Mohammad Uzzal Hossain

A comprehensive immunoinformatics and target site study revealed the corner-stone toward Chikungunya virus treatment

Abstract Recent concerning facts of Chikungunya virus (CHIKV); a Togaviridae family alphavirus has proved this as a worldwide emerging threat which causes Chikungunya fever and devitalizing arthritis. Despite severe outbreaks and lack of antiviral drug, a mere progress has been made regarding to an epitope-based vaccine designed for CHIKV. In this study, we aimed to design an epitope-based vaccine that can trigger a significant immune response as well as to prognosticate inhibitor that can bind with potential drug target sites by using various immunoinformatics and docking simulation tools. Initially, whole proteome of CHIKV was retrieved from database and perused to identify the most immunogenic protein. Structural properties of the selected protein were analyzed. The capacity to induce both humoral and cell-mediated immunity by T cell and B cell were checked for the selected protein. The peptide region spanning 9 amino acids from 397 to 405 and the sequence YYYELYPTM were found as the most potential B cell and T cell epitopes respectively. This peptide could interact with as many as 19 HLAs and showed high population coverage ranging from 69.50% to 84.94%. By using in silico docking techniques the epitope was further assessed for binding against HLA molecules to verify the binding cleft interaction. In addition with this, the allergenicity of the epitopes was also evaluated. In the post therapeutic strategy, three dimensional structure was predicted along with validation and verification that resulted in molecular docking study to identify the potential drug binding sites and suitable therapeutic inhibitor against targeted protein. Finally, pharmacophore study was also performed in quest of seeing potent drug activity. However, this computational epitope-based peptide vaccine designing and target site prediction against CHIKV opens up a new horizon which may be the prospective way in Chikungunya virus research; the results require validation by in vitro and in vivo experiments.

Epitope‐based peptide vaccine design and target site depiction against Ebola viruses: an immunoinformatics study

Ebola viruses (EBOVs) have been identified as an emerging threat in recent year as it causes severe haemorrhagic fever in human. Epitope‐based vaccine design for EBOVs remains a top priority because a mere progress has been made in this regard. Another reason is the lack of antiviral drug and licensed vaccine although there is a severe outbreak in Central Africa. In this study, we aimed to design an epitope‐based vaccine that can trigger a significant immune response as well as to prognosticate inhibitor that can bind with potential drug target sites using various immunoinformatics and docking simulation tools. The capacity to induce both humoral and cell‐mediated immunity by T cell and B cell was checked for the selected protein. The peptide region spanning 9 amino acids from 42 to 50 and the sequence TLASIGTAF were found as the most potential B and T cell epitopes, respectively. This peptide could interact with 12 HLAs and showed high population coverage up to 80.99%. Using molecular docking, the epitope was further appraised for binding against HLA molecules to verify the binding cleft interaction. In addition with this, the allergenicity of the epitopes was also evaluated. In the post‐therapeutic strategy, docking study of predicted 3D structure identified suitable therapeutic inhibitor against targeted protein. However, this computational epitope‐based peptide vaccine designing and target site prediction against EBOVs open up a new horizon which may be the prospective way in Ebola viruses research; the results require validation by in vitro and in vivo experiments.

Treating Diabetes Mellitus: Pharmacophore Based Designing of Potential Drugs from Gymnema sylvestre against Insulin Receptor Protein.

Diabetes mellitus (DM) is one of the most prevalent metabolic disorders which can affect the quality of life severely. Injectable insulin is currently being used to treat DM which is mainly associated with patient inconvenience. Small molecules that can act as insulin receptor (IR) agonist would be better alternatives to insulin injection. Herein, ten bioactive small compounds derived from Gymnema sylvestre (G. sylvestre) were chosen to determine their IR binding affinity and ADMET properties using a combined approach of molecular docking study and computational pharmacokinetic elucidation. Designing structural analogues were also performed for the compounds associated with toxicity and less IR affinity. Among the ten parent compounds, six were found to have significant pharmacokinetic properties with considerable binding affinity towards IR while four compounds were associated with toxicity and less IR affinity. Among the forty structural analogues, four compounds demonstrated considerably increased binding affinity towards IR and less toxicity compared with parent compounds. Finally, molecular interaction analysis revealed that six parent compounds and four analogues interact with the active site amino acids of IR. So this study would be a way to identify new therapeutics and alternatives to insulin for diabetic patients.

Identification of highly conserved regions in L-segment of Crimean-Congo hemorrhagic fever virus and immunoinformatic prediction about potential novel vaccine.

