiety of Donepezil with the different five and six-membered heterocyclic rings and selected 15 compounds that show higher or comparable docking scores as compared to standard Donepezil and pose no risk for carcinogenicity. Furthermore, MD results imply the structural stability of the selected docked complexes and seven exhibit a stronger binding affinity towards the AChE than Donepezil. Thus, heterocyclic-based derivatives based on oxazole, pyrazole, and tetrahydropyran may be potential therapeutic candidates for AD. Our structure-based drug design approach allows us to identify and gain insight into the structural stability of the inhibitor-protein complex and the inhibition mechanism of the newly designed inhibitors. The present finding might be an initial selection for developing a new inhibitor for AD and provide a direction for further experiments on its biological activities. Communicated by Ramaswamy H. Sarma

Integrating molecular docking and molecular dynamics simulation approaches for investigation of the affinity and interactions of Berberine with Class C β-Lactamase

Background: Antibiotic resistance is a significant health concern, as bacteria produce enzymes that inhibit antimicrobial drug activity, increasing disease generation. This study investigates the inhibitory effect of berberine on β-lactamase enzyme activity and antibiotic effectiveness. Methods: Molecular docking was utilized to find the binding pose and binding affinity of a new inhibitory ligand with the AmpC enzyme using Autodock software version 4.2.2. MD simulations were performed in free form and complicated to understand the stability of the protein-ligand docked complex. Results: The molecular docking result indicated the proper interaction between berberine and the AmpC β-lactamase enzyme with a suitable binding pose and binding energy of -6.55 kcal/mol. The MD simulation of systems verifies the docking result, which shows stable hydrogen bonds of berberine with AmpC and good equivalence between RMSD, RMSF, SASA, etc. Conclusion: This paper reveals that berberine, which is a natural ingredient with multiple medicinal characteristics, can be applied as a potential inhibitor of class C β-lactamase AmpC. Hence, the outcome of the calculations performed provides valuable data to design new inhibitors with therapeutic potential to control the β-lactamase activity.

CarsiDock: a deep learning paradigm for accurate protein-ligand docking and screening based on large-scale pre-training.

The expertise accumulated in deep neural network-based structure prediction has been widely transferred to the field of protein-ligand binding pose prediction, thus leading to the emergence of a variety of deep learning-guided docking models for predicting protein-ligand binding poses without relying on heavy sampling. However, their prediction accuracy and applicability are still far from satisfactory, partially due to the lack of protein-ligand binding complex data. To this end, we create a large-scale complex dataset containing ∼9 M protein-ligand docking complexes for pre-training, and propose CarsiDock, the first deep learning-guided docking approach that leverages pre-training of millions of predicted protein-ligand complexes. CarsiDock contains two main stages, i.e., a deep learning model for the prediction of protein-ligand atomic distance matrices, and a translation, rotation and torsion-guided geometry optimization procedure to reconstruct the matrices into a credible binding pose. The pre-training and multiple innovative architectural designs facilitate the dramatically improved docking accuracy of our approach over the baselines in terms of multiple docking scenarios, thereby contributing to its outstanding early recognition performance in several retrospective virtual screening campaigns. Further explorations demonstrate that CarsiDock can not only guarantee the topological reliability of the binding poses but also successfully reproduce the crucial interactions in crystalized structures, highlighting its superior applicability.

Exploring the effectiveness of flavone derivatives for treating liver diseases: Utilizing DFT, molecular docking, and molecular dynamics techniques

In exploring nature's potential in addressing liver-related conditions, this study investigates the therapeutic capabilities of flavonoids. Utilizing in silico methodologies, we focus on flavone and its analogs (1–14) to assess their therapeutic potential in treating liver diseases. Molecular change calculations using density functional theory (DFT) were conducted on these compounds, accompanied by an evaluation of each analog's physiochemical and biochemical properties. The study further assesses these flavonoids' binding effectiveness and locations through molecular docking studies against six target proteins associated with human cancer. Tropoflavin and taxifolin served as reference drugs. The structurally modified flavone analogs (1–14) displayed a broad range of binding affinities, ranging from -7.0 to -9.4 kcal mol⁻¹, surpassing the reference drugs. Notably, flavonoid (7) exhibited significantly higher binding affinities with proteins Nrf2 (PDB:1 × 2 J) and DCK (PDB:1 × 2 J) (-9.4 and -8.1 kcal mol⁻¹) compared to tropoflavin (-9.3 and -8.0 kcal mol⁻¹) and taxifolin (-9.4 and -7.1 kcal mol⁻¹), respectively. Molecular dynamics (MD) simulations revealed that the docked complexes had a root mean square deviation (RMSD) value ranging from 0.05 to 0.2 nm and a root mean square fluctuation (RMSF) value between 0.35 and 1.3 nm during perturbation. The study concludes that 5,7-dihydroxyflavone (7) shows substantial promise as a potential therapeutic agent for liver-related conditions. However, further validation through in vitro and in vivo studies is necessary.Key insights from this study include:•Screening of flavanols and their derivatives to determine pharmacological and bioactive properties using ADMET, molinspiration, and pass prediction analysis.•Docking of shortlisted flavone derivatives with proteins having essential functions.•Analysis of the best protein-flavonoid docked complexes using molecular dynamics simulation to determine the flavonoid's efficiency and stability within a system.

