Formulation of next-generation polyvalent vaccine candidates against three important poxviruses by targeting DNA-dependent RNA polymerase using an integrated immunoinformatics and molecular modeling approach

BACKGROUND

Poxviruses comprise a group of large double-stranded DNA viruses and are known to cause diseases in humans, livestock animals, and other animal species. The Mpox virus (MPXV; formerly Monkeypox), variola virus (VARV), and volepox virus (VPXV) are among the prevalent poxviruses of the Orthopoxviridae genera. The ongoing Mpox infectious disease pandemic caused by the Mpox virus has had a major impact on public health across the globe. To date, only limited repurposed antivirals and vaccines are available for the effective treatment of Mpox and other poxviruses that cause contagious diseases.

METHODS

The present study was conducted with the primary goal of formulating multi-epitope vaccines against three evolutionary closed poxviruses i.e., MPXV, VARV, and VPXV using an integrated immunoinformatics and molecular modeling approach. DNA-dependent RNA polymerase (DdRp), a potential vaccine target of poxviruses, has been used to determine immunodominant B and T-cell epitopes followed by interactions analysis with Toll-like receptor 2 at the atomic level.

RESULTS

Three multi-epitope vaccine constructs, namely DdRp_MPXV (V1), DdRp_VARV (V2), and DdRp_VPXV (V3) were designed. These vaccine constructs were found to be antigenic, non-allergenic, non-toxic, and soluble with desired physicochemical properties. Protein-protein docking and interaction profiling analysis depicts a strong binding pattern between the targeted immune receptor TLR2 and the structural models of the designed vaccine constructs, and manifested a number of biochemical bonds (hydrogen bonds, salt bridges, and non-bonded contacts). State-of-the-art all-atoms molecular dynamics simulations revealed highly stable interactions of vaccine constructs with TLR2 at the atomic level throughout the simulations on 300 nanoseconds. Additionally, the outcome of the immune simulation analysis suggested that designed vaccines have the potential to induce protective immunity against targeted poxviruses.

CONCLUSIONS

Taken together, formulated next-generation polyvalent vaccines were found to have good efficacy against closely related poxviruses (MPXV, VARV, and VPXV) as demonstrated by our extensive immunoinformatics and molecular modeling evaluations; however, further experimental investigations are still needed.

Immuno-informatics study identifies conserved T cell epitopes in non-structural proteins of Bluetongue virus serotypes: formulation of a computationally optimized next-generation broad-spectrum multi-epitope vaccine

Introduction

Bluetongue (BT) poses a significant threat to the livestock industry, affecting various animal species and resulting in substantial economic losses. The existence of numerous BT virus (BTV) serotypes has hindered control efforts, highlighting the need for broad-spectrum vaccines.

Methodology

In this study, we evaluated the conserved amino acid sequences within key non-structural (NS) proteins of BTV and identified numerous highly conserved murine- and bovine-specific MHC class I-restricted (MHC-I) CD8+ and MHC-II-restricted CD4+ epitopes. We then screened these conserved epitopes for antigenicity, allergenicity, toxicity, and solubility. Using these epitopes, we developed in silico-based broad-spectrum multiepitope vaccines with Toll-like receptor (TLR-4) agonists. The predicted proinflammatory cytokine response was assessed in silico using the C-IMMSIM server. Structural modeling and refinement were achieved using Robetta and GalaxyWEB servers. Finally, we assessed the stability of the docking complexes through extensive 100-nanosecond molecular dynamics simulations before considering the vaccines for codon optimization and in silico cloning.

Results

We found many epitopes that meet these criteria within NS1 and NS2 proteins and developed in silico broad-spectrum vaccines. The immune simulation studies revealed that these vaccines induce high levels of IFN-γ and IL-2 in the vaccinated groups. Protein-protein docking analysis demonstrated promising epitopes with strong binding affinities to TLR-4. The docked complexes were stable, with minimal Root Mean Square Deviation and Root Mean Square Fluctuation values. Finally, the in silico-cloned plasmids have high % of GC content with > 0.8 codon adaptation index, suggesting they are suitable for expressing the protein vaccines in prokaryotic system.

Discussion

These next-generation vaccine designs are promising and warrant further investigation in wet lab experiments to assess their immunogenicity, safety, and efficacy for practical application in livestock. Our findings offer a robust framework for developing a comprehensive, broad-spectrum vaccine, potentially revolutionizing BT control and prevention strategies in the livestock industry.

Immunomodulatory potential of bioactive glycoside syringin: a network pharmacology and molecular modeling approach

Many diseases, such as rheumatoid arthritis, neurodegenerative disease, lupus, autoimmune disease, and cancer, are described by chronic inflammation following tissue damage. Anti-inflammatory drugs like non-steroidal anti-inflammatory drugs and other steroids cause many side effects and generally need careful consideration and monitoring during usage. In recent years, a significant interest in plant-derived approaches has been warranted. The bioactive glycoside syringin might be one of the effective immunomodulatory agents. However, its immunomodulatory potential needs to be better known. In this study, we evaluated the immunomodulatory potential of syringin using network pharmacology, molecular docking, and molecular dynamics simulation-based approaches. First, we applied the GeneCards and OMIM databases to acquire the immunomodulatory agents. Then, the STRING database was utilized to get the hub genes. Interaction analysis and molecular docking described strong binding of the active site of immunomodulatory proteins with the bioactive syringin. Molecular dynamics simulations (200 ns) showed a very stable interaction of syringin with the immunomodulatory protein. Further, the optimized structure and molecular electrostatic potential of the syringin were calculated by a density-functional theory utilizing basis levels of B3LYP/6-31. Syringin investigated in this study holds the required drug-likeness characteristics and follows Lipinski's rule of five. However, quantum-chemical estimations show the syringin has potent reactivity, demonstrating a lower energy gap. Furthermore, the gap between ELUMO and EHOMO was low, suggesting the excellent affinity of syringin towards the immunomodulatory proteins. The present study shows that syringin might be an effective immunomodulatory agent and can be further explored using different experimental methods.Communicated by Ramaswamy H. Sarma.

