Targeting of essential mycobacterial replication enzyme DnaG primase revealed Mitoxantrone and Vapreotide as novel mycobacterial growth inhibitors

Tuberculosis (TB) is the second leading cause of mortality after COVID-19, with a global death toll of 1.6 million in 2021. The escalating situation of drug-resistant forms of TB has threatened the current TB management strategies. New therapeutics with novel mechanisms of action are urgently required to address the current global TB crisis. The essential mycobacterial primase DnaG with no structural homology to homo sapiens presents itself as a good candidate for drug targeting. In the present study, Mitoxantrone and Vapreotide, two FDA-approved drugs, were identified as potential anti-mycobacterial agents. Both Mitoxantrone and Vapreotide exhibit a strong Minimum Inhibitory Concentration (MIC) of ≤25μg/ml against both the virulent (M.tb-H37Rv) and avirulent (M.tb-H37Ra) strains of M.tb. Extending the validations further revealed the inhibitory potential drugs in ex vivo conditions. Leveraging the computational high-throughput multi-level docking procedures from the pool of ~2700 FDA-approved compounds, Mitoxantrone and Vapreotide were screened out as potential inhibitors of DnaG. Extensive 200 ns long all-atoms molecular dynamic simulation of DnaGDrugs complexes revealed that both drugs bind strongly and stabilize the DnaG during simulations. Reduced solvent exposure and confined motions of the active centre of DnaG upon complexation with drugs indicated that both drugs led to the closure of the active site of DnaG. From this study's findings, we propose Mitoxantrone and Vapreotide as potential anti-mycobacterial agents, with their novel mechanism of action against mycobacterial DnaG.

Mechanistic and structural insight into R2R3-MYB transcription factor in plants: molecular dynamics based binding free energy analysis

The MYB transcription factor (TF) family is essential for various plant growth and development processes, including responses to biotic and abiotic stresses. This study investigated the R2R3-MYB protein structure from five plants, including cereal crops. The R2R3-MYB protein structure was docked with the DNA structure, and the best complexes were selected for two runs of molecular dynamics (MD) simulations to investigate the key interacting residues and conformational changes in the R2R3-MYB proteins caused by DNA binding. The MM/PBSA method calculated the binding free energy for each R2R3-MYB protein-DNA complex, showing strong interaction. Hydrophobic and hydrogen bonds significantly stabilized the R2R3-MYB protein-DNA complexes. The principal component analysis showed high restrictions on the movement of protein atoms in the phase space. A similar MD simulation analysis was performed using the crystal structure of the R2R3-MYB protein-DNA complex from Arabidopsis thaliana, and the generated complexes resembled the X-ray crystal structure. This is the first detailed study on the R2R3-MYB protein-DNA complex in cereal crops, providing a cost-effective solution to identify the key interacting residues and analyze the conformational changes in the MYB domain before and after DNA binding.Communicated by Ramaswamy H. Sarma.

Atosiban and Rutin exhibit anti-mycobacterial activity - An integrated computational and biophysical insight toward drug repurposing strategy against Mycobacterium tuberculosis targeting its essential enzyme HemD

With the advancements of high throughput computational screening procedures, drug repurposing became the privileged framework for drug discovery. The structure-based drug discovery is the widely used method of drug repurposing, consisting of computational screening of compounds and testing them in-vitro. This current method of repurposing leaves room for mechanistic insights into how these screened hits interact with and influence their targets. We addressed this gap in the current study by integrating highly sensitive biophysical methods into existing computational repurposing methods. We also corroborated our computational and biophysical findings on H37Rv for the anti-mycobacterial action of selected drugs in-vitro and ex-vivo conditions. Atosiban and Rutin were screened as highly interacting hits against HemD through multi-stage docking and were cross-validated in biophysical studies. The affinity of these drugs (K ~ 106 M-1) was quantified using fluorescence quenching studies. Differential Scanning Fluorimetry (DSF) and urea-based chemical denaturation studies revealed a destabilizing effect of these drugs on target which was further validated using MD simulations. Conformational rearrangements of secondary structures were established using CD spectra and intrinsic fluorescence. Furthermore, Atosiban and Rutin inhibited M.tb growth in-vitro and ex-vivo while remaining non-toxic to mice peritoneal macrophages.

Early Cutaneous Manifestations of COVID-19: A Systematic Review and Public Health Implications

INTRODUCTION

Cutaneous manifestations before other symptoms have great potential for early COVID-19 diagnosis to prevent surge.

METHODS

We conducted a search of PubMed and Embase databases through April 11, 2021 to include 39 studies reporting skin manifestations occurring prior to any other COVID-19 symptoms in laboratory-confirmed cases.

RESULTS

Ninety-seven patients were included. Urticarial (24.7%) and maculopapular (22.7%) lesions were most common, followed by pernio (17.5%), vesicular (14.4%), papulosquamous (8.2%), and purpuric (5.1%) lesions. Cutaneous to systemic symptom latency ranged from 2 to 20 days in cases that reported it (26%), while skin lesions were the only presentation in 23 cases (23.7%). Skin lesions were the only COVID-19 manifestation in 58.8% of pernio, 40% of vesicular, 16.6% of urticarial, 18.2% of maculopapular, and 12.5% of papulosquamous presymptomatic cases. Although sample size is limited, all purpuric cases developed other symptom(s) later.

CONCLUSIONS

Pernio and purpuric lesions have been well-associated with COVID-19, but papulosquamous, vesicular, mild maculopapular, and urticarial lesions can easily be dismissed as unrelated to COVID-19. Pernio lesions are thought to be related to strong immune response and low contagiousness, while purpuric and vesicular cases are speculated to be related to higher SARS-CoV2 viral load, severity, and contagiousness. All rashes, even without other symptoms, should necessitate high level of suspicion for isolation or contact tracing.

A Review of Morphologic Findings in Peripheral Blood Smears of COVID-19 Patients

INTRODUCTION

Peripheral smear examination is a simple and cost-effective test that is routinely performed while monitoring patients diagnosed with COVID-19. We sought to summarize the peripheral blood morphologic findings in patients with COVID-19 infection.

METHODS

A systematic review was conducted using a standardized keyword search on Medline database (PubMed), med RXIV, Google Scholar, EMBASE, and SCOPUS for studies discussing peripheral blood smear or morphologic blood findings in patients diagnosed with COVID-19.

RESULTS

A total of 28 studies were included in the review. Normocytic normochromic anemia was the most frequently encountered red blood cell finding. Neutrophilia was seen in most of the studies. A variety of morphological changes were observed in neutrophils, including pyknotic nuclei, variable shapes, toxic granules, and cytoplasmic vacuolization. Hyposegmented neutrophils, pseudo-Pegler Huet forms, and hypogranular forms were common findings reported by many studies. Lymphopenia was reported by most studies. Lymphocytes showed numerous morphological changes, including reactive forms, Downey forms, increased large granular lymphocytes, and plasmacytoid cells. The presence of giant platelets was seen frequently.

CONCLUSIONS

The peripheral blood in COVID-19 shows a spectrum of findings, mostly reactive changes in neutrophils, monocytes, lymphocytes, and platelets. Increased neutrophil/lymphocyte ratio and higher neutrophil counts have been associated with poor prognosis, which potentially could help triage patients, but this needs to be confirmed in larger studies.