Genetic Alterations of NF-κB and Its Regulators: A Rich Platform to Advance Colorectal Cancer Diagnosis and Treatment.

Colorectal cancer (CRC) is the third leading cause of cancer mortality in the United States, with an estimated 52,000 deaths in 2023. Though significant progress has been made in both diagnosis and treatment of CRC in recent years, genetic heterogeneity of CRC-the culprit for possible CRC relapse and drug resistance, is still an insurmountable challenge. Thus, developing more effective therapeutics to overcome this challenge in new CRC treatment strategies is imperative. Genetic and epigenetic changes are well recognized to be responsible for the stepwise development of CRC malignancy. In this review, we focus on detailed genetic alteration information about the nuclear factor (NF)-κB signaling, including both NF-κB family members, and their regulators, such as protein arginine methyltransferase 5 (PRMT5), and outer dynein arm docking complex subunit 2 (ODAD2, also named armadillo repeat-containing 4, ARMC4), etc., in CRC patients. Moreover, we provide deep insight into different CRC research models, with a particular focus on patient-derived xenografts (PDX) and organoid models, and their potential applications in CRC research. Genetic alterations on NF-κB signaling components are estimated to be more than 50% of the overall genetic changes identified in CRC patients collected by cBioportal for Cancer Genomics; thus, emphasizing its paramount importance in CRC progression. Consequently, various genetic alterations on NF-κB signaling may hold great promise for novel therapeutic development in CRC. Future endeavors may focus on utilizing CRC models (e.g., PDX or organoids, or isogenic human embryonic stem cell (hESC)-derived colonic cells, or human pluripotent stem cells (hPSC)-derived colonic organoids, etc.) to further uncover the underpinning mechanism of these genetic alterations in NF-κB signaling in CRC progression. Moreover, establishing platforms for drug discovery in dishes, and developing Biobanks, etc., may further pave the way for the development of innovative personalized medicine to treat CRC in the future.

Assessment of Melia azedarach Plant Extracts Activity Against Hypothetical Protein of Mycobacterium tuberculosis via GC-MS Analysis and In Silico Approaches

Medicinal plants have played an important role in treating different diseases. Melia azedarach is a plant with significant medical and biological applications. This research aimed to explore the possible bioactivity of various biological compounds. The gas chromatography-mass spectrometry (GC-MS) analysis of Melia azedarach identified 25 compounds, among which 1-ethyl-3-methyl-2-nitrosobenzene and 2-ethyl-1,3-dimethyl-5-(nitromethyl)benzene were the main phytochemicals present in the crude extract of Melia azedarach. Mycobacterium tuberculosis is a zoonotic pathogen that causes tuberculosis (TB). The hypothetical protein OHO21363.1 of Mycobacterium tuberculosis is characterized using an in silico approach for exploring immunogenicity and virulence. After the homology prediction and characterization, this protein was predicted to be a PEE family protein with virulence and immune response functions. This virulent protein lies in the extracellular region of the cell according to subcellular localization and gene ontology. Due to its virulence factor and disease privilege against the host immune response, it can be used as a potential receptor for drug designing. After the GC-MS analysis, the 28 phytochemicals were retrieved and analyzed. Pharmacophore characterization of 1-ethyl-3-methyl-2-nitrosobenzene and 2-ethyl-1,3-dimethyl-5-(nitromethyl)benzene was performed to get the initial information on phytochemical bonding properties. Chemical absorption, distribution, metabolism, excretion, and toxicity (ADMET) predicted that out of 28 drugs, only 2 could cross the PGP+ through the blood–brain barrier and gastrointestinal tract without violating Lipinski’s rule of 5. Both 1-ethyl-3-methyl-2-nitrosobenzene and 2-ethyl-1,3-dimethyl-5-(nitromethyl) benzene were predicted to have the best docking score against the protein, with –4.9 KJ/Mol and –5.0 KJ/Mol, respectively. Molecular dynamics simulation showed favorable results and provided useful information about the behavior and interactions of the molecules in the dock complex. Immune simulation confirms no immune response on the protein, proving it to be a virulent protein. The phytoconstituents present in Melia azedarach have the potential for multiple pharmacological applications. These findings can be used to design the potential drug candidates against TB. These ligands may be good candidates to fight against the resistant strain of TB compared to the drugs available in the market in the future. More research must be conducted to identify the bioactive compounds that may be used to treat different ailments.

