Discovery of Rift Valley fever virus natural pan-inhibitors by targeting its multiple key proteins through computational approaches

Targeting XGHPRT enzyme to manage Helicobacter pylori induced gastric cancer: A multi-pronged machine learning, artificial intelligence and biophysics-based study

Helicobacter pylori infects the stomach mucosa of over half of the global population and can lead to gastric cancer. This pathogen has demonstrated resistance to many frequently prescribed antibiotics, thereby underscoring the pressing need to identify novel therapeutic targets. The inhibition or disruption of nucleic acid biosynthesis constitutes a promising avenue for either restraining or eradicating bacterial proliferation. The synthesis of RNA and DNA precursors (6-oxopurine nucleoside monophosphates) is catalyzed by the XGHPRT enzyme. In this study, using machine learning, artificial intelligence and biophysics-based software, CHEMBRIDGE-10000196, CHEMBRIDGE-10000295, and CHEMBRIDGE-10000955 were predicted as promising binders to the XGHPRT with a binding score of -14.20, -13.64, and -12.08 kcal/mol, respectively, compared to a control guanosine-5'-monophosphate exhibiting a docking score of -10.52 kcal/mol. These agents formed strong interactions with Met33, Arg34, Ala57, Asp92, Ser93, and Gly94 at short distance. The docked complexes of the lead compounds exhibited stable dynamics during the simulation time with no global changes noticed. The docked complexes demonstrate a significantly stable MM-GBSA and MM-PBSA net binding energy of -60.1 and -61.18 kcal/mol for the CHEMBRIDGE-10000196 complex. The MM-GBSA net energy value of the CHEMBRIDGE-10000295 complex and the CHEMBRIDGE-10000955 complex is -71.17 and -65.29 kcal/mol, respectively. The CHEMBRIDGE-10000295 and CHEMBRIDGE-10000955 complexes displayed a net value of -71.91 and -63.49 kcal/mol, respectively, as per the MM-PBSA. The major driving intermolecular interactions for the docked complexes were found to be the electrostatic and van der Waals. The three filtered molecules hold potential for experimental evaluation of their potency against the XGHPRT enzyme.

Cloning and phylogenetic analysis of N protein gene from Rift Valley Fever Virus (RVFV)

Rift Valley Fever (RVF) is a mosquito-borne viral zoonosis caused by RVFV in humans and livestock. Currently, there are no approved vaccines or antiviral therapies available. Additionally, in Saudi Arabia, there is a lack of a routine screening system to monitor RVFV in humans and animals which hinders to design and develop the preventive measures as well as the prediction of future outbreaks and the potential re-emergence of RVFV. Hence, we have performed the cloning, sequencing, and phylogenetic analysis, of nucleocapsid (N) protein gene. The sequence analysis showed high similarities with RVFV isolates reported from humans and animals. The highest similarity (99.5%) was observed with an isolate from Saudi Arabia (KU978775-Human) followed by 99.1% with four RVFV isolates (Human and Bovine) from other locations. A total of 51 nucleotides and 31 amino acid variations were observed throughout the N protein gene sequences. The phylogenetic relationship formed closed clusters with other isolates collected from Saudi Arabia. Thus, we report of the cloning, sequencing, and phylogenetic analysis of the RVFV-N protein gene from Saudi Arabia.

A hierarchical approach towards identification of novel inhibitors against L, D-transpeptidase YcbB as an anti-bacterial therapeutic target

