Molecular docking and molecular dynamics simulation

Morin attenuates arsenic-induced toxicity in 3T3 embryonic fibroblast cells by suppressing oxidative stress, inflammation, and apoptosis: In vitro and silico evaluations

This study aims to investigate the curative effects of Morin, a flavonoid, against arsenic toxicity in 3T3 embryonic fibroblast cells and its effect on the molecular mechanisms of cells. The cytotoxicity and viability of the cells were measured by MTT and LDH tests. Arsenic (0.74 μM) was used to trigger toxicity and Morin (50 μM) was used for treatment. The levels of oxidative stress biomarkers and the activities of antioxidant enzymes were measured by spectrophotometric method, and inflammatory markers were measured by ELISA method. While mRNA expression levels of Bax, Bcl-2 levels, and Caspase-3 activity were measured by qRT-PCR technique, TUNEL staining was performed to detect DNA breaks and DAPI staining to visualize nuclear changes. Protein structures were retrieved from the protein data bank. OpenBabel and Autodock programs were used for the molecular docking study. Morin rescued the 3T3 embryonic fibroblast cells exposed to arsenic. However, Arsenic decreased the activities of antioxidant enzymes in cells and significantly increased oxidative stress, inflammation, and apoptosis. Morin treatment reduced oxidative damage and TNF-α and IL-1β levels. Arsenic-induced Caspase-3 mRNA expression level and Bax protein mRNA expression level were significantly increased, while Bcl-2 mRNA expression level was significantly decreased. While Caspase-3 mRNA expression level and Bax protein mRNA expression level decreased with morin treatment, Bcl-2 mRNA expression level increased significantly. Molecular docking study results showed good binding affinity of morin in SOD, GSH-Px, Bax, Bcl-2, Caspase-3, TNF-α, and IL-1β structures. Morin showed antioxidant, anti-inflammatory, and anti-apoptotic effects against Arsenic-induced cellular toxicity.

Lubricin-Inspired Nanozymes Reconstruct Cartilage Lubrication System with an "In-Out" Strategy

Lubricin, secreted primarily by chondrocytes, plays a critical role in maintaining the function of the cartilage lubrication system. However, both external factors such as friction and internal factors like oxidative stress can disrupt this system, leading to osteoarthritis. Inspired by lubricin, a lubricating nanozyme, that is, Poly-2-acrylamide-2-methylpropanesulfonic acid sodium salt-grafted aminofullerene, is developed to restore the cartilage lubrication system using an "In-Out" strategy. The "Out" aspect involves reducing friction through a combination of hydration lubrication and ball-bearing lubrication. Simultaneously, the "In" aspect aims to mitigate oxidative stress by reducing free radical, increasing autophagy, and improving the mitochondrial respiratory chain. This results in reduced chondrocyte senescence and increased lubricin production, enhancing the natural lubrication ability of cartilage. Transcriptome sequencing and Western blot results demonstrate that it enhances the functionality of mitochondrial respiratory chain complexes I, III, and V, thereby improving mitochondrial function in chondrocytes. In vitro and in vivo experiments show that the lubricating nanozymes reduce cartilage wear, improve chondrocyte senescence, and mitigate oxidative stress damage, thereby mitigating the progression of osteoarthritis. These findings provide novel insights into treating diseases associated with oxidative stress and frictional damage, such as osteoarthritis, and set the stage for future research and development of therapeutic interventions.

Structure-based screening of FDA-approved drugs identifies potential histone deacetylase 3 repurposed inhibitor: molecular docking and molecular dynamic simulation approaches

Histone deacetylase 3 (HDAC3) is a member of the histone deacetylase family that has emerged as a crucial target in the quest for novel therapeutic interventions against various complex diseases, including cancer. The repositioning of FDA-approved drugs presents a promising avenue for the rapid discovery of potential HDAC3 inhibitors. In this study, we performed a structure-based virtual screening of FDA-approved drugs obtained from DrugBank. Candidate hits were selected based on their binding affinities and interactions with HDAC3. These promising hits were then subjected to a comprehensive assessment of their biological properties and drug profiles. Our investigation identified two FDA-approved drugs, Imatinib and Carpipramine, characterized by their exceptional affinity and specificity for the binding pocket of HDAC3. These molecules demonstrated a strong preference for HDAC3 binding site and formed interactions with functionally significant residues within the active site pocket. To gain deeper insights into the binding dynamics, structural stability, and interaction mechanisms, we performed molecular dynamics (MD) simulations spanning 300 nanoseconds (ns). The results of MD simulations indicated that Imatinib and Carpipramine stabilized the structure of HDAC3 and induced fewer conformational changes. Taken together, the findings from this study suggest that Imatinib and Carpipramine may offer significant therapeutic potential for treating complex diseases, especially cancer.

