Plasmodium falciparum cysteine protease Falcipain 3: A potential enzyme for proteolytic processing of histone acetyltransferase PfGCN5.

In spite of 150 years of studying malaria, the unique features of the malarial parasite, Plasmodium, still perplex researchers. One of the methods by which the parasite manages its gene expression is epigenetic regulation, the champion of which is PfGCN5, an essential enzyme responsible for acetylating histone proteins. PfGCN5 is a ∼170 kDa chromatin-remodeling enzyme that harbors the conserved bromodomain and acetyltransferase domain situated in its C-terminus domain. Although the PfGCN5 proteolytic processing is essential for its activity, the specific protease involved in this process still remains elusive. Identification of PfGCN5 interacting proteins through immunoprecipitation (IP) followed by LC-tandem mass spectrometry analysis revealed the presence of food vacuolar proteins, such as the cysteine protease Falcipain 3 (FP3), in addition to the typical members of the PfGCN5 complex. The direct interaction between FP3 and PfGCN5 was further validated by in vitro pull-down assay as well as IP assay. Subsequently, use of cysteine protease inhibitor E64d led to the inhibition of protease-specific processing of PfGCN5 with concomitant enrichment and co-localization of PfGCN5 and FP3 around the food vacuole as evidenced by confocal microscopy as well as electron microscopy. Remarkably, the proteolytic cleavage of the nuclear protein PfGCN5 by food vacuolar protease FP3 is exceptional and atypical in eukaryotic organisms. Targeting the proteolytic processing of GCN5 and the associated protease FP3 could provide a novel approach for drug development aimed at addressing the growing resistance of parasites to current antimalarial drugs.

Reinvestigation of diphenylmethylpiperazine analogues of pyrazine as new class of Plasmodial cysteine protease inhibitors for the treatment of malaria.

Malaria eradication is still a global challenge due to the lack of a broadly effective vaccine and the emergence of drug resistance to most of the currently available drugs as part of the mainline artemisinin-based combination therapy. A variety of experimental approaches are quite successful in identifying and synthesizing new promising pharmacophore hybrids with distinct mechanisms of action. Based on our recent findings, the current study demonstrates the reinvestigation of a series of diphenylmethylpiperazine and pyrazine-derived molecular hybrids. Pyrazine-derived molecular hybrids were screened to investigate the antiplasmodial activity on drug-susceptible Pf3D7 and drug-resistant PfW2 strains. The selected compounds were shown to be potent dual inhibitors of cysteine protease PfFP2 and PfFP3. Time-course parasitic development study demonstrated that compounds were able to arrest the growth of the parasite at the early trophozoite stage. The compounds did not show hemolysis of red blood cells and showed selectivity to the parasite compared with the mammalian Vero and A5489 cell lines. The study underlined HR5 and HR15 as a new class of Plasmodial falcipain inhibitors with an IC50 of 6.2 µM and 5.9 µM for PfFP2 and 6.8 µM and 6.4 µM for PfFP3, respectively. Both compounds have antimalarial efficacy with IC50 values of 3.05 µM and 2.80 µM for the Pf3D7 strain, and 4.35 µM and 3.39 µM for the PfW2 strain, respectively. Further structural optimization may turn them into potential Plasmodial falcipain inhibitors for malaria therapeutics.

Potential inhibitors of RPS6KB2 and NRF2 in head and neck squamous cell carcinoma.

Among the major altered pathways in head and neck squamous cell carcinoma, AKT/mTORC1/S6K and NRF2/KEAP1 pathway are quite significant. The overexpression and overstimulation of proteins from both these pathways makes them the promising candidates in cancer therapeutics. Inhibiting mTOR has been in research from past several decades but the tumour heterogeneity, and upregulation of several compensatory feed-back mechanisms, encourages to explore other downstream targets for inhibiting the pathway. One such downstream effectors of mTOR is S6K2. It is reported to be overexpressed in cancers such as head and neck cancer, breast cancer and prostate cancer. In case of NRF2/KEAP1 pathway, nuclear factor erythroid 2-related factor 2 (NFE2L2 or NRF2) is overexpressed in ∼90% of head and neck squamous cell carcinoma (HNSCC) cases. It associates with poor survival rate and therapeutic resistance in HNSCC treatment. NRF2 pathway is the primary antioxidant pathway in the cell which also serves pro-tumorigenic functions, such as repression of apoptosis, cell proliferation support and chemoresistance. The aim of this work was to explore S6K2 and NRF2 and identify novel and potential inhibitors against them for treating head and neck squamous cell carcinoma. Since the crystal structure of S6K2 was not available at the time of this study, we modelled its structure using homology modelling and performed high throughput screening, molecular dynamics simulations, free energy calculations and protein-ligand interaction studies to identify the inhibitors. We identified natural compounds Crocin and Gypenoside XVII against S6K2 and Chebulinic acid and Sennoside A against NRF2. This study provides a significant in-depth understanding of the two studied pathways and therefore can be used in the development of potential therapeutics against HNSCC.Communicated by Ramaswamy H. Sarma.