The bacterial cell wall, being a vital component for cell viability, is regarded as a promising drug target. The L, D-Transpeptidase YcbB enzyme has been implicated for a significant role in cell wall polymers cross linking during typhoid toxin release, β-lactam resistance and outer membrane defect rescue. These observations have been recorded in different bacterial pathogens such as Salmonella Typhimurium, Citrobacter rodentium, and Salmonella typhi. In this work, we have shown structure based virtual screening of diverse natural and synthetic drug libraries against the enzyme and revealed three compounds as LAS_32135590, LAS_34036730 and LAS-51380924. These compounds showed highly stable energies and the findings are very competitive with the control molecule ((1RG or (4 R,5S)-3-({(3S,5S)-5-[(3-carboxyphenyl)carbamoyl]pyrrolidin-3-yl}sulfanyl)-5-[(1S,2R)-1-formyl-2-hydroxypropyl]-4-methyl-4,5-dihydro-1H-pyrrole-2-carboxylic acid or ertapenem)) used. Compared to control (which has binding energy score of -11.63 kcal/mol), the compounds showed better binding energy. The binding energy score of LAS_32135590, LAS_34036730 and LAS-51380924 is -12.63 kcal/mol, -12.22 kcal/mol and -12.10 kcal/mol, respectively. Further, the docked snapshot of the lead compounds and control were investigated for stability under time dependent dynamics environment. All the three leads complex and control system showed significant equilibrium (mean RMSD < 3 Å) both in term of intermolecular docked conformation and binding interactions network. Further validation on the complex's stability was acquired from the end-state MMPB/GBSA analysis that observed greater contribution from van der Waals forces and electrostatic energy while less contribution was noticed from solvation part. The compounds were also showed good drug-likeness and are non-toxic and non-mutagenic. In short, the compounds can be used in experimental testing's and might be subjected to structure modification to get better results.Communicated by Ramaswamy H. Sarma.

Network pharmacology and molecular dynamic simulation integrated strategy for the screening of active components and mechanisms of phytochemicals from Datura innoxia on Alzheimer and cognitive decline

Alzheimer's disease (AD) ranks as the most prevalent neurodegenerative disorder with dementia and it accounts for more than 70% of all cases. Despite extensive reporting on the experimental investigation of Datura innoxia (DI) and its phytochemical components in the treatment of AD, the urgent need for elucidation of the principle of multi-mechanism and multi-level treatment of AD remains. In this research, molecular docking and network pharmacology were used to evaluate active compounds and molecular targets of DI for the treatment of AD. The phytochemical compounds of DI were obtained from the Indian Medicinal Plants, Phytochemistry, and Therapeutics (IMPPAT) as well as the Traditional Chinese Medicine System Pharmacology (TCMSP) databases. The screening includes the 28 most abundant components of DI and the Swiss Target Prediction database was used to predict targets of these compounds. The GeneCards database was used to collect AD-related genes. Both DI and AD targets were imported into a Venn diagram, and the 28 overlapped genes were identified as potential DI anti-AD targets. The results showed that Dinoxin B, Meteloidine, Scopoline, and Tropic acid had no effect on AD-related genes. Furthermore, the GO enrichment analysis indicates that DI influences molecular functions and biological processes such as learning or memory and modulation of chemical synaptic transmission as well as the membrane raft and membrane microdomain. The KEGG pathway analysis revealed that the key pathways implicated in DI's anti-AD actions include serotonergic synapse, IL-17 signaling pathway, and AGE-RAGE signaling pathway in diabetic complications. Based on the STRING and Cytoscape network-analysis platforms, the top ten anti-AD core targets include APP, CASP3, IL6, BACE1, IL1B, ACE, PSEN1, GAPDH, GSK3B and ACHE. The molecular docking and molecular dynamic simulation of the top two molecules against the top three target proteins confirmed the strong binding affinity and stability at the docked site. Overall, our findings pave the path for further research into the development and optimization of potential anti-AD agents from DI.Communicated by Ramaswamy H. Sarma.