Inhibition potential of natural flavonoids against selected omicron (B.1.19) mutations in the spike receptor binding domain of SARS-CoV-2: a molecular modeling approach

The omicron (B.1.19) variant of contagious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is considered a variant of concern (VOC) due to its increased transmissibility and highly infectious nature. The spike receptor-binding domain (RBD) is a hotspot of mutations and is regarded as a prominent target for screening drug candidates owing to its crucial role in viral entry and immune evasion. To date, no effective therapy or antivirals have been reported; therefore, there is an urgent need for rapid screening of antivirals. An extensive molecular modelling study has been performed with the primary goal to assess the inhibition potential of natural flavonoids as inhibitors against RBD from a manually curated library. Out of 40 natural flavonoids, five natural flavonoids, namely tomentin A (-8.7 kcal/mol), tomentin C (-8.6 kcal/mol), hyperoside (-8.4 kcal/mol), catechin gallate (-8.3 kcal/mol), and corylifol A (-8.2 kcal/mol), have been considered as the top-ranked compounds based on their binding affinity and molecular interaction profiling. The state-of-the-art molecular dynamics (MD) simulations of these top-ranked compounds in complex with RBD exhibited stable dynamics and structural compactness patterns on 200 nanoseconds. Additionally, complexes of these molecules demonstrated favorable free binding energies and affirmed the docking and simulation results. Moreover, the post-simulation validation of these interacted flavonoids using principal component analysis (PCA) revealed stable interaction patterns with RBD. The integrated results suggest that tomentin A, tomentin C, hyperoside, catechin gallate, and corylifol A might be effective against the emerging variants of SARS-CoV-2 and should be further evaluated using in-vitro and in-vivo experiments.Communicated by Ramaswamy H. Sarma.

Multiplex Cas9-based excision of CLCuV betasatellite and DNA-A revealed reduction of viral load with asymptomatic cotton plants

MAIN CONCLUSION

Multiplexed Cas9-based genome editing of cotton resulted in reduction of viral load with asymptomatic cotton plants. In depth imaging of proteomic dynamics of resulting CLCuV betasatellite and DNA-A protein was also performed. The notorious  cotton leaf curl virus (CLCuV), which is transmitted by the sap-sucking insect whitefly, continuously damages cotton crops. Although the application of various toxins and RNAi has shown some promise, sustained control has not been achieved. Consequently, CRISPR_Cas9 was applied by designing multiplex targets against DNA-A (AC2 and AC3) and betasatellite (βC1) of CLCuV using CRISPR direct and ligating into the destination vector of the plant using gateway ligation method. The successful ligation of targets into the destination vector was confirmed by the amplification of 1049 bp using a primer created from the promoter and target, while restriction digestion using the AflII and Asc1 enzymes determined how compact the plasmid developed and the nucleotide specificity of the plasmid was achieved through Sanger sequencing. PCR confirmed the successful introduction of plasmid into CKC-1 cotton variety. Through Sanger sequencing and correlation with the mRNA expression of DNA-A and betasatellite in genome-edited cotton plants subjected to agroinfiltration of CLCuV infectious clone, the effectiveness of knockout was established. The genome-edited cotton plants demonstrated edited efficacy of 72% for AC2 and AC3 and 90% for the (βC1) through amplicon sequencing, Molecular dynamics (MD) simulations were used to further validate the results. Higher RMSD values for the edited βC1 and AC3 proteins indicated functional loss caused by denaturation. Thus, CRISPR_Cas9 constructs can be rationally designed using high-throughput MD simulation technique. The confidence in using this technology to control plant virus and its vector was determined by the knockout efficiency and the virus inoculation assay.

Computational analysis of immunogenic epitopes in the p30 and p54 proteins of African swine fever virus

African swine fever (ASF) is a highly infectious viral disease of pigs, which causes acute fatal haemorrhage and is a severe concern to the global pork industry. The present study followed computational approaches to identify B- and T-cell epitopes for the p30 and p54 proteins of the African swine fever virus (ASFV) by interacting with the swine leukocyte antigen (SLA) alleles. The amino acid sequences of p30 and p54 were analysed for variability and relative solvent accessibility, and their three-dimensional structures were predicted and validated. Molecular dynamics simulation was performed to study the structural and dynamic properties of the protein. Six and five linear B-cell epitopes have been predicted for p30 and p54, respectively. Four and three discontinuous B-cell epitopes have been predicted for p30 and p54, respectively. Further, the top five T-cell epitopes for SLA-1, 2, and 3 have been listed for both proteins. These results can help us to understand the immunodominant regions in the p30 and p54 proteins of ASFV and potentially assist in designing peptide-based diagnostics and vaccines. Also, the identified T-cell epitopes may be considered for peptide-based vaccine design against ASFV.Communicated by Ramaswamy H. Sarma.

Drug repurposing for Mpox: Discovery of small molecules as potential inhibitors against DNA-dependent RNA polymerase using molecular modeling approach

Mpox (formerly Monkeypox), a zoonotic illness caused by the Mpox virus, belongs to the Orthopoxvirus genus in the family Poxviridae. To design and develop effective antiviral therapeutics against DNA viruses, the DNA-dependent RNA polymerase (DdRp) of poxviruses has emerged as a promising drug target. In the present study, we modeled the three-dimensional (3D) structure of DdRp using a template-based homology approach. After modeling, virtual screening was performed to probe the molecular interactions between 1755 Food and Drug Administration-approved small molecule drugs (≤500 molecular weight) and the DdRp of Mpox. Based on the binding affinity and molecular interaction patterns, five drugs, lumacaftor (-11.7 kcal/mol), conivaptan (-11.7 kcal/mol), betulinic acid (-11.6 kcal/mol), fluspirilene (-11.3 kcal/mol), and imatinib (-11.2 kcal/mol), have been ranked as the top drug compounds interacting with Mpox DdRp. Complexes of these shortlisted drugs with DdRp were further evaluated using state-of-the-art all-atoms molecular dynamics (MD) simulations on 200 nanoseconds followed by principal component analysis (PCA). MD simulations and PCA results revealed highly stable interactions of these small drugs with DdRp. After due validation in wet-lab using available in vitro and in vivo experiments, these repurposed drugs can be further utilized for the treatment of contagious Mpox virus. The outcome of this study may establish a solid foundation to screen repurposed and natural compounds as potential antiviral therapeutics against different highly pathogenic viruses.

Therapeutic strategies for Covid-19 based on molecular docking and dynamic studies to the ACE-2 receptors, Furin, and viral spike proteins

SARS-CoV-2 is a pandemic virus that caused infections and deaths in many world countries, including the Middle East. The virus-infected human cells by binding via ACE-2 receptor through the Spike protein of the virus with Furin's help causing cell membrane fusion leading to Covid-19-cell entry. No registered drugs or vaccines are triggering this pandemic viral disease yet. Our present work is based on molecular docking and dynamics simulation that performed to spike protein-ACE-2 interface complex, ACE-2 receptor, Spike protein (RBD), and Furin as targets for new small molecules. These drugs target new potential therapies to show their probabilities toward the active sites of mentioned proteins, strongly causing inhibition and/or potential therapy for covid-19. All target proteins were estimated against new target compounds under clinical trials and repurposing drugs currently present. Possibilities of those molecules and potential therapeutics acting on a certain target were predicted. MD simulations over 200 ns with molecular mechanics-generalized Born surface area (MMGBSA) binding energy calculations were performed. The structural and energetic analyses demonstrated the stability of the ligands-M^Pros complex. Our present work will introduce new visions of some biologically active molecules for further studies in-vitro and in-vivo for Covid-19, repurposing of these molecules should be taking place under clinical works and offering different strategies for drugs repurposing against Covid-19 diseases.Communicated by Ramaswamy H. Sarma.

