"Affimer" synthetic protein scaffolds block oxidized LDL binding to the LOX-1 scavenger receptor and inhibit ERK1/2 activation.

In multicellular organisms, a variety of lipid-protein particles control the systemic flow of triacylglycerides, cholesterol, and fatty acids between cells in different tissues. The chemical modification by oxidation of these particles can trigger pathological responses, mediated by a group of membrane proteins termed scavenger receptors. The lectin-like oxidized low-density lipoprotein (LOX-1) scavenger receptor binds to oxidized low-density lipoprotein (oxLDL) and mediates both signaling and trafficking outcomes. Here, we identified five synthetic proteins termed Affimers from a phage display library, each capable of binding recombinant LOX-1 extracellular (oxLDL-binding) domain with high specificity. These Affimers, based on a phytocystatin scaffold with loop regions of variable sequence, were able to bind to the plasma membrane of HEK293T cells exclusively when human LOX-1 was expressed. Binding and uptake of fluorescently labeled oxLDL by the LOX-1-expressing cell model was inhibited with subnanomolar potency by all 5 Affimers. ERK1/2 activation, stimulated by oxLDL binding to LOX-1, was also significantly inhibited (p < 0.01) by preincubation with LOX-1-specific Affimers, but these Affimers had no direct agonistic effect. Molecular modeling indicated that the LOX-1-specific Affimers bound predominantly via their variable loop regions to the surface of the LOX-1 lectin-like domain that contains a distinctive arrangement of arginine residues previously implicated in oxLDL binding, involving interactions with both subunits of the native, stable scavenger receptor homodimer. These data provide a new class of synthetic tools to probe and potentially modulate the oxLDL/LOX-1 interaction that plays an important role in vascular disease.

In-silico prediction, characterization, molecular docking and dynamic simulation studies for screening potential fungicides against leaf rust of Triticum aestivum.

Triticum aestivum is an important crop worldwide, which is a large source of food grain. T.aestivum demands on developed countries will grow every year, this increase in the demand is profoundly serious especially in the light climate change which would lead to a 29% reduction in final productivity. Rust fungus attacks the T.aestivum, specifically newly planted T.aestivum plants, which block the vascular system, stun, and finally damage grain and tillers. In present study we predict the 3D structure then find the binding pocket and conserved domains for MAPkinase-1 of Puccinia triticina. After that, screen the FungiPAD, PubChem, NPAtlas databases by physicochemical properties, docking, clustering, ADME (Absorption, distribution, metabolism, and excretion) and PAINS (pan assay interference compounds) filter analysis. Through this screening process screen the nine compounds, which are benzovindiflupyr, furametpyr, isopyrazam, fenaminstrobin, and flumorph from Fungicide database: zoxamide, vinclozolin, pentachloronitrobenzene, and dithianon from PubChem database, based on the binding energy, clustering, ADME and PAINS analysis. All these nine compounds bind in the same pocket and show the same pattern of interaction. Among these nine compounds, select the two compounds (PubChem:122087 (-6.96 kcal/mol) and FDBD02904 (-8.62 kcal/mol)) based on binding energy for 100 ns MD simulation and free energy calculation. MD simulation shows stability throughout the simulation, and it shows the sable interaction when compounds bind to the MAPKinase 1 protein which may help to protein kinase pathways in plant defense response. This result helps to design alternative fungicide against the wheat rust disease.Communicated by Ramaswamy H. Sarma.

Virtual high throughput screening of natural peptides against ErbB1 and ErbB2 to identify potential inhibitors for cancer chemotherapy.

Human epidermal growth factor receptors (EGFR), namely ErbB1/HER1, ErbB2/HER2/neu, ErbB3/HER3, and ErbB4/HER4, the trans-membrane family of tyrosine kinase receptors, are overexpressed in many types of cancers. These receptors play an important role in cell proliferation, differentiation, invasion, metastasis and angiogenesis including unregulated activation of cancer cells. Overexpression of ErbB1 and ErbB2 that occurs in several types of cancers is associated with poor prognosis leading to resistance to ErbB1-directed therapies. In this connection, promising strategy to overcome the disadvantages of the existing chemotherapeutic drugs is the use of short peptides as anticancer agents. In the present study, we have performed virtual high throughput screening of natural peptides against ErbB1 and ErbB2 to identify potential dual inhibitors and identified five inhibitors based on their binding affinities, ADMET analysis, MD simulation studies and calculation of free energy of binding. These natural peptides could be further exploited for developing drugs for treating cancer.Communicated by Ramaswamy H. Sarma.