Chemoinformatics Study of Benzodiazepine-1, 2, 3-triazole Derivatives Targeting Butyrylcholinesterase

This study aims to assess the potential bioactivity of newly designed benzodiazepine-1,2,3-triazole derivatives using in-silico methodologies, with a primary focus on elucidating their inhibitory interactions with the butyrylcholinesterase (BuChE) enzyme, which is implicated in Alzheimer's disease. We employed multiple linear regression (MLR) methods to conduct a quantitative structure-activity relationship (QSAR) analysis on a collection of 31 benzodiazepine-1,2,3-triazole derivatives, with the goal of investigating, assessing, and predicting their activities, as well as designing novel compounds. This approach yielded highly accurate results, with coefficients of determination (R²) of 0.77 and 0.81 for the training and test datasets, respectively. Additionally, the optimized compounds were subjected to an Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) analysis, demonstrating their potential as non-hepatotoxic agents with enhanced absorption and blood-brain barrier permeability. To further validate these findings, the most favorable docking conformations were analyzed using molecular dynamics (MD) simulations with GROMACS software, predicting the stability of the formed complexes. These simulations underscored the critical role of hydrogen bonds in stabilizing the compounds at the BuChE receptor binding site. The results hold great promise for the development of innovative benzodiazepine-1,2,3-triazole derivatives as effective BuChE inhibitors, potentially leading to therapeutic interventions for Alzheimer's disease.

Comparative analysis, diversification, and functional validation of plant nucleotide-binding site domain genes

Nucleotide-binding site (NBS) domain genes are one of the superfamily of resistance genes involved in plant responses to pathogens. The current study identified 12,820 NBS-domain-containing genes across 34 species covering from mosses to monocots and dicots. These identified genes are classified into 168 classes with several novel domain architecture patterns encompassing significant diversity among plant species. Several classical (NBS, NBS-LRR, TIR-NBS, TIR-NBS-LRR, etc.) and species-specific structural patterns (TIR-NBS-TIR-Cupin_1-Cupin_1, TIR-NBS-Prenyltransf, Sugar_tr-NBS etc.) were discovered. We observed 603 orthogroups (OGs) with some core (most common orthogroups; OG0, OG1, OG2, etc.) and unique (highly specific to species; OG80, OG82, etc.) OGs with tandem duplications. The expression profiling presented the putative upregulation of OG2, OG6, and OG15 in different tissues under various biotic and abiotic stresses in susceptible and tolerant plants to cotton leaf curl disease (CLCuD). The genetic variation between susceptible (Coker 312) and tolerant (Mac7) Gossypium hirsutum accessions identified several unique variants in NBS genes of Mac7 (6583 variants) and Coker312 (5173 variants). The protein-ligand and proteins-protein interaction showed a strong interaction of some putative NBS proteins with ADP/ATP and different core proteins of the cotton leaf curl disease virus. The silencing of GaNBS (OG2) in resistant cotton through virus-induced gene silencing (VIGS) demonstrated its putative role in virus tittering. The presented study will be further helpful in understanding the plant adaptation mechanism.

Systems biology approach: identification of hub genes, signaling pathways, and molecular docking of COL1A1 gene in cervical insufficiency

The collagen type I alpha 1 (COL1A1, OMIM #120,150) gene, encoding the alpha-1 chain of type I collagen (UniProt #P02452), plays a key role in life-homeostasis due to its remarkable involvement in collagen synthesis. It is a promising candidate gene implicated in the pathogenesis of cervical insufficiency (CI). This study aimed to identify genetic variations within the COL1A1 gene that contribute to the development of CI. Polymerase chain reaction (PCR) and amplicon sequencing were implemented for single nucleotide polymorphisms (SNPs) detection (+ 1245G/T, SP1 rs1800012), which revealed wild-type sequence for targeted SNPs in enrolled proband indicated negative results regarding COL1A1 gene involvement for current form of CI. It allows further investigation of other closely connected genes probed in this study. Computational approaches viz. Protein-protein interaction (PPI), gene ontology (GO), and pathway participation were used to identify the crucial hub genes and signaling pathways for COL1A1 and CI. Using the Yet Another Scientific Artificial Reality Application (YASARA) software, molecular docking, and molecular dynamic (MD) simulation with the oxytocin (CID 439,302), estradiol (CID 129,728,744), progesterone (CID 5994) and hydroxyprogesterone (CID 150,788) were done. Interactive bioinformatics analysis demonstrated that the COL1A1 and more than 10 collagen sister genes had a strong connection with CI. In sum, the findings of this study provide insights into a modus operandi that can be utilized to illuminate the path toward studying sister genes and smooth diagnosis of CI. These findings have implications for understanding the foundational process of the condition and potentially developing screening, diagnostic, and therapeutic interventions.

