Current Topics in Medicinal Chemistry - Volume 19, Issue 2, 2019

Identification of B-cell epitopes in target antigens is one of the most crucial steps for epitopebased vaccine development, immunodiagnostic tests, antibody production, and disease diagnosis and therapy. Experimental methods for B-cell epitope mapping are time consuming, costly and labor intensive; in the meantime, various in-silico methods are proposed to predict both linear and conformational B-cell epitopes. The accurate identification of B-cell epitopes presents major challenges for immunoinformaticians. In this paper, we have comprehensively reviewed in-silico methods for B-cell epitope identification. The aim of this review is to stimulate the development of better tools which could improve the identification of B-cell epitopes, and further for the development of therapeutic antibodies and diagnostic tools.

Several phenolic compounds bind to proteins (such as enzymes) and interfere in their catalytic mechanism. Interaction studies of natural polyphenol; Resveratrol with various targets like with tubulin, protein kinase C alpha (PKCα), phosphodiesterase-4D, human oral cancer cell line proteins, DNA sequences having AATT/TTAA segments, protein kinase C alpha, lysine-specific demethylase 1 have been reviewed in this article. Simulation studies indicate that resveratrol and its analogs/ derivatives show good interaction with the target receptor through its hydroxyl groups by forming hydrogen bonds and hydrophobic interactions with amino acid residues at the binding site. Binding geometry and stability of complex formed by resveratrol show that it is a good inhibitor for many pathogenic targets. Further studies in this direction is, however, the need of the hour to develop many more ligands based on resveratrol skeleton which can further serve in the treatment of ailments.

Background: A large number of disorders and their symptoms emerge from deficiency or overproduction of specific metabolites has drawn the attention for the discovery of new therapeutic agents for the treatment of disorders. Various approaches such as computational drug design have provided the new methodology for the selection and evaluation of target protein and the lead compound mechanistically. For instance, the overproduction of xanthine oxidase causes the accumulation of uric acid which can prompt gout. Objective: In the present study we critically discussed the various techniques such as 3-D QSAR and molecular docking for the study of the natural based xanthine oxidase inhibitors with their mechanistic insight into the interaction of xanthine oxidase and various natural leads. Conclusion: The computational studies of deferent natural compounds were discussed as a result the flavonoids, anthraquinones, xanthones shown the remarkable inhibitory potential for xanthine oxidase inhibition moreover the flavonoids such as hesperidin and rutin were found as promising candidates for further exploration.

Introduction: It is well-known that the biogeography-based optimization (BBO) algorithm lacks searching power in some circumstances. Material & Methods: In order to address this issue, an adaptive opposition-based biogeography-based optimization algorithm (AO-BBO) is proposed. Based on the BBO algorithm and opposite learning strategy, this algorithm chooses different opposite learning probabilities for each individual according to the habitat suitability index (HSI), so as to avoid elite individuals from returning to local optimal solution. Meanwhile, the proposed method is tested in 9 benchmark functions respectively. Result: The results show that the improved AO-BBO algorithm can improve the population diversity better and enhance the search ability of the global optimal solution. The global exploration capability, convergence rate and convergence accuracy have been significantly improved. Eventually, the algorithm is applied to the parameter optimization of soft-sensing model in plant medicine extraction rate. Conclusion: The simulation results show that the model obtained by this method has higher prediction accuracy and generalization ability.

Background: Protein-Protein interaction (PPI) network analysis of virulence proteins of Aspergillus fumigatus is a prevailing strategy to understand the mechanism behind the virulence of A. fumigatus. The identification of major hub proteins and targeting the hub protein as a new antifungal drug target will help in treating the invasive aspergillosis. Materials & Method: In the present study, the PPI network of 96 virulence (drug target) proteins of A. fumigatus were investigated which resulted in 103 nodes and 430 edges. Topological enrichment analysis of the PPI network was also carried out by using STRING database and Network analyzer a cytoscape plugin app. The key enriched KEGG pathway and protein domains were analyzed by STRING. Conclusion: Manual curation of PPI data identified three proteins (PyrABCN-43, AroM-34, and Glt1- 34) of A. fumigatus possessing the highest interacting partners. Top 10% hub proteins were also identified from the network using cytohubba on the basis of seven algorithms, i.e. betweenness, radiality, closeness, degree, bottleneck, MCC and EPC. Homology model and the active pocket of top three hub proteins were also predicted.

Background: Monoamine oxidase (MAO) is a critical target used for the cure of neuropsychological diseases. Objective: A series of quercetin based derivatives was designed, synthesized, and evaluated as novel multifunctional agents against monoamine oxidase A and B with antioxidant potential. Methods: Hybrid derivatives based on quercetin were synthesized and screened for hMAO inhibition along with antioxidant activity. Molecular docking was performed to explicate the rationale of the different MAO (IC50) values and to explain the presence of inhibitory activity against specificity, respectively. Results: The results of in vitro hMAO inhibition showed that compound 8a, 6c, and 4 were found as potent hMAO-A inhibitors whereas compounds 6b, 6a, and 6d were observed as potent hMAO-B inhibitors. The DPPH radical scavenging activity showed that compounds 6b, 6a, and 4 exhibited a promising antioxidant potential with IC50 values 5.931±0.007, 6.421±0.037, and 8.516±0.098 respectively. Moreover, the compound 6b, 6a, and 4 exhibited remarkable H2O2 scavenging potential with IC50 values 05.80±0.004 μM, 06.20±0.009 μM, and 07.66±0.009 μM respectively. Conclusion: The results of docking studies were found in good correlation with experimental MAO inhibition studies. Moreover, the mechanistic insight into the docking poses was also explored by binding interactions of quercetin based derivatives inside the dynamic site of hMAO-A and hMAO-B. It was also noticed that the potent MAO inhibitors were also acting as better antioxidants as evaluated through DPPH radical scavenging activity and H2O2 radical scavenging assay.