Identification of FDA-approved drugs against SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) through computational virtual screening.

The SARS-CoV-2 coronavirus is responsible for the COVID-19 outbreak, which overwhelmed millions of people worldwide; hence, there is an urgency to identify appropriate antiviral drugs. This study focuses on screening compounds that inhibit RNA-dependent RNA-polymerase (RdRp) essential for RNA synthesis required for replication of positive-strand RNA viruses. Computational screening against RdRp using Food and Drug Administration (FDA)-approved drugs identified ten prominent compounds with binding energies of more than - 10.00 kcal/mol, each a potential inhibitor of RdRp. These compounds' binding energy is comparable to known RdRp inhibitors remdesivir (IC50 = 10.09 µM, SI = 4.96) and molnupiravir (EC50 = 0.67 - 2.66 µM) and 0.32-2.03 µM). Remdesivir and molnupiravir have been tested in clinical trial and remain authorized for emergency use in the treatment of COVID-19. In docking simulations, selected compounds are bound to the substrate-binding pocket of RdRp and showed hydrophobic and hydrogen bond interaction. For molecular dynamics simulation, capmatinib, pralsetinib, ponatinib, and tedizolid phosphate were selected from the initial ten candidate compounds. MD simulation indicated that these compounds are stable at 50-ns MD simulation when bound to RdRp protein. The screen hit compounds, remdesivir, molnupiravir, and GS-441524, are bound in the substrate binding pocket with good binding-free energy. As a consequence, capmatinib, pralsetinib, ponatinib, and tedizolid phosphate are potential new inhibitors of RdRp protein with potential of limiting COVID-19 infection by blocking RNA synthesis. Supplementary Information: The online version contains supplementary material available at 10.1007/s11224-022-02072-1.

Identification of natural inhibitor against L1 ß-lactamase present in Stenotrophomonas maltophilia.

Antibiotic resistance is threatening the medical industry in treating microbial infections. Many organisms are acquiring antibiotic resistance because of the continuous use of the same drug. Gram-negative organisms are developing multi-drug resistance properties (MDR) due to chromosomal level changes that occurred as a part of evolution or some intrinsic factors already present in the organism. Stenotrophomonas maltophilia falls under the category of multidrug-resistant organism. WHO has also urged to evaluate the scenario and develop new strategies for making this organism susceptible to otherwise resistant antibiotics. Using novel compounds as drugs can ameliorate the issue to some extent. The ß-lactamase enzyme in the bacteria is responsible for inhibiting several drugs currently being used for treatment. This enzyme can be targeted to find an inhibitor that can inhibit the enzyme activity and make the organism susceptible to ß-lactam antibiotics. Plants produce several secondary metabolites for their survival in adverse environments. Several phytoconstituents have antimicrobial properties and have been used in traditional medicine for a long time. The computational technologies can be exploited to find the best compound from many compounds. Virtual screening, molecular docking, and dynamic simulation methods are followed to get the best inhibitor for L1 ß-lactamase. IMPPAT database is screened, and the top hit compounds are studied for ADMET properties. Finally, four compounds are selected to set for molecular dynamics simulation. After all the computational calculations, withanolide R is found to have a better binding and forms a stable complex with the protein. This compound can act as a potent natural inhibitor for L1 ß-lactamase.

Potential inhibitors for FKBP51: an in silico study using virtual screening, molecular docking and molecular dynamics simulation.