Crimean–Congo hemorrhagic fever (CCHF) is a tick-borne zoonotic viral disease with a disease fatality rate between 15% and 70%. Despite the wide range of distribution, the virus (CCHFV) is basically endemic in Africa, Asia, eastern Europe, and the Middle East. Acute febrile illness associated with petechiae, disseminated intravascular coagulation, and multiple-organ failure are the main symptoms of the disease. With all these fatal effects, CCHFV is considered a huge threat as no successful therapeutic approach is currently available for the treatment of this disease. In the present study, we have used the immunoinformatics approach to design a potential epitope-based vaccine against the RNA-dependent RNA polymerase-L of CCHFV. Both the T-cell and B-cell epitopes were assessed, and the epitope “DCSSTPPDR” was found to be the most potential one, with 100% conservancy among all the strains of CCHFV. The epitope was also found to interact with both type I and II major histocompatibility complex molecules and is considered nonallergenic as well. In vivo study of our proposed peptide is advised for novel universal vaccine production, which might be an effective path to prevent CCHF disease.

Therapeutics Insight with Inclusive Immunopharmacology Explication of Human Rotavirus A for the Treatment of Diarrhea

Rotavirus is the most common cause of severe infant and childhood diarrhea worldwide, and the morbidity and mortality rate is going to be outnumbered in developing countries like Bangladesh. To mitigate this substantial burden of disease, new therapeutics such as vaccine and drug are swiftly required against rotavirus. The present therapeutics insight study was performed with comprehensive immunoinformatics and pharmacoinformatics approach. T and B-cell epitopes were assessed in the conserved region of outer capsid protein VP4 among the highly reviewed strains from different countries including Bangladesh. The results suggest that epitope SU1 (TLKNLNDNY) could be an ideal candidate among the predicted five epitopes for both T and B-cell epitopes for the development of universal vaccine against rotavirus. This research also suggests five novel drug compounds from medicinal plant Rhizophora mucronata Lamk. for better therapeutics strategies against rotavirus diarrhea based on 3D structure building, pharmacophore, ADMET, and QSAR properties. The exact mode of action between drug compounds and target protein VP4 were revealed by molecular docking analysis. Drug likeness and oral bioavailability further confirmed the effectiveness of the proposed drugs against rotavirus diarrhea. This study might be implemented for experimental validation to facilitate the novel vaccine and drug design.

Identification of potential inhibitor and enzyme-inhibitor complex on trypanothione reductase to control Chagas disease

Chagas is a parasitic disease with major threat to public health due to its resistance against commonly available drugs. Trypanothione reductase (TryR) is the key enzyme to develop this disease. Though this enzyme is well thought-out as potential drug target, the accurate structure of enzyme-inhibitor complex is required to design a potential inhibitor which is less available for TryR. In this research, we aimed to investigate the advanced drug over the available existing drugs by designing inhibitors as well as to identify a new enzyme-inhibitor complex that may act as a template for drug design. A set of analogues were designed from a known inhibitor Quinacrine Mustard (QUM) to identify the effective inhibitor against this enzyme. Further, the pharmacoinformatics elucidation and structural properties of designed inhibitor proposed effective drug candidates against Chagas disease. Molecular docking study suggests that a designed inhibitor has higher binding affinity in both crystal and modeled TryR and also poses similar interacting residues as of crystal TryR-QUM complex structure. The comparative studies based on in silico prediction proposed an enzyme-inhibitor complex which could be effective to control the disease activity. So our in silico analysis based on TryR built model, Pharmacophore and docking analysis might play an important role for the development of novel therapy for Chagas disease. But both animal model experiments and clinical trials must be done to confirm the efficacy of the therapy.

Molecular Characterization of Legionellosis Drug Target Candidate Enzyme Phosphoglucosamine Mutase from Legionella pneumophila (strain Paris): An In Silico Approach

The harshness of legionellosis differs from mild Pontiac fever to potentially fatal Legionnaires disease. The increasing development of drug resistance against legionellosis has led to explore new novel drug targets. It has been found that phosphoglucosamine mutase, phosphomannomutase, and phosphoglyceromutase enzymes can be used as the most probable therapeutic drug targets through extensive data mining. Phosphoglucosamine mutase is involved in amino sugar and nucleotide sugar metabolism. The purpose of this study was to predict the potential target of that specific drug. For this, the 3D structure of phosphoglucosamine mutase of Legionella pneumophila (strain Paris) was determined by means of homology modeling through Phyre2 and refined by ModRefiner. Then, the designed model was evaluated with a structure validation program, for instance, PROCHECK, ERRAT, Verify3D, and QMEAN, for further structural analysis. Secondary structural features were determined through self-optimized prediction method with alignment (SOPMA) and interacting networks by STRING. Consequently, we performed molecular docking studies. The analytical result of PROCHECK showed that 95.0% of the residues are in the most favored region, 4.50% are in the additional allowed region and 0.50% are in the generously allowed region of the Ramachandran plot. Verify3D graph value indicates a score of 0.71 and 89.791, 1.11 for ERRAT and QMEAN respectively. Arg419, Thr414, Ser412, and Thr9 were found to dock the substrate for the most favorable binding of S-mercaptocysteine. However, these findings from this current study will pave the way for further extensive investigation of this enzyme in wet lab experiments and in that way assist drug design against legionellosis.