Designing of disruptor molecules to restrain the protein-protein interaction network of VANG1/SCRIB/NOS1AP using fragment-based drug discovery techniques

Governing protein-protein interaction networks are the cynosure of cell signaling and oncogenic networks. Multifarious processes when aligned with one another can result in a dysregulated output which can result in cancer progression. In the current research, one such network of proteins comprising VANG1/SCRIB/NOS1AP, which is responsible for cell migration, is targeted. The proteins are modeled using in-silico approaches, and the interaction is visualized utilizing protein-protein docking. Designing drugs for the convoluted protein network can serve as a challenging task that can be overcome by fragment-based drug designing, a recent game-changer in the computational drug discovery strategy for protein interaction networks. The model is exposed to the extraction of hotspots, also known as the restrained regions for small molecular hits. The hotspot regions are subjected to a library of generated fragments, which are then recombined and rejoined to develop small molecular disruptors of the macromolecular assemblage. Rapid screening methods using pharmacokinetic tools and 2D interaction studies resulted in four molecules that could serve the purpose of a disruptor. The final validation is executed by long-range simulations of 100 ns and exploring the stability of the complex using several parameters leading to the emergence of two novel molecules VNS003 and VNS005 that could be used as the disruptors of the protein assembly VANG1/SCRIB/NOS1AP. Also, the molecules were explored as single protein targets approbated via molecular docking and 100 ns molecular dynamics simulation. This concluded VNS003 as the most suitable inhibitor module capable of acting as a disruptor of a macromolecular assembly as well as acting on individual protein chains, thus leading to the primary hindrance in the formation of the protein interaction complex.

Potential of Natural Alkaloids From Jadwar (Delphinium denudatum) as Inhibitors Against Main Protease of COVID-19: A Molecular Modeling Approach

The ongoing pandemic coronavirus disease (COVID-19) caused by a novel corona virus, namely, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has had a major impact on global public health. COVID-19 cases continue to increase across the globe with high mortality rates in immunocompromised patients. There is still a pressing demand for drug discovery and vaccine development against this highly contagious disease. To design and develop antiviral drugs against COVID-19, the main protease (M^pro) has emerged as one of the important drug targets. In this context, the present work explored Jadwar (Delphinium denudatum)-derived natural alkaloids as potential inhibitors against M^pro of SARS-CoV-2 by employing a combination of molecular docking and molecular dynamic simulation-based methods. Molecular docking and interaction profile analysis revealed strong binding on the M^pro functional domain with four natural alkaloids viz. panicutine (-7.4 kcal/mol), vilmorrianone (-7.0 kcal/mol), denudatine (-6.0 kcal/mol), and condelphine (-5.9 kcal/mol). The molecular docking results evaluated by using the MD simulations on 200 nanoseconds confirmed highly stable interactions of these compounds with the M^pro. Additionally, mechanics/generalized Born/Poisson-Boltzmann surface area (MM/G/P/BSA) free energy calculations also affirmed the docking results. Natural alkaloids explored in the present study possess the essential drug-likeness properties, namely, absorption, distribution, metabolism, and excretion (ADME), and are in accordance with Lipinski's rule of five. The results of this study suggest that these four bioactive molecules, namely, condelphine, denudatine, panicutine, and vilmorrianone, might be effective candidates against COVID-19 and can be further investigated using a number of experimental methods.

PSnpBind: a database of mutated binding site protein-ligand complexes constructed using a multithreaded virtual screening workflow

A key concept in drug design is how natural variants, especially the ones occurring in the binding site of drug targets, affect the inter-individual drug response and efficacy by altering binding affinity. These effects have been studied on very limited and small datasets while, ideally, a large dataset of binding affinity changes due to binding site single-nucleotide polymorphisms (SNPs) is needed for evaluation. However, to the best of our knowledge, such a dataset does not exist. Thus, a reference dataset of ligands binding affinities to proteins with all their reported binding sites’ variants was constructed using a molecular docking approach. Having a large database of protein–ligand complexes covering a wide range of binding pocket mutations and a large small molecules’ landscape is of great importance for several types of studies. For example, developing machine learning algorithms to predict protein–ligand affinity or a SNP effect on it requires an extensive amount of data. In this work, we present PSnpBind: A large database of 0.6 million mutated binding site protein–ligand complexes constructed using a multithreaded virtual screening workflow. It provides a web interface to explore and visualize the protein–ligand complexes and a REST API to programmatically access the different aspects of the database contents. PSnpBind is open source and freely available at https://psnpbind.org.

Exploring Klebsiella pneumoniae capsule polysaccharide proteins to design multiepitope subunit vaccine to fight against pneumonia

BACKGROUND

Klebsiella pneumoniae is an emerging human pathogen causing neonatal lung disease, catheter-associated infections, and nosocomial outbreaks with high fatality rates. Capsular polysaccharide (CPS) protein plays a major determinant in virulence and is considered as a promising target for vaccine development.

RESEARCH DESIGN AND METHODS

In this study, we used immunoinformatic approaches to design a multi-peptide vaccine against K. pneumonia. The epitopes were selected through several immune filters, such as antigenicity, conservancy, nontoxicity, non-allergenicity, binding affinity to HLA alleles, overlapping epitopes, and peptides having common epitopes.

RESULTS

Finally, a construct comprising 2 B-Cell, 8 CTL, 2 HTL epitopes, along with adjuvant, linkers was designed. Peptide-HLA interaction analysis showed strong binding of these epitopes with several common HLA molecules. The in silico immune simulation and population coverage analysis of the vaccine showed its potential to evoke strong immune responses.. Further, the interaction between vaccine and immune was evaluated by docking and simulation, revealing high affinity and complex stability. Codon adaptation and in silico cloning revealed higher expression of vaccine in E. coli K12 expression system.

CONCLUSIONS

Conclusively, the findings of the present study suggest that the designed novel multi-epitopic vaccine holds potential for further experimental validation against the pathogen.

Structural and functional insights into the candidate genes associated with different developmental stages of flag leaf in bread wheat (Triticum aestivum L.)

Grain yield is one of the most important aims for combating the needs of the growing world population. The role of development and nutrient transfer in flag leaf for higher yields at the grain level is well known. It is a great challenge to properly exploit this knowledge because all the processes, starting from the emergence of the flag leaf to the grain filling stages of wheat (Triticum aestivum L.), are very complex biochemical and physiological processes to address. This study was conducted with the primary goal of functionally and structurally annotating the candidate genes associated with different developmental stages of flag leaf in a comprehensive manner using a plethora of in silico tools. Flag leaf-associated genes were analyzed for their structural and functional impacts using a set of bioinformatics tools and algorithms. The results revealed the association of 17 candidate genes with different stages of flag leaf development in wheat crop. Of these 17 candidate genes, the expression analysis results revealed the upregulation of genes such as TaSRT1-5D, TaPNH1-7B, and TaNfl1-2B and the downregulation of genes such as TaNAP1-7B, TaNOL-4D, and TaOsl2-2B can be utilized for the generation of high-yielding wheat varieties. Through MD simulation and other in silico analyses, all these proteins were found to be stable. Based on the outcome of bioinformatics and molecular analysis, the identified candidate genes were found to play principal roles in the flag leaf development process and can be utilized for higher-yield wheat production.