Over the years, FK506-binding proteins have been targeted for different pharmaceutical interests. The FK506-binding protein, encoded by the FKBP5 gene, is responsible for stress and metabolic-related disorders, including cancer. In addition, the FKBD-I domain of the protein is a potential target for endocrine-related physiological diseases. In the present study, a set of natural compounds from the ZINC database was screened against FKBP51 protein using in silico strategy, namely pharmacophore modeling, molecular docking, and molecular dynamic simulation. A protein-ligand-based pharmacophore model workflow was employed to identify small molecules. The resultant compounds were then assessed for their toxicity using ADMET prediction. Based on ADMET prediction, 4768 compounds were selected for molecular docking to elucidate their binding mode. Based on the binding energy, 857 compounds were selected, and their Similarity Tanimoto coefficient was calculated, followed by clustering according to Jarvis-Patrick clustering methods (Jarp). The clustered singletons resulted in 14 hit compounds. The top 05 hit compounds and 05 known compounds were then subjected to 100 ns MD simulation to check the stability of complexes. The study revealed that the selected complexes are stable throughout the 100 ns simulation; for FKBD-I (4TW6), crystal structure compared with FKBP-51 (1KT0) crystal structure. Finally, the binding free energies of the hit complexes were calculated using molecular mechanics energies combined with Poisson-Boltzmann. The data reveal that all the complexes show negative BFEs, indicating a good affinity of the hit compounds to the protein. The top five compounds are, therefore, potential inhibitors for FKBP51. Communicated by Ramaswamy H. Sarma.

Ligand-based pharmacophore modeling of TNF-α to design novel inhibitors using virtual screening and molecular dynamics.

Tumor necrosis factor-α (TNF-α) is one of the promising targets for treating inflammatory (Crohn disease, psoriasis, psoriatic arthritis, rheumatoid arthritis) and various other diseases. Commercially available TNF-α inhibitors are associated with several risks and limitations. In the present study, we have identified small TNF-α inhibitors using in silico approaches, namely pharmacophore modeling, virtual screening, molecular docking, molecular dynamics simulation and free binding energy calculations. The study yielded better and potent hits that bind to TNF-α with significant affinity. The best pharmacophore model generated using LigandScout has an efficient hit rate and Area Under the operating Curve. High throughput virtual screening of SPECS database molecules against crystal structure of TNF-α protein, coupled with physicochemical filtration, PAINS test. Virtual hit compounds used for molecular docking enabled the identification of 20 compounds with better binding energies when compared with previously known TNF-α inhibitors. MD simulation analysis on 20 virtual identified hits showed that ligand binding with TNF-α protein is stable and protein-ligand conformation remains unchanged. Further, 16 compounds passed ADMET analysis suggesting these identified hit compounds are suitable for designing a future class of potent TNF-α inhibitors.Communicated by Ramaswamy H. Sarma.

Identification of Therapeutic Drug Target of Stenotrophomonas maltophilia Through Subtractive Genomic Approach and in-silico Screening Based on 2D Similarity Filtration and Molecular Dynamic Simulation.

BACKGROUND: Stenotrophomonas maltophilia is a multi-drug resistant, gram-negative bacterium that causes opportunistic infections and is associated with high morbidity and mortality in severely immunocompromised individuals. AIM: The study aimed to find out the drug target and a novel inhibitor for Stenotrophomonas maltophilia. OBJECTIVES: The current study focused on identifying specific drug targets by subtractive genomes analysis to determine the novel inhibitor for the specified target protein by virtual screening, molecular docking, and molecular simulation approach. MATERIALS AND METHODS: In this study, we performed a subtractive genomics approach to identify the novel drug target for S.maltophilia. After obtaining the specific target, the next step was to identify inhibitors that include calculating 2D similarity search, molecular docking, and molecular simulation for drug development for S.maltophilia. RESULTS: With an efficient subtractive genomic approach, out of 4386 proteins, five unique targets were found, in which UDP-D-acetylmuramic (murF) was the most remarkable target. Further virtual screening, docking, and dynamics analyses resulted in the identification of seven novel inhibitors. CONCLUSION: Further, in vitro and in vivo bioassay of the identified novel inhibitors could facilitate effective drug use against S.maltophilia.

Structural and functional analysis of Chitinase-IV of Brassica juncea: molecular modeling and dynamic simulation study.