Graphical Abstract

Identifying Phosphodiesterase-5 Inhibitors with Drug Repurposing Approach: Implications in Vasodysfunctional Disorders

Phosphodiesterase type 5 (PDE5) is a multidomain protein that plays a crucial role in regulating cellular cyclic guanosine monophosphate (cGMP), a key signaling molecule involved in various physiological processes. Dysregulation of PDE5 and cGMP signaling is associated with a range of vasodysfunctional disorders, necessitating the development of effective therapeutic interventions. This study adopts comprehensive approach, combining virtual screening and molecular dynamics (MD) simulations, to repurpose FDA-approved drugs as potential PDE5 inhibitors. The initial focus involves selecting compounds based on their binding affinity. Shortlisted compounds undergo a meticulous analysis for their drug profiling and biological significance, followed by the activity evaluation and interaction analysis. Notably, based on binding potential and drug profiling, two molecules, Dutasteride and Spironolactone, demonstrate strong potential as PDE5 inhibitors. Furthermore, all atom MD simulations were employed (500 ns) to explore dynamic behavior of Dutasteride and Spironolactone in complexes with PDE5. Principal components analysis (PCA) and free energy landscape (FEL) analyses are further leveraged to decipher that the binding of Dutasteride and Spironolactone stabilizes the structure of PDE5 with minimal conformational changes. In summary, Dutasteride and Spironolactone exhibit remarkable affinity for PDE5 and possess characteristics that suggest their potential as therapeutic agents for conditions associated with PDE5 dysfunction.

Identification of new potent NLRP3 inhibitors by multi-level in-silico approaches

Nod-like receptor protein 3 (NLRP-3), is an intracellular sensor that is involved in inflammasome activation, and the aberrant expression of NLRP3 is responsible for diabetes mellitus, its complications, and many other inflammatory diseases. NLRP3 is considered a promising drug target for novel drug design. Here, a pharmacophore model was generated from the most potent inhibitor, and its validation was performed by the Gunner-Henry scoring method. The validated pharmacophore was used to screen selected compounds databases. As a result, 646 compounds were mapped on the pharmacophore model. After applying Lipinski's rule of five, 391 hits were obtained. All the hits were docked into the binding pocket of target protein. Based on docking scores and interactions with binding site residues, six compounds were selected potential hits. To check the stability of these compounds, 100 ns molecular dynamic (MD) simulations were performed. The RMSD, RMSF, DCCM and hydrogen bond analysis showed that all the six compounds formed stable complex with NLRP3. The binding free energy with the MM-PBSA approach suggested that electrostatic force, and van der Waals interactions, played a significant role in the binding pattern of these compounds. Thus, the outcomes of the current study could provide insights into the identification of new potential NLRP3 inflammasome inhibitors against diabetes and its related disorders.

Redirecting pantoprazole as a metallo-beta-lactamase inhibitor in carbapenem-resistant Klebsiella pneumoniae

The development of resistance to carbapenems in Klebsiella pneumoniae due to the production of metallo-β-lactamases (MBLs) is a critical public health problem because carbapenems are the last-resort drugs used for treating severe infections of extended-spectrum β-lactamases (ESBLs) producing K. pneumoniae. Restoring the activity of carbapenems by the inhibition of metallo-β-lactamases is a valuable approach to combat carbapenem resistance. In this study, two well-characterized clinical multidrug and carbapenem-resistant K. pneumoniae isolates were used. The sub-inhibitory concentrations of pantoprazole and the well-reported metallo-β-lactamase inhibitor captopril inhibited the hydrolytic activities of metallo-β-lactamases, with pantoprazole having more inhibiting activities. Both drugs, when used in combination with meropenem, exhibited synergistic activities. Pantoprazole could also downregulate the expression of the metallo-β-lactamase genes bla NDM and bla VIM. A docking study revealed that pantoprazole could bind to and chelate zinc ions of New Delhi and Verona integron-encoded MBL (VIM) enzymes with higher affinity than the control drug captopril and with comparable affinity to the natural ligand meropenem, indicating the significant inhibitory activity of pantoprazole against metallo-β-lactamases. In conclusion, pantoprazole can be used in combination with meropenem as a new strategy for treating serious infections caused by metallo-β-lactamases producing K. pneumoniae.