SARS CoV-2 spike protein variants exploit DC-SIGN/DC-SIGNR receptor for evolution and severity: an in-silico insight

The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is related with the COVID-19 pandemic. Recent spike protein variations have had an effect on the transmission of the virus. In addition to ACE-2, spike proteins can employ DC-SIGN and its analogous receptor, DC-SIGNR, for host evasion. Spike variations in the DC-SIGN interaction region and role of DC-SIGN in immune evasion have not been well defined. To understand the spike protein variations and their binding mode, phylogenetic analysis of the complete GISAID (Global Initiative for Sharing Avian Influenza Data) data of the SARS-CoV-2 spike protein was considered. In addition, an in silico knockout network evaluation of the SARS-CoV-2 single-cell transcriptome was conducted to determine the key role of DC-SIGN/R in immunological dysregulation. Within the DC-SIGN-interacting region of the SARS-CoV spike protein, the spike protein of SARS-CoV-2 displayed remarkable similarity to the SARS-CoV spike protein. Surprisingly, the phylogenetic analysis revealed that the SARS-CoV-2's spike exhibited significantly diverse variants in the DC-SIGN interaction domain, which altered the frequency of these variants. The variation within the DC-SIGN-interacting domain of spike proteins affected the binding of a limited number of variants with DC-SIGN and DC-SIGNR and affected their evolution. MMGBSA binding free energies evaluation differed for variants from those of the wild type, suggesting the influence of substitution mutations on the interaction pattern. In silico knockout network analysis of the single-cell transcriptome of Bronchoalveolar Lavage and peripheral blood mononuclear cells revealed that SARS-CoV-2 altered DC-SIGN/R signaling. Early surveillance of diverse SARS-CoV-2 strains could preclude a worsening of the pandemic and facilitate the development of an optimum vaccine against variations. The spike Receptor Binding Domain genetic variants are thought to boost SARS CoV-2 immune evasion, resulting in its higher longevity.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13337-023-00820-3.

Potential Repurposed Drug Candidates for Tuberculosis Treatment: Progress and Update of Drugs Identified in Over a Decade

The devastating impact of Tuberculosis (TB) has been a menace to mankind for decades. The World Health Organization (WHO) End TB Strategy aims to reduce TB mortality up to 95% and 90% of overall TB cases worldwide, by 2035. This incessant urge will be achieved with a breakthrough in either a new TB vaccine or novel drugs with higher efficacy. However, the development of novel drugs is a laborious process involving a timeline of almost 20-30 years with huge expenditure; on the other hand, repurposing previously approved drugs is a viable technique for overcoming current bottlenecks in the identification of new anti-TB agents. The present comprehensive review discusses the progress of almost all the repurposed drugs that have been identified to the present day (∼100) and are in the development or clinical testing phase against TB. We have also emphasized the efficacy of repurposed drugs in combination with already available frontline anti-TB medications along with the scope of future investigations. This study would provide the researchers a detailed overview of nearly all identified anti-TB repurposed drugs and may assist them in selecting the lead compounds for further in vivo/clinical research.

Correction: Self-reported Morisky Eight-item Medication Adherence Scale for Statins Concords with the Pill Count Method and Correlates with Serum Lipid Profile Parameters and Serum HMGCoA Reductase Levels

[This corrects the article DOI: 10.7759/cureus.6542.].

A Case of Fabry Disease With Lacrimal Gland Involvement

Fabry disease is an X-linked lysosomal storage disease resulting from an error in the glycosphingolipid metabolic pathway, which leads to accumulation of globotriaosylceramide in lysosomes of the skin, kidneys, heart, brain, and other organs. There are no existing reports of histologically proven lacrimal gland involvement in Fabry disease. The authors report the case of a 26-year-old male with Fabry disease who presented with bilateral upper eyelid dermatochalasis, steatoblepharon, and prolapsed lacrimal glands. The patient underwent surgical repair of the upper eyelids and biopsy of the lacrimal glands. The pathologic assessment demonstrated lamellated intracytoplasmic inclusions characteristic of Fabry disease. The prevalence of globotriaosylceramide lacrimal gland deposition in Fabry disease and the effect on lacrimal gland morphology and function have yet to be determined.

Immuno-informatics guided designing of a multi-epitope vaccine against Dengue and Zika

Dengue and zika are amongst the most prevalent mosquito-borne diseases caused by closely related members Dengue virus (DENV) and Zika virus (ZIKV), respectively, of the Flaviviridae family. DENV and ZIKV have been reported to co-infect several people, resulting in fatalities across the world. A vaccine that can safeguard against both these pathogens concurrently, can offer several advantages. This study has employed immuno-informatics for devising a multi-epitope, multi-pathogenic vaccine against both these viruses. Since, the two viruses share a common vector source, whose salivary components are reported to aid viral pathogenesis; antigenic salivary proteins from Aedes aegypti were also incorporated into the design of the vaccine along with conserved structural and non-structural viral proteins. Conserved B- and T-cell epitopes were identified for all the selected antigenic proteins. These epitopes were merged and further supplemented with β-defensin as an adjuvant, to yield an immunogenic vaccine construct. In-silico 3D modeling and structural validation of the vaccine construct was conducted, followed by its molecular docking and molecular dynamics simulation studies with human TLR2. Immune simulation study was also performed, and it further provided support that the designed vaccine can mount an effective immune response and hence provide protection against both DENV and ZIKV. Communicated by Ramaswamy H. Sarma.

Insights into the mutations leading to capreomycin resistance in S-adenosyl-L-methionine binding motif in TlyA from Mycobacterium tuberculosis

Capreomycin is a second line antibiotic used for the treatment of drug resistant Tuberculosis (TB), primary reason of death from a solo infectious organism, Mycobacterium tuberculosis (M.tb). Capreomycin targets the ribosome of bacteria and is known to bind at the interface where the large and small ribosomal subunits interact in M.tb using an S-Adenosyl Methionine (SAM) dependent methyltransferase, TlyA (Rv1794). Besides the methyltransferase activity, TlyA has also been found to show substantial haemolytic activity. The dual activity of TlyA highlights its crucial role in pathogenesis and virulence of M.tb. In the present study, docking and molecular dynamics (MD) simulations were carried out to explore the impact of mutations in a conserved SAM binding motif, ⁹⁰GASTG⁹⁴, on the affinity of TlyA enzyme for SAM. Two already reported mutations, A91E and S92L, and the remaining wild type residues, Gly90, Thr93, Gly94 mutated to alanine were taken into consideration resulting in a total of six systems, wild type + SAM, G90A + SAM, A91E + SAM, S92L + SAM, T93A + SAM and G94A + SAM that were subjected to 100 ns MD simulations. Docking scores and MD simulations analyses revealed that in contrast to wild type, mutants reduced the affinity of SAM for TlyA with most prominent effect observed in case of alanine mutants. Mutations also led to the loss of hydrogen bond and hydrophobic interactions and large-scale movement of atoms evident from the principal component analyses indicating their destabilizing impact on TlyA. The present study gives insights into influence of mutations on binding of SAM to TlyA in M.tb and promoting capreomycin resistance.Communicated by Ramaswamy H. Sarma.

Correction: Amyloid fibrillation of the glaucoma associated myocilin protein is inhibited by epicatechin gallate (ECG)

[This corrects the article DOI: 10.1039/D2RA05061G.].

