Prevalence and risk factors associated with Q fever infection in slaughterhouse workers in Fars province, Iran.

OBJECTIVE: Q fever is a main occupational zoonotic disease. Slaughterhouse is one of the most remarkable ways of transmitting the infection from livestock to humans. This study aimed to survey the prevalence of Q fever in slaughterhouse workers in Fars province, Iran, for the first time. METHODS: Ninety serum samples were collected from slaughterhouse workers and tested to detect Immunoglobulin G (IgG) against Coxiella burnetii using ELISA and indirect immunofluorescence assay (IFA). PCR was also applied to identify C. burnetii DNA in the blood samples. RESULTS: Q fever seroprevalence was found at 26.7% in ELISA, showing recent infection. This result indicates that Q fever seroprevalence is relatively high in the Fars region. IFA showed a high seroprevalence of total IgG antibodies at 1:64 titer (73.3%) and relatively high IgG at 1:256 titer (40%) against C. burnetii. 2.2% of the workers were recognized as having probable acute Q fever. The IgG II prevalence at 1:64 and 1:256 titers was, respectively, 63.3% and 24.4% positive. The IgG I prevalence at 1:64 and 1:256 titers was also found 33.3% and 22.2% positive, respectively. Molecular prevalence of Q fever was also 8.9%. A significant relationship was found between IgG I seropositivity and longer work experience and employing other livestock-related jobs (animal husbandry and butchery) (P < 0.05). CONCLUSIONS: As such, the high seroprevalence of Q fever among abattoir workers highlights the importance of further comprehensive epidemiological studies, occupational screening programs, and preventive measures for Q fever in high-risk groups. This also warns animal health care organizations about the risk of Q fever infection in livestock in this region.

Impact of SNPs, off-targets, and passive permeability on efficacy of BCL6 degrading drugs assigned by virtual screening and 3D-QSAR approach.

B-cell lymphoma 6 (BCL6) regulates various genes and is reported to be overexpressed in lymphomas and other malignancies. Thus, BCL6 inhibition or its tagging for degradation would be an amenable therapeutic approach. A library of 2500 approved drugs was employed to find BCL6 inhibitory molecules via virtual screening. Moreover, the 3D core structure of 170 BCL6 inhibitors was used to build a 3D QSAR model and predict the biological activity. The SNP database was analyzed to study the impact on the destabilization of BCL6/drug interactions. Structural similarity search and molecular docking analyses were used to assess the interaction between possible off-targets and BCL6 inhibitors. The tendency of drugs for passive membrane permeability was also analyzed. Lifitegrast (DB11611) had favorable binding properties and biological activity compared to the BI-3802. Missense SNPs were located at the essential interaction sites of the BCL6. Structural similarity search resulted in five BTB-domain containing off-target proteins. BI-3802 and Lifitegrast had similar chemical behavior and binding properties against off-target candidates. More interestingly, the binding affinity of BI-3802 (against off-targets) was higher than Lifitegrast. Energetically, Lifitegrast was less favorable for passive membrane permeability. The interaction between BCL6 and BI-3802 is more prone to SNP-derived variations. On the other hand, higher nonspecific binding of BI-3802 to off-target proteins could bring about higher undesirable properties. It should also be noted that energetically less desirable passive membrane translocation of Lifitegrast would demand drug delivery vehicles. However, further empirical evaluation of Lifitegrast would unveil its true potential.

Liothyronine could block the programmed death-ligand 1 (PDL1) activity: an e-Pharmacophore modeling and virtual screening study.

PURPOSE: The interaction between PD-L1 on tumor cells and the programmed death 1 (PD1) on immune cells helps them to escape the immune system elimination. Therefore, developing therapeutic agents to block this interaction has garnered a lot of attention as a therapeutic approach. In the present study, we have tried to screen for an inhibitory compound to inhibit the interaction between the PD1/PD-L1 molecules. METHODS: In this regard, the structure of PD-L1 and its inhibitor were prepared and employed to generate an e-Pharmacophore model. A library of approved compounds was prepared and toxicity analysis using Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) predictor was performed. The built e-Pharmacophore model was validated and used to screen the prepared compound library. Ligand docking and binding energy calculation were performed on the screened ligands. RESULTS: A seven-feature e-Pharmacophore model was generated using the PD-L1 complex. All of the compounds within the library passed the ADMET criteria. Performing the virtual screening, only 79 compounds have survived the criteria to fit four pharmacophoric features. The compound with the highest binding energy was the liothyronine (T3). CONCLUSION: The ability of T3 in PD1/PD-L1 checkpoint blockade along with its potential in T4 reduction could be a desirable combination in cancer treatment. These abilities of T3 could be used to restore the ability of the immune system to eliminate tumor cells.

Pierce into Structural Changes of Interactions Between Mutated Spike Glycoproteins and ACE2 to Evaluate Its Potential Biological and Therapeutic Consequences.