Identification of novel inhibitors against VP40 protein of Marburg virus by integrating molecular modeling and dynamics approaches

Marburg virus (MV) is a highly etiological agent of haemorrhagic fever in humans and has spread across the world. Its outbreaks caused a 23-90% human death rate. However, there are currently no authorized preventive or curative measures yet. VP40 is the MV matrix protein, which builds protein shell underneath the viral envelope and confers hallmark filamentous. VP40 alone is able to induce assembly and budding of filamentous virus-like particles (VLPs), which resemble authentic virions. As a result, this research is credited with clarifying the function of VP40 and leading to the discovery of new therapeutic targets effective in combating MV disease (MVD). Virtual screening, molecular docking and molecular dynamics (MD) simulation were used to find the putative active chemicals based on a 3D pharmacophore model of the protein's active site cavity. Initially, andrographidine-C, a potent inhibitor was selected for the development of the pharmacophore model. Later, a library of 30,000 compounds along with the andrographidine-C was docked against VP40 protein. Three best hits including avanafil, diuvaretin and macrourone were subjected to further MD simulation analysis, as these compounds had better binding affinities as compared to andrographidine-C. Furthermore, throughout the 100 ns simulations, the back bone of VP40 protein in presence of avanafil, diuvaretin and macrourone remained stable which was further validated by MM-PBSA analysis. Additionally, all of these compounds depict maximum drug-like properties. The predicted drugs based on the ligand, avanafil, diuvaretin and macrourone could be exploited and developed as an alternative or complementary therapy for the treatment of MVD.Communicated by Ramaswamy H. Sarma.

Network pharmacology based virtual screening of Flavonoids from Dodonea angustifolia and the molecular mechanism against inflammation

Inflammation is a nonspecific immune response against injury caused by a harmful agent that strives to restore tissue function and homeostasis. Dodonaea angustifolia L.f. (Sapindaceae) is a medium-sized shrub used to treat a variety of diseases in traditional medicine. In the current study, integrated network-pharmacology and molecular docking approaches were used to identify the active constituents, their possible targets, signaling pathways, and anti-inflammatory effects of flavonoids from D.angustifolia. D. angustifolia active ingredients were acquired from the Indian Medicinal Plants, Phytochemistry and Therapeutics (IMPPAT), and Traditional Chinese Medicine System Pharmacology (TCMSP) databases. The screening included the ten most prevalent D. angustifolia components, and the SwissTargetPrediction database was utilized to anticipate the targets of these compounds. Anti-inflammatory genes were found using the GeneCards database. The 175 overlapping genes were discovered as prospective D. angustifolia anti-inflammatory targets. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that the overlapped targets were closely related to the major pathogenic processes linked to inflammation, such as response to organonitrogen compound, protein kinase activity, phosphotransferase activity, pI3k-Akt signaling pathway, metabolic pathways, and chemical carcinogenesis. Compound-target-pathway, and protein-protein interaction networks revealed 6-Methoxykaempferol and 5-Hydroxy-7,8 dimethoxyflavone as key compounds, and AKT1, VEGFA, and EGFR as key targets. Furthermore, molecular docking followed by molecular dynamic (MD) simulation of D. angustifolia active ingredients with core proteins fully complemented the binding affinity of these compounds and indicated stable complexes at the docked site. These findings reveal D. angustifolia 's multi-target, multi-compound, and multi-pathway strategies against inflammation. Our study paved the way for further research into the mechanism for developing D. angustifolia -based natural products as alternative therapies for inflammation.

Computational prediction of phytochemical inhibitors against the cap-binding domain of Rift Valley fever virus

Rift Valley fever is a zoonotic disease that can spread through livestock and mosquitoes, and its symptoms include retinitis, photophobia, hemorrhagic fever and neurological effects. The World Health Organization has identified Rift Valley fever as one of the viral infections that has potential to cause a future epidemic. Hence, efforts are urgently needed toward development of therapeutics and vaccine against this infectious disease. Notably, the causative virus namely, the Rift Valley fever virus (RVFV), utilizes the cap-snatching mechanism for viral transcription, rendering its cap-binding domain (CBD) as an effective antiviral target. To date, there are no published studies towards identification of potential small molecule inhibitors for the CBD of RVFV. Here, we employ a virtual screening workflow comprising of molecular docking and molecular dynamics (MD) simulation, to identify 5 potential phytochemical inhibitors of the CBD of RVFV. These 5 phytochemical inhibitors can be sourced from Indian medicinal plants, Ferula assa-foetida, Glycyrrhiza glabra and Leucas cephalotes, used in traditional medicine. In sum, the 5 phytochemical inhibitors of the CBD of RVFV identified by this purely computational study are promising drug lead molecules which can be considered for detailed experimental validation against RVFV infection.