Amyloid fibrillation of the glaucoma associated myocilin protein is inhibited by epicatechin gallate (ECG)

Inherited glaucoma is a recent addition to the inventory of diseases arising due to protein misfolding. Mutations in the olfactomedin (OLF) domain of myocilin are the most common genetic cause behind this disease. Disease associated variants of m-OLF are predisposed to misfold and aggregate in the trabecular meshwork (TM) tissue of the eye. In recent years, the nature of these aggregates was revealed to exhibit the hallmarks of amyloids. Amyloid aggregates are highly stable structures that are formed, often with toxic consequences in a number of debilitating diseases. In spite of its clinical relevance the amyloidogenic nature of m-OLF has not been studied adequately. Here we have studied the amyloid fibrillation of m-OLF and report ECG as an inhibitor against it. Using biophysical and biochemical assays, coupled with advanced microscopic evaluations we show that ECG binds and stabilizes native m-OLF and thus prevents its aggregation into amyloid fibrils. Furthermore, we have used REMD simulations to delineate the stabilizing effects of ECG on the structure of m-OLF. Collectively, we report ECG as a molecular scaffold for designing and testing of novel inhibitors against m-OLF amyloid fibrillation.

ARMC5-associated Bilateral Macronodular Adrenocortical Hyperplasia: A Novel Germline Variant Associated with Concomitant Papillary Thyroid Carcinoma and Meningioma

Introduction/Objective

Germline mutations in the tumor suppressor gene Armadillo-containing repeat protein 5 gene (ARMC5) have been very recently recognized as a cause for a familial form of bilateral macronodular adrenocortical hyperplasia (BMAH), itself a rare cause of Cushing syndrome. In patients with ARMC5 mutations, scattered case reports have also shown an association with meningiomas and cancers of the pancreas, breast, colon, and thyroid.

Methods/Case Report

We present the case of BMAH, arising in a 61-year-old female with a history of metastatic papillary thyroid carcinoma and meningioma. The patient presented with bilateral but asymmetric adrenal enlargement (right greater than left) and Cushing syndrome. Given history of thyroid cancer and meningioma, genetics referral was ordered. Counseling revealed a pedigree without a strongly evident familial pattern of hereditary endocrine neoplasia characteristic of any of the more common inherited dispositions to endocrine neoplasia. Additionally, a targeted capture-based NGS germline genetic sequencing study for variants in 12 genes associated with associated with hereditary thyroid cancer was performed and negative. However, based on recent scholarship regarding ARMC5, follow-up germline NGS and Sanger sequencing studies encompassing the entire coding sequences of ARMC5 were ordered. These identified a germline, heterozygous, novel (not in ClinVar) but likely pathogenic variant in (c.802C>T, p.Arg268*), providing a likely explanation for the patient’s BMAH. In attempt to control the patient’s Cushing symptoms, right-sided adrenalectomy was performed, revealing a 220g adrenal gland with marked multinodular hyperplasia with solid, nested, and tubular architecture.

Results (if a Case Study enter NA)

NA

Conclusion

While case reports exist describing an association between other ARMC5 mutations and BMAH with concomitant meningiomas and/or malignancies, greater study is needed in order to better characterize the phenotypic spectrum of this disease. Our experience with this case not only reports a novel, apparently pathogenic mutation, but it documents its association with BMAH and, additionally, papillary thyroid carcinoma and meningioma.

Myocilin-associated Glaucoma: A Historical Perspective and Recent Research Progress

Glaucoma a debilitating disease, is globally the second most common kind of permanent blindness. Primary open-angle glaucoma (POAG) is its most prevalent form and is often linked with alterations in the myocilin gene (MYOC). MYOC encodes the myocilin protein, which is expressed throughout the body, but primarily in trabecular meshwork (TM) tissue in the eyes. TM is principally involved in regulating intraocular pressure (IOP), and elevated IOP is the main risk factor associated with glaucoma. The myocilin protein's function remains unknown; however, mutations compromise its folding and processing inside TM cells, contributing to the glaucoma phenotype. While glaucoma is a complex disease with various molecules and factors as contributing causes, the role played by myocilin has been the most widely studied. The current review describes the present understanding of myocilin and its association with glaucoma and aims to shift the focus toward developing targeted therapies for treating glaucoma patients with variations in MYOC.

An immunoinformatics approach to design a multi-epitope vaccine against Mycobacterium tuberculosis exploiting secreted exosome proteins

Tuberculosis is one the oldest known affliction of mankind caused by the pathogen Mycobacterium tuberculosis. Till date, there is no absolute single treatment available to deal with the pathogen, which has acquired a great potential to develop drug resistance rapidly. BCG is the only anti-tuberculosis vaccine available till date which displays limited global efficacy due to genetic variation and concurrent pathogen infections. Extracellular vesicles or exosomes vesicle (EVs) lie at the frontier cellular talk between pathogen and the host, and therefore play a significant role in establishing pathogenesis. In the present study, an in-silico approach has been adopted to construct a multi-epitope vaccine from selected immunogenic EVs proteins to elicit a cellular as well as a humoral immune response. Our designed vaccine has wide population coverage and can effectively compensate for the genetic variation among different populations. For maximum efficacy and minimum adverse effects possibilities the antigenic, non-allergenic and non-toxic B-cell, HTL and CTL epitopes from experimentally proven EVs proteins were selected for the vaccine construct. TLR4 agonist RpfE served as an adjuvant for the vaccine construct. The vaccine construct structure was modelled, refined and docked on TLR4 immune receptor. The designed vaccine construct displayed safe usage and exhibits a high probability to elicit the critical immune regulators, like B cells, T-cells and memory cells as displayed by the in-silico immunization assays. Therefore, it can be further corroborated using in vitro and in vivo assays to fulfil the global need for a more efficacious anti-tuberculosis vaccine.

Engineering a multi epitope vaccine against SARS-CoV-2 by exploiting its non structural and structural proteins

SARS-CoV-2, the causative agent behind the ongoing pandemic exhibits an enhanced potential for infection when compared to its related family members- the SARS-CoV and MERS-CoV; which have caused similar disease outbreaks in the past. The severity of the global health burden, increasing mortality rate and the emergent economic crisis urgently demands the development of next generation vaccines. Amongst such emergent next generation vaccines are the multi-epitope subunit vaccines, which hold promise in combating deadly pathogens. In this study we have exploited immunoinformatics applications to delineate a vaccine candidate possessing multiple B and T cells epitopes by utilizing the SARS-CoV-2 non structural and structural proteins. The antigenicity potential, safety, structural stability and the production feasibility of the designed construct was evaluated computationally. Furthermore, due to the known role of human TLR-3 immune receptor in viral sensing, which facilitates host cells activation for an immune response, the vaccine construct was examined for its binding efficiency using molecular docking and molecular dynamics simulation studies, which resulted in strong and stable interactions. Finally, the immune simulation studies suggested an effective immune response on vaccine administration. Overall, the immunoinformatics analysis advocates that the proposed vaccine candidate is safe and immunogenic and therefore can be pushed as a lead for in vitro and in vivo investigations.Communicated by Ramaswamy H. Sarma.