Disruption of DYRK1A-induced hyperphosphorylation of amyloid-beta and tau protein in Alzheimer's disease: An integrative molecular modeling approach

Alzheimer's disease (AD) is a neurological disorder caused by the abnormal accumulation of hyperphosphorylated proteins. Dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) is a dual phosphorylation enzyme which phosphorylates the amyloid-β (Aβ) and neurofibrillary tangles (NFTs). A high throughput virtual screening approach was applied to screen a library of 98,071 compounds against DYRK1A using different programs including AutoDock Vina, Smina, and idock. Based on the binding affinities, we selected 330 compounds for absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis. Various pharmacokinetics parameters were predicted using the admetSAR server, and based on the pharmacokinetics results, 14 compounds were selected for cross-docking analysis using AutoDock. Cross-docking analysis revealed four compounds, namely, ZINC3843365 (-11.07 kcal/mol^-1), ZINC2123081 (-10.93 kcal/mol^-1), ZINC5220992 (-10.63 kcal/mol^-1), and ZINC68569602 (-10.35 kcal/mol^-1), which had the highest negative affinity scores compared to the 10 other molecules analyzed. Density functional theory (DFT) analysis was conducted for all the four top-ranked compounds. The molecular interaction stability of these four compounds with DYRK1A has been evaluated using molecular dynamics (MD) simulations on 100 nanoseconds followed by principal component analysis (PCA) and binding free energy calculations. The Gibbs free energy landscape analysis suggested the metastable state and folding pattern of selected docking complexes. Based on the present study outcome, we propose four antagonists, viz., ZINC3843365, ZINC2123081, ZINC5220992, and ZINC68569602 as potential inhibitors against DYRK1A and to reduce the amyloid-β and neurofibrillary tangle burden. These screened molecules can be further investigated using a number of in vitro and in vivo experiments.

Computer-aided identification of potential inhibitors against Necator americanus glutathione S-transferase 3

Hookworm infection is caused by the blood-feeding hookworm gastrointestinal nematodes. Its harmful effects include anemia and retarded growth and are common in the tropics. A current control method involves the mass drug administration of synthetic drugs, mainly albendazole and mebendazole. There are however concerns of low efficacy and drug resistance due to their repeated and excessive use. Although, Necator americanus glutathione S-transferase 3 (Na-GST-3) is a notable target, using natural product libraries for computational elucidation of promising leads is underexploited. This study sought to use pharmacoinformatics techniques to identify compounds of natural origins with the potential to be further optimized as promising inhibitors. A compendium of 3182 African natural products together with five known helminth GST inhibitors including Cibacron blue was screened against the active sites of the Na-GST-3 structure (PDB ID: 3W8S). The hit compounds were profiled to ascertain the mechanisms of binding, anthelmintic bioactivity, physicochemical and pharmacokinetic properties. The AutoDock Vina docking protocol was validated by obtaining 0.731 as the area under the curve calculated via the receiver operating characteristics curve. Four compounds comprising ZINC85999636, ZINC35418176, ZINC14825190, and Dammarane Triterpene13 were identified as potential lead compounds with binding energies less than -9.0 kcal/mol. Furthermore, the selected compounds formed key intermolecular interactions with critical residues Tyr95, Gly13 and Ala14. Notably, ZINC85999636, ZINC14825190, and dammarane triterpene13 were predicted as anthelmintics, whilst all the four molecules shared structural similarities with known inhibitors. Molecular modelling showed that the compounds had reasonably good binding free energies. More so, they had high binding affinities when screened against other variants of the Na-GST, namely Na-GST-1 and Na-GST-2. Ligand quality assessment using ligand efficiency dependent lipophilicity, ligand efficiency, ligand efficiency scale and fit quality scale showed the molecules are worthy candidates for further optimization. The inhibitory potentials of the molecules warrant in vitro studies to evaluate their effect on the heme regulation mechanisms.

CellSys: An open-source tool for building initial structures for bio-membranes and drug-delivery systems

Since phospholipids are the most important components in the structure of biomembranes, they deserve to be considered with a lot of attention in both experimental and computational theoretical studies using molecular simulation methods related to the research in the fields of drug design and drug delivery where they involve knowledge about the interactions of drug molecules with cell membranes. To employ the molecular simulation approach for this purpose the essential requirement is having information about the initial structure of phospholipids and how they interact with the drugs. Therefore in this article, we introduce an open-source software package in Python programming language for utilizing data manipulation for generation and developing the initial structure of biomolecular cells to provide the needed information for investigation in drug delivery systems. In addition, the proposed software package can be used for the efficient storage of membrane structural data to be exploited in designing new drug delivery systems. To verify the performance of the code and the results of the simulations, several analyses have been done, such as the calculation of area per lipid and self-diffusion coefficient, in addition to lipid order parameter. The results were in complete agreement with the references.

QSAR and deep learning model for virtual screening of potential inhibitors against Inosine 5' Monophosphate dehydrogenase (IMPDH) of Cryptosporidium parvum

Cryptosporidium parvum (Cp) causes a gastro-intestinal disease called Cryptosporidiosis. C. parvum Inosine 5' monophosphate dehydrogenase (CpIMPDH) is responsible for the production of guanine nucleotides. In the present study, 37 known urea-based congeneric compounds were used to build a 2D and 3D QSAR model against CpIMPDH. The built models were validated based on OECD principles. A deep learning model was adopted from a framework called Deep Purpose. The model was trained with 288 known active compounds and validated using a test set. From the training set of the 3D QSAR, a pharmacophore model was built and the best pharmacophore hypotheses were scored and sorted using a phase-hypo score. A phytochemical database was screened using both the pharmacophore model and a deep learning model. The screened compounds were considered for glide XP docking, followed by quantum polarized ligand docking. Finally, the best compound among them was considered for molecular dynamics simulation study.

Inhibition Potencies of Phytochemicals Derived from Sesame Against SARS-CoV-2 Main Protease: A Molecular Docking and Simulation Study

The ongoing COVID-19 pandemic, caused by SARS-CoV-2, has now spread across the nations with high mortality rates and multifaceted impact on human life. The proper treatment methods to overcome this contagious disease are still limited. The main protease enzyme (Mpro, also called 3CLpro) is essential for viral replication and has been considered as one of the potent drug targets for treating COVID-19. In this study, virtual screening was performed to find out the molecular interactions between 36 natural compounds derived from sesame and the Mpro of COVID-19. Four natural metabolites, namely, sesamin, sesaminol, sesamolin, and sesamolinol have been ranked as the top interacting molecules to Mpro based on the affinity of molecular docking. Moreover, stability of these four sesame-specific natural compounds has also been evaluated using molecular dynamics (MD) simulations for 200 nanoseconds. The molecular dynamics simulations and free energy calculations revealed that these compounds have stable and favorable energies, causing strong binding with Mpro. These screened natural metabolites also meet the essential conditions for drug likeness such as absorption, distribution, metabolism, and excretion (ADME) properties as well as Lipinski's rule of five. Our finding suggests that these screened natural compounds may be evolved as promising therapeutics against COVID-19.