Molecular structure, vibrational spectral, electron density analysis on linaloe oil and molecular docking efficacy against the therapeutic target on human immunodeficiency virus-1 organism (VIRAL protein)

Natural traditional medicine extensively uses certain terpenes and gives plants their flavor, aroma, and color. Treatments for bacterial infections, malaria, and cardiovascular disorders, anti-inflammatory, promote circulation, and heal wounds. 3,7-Dimethyl-1,6-octadien-3-ol (Linalool) is a naturally occurring monoterpene alcohol with no cycle and is a colorless liquid. Spectral analysis such as UV absorption spectra, NMR for structure determination, and IR and Raman for vibrational analysis. The Quantum mechanical approach uses DFT, ELF, and LOL-promolecular electron density, non-relaxed, and atomic density analysis. The biomolecular studies such as molecular dynamics using protein-ligand complex with HIV-1 organism (energy minimization). ADMET for the usage of linalool in different metabolism studies and Molecular docking for binding affinity, its reactive site estimation, and macromolecules that come into contact with protein receptors and conclude ligand binding affinity with protein.

Unlocking therapeutic potential: computational insights into TREM2 protein targeting with FDA-approved drugs for neurodegeneration

Neurodegenerative diseases such as Alzheimer's disease (AD) pose a significant global health challenge that requires the exploration of innovative therapeutic strategies. Triggering receptor expressed on myeloid cells-2 (TREM2) is one of the critical proteins involved in immune regulation and neuroinflammation. It has emerged as a promising therapeutic target to develop treatments for neurodegenerative disorders like AD. Here, we employed a comprehensive virtual screening approach to identify potential small molecule inhibitors among FDA-approved drugs for TREM2. The docking study reveals significant binding affinity, ranging from -7.8 kcal/mol to -8.5 kcal/mol, for the elucidated hits against TREM2, accompanied by several crucial interactions. Among the repurposed drugs identified in the initial screening, Carpipramine, Clocapramine, and Pimozide stood out due to their notable binding potential and favorable drug profiling. Further, we conducted molecular dynamics (MD) simulations on the selected molecules that probed their structural dynamics and stability within the TREM2 binding pocket. The structural parameters and hydrogen bond dynamics remained remarkably stable throughout the simulated trajectories. Furthermore, we performed principal component analysis (PCA) and constructed free energy landscapes (FELs) to gain deeper insights into ligand binding and conformational flexibility of TREM2. The findings revealed that the elucidated molecules, Carpipramine, Clocapramine, and Pimozide, exhibited an exceptional fit within the binding pocket of TREM2 with remarkable stability and interaction patterns throughout the 500 ns simulation window. Interestingly, these molecules possessed a spectrum of anti-neurodegenerative properties and favorable drug profiles, which suggest their potential as promising drug candidates for repurposing in the treatment of AD.Communicated by Ramaswamy H. Sarma.

Exploring promising natural compounds for breast cancer treatment: in silico molecular docking targeting WDR5-MYC protein interaction

Cancer is an aberrant differentiation of normal cells, characterized by uncontrolled growth and the potential to acquire invasive and aggressive properties that ultimately lead to metastasis. In the realm of scientific exploration, a multitude of pathways has been investigated and targeted by researchers, among which one specific pathway is recognized as WDR5-MYC. Continuous investigations and research show that WDR5-MYC is a therapeutic target protein. Hence, the discovery of naturally occurring compounds with anticancer properties has been suggested as a rapid and efficient alternative for the development of anticancerous therapeutics. A virtual screening approach was used to identify the most potent compounds from the NP-lib database at the MTiOpenScreen webserver against WDR5-MYC. This process yielded a total of 304 identified compounds. Subsequently, after screening, four potent compounds, namely Estrone (ZINC000003869899), Ethyl-1,2-benzanthracene (ZINC000003157052), Strychnine (ZINC000000119434) and 7H-DIBENZO [C, G] CARBAZOLE (ZINC000001562130), along with a cocrystallized 5-[4-(trifluoromethyl) phenyl]-1H-tetrazole inhibitor (QBP) as a reference ligand, were considered for stringent molecular docking. Thus, each compound exhibited significant docking energy between -8.2 and -7.7 kcal/mol and molecular contacts with essential residue Asn225, Lys250, Ser267 and Lys272 in the active pocket of WDR5-MYC against the QBP inhibitor (the native ligand QBP serves as a reference in the comparative analysis of docked complexes). The results support the potent compounds for drug-likeness and strong binding affinity with WDR5-MYC protein. Further, the stability of the selected compounds was predicted by molecular dynamics simulation (100 ns) contributed by intermolecular hydrogen bonds and hydrophobic interactions. This demonstrates the potential of the selected compounds to be used against breast cancer treatment.Communicated by Ramaswamy H. Sarma.