Predicting phosphorylation sites using machine learning by integrating the sequence, structure, and functional information of proteins

BACKGROUND

Post-translational modification (PTM) is a biological process that alters proteins and is therefore involved in the regulation of various cellular activities and pathogenesis. Protein phosphorylation is an essential process and one of the most-studied PTMs: it occurs when a phosphate group is added to serine (Ser, S), threonine (Thr, T), or tyrosine (Tyr, Y) residue. Dysregulation of protein phosphorylation can lead to various diseases-most commonly neurological disorders, Alzheimer's disease, and Parkinson's disease-thus necessitating the prediction of S/T/Y residues that can be phosphorylated in an uncharacterized amino acid sequence. Despite a surplus of sequencing data, current experimental methods of PTM prediction are time-consuming, costly, and error-prone, so a number of computational methods have been proposed to replace them. However, phosphorylation prediction remains limited, owing to substrate specificity, performance, and the diversity of its features.

METHODS

In the present study we propose machine-learning-based predictors that use the physicochemical, sequence, structural, and functional information of proteins to classify S/T/Y phosphorylation sites. Rigorous feature selection, the minimum redundancy/maximum relevance approach, and the symmetrical uncertainty method were employed to extract the most informative features to train the models.

RESULTS

The RF and SVM models generated using diverse feature types in the present study were highly accurate as is evident from good values for different statistical measures. Moreover, independent test sets and benchmark validations indicated that the proposed method clearly outperformed the existing methods, demonstrating its ability to accurately predict protein phosphorylation.

CONCLUSIONS

The results obtained in the present work indicate that the proposed computational methodology can be effectively used for predicting putative phosphorylation sites further facilitating discovery of various biological processes mechanisms.

Multifaceted role of drugs: a potential weapon to outsmart Mycobacterium tuberculosis resistance by targeting its essential ThyX

Tuberculosis (TB) is one of the prominent cause of deaths across the world and multidrug-resistant and extensively drug-resistant TB continues to pose challenges for clinicians and public health centers. The risk of death is extremely high in individuals who have compromised immune systems, HIV infection, or diabetes. Research institutes and pharmaceutical companies have been working on repurposing existing drugs as effective therapeutic options against TB. The identification of suitable drugs with multi-target affinity profiles is a widely accepted way to combat the development of resistance. Flavin-dependent thymidylate synthase (FDTS), known as ThyX, is in the class of methyltransferases and is a possible target in the discovery of novel anti-TB drugs. In this study, we aimed to repurpose existing drugs approved by Food and Drug Administration (FDA) that could be used in the treatment of TB. An integrated screening was performed based on computational procedures: high-throughput molecular docking techniques, followed by molecular dynamics simulations of the target enzyme, ThyX. After performing in silico screening using a library of 3,967 FDA-approved drugs, the two highest-scoring drugs, Carglumic acid and Mesalazine, were selected as potential candidates that could be repurposed to treat TB.Communicated by Ramaswamy H. Sarma.

A systematic review and meta-analysis to evaluate the clinical outcomes in COVID-19 patients on angiotensin-converting enzyme inhibitors or angiotensin receptor blockers

Introduction

Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) share their target receptor site with the SARS-CoV-2 virus, that may cause ACE2 receptor up-regulation which raised concerns regarding ACEI and ARB use in COVID-19 patients. However, many medical professional societies recommended their continued use given the paucity of clinical evidence, but there is a need for an updated systematic review and meta-analysis of the latest clinical studies.

Methods and results

A search was conducted on PubMed, Google Scholar, EMBASE, and various preprint servers for studies comparing clinical outcomes and mortality in COVID-19 patients on ACEIs and/or ARBs, and a meta-analysis was performed. A total of 16 studies were included for the review and meta-analysis. There were conflicting findings reported in the rates of severity and mortality in several studies. In a pooled analysis of four studies, there was a statistically non-significant association of ACEI/ARB use with lower odds of developing severe disease vs. non-users [odds ratio (OR) = 0.81, 95% confidence interval (CI): 0.41–1.58, I²=50.52, P-value = 0.53). In a pooled analysis of six studies, there was a statistically non-significant association of ACEI/ARB use with lower odds of mortality as compared with non-users (OR = 0.86, 95% CI = 0.53–1.41, I² = 79.12, P-value = 0.55).

Conclusion

It is concluded that ACEIs and ARBs should be continued in COVID-19 patients, reinforcing the recommendations made by several medical societies. Additionally, the individual patient factors such as ACE2 polymorphisms which might confer higher risk of adverse outcomes need to be evaluated further.

Inhibitory mechanism of an antifungal drug, caspofungin against amyloid β peptide aggregation: Repurposing via neuroinformatics and an experimental approach

The multifactorial neurological condition called Alzheimer's disease (AD) primarily affects elderly individuals. Despite the calamitous consequences of AD, curative strategies for a regimen to apply remain inadequate as several factors contribute to AD etiology. Drug repurposing is an advance strategy prior to drug discovery as various effective drugs perform through alteration of multiple targets, and the present "poly-pharmacology" can be a curative approach to complex disorders. AD's multifactorial behavior actively encourages the hypothesis for a drug design approach focused on drug repurposing. In this study, we discovered that an antifungal drug, Caspofungin (CAS) is a potent Aβ aggregation inhibitor that displays significantly reduced toxicity associated with AD. Drug reprofiling and REMD simulations demonstrated that CAS interacts with the β-sheet section, known as Aβ amyloid fibrils hotspot. CAS leads to destabilization of β-sheet and, conclusively, in its devaluation. Later, in vitro experiments were acquired in which the fibrillar volume was reduced for CAS-treated Aβ peptide. For the first time ever, this study has determined an antifungal agent as the Aβ amyloid aggregation's potent inhibitor. Several efficient sequence-reliant potent inhibitors can be developed in future against the amyloid aggregation for different amyloid peptide by the processing and conformational optimization of CAS.

The polyphenolic phytoalexin polydatin inhibits amyloid aggregation of recombinant human prion protein

Prion diseases involve misfolded and highly infectious aggregates of prion protein (PrP^Sc) which forms amyloid plaques leading to fatal neurodegeneration. The absence of clinically proven therapeutics makes the discovery of effective remedial interventions a prime concern. Herein, we report novel prion intervention by the polyphenolic phytoalexin, polydatin which binds with moderate affinity to the recombinant protease resistant core of human prion protein, encompassing the sequence 90–231 (rPrP^res) and inhibits its conversion into the highly neurotoxic forms. An extensive evaluation using biophysical techniques revealed that polydatin incubated rPrP^res samples generate off-pathway oligomers having reduced cross-β sheet signature, and relatively smaller in size than the native rPrP^res oligomers. The detailed structural analysis using molecular dynamics simulations elucidated the induction of antagonistic mobilities in the β2–α2 loop, α3 helix and the N-terminal amyloidogenic region of prions. This study puts forward novel prion fibrillogenesis inhibitory potential of polydatin, specifically by stabilizing the N-terminal amyloidogenic region. Collectively our results affirm the importance of polydatin in crippling the prion pathogenesis and may serve as a structural scaffold for designing novel therapeutic agents targeting amyloidogenic transition in prions.

Polydatin is found to be a pharmacologically-significant scaffold that can bind to the rPrP^res repertoire and inhibit its conversion to the highly infectious and neurotoxic PrP^Sc-like form, thus acting like a promising anti-prion drug lead.

