Consolidated knowledge-guided computational pipeline for therapeutic intervention against bacterial biofilms - a review.

Biofilm-associated bacterial infections attributed to multifactorial antimicrobial resistance have caused worldwide challenges in formulating successful treatment strategies. In search of accelerated yet cost-effective therapeutics, several researchers have opted for bioinformatics-based protocols to systemize targeted therapies against biofilm-producing strains. The present review investigated the up-to-date computational databases and servers dedicated to anti-biofilm research to design/screen novel biofilm inhibitors (antimicrobial peptides/phytocompounds/synthetic compounds) and predict their biofilm-inhibition efficacy. Scrutinizing the contemporary in silico methods, a consolidated approach has been highlighted, referred to as a knowledge-guided computational pipeline for biofilm-targeted therapy. The proposed pipeline has amalgamated prominently employed methodologies in genomics, transcriptomics, interactomics and proteomics to identify potential target proteins and their complementary anti-biofilm compounds for effective functional inhibition of biofilm-linked pathways. This review can pave the way for new portals to formulate successful therapeutic interventions against biofilm-producing pathogens.

Translational protein RpsE as an alternative target for novel nucleoside analogues to treat MDR Enterobacter cloacae ATCC 13047: network analysis and molecular dynamics study.

The pathogenic Enterobacter cloacae subsp. cloacae str. ATCC 13047 has contemporarily emerged as a multi-drug resistant strain. To formulate an effective treatment option, alternative therapeutic methods need to be explored. The present study focused on Gene Interaction Network study of 46 antimicrobial resistance genes to reveal the densely interconnecting and functional hub genes in E. cloacae ATCC 13047. The AMR genes were subjected to clustering, topological and functional enrichment analysis, revealing rpsE (RpsE), acrA (AcrA) and arnT (ArnT) as novel therapeutic drug targets for hindering drug resistance in the pathogenic strain. Network topology further indicated translational protein RpsE to be exploited as a promising drug-target candidate for which the structure was predicted, optimized and validated through molecular dynamics simulations (MDS). Absorption, distribution, metabolism and excretion screening recognized ZINC5441082 (N-Isopentyladenosine) (Lead_1) and ZINC1319816 (cyclopentyl-aminopurinyl-hydroxymethyl-oxolanediol) (Lead_2) as orally bioavailable compounds against RpsE. Molecular docking and MDS confirmed the binding efficacy and protein-ligand complex stability. Furthermore, binding free energy (Gbind) calculations, principal component and free energy landscape analyses affirmed the predicted nucleoside analogues against RpsE protein to be comprehensively examined as a potential treatment strategy against E. cloacae ATCC 13047.

Impact of the COVID-19 pandemic on routine vaccine landscape: A global perspective.

The coronavirus disease (COVID-19) threat is subsiding through extensive vaccination worldwide. However, the pandemic imposed major disruptions in global immunization programs and has aggravated the risks of vaccine-preventable disease (VPD) outbreaks. Particularly, lower-middle-income regions with minimal vaccine coverage and circulating vaccine-derived viral strains, such as polio, suffered additional burden of accumulated zero-dose children, further making them vulnerable to VPDs. However, there is no compilation of routine immunization disruptions and recovery prospects. There is a noticeable change in the routine vaccination coverage across different phases of the pandemic in six distinct global regions. We have summarized the impact of COVID-19 on routine global vaccination programs and also identified the prospects of routine immunization to combat COVID-like outbreaks.

Bioactive phytocompounds against specific target proteins of Borrelia recurrentis responsible for louse-borne relapsing fever: Genomics and structural bioinformatics evidence.

