Combining in silico and in vitro approaches to identification of potent inhibitor against phospholipase A2 (PLA2)

Temperature effect in the inhibition of PLA2 activity of Bothrops brazili venom by Rosmarinic and Chlorogenic acids, experimental and computational approaches

Myotoxicity caused by snakebite envenoming emerges as one of the main problems of ophidic accidents as it is not well neutralized by the current serum therapy. A promising alternative is to search for efficient small molecule inhibitors that can act against multiple venom components. Phospholipase A2 (PLA2) is frequently found in snake venom and is usually associated with myotoxicity. Thus it represents an excellent target for the search of new treatments. This work reports the effect of temperature in the inhibition of catalytic properties of PLA2 from Bothrops brazili venom by Rosmarinic (RSM) and Chlorogenic (CHL) acids through experimental and computational approaches. Three temperatures were evaluated (25, 37 and 50 °C). In the experimental section, enzymatic assays showed that RSM is a better inhibitor in all three temperatures. At 50 °C, the inhibition efficiency decayed significantly for both acids. Docking studies revealed that both ligands bind to the hydrophobic channel of the protein dimer where the phospholipid binds in the catalytic process, interacting with several functional residues. In this context, RSM presents better interaction energies due to stronger interactions with chain B of the dimer. Molecular dynamics simulations showed that RSM can establish selective interactions with ARG112B of PLA2, which is located next to residues of the putative Membrane Disruption Site in PLA2-like structures. The affinity of RSM and CHL acids towards PLA2 is mainly driven by electrostatic interactions, especially salt bridge interactions established with residues ARG33B (for CHL) and ARG112B (RSM) and hydrogen bonds with residue ASP89A. The inability of CHL to establish a stable interaction with ARG112B was identified as the reason for its lower inhibition efficiency compared to RSM at the three temperatures. Furthermore, extensive structural analysis was performed to explain the lower inhibition efficiency at 50 °C for both ligands. The analysis performed in this work provides important information for the future design of new inhibitors.Communicated by Ramaswamy H. Sarma.

Potential inhibitors of VEGFR1, VEGFR2, and VEGFR3 developed through Deep Learning for the treatment of Cervical Cancer

Cervical cancer stands as a prevalent gynaecologic malignancy affecting women globally, often linked to persistent human papillomavirus infection. Biomarkers associated with cervical cancer, including VEGF-A, VEGF-B, VEGF-C, VEGF-D, and VEGF-E, show upregulation and are linked to angiogenesis and lymphangiogenesis. This research aims to employ in-silico methods to target tyrosine kinase receptor proteins-VEGFR-1, VEGFR-2, and VEGFR-3, and identify novel inhibitors for Vascular Endothelial Growth Factors receptors (VEGFRs). A comprehensive literary study was conducted which identified 26 established inhibitors for VEGFR-1, VEGFR-2, and VEGFR-3 receptor proteins. Compounds with high-affinity scores, including PubChem ID-25102847, 369976, and 208908 were chosen from pre-existing compounds for creating Deep Learning-based models. RD-Kit, a Deep learning algorithm, was used to generate 43 million compounds for VEGFR-1, VEGFR-2, and VEGFR-3 targets. Molecular docking studies were conducted on the top 10 molecules for each target to validate the receptor-ligand binding affinity. The results of Molecular Docking indicated that PubChem IDs-71465,645 and 11152946 exhibited strong affinity, designating them as the most efficient molecules. To further investigate their potential, a Molecular Dynamics Simulation was performed to assess conformational stability, and a pharmacophore analysis was also conducted for indoctrinating interactions.

Toxicological study on ibuprofen and selenium in freshwater mussel Lamellidens marginalis and exploring the microbial cytochrome through modelling and quantum mechanics approaches for its toxicity degradation in contaminated environment

Toxicological stress in aquatic organisms is caused by the discharge of hundreds of toxic pollutants and contaminants among which the current study concentrates on the toxic effect of non-steroidal anti-inflammatory drug ibuprofen (IBF) and the trace element selenium (Se). In this study, IBF and Se toxicity on freshwater mussel Lamellidens marginalis was studied for 14 days, and in silico predictions for their degradation were made using Molecular modelling and Quantum Mechanical approaches. The degrading propensity of cytochrome c oxidase proteins from Trametes verticillatus and Thauera selenatis (Turkey tail fungi and Gram-negative bacteria) is examined into atom level. The results of molecular modelling study indicate that ionic interactions occur in the T. selenatis-HEME bound complex by Se interacting directly with HEME, and in the T. versicolor-HEME bound complex by IBF bound to a nearby region of HEME. Experimental and theoretical findings suggest that, the toxicological effects of Se and IBF pollution can be reduced by bioremediation with special emphasis on T. versicolor, and T. selenatis, which can effectively interact with Se and IBF present in the environment and degrade them. Besides, this is the first time in freshwater mussel L. marginalis that ibuprofen and selenium toxicity have been studied utilizing both experimental and computational methodologies for their bioremediation study.

