Target-based drug repurposing against Candida albicans-A computational modeling, docking, and molecular dynamic simulations study.

The emergence of multidrug-resistant strains of Candida albicans has become a global threat mostly due to co-infection with immune-compromised patients leading to invasive candidiasis. The life-threatening form of the disease can be managed quickly and effectively by drug repurposing. Thus, the study used in silico approaches to evaluate Food and Drug Administration (FDA) approved drugs against three drug targets-TRR1, TOM40, and YHB1. The tertiary structures of three drug targets were modeled, refined, and evaluated for their structural integrity based on PROCHECK, ERRAT, and PROSA. High-throughput virtual screening of FDA-approved drugs (8815), interaction analysis, and energy profiles had revealed that DB01102 (Arbutamine), DB01611 (Hydroxychloroquine), and DB09319 (Carindacillin) exhibited better binding affinity with TRR1, TOM40, and YHB1, respectively. Notably, the molecular dynamic simulation explored that Gln45, Thr119, and Asp288 of TRR1; Thr107 and Ser121 of TOM40; Arg193, Glu213, and Ser228 of YHB1 are crucial residues for stable drug-target interaction. Additionally, it also prioritized Arbutamine-TRR1 as the best drug-target complex based on MM-PBSA (-52.72 kcal/mol), RMSD (2.43 Å), and radius of gyration (-21.49 Å) analysis. In-depth, PCA results supported the findings of molecular dynamic simulations. Interestingly, the conserved region (>70%) among the TRR1 sequences from pathogenic Candida species indicated the effectiveness of Arbutamine against multiple species of Candida as well. Thus, the study dispenses new insight and enriches the understanding of developing an advanced technique to consider potential antifungals against C. albicans. Nonetheless, a detailed experimental validation is needed to investigate the efficacy of Arbutamin against life-threatening candidiasis.

A systematic review on distribution and antifungal resistance pattern of Candida species in the Indian population.

The emergence of antifungal drug resistance in Candida species has led to increased morbidity and mortality in immunocompromised patients. Understanding species distribution and antifungal drug resistance patterns is an essential step for novel drug development. A systematic review was performed addressing this challenge in India with keywords inclusive of 'Candida', 'Antifungal Drug Resistance', 'Candidemia', 'Candidiasis' and 'India'. A total of 106 studies (January 1978-March 2020) from 20 Indian states were included. Of over 11,429 isolates, Candida albicans was the major species accounting for 37.95% of total isolates followed by C. tropicalis (29.40%), C. glabrata (11.68%) and C. parapsilosis (8.36%). Rates of antifungal resistance were highest in non-albicans Candida (NAC) species - C. haemuloni (47.16%), C. krusei (28.99%), C. lipolytica (28.89%) and C. glabrata (20.69%). Approximately 10.34% isolates of C. albicans were observed to be drug resistant. Candida species were frequently resistant to certain azoles (ketoconazole-22.2%, miconazole-22.1% and fluconazole-21.8%). In conclusion, the present systematic review illustrates the overall distribution and antifungal resistance pattern of Candida species among the Indian population that could be helpful in the future for the formation of treatment recommendations for the region but also elsewhere. LAY SUMMARY: A total of 106 studies were reviewed to define the prevalence, distribution and antifungal resistance pattern of Candida species in India. The presented data could become the point of reference for all reported findings on Candida species in India.

Analysis of interleukin 23 and 7G10 interactions for computational design of lead antibodies against immune-mediated inflammatory diseases.

Wealth of structural data on theurapeutic targets in complex with monoclonal antibodies (mAbs) and advances in molecular modeling algorithms present exciting opportunities in the field of novel biologic design. Interleukin 23 (IL23), a well-known drug target for autoimmune diseases, in complex with mAb 7G10 offers prospect to design potent lead antibodies by traversing the complete epitope-paratope interface. Herein, key interactions aiding antibody-based neutralization in IL23-7G10 complex are resolute through PyMOL, LigPlot+, Antibody i-Patch, DiscoTope and FoldX. Six amino acids Ser31, Val33, Asn55, Lys59 in heavy chain and His34, Ser93 in light chain are subjected to in silico mutagenesis with residues Met, Trp, Ile, Leu and Arg. A set of 431 mutant macromolecules are outlined. Binding affinities of these molecules with IL23 are estimated through protein-protein docking by employing ZDOCK, ClusPro and RosettaDock. Subsequently, the macromolecules revealed comparable result with 7G10 are cross validated through binding free-energy calculations by applying Molecular Mechanics/Poisson Boltzman Surface Area method in CHARMM. Thirty nine designed theoretical antibodies showed improved outcome in all evaluations; from these, top 10 molecules showed at least nine unit better binding affinity compared to the known mAb. These molecules have the potential to act as lead antibodies. Subsequent molecular dynamics simulations too favored prospective of best ranked molecule to have therapeutic implications in autoimmune and inflammatory diseases. Abbreviations: IL23: interleukin 23; IL17: interleukin17; Ab: antibody; Ag: antigen; mAbs: monoclonal antibodies; STAT3: signal transducer and activator of transcription 3; STAT4: signal transducer and activator of transcription 4; PDB: protein databank; MM/PBSA: molecular mechanics Poisson-Boltzmann surface area; Ag-Ab: antigen- antibody complex; SPC/E: extended simple point charge; SD: steepest descents; PME: particle mesh ewald; dG: binding free energies; Fv: variable fragment.