A Double-Edged Sword: The Anti-Cancer Effects of Emodin by Inhibiting the Redox-Protective Protein MTH1 and Augmenting ROS in NSCLC

Background: Reactive oxygen species (ROS), playing a two-fold role in tumorigenesis, are responsible for tumor formation and progression through the induction of genome instability and pro-oncogenic signaling. The same ROS is toxic to cancer cells at higher levels, oxidizing free nucleotide precursors (dNTPs) as well as damaging DNA leading to cell senescence. Research has highlighted the tumor cell-specific expression of a redox-protective phosphatase, MutT homolog 1 (MTH1), that performs the enzymatic conversion of oxidized nucleotides (like 8-oxo-dGTP) to their corresponding monophosphates, up-regulated in numerous cancers, circumventing their misincorporation into the genomic DNA and preventing damage and cell death. Methods: To identify novel natural small molecular inhibitors of MTH1 to be used as cancer therapeutic agents, molecular screening for MTH1 active site binders was performed from natural small molecular libraries. Emodin was identified as a lead compound for MTH1 active site functional inhibition and its action on MTH1 inhibition was validated on non-small cell lung cancer cellular models (NSCLC). Results: Our study provides strong evidence that emodin mediated MTH1 inhibition impaired NSCLC cell growth, inducing senescence. Emodin treatment enhanced the cellular ROS burdens, on one hand, damaged dNTP pools and inhibited MTH1 function on the other. Our work on emodin indicates that ROS is the key driver of cancer cell-specific increased DNA damage and apoptosis upon MTH1 inhibition. Consequently, we observed a time-dependent increase in NSCL cancer cell susceptibility to oxidative stress with emodin treatment. Conclusions: Based on our data, the anti-cancer effects of emodin as an MTH1 inhibitor have clinical potential as a single agent capable of functioning as a ROS inducer and simultaneous blocker of dNTP pool sanitation in the treatment of NSCL cancers. Collectively, our results have identified for the first time that the potential molecular mechanism of emodin function, increasing DNA damage and apoptosis in cancer cells, is via MTH1 inhibition.

Dual inhibition of SARS-CoV-2 spike and main protease through a repurposed drug, rutin

The global health emergency caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to alarming numbers of fatalities across the world. So far the researchers worldwide have not been able to discover a breakthrough in the form of a potent drug or an effective vaccine. Therefore, it is imperative to discover drugs to curb the ongoing menace. In silico approaches using FDA approved drugs can expedite the drug discovery process by providing leads that can be pursued. In this report, two drug targets, namely the spike protein and main protease, belonging to structural and non-structural class of proteins respectively, were utilized to carry out drug repurposing based screening. The exposed nature of the spike protein on the viral surface along with its instrumental role in host infection and the involvement of main protease in processing of polyproteins along with no human homologue make these proteins attractive drug targets. Interestingly, the screening identified a common high efficiency binding molecule named rutin. Further, molecular dynamics simulations in explicit solvent affirmed the stable and sturdy binding of rutin with these proteins. The decreased R_g value (4 nm for spike-rutin and 2.23 nm for main protease-rutin) and stagnant SASA analysis (485 nm/S²/N in spike-rutin and 152 nm/S2/N in main protease-rutin) for protein surface and its orientation in the exposed and buried regions suggests a strong binding interaction of the drug. Further, cluster analysis and secondary structure analysis of complex trajectories validated the conformational changes due to binding of rutin.

Multiple epitope-based vaccine prediction against SARS-CoV-2 spike glycoprotein

The global emergence of novel coronavirus disease and its rapid global expansion over a short span of time require effective countermeasures to combat it. Development of a specific vaccine can induce an optimal antibody response, thus providing immunity against it. Our study proposes a detailed and comprehensive immunoinformatic approach that can be applied to the currently available coronavirus protein data in the online server for vaccine candidate development. We have identified the receptor binding domain (RBD) of structural spike protein (S1) as a potential target for immunity against COVID- 19 infection. Epitope prediction illustrated cytotoxic T-cell epitopes, helper T-cell epitopes, and B-cell epitopes associated with the target protein. These were joined through specific linkers along with adjuvant beta-defensin located at the N-terminal to create a multi epitope subunit vaccine (MESV). The specificity in the binding of the devised vaccine candidate to the TLR-3 immune cell receptor was evaluated via molecular docking interaction studies. Good docking score combined with robust interactions in the binding cavity certified the stringency of the engineered vaccine. Molecular dynamics simulation data showed minimal variation of the root-mean square deviations (RMSDs) and root-mean-square fluctuations (RMSFs) which confirmed the interaction stability. These results obtained from various in-silico experiments indicate the potency of this vaccine candidate as a probable therapeutic agent against COVID-19. Vaccination strategies targeting conserved epitope-based immune response would be beneficial in providing cross protection across beta-coronaviruses, and such vaccines would be resistant to the ever-evolving viruses.Communicated by Ramaswamy H. Sarma.

Maslinic acid differentially exploits the MAPK pathway in estrogen-positive and triple-negative breast cancer to induce mitochondrion-mediated, caspase-independent apoptosis

Breast cancer accounts for 1.4 million new cases every year. Triple-negative breast cancer (TNBC) is one the leading cause of mortality in developing countries and is associated with early age onset (under 40 years old). Chemotherapy has a poor success rate in patients with TNBC as compared to other types of breast cancers. It is due to the lack of expression of three validated molecular markers for breast cancer, the estrogen and progesterone receptors, and the amplification of HER-2/Neu. Therefore, a clear need exists for a greater understanding of TNBC at all levels and for the development of better therapies. We have studied the anti-tumor effects of a potential drug, maslinic acid, which can be extracted from olive oil industry waste. This natural product showed inhibitory effect at concentrations ranging from 30 to 50 µM within 24 h. It exhibited divergent effects in cell cycle progression for the MCF7 (estrogen positive) cell line when compared with TNBCs like MDA-MB-231 and MDA-MB-468. Also, maslinic acid treatment altered the mitochondrial membrane electrochemical potential and the reactive oxygen species (ROS) levels to cause a caspase-independent programmed cell death. In silico approaches and immunoblotting suggested the involvement of the MAPK pathway explaining the variability in cell cycle progression along with the apoptotic cell death caused by maslinic acid.

Author Correction: Artificial Intelligence and Machine learning based prediction of resistant and susceptible mutations in Mycobacterium tuberculosis

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Antitussive noscapine and antiviral drug conjugates as arsenal against COVID-19: a comprehensive chemoinformatics analysis

Coronavirus pandemic has caused a vast number of deaths worldwide. Thus creating an urgent need to develop effective counteragents against novel coronavirus disease (COVID-19). Many antiviral drugs have been repurposed for treatment but implicated minimal recovery, which further advanced the need for clearer insights and innovation to derive effective therapeutics. Strategically, Noscapine, an approved antitussive drug with positive effects on lung linings may show favorable outcomes synergistically with antiviral drugs in trials. Hence, we have theoretically examined the combinatorial drug therapy by culminating the existing experimental results with in silico analyses. We employed the antitussive noscapine in conjugation with antiviral drugs (Chloroquine, Umifenovir, Hydroxychloroquine, Favlplravir and Galidesivir). We found that Noscapine-Hydroxychloroquine (Nos-Hcq) conjugate has strong binding affinity for the main protease (Mpro) of SARS-CoV-2, which performs key biological function in virus infection and progression. Nos-Hcq was analyzed through molecular dynamics simulation. The MD simulation for 100 ns affirmed the stable binding of conjugation unprecedentedly through RMSD and radius of gyration plots along with critical reaction coordinate binding free energy profile. Also, dynamical residue cross-correlation map with principal component analysis depicted the stable binding of Nos-Hcq conjugate to Mpro domains with optimal secondary structure statistics of complex dynamics. Also, we reveal the drugs with stable binding to major domains of Mpro can significantly improve the work profile of reaction coordinates, drug accession and inhibitory regulation of Mpro. The designed combinatorial therapy paves way for further prioritized in vitro and in vivo investigations for drug with robust binding against Mpro of SARS-CoV-2.

