Toward novel inhibitors against KdsB: a highly specific and selective broad-spectrum bacterial enzyme

Identification of novel chemical scaffolds against kinase domain of cancer causing human epidermal growth factor receptor 2: a systemic chemoinformatic approach

The Human epidermal growth factor receptor 2 (HER2) is expressed in high magnitude in several cancers. Designing new drug molecules that target kinase domain of the HER2 enzyme might provide an appealing platform. Considering this, herein, a multi-phase bioinformatic approach is applied to screen diverse natural and chemical scaffolds to identify compounds that fit best at the kinase domain of HER2. By doing so, three compounds; LAS_51187157, LAC_51217113, LAC_51390233 were pointed with docking score of -11.4 kcal/mol, -11.3 kcal/mol and -11.2 kcal/mol, respectively. In molecular dynamic simulation, the complexes behaved in a stable dynamic with no major local/global structural variations. The intermolecular binding free energies were further estimated that concluded LAC_51390233 complex was the most stable and has less entropy energy. The good docked affinity of LAC_51390233 with HER2 was confirmed by WaterSwap absolute binding free energy. The entropy energy demonstrated that LAC_51390233 has less freedom energy compared to others. Similarly, all three compounds revealed very favorable druglike properties and pharmacokinetics. All the selected three compounds were also non-carcinogenic, non-immunotoxicity, non-mutagenicity, and non-cytotoxic. In a nutshell, the compounds are interesting scaffolds and might be subjected to extensive experimental testing to reveal their real biological potency.Communicated by Ramaswamy H. Sarma.

Targeting XGHPRT enzyme to manage Helicobacter pylori induced gastric cancer: A multi-pronged machine learning, artificial intelligence and biophysics-based study

Helicobacter pylori infects the stomach mucosa of over half of the global population and can lead to gastric cancer. This pathogen has demonstrated resistance to many frequently prescribed antibiotics, thereby underscoring the pressing need to identify novel therapeutic targets. The inhibition or disruption of nucleic acid biosynthesis constitutes a promising avenue for either restraining or eradicating bacterial proliferation. The synthesis of RNA and DNA precursors (6-oxopurine nucleoside monophosphates) is catalyzed by the XGHPRT enzyme. In this study, using machine learning, artificial intelligence and biophysics-based software, CHEMBRIDGE-10000196, CHEMBRIDGE-10000295, and CHEMBRIDGE-10000955 were predicted as promising binders to the XGHPRT with a binding score of -14.20, -13.64, and -12.08 kcal/mol, respectively, compared to a control guanosine-5'-monophosphate exhibiting a docking score of -10.52 kcal/mol. These agents formed strong interactions with Met33, Arg34, Ala57, Asp92, Ser93, and Gly94 at short distance. The docked complexes of the lead compounds exhibited stable dynamics during the simulation time with no global changes noticed. The docked complexes demonstrate a significantly stable MM-GBSA and MM-PBSA net binding energy of -60.1 and -61.18 kcal/mol for the CHEMBRIDGE-10000196 complex. The MM-GBSA net energy value of the CHEMBRIDGE-10000295 complex and the CHEMBRIDGE-10000955 complex is -71.17 and -65.29 kcal/mol, respectively. The CHEMBRIDGE-10000295 and CHEMBRIDGE-10000955 complexes displayed a net value of -71.91 and -63.49 kcal/mol, respectively, as per the MM-PBSA. The major driving intermolecular interactions for the docked complexes were found to be the electrostatic and van der Waals. The three filtered molecules hold potential for experimental evaluation of their potency against the XGHPRT enzyme.

Unveiling MurE ligase potential inhibitors for treating multi-drug resistant Acinetobacter baumannii

Acinetobacter baumannii is an opportunistic pathogen with ability to cause serious infection such as bacteremia, ventilator associated pneumonia, and wound infections. As strains of A. baumannii are resistant to almost all clinically used antibiotics and with the emergence of carbapenems resistant phenotypes warrants the search for novel antibiotics. Considering this, herein, a series of computer aided drug designing approach was utilized to search novel chemical scaffolds that bind stronger to MurE ligase enzyme of A. baumannii, which is involved peptidoglycan synthesis. The work identified LAS_22461675, LAS_34000090 and LAS_51177972 compounds as promising binding molecules with MurE enzyme having binding energy score of -10.5 kcal/mol, -9.3 kcal/mol and -8.6 kcal/mol, respectively. The compounds were found to achieve docked inside the MurE substrate binding pocket and established close distance chemical interactions. The interaction energies were dominated by van der Waals and less contributions were seen from hydrogen bonding energy. The dynamic simulation assay predicted the complexes stable with no major global and local changes noticed. The docked stability was also validated by MM/PBSA and MM/GBSA binding free energy methods. The net MM/GBSA binding free energy of LAS_22461675 complex, LAS_34000090 complex and LAS_51177972 complex is -26.25 kcal/mol, -27.23 kcal/mol and -29.64 kcal/mol, respectively. Similarly in case of MM-PBSA, the net energy value was in following order; LAS_22461675 complex (-27.67 kcal/mol), LAS_34000090 complex (-29.94 kcal/mol) and LAS_51177972 complex (-27.32 kcal/mol). The AMBER entropy and WaterSwap methods also confirmed stable complexes formation. Further, molecular features of the compounds were determined that predicted compounds to have good druglike properties and pharmacokinetic favorable. The study concluded the compounds to good candidates to be tested by in vivo and in vitro experimental assays.Communicated by Ramaswamy H. Sarma.