Structure Identification and Risk Assurance of Unknown Impurities in Pramipexole Oral Drug Formulation

Impurities compounds in any pharmaceutical product or drug substance are inevitable from a chemistry point of view. The quality and safety of a pharmaceutical product are also significantly affected by these impurities content; therefore, impurities need to be identified and characterized through the use of appropriate analytical methods. Pramipexole is a nonergot dopamine agonist used to treat various Parkinson's disease symptoms. Two unknown impurities were detected from a pramipexole dihydrochloride solid dosage form. These impurities were identified and characterized using ultra-performance liquid chromatography coupled with high-resolution mass spectroscopy (UPLC-HRMS). These impurities were found to be enriched when mannitol existed in the formulation. The structure and mechanism involved in the existence of the impurities were proposed. Furthermore, observation of the binding affinity potential risk of these impurities to the pramipexole receptor has also been demonstrated through molecular docking and molecular dynamics simulation study. The binding energy result showed that pramipexole interaction with dopamine receptors D2 and D3 was higher than pramipexole mannose adduct and pramipexole ribose adduct.

Potential molecular mechanism of reuterin on the inhibition of Aspergillus flavus conidial germination: An in silico study

Reuterin is a natural antifungal agent derived from certain strains of Limosilactobacillus reuteri. Our previous study revealed that 6 mM reuterin inhibited completely the conidial germination of aflatoxigenic Aspergillus flavus. This study investigated the potential molecular mechanism of reuterin in inhibiting A. flavus conidial germination, which was pre-assumed that it correlated to the inhibition of some essential enzyme activity involved in conidial germination, specifically 1,3-β-glucan synthase, chitin synthase, and catalases (catalase, bifunctional catalase-peroxidase, and spore-specific catalase). The complex of 1,3-β-glucan synthase and chitin synthase with reuterin had a lower binding affinity than that with the substrate. Conversely, the complex of catalases with reuterin had a higher binding affinity than that with the substrate. It was suggested that 1,3-β-glucan synthase and chitin synthase tended to bind the substrate rather than bind reuterin. In contrast, catalases tended to bind reuterin rather than bind the substrate. Therefore, reuterin could be a potential inhibitor of catalases but may not be an inhibitor of 1,3-β-glucan synthase and chitin synthase. In this in silico study, we predicted that the potential molecular mechanism of reuterin in inhibiting A. flavus conidial germination was due to the inhibition of catalases activities by competitively binding to the enzymes active sites, thus resulting in the accumulation of reactive oxygen species in cells, leading to cells damage. PRACTICAL APPLICATION: This in silico study revealed that reuterin is a potential inhibitor of catalases in A. flavus, thereby interfering with the antioxidant system during conidial germination. This finding shows that reuterin can be used as an antifungal agent in food or agricultural products, inhibiting conidial germination completely.

Targeting PDE4A for therapeutic potential: exploiting drug repurposing approach through virtual screening and molecular dynamics

cAMP-specific 3',5'-cyclic phosphodiesterase 4 A (PDE4A) holds a pivotal role in modulating intracellular levels of cyclic adenosine monophosphate (cAMP). Targeting PDE4A with novel therapeutic agents shows promise in addressing neurological disorders (e.g. Alzheimer's and Parkinson's diseases), mood disorders (depression, anxiety), inflammatory conditions (asthma, chronic obstructive pulmonary disease), and even cancer. In this study, we present a comprehensive approach that integrates virtual screening and molecular dynamics (MD) simulations to identify potential inhibitors of PDE4A from the existing pool of FDA-approved drugs. The initial compound selection was conducted focusing on binding affinity scores, which led to the identification of several high-affinity compounds with potential PDE4A binding properties. From the refined selection process, two promising compounds, Fluspirilene and Dihydroergocristine, emerged as strong candidates, displaying substantial affinity and specificity for the PDE4A binding site. Interaction analysis provided robust evidence of their binding capabilities. To gain deeper insights into the dynamic behavior of Fluspirilene and Dihydroergocristine in complex with PDE4A, we conducted 300 ns MD simulations, principal components analysis (PCA), and free energy landscape (FEL) analysis. These analyses revealed that Fluspirilene and Dihydroergocristine binding stabilized the PDE4A structure and induced minimal conformational changes, highlighting their potential as potent binders. In conclusion, our study systematically explores repurposing existing FDA-approved drugs as PDE4A inhibitors through a comprehensive virtual screening pipeline. The identified compounds, Fluspirilene and Dihydroergocristine, exhibit a strong affinity for PDE4A, displaying characteristics that support their suitability for further development as potential therapeutic agents for conditions associated with PDE4A dysfunction.Communicated by Ramaswamy H. Sarma.