Computational and experimental characterization of isomers of escin-induced renal cytotoxicity by inhibiting heat shock proteins

Escin is a natural mixture of triterpene saponins, exhibits anti-oedematous properties and promotes venous drainage by oral administration or injection. Upon clinical application of escin, adverse kidney reactions have been reported and the nephrotoxic mechanism responsible for this reaction remains elusive. In the present study, four isomeric escins (β-form: escin Ia and escin Ib; α-form: isoescin Ia and isoescin Ib) were found severely decreasing the cell viability of human kidney (HK-2) cells. A decline in HK-2 cell viability caused by sodium aescinate (a mixture of four isomers) was reduced after β-glucuronidase hydrolysis. In addition, sodium aescinate concentration-dependently inhibited the expression level of heat shock proteins (HSPs) in the Madin-Darby Canine Kidney (MDCK) cells. Moreover, with molecular docking and molecular dynamics simulation, these four isomeric escins could directly bind to the ATP-binding domain of HSP70 and HSP90, thus competitively inhibiting the function of HSPs. Escin Ia is bound to HSPs with the lowest binding free energy, which is consistent with the observation that escin Ia most severely decreases HK-2 cell viability. Thus, we demonstrate a heretofore unknown molecular mechanism of escin-induced renal cytotoxicity as well as identify HSPs as potential targets for the renal cytotoxic effect of escin.

In silico investigation of phytoconstituents from Indian medicinal herb 'Tinospora cordifolia (giloy)' against SARS-CoV-2 (COVID-19) by molecular dynamics approach

The recent appearance of COVID-19 virus has created a global crisis due to unavailability of any vaccine or drug that can effectively and deterministically work against it. Naturally, different possibilities (including herbal medicines having known therapeutic significance) have been explored by the scientists. The systematic scientific study (beginning with in silico study) of herbal medicines in particular and any drug in general is now possible as the structural components (proteins) of COVID-19 are already characterized. The main protease of COVID-19 virus is Mpro or 3CLpro which is a key CoV enzyme and an attractive drug target as it plays a pivotal role in mediating viral replication and transcription. In the present study, 3CLpro is used to study drug:3CLpro interactions and thus to investigate whether all or any of the main chemical constituents of Tinospora cordifolia (e.g. berberine (C20H18NO4), β-sitosterol (C29H50O), coline (C5H14NO), tetrahydropalmatine (C21H25NO4) and octacosanol (C28H58O)) can be used as an anti-viral drug against SARS-CoV-2. The in silico study performed using tools of network pharmacology, molecular docking including molecular dynamics have revealed that among all considered phytochemicals in Tinospora cordifolia, berberine can regulate 3CLpro protein's function due to its easy inhibition and thus can control viral replication. The selection of Tinospora cordifolia was motivated by the fact that the main constituents of it are known to be responsible for various antiviral activities and the treatment of jaundice, rheumatism, diabetes, etc.Communicated by Ramaswamy H. Sarma.

Identification of phytochemical inhibitors against main protease of COVID-19 using molecular modeling approaches

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a novel corona virus that causes corona virus disease 2019 (COVID-19). The COVID-19 rapidly spread across the nations with high mortality rate even as very little is known to contain the virus at present. In the current study, we report novel natural metabolites namely, ursolic acid, carvacrol and oleanolic acid as the potential inhibitors against main protease (Mpro) of COVID-19 by using integrated molecular modeling approaches. From a combination of molecular docking and molecular dynamic (MD) simulations, we found three ligands bound to protease during 50 ns of MD simulations. Furthermore, the molecular mechanic/generalized/Born/Poisson-Boltzmann surface area (MM/G/P/BSA) free energy calculations showed that these chemical molecules have stable and favourable energies causing strong binding with binding site of Mpro protein. All these three molecules, namely, ursolic acid, carvacrol and oleanolic acid, have passed the ADME (Absorption, Distribution, Metabolism, and Excretion) property as well as Lipinski's rule of five. The study provides a basic foundation and suggests that the three phytochemicals, viz. ursolic acid, carvacrol and oleanolic acid could serve as potential inhibitors in regulating the Mpro protein's function and controlling viral replication. Communicated by Ramaswamy H. Sarma.

Marine natural compounds as potents inhibitors against the main protease of SARS-CoV-2-a molecular dynamic study

Sever acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA (ssRNA) virus, responsible for severe acute respiratory disease (COVID-19). A large number of natural compounds are under trial for screening compounds, possessing potential inhibitory effect against the viral infection. Keeping in view the importance of marine compounds in antiviral activity, we investigated the potency of some marine natural products to target SARS-CoV-2 main protease (Mpro) (PDB ID 6MO3). The crystallographic structure of Mpro in an apo form was retrieved from Protein Data Bank and marine compounds from PubChem. These structures were prepared for docking and the complex with good docking score was subjected to molecular dynamic (MD) simulations for a period of 100 ns. To measure the stability, flexibility, and average distance between the target and compounds, root mean square deviations (RMSD), root mean square fluctuation (RMSF), and the distance matrix were calculated. Among five marine compounds, C-1 (PubChem CID 11170714) exhibited good activity, interacting with the active site and surrounding residues, forming many hydrogen and hydrophobic interactions. The C-1 also attained a stable dynamic behavior, and the average distance between compound and target remains constant. In conclusion, marine natural compounds may be used as a potential inhibitor against SARS-CoV-2 for better management of COVID-19.

Marine natural compounds as potents inhibitors against the main protease of SARS-CoV-2-a molecular dynamic study

Sever acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a single-stranded RNA (ssRNA) virus, responsible for severe acute respiratory disease (COVID-19). A large number of natural compounds are under trial for screening compounds, possessing potential inhibitory effect against the viral infection. Keeping in view the importance of marine compounds in antiviral activity, we investigated the potency of some marine natural products to target SARS-CoV-2 main protease (M^pro) (PDB ID 6MO3). The crystallographic structure of M^pro in an apo form was retrieved from Protein Data Bank and marine compounds from PubChem. These structures were prepared for docking and the complex with good docking score was subjected to molecular dynamic (MD) simulations for a period of 100 ns. To measure the stability, flexibility, and average distance between the target and compounds, root mean square deviations (RMSD), root mean square fluctuation (RMSF), and the distance matrix were calculated. Among five marine compounds, C-1 (PubChem CID 11170714) exhibited good activity, interacting with the active site and surrounding residues, forming many hydrogen and hydrophobic interactions. The C-1 also attained a stable dynamic behavior, and the average distance between compound and target remains constant. In conclusion, marine natural compounds may be used as a potential inhibitor against SARS-CoV-2 for better management of COVID-19.