A hierarchical approach towards identification of novel inhibitors against L, D-transpeptidase YcbB as an anti-bacterial therapeutic target

The bacterial cell wall, being a vital component for cell viability, is regarded as a promising drug target. The L, D-Transpeptidase YcbB enzyme has been implicated for a significant role in cell wall polymers cross linking during typhoid toxin release, β-lactam resistance and outer membrane defect rescue. These observations have been recorded in different bacterial pathogens such as Salmonella Typhimurium, Citrobacter rodentium, and Salmonella typhi. In this work, we have shown structure based virtual screening of diverse natural and synthetic drug libraries against the enzyme and revealed three compounds as LAS_32135590, LAS_34036730 and LAS-51380924. These compounds showed highly stable energies and the findings are very competitive with the control molecule ((1RG or (4 R,5S)-3-({(3S,5S)-5-[(3-carboxyphenyl)carbamoyl]pyrrolidin-3-yl}sulfanyl)-5-[(1S,2R)-1-formyl-2-hydroxypropyl]-4-methyl-4,5-dihydro-1H-pyrrole-2-carboxylic acid or ertapenem)) used. Compared to control (which has binding energy score of -11.63 kcal/mol), the compounds showed better binding energy. The binding energy score of LAS_32135590, LAS_34036730 and LAS-51380924 is -12.63 kcal/mol, -12.22 kcal/mol and -12.10 kcal/mol, respectively. Further, the docked snapshot of the lead compounds and control were investigated for stability under time dependent dynamics environment. All the three leads complex and control system showed significant equilibrium (mean RMSD < 3 Å) both in term of intermolecular docked conformation and binding interactions network. Further validation on the complex's stability was acquired from the end-state MMPB/GBSA analysis that observed greater contribution from van der Waals forces and electrostatic energy while less contribution was noticed from solvation part. The compounds were also showed good drug-likeness and are non-toxic and non-mutagenic. In short, the compounds can be used in experimental testing's and might be subjected to structure modification to get better results.Communicated by Ramaswamy H. Sarma.

Discovery of novel inhibitor via molecular dynamics simulations against D-alanyl-D-alanine carboxypeptidase of Enterobacter cloacae

Antibiotics resistance by bacterial pathogens is a major concern to public health worldwide resulting in high health care costs and rising mortality. Subtractive proteomics prioritized D-alanyl-D-alanine carboxypeptidas (DacB) enzyme from Enterobacter cloacae ATCC 13047 as a potential candidate for drugs designing to block pathogen cell wall biosynthesis. Virtual screening of an antibacterial library against the target unraveled a hit compound (2-[(1-methylsulfonylpiperidin-3-yl)methyl]-6-(1H-pyrazol-4-yl) pyrazine) showing high affinity and stability with the target. The N-methyl-N-propyl-methanesulfonamide of the compound is seen as a closed affinity towards domain involving strong hydrogen bonds with Ser41, Lys44, Ser285, and Asn287. The 4-methyl-1H-pyrazole is posed towards the open cavity of domain I and II and formed hydrophobic and hydrophilic contacts. The system is highly stable with average carbon-alpha deviations of 1.69 Å over trajectories of 400-ns. Three vital residues projected: Arg437, Arg438 and Leu400 from enzyme pocket via Radial distribution function (RDF) assay, which actively engaged the inhibitor. Further confirmation is done by estimating binding free energies, which confirms the very low delta energy of -7.24 kcal/mol in Generalized Born (GB) method and -7.4363 kcal/mol in Poisson-Boltzmann (PB) method. WaterSwap calculations were performed that revealed the energies highly converged, an agreement on good system stability. Lastly, three DacB mutants were created to investigate the role of functional active residues and a decline in binding affinity of the residues was noticed. These computational results provide a gateway for experimentalists to further confirm their efficacy both in-vitro and in-vivo.Communicated by Ramaswamy H. Sarma.