Current perspectives and trend of computer-aided drug design: a review and bibliometric analysis

AIM

Computer-aided drug design (CADD) is a drug design technique for computing ligand‒receptor interactions and is involved in various stages of drug development. To better grasp the frontiers and hotspots of CADD, we conducted a review analysis through bibliometrics.

METHODS

A systematic review of studies published between 2000 and July 20, 2023 was conducted following the PRISMA guidelines. Literature on CADD was selected from the Web of Science Core Collection. General information, publications, output trends, countries/regions, institutions, journals, keywords, and influential authors were visually analysed using software such as Excel, VOSviewer, RStudio, and CiteSpace.

RESULTS

A total of 2,031 publications were included. These publications primarily originated from 99 countries or regions, led by the U.S. and China. Among the contributors, MacKerell AD had the highest number of articles and greatest influence. The Journal of Medicinal Chemistry was the most cited journal, whereas the Journal of Chemical Information and Modeling had the highest number of publications.

CONCLUSIONS

Influential authors in the field were identified. Current research shows active collaboration between countries, institutions, and companies. CADD technologies such as homology modelling, pharmacophore modelling, quantitative conformational relationships, molecular docking, molecular dynamics simulation, binding free energy prediction, and high-throughput virtual screening can effectively improve the efficiency of new drug discovery. Artificial intelligence-assisted drug design and screening based on CADD represent key topics direction for future development. Furthermore, this paper will be helpful for better understanding the frontiers and hotspots of CADD.

Integrating artificial intelligence into the modernization of traditional Chinese medicine industry: a review

Traditional Chinese medicine (TCM) is the practical experience and summary of the Chinese nation for thousands of years. It shows great potential in treating various chronic diseases, complex diseases and major infectious diseases, and has gradually attracted the attention of people all over the world. However, due to the complexity of prescription and action mechanism of TCM, the development of TCM industry is still in a relatively conservative stage. With the rise of artificial intelligence technology in various fields, many scholars began to apply artificial intelligence technology to traditional Chinese medicine industry and made remarkable progress. This paper comprehensively summarizes the important role of artificial intelligence in the development of traditional Chinese medicine industry from various aspects, including new drug discovery, data mining, quality standardization and industry technology of traditional Chinese medicine. The limitations of artificial intelligence in these applications are also emphasized, including the lack of pharmacological research, database quality problems and the challenges brought by human-computer interaction. Nevertheless, the development of artificial intelligence has brought new opportunities and innovations to the modernization of traditional Chinese medicine. Integrating artificial intelligence technology into the comprehensive application of Chinese medicine industry is expected to overcome the major problems faced by traditional Chinese medicine industry and further promote the modernization of the whole traditional Chinese medicine industry.

Exploring the role of microbial proteins in controlling environmental pollutants based on molecular simulation

Molecular simulation has been widely used to study microbial proteins' structural composition and dynamic properties, such as volatility, flexibility, and stability at the microscopic scale. Herein, this review describes the key elements of molecular docking and molecular dynamics (MD) simulations in molecular simulation; reviews the techniques combined with molecular simulation, such as crystallography, spectroscopy, molecular biology, and machine learning, to validate simulation results and bridge information gaps in the structure, microenvironmental changes, expression mechanisms, and intensity quantification; illustrates the application of molecular simulation, in characterizing the molecular mechanisms of interaction of microbial proteins with four different types of contaminants, namely heavy metals (HMs), pesticides, dyes and emerging contaminants (ECs). Finally, the review outlines the important role of molecular simulations in the study of microbial proteins for controlling environmental contamination and provides ideas for the application of molecular simulation in screening microbial proteins and incorporating targeted mutagenesis to obtain more effective contaminant control proteins.

A novel peptide able to reduce PLA2 activity and modulate inflammatory cytokine production

Phospholipases A2 (PLA2s) are associated with inflammatory response, performing a complex process involving, specially, cytokines. The excess of pro-inflammatory cytokines induces a chronic inflammatory response and can cause several disorders in the body. Therefore, the inhibition or regulation of cytokines' signaling pathways is a target for new treatment development strategies. Thus, this study aimed to select PLA2 inhibitor mimetic peptides through phage display technology with anti-inflammatory activity. Specific mimetic peptides were selected using BpPLA2-TXI, a PLA2 isolated from Bothrops pauloensis, as a target, and γCdcPL, a PLA2 inhibitor isolated from Crotalus durissus collilineatus, which was used as a competitor during the elution step. We selected the peptide C2PD, which seems to play a pivotal role in the modulation of IL-6, IL-1β, and IL-10 cytokines in inflammatory cells. The C2PD showed a significant reduction in PLA2 activity. Furthermore, the synthetic peptide was tested in PBMC and showed a significant down-modulation of IL-6 and IL-1β release, whereas IL-10 responses were up-regulated. Our findings suggest that this novel peptide may be a potential therapeutic candidate for the treatment of inflammatory diseases, mainly due to its anti-inflammatory properties and absence of cytotoxicity.