Louse-borne relapsing fever (LBRF) with high untreated mortality caused by spirochete Borrelia recurrentis is predominantly endemic to Sub-Saharan Africa and has re-emerged in parts of Eastern Europe, Asia and Latin America due to population migrations. Despite subtractive evolution of lice-borne pathogenic Borrelia spp. from tick-borne species, there has been no comprehensive report on conservation of protein targets across tick and lice-borne pathogenic Borrelia nor exploration of phytocompounds that are toxic to tick against lice. From the 19 available whole genomes including B. recurrentis, B. burgdorferi, B. hermsii, B. parkeri and B. miyamotoi, conservation of seven drug targets (>80% domain identity) viz. 30 S ribosomal subunit proteins (RSP) S3, S7, S8, S14, S19, penicillin-binding protein-2 and 50 S RSP L16 were deciphered through multiple sequence alignments. Twelve phytocompounds (hydroxy-tyrosol, baicalein, cis-2-decanoic acid, morin, oenin, rosemarinic acid, kaempferol, piceatannol, rottlerin, luteolin, fisetin and monolaurin) previously explored against Lyme disease spirochete B. burgdorferi when targeted against LBRF-causing B. recurrentis protein targets revealed high multi-target affinity (2%-20% higher than conventional antibiotics) through molecular docking. However, based on high binding affinity against all target proteins, stable coarse-grained dynamics (fluctuations <1 Å) and safe pharmacological profile, luteolin was prioritized. The study encourages experimental evaluation of the potent phytocompounds and similar protocols for investigating other emerging vector-borne diseases.

Network metrics, structural dynamics and density functional theory calculations identified a novel Ursodeoxycholic Acid derivative against therapeutic target Parkin for Parkinson's disease.

Parkinson's disease (PD) has been designated as one of the priority neurodegenerative disorders worldwide. Although diagnostic biomarkers have been identified, early onset detection and targeted therapy are still limited. An integrated systems and structural biology approach were adopted to identify therapeutic targets for PD. From a set of 49 PD associated genes, a densely connected interactome was constructed. Based on centrality indices, degree of interaction and functional enrichments, LRRK2, PARK2, PARK7, PINK1 and SNCA were identified as the hub-genes. PARK2 (Parkin) was finalized as a potent theranostic candidate marker due to its strong association (score > 0.99) with α-synuclein (SNCA), which directly regulates PD progression. Besides, modeling and validation of Parkin structure, an extensive virtual-screening revealed small (commercially available) inhibitors against Parkin. Molecule-258 (ZINC5022267) was selected as a potent candidate based on pharmacokinetic profiles, Density Functional Theory (DFT) energy calculations (ΔE = 6.93 eV) and high binding affinity (Binding energy = -6.57 ± 0.1 kcal/mol; Inhibition constant = 15.35 µM) against Parkin. Molecular dynamics simulation of protein-inhibitor complexes further strengthened the therapeutic propositions with stable trajectories (low structural fluctuations), hydrogen bonding patterns and interactive energies (>0kJ/mol). Our study encourages experimental validations of the novel drug candidate to prevent the auto-inhibition of Parkin mediated ubiquitination in PD.

MurC ligase of multi-drug resistant Salmonella Typhi can be inhibited by novel Curcumin derivative: Evidence from molecular docking and dynamics simulations.

Emerging multi-drug resistance in recent Salmonella Typhi isolates, causative agent of enteric Typhoid fever, compelled us to investigate alternative therapeutic strategies. The present study encompassed virtual screening, ADMET screening as well as antibacterial activity prediction to shortlist potent lead molecules whose binding affinities (BAs) were checked against major druggable S. Typhi targets. BA profile revealed a deoxy-tetradeutero- curcumin derivative to be novel bioactive compound having high BA towards UDP-N-acetylmuramate-L-alanine ligase (MurC) protein involved in peptidoglycan synthesis. Molecular docking indicated that our lead {Binding energy (BE)= -8.00 ± 0.02 kcal/mol}could competitively bind to MurC with respect to its natural ligand ATP (BE= -7.65 ± 0.19 kcal/mol). The lead also possessed superior binding and inhibition profile against MurC than other commercial antibiotics. This BE was contributed by Hydrogen (H-) bonds and numerous non-canonical interactions with the evolutionary conserved active-site residues. From molecular docking and coarse-grained dynamics simulations, it was inferred that the novel curcumin derivative was predicted to be potential competitive inhibitor of ATP for MurC-catalytic domain having low relative RMSF (0.59 Å) to inhibit MurC-induced peptidoglycan biosynthesis. The inferences drawn from the study can open new portals for designing efficient therapeutic strategies against S. Typhi.

Non-steroidal anti-inflammatory drugs ketorolac and etodolac can augment the treatment against pneumococcal meningitis by targeting penicillin-binding proteins.