Cheminformatics and biomolecular dynamics studies towards the discovery of anti-staphylococcal nuclease domain-containing 1 (SND1) inhibitors to treat metastatic breast cancer

Metastatic breast cancer is a prime health concern and leading health burden across the globe. Previous efforts have shown that protein-protein interaction between Metadherin and Staphylococcal nuclease domaincontaining 1 (SND1) promotes initiation of breast cancer, progression, therapy resistance and metastasis. Therefore, small drug molecules that can interrupt the Metadherin and SND1 interaction may be ideal to suppress tumor growth, metastasis and increases chemotherapy sensitivity of triple negative breast cancer. Here, in this study, structure based virtual screening was conducted against the reported active site of SND1 enzyme, which revealed three promising lead molecules from Asinex library. These compounds were; BAS_00381028, BAS_00327287, and BAS_01293454 with binding energy score -10.25 kcal/mol, -9.65 kcal/mol and -9.32 kcal/mol, respectively. Compared to control (5-chloro-2-methoxy-N-([1,2,4]triazolo[1,5-a]pyridin-8-yl)benzene-1-sulfonamide) the lead molecules showed robust hydrophilic and hydrophobic interactions with the enzyme and revealed stable docked conformation in molecular dynamics simulation. During the simulation time, the compounds reported stable dynamics with no obvious fluctuation in binding mode and interactions noticed. The mean root mean square deviation (RMSD) of BAS_00381028, BAS_00327287, and BAS_01293454 complexes were 1.87 Å, 1.75 Å, 1.34 Å, respectively. Furthermore, the MM/GBSA analysis was conduction on the simulation trajectories of complexes that unveiled binding energy score of -19.25 kcal/mol, -27.03 kcal/mol, -34.6 kcal/mol and -29.61 kcal/mol for control, BAS_00381028, BAS_00327287, and BAS_01293454, respectively. In MM/PBSA, the binding energy value of for control, BAS_00381028, BAS_00327287, and BAS_01293454 was -20.45 kcal/mol, -27.89 kcal/mol, -36.41 kcal/mol and -32.01 kcal/mol, respectively. Additionally, the compounds were classified as druglike and have favorable pharmacokinetic properties. The compounds were predicted as promising leads and might be used in experimental investigation to study their anti-SND1 activity.

Identification of promising methionine aminopeptidase enzyme inhibitors: A combine study of comprehensive virtual screening and dynamics simulation study

Methionine aminopeptidase (MetAP) enzymes play a critical role in bacterial cell survival by cleaving formyl-methionine initiators at N-terminal of nascent protein, a process which is vital in proper protein folding. This makes MetAP an attractive and novel antibacterial target to unveil promising antibiotics. In this study, the crystal structure of R. prowazekii MetAP was used in structure-based virtual screening of drug libraries such as Asinex antibacterial library and Comprehensive Marine Natural Products Database (CMNPD) to identify promising lead molecules against the enzyme. This shortlisted three drug molecules; BDE-25098678, BDE-30686468 and BDD_25351157 as most potent leads that showed strong binding to the MetAP enzyme. The static docked conformation of the compounds to the MetAP was reevaluated in molecular dynamics simulation studies. The analysis observed the docked complexes as stable structure with no major local or global deviations noticed. These findings suggest the formation of strong intermolecular docked complexes, which showed stable dynamics and atomic level interactions network. The binding free energy analysis predicted net MMGBSA energy of complexes as: BDE-25098678 (-73.41 kcal/mol), BDE-30686468 (-59.93 kcal/mol), and BDD_25351157 (-75.39 kcal/mol). In case of MMPBSA, the complexes net binding energy was as; BDE-25098678 (-77.47 kcal/mol), BDE-30686468 (-69.47 kcal/mol), and BDD_25351157 (-75.6 kcal/mol). Further, the compounds were predicted to follow the famous Lipinski rule of five and have non-toxic, non-carcinogenic and non-mutagenic profile. The screened compounds might be used in experimental test to highlight the real anti- R. prowazekii MetAP activity.

A cheminformatics-biophysics correlate to identify promising lead molecules against matrix metalloproteinase-2 (MMP-2) enzyme: A promising anti-cancer target

Matrix metalloproteinase-2 (MMP-2) is an endopeptidase enzyme that is devoted to extracellular matrix proteins degradation. The enzyme is warranted as promising drugs target for different light threating diseases such as arthritis, cancer and fibrosis. Herein, in this study, three drug molecules: CMNPD8322, CMNPD8320, and CMNPD8318 were filtered as high affinity binding compounds with binding energy score of -9.75 kcal/mol, -9.11 kcal/mol, -9.05 kcal/mol, respectively. The control binding energy score was -9.01 kcal/mol. The compounds docked deeply inside the pocket interacting with S1 pocket residues. The docked complexes dynamics in real time at cellular environment was then done to decipher the stable binding conformation and intermolecular interactions network. The compounds complexes achieved very stable dynamics with root mean square deviation (RMSD) with mean value of around 2-3 Å compared to control complex that showed higher fluctuations of 5 Å. The simulation trajectories frames based binding free energy demonstrated all the compounds-MMP-2 complexes reported highly stable energy, particularly the van der Waals energy dominate the overall net energy. Similarly, the complexes revalidation of WaterSwap based energies also disclosed the complexes highly stable in term docked conformation. Also, the compounds illustrated the compounds favorable pharmacokinetics and were non-toxic and non-mutagenic. Thus, the compounds might be used thorough experimental assays to confirm compounds selective biological potency against MMP-2 enzyme.