β-Sitosterol could serve as a dual inhibitor of Trypanosoma congolense sialidase and phospholipase A2: in vitro kinetic analyses and molecular dynamic simulations

The involvement of Trypanosoma congolense sialidase alongside phospholipase A2 has been widely accepted as the major contributing factor to anemia during African animal trypanosomiasis. The enzymes aid the parasite in scavenging sialic acid and fatty acids necessary for survival in the infected host, but there are no specific drug candidates against the two enzymes. This study investigated the inhibitory effects of β-sitosterol on the partially purified T. congolense sialidase and phospholipase A2. Purification of the enzymes using DEAE cellulose column led to fractions with highest specific activities of 8016.41 and 39.26 µmol/min/mg for sialidase and phospholipase A2, respectively. Inhibition kinetics studies showed that β-sitosterol is non-competitive and an uncompetitive inhibitor of sialidase and phospholipase A2 with inhibition binding constants of 0.368 and 0.549 µM, respectively. Molecular docking of the compound revealed binding energies of - 8.0 and - 8.6 kcal/mol against the sialidase and phospholipase A2, respectively. Furthermore, 100 ns molecular dynamics simulation using GROMACS revealed stable interaction of β-sitosterol with both enzymes. Hydrogen bond interactions between the ligand and Glu284 and Leu102 residues of the sialidase and phospholipase A2, respectively, were found to be the major stabilizing forces. In conclusion, β-sitosterol could serve as a dual inhibitor of T. congolense sialidase and phospholipase A2; hence, the compound could be exploited further in the search for newer trypanocides.

In silico and In vitro Analysis of Nigella sativa Bioactives Against Chorismate Synthase of Listeria monocytogenes: a Target Protein for Biofilm Inhibition

Listeria monocytogenes have the ability to form biofilms, which aid in the contamination of food and the evasion of antimicrobials. Consumption of L. monocytogenes laden food can promote mild to severe infection in humans and cause serious health issues. Therefore, biofilm development by L. monocytogenes is considered to be a major concern for both healthcare and food safety. This study attempted to target chorismate synthase, an essential protein predicted to be involved in the biofilm pathway. Nigella sativa is renowned for its applications in folk medicine; hence, bioactive ingredients reported were used for molecular docking studies. In the absence of a three-dimensional structure of chorismate synthase from L. monocytogenes, a homology model was generated using the Modeller program. A model with the highest DOPE score was chosen and validated. The reliable model was subjected to docking studies with 30 ligands from N. sativa. From this approach, α-longipinene was unveiled as the best hit. Further in vitro studies demonstrated the antibiofilm potential of α-longipinene against L. monocytogenes. Overall, the study reveals lead molecules from N. sativa as promising antibiofilm agents against L. monocytogenes. Hence, extended investigation with lead molecules will provide sustainable strategies to prevent biofilm-mediated problems due to L. monocytogenes.

Computer especially AI-assisted drug virtual screening and design in traditional Chinese medicine

BACKGROUND

Traditional Chinese medicine (TCM), as a significant part of the global pharmaceutical science, the abundant molecular compounds it contains is a valuable potential source of designing and screening new drugs. However, due to the un-estimated quantity of the natural molecular compounds and diversity of the related problems drug discovery such as precise screening of molecular compounds or the evaluation of efficacy, physicochemical properties and pharmacokinetics, it is arduous for researchers to design or screen applicable compounds through old methods. With the rapid development of computer technology recently, especially artificial intelligence (AI), its innovation in the field of virtual screening contributes to an increasing efficiency and accuracy in the process of discovering new drugs.

PURPOSE

This study systematically reviewed the application of computational approaches and artificial intelligence in drug virtual filtering and devising of TCM and presented the potential perspective of computer-aided TCM development.

STUDY DESIGN

We made a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Then screening the most typical articles for our research.

METHODS

The systematic review was performed by following the PRISMA guidelines. The databases PubMed, EMBASE, Web of Science, CNKI were used to search for publications that focused on computer-aided drug virtual screening and design in TCM.

RESULT

Totally, 42 corresponding articles were included in literature reviewing. Aforementioned studies were of great significance to the treatment and cost control of many challenging diseases such as COVID-19, diabetes, Alzheimer's Disease (AD), etc. Computational approaches and AI were widely used in virtual screening in the process of TCM advancing, which include structure-based virtual screening (SBVS) and ligand-based virtual screening (LBVS). Besides, computational technologies were also extensively applied in absorption, distribution, metabolism, excretion and toxicity (ADMET) prediction of candidate drugs and new drug design in crucial course of drug discovery.

CONCLUSIONS

The applications of computer and AI play an important role in the drug virtual screening and design in the field of TCM, with huge application prospects.