Brassica juncea is an important oil seed crop. The productivity of this plant, however, is known to be low due to the attack of plant pathogens. The plant chitinase-IV is known to hydrolyse the chitin present in the cell walls of the plant pathogens and thus enhance the plant defense systems. In this connection, studies were carried out by us on the prediction and characterization of the 3D structure of chitinase-IV, the structural changes that take place when the protein is in complex with Allosamidin and the chitin fragments (Tri-oligosaccharide and N-acetyl glucosamine) that act as elicitors to induce plant innate immunity against the invading pathogens, and molecular dynamic simulation studies on the stability of these complexes. These studies are expected to give us an insight into the chitin-binding domain and information on the dynamics and energetics of the protein, which is not possible to obtain by experimental methods. The predicted 3D structure of the protein should give us a better understanding of the molecular function of the chitinase gene in Brassica juncea for devising better methods of biocontrol against fungal phytopathogens and harmful insects so as to increase the crop yield.

In silico screening of FDA approved drugs against ACE2 receptor: potential therapeutics to inhibit the entry of SARS-CoV-2 to human cells.

An unknown coronavirus that emerged sometime at the end of 2019 in China, the novel SARS-CoV-2, now called COVID-19, has spread all over the world. Several efforts have been made to prevent or treat this disease, though not with success. The initiation of COVID-19 viral infection involves specific binding of SARS-CoV-2 to the host surface of the receptor, ACE2. The ACE2- SARS-CoV-2 complex then gets transferred into the endosomes where the endosomal acidic proteases cleave the S protein present in SARS-CoV-2, activating its fusion and release of the viral genome. We have carried out detailed and thorough in silico studies to repurpose FDA approved compounds to inhibit human ACE2 receptor so as to prevent the viral entry. Our study reveals that five compounds show good binding to the ACE2 receptor and hence are potential candidates to interact with ACE2 and prevent it's recognition by the virus, SARS-CoV-2. Communicated by Ramaswamy H. Sarma.

Virtual high throughput screening: Potential inhibitors for SARS-CoV-2 PLPRO and 3CLPRO proteases.

The pandemic, COVID-19, has spread worldwide and affected millions of people. There is an urgent need, therefore, to find a proper treatment for the novel coronavirus, Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the causative agent. This paper focuses on identifying inhibitors that target SARS-CoV-2 proteases, PLPRO and 3CLPRO, which control the duplication and manages the life cycle of SARS-CoV-2. We have carried out detailed in silico Virtual high-throughput screening using Food and Drug Administration (FDA) approved drugs from the Zinc database, COVID-19 clinical trial compounds from Pubchem database, Natural compounds from Natural Product Activity and Species Source (NPASS) database and Maybridge database against PLPRO and 3CLPRO proteases. After thoroughly analyzing the screening results, we found five compounds, Bemcentinib, Pacritinib, Ergotamine, MFCD00832476, and MFCD02180753 inhibit PLPRO and six compounds, Bemcentinib, Clofazimine, Abivertinib, Dasabuvir, MFCD00832476, Leuconicine F inhibit the 3CLPRO. These compounds are stable within the protease proteins' active sites at 20ns MD simulation. The stability is revealed by hydrogen bond formations, hydrophobic interactions, and salt bridge interactions. Our study results also reveal that the selected five compounds against PLPRO and the six compounds against 3CLPRO bind to their active sites with good binding free energy. These compounds that inhibit the activity of PLPRO and 3CLPRO may, therefore, be used for treating COVID-19 infection.

In-silico screening for identification of potential inhibitors against SARS-CoV-2 transmembrane serine protease 2 (TMPRSS2).

A new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a respiratory infection out broke in December 2019 in Wuhan, Hubei province, China, resulted in pandemic conditions worldwide. COVID-19 spread swiftly around the world over with an alert of an emergency for an adequate drug. Therefore, in this research, we repurposed the FDA-approved medicines to find the prominent drug used to cure the COVID infected patients. We performed homology modeling of the transmembrane serine protease 2 (TMPRSS2), responsible for the viral entry. The prediction of the transmembrane region and the Conserved Domain in TMPRSS2 protein was made for docking. 4182 FDA-approved compounds from the ZINC database were downloaded and used for the calculation of physicochemical properties. Two thousand eight hundred fifteen screened compounds were used for molecular docking against the modelled protein structure. From which top hit compounds based on binding energy were extracted. At 1st site pose, ZINC3830554 showed the highest binding energy -12.91kcal/mol by forming Salt Bridge at LYS143, Hydrogen bond at ALA8, VAL45, HIS47, SER142, ASN277, ASN359, and TRP363. The hydrophobic Interactions at PHE3, LEU4, ALA7, ALA8, ALA139, PRO197, and PHE266. In the 2nd site pose, ZINC203686879 shows the highest binding energy (-12.56 kcal/mol) and forms a hydrophobic interaction with VAL187, VAL189, HIS205, LYS301, GLN347, TRP370 and hydrogen bond was at GLY300, THR302, GLN347, SER350 residues. These hit compounds were subjected to stability checks between the protein-ligand complex through the dynamics simulation (MD), and binding free energy was calculated through the Molecular Mechanics energies combined with Poisson-Boltzmann (MM/PBSA) method. We hope that hit compounds would be an efficient inhibitor that can block the TMPRSS2 activity and resist the entry of the SARS-CoV-2 virus into targeted human cells by reducing the virus's infectivity and transmissibility.