An integrated computational approach towards novel drugs discovery against polyketide synthase 13 thioesterase domain of Mycobacterium tuberculosis

The acquired drug resistance by Mycobacterium tuberculosis (M. tuberculosis) to antibiotics urges the need for developing novel anti-M. tuberculosis drugs that possess novel mechanism of action. Since traditional drug discovery is a labor-intensive and costly process, computer aided drug design is highly appreciated tool as it speeds up and lower the cost of drug development process. Herein, Asinex antibacterial compounds were virtually screened against thioesterase domain of Polyketide synthase 13, a unique enzyme that forms α-alkyl β-ketoesters as a direct precursor of mycolic acids which are essential components of the lipid-rich cell wall of M. tuberculosis. The study identified three drug-like compounds as the most promising leads; BBB_26582140, BBD_30878599 and BBC_29956160 with binding energy value of - 11.25 kcal/mol, - 9.87 kcal/mol and - 9.33 kcal/mol, respectively. The control molecule binding energy score is -9.25 kcal/mol. Also, the docked complexes were dynamically stable with maximum root mean square deviation (RMSD) value of 3 Å. Similarly, the MM-GB\PBSA method revealed highly stable complexes with mean energy values < - 75 kcal/mol for all three systems. The net binding energy scores are validated by WaterSwap and entropy energy analysis. Furthermore, The in silico druglike and pharmacokinetic investigation revealed that the compounds could be suitable candidates for additional experimentations. In summary, the study findings are significant, and the compounds may be used in experimental validation pipeline to develop potential drugs against drug-resistant tuberculosis.

Alterations of the intestinal microbiota in age-related macular degeneration

Purpose

Age-related macular degeneration (AMD) is the leading cause of vision loss in those over the age of 50. Recently, intestinal microbiota has been reported to be involved in the pathogenesis of ocular diseases. The purpose of this study was to discover more about the involvement of the intestinal microbiota in AMD patients.

Methods

Fecal samples from 30 patients with AMD (AMD group) and 17 age- and sex-matched healthy controls (control group) without any fundus disease were collected. DNA extraction, PCR amplification, and 16S rRNA gene sequencing of the samples were performed to identify intestinal microbial alterations. Further, we used BugBase for phenotypic prediction and PICRUSt2 for KEGG Orthology (KO) as well as metabolic feature prediction.

Results

The intestinal microbiota was found to be significantly altered in the AMD group. The AMD group had a significantly lower level of Firmicutes and relatively higher levels of Proteobacteria and Bacteroidota compared to those in the control group. At the genus level, the AMD patient group showed a considerably higher proportion of Escherichia-Shigella and lower proportions of Blautia and Anaerostipes compared with those in the control group. Phenotypic prediction revealed obvious differences in the four phenotypes between the two groups. PICRUSt2 analysis revealed KOs and pathways associated with altered intestinal microbiota. The abundance of the top eight KOs in the AMD group was higher than that in the control group. These KOs were mainly involved in lipopolysaccharide biosynthesis.

Conclusion

The findings of this study indicated that AMD patients had different gut microbiota compared with healthy controls, and that AMD pathophysiology might be linked to changes in gut-related metabolic pathways. Therefore, intestinal microbiota might serve as non-invasive indicators for AMD clinical diagnosis and possibly also as AMD treatment targets.

Fibroblast growth factor 2 is a druggable target against glioblastoma: A computational investigation

Fibroblast growth factor 2 (FGF2) is a key player in cancer and tissue homeostasis and regulates renewal of several stem cell types. The FGF2 role in malignant glioma is proven and tagged FGF2, a novel druggable target, is used for developing potent drugs against glioblastoma. In this study, Asinex 51412372, Asinex 51217461, and Asinex 51216586 were filtered to show the best binding affinity for FGF2 with binding energy scores of -8.3 kcal/mol, -8.2 kcal/mol, and -7.8 kcal/mol, respectively. The compounds showed chemical interactions with several vital residues of FGF2 along the compound length. The noticeable residues that interacted with the compounds were Arg15, Asp23, Arg63, and Gln105. In dynamic investigation in solution, the FGF2 reported unstable dynamics in the first 100 ns and gained structural equilibrium in the second phase of 100 ns. The maximum root mean square deviation (RMSD) value touched by the systems is 3 Å. Similarly, the residue flexibility of FGF2 in the presence of compounds was within a stable range and is compact along the simulation time length. The compounds showed robust atomic-level stable energies with FGF2, which are dominated by both van der Waals and electrostatic interactions. The net binding energy of systems varies between -40 kcal/mol and -86 kcal/mol, suggesting the formation of strong intermolecular docked complexes. The drug-likeness and pharmacokinetic properties also pointed toward good structures that are not toxic, have high gastric absorption, showed good distribution, and readily excreted from the body. In summary, the predicted compounds in this study might be ideal hits that might be further optimized for structure and activity during experimental studies.