Protective Effects of a Neurohypophyseal Hormone Analogue on Prion Aggregation, Cellular Internalization, and Toxicity

Herein, we report novel neuroprotective activity of the neurohypophyseal hormone analogue desmopressin (DDAVP) against toxic conformations of human prion protein. Systematic analysis using biophysical techniques in conjunction with surface plasmon resonance, high-end microscopy, conformational antibodies, and cell-based assays demonstrated DDAVP's specific binding and potent antiaggregating effects on prion protein (rPrP^res). In addition to subjugating conformational conversion of rPrP^res into oligomeric forms, DDAVP also exhibits potent fibril modulatory effects. It eventually ameliorated neuronal toxicity of rPrP^res oligomers by significantly reducing their cellular internalization. Molecular dynamics simulations showed that DDAVP prevents β-sheet transitions in the N-terminal amyloidogenic region of prion and induces antagonistic mobilities in its α2-α3 and β2-α2 loop regions. Collectively, our data proposes DDAVP as a new structural motif for rational drug discovery against prion diseases.

EUS-directed transgastric endoscopic retrograde cholangiopancreatography versus laparoscopic-assisted ERCP versus deep enteroscopy-assisted ERCP for patients with RYGB

Background and study aims  Endoscopic ultrasound-directed transgastric endoscopic retrograde cholangiopancreatography (ERCP) (EDGE) is a novel technique for managing pancreaticobiliary diseases in patients with a history of Roux-en-Y Gastric Bypass (RYGB). It has shown to have high technical success rates and fewer adverse events as compared to laparoscopic-assisted ERCP (LA-ERCP). We compared the technical success and clinical outcomes of EDGE vs. LA-ERCP vs. E-ERCP. Patients and methods  A retrospective chart review was performed for 56 patients, of whom 18 underwent LA-ERCP, 12 underwent E-ERCP, and 26 had EDGE, and a comparison of technical success and complication rates was done. Results  Baseline demographic characteristics of patients undergoing these procedures, including age and gender, were comparable. The technical success rate for patients in the EDGE group were 100 % (n = 26), compared with 94 % (n = 17) and 75 % (n = 9) in the LA-ERCP and E-ERCP groups ( P  = 0.02). In the EDGE group, 8 % of patients (n = 2) had bleeding, and 4 % of patients (n = 1) had lumen-apposing metal stent migration occur during the procedure. In the LA-ERCP group 6 % (n = 1) of patient had bleeding, 6 % (n = 1) post-ERCP pancreatitis and 6 % (n = 1) were diagnosed with an intra-abdominal infection post-procedure. Time to complete the EDGE procedure was significantly shorter at 79 ± 31 mins, compared with 158 ± 50 mins for LA-ERCP and 102 ± 43 mins for E-ERCP ( P  < 0.001). Conclusion  EDGE is a novel procedure with short procedure times and an effective alternative to LA-ERCP and E-ERCP in management of pancreaticobiliary diseases in patients with a history of RYGB.

Risk of de-novo inflammatory bowel disease among obese patients treated with bariatric surgery or weight loss medications

BACKGROUND

An association between bariatric surgery and development of de-novo inflammatory bowel disease (IBD) has been observed.

AIM

To evaluate further the association among bariatric surgery, weight loss medications, obesity and new-onset IBD.

METHODS

Using Explorys, a population-based Health Insurance Portability and Accountability Act compliant database, we estimated the prevalence of de-novo IBD among patients treated with bariatric surgery (Roux-en-Y gastrojejunostomy, laparoscopic sleeve gastrectomy or gastric banding) (n = 60 870) or weight loss medications (orlistat, phentermine/topiramate, lorcaserin, bupropion/naltrexone and liraglutide) (n = 193 790) compared with obese controls (n = 5 021 210), between 1999 and 2018.

RESULTS

The prevalence of de-novo IBD was lower among obese patients exposed to bariatric surgery (7.72 per 1000 patients) or weight loss medications (7.22 per 1000 patients) compared with patients with persistent obesity not exposed to these interventions (11.66 per 1000 patients, P < 0.0001). The risk reduction for de-novo IBD was consistent across bariatric surgeries and weight loss medications with the exception of orlistat which was not associated with a reduction in risk for de-novo IBD compared with the persistent obese control cohort.

CONCLUSION

Obese patients undergoing treatment with bariatric surgery or weight loss medications are at a lower risk for developing de-novo IBD compared with persistently obese controls not exposed to these interventions. These data suggest that obesity and ineffective management of obesity are risk factors for de-novo IBD. Further research is needed to confirm these observations and understand potential mechanisms.

Artificial Intelligence and Machine learning based prediction of resistant and susceptible mutations in Mycobacterium tuberculosis

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (M.tb), causes highest number of deaths globally for any bacterial disease necessitating novel diagnosis and treatment strategies. High-throughput sequencing methods generate a large amount of data which could be exploited in determining multi-drug resistant (MDR-TB) associated mutations. The present work is a computational framework that uses artificial intelligence (AI) based machine learning (ML) approaches for predicting resistance in the genes rpoB, inhA, katG, pncA, gyrA and gyrB for the drugs rifampicin, isoniazid, pyrazinamide and fluoroquinolones. The single nucleotide variations were represented by several sequence and structural features that indicate the influence of mutations on the target protein coded by each gene. We used ML algorithms - naïve bayes, k nearest neighbor, support vector machine, and artificial neural network, to build the prediction models. The classification models had an average accuracy of 85% across all examined genes and were evaluated on an external unseen dataset to demonstrate their application. Further, molecular docking and molecular dynamics simulations were performed for wild type and predicted resistance causing mutant protein and anti-TB drug complexes to study their impact on the conformation of proteins to confirm the observed phenotype.