In silico identification of colchicine derivatives as novel and potential inhibitors based on molecular docking and dynamic simulations targeting multifactorial drug targets involved in Alzheimer's disease.

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder, characterized by a gradual and steady deterioration in cognitive function over time. At least 50 million people worldwide are considered to have AD or another form of dementia. AD is marked by a gradual decline in cognitive abilities, memory deterioration and neurodegenerative transformations within the brain. The intricate and multifaceted nature of polygenic AD presents significant challenges within the landscape of drug development. The pathophysiology of AD unfolds in a non-linear and dynamic pattern, encompassing various systems and giving rise to a multitude of factors and hypotheses that contribute to the disease's onset. These encompass theories such as the beta-amyloid hypothesis, cholinergic hypothesis, tau hypothesis, oxidative stress and more. In the realm of drug development, polypharmacological drug profiles have emerged as a strategy that can yield combined or synergistic effects, effectively mitigating undesirable side effects and significantly enhancing the therapeutic efficacy of essential medications. With this concept in mind, our in-silico study sought to delve into the binding interactions of a diverse array of colchicine derivative compounds. These derivatives are chosen for their potential anti-inflammatory, antioxidant, anti-neurodegenerative and neuroprotective properties against Alzheimer's and other neurodegenerative diseases. We investigated compound interactions with AD-related targets, utilizing comprehensive molecular docking and dynamic simulations. COM111X showed impressive docking with acetylcholinesterase, indicating potential as an anti-Alzheimer's drug. COM112Y displayed strong docking scores with PDE4D and butyrylcholinesterase, suggesting dual inhibition for Alzheimer's treatment. Further in vitro and in vivo studies are warranted to explore these findings.Communicated by Ramaswamy H. Sarma.

In silico analysis of Diosmetin as an effective chemopreventive agent against prostate cancer: molecular docking, validation, dynamic simulation and pharmacokinetic prediction-based studies.

Prostate cancer is the second most dangerous cancer type worldwide. While various treatment options are present i.e. agonists and antagonists, their utilization leads to adverse effects and due to this resistance developing, ultimately the outcome is remission. So, to overcome this issue, we have undertaken an in-silico investigation to identify promising and unique flavonoid candidates for combating prostate cancer. Using GOLD software, the study assessed the effectiveness of 560 natural secondary polyphenols against CDKN2. Protein Data Bank was used to retrieve the 3D crystal structure of CDKN2 (PDB Id: 4EK3) and we retrieved the structure of selected secondary polyphenols from the PubChem database. The compound Diosmetin shows the highest GOLD score with the selected Protein i.e. CDKN2 which is 58.72. To better understand the 2-dimensional and 3-dimensional interactions, the interacting amino acid residues were visualised using Discovery Studio 3.5 and Maestro 13.5. Using Schrodinger-Glide, the Diosmetin and CDKN2 were re-docked, and decoy ligands were docked to CDKN2, which was used to further ascertain the study. The ligands with the highest Gold score were forecasted for pharmacokinetics characteristics, and the results were tabulated and analysed. Utilising the Gromacs software and Desmond packages, 100 ns of Diosmetin molecular dynamics simulations were run to evaluate the structural persistence and variations of protein-ligand complexes. Additionally, our investigation revealed that Diosmetin had a better binding affinity with CDKN2 measuring 58.72, and it also showed remarkable stability across a 100-ns simulation. Thus, following in-vitro and in-vivo clinical studies, diosmetin might lead to the Prostate regimen.Communicated by Ramaswamy H. Sarma.

