Investigation of Zika virus methyl transferase inhibitors using steered molecular dynamics

Zika virus (ZIKV) spread is considered a major public health threat by the World Health Organization (WHO). There are no vaccines or drugs available to control the infection of the Zika virus, therefore a highly effective medicinal molecule is urgently required. In this study, a computationally intensive investigation was performed to identify a potent natural compound that could inhibit the ZIKV NS5 methyltransferase. This research approach is based on target-based drug identification principles where the native inhibitor SAH (S-adenosylhomocysteine) of ZIKV NS5 methyltransferase was selected as a reference. High-throughput virtual screening and tanimoto similarity coefficient were applied to the natural compound library for ranking the potential candidates. The top five compounds were selected for interaction analysis, MD simulation, total binding free energy through MM/GBSA, and steered MD simulation. Among these compounds, Adenosine 5'-monophosphate monohydrate, Tubercidin, and 5-Iodotubercidin showed stable binding to the protein compared to the native compound, SAH. These three compounds also showed less fluctuations in RMSF in contrast to native compound. Additionally, the same interacting residues observed in SAH also made strong interactions with these three compounds. Adenosine 5'-monophosphate monohydrate and 5-Iodotubercidin had greater total binding free energies than the reference ligand. Moreover, the dissociation resistance of all three compounds was equivalent to that of the reference ligand. This study suggested binding properties of three-hit compounds that could be used to develop drugs against Zika virus infections.Communicated by Ramaswamy H. Sarma.

Evaluating the Sensitivity of Different Molecular Techniques for Detecting Mycobacterium tuberculosis Complex in Patients with Pulmonary Infection

This study aimed to evaluate the accuracy of detecting drug-resistant Mycobacterium tuberculosis complex (MTBC)-specific DNA in sputum specimens from 48 patients diagnosed with pulmonary tuberculosis. The presence of MTBC DNA in the specimens was validated using the GeneXpert MTB/RIF system and compared with a specific PCR assay targeting the IS6110 and the mtp40 gene sequence fragments. Additionally, the results obtained by multiplex PCR assays to detect the most frequently encountered rifampin, isoniazid, and ethambutol resistance-conferring mutations were matched with those obtained by GeneXpert and phenotypic culture-based drug susceptibility tests. Of the 48 sputum samples, 25 were positive for MTBC using the GeneXpert MTB/RIF test. Nevertheless, the IS6110 and mtp40 single-step PCR revealed the IS6110 in 27 of the 48 sputum samples, while the mtp40 gene fragment was found in only 17 of them. Furthermore, multiplex PCR assays detected drug-resistant conferring mutations in 21 (77.8%) of the 27 samples with confirmed MTBC DNA, 10 of which contained single drug-resistant conferring mutations towards ethambutol and two towards rifampin, and the remaining nine contained double-resistant mutations for ethambutol and rifampin. In contrast, only five sputum specimens (18.5%) contained drug-resistant MTBC isolates, and two contained mono-drug-resistant MTBC species toward ethambutol and rifampin, respectively, and the remaining three were designated as multi-drug resistant toward both drugs using GeneXpert and phenotypic culture-based drug susceptibility tests. Such discrepancies in the results emphasize the need to develop novel molecular tests that associate with phenotypic non-DNA-based assays to improve the detection of drug-resistant isolates in clinical specimens in future studies.

Deep and Transfer Learning Approaches for Automated Early Detection of Monkeypox (Mpox) Alongside Other Similar Skin Lesions and Their Classification