Computational Identification of Potential Anti-Inflammatory Natural Compounds Targeting the p38 Mitogen-Activated Protein Kinase (MAPK): Implications for COVID-19-Induced Cytokine Storm

Severely ill coronavirus disease 2019 (COVID-19) patients show elevated concentrations of pro-inflammatory cytokines, a situation commonly known as a cytokine storm. The p38 MAPK receptor is considered a plausible therapeutic target because of its involvement in the platelet activation processes leading to inflammation. This study aimed to identify potential natural product-derived inhibitory molecules against the p38α MAPK receptor to mitigate the eliciting of pro-inflammatory cytokines using computational techniques. The 3D X-ray structure of the receptor with PDB ID 3ZS5 was energy minimized using GROMACS and used for molecular docking via AutoDock Vina. The molecular docking was validated with an acceptable area under the curve (AUC) of 0.704, which was computed from the receiver operating characteristic (ROC) curve. A compendium of 38,271 natural products originating from Africa and China together with eleven known p38 MAPK inhibitors were screened against the receptor. Four potential lead compounds ZINC1691180, ZINC5519433, ZINC4520996 and ZINC5733756 were identified. The compounds formed strong intermolecular bonds with critical residues Val38, Ala51, Lys53, Thr106, Leu108, Met109 and Phe169. Additionally, they exhibited appreciably low binding energies which were corroborated via molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. The compounds were also predicted to have plausible pharmacological profiles with insignificant toxicity. The molecules were also predicted to be anti-inflammatory, kinase inhibitors, antiviral, platelet aggregation inhibitors, and immunosuppressive, with probable activity (Pa) greater than probable inactivity (Pi). ZINC5733756 is structurally similar to estradiol with a Tanimoto coefficient value of 0.73, which exhibits anti-inflammatory activity by targeting the activation of Nrf2. Similarly, ZINC1691180 has been reported to elicit anti-inflammatory activity in vitro. The compounds may serve as scaffolds for the design of potential biotherapeutic molecules against the cytokine storm associated with COVID-19.

Unraveling the potential role of bioactive molecules produced by Trichoderma spp. as inhibitors of tomatinase enzyme having an important role in wilting disease: an in-silico approach

Tomatinase; a saponin detoxification enzyme produced by Fusarium oxysporumf.sp. lycopersici is reported as a causative agent for wilting disease in tomato crops. The disease is instigated by inhibiting the activity of α-tomatine. Trichoderma spp. widely used as biocontrol agent play an essential role in plant growth and pathogen control. In the current study, an in-silico approach using substrate docking, molecular dynamics and MM/PBSA analysis was used to evaluate the potential role of bioactive metabolites produced by Trichoderma spp. The study aims to establish the efficacy of catalytic tendency of the bioactive metabolites to combat the effect of tomatinase enzyme employing α-tomatine as the substrate. By means of the integrated molecular modeling approach; novel bioactive metabolites namely, Trichodermamide B, Trichosetin and Virone were found to be the potential inhibitors against tomatinase enzyme secreted by Fusarium oxysporum f.sp. lycopersici. Molecular dynamic (MD) simulations displayed that the screened ligands bound tomatinase during 150 ns of MD simulations. Furthermore, the (MM-PBSA) free energy calculations depicted that screened molecules possess stable and favorable energies for Trichodermamide B (-7.1 kcal/mol), Trichosetin (-7.4 kcal/mol) and Virone (-7.9 kcal/mol) thereby instigating robust binding with the enzyme's binding site. The results attained in this study, reflects that these bioactive metabolites may serve as potential substrates to control and inhibit the tomatinase enzyme; playing an integral role in combating the wilt disease.Communicated by Ramaswamy H. Sarma.

Thermodynamic and structural aspects of molecular recognition in mannose-binding protein complexes: a theoretical study over HRP-ArtinM association

The biomolecular recognition of D-mannose-binding lectin from Artocarpus heterophyllus (ArtinM) by Horseradish Peroxidase (HRP) mediated by glycosylation allows their application in a multitude of biological systems. The present work describes the use of molecular dynamics (MD) to assess the Gibbs free energy associated with the formation of a ArtinM-HRP conjugate mediated by a glycosylation molecule. For the enthalpy term, we applied the molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method and for the vibrational entropy term, we use the quasi-harmonic approximation. Our results show that, even without glycosylation, the binding free energy between ArtinM and HRP is - 196.154 kJmol^- 1, an extremely high affinity with low selectivity, originated mainly through the van der Waals energy terms. The binding free energy between ArtinM and the glycosylated HRP (gHRP) was calculated at - 66.156 kJmol^- 1, an absolute and considerably lower value, however, originated from electrostatic energy terms, which increases the selectivity of molecular recognition. Our work has shown that the HRP active site region has a high affinity and low selectivity for other biomolecules. The presence of glycosylation plays a role in increasing this selectivity for this region. Thus, we conclude that performing mutagenesis of amino acid residues near the entrance of the catalytic site, can improve the activity of non-glycosylated HRPs. This illustrates new insights that can be applied to carbohydrate-based immunochemistry.

Potential of Pueraria tuberosa (Willd.) DC. to rescue cognitive decline associated with BACE1 protein of Alzheimer's disease on Drosophila model: An integrated molecular modeling and in vivo approach

The indispensable role of Beta-site amyloid precursor protein cleaving enzyme-1 (BACE1) in Amyloid beta (Aβ) plaques generation and Aβ-mediated synaptic dysfunctions makes it a crucial target for therapeutic intervention in Alzheimer's disease (AD). In order to find out the potential inhibitors of BACE1, the present study focused on five phytochemicals from Pueraria tuberosa, namely, daidzin, genistin, mangiferin, puerarin, and tuberosin. A molecular docking study showed that all five phytochemicals presented the strongest BACE1 inhibition. Integrated molecular dynamics simulations and free energy calculations demonstrated that all five natural compounds have stable and favorable energies causing strong binding with the pocket site of BACE1 on 50 ns. All these molecules also passed Lipinski's rule of five. To validate the molecular modeling based findings, we primarily targeted the cognitive decline associated with BACE1 expression in AD flies with P. tuberosa. Significant improvement in cognitive decline was observed in AD flies in different behavioral assays such as Larval crawling assay (16.38%), Larval light preference assay (26.39%), Climbing assay (32.97%), Cold sensitivity assay (43.6%), and Thermal sensitivity assay (44.42%). The present findings suggest that P. tuberosa may be considered as a promising dietary supplement that can significantly ameliorate cognitive decline caused by BACE1 in Alzheimer's disease (AD).