dbGAPs: A comprehensive database of genes and genetic markers associated with psoriasis and its subtypes.

Psoriasis is a systemic hyperproliferative inflammatory skin disorder, although rarely fatal but significantly reduces quality of life. Understanding the full genetic component of the disease association may provide insight into biological pathways as well as targets and biomarkers for diagnosis, prognosis and therapy. Studies related to psoriasis associated genes and genetic markers are scattered and not easily amendable to data-mining. To alleviate difficulties, we have developed dbGAPs an integrated knowledgebase representing a gateway to psoriasis associated genomic data. The database contains annotation for 202 manually curated genes associated with psoriasis and its subtypes with cross-references. Functional enrichment of these genes, in context of Gene Ontology and pathways, provide insight into their important role in psoriasis etiology and pathogenesis. The dbGAPs interface is enriched with an interactive search engine for data retrieval along with unique customized tools for Single Nucleotide Polymorphism (SNP)/indel detection and SNP/indel annotations. dbGAPs is accessible at http://www.bmicnip.in/dbgaps/.

Probing binding mechanism of interleukin-6 and olokizumab: in silico design of potential lead antibodies for autoimmune and inflammatory diseases.

Computer-aided antibody engineering has been successful in the design of new biologics for disease diagnosis and therapeutic interventions. Interleukin-6 (IL-6), a well-recognized drug target for various autoimmune and inflammatory diseases such as rheumatoid arthritis, multiple sclerosis, and psoriasis, was investigated in silico to design potential lead antibodies. Here, crystal structure of IL-6 along with monoclonal antibody olokizumab was explored to predict antigen-antibody (Ag - Ab)-interacting residues using DiscoTope, Paratome, and PyMOL. Tyr56, Tyr103 in heavy chain and Gly30, Ile31 in light chain of olokizumab were mutated with residues Ser, Thr, Tyr, Trp, and Phe. A set of 899 mutant macromolecules were designed, and binding affinity of these macromolecules to IL-6 was evaluated through Ag - Ab docking (ZDOCK, ClusPro, and Rosetta server), binding free-energy calculations using Molecular Mechanics/Poisson Boltzman Surface Area (MM/PBSA) method, and interaction energy estimation. In comparison to olokizumab, eight newly designed theoretical antibodies demonstrated better result in all assessments. Therefore, these newly designed macromolecules were proposed as potential lead antibodies to serve as a therapeutics option for IL-6-mediated diseases.

Transforming respiratory tract infection diagnosis in the kingdom of saudi arabia through point-of-care testing: A white paper for policy makers.

With the evident increased prevalence of respiratory tract infections (RTIs) such as Respiratory Syncytial Virus (RSV), influenza, Group A Streptococcus (GAS), and COVID-19, the conventional diagnostic methods are considered sub-optimal in providing timely management to patients in the Kingdom of Saudi Arabia (KSA). Gaps in current diagnostics are magnified by the Kingdom's unique demographic composition, comprising 11.9 million foreign workers, and the annual influx of over 10 million pilgrims. Current gaps in timely diagnosis leads to delays in treatment, misuse of antibiotics, and protracted hospital stays, subsequently compromising patient care, and escalating healthcare costs. KSA healthcare stakeholders suggest that the integration of rapid molecular Point-of-Care Testing (POCT) into the Kingdom's healthcare infrastructure is an absolute necessity. This publication serves as an urgent call for action aimed at healthcare policymakers in Saudi Arabia, to review the existing diagnostic challenges and include rapid POCTs in the Saudi healthcare strategy for respiratory infections.