Genome-Based Multi-Antigenic Epitopes Vaccine Construct Designing against Staphylococcus hominis Using Reverse Vaccinology and Biophysical Approaches

Staphylococcus hominis is a Gram-positive bacterium from the staphylococcus genus; it is also a member of coagulase-negative staphylococci because of its opportunistic nature and ability to cause life-threatening bloodstream infections in immunocompromised patients. Gram-positive and opportunistic bacteria have become a major concern for the medical community. It has also drawn the attention of scientists due to the evaluation of immune evasion tactics and the development of multidrug-resistant strains. This prompted the need to explore novel therapeutic approaches as an alternative to antibiotics. The current study aimed to develop a broad-spectrum, multi-epitope vaccine to control bacterial infections and reduce the burden on healthcare systems. A computational framework was designed to filter the immunogenic potent vaccine candidate. This framework consists of pan-genomics, subtractive proteomics, and immunoinformatics approaches to prioritize vaccine candidates. A total of 12,285 core proteins were obtained using a pan-genome analysis of all strains. The screening of the core proteins resulted in the selection of only two proteins for the next epitope prediction phase. Eleven B-cell derived T-cell epitopes were selected that met the criteria of different immunoinformatics approaches such as allergenicity, antigenicity, immunogenicity, and toxicity. A vaccine construct was formulated using EAAAK and GPGPG linkers and a cholera toxin B subunit. This formulated vaccine construct was further used for downward analysis. The vaccine was loop refined and improved for structure stability through disulfide engineering. For an efficient expression, the codons were optimized as per the usage pattern of the E coli (K12) expression system. The top three refined docked complexes of the vaccine that docked with the MHC-I, MHC-II, and TLR-4 receptors were selected, which proved the best binding potential of the vaccine with immune receptors; this was followed by molecular dynamic simulations. The results indicate the best intermolecular bonding between immune receptors and vaccine epitopes and that they are exposed to the host’s immune system. Finally, the binding energies were calculated to confirm the binding stability of the docked complexes. This work aimed to provide a manageable list of immunogenic and antigenic epitopes that could be used as potent vaccine candidates for experimental in vivo and in vitro studies.

Classic mechanisms and experimental models for the anti‐inflammatory effect of traditional Chinese medicine

Inflammation is a common disease involved in the pathogenesis, complications, and sequelae of a large number of related diseases, and therefore considerable research has been directed toward developing anti‐inflammatory drugs for the prevention and treatment of these diseases. Traditional Chinese medicine (TCM) has been used to treat inflammatory and related diseases since ancient times. According to the review of abundant modern scientific researches, it is suggested that TCM exhibit anti‐inflammatory effects at different levels, and via multiple pathways with various targets, and recently a series of in vitro and in vivo anti‐inflammatory models have been developed for anti‐inflammation research in TCM. Currently, the reported classic mechanisms of TCM and experimental models of its anti‐inflammatory effects provide reference points and guidance for further research and development of TCM. Importantly, the research clearly confirms that TCM is now and will continue to be an effective form of treatment for many types of inflammation and inflammation‐related diseases.

Genome sequencing and in silico analysis of isoprene degrading monooxygenase enzymes of Sphingobium sp. BHU LFT2

The whole genome sequencing of a novel isoprene degrading strain of Sphingobium sp. BHU LFT2, its in silico analysis for identifying and characterizing enzymes, especially isoprene monooxygenases (IsoMO), which initiate the degradation process, and in vitro validation with cell extract of optimal temperature and pH and analysis for utilizing isoprene as the preferential substrate, were conducted. The most efficient monooxygenase was identified through comparative analyses using molecular docking followed by molecular dynamics simulation approach. The in silico results revealed high thermostability for most of the monooxygenases. Most potent monooxygenase with locus ID JQK15_20300 exhibiting high sequence similarity with known monooxygenases of isoprene-degrading Rhodococcus sp. LB1 and SC4 strains was identified. Interaction energy of -17.25 kJ/mol for JQK15_20300 with isoprene, was almost similar as that analysed for above-mentioned similar known counterparts, was exhibited by the molecular docking. Molecular dynamic simulation of 100 ns and free energy analysis of JQK15_20300 in the complex with isoprene gave persistent interaction of isoprene with JQK15_20300 during the simulation with high average binding energy of -47.13 kJ/mol thus proving higher affinity of JQK15_20300 for isoprene. The study revealed that the highly efficient isoprene degrading strain of Sphingobium sp. BHU LFT2 having effective monooxygenase could be utilized for large-scale applications including detoxification of air contaminated with isoprene in closed working systems.Communicated by Ramaswamy H. Sarma.