Ecogenomics reveals viral communities across the Challenger Deep oceanic trench

Despite the environmental challenges and nutrient scarcity, the geographically isolated Challenger Deep in Mariana trench, is considered a dynamic hotspot of microbial activity. Hadal viruses are the least explored microorganisms in Challenger Deep, while their taxonomic and functional diversity and ecological impact on deep-sea biogeochemistry are poorly described. Here, we collect 13 sediment cores from slope and bottom-axis sites across the Challenger Deep (down to ~11 kilometers depth), and identify 1,628 previously undescribed viral operational taxonomic units at species level. Community-wide analyses reveals 1,299 viral genera and distinct viral diversity across the trench, which is significantly higher at the bottom-axis vs. slope sites of the trench. 77% of these viral genera have not been previously identified in soils, deep-sea sediments and other oceanic settings. Key prokaryotes involved in hadal carbon and nitrogen cycling are predicted to be potential hosts infected by these viruses. The detected putative auxiliary metabolic genes suggest that viruses at Challenger Deep could modulate the carbohydrate and sulfur metabolisms of their potential hosts, and stabilize host's cell membranes under extreme hydrostatic pressures. Our results shed light on hadal viral metabolic capabilities, contribute to understanding deep sea ecology and on functional adaptions of hadal viruses for future research.

Novel Chimeric Vaccine Candidate Development against Leptotrichia buccalis

The misuse of antibiotics in our daily lives has led to the emergence of antimicrobial resistance. As a result, many antibiotics are becoming ineffective. This phenomenon is linked with high rates of mortality and morbidity. Therefore, new approaches are required to address this major health issue. Leptotrichia buccalis is a Gram-negative, rod-shaped bacterium which normally resides in the oral and vaginal cavities. It is an emerging bacterial pathogen which is developing new antibiotic-resistance mechanisms. No approved vaccine is available against this pathogen, which is a cause for growing concern. In this study, an in silico-based, multi-epitopes vaccine against this pathogen was designed by applying reverse vaccinology and immunoinformatic approaches. Of a total of 2193 predicted proteins, 294 were found to be redundant while 1899 were non-redundant. Among the non-redundant proteins, 6 were predicted to be present in the extracellular region, 12 in the periplasmic region and 23 in the outer-membrane region. Three proteins (trypsin-like peptidase domain-containing protein, sel1 repeat family protein and TrbI/VirB10 family protein) were predicted to be virulent and potential subunit vaccine targets. In the epitopes prediction phase, the three proteins were subjected to B- and T-cell epitope mapping; 19 epitopes were used for vaccine design. The vaccine construct was docked with MHC-I, MHC-II and TLR-4 immune receptors and only the top-ranked complex (based on global energy value) was selected in each case. The selected docked complexes were examined in a molecular dynamic simulation and binding free energies analysis in order to assess their intermolecular stability. It was observed that the vaccine binding mode with receptors was stable and that the system presented stable dynamics. The net binding free energy of complexes was in the range of -300 to -500 kcal/mol, indicating the formation of stable complexes. In conclusion, the data reported herein might help vaccinologists to formulate a chimeric vaccine against the aforementioned target pathogen.

Molecular Insights into Binding Mode and Interactions of Structure-Based Virtually Screened Inhibitors for Pseudomonas aeruginosa Multiple Virulence Factor Regulator (MvfR)