Cheminformatics-Based Identification of Potential Novel Anti-SARS-CoV-2 Natural Compounds of African Origin

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome virus 2 (SARS-CoV-2) has impacted negatively on public health and socioeconomic status, globally. Although, there are currently no specific drugs approved, several existing drugs are being repurposed, but their successful outcomes are not guaranteed. Therefore, the search for novel therapeutics remains a priority. We screened for inhibitors of the SARS-CoV-2 main protease and the receptor-binding domain of the spike protein from an integrated library of African natural products, compounds generated from machine learning studies and antiviral drugs using AutoDock Vina. The binding mechanisms between the compounds and the proteins were characterized using LigPlot+ and molecular dynamics simulations techniques. The biological activities of the hit compounds were also predicted using a Bayesian-based approach. Six potential bioactive molecules NANPDB2245, NANPDB2403, fusidic acid, ZINC000095486008, ZINC0000556656943 and ZINC001645993538 were identified, all of which had plausible binding mechanisms with both viral receptors. Molecular dynamics simulations, including molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) computations revealed stable protein-ligand complexes with all the compounds having acceptable free binding energies <-15 kJ/mol with each receptor. NANPDB2245, NANPDB2403 and ZINC000095486008 were predicted as antivirals; ZINC000095486008 as a membrane permeability inhibitor; NANPDB2403 as a cell adhesion inhibitor and RNA-directed RNA polymerase inhibitor; and NANPDB2245 as a membrane integrity antagonist. Therefore, they have the potential to inhibit viral entry and replication. These drug-like molecules were predicted to possess attractive pharmacological profiles with negligible toxicity. Novel critical residues identified for both targets could aid in a better understanding of the binding mechanisms and design of fragment-based de novo inhibitors. The compounds are proposed as worthy of further in vitro assaying and as scaffolds for the development of novel SARS-CoV-2 therapeutic molecules.

Design, Screening, and Testing of Non-Rational Peptide Libraries with Antimicrobial Activity: In Silico and Experimental Approaches

One of the challenges of modern biotechnology is to find new routes to mitigate the resistance to conventional antibiotics. Antimicrobial peptides (AMPs) are an alternative type of biomolecules, naturally present in a wide variety of organisms, with the capacity to overcome the current microorganism resistance threat. Here, we reviewed our recent efforts to develop a new library of non-rationally produced AMPs that relies on bacterial genome inherent diversity and compared it with rationally designed libraries. Our approach is based on a four-stage workflow process that incorporates the interplay of recent developments in four major emerging technologies: artificial intelligence, molecular dynamics, surface-display in microorganisms, and microfluidics. Implementing this framework is challenging because to obtain reliable results, the in silico algorithms to search for candidate AMPs need to overcome issues of the state-of-the-art approaches that limit the possibilities for multi-space data distribution analyses in extremely large databases. We expect to tackle this challenge by using a recently developed classification algorithm based on deep learning models that rely on convolutional layers and gated recurrent units. This will be complemented by carefully tailored molecular dynamics simulations to elucidate specific interactions with lipid bilayers. Candidate AMPs will be recombinantly-expressed on the surface of microorganisms for further screening via different droplet-based microfluidic-based strategies to identify AMPs with the desired lytic abilities. We believe that the proposed approach opens opportunities for searching and screening bioactive peptides for other applications.

A Computational Study to Identify Potential Inhibitors of SARS-CoV-2 Main Protease (Mpro) from Eucalyptus Active Compounds

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was found to be a severe threat to global public health in late 2019. Nevertheless, no approved medicines have been found to inhibit the virus effectively. Anti-malarial and antiviral medicines have been reported to target the SARS-CoV-2 virus. This paper chose eight natural eucalyptus compounds to study their binding interactions with the SARS-CoV-2 main protease (Mpro) to assess their potential for becoming herbal drugs for the new SARS-CoV-2 infection virus. In-silico methods such as molecular docking, molecular dynamics (MD) simulations, and Molecular Mechanics Poisson Boltzmann Surface Area (MM/PBSA) analysis were used to examine interactions at the atomistic level. The results of molecular docking indicate that Mpro has good binding energy for all compounds studied. Three docked compounds, α-gurjunene, aromadendrene, and allo-aromadendrene, with highest binding energies of −7.34 kcal/mol (−30.75 kJ/mol), −7.23 kcal/mol (−30.25 kJ/mol), and −7.17 kcal/mol (−29.99 kJ/mol) respectively, were simulated with GROningen MAchine for Chemical Simulations (GROMACS) to measure the molecular interactions between Mpro and inhibitors in detail. Our MD simulation results show that α-gurjunene has the strongest binding energy of −20.37 kcal/mol (−85.21 kJ/mol), followed by aromadendrene with −18.99 kcal/mol (−79.45 kJ/mol), and finally allo-aromadendrene with −17.91 kcal/mol (−74.95 kJ/mol). The findings indicate that eucalyptus may be used to inhibit the Mpro enzyme as a drug candidate. This is the first computational analysis that gives an insight into the potential role of structural flexibility during interactions with eucalyptus compounds. It also sheds light on the structural design of new herbal medicinal products against Mpro.

In-silico screening of plant-derived antivirals against main protease, 3CLpro and endoribonuclease, NSP15 proteins of SARS-CoV-2

Novel Coronavirus or SARS-CoV-2 outbreak has developed a pandemic condition all over the world. The virus is highly infectious and spreads by human to human local transmission mode. Till date, there is no vaccination or drugs been approved for the treatment by the World Health Organisation. Henceforth, the discovery of the potential drugs is an urgent and utmost requirement for the medical fraternity. Since, the side effects of plant-derived compounds will be lower compared to synthetic/chemical drugs. The Main protease (3CL^pro or NSP5) and endoribonuclease (NSP15) proteins are necessity for viral replication and its survival in the host cell. In the present study, in-silico approach of drug development was used to search for potential antiviral plant-derived compounds as inhibitors against SARS-CoV-2 replication proteins. Eight plant-derived compounds of which the antiviral activity was known and available, and two reported drugs against SARS-CoV-2 selected for the molecular docking analysis. The docking results suggested that bisdemethoxycurcumin, demethoxycurcumin, scutellarin, quercetin and myricetin showed least binding energy, i.e., greater than −6.5 Kcal/mol against 3CL^pro and endoribonuclease of SARS-CoV-2. Further studies of ADME-Tox and bioavailability of drugs were also performed that exhibited efficient parameters of drug likeness. Molecular dynamics simulation calculations were performed for the most negative binding affinity of the compound to evaluate the dynamic behavior,and stability of protein-ligand complex. Our findings suggest that these compounds could be potential inhibitors of SARS‐CoV-2 main protease and endoribonuclease. However, further in-vitro and pre-clinical experiments would validate the potential inhibitors of SARS‐CoV‐2 proteins.