Strategies for Heterologous Expression, Synthesis, and Purification of Animal Venom Toxins

Animal venoms are complex mixtures containing peptides and proteins known as toxins, which are responsible for the deleterious effect of envenomations. Across the animal Kingdom, toxin diversity is enormous, and the ability to understand the biochemical mechanisms governing toxicity is not only relevant for the development of better envenomation therapies, but also for exploiting toxin bioactivities for therapeutic or biotechnological purposes. Most of toxinology research has relied on obtaining the toxins from crude venoms; however, some toxins are difficult to obtain because the venomous animal is endangered, does not thrive in captivity, produces only a small amount of venom, is difficult to milk, or only produces low amounts of the toxin of interest. Heterologous expression of toxins enables the production of sufficient amounts to unlock the biotechnological potential of these bioactive proteins. Moreover, heterologous expression ensures homogeneity, avoids cross-contamination with other venom components, and circumvents the use of crude venom. Heterologous expression is also not only restricted to natural toxins, but allows for the design of toxins with special properties or can take advantage of the increasing amount of transcriptomics and genomics data, enabling the expression of dormant toxin genes. The main challenge when producing toxins is obtaining properly folded proteins with a correct disulfide pattern that ensures the activity of the toxin of interest. This review presents the strategies that can be used to express toxins in bacteria, yeast, insect cells, or mammalian cells, as well as synthetic approaches that do not involve cells, such as cell-free biosynthesis and peptide synthesis. This is accompanied by an overview of the main advantages and drawbacks of these different systems for producing toxins, as well as a discussion of the biosafety considerations that need to be made when working with highly bioactive proteins.

Quantum Biochemical Investigation of Lys49-PLA2 from Bothrops moojeni

Envenomation via snakebites occurs largely in areas where it is harder to access the hospital. Its mortality rate and sequelae acquired by the survivors symbolize a big challenge for antivenom therapy. In particular, the homologous phospholipase A₂ (Lys49-PLA₂) proteins can induce myonecrosis and are not effectively neutralized by current treatments. Thus, by taking advantage of crystallographic structures of Bothrops moojeni Lys49-PLA₂ complexed with VRD (varespladib) and AIN (aspirin), a quantum biochemistry study based on the molecular fractionation with conjugate cap scheme within the density functional theory formalism is performed to unveil these complexes' detailed interaction energies. The calculations revealed that important interactions between ligands and the Lys49-PLA₂ pocket could occur up to a pocket radius of r = 6.5 (5.0 Å) for VRD (AIN), with the total interaction energy of the VRD ligand being higher than that of the AIN ligand, which is well-correlated with the experimental binding affinity. Furthermore, we have identified the role played by the amino acids LYS0069, LYS0049, LEU0005, ILE0009, CYS0029, GLY0030, HIS0048, PRO0018, ALA0019, CYS0045, TYR0052, TYR0022, PRO0125*, and PHE0126* (LYS0069, LYS0049, GLY0032, LEU0002, and LEU0005) in the VRD↔Lys49-PLA₂ (AIN↔Lys49-PLA₂) complex. Our simulations are a valuable tool to support the big challenge for neutralizing the damages in victims of snakebites.

Preliminary modelling as the first stage of targeted organic synthesis

The review aims to present a classification and applicability analysis of methods for preliminary molecular modelling for targeted organic, catalytic and biocatalytic synthesis. The following three main approaches are considered as a primary classification of the methods: modelling of the target – ligand coordination without structural information on both the target and the resulting complex; calculations based on experimentally obtained structural information about the target; and dynamic simulation of the target – ligand complex and the reaction mechanism with calculation of the free energy of the reaction. The review is meant for synthetic chemists to be used as a guide for building an algorithm for preliminary modelling and synthesis of structures with specified properties.

The bibliography includes 353 references.

Identification of a Chitooligosaccharide Mechanism against Bacterial Leaf Blight on Rice by In Vitro and In Silico Studies

This study focuses on a commercial plant elicitor based on chitooligosaccharides (BIG^®), which aids in rice plant growth and disease resistance to bacterial leaf blight (BLB). When the pathogen (Xoo) vigorously attacks rice that has suffered yield losses, it can cause damage in up to 20% of the plant. Furthermore, Xoo is a seed-borne pathogen that can survive in rice seeds for an extended period. In this study, when rice seeds were soaked and sprayed with BIG^®, there was a significant increase in shoot and root length, as well as plant biomass. Furthermore, BIG^®-treated rice plants showed a significant reduction in BLB severity of more than 33%. Synchrotron radiation-based Fourier transform infrared (SR-FTIR) analysis was used to characterize BIG^®’s mechanism in the chemical structure of rice leaves. The SR-FTIR results at 1650, 1735, and 1114 cm⁻¹ indicated changes in biochemical components such as pectins, lignins, proteins, and celluloses. These findings demonstrated that commercial BIG^® not only increased rice growth but also induced resistance to BLB. The drug’s target enzyme, Xoo 1075 from Xanthomonas oryzae (PDB ID: 5CY8), was analyzed for its interactions with polymer ingredients, specifically chitooligosaccharides, to gain molecular insights down to the atomic level. The results are intriguing, with a strong binding of the chitooligosaccharide polymer with the drug target, revealing 10 hydrogen bonds between the protein and polymer. Overall, the computational analysis supported the experimentally demonstrated strong binding of chitooligosaccharides to the drug target.