Long-range replica exchange molecular dynamics guided drug repurposing against tyrosine kinase PtkA of Mycobacterium tuberculosis

Tuberculosis (TB) is a leading cause of death worldwide and its impact has intensified due to the emergence of multi drug-resistant (MDR) and extensively drug-resistant (XDR) TB strains. Protein phosphorylation plays a vital role in the virulence of Mycobacterium tuberculosis (M.tb) mediated by protein kinases. Protein tyrosine phosphatase A (MptpA) undergoes phosphorylation by a unique tyrosine-specific kinase, protein tyrosine kinase A (PtkA), identified in the M.tb genome. PtkA phosphorylates PtpA on the tyrosine residues at positions 128 and 129, thereby increasing PtpA activity and promoting pathogenicity of MptpA. In the present study, we performed an extensive investigation of the conformational behavior of the intrinsically disordered domain (IDD) of PtkA using replica exchange molecular dynamics simulations. Long-term molecular dynamics (MD) simulations were performed to elucidate the role of IDD on the catalytic activity of kinase core domain (KCD) of PtkA. This was followed by identification of the probable inhibitors of PtkA using drug repurposing to block the PtpA-PtkA interaction. The inhibitory role of IDD on KCD has already been established; however, various analyses conducted in the present study showed that IDD_PtkA had a greater inhibitory effect on the catalytic activity of KCD_PtkA in the presence of the drugs esculin and inosine pranobex. The binding of drugs to PtkA resulted in formation of stable complexes, indicating that these two drugs are potentially useful as inhibitors of M.tb.

Self-reported Morisky Eight-item Medication Adherence Scale for Statins Concords with the Pill Count Method and Correlates with Serum Lipid Profile Parameters and Serum HMGCoA Reductase Levels

Background It is imperative that non-compliance with statins be identified and addressed to maximize their clinical benefits. Patient self-reporting methods are convenient to apply in clinical practice but need to be validated. Objective We studied the concordance of a patient self-report method, Morisky eight-item medication adherence scale (MMAS)), with the pill count method in measuring adherence with statins and their correlation with extended lipid profile parameters and serum hydroxyl-methylglutaryl coenzyme A reductase (HMGCoA-R) enzyme levels. Methods MMAS and the pill count method were used to measure the adherence with statins in patients on statins for any duration. Patients were subjected to an estimation of extended lipid profile and serum HMGCoA-R levels at the end of three months follow-up. Results Out of a total of 200 patients included in the study, 117 patients had a low adherence (score less than 6 on MMAS) whereas 65 and 18 patients had medium (score 6 or 7) and high adherence (score of 8), respectively. The majority of patients who had low adherence to statins by MMAS were nonadherent by the pill count method yielding a concordance of 96.5%. Medium or high adherence to statins by the MMAS method had a concordance of 89.1% with the pill count method. The levels of total cholesterol, low-density lipoprotein-cholesterol, apolipoprotein B, and HMGCoA-R were negatively correlated with compliance measured by pill count and MMAS in a statistically significant way and with similar correlation coefficients. HMGCoA-R levels demonstrated a plateau phenomenon, with levels being 9-10 ng/ml when compliance with statin therapy was greater than 60% by pill count and greater than 6 on the Morisky scale. Conclusion In conclusion, MMAS and the pill count method showed concordance in measuring adherence to statins. These methods need to be explored further for their interchangeability as surrogates for biomarker levels.

Electronic structure of iron dinitrogen complex [(TPB)FeN2]2−/1−/0: correlation to Mössbauer parameters

Low-valent species of iron are key intermediates in many important biological processes such as the nitrogenase enzymatic catalytic reaction. These species play a major role in activating highly stable N₂ molecules. Thus, there is a clear need to establish the factors which are responsible for the reactivity of the metal–dinitrogen moiety. In this regard, we have investigated the electronic structure of low-valent iron (2−/1−/0) in a [(TPB)FeN₂]^2−/1−/0 complex using density functional theory (DFT). The variation in the oxidation states of iron in the nitrogenase enzyme cycle is associated with the flexibility of Fe→B bonding. Therefore, the flexibility of Fe→B bonding acts as an electron source that sustains the formation of various oxidation states, which is necessary for the key species in dinitrogen activation. AIM calculations are also performed to understand the strength of Fe→B and Fe–N₂ bonds. A detailed interpretation of the contributions to the isomer shift (IS) and quadrupole splitting (ΔE_Q) are discussed. The major contribution to IS comes mainly from the 3s-contribution, which differs depending on the d orbital population due to different shielding. The valence shell contribution also comes from the 4s-orbital. The Fe–N₂ bond distance has a great influence on the Mössbauer parameters, which are associated with the radial distribution, i.e. the shape of the 4s-orbital and the charge density at the nucleus. A linear relationship between IS with Fe–N₂ and ΔE_Q with Fe–N₂ is observed.

We use density functional theory studies to explore the electronic structure, bonding and spectroscopic analysis of a low-valent iron (2−/1−/0) complex [(TPB)FeN₂]^2−/1−/0 and reveled the factor which affects the reactivity of the metal–dinitrogen moiety.

Bleomycin modulates amyloid aggregation in β-amyloid and hIAPP

Aberrant misfolding and amyloid aggregation, which result in amyloid fibrils, are frequent and critical pathological incidents in various neurodegenerative disorders. Multiple drugs or inhibitors have been investigated to avert amyloid aggregation in individual peptides, exhibiting sequence-dependent inhibition mechanisms. Establishing or inventing inhibitors capable of preventing amyloid aggregation in a wide variety of amyloid peptides is quite a daunting task. Bleomycin (BLM), a complex glycopeptide, has been widely used as an antibiotic and antitumor drug due to its ability to inhibit DNA metabolism, and as an antineoplastic, especially for solid tumors. In this study, we investigated the dual inhibitory effects of BLM on Aβ aggregation, associated with Alzheimer's disease and hIAPP, which is linked to type 2 diabetes, using both computational and experimental techniques. Combined results from drug repurposing and replica exchange molecular dynamics simulations demonstrate that BLM binds to the β-sheet region considered a hotspot for amyloid fibrils of Aβ and hIAPP. BLM was also found to be involved in β-sheet destabilization and, ultimately, in its reduction. Further, experimental validation through in vitro amyloid aggregation assays was obtained wherein the fibrillar load was decreased for the BLM-treated Aβ and hIAPP peptides in comparison to controls. For the first time, this study shows that BLM is a dual inhibitor of Aβ and hIAPP amyloid aggregation. In the future, the conformational optimization and processing of BLM may help develop various efficient sequence-dependent inhibitors against amyloid aggregation in various amyloid peptides.

Bleomycin acts as a dual inhibitor against both amyloid β and human islet amyloid polypeptide by binding to the β-sheet grooves considered as the amyloids hotspot.

Ameliorating amyloid aggregation through osmolytes as a probable therapeutic molecule against Alzheimer's disease and type 2 diabetes

Large numbers of neurological and metabolic disorders occurring in humans are induced by the aberrant growth of aggregated or misfolded proteins.

Machine Learning From Molecular Dynamics Trajectories to Predict Caspase-8 Inhibitors Against Alzheimer's Disease

Alzheimer’s disease (AD) is a neurodegenerative disorder in which the death of brain cells takes place leading to loss of memory and decreased cognitive ability. AD is a leading cause of death worldwide and is progressive in nature with symptoms worsening over time. Machine learning–based computational predictive models based on 2D and 3D descriptors have been effective in identifying potential active compounds. However, the use of data from molecular dynamics (MD) trajectories for training machine learning models still needs to be explored. In the present study, descriptors have been extracted from the MD trajectories of caspase-8 ligand complexes to train models using artificial neural networks and random forest algorithms. Caspase-8 plays a key role in causing AD by cleaving amyloid precursor proteins during apoptosis leading to increased formation of the amyloid-beta peptide. A total of 43 ligands were docked using the glide module of Schrodinger software, and short MD simulations of 10 ns were performed for the calculation of MD descriptors. The MD descriptors were also combined with the 2D and 3D descriptors of chemical compounds, and individual descriptor based as well as combination models were generated. This study demonstrated that MD descriptors could be effectively used for the characterization of bioactive compounds along with lead prioritization and optimization.