Molecular Docking of Intrinsically Disordered Proteins: Challenges and Strategies

Intrinsically disordered proteins (IDPs) are a novel class of proteins that have established a significant importance and attention within a very short period of time. These proteins are essentially characterized by their inherent structural disorder, encoded mainly by their amino acid sequences. The profound abundance of IDPs and intrinsically disordered regions (IDRs) in the biological world delineates their deep-rooted functionality. IDPs and IDRs convey such extensive functionality through their unique dynamic nature, which enables them to carry out huge number of multifaceted biomolecular interactions and make them "interaction hub" of the cellular systems. Additionally, with such widespread functions, their misfunctioning is also intimately associated with multiple diseases. Thus, understanding the dynamic heterogeneity of various IDPs along with their interactions with respective binding partners is an important field with immense potentials in biomolecular research. In this context, molecular docking-based computational approaches have proven to be remarkable in case of ordered proteins. Molecular docking methods essentially model the biomolecular interactions in both structural and energetic terms and use this information to characterize the putative interactions between the two participant molecules. However, direct applications of the conventional docking methods to study IDPs are largely limited by their structural heterogeneity and demands for unique IDP-centric strategies. Thus, in this chapter, we have presented an overview of current methodologies for successful docking operations involving IDPs and IDRs. These specialized methods majorly include the ensemble-based and fragment-based approaches with their own benefits and limitations. More recently, artificial intelligence and machine learning-assisted approaches are also used to significantly reduce the complexity and computational burden associated with various docking applications. Thus, this chapter aims to provide a comprehensive summary of major challenges and recent advancements of molecular docking approaches in the IDP field for their better utilization and greater applicability.Asp (D).

Bioinformatic investigation of Nipah virus surface protein mutations: Molecular docking with Ephrin B2 receptor, molecular dynamics simulation, and structural impact analysis

The SARS-CoV-2 outbreak resulted in significant challenges and loss of life. The Nipah virus, known for its high infectivity and severity, was designated an emergency concern by the World Health Organization. To understand its mutations, the Nipah virus proteins were analyzed extensively, with a focus on the essential G and F proteins responsible for viral entry into host cells. Our bioinformatics analysis unveiled multiple mutations, including simultaneous mutations within a single sequence. Notably, the G273S mutation in the F protein was identified as a potential cause of structural damage, which carries significant implications for vaccine development. Comparing the docking scores of G and F proteins with the Ephrin B2 receptor, it was found that the Y228H mutation in the G protein and the D252G mutation in the F protein likely affect virus entry into host cells. Moreover, our investigation into stability and deformability highlighted the impact of the Y228H mutation in the G protein complex. Molecular dynamics simulations revealed increased flexibility and conformational changes in the G protein complex with the Y228H mutation compared with the known complex. Furthermore, evaluating the root mean square deviation variation demonstrated greater dynamic behavior in the G protein complex and the Ephrin B2 receptor complex. This comprehensive study provides valuable insights into Nipah virus mutations, their significance for vaccine development, and the importance of understanding protein complex behavior in drug discovery. The identified mutations, especially G273S and Y228H, hold crucial implications for future research and potential interventions against the Nipah virus.