High-Throughput Screening and Quantum Mechanics for Identifying Potent Inhibitors Against Mac1 Domain of SARS-CoV-2 Nsp3

SARS-CoV-2 encodes the Mac1 domain within the large nonstructural protein 3 (Nsp3), which has an ADP-ribosylhydrolase activity conserved in other coronaviruses. The enzymatic activity of Mac1 makes it an essential virulence factor for the pathogenicity of coronavirus (CoV). They have a regulatory role in counteracting host-mediated antiviral ADP-ribosylation, which is unique part of host response towards viral infections. Mac1 shows highly conserved residues in the binding pocket for the mono and poly ADP-ribose. Therefore, SARS-CoV-2 Mac1 enzyme is considered as an ideal drug target and inhibitors developed against them can possess a broad antiviral activity against CoV. ADP-ribose-1 phosphate bound closed form of Mac1 domain is considered for screening with large database of ZINC. XP docking and QPLD provides strong potential lead compounds, that perfectly fits inside the binding pocket. Quantum mechanical studies expose that, substrate and leads have similar electron donor ability in the head regions, that allocates tight binding inside the substrate-binding pocket. Molecular dynamics study confirms the substrate and new lead molecules presence of electron donor and acceptor makes the interactions tight inside the binding pocket. Overall binding phenomenon shows both substrate and lead molecules are well-adopt to bind with similar binding mode inside the closed form of Mac1.

Insight into Shared Properties and Differential Dynamics and Specificity of Secretory Phospholipase A2 Family Members

Understanding generic mechanisms of functions shared by the secretory phospholipase A₂ (sPLA₂) family involved in the lipid metabolism and cell signaling and the molecular basis of function specificity for family members is an intriguing but challenging problem for biologists. Here, we explore the issue through extensive analyses using a combination of structure-based methods and bioinformatics tools on130 sPLA₂ family members. The principal component analysis of the structure ensemble reveals that the enzyme has an open-close motion which helps widen the substrate binding channel, facilitating its binding to phospholipid. Performing elastic network model and sequence analyses found that the residues critical for family functions, such as cysteine and catalytic residues, are highly conserved and undergo minimal movements, which is evolutionarily essential as their perturbation would impact the function, while the four residue regions involved in the association with the calcium ion/membrane are lowly conserved and of high mobility and large variations in low-to-intermediate frequency modes, which reflects the specificity of members. The analyses from perturbation response scanning also reveal that the above four regions with high sensitivity to an external perturbation are member-specific, suggesting their different roles in allosteric modulation, while the minimal sensitive residues are the shared characteristics across family members, which play an important role in maintaining structural stability as the folding core. This study is helpful for understanding how sequences, structures, and dynamics of sPLA₂ family members evolve to ensure their common and specific functions and can provide a guide for accurate design of proteins with finely tuned activities.

Structure insights of SARS-CoV-2 open state envelope protein and inhibiting through active phytochemical of ayurvedic medicinal plants from Withania somnifera

Coronaviruses have been causing pandemic situations across the globe for the past two decades and the focus is on identifying suitable novel targets for antivirals and vaccine development. SARS-CoV-2 encodes a small hydrophobic envelope (E) protein that mediates envelope formation, budding, replication, and release of progeny viruses from the host. Through this study, the SARS-CoV-2 E protein is studied for its open and closed state and focused in identifying antiviral herbs used in traditional medicine practices for COVID-19 infections. In this study using computational tools, we docked the shortlisted phytochemicals with the envelope protein of the SARS-CoV-2 virus and the results hint that these compounds interact with the pore-lining residues. The molecular level understanding of the open state is considered and the active inhibitors from the phytochemicals of Ayurvedic medicinal plants from Withania somnifera. We have thus identified a potential phytochemical compound that directly binds with the pore region of the E protein and thereby blocks its channel activity. Blocking the ion channel activity of E protein is directly related to the inhibition of virus replication. The study shows encouraging results on the usage of these phytochemicals in the treatment/management of SARS-CoV-2 infection.