The world faces multiple public health emergencies simultaneously, such as COVID-19 and Monkeypox (mpox). mpox, from being a neglected disease, has emerged as a global threat that has spread to more than 100 nonendemic countries, even as COVID-19 has been spreading for more than 3 years now. The general mpox symptoms are similar to chickenpox and measles, thus leading to a possible misdiagnosis. This study aimed at facilitating a rapid and high-brevity mpox diagnosis. Reportedly, mpox circulates among particular groups, such as sexually promiscuous gay and bisexuals. Hence, selectively vaccinating, isolating, and treating them seems difficult due to the associated social stigma. Deep learning (DL) has great promise in image-based diagnosis and could help in error-free bulk diagnosis. The novelty proposed, the system adopted, and the methods and approaches are discussed in the article. The present work proposes the use of DL models for automated early mpox diagnosis. The performances of the proposed algorithms were evaluated using the data set available in public domain. The data set adopted for the study was meant for both training and testing, the details of which are elaborated. The performances of CNN, VGG19, ResNet 50, Inception v3, and Autoencoder algorithms were compared. It was concluded that CNN, VGG19, and Inception v3 could help in early detection of mpox skin lesions, and Inception v3 returned the best (96.56%) classification accuracy.

Identification of natural potent inhibitors against Mycobacterium tuberculosis isocitrate lyase: an in silico study

Tuberculosis (TB) is a global burden to humanity due to its adverse effects on health and society since time is not clearly defined. The existence of drug-resistant strains and the potential threat posed by latent tuberculosis act as strong impetuses for developing novel anti-tuberculosis drugs. In this study, various flavonoids were tested against the Mycobacterium tuberculosis (Mtb) Isocitrate Lyase (ICL), which has been identified as an authorised therapeutic target for treating Mtb infection. Using in silico drug discovery approach, a library of 241 flavonoid compounds was virtually screened against the binding pocket of the crystalline ligand, the VGX inhibitor, in the Mtb ICL protein. As a result, the top four flavonoids were selected based on binding score and were further considered for redocking and intermolecular contact profiling analysis. The global and local fluctuations in the protein and ligand structure were analysed using their root mean square deviation (RMSD) and root mean square fluctuation (RMSF) values obtained from the GROMACS generated 100 ns molecular dynamics (MD) simulation trajectories. The end-state binding free energy was also calculated using the MMPBSA approach for all the respective docked complexes. All four selected compounds exhibited considerable stability and affinity compared to control ligands, i.e. VGX inhibitor; however, Vaccarin showed the highest stability and affinity against the Mtb ICL protein active site, followed by the Genistin, Glabridin, and Corylin. Therefore, this study recommends selected flavonoids for in vitro and in vivo experimental studies to check their potency and efficacy against Mtb.

Cheminformatics and machine learning approaches for repurposing anti-viral compounds against monkeypox virus thymidylate kinase

One of the emerging epidemic concerns is Monkeypox disease which is spreading globally. This disease is caused by the monkeypox virus (MPXV), with an increasing global incidence with an outbreak in 2022. One of the novel targets for monkeypox disease is thymidylate kinase, which is involved in pyrimidine metabolism. In this study, docking-based virtual screening and molecular dynamics techniques were employed in addition to the machine learning (ML) model to investigate the potential anti-viral natural small compounds to inhibit thymidylate kinase of MPXV. Several potential hits were identified through high-throughput virtual screening, and further top three candidates were selected, which ranked using the ML model. These three compounds were then examined under molecular dynamics simulation and MM/GBSA-binding free energy analysis. Among these, Chlorhexidine HCl showed high potential for binding to the thymidylate kinase with stable and consistent conformation with RMSD < 0.3 nm. The MM/GBSA analysis also showed the minimum binding free energy (ΔG_TOTAL) of -62.41 kcal/mol for this compound. Overall, this study used structure-based drug design complemented by machine learning-guided ligand-based drug design to screen potential hit compounds from the anti-viral natural compound database.