Homology modeling and molecular dynamics based insights into Chalcone synthase and Chalcone isomerase in Phyllanthus emblica L

Chalcone synthase (CHS) and chalcone isomerase (CHI) plays a major role in the biosynthesis of flavonoid in plants. In this study, we made extensive bioinformatics analysis to gain functional and structural insight into PeCHS and PeCHI proteins. The phylogenetic distribution of PeCHS and PeCHI genes encoding proteins demonstrated the close evolutionary relationship with different CHS and CHI proteins of other dicot plants. MicroRNA target analysis showed miR169n and 3p miR5053 targeting PeCHS gene while miR169c-3p and miR4248 are targeting PeCHI gene, respectively. Three-dimensional structural models of PeCHS and PeCHI proteins were elucidated by homology modeling with Ramachandran plots showing the excellent geometry of the proteins structure. Molecular docking revealed that cinnamoyl-coa and naringenin chalcone substrates are strongly bound to PeCHS and PeCHI proteins, respectively. Finally, molecular dynamics (MD) simulation for 30 ns, further yielded stability checks of ligands in the binding pocket and behavior of protein complexes. Thus MD simulation and interaction fraction analysis showed the stable conformation of PeCHS and PeCHI proteins with their respective substrates during theee simulation. Our study provides first-hand structural prospective of PeCHS and PeCHI proteins towards understanding the mechanism of flavonoid biosynthetic pathway in P. emblica.

Molecular Dynamics Studies on COX-2 Protein-tyrosine Analogue Complex and Ligand-based Computational Analysis of Halo-substituted Tyrosine Analogues

Background:

The quest for new drug entities and novel structural fragments with applications in therapeutic areas is always at the core of medicinal chemistry.

Methods:

As part of our efforts to develop novel selective cyclooxygenase-2 (COX-2) inhibitors containing tyrosine scaffold. The objective of this study was to identify potent COX-2 inhibitors by dynamic simulation, pharmacophore and 3D-QSAR methodologies. Dynamics simulation was performed for COX-2/tyrosine derivatives complex to characterise structure validation and binding stability. Certainly, Arg120 and Tyr355 residue of COX-2 protein formed a constant interaction with tyrosine inhibitor throughout the dynamic simulation phase. A four-point pharmacophore with one hydrogen bond acceptor, two hydrophobic and one aromatic ring was developed using the HypoGen algorithm. The generated, statistically significant pharmacophore model, Hypo 1 with a correlation coefficient of r2, 0.941, root mean square deviation, 1.15 and total cost value of 96.85.

Results:

The QSAR results exhibited good internal (r2, 0.992) and external predictions (r2pred, 0.814). The results of this study concluded the COX-2 docked complex was stable and interactive like experimental protein structure. Also, it offered vital chemical features with geometric constraints responsible for the inhibition of the selective COX-2 enzyme by tyrosine derivatives.

Conclusion:

In principle, this work offers significant structural understandings to design and develop novel COX-2 inhibitors.

Aqueous solution interactions with sex hormone-binding globulin and estradiol: a theoretical investigation

Sex hormone-binding globulin (SHBG) is a binding protein that regulates the availability of steroid hormones in the plasma. Although best known as a steroid carrier, recent studies have associated SHBG in modulating behavioral aspects related to sexual receptivity. Among steroids, estradiol (17β-estradiol, oestradiol or E2), documented as the most active endogenous female hormone, exerts important physiological roles in both reproductive and non-reproductive functions. In this framework, we employed molecular dynamics (MD) and docking techniques for quantifying the interaction energy between a complex aqueous solution, composed by different salts, SHBG and E2. As glucose concentration resembles measured levels in diabetes, special emphasis was devoted to analyzing the interaction energy between this carbohydrate, SHBG and E2 molecules. The calculations revealed remarkable interaction energy between glucose and SHBG surface. Surprisingly, a movement of solute components toward SHBG was observed, yielding clusters surrounding the protein. The high energy and short distance between glucose and SHBG suggests a possible scenario in favor of a detainment state between the sugar and the protein. In this context, we found that glucose clustering does not insert modification on binding site area nor over binding energy SHBG-E2 complex, in spite of protein superficial area increment. The calculations also point to a more pronounced interaction between E2 and glucose, considering the hormone immersed in the solution. In summary, our findings contribute to a better comprehension of both SHBG and E2 interplay with aqueous solution components.

Ursolic acid and carvacrol may be potential inhibitors of dormancy protein small heat shock protein16.3 of Mycobacterium tuberculosis

Small heat shock protein16.3 (sHSP16.3) is a crucial protein for survival of Mycobacterium tuberculosis (MTB) in its host. Besides, this protein acts as a molecular chaperone during stress and is indispensable for MTB's growth, virulence and cell-wall thickening. sHSP16.3 is also a promising candidate for vaccine, serodiagnosis and drug design as well. In the present study, we have targeted sHSP16.3 with two phytochemicals, namely ursolic acid and carvacrol using in silico approach. Molecular docking analysis showed that both phytochemicals (ursolic acid and carvacrol) have docked with sHSP16.3 and shown tendency to inhibit the function of this vital protein of MTB. In addition, both compounds have exhibited strong compatibility with sHSP16.3 during whole 60 ns duration of molecular dynamics simulation. Further, the molecular mechanic/generalized Born/Poisson-Boltzmann surface area (MM/G/P/BSA) free energies were calculated which showed that both phytocompounds have stable and favourable binding energies causing strong binding with binding site of sHSP16.3. Taking together, the data of present study suggest that both phytocompounds may be potential inhibitor of sHSP16.3 of MTB and a best alternative to standard anti-tuberculosis drugs.

Identification, expression analysis, and molecular modeling of Iron-deficiency-specific clone 3 (Ids3)-like gene in hexaploid wheat

Graminaceous plants secrete hydroxylated phytosiderophores encoded by the genes iron-deficiency-specific clone 2 (Ids2) and iron-deficiency-specific clone 3 (Ids3). An effort was made to identify a putative ortholog of Hodeum vulgare Ids3 gene in hexaploid wheat. The protein structure of TaIDS3 was modeled using homology modeling and structural behavior of modeled structure was analyzed at 20 ns. The simulation trajectory using molecular dynamics simulation suggested the model to be stable with no large fluctuations in residues and local domain level RMSF values (< 2.4 Å). In addition, the ProFunc results also predict the functional similarity between the proteins of HvIDS3 and its wheat ortholog (TaIDS3). The TaIds3 gene was assigned to the telomeric region of chromosome arm 7AS which supports the results obtained through bioinformatics analysis. The relative expression analysis of TaIds3 indicated that the detectable expression of TaIds3 is induced after 5th day of Fe starvation and increases gradually up to 15th day, and thereafter, it decreases until 35th day of Fe-starvation. This reflects that Fe deficiency directly regulates the induction of TaIds3 in the roots of hexaploid wheat. The identification of HvIds3-like gene in wheat has opened up new opportunities to enhance the nutrient quality in wheat through biofortification program.