Computational molecular docking and virtual screening revealed promising SARS-CoV-2 drugs

The pandemic of novel coronavirus disease 2019 (COVID-19) has rampaged the world, with more than 58.4 million confirmed cases and over 1.38 million deaths across the world by 23 November 2020. There is an urgent need to identify effective drugs and vaccines to fight against the virus. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) belongs to the family of coronaviruses consisting of four structural and 16 non-structural proteins (NSP). Three non-structural proteins, main protease (Mpro), papain-like protease (PLpro), and RNA-dependent RNA polymerase (RdRp), are believed to have a crucial role in replication of the virus. We applied computational ligand-receptor binding modeling and performed comprehensive virtual screening on FDA-approved drugs against these three SARS-CoV-2 proteins using AutoDock Vina, Glide, and rDock. Our computational studies identified six novel ligands as potential inhibitors against SARS-CoV-2, including antiemetics rolapitant and ondansetron for Mpro; labetalol and levomefolic acid for PLpro; and leucal and antifungal natamycin for RdRp. Molecular dynamics simulation confirmed the stability of the ligand-protein complexes. The results of our analysis with some other suggested drugs indicated that chloroquine and hydroxychloroquine had high binding energy (low inhibitory effect) with all three proteins-Mpro, PLpro, and RdRp. In summary, our computational molecular docking approach and virtual screening identified some promising candidate SARS-CoV-2 inhibitors that may be considered for further clinical studies.

Microsecond MD Simulation and Multiple-Conformation Virtual Screening to Identify Potential Anti-COVID-19 Inhibitors Against SARS-CoV-2 Main Protease

The recent pandemic outbreak of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), raised global health and economic concerns. Phylogenetically, SARS-CoV-2 is closely related to SARS-CoV, and both encode the enzyme main protease (M^pro/3CL^pro), which can be a potential target inhibiting viral replication. Through this work, we have compiled the structural aspects of M^pro conformational changes, with molecular modeling and 1-μs MD simulations. Long-scale MD simulation resolves the mechanism role of crucial amino acids involved in protein stability, followed by ensemble docking which provides potential compounds from the Traditional Chinese Medicine (TCM) database. These lead compounds directly interact with active site residues (His41, Gly143, and Cys145) of M^pro, which plays a crucial role in the enzymatic activity. Through the binding mode analysis in the S1, S1′, S2, and S4 binding subsites, screened compounds may be functional for the distortion of the oxyanion hole in the reaction mechanism, and it may lead to the inhibition of M^pro in SARS-CoV-2. The hit compounds are naturally occurring compounds; they provide a sustainable and readily available option for medical treatment in humans infected by SARS-CoV-2. Henceforth, extensive analysis through molecular modeling approaches explained that the proposed molecules might be promising SARS-CoV-2 inhibitors for the inhibition of COVID-19, subjected to experimental validation.

Understanding the structural insights of enzymatic conformations for adenylosuccinate lyase receptor in malarial parasite Plasmodium falciparum

The dreadful disease malaria is one among the infectious diseases that comes in third number after the tuberculosis and HIV. This disease is spread by female Anopheles mosquito and caused by the malarial parasite sp notably Plasmodium falciparum. In this, the organism has several enzymes for processing the infection and growth mechanism and among that, the adenylosuccinate lyase is an enzyme that plays a critical role in metabolism and cellular replication via its action in the de novo purine biosynthetic pathway. Adenylosuccinate has been studied for two reaction mechanisms, and in that, the adenylosuccinate to AMP and fumarate is core important. As of now, there have been several studies indicating the reaction mechanism of adenylosuccinate lyase, this study projects the conformations of the reactant and product changes through molecular docking and molecular dynamic simulations. Adenylosuccinate bound complex involves His role in the product than the reactant complex, and the complex shows high flexibility due to fumarate. Thus, identifying the core inhibitor that binds to His rings could be a standard adenylosuccinate lyase inhibitor, that can block the malarial diseases in humans. In addition to the competitive inhibition site, we also predicted the uncompetitive ligand binding site, which suggest the alternate region to be targeted. Thus, from this work, we suggest both competitive and uncompetitive binding regions for the purpose identifying the malarial inhibitors.

Bacterial protein azurin and derived peptides as potential anti-SARS-CoV-2 agents: insights from molecular docking and molecular dynamics simulations

The current pandemic SARS-CoV-2 has wreaked havoc in the world, and neither drugs nor vaccine is available for the treatment of this disease. Thus, there is an immediate need for novel therapeutics that can combat this deadly infection. In this study, we report the therapeutic assessment of azurin and its peptides: p18 and p28 against the viral structural S-protein and non-structural 3CL^pro and PL^pro proteins. Among the analyzed complexes, azurin docked relatively well with the S2 domain of S-protein compared to the other viral proteins. The derived peptide p18 bound to the active site domain of the PL^pro protein; however, in other complexes, lesser interactions were recorded. The second azurin derived peptide p28, fared the best among the docked proteins. p28 interacted with all the three viral proteins and the host ACE-2 receptor by forming several electrostatic and hydrogen bonds with the S-protein, 3CL^pro, and PL^pro. MD simulations indicated that p28 exhibited a strong affinity to S-protein and ACE-2 receptor, indicating a possibility of p28 as a protein-protein interaction inhibitor. Our data suggest that the p28 has potential as an anti-SARS-CoV-2 agent and can be further exploited to establish its validity in the treatment of current and future SARS-CoV crisis.Communicated by Ramaswamy H. Sarma.