The molecular interplay of known phytochemicals as Culex pipiens and Rift Valley fever virus inhibitors through molecular docking

Infectious diseases transmitted by vectors have claimed millions of lives. The mosquito Culex pipiens is a main vector species of Rift Valley Fever virus (RVFV) transmission. RVFV is an arbovirus that infects both people and animals. No effective vaccine or drugs are available for RVFV. Therefore, it is vital to find effective therapies for this viral infection. Because of their critical roles in transmission and infection, acetylcholinesterase 1 (AChE1) of Cx. Pipiens and RVFV glycoproteins, and nucleocapsid proteins are appealing protein targets. To understand intermolecular interactions, computational screening was carried out using molecular docking. More than 50 compounds were tested against different target proteins in the current study. Anabsinthin (-11.1 kcal/mol), zapoterin (-9.4 kcal/mol), porrigenin A (-9.4 kcal/mol), and 3-Acetyl-11-keto-beta-boswellic acid (AKBA) (-9.4 kcal/mol) were the top hit compounds for Cx. Pipiens. Similarly, the top hit compounds for RVFV were zapoterin, porrigenin A, anabsinthin, and yamogenin. The toxicity of Rofficerone is predicted as fatal (Class II), whereas Yamogenin is safe (Class VI). Further investigations are needed to validate the selected promising candidates against Cx. pipiens and RVFV infection using in-vitro and in-vivo methods.

Identification of novel inhibitors against hantaviruses through 2D fingerprinting and molecular modeling approaches

With the immensely growing outbreaks of hantavirus with still no effective treatment available, there is an urgent need of exploring new computational approaches which will target potential virulent proteins that will eventually reduce its growth. In this study, an envelope glycoprotein, Gn, was targeted. The glycoproteins, which are the sole targets of neutralizing antibodies, drive virus entry via receptor-mediated endocytosis and endosomal membrane fusion. Inhibitors are herein proposed to negate its action mechanism. On the basis of the scaffolds of favipiravir, a FDA compound already used against hantavirus, a library was designed using a 2D fingerprinting approach. Upon molecular docking analysis, the top four docked compounds-(1) favipiravir (-4.5 kcal/mol), (2) N-hydroxy-3-oxo-3, 4-dihydropyrazine-2-carboxamide (-4.7 kcal/mol), (3) N, 5, 6-trimethyl-2-oxo-1H-pyrazine-3-carboxamide (-4.5 kcal/mol), and (4) 3-propyl-1H-pyrazin-2-one (-3.8)-were prioritized on the basis of the lowest binding energies score. Through molecular docking, the best-categorized compound was subjected to molecular dynamics simulation for a 100-ns time span. Molecular dynamics sheds light on each ligand behavior within the active site. Among the four complexes, only favipiravir and 6320122 compound were found to be stable inside the pocket. This is due to the presence of common rings, pyrazine and carboxamide ring, which make a significant interaction with active key residues Furthermore, the MMPB/GBSA binding free energy analysis calculated for all complexes supported the dynamics results by calculating the most stable values for favipiravir complex (-9.9933 and -8.6951 kcal/mol) and for 6320122 compound complex (-13.8675 and -9.3439 kcal/mol), which demonstrated that the selected compounds have a proper binding affinity with the targeted proteins. The hydrogen bond analysis similarly revealed a strong bonding interaction. The results yielded a strong interaction between the enzyme and the inhibitor throughout the simulation; thus, the inhibitor has the potential to become a lead compound and could be subjected to experimental evaluation to unveil their blockage ability.