In silico identification of small molecule protein-protein interaction inhibitors: targeting hotspot regions at the interface of MXRA8 and CHIKV envelope protein.

Chikungunya virus (CHIKV) is an arthritogenic arbovirus responsible for re-emerging epidemics of Chikungunya fever around the world for centuries. Chikungunya has become endemic in Africa, Southeast Asia, the Indian subcontinent, and subtropical regions of the Americas. The unavailability of antiviral therapy or vaccine against the CHIKV and its continuous re-emergence demands an urgent need to develop potential candidate therapeutics. CHIKV entry into the host cell is mediated by its envelope proteins engaging the cellular receptor MXRA8 to invade the susceptible cells. We report here two essential target binding sites at the CHIKV E1-E2 proteins by identifying hotspot regions at the E1-E2-MXRA8 binding interface. Further, we employed high throughput computational screening to identify potential small molecule protein-protein interaction (PPI) modulators which could effectively bind at the identified target sites. Molecular dynamics simulations and binding free energy calculations confirmed the stability of three compounds, viz., ZINC299817498, ZINC584908978, and LAS52155651, at both the predicted interface binding sites. The polar and charged residues at the interface were responsible for energetically holding the ligands at the binding sites. Altogether, our findings suggest that the predicted target binding sites at the E1-E2 dimer could be essential to block the receptor interaction as well as the fusion process of the CHIKV particles. Thus, we identified a few small molecule PPI inhibitors with great potential to block the E1-E2-MXRA8 interaction and act as promising templates to design anti-CHIKV drugs.Communicated by Ramaswamy H. Sarma.

Identification of potent and novel inhibitors against RAC1: a Rho family GTPase.

Head and Neck Squamous Cell Carcinoma (HNSCC) is one of the most common form of cancer worldwide. It has high incidence and mortality rate making it one of the top causes of cancer related deaths. Tremendous efforts have being made towards treatment of HNSCC but still the overall survival rate hasn't improved much. Unregulated activation of Rho GTPase Ras-related C3 botulinum toxin substrate 1 or Rac1 has been reported in various tumor such as HNSCC, breast cancer, pancreatic cancer, etc. Rac1 is significant in activation and regulation of multiple signaling pathways and it's aberrant activation leads to uncontrolled proliferation, invasion and metastasis which contributes to the hallmarks of cancer. Therefore for treating proliferative disorders such as cancer, inhibition of Rac1 could be a viable approach. Rho GTPases were earlier considered "undruggable" due to their picomolar binding affinity for their guanine nucleotides. In addition presence of high micromolar concentrations of GDP (> 30 µm) and GTP (> 300 µm) in the cell, led to unsuccessful attempts in identification of potent or selective nucleotide competitive GTPase inhibitors. Therefore we identified small molecule inhibitors that target the GEF binding site of the Rho GTPase instead of nucleotide binding site by performing high throughput screening, molecular dynamics simulations, free energy calculations and protein-ligand interaction studies. As a result of this study, we identified four potential inhibitors against RAC1. This study provides a significant in-depth understanding of the Rho GTPases and can prove beneficial in the development of potential therapeutics against HNSCC.

A hybrid resampling algorithms SMOTE and ENN based deep learning models for identification of Marburg virus inhibitors.

Background: Marburg virus (MARV) is a sporadic outbreak of a zoonotic disease that causes lethal hemorrhagic fever in humans. We propose a deep learning model with resampling techniques and predict the inhibitory activity of MARV from unknown compounds in the virtual screening process. Methodology & results: We applied resampling techniques to solve the imbalanced data problem. The classifier model comparisons revealed that the hybrid model of synthetic minority oversampling technique - edited nearest neighbor and artificial neural network (SMOTE-ENN + ANN) achieved better classification performance with 95% overall accuracy. The trained SMOTE-ENN+ANN hybrid model predicted as lead molecules; 25 out of 87,043 from ChemDiv, four out of 340 from ChEMBL anti-viral library, three out of 918 from Phytochemical database, and seven out of 419 from Natural products from NCI divsetIV, and 214 out of 1,12,267 from Natural compounds ZINC database for MARV. Conclusion: Our studies reveal that the proposed SMOTE-ENN + ANN hybrid model can improve overall accuracy more effectively and predict new lead molecules against MARV.