Structure-based virtual screening and molecular dynamics simulation of SARS-CoV-2 Guanine-N7 methyltransferase (nsp14) for identifying antiviral inhibitors against COVID-19

The recent pandemic caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) calls the whole world into a medical emergency. For tackling Coronavirus Disease 2019 (COVID-19), researchers from around the world are swiftly working on designing and identifying inhibitors against all possible viral key protein targets. One of the attractive drug targets is guanine-N7 methyltransferase which plays the main role in capping the 5′-ends of viral genomic RNA and sub genomic RNAs, to escape the host’s innate immunity. We performed homology modeling and molecular dynamic (MD) simulation, in order to understand the molecular architecture of Guanosine-P3-Adenosine-5’,5’-Triphosphate (G3A) binding with C-terminal N7-MTase domain of nsp14 from SARS-CoV-2. The residue Asn388 is highly conserved in present both in N7-MTase from SARS-CoV and SARS-CoV-2 and displays a unique function in G3A binding. For an in-depth understanding of these substrate specificities, we tried to screen and identify inhibitors from the Traditional Chinese Medicine (TCM) database. The combination of several computational approaches, including screening, MM/GBSA, MD simulations, and PCA calculations, provides the screened compounds that readily interact with the G3A binding site of homology modeled N7-MTase domain. Compounds from this screening will have strong potency towards inhibiting the substrate-binding and efficiently hinder the viral 5’-end RNA capping mechanism. We strongly believe the final compounds can become COVID-19 therapeutics, with huge international support.

Communicated by Ramaswamy H. Sarma.

Synergistic Effect of Chlorogenic Acid and Caffeic Acid with Fosfomycin on Growth Inhibition of a Resistant Listeria monocytogenes Strain

Listeria monocytogenes, a human foodborne pathogen that causes listeriosis with high-rate mortality, has been reported to be resistant to commonly used antibiotics. New antibiotics or cocktails of existing antibiotics with synergistic compounds are in high demand for treating this multi-drug-resistant pathogen. Fosfomycin is one of the novel and promising therapeutic antibiotics for the treatment of listeriosis. However, some L. monocytogenes strains with the FosX gene were recently reported to survive from the fosfomycin treatment. This work aims to identify FosX inhibitors that can revive fosfomycin in treating resistant L. monocytogenes. Since structures and activities of the FosX protein in L. monocytogenes have been well studied, we used an integrated computational and experimental approach to identify FosX inhibitors that show synergistic effect with fosfomycin in treating resistant L. monocytogenes. Specifically, automated ligand docking was implemented to perform virtual screening of the Indofine natural-product database and FDA-approved drugs to identify potential inhibitors. An in vitro bacterial growth inhibition test was then utilized to verify the effectiveness of identified compounds combined with fosfomycin in inhibiting the resistant L. monocytogenes strains. Two phenolic acids, i.e., caffeic acid and chlorogenic acid, were predicted as high-affinity FosX inhibitors from the ligand-docking platform. Experiments with these compounds indicated that the cocktail of either caffeic acid (1.5 mg/mL) or chlorogenic acid (3 mg/mL) with fosfomycin (50 mg/L) was able to significantly inhibit the growth of the pathogen. The finding of this work implies that the combination of fosfomycin with either caffeic acid or chlorogenic acid is of potential to be used in the clinical treatment of Listeria infections.

BoaγPLI: Structural and functional characterization of the gamma phospholipase A2 plasma inhibitor from the non-venomous Brazilian snake Boa constrictor

Plasma in several organisms has components that promote resistance to envenomation by inhibiting specific proteins from snake venoms, such as phospholipases A₂ (PLA₂s). The major hypothesis for inhibitor’s presence would be the protection against self-envenomation in venomous snakes, but the occurrence of inhibitors in non-venomous snakes and other animals has opened new perspectives for this molecule. Thus, this study showed for the first time the structural and functional characterization of the PLA₂ inhibitor from the Boa constrictor serum (BoaγPLI), a non-venomous snake that dwells extensively the Brazilian territory. Therefore, the inhibitor was isolated from B. constrictor serum, with 0.63% of recovery. SDS-PAGE showed a band at ~25 kDa under reducing conditions and ~20 kDa under non-reducing conditions. Chromatographic analyses showed the presence of oligomers formed by BoaγPLI. Primary structure of BoaγPLI suggested an estimated molecular mass of 22 kDa. When BoaγPLI was incubated with Asp-49 and Lys-49 PLA₂ there was no severe change in its dichroism spectrum, suggesting a non-covalent interaction. The enzymatic assay showed a dose-dependent inhibition, up to 48.2%, when BoaγPLI was incubated with Asp-49 PLA₂, since Lys-49 PLA₂ has a lack of enzymatic activity. The edematogenic and myotoxic effects of PLA₂s were also inhibited by BoaγPLI. In summary, the present work provides new insights into inhibitors from non-venomous snakes, which possess PLIs in their plasma, although the contact with venom is unlikely.