Multi-drug resistance (MDR) bacterial pathogens pose a threat to global health and warrant the discovery of new therapeutic molecules, particularly those that can neutralize their virulence and stop the evolution of new resistant mechanisms. The superbug nosocomial pathogen, Pseudomonas aeruginosa, uses a multiple virulence factor regulator (MvfR) to regulate the expression of multiple virulence proteins during acute and persistent infections. The present study targeted MvfR with the intention of designing novel anti-virulent compounds, which will function in two ways: first, they will block the virulence and pathogenesis P. aeruginosa by disrupting the quorum-sensing network of the bacteria, and second, they will stop the evolution of new resistant mechanisms. A structure-based virtual screening (SBVS) method was used to screen druglike compounds from the Asinex antibacterial library (~5968 molecules) and the comprehensive marine natural products database (CMNPD) (~32 thousand compounds), against the ligand-binding domain (LBD) of MvfR, to identify molecules that show high binding potential for the relevant pocket. In this way, two compounds were identified: Top-1 (4-((carbamoyloxy)methyl)-10,10-dihydroxy-2,6-diiminiodecahydropyrrolo[1,2-c]purin-9-yl sulfate) and Top-2 (10,10-dihydroxy-2,6-diiminio-4-(((sulfonatocarbamoyl)oxy)methyl)decahydropyrrolo[1,2-c]purin-9-yl sulfate), in contrast to the co-crystallized M64 control. Both of the screened leads were found to show deep pocket binding and interactions with several key residues through a network of hydrophobic and hydrophilic interactions. The docking results were validated by a long run of 200 ns of molecular dynamics simulation and MM-PB/GBSA binding free energies. All of these analyses confirmed the presence of strong complex formation and rigorous intermolecular interactions. An additional analysis of normal mode entropy and a WaterSwap assay were also performed to complement the aforementioned studies. Lastly, the compounds were found to show an acceptable range of pharmacokinetic properties, making both compounds potential candidates for further experimental studies to decipher their real biological potency.

Gene Amplification Uncovers Large Previously Unrecognized Cryptic Antibiotic Resistance Potential in E. coli

The activation of unrecognized antibiotic resistance genes in the bacterial cell can give rise to antibiotic resistance without the need for major mutations or horizontal gene transfer. We hypothesize that bacteria harbor an extensive array of diverse cryptic genes that can be activated in response to antibiotics via adaptive resistance. To test this hypothesis, we developed a plasmid assay to randomly manipulate gene copy numbers in Escherichia coli cells and identify genes that conferred resistance when amplified. We then tested for cryptic resistance to 18 antibiotics and identified genes conferring resistance. E. coli could become resistant to 50% of the antibiotics tested, including chloramphenicol, d-cycloserine, polymyxin B, and 6 beta-lactam antibiotics, following this manipulation. Known antibiotic resistance genes comprised 13% of the total identified genes, where 87% were unclassified (cryptic) antibiotic resistance genes. These unclassified genes encoded cell membrane proteins, stress response/DNA repair proteins, transporters, and miscellaneous or hypothetical proteins. Stress response/DNA repair genes have a broad antibiotic resistance potential, as this gene class, in aggregate, conferred cryptic resistance to nearly all resistance-positive antibiotics. We found that antibiotics that are hydrophilic, those that are amphipathic, and those that inhibit the cytoplasmic membrane or cell wall biosynthesis were more likely to induce cryptic resistance in E. coli. This study reveals a diversity of cryptic genes that confer an antibiotic resistance phenotype when present in high copy number. Thus, our assay can identify potential novel resistance genes while also describing which antibiotics are prone to induce cryptic antibiotic resistance in E. coli. IMPORTANCE Predicting where new antibiotic resistance genes will rise is a challenge and is especially important when new antibiotics are developed. Adaptive resistance allows sensitive bacterial cells to become transiently resistant to antibiotics. This provides an opportune time for cells to develop more efficient resistance mechanisms, such as tolerance and permanent resistance to higher antibiotic concentrations. The biochemical diversity harbored within bacterial genomes may lead to the presence of genes that could confer resistance when timely activated. Therefore, it is crucial to understand adaptive resistance to identify potential resistance genes and prolong antibiotics. Here, we investigate cryptic resistance, an adaptive resistance mechanism, and identify unknown (cryptic) antibiotic resistance genes that confer resistance when amplified in a laboratory strain of E. coli. We also pinpoint antibiotic characteristics that are likely to induce cryptic resistance. This study may help detect novel antibiotic resistance genes and provide the foundation to help develop more effective antibiotics.

A Comprehensive Computational Screening of Phytochemicals Derived from Saudi Medicinal Plants against Human CC Chemokine Receptor 7 to Identify Potential Anti-Cancer Therapeutics

Homeostatic trafficking of immune cells by CC chemokine receptor 7 (CCR7) keeps immune responses and tolerance in a balance. The involvement of this protein in lymph node metastasis in cancer marks CCR7 as a penitential drug target. Using the crystal structure of CCR7, herein, a comprehensive virtual screening study is presented to filter novel strong CCR7 binding phytochemicals from Saudi medicinal plants that have a higher binding affinity for the intracellular allosteric binding pocket. By doing so, three small natural molecules named as Hit-1 (1,8,10-trihydroxy-3-methoxy-6-methylanthracen-9(4H)-one), Hit-2 (4-(3,4-dimethoxybenzyl)-3-(4-hydroxy-3-methoxybenzyl)dihydrofuran-2(3H)-one), and Hit-3 (10-methyl-12,13-dihydro-[1,2]dioxolo[3,4,5-de]furo[3,2-g]isochromeno[4,3-b]chromen-8-ol) are predicted showing strong binding potential for the CC chemokine receptor 7 allosteric pocket. During molecular dynamics simulations, the compounds were observed in the formation of several chemical bonding of short bond distances. Additionally, the molecules remained in strong contact with the active pocket residues and experienced small conformation changes that seemed to be mediated by the CCR7 loops to properly engage the ligands. Two types of binding energy methods (MM/GBPBSA and WaterSwap) were additionally applied to further validate docking and simulation findings. Both analyses complement the good affinity of compounds for CCR7, the electrostatic and van der Waals energies being the most dominant in intermolecular interactions. The active pocket residue's role in compounds binding was further evaluated via alanine scanning, which highlighted their importance in natural compounds binding. Additionally, the compounds fulfilled all drug-like rules: Lipinski, Ghose, Veber, Egan, and Muegge passed many safety parameters, making them excellent anti-cancer candidates for experimental testing.