Genome-wide expression reveals potential biomarkers in breast cancer bone metastasis.

Breast cancer metastases are most commonly found in bone, an indication of poor prognosis. Pathway-based biomarkers identification may help elucidate the cellular signature of breast cancer metastasis in bone, further characterizing the etiology and promoting new therapeutic approaches. We extracted gene expression profiles from mouse macrophages from the GEO dataset, GSE152795 using the GEO2R webtool. The differentially expressed genes (DEGs) were filtered by log2 fold-change with threshold 1.5 (FDR < 0.05). STRING database and Enrichr were used for GO-term analysis, miRNA and TF analysis associated with DEGs. Autodock Vienna was exploited to investigate interaction of anti-cancer drugs, Actinomycin-D and Adriamycin. Sensitivity and specificity of DEGs was assessed using receiver operating characteristic (ROC) analyses. A total of 61 DEGs, included 27 down-regulated and 34 up-regulated, were found to be significant in breast cancer bone metastasis. Major DEGs were associated with lipid metabolism and immunological response of tumor tissue. Crucial DEGs, Bcl3, ADGRG7, FABP4, VCAN, and IRF4 were regulated by miRNAs, miR-497, miR-574, miR-138 and TFs, CCDN1, STAT6, IRF8. Docking analysis showed that these genes possessed strong binding with the drugs. ROC analysis demonstrated Bcl3 is specific to metastasis. DEGs Bcl3, ADGRG7, FABP4, IRF4, their regulating miRNAs and TFs have strong impact on proliferation and metastasis of breast cancer in bone tissues. In conclusion, present study revealed that DEGs are directly involved in of breast tumor metastasis in bone tissues. Identified genes, miRNAs, and TFs can be possible drug targets that may be used for the therapeutics. However, further experimental validation is necessary.

The tetrameric structure of Plasmodium falciparum phosphoglycerate mutase is critical for optimal enzymatic activity.

The glycolytic enzyme phosphoglycerate mutase (PGM) is of utmost importance for overall cellular metabolism and has emerged as a novel therapeutic target in cancer cells. This enzyme is also conserved in the rapidly proliferating malarial parasite Plasmodium falciparum, which have a similar metabolic framework as cancer cells and rely on glycolysis as the sole energy-yielding process during intraerythrocytic development. There is no redundancy among the annotated PGM enzymes in Plasmodium, and PfPGM1 is absolutely required for the parasite survival as evidenced by conditional knockdown in our study. A detailed comparison of PfPGM1 with its counterparts followed by in-depth structure-function analysis revealed unique attributes of this parasitic protein. Here, we report for the first time the importance of oligomerization for the optimal functioning of the enzyme in vivo, as earlier studies in eukaryotes only focused on the effects in vitro. We show that single point mutation of the amino acid residue W68 led to complete loss of tetramerization and diminished catalytic activity in vitro. Additionally, ectopic expression of the WT PfPGM1 protein enhanced parasite growth, whereas the monomeric form of PfPGM1 failed to provide growth advantage. Furthermore, mutation of the evolutionarily conserved residue K100 led to a drastic reduction in enzymatic activity. The indispensable nature of this parasite enzyme highlights the potential of PfPGM1 as a therapeutic target against malaria, and targeting the interfacial residues critical for oligomerization can serve as a focal point for promising drug development strategies that may not be restricted to malaria only.

In-silico prediction of potential inhibitors against phosphatidylinositol 3-kinase catalytic subunit alpha involved in head and neck squamous cell carcinomas.

Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers, globally. Its high mortality rates remained unaltered in the last three decades, therefore, there is an enormous need for novel therapeutics. The most frequent somatically mutated oncogenic pathway in HNSCC tumors is the Phosphatidylinositol-3-kinases (PI3K) pathway. PI3Ks are lipid kinases involved in the regulation of cell survival, growth and metabolism. PI3Ks phosphorylates PI (4,5) P2 (PIP2) converting it to PI (3, 4, 5) P3 (PIP3). Alterations such as mutation, gene amplification and overexpression in PIK3CA, encoding the catalytic subunit p110α of PI3K pathway were found to be prevalent. The aberrant activation leads to irregulated cell growth due to improper p110α enzymatic activity. p110α is therefore, considered a potential oncogenic target for cancer therapy. The only FDA approved specific inhibitor of p110α is Alpelisib (BYL719). Therefore, designing more effective and specific p110α inhibitors could be a promising strategy in the treatment of HNSCC. The present study aims to find out the potent and novel inhibitors of p110α using High Throughput Screening (HTS) of huge databases (National Cancer Institute (NCI), Life Chemicals, ChemDiv and ChEMBL) and Molecular Dynamic Simulations. As a result, from more than 400,000 compounds, a total of 3 best candidate compounds (Echinacoside, Isoacteoside, K284-4402) were selected and validated for their binding to catalytic site of p110α and stability during Molecular Dynamics (MD) simulations. The binding free energy (calculated from MM-PBSA) of the selected compounds, Echinacoside, Isoacteoside, K284-4402 were -23.43 kcal/mol, -33.02 kcal/mol and -30.57 kcal/mol, respectively, which suggested these compounds bind to p110α with higher affinity than Alpelisib which has binding free energy -20.9 kcal/mol. This study provides a significant in-depth understanding of p110α inhibitors that can be used in the development of potential therapeutics against HNSCC.Communicated by Ramaswamy H. Sarma.

Noncovalent molecular interactions between antineoplastic drug gemcitabine and a carrier protein identified through spectroscopic and in silico methods.

Herein we have studied the noncovalent molecular interactions between hen egg white lysozyme (HEWL) and the commonly employed antineoplastic drug gemcitabine through the cumulative implementation of spectroscopic techniques and in silico approaches. The formation of a complex between HEWL and gemcitabine was made evident by the differences between the UV-visible spectra of the protein and protein-gemcitabine complex. Fluorescence quenching of HEWL by gemcitabine was hardly detectable at room temperature, but it became prominent at higher temperatures. Very low values for the bimolecular quenching constant and the non-reciprocal dependence of quenching on temperature indicated that dynamic quenching was taking place. Analysis of experimental data indicated that the interaction was dominated by hydrophobic forces, while the results of a computational investigation suggested the concomitant contribution of hydrogen bonding. Gemcitabine binding induced modifications of the secondary structure of HEWL by slightly increasing the α-helical content of the protein. Finally, gemcitabine binding site was inferred to be located in HEWL big hydrophobic cavity.

Deep learning model for virtual screening of novel 3C-like protease enzyme inhibitors against SARS coronavirus diseases.

In the context of the recently emerging COVID-19 pandemic, we developed a deep learning model that can be used to predict the inhibitory activity of 3CLpro in severe acute respiratory syndrome coronavirus (SARS-CoV) for unknown compounds during the virtual screening process. This paper proposes a novel deep learning-based method to implement virtual screening with convolutional neural network (CNN) architecture. The descriptors represent chemical molecules, and these descriptors are input into the CNN framework to train a model and predict active compounds. When compared to other machine learning methods, including random forest, naive Bayes, decision tree, and support vector machine, the proposed CNN model's evaluation of the test set showed an accuracy of 0.86, a sensitivity of 0.45, a specificity of 0.96, a precision of 0.73, a recall of 0.45, an F-measure of 0.55, and a ROC of 0.71. The CNN model screened 17 out of 918 phytochemical compounds; 60 out of 423 from the natural product NCI divset IV; 17,831 out of 112,267 from the ZINC natural product database; and 315 out of 1556 FDA-approved drugs as anti-SARS-CoV agents. Further, to prioritize drug-like compounds, Lipinski's rule of five was applied to screen anti-SARS-CoV compounds (excluding FDA-approved drugs), resulting in 10, 59, and 14,025 hit molecules. Out of 10 phytochemical compounds, 9 anti-SARS-CoV agents belonged to the flavonoid group. In conclusion, the proposed CNN model can prove useful for developing novel target-specific anti-SARS-CoV compounds.

New Framework for the Discovery of PRC2 Inhibitors: Epigenetic Drugs.