The structural consequences of ongoing mutations on the SARS-CoV-2 spike-protein remains to be fully elucidated. These mutations could change the binding affinity between the virus and its target cell. Moreover, obtaining new mutations would also change the therapeutic efficacy of the designed drug candidates. To evaluate these consequences, 3D structure of a mutant spike protein was predicted and checked for stability, cavity sites, and residue depth. The docking analyses were performed between the 3D model of the mutated spike protein and the ACE2 protein and an engineered therapeutic ACE2 against COVID-19. The obtained results revealed that the N501Y substitution has altered the interaction orientation, augmented the number of interface bonds, and increased the affinity against the ACE2. On the other hand, the P681H mutation contributed to the increased cavity size and relatively higher residue depth. The binding affinity between the engineered therapeutic ACE2 and the mutant spike was significantly higher with a distinguished binding orientation. It could be concluded that the mutant spike protein increased the affinity, preserved the location, changed the orientation, and altered the interface amino acids of its interaction with both the ACE2 and its therapeutic engineered version. The obtained results corroborate the more aggressive nature of mutated SARS-CoV-2 due to their higher binding affinity. Moreover, designed ACe2-baased therapeutics would be still highly effective against covid-19, which could be the result of conserved nature of cellular ACE2. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10989-021-10346-1.

Recent Advances in Understanding the Pathogenesis of Rheumatoid Arthritis: New Treatment Strategies.

Rheumatoid arthritis (RA) is considered a chronic systemic, multi-factorial, inflammatory, and progressive autoimmune disease affecting many people worldwide. While patients show very individual courses of disease, with RA focusing on the musculoskeletal system, joints are often severely affected, leading to local inflammation, cartilage destruction, and bone erosion. To prevent joint damage and physical disability as one of many symptoms of RA, early diagnosis is critical. Auto-antibodies play a pivotal clinical role in patients with systemic RA. As biomarkers, they could help to make a more efficient diagnosis, prognosis, and treatment decision. Besides auto-antibodies, several other factors are involved in the progression of RA, such as epigenetic alterations, post-translational modifications, glycosylation, autophagy, and T-cells. Understanding the interplay between these factors would contribute to a deeper insight into the causes, mechanisms, progression, and treatment of the disease. In this review, the latest RA research findings are discussed to better understand the pathogenesis, and finally, treatment strategies for RA therapy are presented, including both conventional approaches and new methods that have been developed in recent years or are currently under investigation.

SARS-CoV-2 Proteome Harbors Peptides Which Are Able to Trigger Autoimmunity Responses: Implications for Infection, Vaccination, and Population Coverage.

Autoimmune diseases (ADs) could occur due to infectious diseases and vaccination programs. Since millions of people are expected to be infected with SARS-CoV-2 and vaccinated against it, autoimmune consequences seem inevitable. Therefore, we have investigated the whole proteome of the SARS-CoV-2 for its ability to trigger ADs. In this regard, the entire proteome of the SARS-CoV-2 was chopped into more than 48000 peptides. The produced peptides were searched against the entire human proteome to find shared peptides with similar experimentally confirmed T-cell and B-cell epitopes. The obtained peptides were checked for their ability to bind to HLA molecules. The possible population coverage was calculated for the most potent peptides. The obtained results indicated that the SARS-CoV-2 and human proteomes share 23 peptides originated from ORF1ab polyprotein, nonstructural protein NS7a, Surface glycoprotein, and Envelope protein of SARS-CoV-2. Among these peptides, 21 peptides had experimentally confirmed equivalent epitopes. Amongst, only nine peptides were predicted to bind to HLAs with known global allele frequency data, and three peptides were able to bind to experimentally confirmed HLAs of equivalent epitopes. Given the HLAs which have already been reported to be associated with ADs, the ESGLKTIL, RYPANSIV, NVAITRAK, and RRARSVAS were determined to be the most harmful peptides of the SARS-CoV-2 proteome. It would be expected that the COVID-19 pandemic and the vaccination against this pathogen could significantly increase the ADs incidences, especially in populations harboring HLA-B*08:01, HLA-A*024:02, HLA-A*11:01 and HLA-B*27:05. The Southeast Asia, East Asia, and Oceania are at higher risk of AD development.

Design of an engineered ACE2 as a novel therapeutics against COVID-19.

The interaction between the angiotensin-converting enzyme 2 (ACE2) and the receptor binding domain (RBD) of the spike protein from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays a pivotal role in virus entry into the host cells. Since recombinant ACE2 protein has been suggested as an anti-SARS-CoV-2 therapeutic agent, this study was conducted to design an ACE2 protein with more desirable properties. In this regard, the amino acids with central roles in enzymatic activity of the ACE2 were substituted. Moreover, saturation mutagenesis at the interaction interface between the ACE2 and RBD was performed to increase their interaction affinity. The best mutations to increase the structural and thermal stability of the ACE2 were also selected based on B factors and mutation effects. The obtained resulted revealed that the Arg273Gln and Thr445Gly mutation have drastically reduced the binding affinity of the angiotensin-II into the active site of ACE2. The Thr27Arg mutation was determined to be the most potent mutation to increase the binding affinity. The Asp427Arg mutation was done to decrease the flexibility of the region with high B factor. The Pro451Met mutation along with the Gly448Trp mutation was predicted to increase the thermodynamic stability and thermostability of the ACE2. The designed therapeutic ACE2 would have no enzymatic activity while it could bear stronger interaction with Spike glycoprotein of the SARS-CoV-2. Moreover, decreased in vivo enzymatic degradation would be anticipated due to increased thermostability. This engineered ACE2 could be exploited as a novel therapeutic agent against COVID-19 after necessary evaluations.