Exploring the molecular underpinning of psoriasis and its associated comorbidities through network approach: cross talks of genes and pathways.

Patients with psoriasis often complain of several linked disorders including autoimmune and cardiometabolic diseases. Understanding of molecular link between psoriasis and associated comorbidities would be of great interest at the point of patient care management. Integrative unbiased network approach, indicates significant unidirectional gene overlap between psoriasis and its associated comorbid condition including obesity (31 upregulated and 26 downregulated), ischemic stroke (14 upregulated and 2 downregulated), dyslipidaemia (5 upregulated, 5 downregulated), atherosclerosis (8 upregulated and 1 downregulated) and type II diabetes (5 upregulated, 5 downregulated). The analysis revealed substantial gene sharing among the different psoriasis-associated comorbidities. Molecular comorbidity index determining the strength of the interrelation between psoriasis and its comorbidities indicates prevalence of dyslipidaemia followed by type II diabetes among psoriasis patients. The Jaccard coefficient indices revealed psoriasis shared maximum number of biological pathways with dyslipidaemia followed by type 2 diabetes, ischemic stroke, obesity and atherosclerosis. Moreover, pathway annotation highlighted nearly 45 shared pathways amongst psoriasis and its comorbidities and a substantial number of shared pathways was found among multi-morbidities. Overall, the present study established conceivable link between psoriasis and comorbid diseases. The shared genes and overlapped pathways may be explored as a common productive target for psoriasis and its comorbid conditions. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03533-y.

Prevalence of Vascular Calcification in Chronic Kidney Disease Stage 4 and 5 Patients and its Correlation with Inflammatory Markers of Atherosclerosis.

Vascular calcification is one of the independent risk factors associated with cardiovascular disease (CVD) in chronic kidney disease (CKD) patients. This study evaluated the prevalence of vascular calcification in Indian patients with CKD stages 4 and 5. This was a prospective study conducted between January 2011 and June 2012. CKD stage 4 and 5 patients of either sex aged >18 years were screened for aortic vascular calcification using digital X-ray lumbar spine and multislice computed tomography (CT) scan. In addition, details of inflammatory markers [high-sensitivity C-reactive protein (hs-CRP) and interleukin (IL-6)] were also collected. A total of 150 patients (stage 4, n = 98; stage 5, n = 56) were screened for vascular calcification, and the mean age was 56.56 years. Patients with CKD stage 5 had significantly higher (P ≤0.05) serum creatinine and lower estimated glomerular filtration rate, total cholesterol, and low-density lipoprotein than CKD stage 4. Significantly, more patients with CKD stage 5 had a history of CVD. A total of 113 (75.3%) patients had vascular calcification [aortic calcification index (ACI) >0] with significantly higher prevalence in CKD stage 5 (85.72%) as compared to CKD stage 4 (69.15%). Patients having high aortic calcification (ACI >20%) were older (P = 0.0013); had a higher frequency of diabetes, and CVD; and had significantly (P <0.05) higher blood urea, serum creatinine, phosphorus, Ca × PO4 product, intact parathyroid hormone, hs-CRP, and IL-6. The higher CKD stage was associated with a higher prevalence of vascular calcification and higher aortic calcification index (ACI). CT techniques (electron beam CT and multislice CT) are the gold standards for detection and quantification of progression of vascular calcification.

Up-regulation of fibroblast growth factor receptor 1 due to prenatal tobacco exposure can lead to developmental defects in new born.

Introduction: Tobacco-smoking is one of the most important risk factor for preterm delivery, pregnancy loss, low birth weight, and fetal growth restriction. It is estimated that approximately 30% of growth-restricted neonates could be independently associated with maternal smoking.Methods: In this study, gene expression profile, GSE11798, was chosen from GEO database with an aim to perceive change in gene expression signature in new born due to maternal smoking. Enrichment analysis was performed to annotate differentially expressed genes (DEGs) through gene ontology and pathway analysis using DAVID. Protein-protein interactions and module detection of these DEGs were carried out using cytoscape v3.6.0. Thirty umbilical cord tissue samples from 15 smokers and 15 non-smokers pregnant women were included in this analysis.Results: Twenty-six differentially expressed genes (DEGs) between two groups were selected using GEO2R tool. The DEGs were observed to be participating in biological processes/pathways related to growth releasing hormone, angiogenesis, embryonic skeletal, and cardiac development. Fibroblast growth factor receptor-1 (FGFR1) was identified to be the hub node with 348 interacting partners, which regulates transcription, cell growth, differentiation, and apoptosis. The up-regulation of FGFR1 in umbilical cord tissue may lead to reproductive and developmental complications such as encephalocraniocutaneous lipomatosis, osteoglophonic dysplasia, and Pfeiffer syndrome in new-borns.Conclusion: The findings manifests the possibility of overcoming these adverse health effects in new born through FGFR1 modulating treatments during pregnancy.