Computational models for the prediction of adverse cardiovascular drug reactions

Background

Predicting adverse drug reactions (ADRs) has become very important owing to the huge global health burden and failure of drugs. This indicates a need for prior prediction of probable ADRs in preclinical stages which can improve drug failures and reduce the time and cost of development thus providing efficient and safer therapeutic options for patients. Though several approaches have been put forward for in silico ADR prediction, there is still room for improvement.

Methods

In the present work, we have used machine learning based approach for cardiovascular (CV) ADRs prediction by integrating different features of drugs, biological (drug transporters, targets and enzymes), chemical (substructure fingerprints) and phenotypic (therapeutic indications and other identified ADRs), and their two and three level combinations. To recognize quality and important features, we used minimum redundancy maximum relevance approach while synthetic minority over-sampling technique balancing method was used to introduce a balance in the training sets.

Results

This is a rigorous and comprehensive study which involved the generation of a total of 504 computational models for 36 CV ADRs using two state-of-the-art machine-learning algorithms: random forest and sequential minimization optimization. All the models had an accuracy of around 90% and the biological and chemical features models were more informative as compared to the models generated using chemical features.

Conclusions

The results obtained demonstrated that the predictive models generated in the present study were highly accurate, and the phenotypic information of the drugs played the most important role in drug ADRs prediction. Furthermore, the results also showed that using the proposed method, different drugs properties can be combined to build computational predictive models which can effectively predict potential ADRs during early stages of drug development.

Electronic supplementary material

The online version of this article (10.1186/s12967-019-1918-z) contains supplementary material, which is available to authorized users.

Pyrazinamide drug resistance in RpsA mutant (∆438A) of Mycobacterium tuberculosis: Dynamics of essential motions and free-energy landscape analysis

Pyrazinamide is an essential first-line antitubercular drug which plays pivotal role in tuberculosis treatment. It is a prodrug that requires amide hydrolysis by mycobacterial pyrazinamidase enzyme for conversion into pyrazinoic acid (POA). POA is known to target ribosomal protein S1 (RpsA), aspartate decarboxylase (PanD), and some other mycobacterial proteins. Spontaneous chromosomal mutations in RpsA have been reported for phenotypic resistance against pyrazinamide. We have constructed and validated 3D models of the native and Δ438A mutant form of RpsA protein. RpsA protein variants were then docked to POA and long range molecular dynamics simulations were carried out. Per residue binding free-energy calculations, free-energy landscape analysis, and essential dynamics analysis were performed to outline the mechanism underlying the high-level PZA resistance conferred by the most frequently occurring deletion mutant of RpsA. Our study revealed the conformational modulation of POA binding site due to the disruptive collective modes of motions and increased conformational flexibility in the mutant than the native form. Residue wise MMPBSA decomposition and protein-drug interaction pattern revealed the difference of energetically favorable binding site in the wild-type (WT) protein in comparison with the mutant. Analysis of size and shape of minimal energy landscape area delineated higher stability of the WT complex than the mutant form. Our study provides mechanistic insights into pyrazinamide resistance in Δ438A RpsA mutant, and the results arising out of this study will pave way for design of novel and effective inhibitors targeting the resistant strains of Mycobacterium tuberculosis.

Molecular mechanism of acetoacetyl-CoA enhanced kinetics for increased bioplastic production from Cupriavidus necator 428

Polyhydroxyalkanoates are gaining importance due to their biodegradable nature and close analogy to plastics. Polyhydroxybutyrate (PHB) is the most widely used bioplastic from polyalkanoate family, which is produced by a legion of bacterial species via phbCAB operon encoding β-ketothiolase (PhaA), NADPH-dependent acetoacetyl-coenzyme A (acetoacetyl-CoA) reductase (PhaB) and polyhydroxyalkanoate synthase (PhaC). Augmentation in the activity of these enzymes is promising for increased PHB production which is achieved by enzyme engineering strategies including non-structural and structural approaches. Our study is deployed on directed evolution-based experimentally reported mutants of PhaB enzyme with increased efficiency due to impact on critical structural factors. We have analyzed and compared the native PhaB with two of its variants Q47L and T173S in complex with their cofactor i.e. NADPH as well as the substrate i.e. acetoacetyl-CoA, via long range molecular dynamics simulations. Interaction profile, MMPBSA, essential dynamics, and free energy landscape analysis revealed that the enzyme efficiency is critically affected by cofactor interactions. It was also observed that mutants have higher equilibrium constant with lesser but optimal affinity for substrate and cofactor than the wild type, which might be the reason for increased efficiency of the mutants via enhanced substrate and cofactor exchange rate. Our study provides insights into the cofactor and substrate binding affinities to PhaB enzyme at atomistic level, which will facilitate designing of highly efficient PhaB enzymes for increased PHB production. Communicated by Ramaswamy H. Sarma.

Structural basis for isoniazid resistance in KatG double mutants of Mycobacterium tuberculosis

The failure of drugs for effective treatment against infectious diseases can be attributed to resistant forms of causative agents. The evasive nature of Mycobacterium tuberculosis is partly associated to its physical features, such as having a thick cell wall and incorporation of beneficial mutations leading to drug resistance. The pro drug Isoniazid (INH) interacts with an enzyme catalase peroxidase to get converted into its active form and upon activation stops the cell wall synthesis thus killing the Mycobacterium. The most common mutation i.e. S315T leads to high degree of drug resistance by virtue of its position in the active site. Here, we have characterized the prominent attributes of two double mutant isolates S315 T/D194G and S315T/M624V which are multi drug resistant and extremely drug resistant, respectively. Protein models were generated using the crystal structure which were then subjected to energy minimization and long term molecular dynamics simulations. Further, computational analysis showed decreasing ability of INH binding to the mutants in order of: Native > S315T/D194G > S315T/M624V. Also, a trend was observed that as the docking score and binding area decreased, there was a significant increase in the distortion of the 3D geometry of the mutants as observed by PCA analysis.

Drug repurposing against arabinosyl transferase (EmbC) of Mycobacterium tuberculosis: Essential dynamics and free energy minima based binding mechanics analysis

Arabinosyl tranferases (embA, embB, embC) are the key enzymes responsible for biogenesis of arabinan domain of arabinogalactan (AG) and lipoarabinomannan (LAM), two major heteropolysaccharide constituents of the peculiar mycobacterial cell envelope. EmbC is predominantly responsible for LAM synthesis and has been commonly associated with Ethambutol resistance. We have screened the FDA library against EmbC to reposition a drug better than Ethambutol with higher binding affinity to Embc. High throughput virtual screening followed by extra precision docking using Glide gave two best leads i.e. Terlipressin and Amikacin with docking score of -11.39 kcal/mol and -10.71 kcal/mol, respectively. Binding mechanics of the selected drugs was elucidated through long range molecular dynamics simulations (100 ns) using binding free energy rescoring, essential dynamics and free energy minima based approaches, thus revealing the most stable binding modes of Terlipressin with EmbC. Our study establishes the EmbC binding potential of the repurposed drugs Terlipressin and Amikacin.