Structural and binding studies of 2'- and 3-fucosyllactose and its complexes with norovirus capsid protein by molecular dynamics simulations

Human breast milk contains free oligosaccharides (Human Milk Oligosaccharides-HMOs) that help to protect breastfed infants against a variety of infectious diseases and act as decoy receptors. In breast milk, HMOs are the third most abundant compounds after lactose and lipids. Structural and conformational models of HMOs are quite crucial to studying the interaction with proteins and molecular recognition phenomenon. Molecular dynamics simulations for two trisaccharides HMOs (2'-FL and 3-FL) were carried out for 250 ns and the conformational models were subsequently substantiated by three replicate simulations. The conformer models of HMOs 2'-FL and 3-FL were deposited in the 3-Dimensional Structural Database for Sialic acid-containing CARbohydrates (3DSDSCAR) database website (www.3dsdscar.in). HMOs were then docked into the active site of norovirus capsid protein and are simulated for 100 ns duration. Each complex system was stabilized by direct and water-mediated hydrogen bonding interactions. Binding free energy calculations predict two possible binding modes for each complex system. The conformational flexibility and binding stability of the complex systems were calculated. The protein folding/unfolding and compactness seem to be better for the two HMOs. From a general perspective, we found that both 2'-FL and 3-FL exhibited higher binding efficacy towards norovirus capsid protein and according to the structural stability, 3-FL might be used as a preventive inhibitor for norovirus infection.Communicated by Ramaswamy H. Sarma.

Exploring bixin from Bixa orellana L. seeds: quantification and in silico insights into its anti-cancer potential

Bixin, the key pigment of Bixa orellana L., is an apo-carotenoid found in the seed arils. The present study aimed to quantitatively determine the bixin content of seeds and explore its anti-cancer activity through in silico studies. The bixin content from the seeds of the local genotype, TNMTP8, quantified by RP-HPLC was 4.58 mg per gram. The prediction of pharmacological activity suggested that bixin may serve as a BRAF, MMP9, TNF expression inhibitors, and TP53 expression enhancer. According to molecular docking analysis, bixin interacted with eight different skin cancer targets and had the lowest binding energy compared to the standard drug, 5-fluorouracil. The binding score between bixin and the targets ranged from -4.7 to -8.7 kcal/mol. The targets BRAF and SIRT3 interacted well with bixin, with binding energies as low as -8.3 and -8.7 kcal/mol, respectively. Hence, the dynamic behavior of these two docked complexes throughout a 500 ns trajectory run was investigated further. The Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF) values, and total contacts as a function of time recorded during scrutiny suggest that both complexes were stable. This was validated by post-molecular dynamics analysis using Molecular Mechanics Generalized Born Surface Area (MM-GBSA). Principal component analysis (PCA) was used to analyze the significant differences in motion exhibited by BRAF-Bixin and SIRT3-Bixin. The results showed that bixin is a promising source for potential treatment interventions in skin cancer therapies.Communicated by Ramaswamy H. Sarma.

Novel computational and drug design strategies for inhibition of monkeypox virus and Babesia microti: molecular docking, molecular dynamic simulation and drug design approach by natural compounds

Background

The alarming increase in tick-borne pathogens such as human Babesia microti is an existential threat to global public health. It is a protozoan parasitic infection transmitted by numerous species of the genus Babesia. Second, monkeypox has recently emerged as a public health crisis, and the virus has spread around the world in the post-COVID-19 period with a very rapid transmission rate. These two novel pathogens are a new concern for human health globally and have become a significant obstacle to the development of modern medicine and the economy of the whole world. Currently, there are no approved drugs for the treatment of this disease. So, this research gap encourages us to find a potential inhibitor from a natural source.

Methods and materials

In this study, a series of natural plant-based biomolecules were subjected to in-depth computational investigation to find the most potent inhibitors targeting major pathogenic proteins responsible for the diseases caused by these two pathogens.

Results

Among them, most of the selected natural compounds are predicted to bind tightly to the targeted proteins that are crucial for the replication of these novel pathogens. Moreover, all the molecules have outstanding ADMET properties such as high aqueous solubility, a higher human gastrointestinal absorption rate, and a lack of any carcinogenic or hepatotoxic effects; most of them followed Lipinski's rule. Finally, the stability of the compounds was determined by molecular dynamics simulations (MDs) for 100 ns. During MDs, we observed that the mentioned compounds have exceptional stability against selected pathogens.

Conclusion

These advanced computational strategies reported that 11 lead compounds, including dieckol and amentoflavone, exhibited high potency, excellent drug-like properties, and no toxicity. These compounds demonstrated strong binding affinities to the target enzymes, especially dieckol, which displayed superior stability during molecular dynamics simulations. The MM/PBSA method confirmed the favorable binding energies of amentoflavone and dieckol. However, further in vitro and in vivo studies are necessary to validate their efficacy. Our research highlights the role of Dieckol and Amentoflavone as promising candidates for inhibiting both monkeypox and Babesia microti, demonstrating their multifaceted roles in the control of these pathogens.