Discovery of potential phytochemicals as inhibitors of TcdB, a major virulence factors of Clostridioides difficile

Clostridioides difficile is a gram-positive bacterium which is associated with different gastrointestinal related infections, and the numbers of cases related to it are continuously increasing in the past few years. Owing to high prevalence and development of resistance towards available antibiotics, it is required to develop new therapeutics to combat C. difficile infection. The current study was aimed to identify novel phytochemicals that could bind and inhibits the TcdB, an exotoxin which is required for the pathogenesis of bacteria, and hence can be considered as the future drug candidates against C. difficile. ∼2500 therapeutically important phyto-compounds were docked against the active sites of TcdB protein by using AutoDock-Vina software. The interactions between the ligands and the binding site of the top five docked complexes, based on the docking scores, were further elucidated by Molecular Dynamics Simulations of 500 ns, Molecular Mechanics Energies combined with the Poisson-Boltzmann and Surface Area (MMPBSA) or Generalized Born and Surface Area (MMGBSA), and WaterSwap Analysis. Findings of molecular docking suggested that natural compounds A183, A704, A1528, A2083, and A2129 with distinct chemical scaffolds are best docked in the binding site of TcdB and their bonding remained stable throughout the simulation studies of 500 ns. Compounds A2129 and A704 can be considered as prospective drug candidates against Clostridioides difficile, however, further wet lab experiments are needed to confirm our study.Communicated by Ramaswamy H. Sarma.

An In-Silico Investigation to Design a Multi-Epitopes Vaccine against Multi-Drug Resistant Hafnia alvei

Antimicrobial resistance has become a significant health issue because of the misuse of antibiotics in our daily lives, resulting in high rates of morbidity and mortality. Hafnia alvei is a rod-shaped, Gram-negative and facultative anaerobic bacteria. The medical community has emphasized H. alvei’s possible association with gastroenteritis. As of now, there is no licensed vaccine for H. alvei, and as such, computer aided vaccine design approaches could be an ideal approach to highlight the potential vaccine epitopes against this bacteria. By using bacterial pan-genome analysis (BPGA), we were able to study the entire proteomes of H. alvei with the aim of developing a vaccine. Based on the analysis, 20,370 proteins were identified as core proteins, which were further used in identifying potential vaccine targets based on several vaccine candidacy parameters. The prioritized vaccine targets against the bacteria are; type 1 fimbrial protein, flagellar hook length control protein (FliK), flagellar hook associated protein (FlgK), curli production assembly/transport protein (CsgF), fimbria/pilus outer membrane usher protein, fimbria/pilus outer membrane usher protein, molecular chaperone, flagellar filament capping protein (FliD), TonB-dependent hemoglobin /transferrin/lactoferrin family receptor, Porin (OmpA), flagellar basal body rod protein (FlgF) and flagellar hook-basal body complex protein (FliE). During the epitope prediction phase, different antigenic, immunogenic, non-Allergenic, and non-Toxic epitopes were predicted for the above-mentioned proteins. The selected epitopes were combined to generate a multi-epitope vaccine construct and a cholera toxin B subunit (adjuvant) was added to enhance the vaccine’s antigenicity. Downward analyses of vaccines were performed using a vaccine three-dimensional model. Docking studies have confirmed that the vaccine strongly binds with MHC-I, MHC-II, and TLR-4 immune cell receptors. Additionally, molecular dynamics simulations confirmed that the vaccine epitopes were exposed to nature and to the host immune system and interpreted strong intermolecular binding between the vaccine and receptors. Based on the results of the study, the model vaccine construct seems to have the capacity to produce protective immune responses in the host, making it an attractive candidate for further in vitro and in vivo studies.