A Systematic Strategy to Find Potential Therapeutic Targets for Pseudomonas aeruginosa Using Integrated Computational Models

Pseudomonas aeruginosa is an opportunistic human pathogen that has been a constant global health problem due to its ability to cause infection at different body sites and its resistance to a broad spectrum of clinically available antibiotics. The World Health Organization classified multidrug-resistant Pseudomonas aeruginosa among the top-ranked organisms that require urgent research and development of effective therapeutic options. Several approaches have been taken to achieve these goals, but they all depend on discovering potential drug targets. The large amount of data obtained from sequencing technologies has been used to create computational models of organisms, which provide a powerful tool for better understanding their biological behavior. In the present work, we applied a method to integrate transcriptome data with genome-scale metabolic networks of Pseudomonas aeruginosa. We submitted both metabolic and integrated models to dynamic simulations and compared their performance with published in vitro growth curves. In addition, we used these models to identify potential therapeutic targets and compared the results to analyze the assumption that computational models enriched with biological measurements can provide more selective and (or) specific predictions. Our results demonstrate that dynamic simulations from integrated models result in more accurate growth curves and flux distribution more coherent with biological observations. Moreover, identifying drug targets from integrated models is more selective as the predicted genes were a subset of those found in the metabolic models. Our analysis resulted in the identification of 26 non-host homologous targets. Among them, we highlighted five top-ranked genes based on lesser conservation with the human microbiome. Overall, some of the genes identified in this work have already been proposed by different approaches and (or) are already investigated as targets to antimicrobial compounds, reinforcing the benefit of using integrated models as a starting point to selecting biologically relevant therapeutic targets.

Exploration of the structural requirements of Aurora Kinase B inhibitors by a combined QSAR, modelling and molecular simulation approach

Aurora kinase B plays an important role in the cell cycle to orchestrate the mitotic process. The amplification and overexpression of this kinase have been implicated in several human malignancies. Therefore, Aurora kinase B is a potential drug target for anticancer therapies. Here, we combine atom-based 3D-QSAR analysis and pharmacophore model generation to identify the principal structural features of acylureidoindolin derivatives that could potentially be responsible for the inhibition of Aurora kinase B. The selected CoMFA and CoMSIA model showed significant results with cross-validation values (q²) of 0.68, 0.641 and linear regression values (r²) of 0.971, 0.933 respectively. These values support the statistical reliability of our model. A pharmacophore model was also generated, incorporating features of reported crystal complex structures of Aurora kinase B. The pharmacophore model was used to screen commercial databases to retrieve potential lead candidates. The resulting hits were analyzed at each stage for diversity based on the pharmacophore model, followed by molecular docking and filtering based on their interaction with active site residues and 3D-QSAR predictions. Subsequently, MD simulations and binding free energy calculations were performed to test the predictions and to characterize interactions at the molecular level. The results suggested that the identified compounds retained the interactions with binding residues. Binding energy decomposition identified residues Glu155, Trp156 and Ala157 of site B and Leu83 and Leu207 of site C as major contributors to binding affinity, complementary to 3D-QSAR results. To best of our knowledge, this is the first comparison of WaterSwap field and 3D-QSAR maps. Overall, this integrated strategy provides a basis for the development of new and potential AK-B inhibitors and is applicable to other protein targets.

Molecular docking, simulation and MM-PBSA studies of nigella sativa compounds: a computational quest to identify potential natural antiviral for COVID-19 treatment