Integrated computational approaches for designing potent pyrimidine-based CDK9 inhibitors: 3D-QSAR, docking, and molecular dynamics simulations

CDK9 is an emerging target for the development of anticancer drugs. The development of CDK9 inhibitors with significant potency had consistently posed a formidable challenge. In the current research, a number of computational methodologies, such as, 3D-QSAR, molecular docking, fingerprint analysis, molecular dynamic (MD) simulations followed by MMGB/PBSA and ADMET studies were used systemically to uncover the binding mechanism of pyrimidine derivatives against CDK9. The CoMFA and CoMSIA models having high q2 (0.53, 0.54) and r2 values (0.96, 0.93) respectively indicating that model could accurately predict the bioactivities of CDK9 inhibitors. Using the R-group exploration technique implemented by the Spark™ by Cresset group, the structural requirements revealed by the contour maps of model were utilized strategically to create an in-house library of 100 new CDK9 inhibitors. Additionally, the compounds from the in-house library were mapped into 3D-QSAR model which predicted pIC50 values comparable to the experimental values. A comparison between 3D-QSAR generated contours and molecular docking conformation of ligands was performed to elucidate the essentials of CDK9 inhibitor design. MD simulations (100 ns) were performed on the selected docked complexes A21, A14 and D98 which contributed in validating the binding interactions. According to the findings of binding free energy analysis (MMGB/PBSA), It was observed that residues CYS106 and GLU107 had a considerable tendency to facilitate ligand-protein interactions via H-bond interactions. The aforementioned findings have the potential to enhance researchers comprehension of the mechanism underlying CDK9 inhibition and may be utilized in the development of innovative and efficacious CDK9 inhibitors.

Nematicidal action of Clonostachys rosea against Meloidogyne incognita: in-vitro and in-silico analyses

ABSTRACTClonostachys rosea is a biocontrol agent against a wide range of pests and diseases. In the present study, an in-vitro nematicidal activity of C. rosea has been documented by observing the behavioural response of Meloidogyne incognita (Mi) towards the culture filtrate of C. rosea. Eleven different biomolecules observed in GC-MS analysis were tested against seven potential target proteins of Mi through molecular modelling using PyRx 0.8 software. Among the biomolecules tested, Dihydro-4-hydroxy-2(3H)-furanone had the highest binding affinity for Acetylcholine esterase (AchE) (−7.5 kcal/mol), Cytochrome c oxidase subunit 1 (COX) (−7.8 kcal/mol), Heat shock protein (Hsp90) (−8.4 kcal/mol), Odorant response gene 1 (ODR 3) (−6.5 kcal/mol), Neuropeptide G-protein coupled receptor (nGPCR) (−7.6 kcal/mol) and Cathepsin L-protease (cpl-1) (−6.8 kcal/mol) protein targets compared to synthetic pesticide, carbofuran. The biomolecule 2,3-dihydroxypropanal has shown the highest binding affinity for Odorant response gene 1 (ODR 1) (−6.6 kcal/mol). Understanding the interactions between the target protein-ligands docked complexes displayed additional contacts such as hydrophobic interactions, van der Waals, pi-pi stacking, alkyl and pi-alkyl. The present investigation demonstrated that C. rosea is a hub of potential biomolecules that could be explored for nematicidal activities.

Unraveling the Structure of Meclizine Dihydrochloride with MicroED.

Meclizine (Antivert, Bonine) is a first-generation H1 antihistamine used in the treatment of motion sickness and vertigo. Despite its wide medical use for over 70 years, its crystal structure and the details of protein-drug interactions remained unknown. Single-crystal X-ray diffraction (SC-XRD) is previously unsuccessful for meclizine. Today, microcrystal electron diffraction (MicroED) enables the analysis of nano- or micro-sized crystals that are merely a billionth the size needed for SC-XRD directly from seemingly amorphous powder. In this study, MicroED to determine the 3D crystal structure of meclizine dihydrochloride is used. Two racemic enantiomers (R/S) are found in the unit cell, which is packed as repetitive double layers in the crystal lattice. The packing is made of multiple strong N-H-Cl- hydrogen bonding interactions and weak interactions like C-H-Cl- and pi-stacking. Molecular docking reveals the binding mechanism of meclizine to the histamine H1 receptor. A comparison of the docking complexes between histamine H1 receptor and meclizine or levocetirizine (a second-generation antihistamine) shows the conserved binding sites. This research illustrates the combined use of MicroED and molecular docking in unraveling elusive drug structures and protein-drug interactions for precision drug design and optimization.