In-silico profiling and structural insights into the impact of nSNPs in the P. falciparum acetyl-CoA transporter gene to understand the mechanism of drug resistance in malaria.

The continuous emergence of resistance to the available drugs poses major constraints in the development of effective therapeutics against malaria. Malaria drug resistance has been attributed to be the manifestation of numerous factors. For example, mutations in the parasite transporter protein acetyl-CoA transporter (Pfact) can remarkably affect its uptake affinity for a drug molecule against malaria, and hence enhance its susceptibility to resistance. To identify major contributors to its loss of functionality, we have thoroughly scrutinized eight such recently reported resistant mutants, via in-silico tools in terms of alterations in different properties. We performed molecular dynamics simulations of the selected Pfact mutants to gain deeper insights into the structural perturbation and dynamicity. Comparison of residue interaction network map of mutants with that of Wild type (WT) protein suggests structural changes as a result of the mutation(s) that translate into the weakening of intra-protein interactions, especially around the drug binding pocket. This, in turn, diminishes the affinity of drug molecules towards the binding site, which was validated by docking analysis. Finally, collating all the observations, we have delineated R108K mutant to deviate the most from WT protein, which, intriguingly suggests that replacing an amino acid with another of similar nature can even translate into greater functional effects as those with dissimilar substitutions.Communicated by Ramaswamy H. Sarma.

In-silico virtual screening for identification of potent inhibitor for L2-ß-lactamase from Stenotrophomonas maltophilia through molecular docking, molecular dynamics analysis study.

Stenotrophomonas maltophilia, a Multiple-Drug-Resistant proteobacterium found in healthy normal flora and fauna with an aerobic and non-fermentative respiratory process, is majorly involved in Healthcare-Associated Infections (HAI). The Multiple-Drug-Resistance takes place by secretion of the ß-Lactamase enzyme, which hydrolyzes the ß-Lactam antibiotics and currently serving as a significant clinical challenge by substantially effecting the mortality rate. In this study, involved 2D Similarity, Molecular docking, and Molecular Simulation for the commercially available ZINC database compounds to overcome this resistance mechanism and find out a proper potent inhibitor for the target L2-ß-Lactamase, which would not get cleaved by the hydrolytic activity of the L2-ß-Lactamase natural enzyme. The ZINC35053014 compound had the highest binding energy: -8.51Kcal/mol with hydrophobic interaction at THR235 and formation of hydrogen bonds at SER70, SER130, ASN170, LYS234, THR235, SER237, and ARG244. In total, 08 hit compounds subjected for the stability check of the protein-ligand complex (MD simulation) analysis which, concluded in the same RMSD, RMSF, and Rg values at the comparison between known compounds and the selected virtual hit compounds. These selected virtual hit compounds can be experimentally verified and used as lead compounds for the future search of ß-Lactamase potent inhibitors for S. maltophilia. Communicated by Ramaswamy H. Sarma.

A novel identification approach for discovery of 5-HydroxyTriptamine 2A antagonists: combination of 2D/3D similarity screening, molecular docking and molecular dynamics.