Genome-wide screening and in silico gene knockout to predict potential candidates for drug designing against Candida albicans.

C. albicans infections are increasingly becoming a threat to public health with emergence of drug resistant strains. It emphasizes the need to look for alternate drug targets through genome-wide screening. In the present study, whole proteome of C. albicans SC5314 was analyzed in single click target mining workflow of TiDv2. A protein-protein interaction network (PPI) for the resulting putative targets was generated based on String database. Ninety four proteins with higher connectivity (degree ≥ 10) in the network are noted as hub genes. Among them, 24 are observed to be known targets while 70 are novel ones. Further, chokepoint analysis revealed FAS2, FOL1 and ERG5 as chokepoint enzymes in their respective pathways. Subsequently, the chokepoints were selected as prior interest for in silico gene knockout via MATLAB and COBRA Toolbox. In silico gene knockout pointed that FAS2 inhibition reduced the growth rate of pathogen from 0.2879 mmol.gDW-1.h-1 to zero. Furthermore, enzyme inhibition assay of FAS2 with cerulenin strengthen the computational outcome with MIC 1.25 µg/mL. Hence, the study establishes FAS2 as a promising target to design therapeutics against C. albicans.

An in silico approach towards identification of novel drug targets in pathogenic species of Leptospira.

Leptospirosis is one of the leading zoonotic infections worldwide. As with other infectious diseases, report of antimicrobial resistance to existing therapeutic arsenal poses challenges in the management of disease. Hence, identification of novel drug targets for the pathogen deems essential. Present study used combined approach of comparative and subtractive genomics to identify putative drug targets. Crucial genes of 16 pathogenic Leptospira strains were filtered and subjected to homology search via target identification tool "TiD". Thereafter, comparative analysis was performed for non-homologous, essential genes to accomplish the broad-spectrum drug target. Consequently, 37 essential genes were found to be conserved in at least 10 strains of Leptospira. Further, prioritization of resultant set of genes revealed 18 were hubs in protein-protein interaction network. Sixteen putative targets among the hub genes were conserved in all strains of Leptospira. Out of sixteen, fourteen were enzymes while 8 were novel and 4 were involved in virulence mechanism. In addition, genome scale metabolic network reconstruction and choke point analysis revealed cobA (porphyrin and chlorophyll metabolism) and thiL (thiamine metabolism) as chokepoints in their respective metabolic pathways. The proposed hub genes could act as putative broad-spectrum drug targets for Leptospira species, however, these putative targets should be validated to ensure them as real one prior to utilizing them for target based lead discovery.

Discovery of T-cell Driven Subunit Vaccines from Zika Virus Genome: An Immunoinformatics Approach.

The recent outbreaks of Zika virus and the absence of a specific therapy have necessitated to identify T-cell-stimulating antigenic peptides as potential subunit vaccine candidates. The translated ssRNA (+) genome of Zika virus was explored in EMBOSS antigenic and VaxiJen to predict 63 peptides as potential antigens. Three MHC-II binding peptide prediction tools, viz. NetMHCIIpan, PREDIVAC and immune epitope database (IEDB) were employed in consensus on 63 antigenic peptides to propose 14 T-helper cell epitopes. Similarly, analysis on 63 antigenic peptides through NetMHC, NetCTL and IEDB MHC-I binding peptide prediction tool led to identification of 14 CTL epitopes. Seven T-cell epitopes, C:44-66, M:135-149, NS2A:124-144, NS3:421-453, NS3:540-554, NS4B:90-134 and NS4B:171-188, are observed to share overlapping MHC-I and MHC-II binding motifs and hence, are being proposed to constitute minimum T-cell antigens to elicit protective T-cell immune response against Zika. Three of them, C:44-66, NS3:421-453 and NS3:540-554 are identified to be conserved across all the selected strains of Zika virus. Moreover, the 21 T-cell epitopes are non-self to humans and exhibited good coverage in variable populations of 14 geographical locations. Therefore, 21 T-cell epitopes are proposed as potential subunit vaccines against Zika virus.