Anti-tubercular activity evaluation of natural compounds by targeting Mycobacterium tuberculosis resuscitation promoting factor B inhibition: An in silico study

Tuberculosis (TB), an infectious disease caused by the Mycobacterium tuberculosis (Mtb), has been responsible for the deaths of millions of individuals around the globe. A vital protein in viral pathogenesis known as resuscitation promoting factor (RpfB) has been identified as a potential therapeutic target of anti-tuberculosis drugs. This study offered an in silico process to examine possible RpfB inhibitors employing a computational drug design pipeline. In this study, a total of 1228 phytomolecules were virtually tested against the RpfB of Mtb. These phytomolecules were sourced from the NP-lib database of the MTi-OpenScreen server, and five top hits (ZINC000044404209, ZINC000059779788, ZINC000001562130, ZINC000014766825, and ZINC000043552589) were prioritized for compute intensive docking with dock score ≤ - 8.5 kcal/mole. Later, molecular dynamics (MD) simulation and principal component analysis (PCA) were used to validate these top five hits. In the list of these top five hits, the ligands ZINC000044404209, ZINC000059779788, and ZINC000043552589 showed hydrogen bond formation with the functional residue Glu²⁹² of the RpfB protein suggesting biological significance of the binding. The RMSD study showed stable protein-ligand complexes and higher conformational consistency for the ligands ZINC000014766825, and ZINC000043552589 with RMSD 3-4 Å during 100 ns MD simulation. The overall analysis performed in the study suggested promising binding of these compounds with the RpfB protein of the Mtb at its functional site, further experimental investigation is needed to validate the computational finding.

Regulatory T Cells (Tregs) and COVID-19: Unveiling the Mechanisms, and Therapeutic Potentialities with a Special Focus on Long COVID

The COVID-19 pandemic has caused havoc all around the world. The causative agent of COVID-19 is the novel form of the coronavirus (CoV) named SARS-CoV-2, which results in immune system disruption, increased inflammation, and acute respiratory distress syndrome (ARDS). T cells have been important components of the immune system, which decide the fate of the COVID-19 disease. Recent studies have reported an important subset of T cells known as regulatory T cells (Tregs), which possess immunosuppressive and immunoregulatory properties and play a crucial role in the prognosis of COVID-19 disease. Recent studies have shown that COVID-19 patients have considerably fewer Tregs than the general population. Such a decrement may have an impact on COVID-19 patients in a number of ways, including diminishing the effect of inflammatory inhibition, creating an inequality in the Treg/Th17 percentage, and raising the chance of respiratory failure. Having fewer Tregs may enhance the likelihood of long COVID development in addition to contributing to the disease's poor prognosis. Additionally, tissue-resident Tregs provide tissue repair in addition to immunosuppressive and immunoregulatory activities, which may aid in the recovery of COVID-19 patients. The severity of the illness is also linked to abnormalities in the Tregs' phenotype, such as reduced expression of FoxP3 and other immunosuppressive cytokines, including IL-10 and TGF-beta. Hence, in this review, we summarize the immunosuppressive mechanisms and their possible roles in the prognosis of COVID-19 disease. Furthermore, the perturbations in Tregs have been associated with disease severity. The roles of Tregs are also explained in the long COVID. This review also discusses the potential therapeutic roles of Tregs in the management of patients with COVID-19.

Antibodies to Combat Fungal Infections: Development Strategies and Progress

The finding that some mAbs are antifungal suggests that antibody immunity may play a key role in the defense of the host against mycotic infections. The discovery of antibodies that guard against fungi is a significant advancement because it gives rise to the possibility of developing vaccinations that trigger protective antibody immunity. These vaccines might work by inducing antibody opsonins that improve the function of non-specific (such as neutrophils, macrophages, and NK cells) and specific (such as lymphocyte) cell-mediated immunity and stop or aid in eradicating fungus infections. The ability of antibodies to defend against fungi has been demonstrated by using monoclonal antibody technology to reconsider the function of antibody immunity. The next step is to develop vaccines that induce protective antibody immunity and to comprehend the mechanisms through which antibodies mediate protective effects against fungus.