Over the past several years, remarkable progress towards the recognition of new therapeutic targets in tumor cells has led to the discovery and development of newer scaffolds of anti-tumor drugs. The exploration and exploitation of epigenetic regulation in tumor cells are of immense importance to both the pharmaceutical and academic biomedical literatures. Epigenetic mechanisms are indispensable for the normal development and maintenance of tissue-specific gene expression. Disruption of epigenetic processes to eradicate tumor cells is among the most promising intervention for cancer control. Polycomb repressive complex 2 (PRC2), a complex that methylates lysine 27 of histone H3 to promote transcriptional silencing, is involved in orchestrating significant pathways in a cell. Overexpression of PRC2 has been found in a number of cancerous malignancies, making it a major target for anti-cancer therapy. Despite its well-understood molecular mechanism, hyperactivation and drug resistance mutations in its subunits have become a matter of discussion. This review outlines the current understanding of the components of PRC2 in active complex formation and assesses their potential as a promising therapeutic target for cancer therapy. We also review the effects of mutations in the PRC2 components, in the purview of human cancers. Finally, we discuss some of the current challenges for therapeutic drug designs targeting the PRC2 complex.

Current and Future Therapeutic Targets: A Review on Treating Head and Neck Squamous Cell Carcinoma.

Head and neck squamous cell carcinoma (HNSCC) continues to be a global public health burden even after a tremendous development in its treatment. It is a heterogeneous cancer of upper aero-digestive tract. The contemporary strategy to treat cancer is the use of anticancer drugs against proteins possessing abnormal expression. Targeted chemotherapy was found successful in HNSCC, but, there is still a stagnant improvement in the survival rates and high recurrence rates due to undesirable chemotherapy reactions, non-specificity of drugs, resistance against drugs and drug toxicity on non-cancerous tissues and cells. Various extensive studies lead to the identification of drug targets capable to treat HNSCC effectively. The current review article gives an insight into these promising anticancer targets along with knowledge of drugs under various phases of development. In addition, new potential targets that are not yet explored against HNSCC are also described. We believe that exploring and developing drugs against these targets might prove beneficial in treating HNSCC.

Exploring Molecular Descriptors and Fingerprints to Predict mTOR Kinase Inhibitors using Machine Learning Techniques.

Mammalian Target of Rapamycin (mTOR) is a Ser/Thr protein kinase, and its role is integral to the autophagy pathway in cancer. Targeting mTOR for therapeutic interventions in cancer through autophagy pathway is challenging due to the dual roles of autophagy in tumor progression. The architecture of mTOR reveals two complexes - mTORC1 and mTORC2, each having multiple protein subunits. mTOR kinase inhibitors target the structurally and functionally similar catalytic subunits of both mTORC1 and mTORC2. In this paper, we have explored two different categories of molecular features - descriptors and fingerprints for developing predictive models using machine learning techniques. Random Forest variable importance measures and autoencoders are used to identify molecular descriptors and fingerprints, respectively. We have built various predictive models using identified features and their combination for predicting mTOR kinase inhibitors. Finally, the best model based on the Mathew correlation co-efficient value over the validation dataset is selected for screening kinase SARfari bioactivity dataset. In this study, we have identified twenty best performing descriptors for predicting mTOR kinase inhibitors. To the best of our knowledge, it is the first study on integrating traditional machine learning and deep learning-based approaches for feature extraction to predict mTOR kinase inhibitors.

Design and in vitro analysis of SIRT2 inhibitor targeting Parkinson's disease.

Inhibition of Sirtuin2 (SIRT2) protein rescues the α-synuclein toxicity in vitro and in vivo models of Parkinson's disease (PD). Thioacetyl group can structurally mimic the acetyl group and restrain the deacetylating p53 reaction by SIRT2. This work evaluated the biological activity of designed pentapeptides inhibitor containing N-thioacetyl-lysine against SIRT2. Pentapeptide by introducing thioacetyl-lysine as an inhibitor of SIRT2 was screened by molecular docking and synthesized by solid phase method. The inhibition of pure recombinant SIRT2 as well as SIRT2 in serum of PD patients by peptide was done by fluorescent activity assay. The inhibition of SIRT2 was assessed in PC12 cell line by measuring acetylated α-tubulin level. The peptide YKK(ε-thioAc)AM and HRK(ε-thioAc)AM were found to be SIRT2 inhibitors by molecular docking. However, YKK(ε-thioAc)AM was more specific towards SIRT2 than SIRT1 (Sirtuin1). It inhibited recombinant SIRT2 by IC50 value of 0.15 µM and KD values 9.92 × 10-8/M. It also inhibited serum SIRT2 of PD. It increased the acetylation of α-tubulin in PC12 neuroblastoma cells which is essential for maintaining the microtubular cell functions of brain. It can be concluded that novel peptide YKK(ε-thioAc)AM may be a platform for therapeutic agent for Parkinson's disease targeting SIRT2.