BACKGROUND: Streptococcus pneumoniae is the principal etiological agent of acute bacterial meningitis (ABM) which has fatal outcome in children and elderly. Due to poor blood-brain barrier (BBB) permeation, conventional ß-lactam antibiotics fail to establish the requisite bactericidal concentration in central nervous system leading to resistance in meningeal infections. The present study intended to identify potential therapeutic alternatives against Streptococcal meningitis. METHODS: Virtual screening, pharmacokinetics/pharmacodynamics (PK/PD) and anti-bacterial evaluations were employed to screen potential drugs. Molecular docking and structural dynamics simulations were performed to analyze the binding affinity and interaction stability of the drugs against the conventional Penicillin binding protein (PBP) targets. Screened drugs were also checked for interactions with other possible Streptococcal targets and relevant host targets. RESULTS: Non-steroidal anti-inflammatory drugs (NSAIDs) ketorolac and etodolac exhibiting high BBB-permeation and anti-bacterial potency were identified. Ketorolac and etodolac possessed uniform binding affinities against PBP1A, PBP2X, PBP2B and PBP3 with low inhibition constants (<50 µM). Against PBP2B and PBP3, higher binding affinities were observed for ketorolac (-6.45 and -6Kcal/mol respectively) and etodolac (-6.36 and -6.55Kcal/mol respectively) than penicillin (-5.95 and -5.85Kcal/mol respectively) and cefotaxime (-5.08 and -5.07Kcal/mol respectively). The binding affinities were contributed by conventional H-bonds and non-canonical interactions with active site residues of PBPs. Structural dynamics simulations further indicated the overall stability of the drug-bound complexes through minimal overall average root-mean square fluctuations (RMSFs) (<1.0 Å). The average binding affinities of Ketorolac and Etodolac with PBPs were marginally higher than other Streptococcal targets and comparable to their conventional inflammatory targets. CONCLUSION: Pharmacological and structural profiles indicated that ketorolac and etodolac can potentially subdue the cause and effects of streptococcal meningitis and hence encourage experimental validations.

A comprehensive review on genomics, systems biology and structural biology approaches for combating antimicrobial resistance in ESKAPE pathogens: computational tools and recent advancements.

In recent decades, antimicrobial resistance has been augmented as a global concern to public health owing to the global spread of multidrug-resistant strains from different ESKAPE pathogens. This alarming trend and the lack of new antibiotics with novel modes of action in the pipeline necessitate the development of non-antibiotic ways to treat illnesses caused by these isolates. In molecular biology, computational approaches have become crucial tools, particularly in one of the most challenging areas of multidrug resistance. The rapid advancements in bioinformatics have led to a plethora of computational approaches involving genomics, systems biology, and structural biology currently gaining momentum among molecular biologists since they can be useful and provide valuable information on the complex mechanisms of AMR research in ESKAPE pathogens. These computational approaches would be helpful in elucidating the AMR mechanisms, identifying important hub genes/proteins, and their promising targets together with their interactions with important drug targets, which is a crucial step in drug discovery. Therefore, the present review aims to provide holistic information on currently employed bioinformatic tools and their application in the discovery of multifunctional novel therapeutic drugs to combat the current problem of AMR in ESKAPE pathogens. The review also summarizes the recent advancement in the AMR research in ESKAPE pathogens utilizing the in silico approaches.

Datasets comprising the quality validations of simulated protein-ligand complexes and SYBYL docking scores of bioactive natural compounds as inhibitors of Mycobacterium tuberculosis protein-targets.