5-HydroxyTriptamine 2A antagonists are potential targets for treatment of various cerebrovascular and cardiovascular disorders. In this study, we have developed and performed a unique screening pipeline for filtering ZINC database compounds on the basis of similarities to known antagonists to determine novel small molecule antagonists of 5-HydroxyTriptamine 2A. The screening pipeline is based on 2D similarity, 3D dissimilarity and a combination of 2D/3D similarity. The shortlisted compounds were docked to a 5-HydroxyTriptamine 2A homology-based model, and complexes with low binding energies (287 complexes) were selected for molecular dynamics (MD) simulations in a lipid bilayer. The MD simulations of the shortlisted compounds in complex with 5-HydroxyTriptamine 2A confirmed the stability of the complexes and revealed novel interaction insights. The receptor residues S239, N343, S242, S159, Y370 and D155 predominantly participate in hydrogen bonding. π-π stacking is observed in F339, F340, F234, W151 and W336, whereas hydrophobic interactions are observed amongst V156, F339, F234, V362, V366, F340, V235, I152 and W151. The known and potential antagonists shortlisted by us have similar overlapping molecular interaction patterns. The 287 potential 5-HydroxyTriptamine 2A antagonists may be experimentally verified.

A consensus-guided approach yields a heat-stable alkane-producing enzyme and identifies residues promoting thermostability.

Aldehyde-deformylating oxygenase (ADO) is an essential enzyme for production of long-chain alkanes as drop-in biofuels, which are compatible with existing fuel systems. The most active ADOs are present in mesophilic cyanobacteria, especially Nostoc punctiforme Given the potential applications of thermostable enzymes in biorefineries, here we generated a thermostable (Cts)-ADO based on a consensus of ADO sequences from several thermophilic cyanobacterial strains. Using an in silico design pipeline and a metagenome library containing 41 hot-spring microbial communities, we created Cts-ADO. Cts-ADO displayed a 3.8-fold increase in pentadecane production on raising the temperature from 30 to 42 °C, whereas ADO from N. punctiforme (Np-ADO) exhibited a 1.7-fold decline. 3D structure modeling and molecular dynamics simulations of Cts- and Np-ADO at different temperatures revealed differences between the two enzymes in residues clustered on exposed loops of these variants, which affected the conformation of helices involved in forming the ADO catalytic core. In Cts-ADO, this conformational change promoted ligand binding to its preferred iron, Fe2, in the di-iron cluster at higher temperature, but the reverse was observed in Np-ADO. Detailed mapping of residues conferring Cts-ADO thermostability identified four amino acids, which we substituted individually and together in Np-ADO. Among these substitution variants, A161E was remarkably similar to Cts-ADO in terms of activity optima, kinetic parameters, and structure at higher temperature. A161E was located in loop L6, which connects helices H5 and H6, and supported ligand binding to Fe2 at higher temperatures, thereby promoting optimal activity at these temperatures and explaining the increased thermostability of Cts-ADO.

Curcumin inhibits growth potential by G1 cell cycle arrest and induces apoptosis in p53-mutated COLO 320DM human colon adenocarcinoma cells.

Curcumin, a natural polyphenolic compound and it is isolated from the rhizome of Curcuma longa, have been reported to possess anticancer effect against stage I and II colon cancer. However, the effect of curcumin on colon cancer at Dukes' type C metastatic stage III remains still unclear. In the present study, we have investigated the anticancer effects of curcumin on p53 mutated COLO 320DM human colon adenocarcinoma cells derived from Dukes' type C metastatic stage. The cellular viability and proliferation were assessed by trypan blue exclusion assay and MTT assay, respectively. The cytotoxicity effect was examined by lactate dehydrogenase (LDH) cytotoxicity assay. Apoptosis was analyzed by DNA fragmentation analysis, Hoechst and propidium iodide double fluorescent staining and confocal microscopy analysis. Cell cycle distribution was performed by flow cytometry analysis. Here we have observed that curcumin treatment significantly inhibited the cellular viability and proliferation potential of p53 mutated COLO 320DM cells in a dose- and time-dependent manner. In addition, curcumin treatment showed no cytotoxic effects to the COLO 320DM cells. DNA fragmentation analysis, Hoechst and propidium iodide double fluorescent staining and confocal microscopy analysis revealed that curcumin treatment induced apoptosis in COLO 320DM cells. Furthermore, curcumin caused cell cycle arrest at the G1 phase, decreased the cell population in the S phase and induced apoptosis in COLO 320DM colon adenocarcinoma cells. Together, these data suggest that curcumin exerts anticancer effects and induces apoptosis in p53 mutated COLO 320DM human colon adenocarcinoma cells derived from Dukes' type C metastatic stage.