Variants of SARS-CoV-2: Influences on the Vaccines' Effectiveness and Possible Strategies to Overcome Their Consequences

The immune response elicited by the current COVID-19 vaccinations declines with time, especially among the immunocompromised population. Furthermore, the emergence of novel SARS-CoV-2 variants, particularly the Omicron variant, has raised serious concerns about the efficacy of currently available vaccines in protecting the most vulnerable people. Several studies have reported that vaccinated people get breakthrough infections amid COVID-19 cases. So far, five variants of concern (VOCs) have been reported, resulting in successive waves of infection. These variants have shown a variable amount of resistance towards the neutralising antibodies (nAbs) elicited either through natural infection or the vaccination. The spike (S) protein, membrane (M) protein, and envelope (E) protein on the viral surface envelope and the N-nucleocapsid protein in the core of the ribonucleoprotein are the major structural vaccine target proteins against COVID-19. Among these targets, S Protein has been extensively exploited to generate effective vaccines against COVID-19. Hence, amid the emergence of novel variants of SARS-CoV-2, we have discussed their impact on currently available vaccines. We have also discussed the potential roles of S Protein in the development of novel vaccination approaches to contain the negative consequences of the variants' emergence and acquisition of mutations in the S Protein of SARS-CoV-2. Moreover, the implications of SARS-CoV-2's structural proteins were also discussed in terms of their variable potential to elicit an effective amount of immune response.

Seroprevalence of community-acquired atypical bacterial pneumonia among adult COVID-19 patients from a single center in Al Madinah Al Munawarah, Saudi Arabia: A retrospective cohort study

OBJECTIVES

To investigate the seroprevalence of the community-acquired bacterial that causes atypical pneumonia among confirmed severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) patients.

METHODS

In this cohort study, we retrospectively investigated the seroprevalence of Chlamydia pneumoniae, Mycoplasma pneumoniae, and Legionella pneumophila among randomly selected 189 confirmed COVID-19 patients at their time of hospital presentation via commercial immunoglobulin M (IgM) antibodies against these bacteria. We also carried out quantitative measurements of procalcitonin in patients' serum.

RESULTS

The seropositivity for L. pneumophila was 12.6%, with significant distribution among patientsolder than 50 years (χ2 test, p=0.009), while those of M. pneumoniae was 6.3% and C. pneumoniae was 2.1%, indicating an overall co-infection rate of 21% among COVID-19 patients. No significant difference (χ2 test, p=0.628) in the distribution of bacterial co-infections existed between male and female patients. Procalcitonin positivity was confirmed amongst 5% of co-infected patients.

CONCLUSION

Our study documented the seroprevalence of community-acquired bacteria co-infection among COVID-19 patients. In this study, procalcitonin was an inconclusive biomarker for non-severe bacterial co-infections among COVID-19 patients. Consideration and proper detection of community-acquired bacterial co-infection may minimize misdiagnosis during the current pandemic and positively reflect disease management and prognosis.

Lack of association between fat mass and obesity-associated genetic variant (rs8050136) and type 2 diabetes mellitus

Objectives:

To study the genotype and allele frequency of the fat mass and obesity-associated (FTO) rs8050136 A>C genetic variant and investigate its association with type 2 diabetes mekkitus (T2DM) parameters.

Methods:

This study was carried out on 118 diabetic patients and 106 healthy individuals (control) from Prince Mohammed bin Abdulaziz Hospital, Al Madinah Al Munawarah, Saudi Arabia. The TaqMan single-nucleotide polymorphism (SNP)genotyping assay was used for rs8050136 genotyping.

Results:

The frequency of the genotype AA was the same among T2DM and healthy control groups (21%). However, the frequency of genotype CC was 19.5% in T2DM patients and 24.5% in control individuals. There was no significant association between FTO SNP rs8050136 and an increased risk of T2DM. Furthermore, there was no association between the risk AA genotype and fasting blood glucose (p=0.092), glycated hemoglobin (p=0.177), or body mass index (p=0.561).

Conclusion:

Our findings show that the FTO rs8050136 A>C variant is not associated with T2DM in the Saudi population.