Docking scores and simulation parameters to study the potency of natural compounds against protein targets in Mycobacterium tuberculosis (Mtb) were retrieved through molecular docking and in-silico structural investigation. The molecular docking datasets comprised 15 natural compounds, seven conventional anti-tuberculosis (anti-TB) drugs and their seven corresponding Mtb target proteins. Mtb protein targets were actively involved in translation mechanism, nucleic acid metabolism and membrane integrity. Standard structural screening and stereochemical optimizations were adopted to generate the 3D protein structures and their corresponding ligands prior to molecular docking. Force-field integration and energy minimization were further employed to obtain the proteins in their ideal geometry. Surflex-dock algorithm using Hammerhead scoring functions were used to finally produce the docking scores between each protein and the corresponding ligand(s). The best-docked complexes selected for simulation studies were subjected to topology adjustments, charge neutralizations, solvation and equilibrations (temperature, volume and pressure). The protein-ligand complexes and molecular dynamics parameter files have been provided. The trajectories of the simulated parameters such as density, pressure and temperature were generated with integrated tools of the simulation suite. The datasets can be useful to computational and molecular medicine researchers to find therapeutic leads relevant to the chemical behaviours of a specific class of compounds against biological systems. Structural parameters and energy functions provided a set of standard values that can be utilised to design simulation experiments regarding similar macromolecular interactions.

Elucidating the multi-drug resistance mechanism of Enterococcus faecalis V583: A gene interaction network analysis.

Resistance to antibiotics have created havoc around the globe due to the emergence of multi-drug resistant (MDR) pathogenic bacterial strains. To decipher this problem, a detailed understanding of the antimicrobial resistance (AMR) genes and their resistant mechanisms are obligatory. The present study is mainly focused on an opportunistic, nosocomial bacterial strain Enterococcus faecalis V583, which possess acquired exogenous AMR genes portraying resistance against Chloramphenicol, Tetracycline, Vancomycin, Linezolid, Ampicillin and other antibiotics. An interaction network of eight AMR genes along with 40 functional partners have been constructed and analysed. Functional enrichment analysis highlighted 20, 21 and 22 genes having significant roles in Cellular Component (CC), Molecular Functions (MF) and Biological Process (BP) respectively. Clustering analysis resulted in four densely interconnected clusters (C1-C4) which were associated with three AMR mechanisms that include the alteration in drug target (pbps, mur and van genes), complete replacement/bypass of target sites (van genes) and ATP Binding Cassette (ABC) transporter efflux pump mechanisms (msrA, EF_1680, EF_1682 and pbps). Our results showed that the genes responsible for ß-lactams resistance (pbp1A, 1C, 2A, 2B); glycopeptide resistance (ddl, vanBHBRBSBWXYB); Erythromycin, Macrolides, Lincosamide and Streptogramin-B (MLSB) resistance (msrA, EF_1680, EF_1682) along with mur genes (murABBCDEFG) played an important role in MDR mechanisms. Network analysis has shown the genes mraY, pbpC, murE, murG and murD possessed 26, 24, 23, 22 and 22 interactions respectively. With more number of direct interactions, these genes can be considered as hub genes that could be exploited as potential drug targets for new drug discovery.

Gene interaction network studies to decipher the multi-drug resistance mechanism in Salmonella enterica serovar Typhi CT18 reveal potential drug targets.

Salmonella enterica subsp. enterica serovar Typhi, a human enteric pathogen causing typhoid fever, developed resistance to multiple antibiotics over the years. The current study was dedicated to understand the multi-drug resistance (MDR) mechanism of S. enterica serovar Typhi CT18 and to identify potential drug targets that could be exploited for new drug discovery. We have employed gene interaction network analysis for 44 genes which had 275 interactions. Clustering analysis resulted in three highly interconnecting clusters (C1-C3). Functional enrichment analysis revealed the presence of drug target alteration and three different multi-drug efflux pumps in the bacteria that were associated with antibiotic resistance. We found seven genes (arnA,B,C,D,E,F,T) conferring resistance to Cationic Anti-Microbial Polypeptide (CAMP) molecules by membrane Lipopolysaccharide (LPS) modification, while macB was observed to be an essential controlling hub of the network and played a crucial role in MacAB-TolC efflux pump. Further, we identified five genes (mdtH, mdtM, mdtG, emrD and mdfA) which were involved in Major Facilitator Superfamily (MFS) efflux system and acrAB contributed towards AcrAB-TolC efflux pump. All three efflux pumps were seen to be highly dependent on tolC gene. The five genes, namely tolC, macB, acrA, acrB and mdfA which were involved in multiple resistance pathways, can act as potential drug targets for successful treatment strategies. Therefore, this study has provided profound insights into the MDR mechanism in S. Typhi CT18. Our results will be useful for experimental biologists to explore new leads for S. enterica.