Effect of preprocessing and simulation parameters on the performance of molecular docking studies

CONTEXT

Molecular docking is an important and rapid tool that provides a comprehensive view of different molecular mechanisms. It is often used to verify the binding interactions of many pairs of molecules and is much faster than more rigorous approaches. However, its application requires carefully preprocessing each molecule and selecting a series of simulation parameters, which is not always done correctly. We show how preprocessing and simulation parameters can positively or negatively impact molecular docking performance. For example, the inclusion of hydrogen atoms leads to better redocking scores, but molecular dynamics simulations must be performed under certain constraints; otherwise, it may worsen performance rather than improve it. This study clarifies the importance and influence of these different parameters in the simulation results.

METHODS

We analyzed the influence of different parameters on the predictive ability of molecular docking techniques using two software packages: AutoDock Vina and AutoDock-GPU. Thus, 90 receptor-ligand complexes were redocked, evaluating the root mean square deviation (RMSD) between the original position of the ligand (receptor-ligand complex obtained experimentally) and that obtained by the software for every analysis. We investigated the influence of hydrogen atoms (on the receptor and on the receptor-ligand complex), partial charges (QEq, QTPIE, EEM, EEM2015ha, MMFF94, Gasteiger-Marsili, and no charge), search boxes (size and exhaustiveness), ligand characteristics (size and number of torsions), and the use of molecular dynamics (of the receptor or the receptor-ligand complex) before docking analyses.

SARS-CoV2 billion-compound docking

This dataset contains ligand conformations and docking scores for 1.4 billion molecules docked against 6 structural targets from SARS-CoV2, representing 5 unique proteins: MPro, NSP15, PLPro, RDRP, and the Spike protein. Docking was carried out using the AutoDock-GPU platform on the Summit supercomputer and Google Cloud. The docking procedure employed the Solis Wets search method to generate 20 independent ligand binding poses per compound. Each compound geometry was scored using the AutoDock free energy estimate, and rescored using RFScore v3 and DUD-E machine-learned rescoring models. Input protein structures are included, suitable for use by AutoDock-GPU and other docking programs. As the result of an exceptionally large docking campaign, this dataset represents a valuable resource for discovering trends across small molecule and protein binding sites, training AI models, and comparing to inhibitor compounds targeting SARS-CoV-2. The work also gives an example of how to organize and process data from ultra-large docking screens.

A comprehensive insight into the effects of caffeic acid (CA) on pepsin: Multi-spectroscopy and MD simulations methods

The interaction between caffeic acid (CA) and pepsin was investigated using multi-spectroscopy approaches and molecular dynamic simulations (MDS). The effects of CA on the structure, stability, and activity of pepsin were studied. Fluorescence emission spectra and UV-vis absorption peaks all represented the static quenching mechanism of pepsin by CA. Moreover, the fluorescence spectra displayed that the interaction of CA exposed the tryptophan chromophores of pepsin to a more hydrophilic micro-environment. Consistent with the simulation results, thermodynamic parameters revealed that CA was bound to pepsin with a high binding affinity. The Van der Waals force and Hydrogen bond interaction were the dominant driving forces during the binding process. The circular dichroism (CD) spectroscopy analysis showed that the CA binding to pepsin decreased the contents of α-Helix and Random Coil but increased the content of β-sheet in the pepsin structure. Accordingly, MD simulations confirmed all the experimental results. As a result, CA is considered an inhibitor with adverse effects on pepsin activity.

The role of S477N mutation in the molecular behavior of SARS-CoV-2 spike protein: An in-silico perspective

The attachment of SARA-CoV-2 happens between ACE2 and the receptor binding domain (RBD) on the spike protein. Mutations in this domain can affect the binding affinity of the spike protein for ACE2. S477N, one of the most common mutations reported in the recent variants, is located in the RBD. Today's computational approaches in biology, especially during the SARS-CoV-2 pandemic, assist researchers in predicting a protein's behavior in contact with other proteins in more detail. In this study, we investigated the interactions of the S477N-hACE2 in silico to find the impact of this mutation on its binding affinity for ACE2 and immunity responses using dynamics simulation, protein-protein docking, and immunoinformatics methods. Our computational analysis revealed an increased binding affinity of N477 for ACE2. Four new hydrogen and hydrophobic bonds in the mutant RBD-ACE2 were formed (with S19 and Q24 of ACE2), which do not exist in the wild type. Also, the protein spike structure in this mutation was associated with an increase in stabilization and a decrease in its fluctuations at the atomic level. N477 mutation can be considered as the cause of increased escape from the immune system through MHC-II.