Towards finding the linkage between metabolic and age-related disorders using semantic gene data network analysis.

A metabolic disorder (MD) occurs when the metabolic process is disturbed. This process is carried out by thousands of enzymes participating in numerous inter-dependent metabolic pathways. Critical biochemical reactions that involve the processing and transportation of carbohydrates, proteins and lipids are affected in metabolic diseases. Therefore, it is of interest to identify the common pathways of metabolic disorders by building protein-protein interactions (PPI) for network analysis. The molecular network linkages between MD and age related diseases (ARD) are intriguing. Hence, we created networks of protein-protein interactions that are related with MD and ARD using relevant known data in the public domain. The network analysis identified known MD associated proteins and predicted genes and or its products of ARD in common pathways. The genes in the common pathways were isolated from the network and further analyzed for their co-localization and shared domains. Thus, a model hypothesis is proposed using interaction networks that are linked between MD and ARD. This data even if less conclusive finds application in understanding the molecular mechanism of known diseases in relation to observed molecular events

Novel insights on ENTH domain-containing proteins in apicomplexan parasites

The phylum Apicomplexa includes a large group of early branching eukaryotes having significant medical and economical importance. The molecular machinery responsible for protein trafficking is poorly understood in these apicomplexans. One of the most important proteins involved in clathrin-mediated protein trafficking is Epsin, which contains ENTH domain, a conserved domain crucial for membrane bending leading to vesicle formation. We undertook homology searching and phylogenetic analyses to produce a rigorously annotated set of Epsin homologs retrieved from diverse apicomplexan genomes. Genomic and phylogenetic comparisons revealed that apicomplexans contain unusual Epsin homologs that are distinct from those observed in mammals and yeast. Although there are four Epsin genes in mammalian system and five in the yeast genome, apicomplexan parasites consist only a single Epsin gene. The apicomplexan Epsin contains the conserved ENTH domain consisting of phosphoinositide (PtdIns)-binding sites which indicate about their functional significance in the formation of vesicles; however, the absence of ubiquitin-interacting motif (UIM) suggests a possible different mechanism for protein trafficking. The existence of dileucine motif in Plasmodium, Cryptosporidum parvum and Eimeria tenella Epsins might solve their functionality while lacking a lot of conserved motifs as this motif is known to interact with different adaptor protein complexes (AP1, AP2 and AP3). Other Epsin homologs are also shown to have different peptide motifs reported for possible interaction with α-ear appendage, γ-ear appendage and EH domain present in different adaptors. Bioinformatic and phylogenetic analyses suggest that the apicomplexan Epsins have unusual functionality from that of the mammalian Epsins. This detailed study may greatly facilitate future molecular cell biological investigation for the role of Epsins in these parasites.

Finding Potential Therapeutic Targets against Shigella flexneri through Proteome Exploration

Background: Shigella flexneri is a gram negative bacteria that causes the infectious disease “shigellosis.” S. flexneri is responsible for developing diarrhea, fever, and stomach cramps in human. Antibiotics are mostly given to patients infected with shigella. Resistance to antibiotics can hinder its treatment significantly. Upon identification of essential therapeutic targets, vaccine and drug could be effective therapy for the treatment of shigellosis. Methods: The study was designed for the identification and qualitative characterization for potential drug targets from S. flexneri by using the subtractive proteome analysis. A set of computational tools were used to identify essential proteins those are required for the survival of S. flexneri. Total proteome (13,503 proteins) of S. flexneri was retrieved from NCBI and further analyzed by subtractive channel analysis. After identification of the metabolic proteins we have also performed its qualitative characterization to pave the way for the identification of promising drug targets. Results: Subtractive analysis revealed that a list of 53 targets of S. flexneri were human non-homologous essential metabolic proteins that might be used for potential drug targets. We have also found that 11 drug targets are involved in unique pathway. Most of these proteins are cytoplasmic, can be used as broad spectrum drug targets, can interact with other proteins and show the druggable properties. The functionality and drug binding site analysis suggest a promising effective way to design the new drugs against S. flexneri. Conclusion: Among the 53 therapeutic targets identified through this study, 13 were found highly potential as drug targets based on their physicochemical properties whilst only one was found as vaccine target against S. flexneri. The outcome might also be used as module as well as circuit design in systems biology.