Envelope proteins as antiviral drug target.

Attachment of a virus with a specific receptor on the cell surface is the first and foremost step in virus infection. In case of enveloped viruses, their interaction with the host cell receptor is mediated by viral encoded glycoproteins on its envelope, a host derived lipid bilayer. Since, virus entry is a multistep process, after receptor recognition, envelope proteins mediate internalisation of virus particles into the host cell. Envelope glycoproteins are the first proteins that the host immune system encounters upon infection. Thus, envelope proteins are important drug target with multiple strategies to inhibit entry of the virus into the host. Currently, there are very few drugs that function as envelope protein inhibitors which are approved for human use. Here, we reviewed different classes of envelope proteins of various viruses and emphasised the use of small molecules to inhibit fusion of envelope proteins. Based on the available information in the literature, envelope proteins can be important drug targets and small molecules inhibitors can serve as potential antiviral drugs to block viral infection at an initial stage.

CID-6033590 inhibits p38MAPK pathway and induces S-phase cell cycle arrest and apoptosis in DU145 and PC-3 cells.

Metastatic prostate cancer, with no effective treatment, is among the leading causes of cancer-associated deaths in men. Overexpression of p38αMAPK has been observed in neuroendocrine prostate cancer patients and in both DU145 and PC-3 cell lines and represents a good drug target. Sulfonamide derivatives have shown biological activities against many human diseases, including cancer. CID-6033590, a sulfonylhydrazide compound, screened from PubChem database by molecular docking with p38αMAPK, was evaluated for anti-cancerous activities. CID-6033590 induced toxicity in both DU145 and PC-3 cells in a concentration and time-dependent manner with an IC50 value of 60 µM and 66 µM, respectively. Sub-cytotoxic concentrations of the compound significantly induced S-phase cell cycle arrest, inhibited cyclinA/CDK2 complex and blocked cell proliferation. Further, CID-6033590 downregulated phosphorylation of p38MAPK (P-p38) as well as its downstream targets, Activating transcription factor 2 (ATF-2) and Heat shock protein 27 (Hsp27). The compound increased ROS and decreased mitochondrial membrane potential (Δψm), downregulated Bcl-2 and survivin and cleaved poly ADP ribose polymerase (PARP) and caspase-3, indicating the induction of apoptosis. The evaluaion of the compound on noncancerous, human prostatic epithelial cell line RWPE-1, and healthy murine tissues yielded no significant toxicity. Taken together, we suggest CID-6033590 as a potential candidate for prostate cancer therapy.

Enhancement in the Catalytic Activity of Human Salivary Aldehyde Dehydrogenase by Alliin from Garlic: Implications in Aldehyde Toxicity and Oral Health.

BACKGROUND: Lower human salivary aldehyde dehydrogenase (hsALDH) activity increases the risk of aldehyde mediated pathogenesis including oral cancer. Alliin, the bioactive compound of garlic, exhibits many beneficial health effects. OBJECTIVE: To study the effect of alliin on hsALDH activity. METHODS: Enzyme kinetics was performed to study the effect of alliin on the activity of hsALDH. Different biophysical techniques were employed for structural and binding studies. Docking analysis was done to predict the binding region and the type of binding forces. RESULTS: Alliin enhanced the dehydrogenase activity of the enzyme. It slightly reduced the Km and significantly enhanced the Vmax value. At 1 µM alliin concentration, the initial reaction rate increased by about two times. Further, it enhanced the hsALDH esterase activity. Biophysical studies indicated a strong complex formation between the enzyme and alliin (binding constant, Kb: 2.35 ± 0.14 x 103 M-1). It changes the secondary structure of hsALDH. Molecular docking study indicated that alliin interacts to the enzyme near the substrate binding region involving some active site residues that are evolutionary conserved. There was a slight increase in the nucleophilicity of active site cysteine in the presence of alliin. Ligand efficiency metrics values indicate that alliin is an efficient ligand for the enzyme. CONCLUSION: Alliin activates the catalytic activity of the enzyme. Hence, consumption of alliincontaining garlic preparations or alliin supplements and use of alliin in pure form may lower aldehyde related pathogenesis including oral carcinogenesis.