Suramin could block the activity of Arabinono-1, 4-lactone oxidase enzyme from Leishmania donovani: structure-based screening and molecular dynamics analyses.

BACKGROUND: Leishmania donovani, a parasitic protozoan causing visceral leishmaniasis, can lead to a dangerous and often fatal disease in humans. Current treatment for leishmaniasis may have severe side effects, low efficacy and high cost, hence an immediate need for new efficient drugs is essential. Arabinono-1, 4-lactone oxidase enzyme from Leishmania donovani (LdALO), which catalyzes the last step of the ascorbate biosynthesis pathway, has been considered as a potential target for antileishmanial drugs design. METHODS: The current study was performed with an in silico approach to predict novel inhibitory molecules against the LdALO enzyme. Various modeling and refinement processes were employed to obtain a reliable 3D structure. RESULTS: The best LdALO model with the highest qualitative model energy analysis score was predicted by the Robetta server and subsequently refined by 3D refine and ModLoop servers. The high quality of the final LdALO model was confirmed using model assessment software. Based on docking analysis results, we predicted 10 inhibitory molecules of a US Food and Drug Administration-approved library, with appropriate criteria regarding energy binding and interaction with the main functionally active sites of LdALO, indicating that they could be significant targets for further drug design investigations against L. donovani. CONCLUSION: Suramin is used to treat the first stage of African sleeping sickness and its mechanism of action is unknown. Our results showed that suramin was the best-predicted inhibitor compound for LdALO enzyme activity.

Serum DKK1 is correlated with γ peak of serum electrophoresis in multiple myeloma: a multicenter biomarker study.

Aim: DKK1 is reported to be produced at high levels by myeloma cells. Therefore, the applicability of DKK1 as a tumor marker for multiple myeloma (MM) diagnosis was examined. Methods: Serum samples were collected and analyzed by DKK1 concentration kit and capillary zone electrophoresis. Then, the obtained results were statically analyzed. Results: It has been determined that the 10 ng/ml of DKK1 is the optimal level for MM diagnosis. Moreover, there was an ascending linear correlation between the DKK1 concentration and γ peak. Discussion: The observed correlation could be rooted in the positive feedback loop between MM cells and the mesenchymal stem cells. In view of these results, DKK1 could be deemed as diagnostic marker for MM.

Immunoinformatics: In Silico Approaches and Computational Design of a Multi-epitope, Immunogenic Protein.

Immunoinformatics is a new critical field with several tools and databases that conduct the eyesight of experimental selection and facilitate analysis of the great amount of immunologic data obtained from experimental researches and helps to design and introducing new hypothesis. Given these visages, immunoinformatics seems to be the way that develop and progress the immunological research. Bioinformatics methods and applications are successfully employed in vaccine informatics to assist different sites of the preclinical, clinical, and post-licensure vaccine enterprises. On the other hand, the progression of molecular biology and immunology caused epitope vaccines have become the focus of research on molecular vaccines. Moreover, reverse vaccinology could improve vaccine production and vaccination protocols by in silico prediction of protein-vaccine candidates from genome sequences. B- and T-cell immune epitopes could be predicted by immunoinformatics algorithms and computational methods to improve the vaccine design, protective immunity analysis, assessment of vaccine safety and efficacy, and immunization modeling. This review aims to discuss the power of computational approaches in vaccine design and their relevance to the development of effective vaccines. Furthermore, the various divisions of this field and available tools in each item are introduced and reviewed.

Enhanced hyluronic acid production in Streptococcus zooepidemicus by over expressing HasA and molecular weight control with Niscin and glucose.

Hyaluronic acid (HA) is a high molecular weight linear polysaccharide, endowed with unique physiological and biological properties. Given its unique properties, HA have unprecedented applications in the fields of medicine and cosmetics. The ever growing demand for HA production is the driving force behind the need for finding and developing novel and amenable sources of the HA producers. Microbial fermentation of Streptococcus zooepidemicus deemed as one the most expeditious and pervasive methods of HA production. Herein, a wild type Streptococcus zooepidemicus, intrinsically expressing high levels of HA, was selected and optimized for HA production. HasA gene was amplified and introduced into the wild type Streptococcus zooepidemicus, under the control of Nisin promoter. The HasA over-expression increased the HA production, while the molecular weight was decreased. In order to compensate for molecular weight loss, the glucose concentration was increased to an optimum amount of 90 g/L. It is hypostatizes that excess glucose would rectify the distribution of the monomers and each HasA molecule would be provided with sufficient amount of substrates to lengthen the HA molecules. Arriving at an improved strain and optimized cultivating condition would pave the way for industrial grade HA production with high quality and quantity.