Nigella sativa or black seed is used as a medicinal plant around the globe. Oil and seeds have a long tradition of folklore use in various medicinal and food systems. The conventional therapeutic use of Nigella sativa, in different ways, has been reported in several studies to treat different diseases including influenza, headache, hypertension, diabetes, inflammation, eczema, fever, cough, asthma, bronchitis, and fever. Based on previously reported potential therapeutic uses of N. sativa compounds, and keeping in mind the dire need of time for the development of potent antiviral, a combined docking, ADMET properties calculation, molecular dynamics, and MM-PBSA approaches were applied in the current study to check the therapeutic potentials of N. sativa chief constituents against COVID-19. Among the studied compounds, we found that dithymoquinone (DTQ), with binding affinity of −8.6 kcal/mol compared to a positive control (chloroquine, −7.2 kcal/mol) , has the high potential of binding at SARS-CoV-2:ACE2 interface and thus could be predicted as a plausible inhibitor to disrupt viral-host interactions. Molecular dynamics simulation of 100 ns well complemented binding affinity of the compound and revealed strong stability of DTQ at the docked site. Additionally, MM-PBSA also affirms the docking results. Compound DTQ of the present study, if validated in wet lab experiments, could be used to treat COVID-19 and could serve as a lead in the future for development of more effective natural antivirals against COVID-19.

Communicated by Ramaswamy H. Sarma

Conformational transition of Acinetobacter baumannii KdsC enzyme and the role of magnesium in binding: An insight from comparative molecular dynamics simulation and its implications in novel antibiotics design

The 3-deoxy-d-manno-octulosonate 8-phosphate phosphatase (KdsC) catalyzes the hydrolysis of 3-deoxy-d-manno-octulosonate 8-phosphate (KDO 8-P) to 3-deoxy-d-manno-octulosonate (KDO) and inorganic phosphate in KDO biosynthesis pathway of Gram-negative bacteria lipopolysaccharide (LPS) hydrophobic lipid-A core. The essentiality of KDO for bacterial cell viability presents the possibility of its targeting to develop broad-spectrum antibacterial agents. In this study, a receptor based virtually screening method was put forward to identify novel lead inhibitory molecules for KdsC enzyme. Dynamics evaluation in solution revealed three complexes: Asinex-1197, Asinex-1705, and Asinex-1710 from Asinex antibacterial library as highly stable, involving conformational transition from open to close upon lead molecules binding and eloquent role of active pocket magnesium towards inhibitors binding and movements. Interconversion of local secondary structure elements in sequence region of Asp192-Asp208 covering motif β-turn, β-hairpin, and β-sheets is seen recurrently that could be in all likelihood of the pressure excreted on this region during closing conformation event or magnesium driven inhibitor adjustments. The binding free energy estimation predicted gas phase energy for all the three complexes dominating with major contribution from van der Waals energy (in case of Asinex-1705 and Asinex-1710) and balanced contributions of both electrostatic and van der Waals (in case of Asinex-1197). Key residues-scanning shortlisted Leu45, Asp185, Gy188, Arg231, and Lys255 as vital in the interaction network of magnesium and inhibitors at the binding site. Their crucial roles in net binding energy were reaffirmed via in silico site directed alanine scanning method. The filtered hits might be useful to further scaffolds addition and structural optimization to yield high affinity binders of KdsC enzyme, whose inhibition, in turn, will disrupt the outer membrane synthesis.

Network-Based Metabolism-Centered Screening of Potential Drug Targets in Klebsiella pneumoniae at Genome Scale

Klebsiella pneumoniae is an opportunistic bacterial pathogen leading to life-threatening nosocomial infections. Emergence of highly resistant strains poses a major challenge in the management of the infections by healthcare-associated K. pneumoniae isolates. Thus, despite intensive efforts, the current treatment strategies remain insufficient to eradicate such infections. Failure of the conventional infection-prevention and treatment efforts explicitly indicates the requirement of new therapeutic approaches. This prompted us to systematically analyze the K. pneumoniae metabolism to investigate drug targets. Genome-scale metabolic networks (GMNs) facilitating the systematic analysis of the metabolism are promising platforms. Thus, we used a GMN of K. pneumoniae MGH 78578 to determine putative targets through gene- and metabolite-centric approaches. To develop more realistic infection models, we performed the bacterial growth simulations within different host-mimicking media, using an improved biomass formation reaction. We selected more suitable targets based on several property-based prioritization procedures. KdsA was identified as the high-ranked putative target satisfying most of the target prioritization criteria specified under the gene-centric approach. Through a structure-based virtual screening protocol, we identified potential KdsA inhibitors. In addition, the metabolite-centric approach extended the drug target list based on synthetic lethality. This revealed the importance of combined metabolic analyses for a better understanding of the metabolism. To our knowledge, this is the first comprehensive effort on the investigation of the K. pneumoniae metabolism for drug target prediction through the constraint-based analysis of its GMN in conjunction with several bioinformatic approaches. This study can guide the researchers for the future drug designs by providing initial findings regarding crucial components of the Klebsiella metabolism.

Creative targeting of the Gram-negative outer membrane in antibiotic discovery

The rising threat of multidrug-resistant Gram-negative bacteria is exacerbated by the scarcity of new antibiotics in the development pipeline. Permeability through the outer membrane remains one of the leading hurdles in discovery efforts. However, the essentiality of a robust outer membrane makes itself an intriguing antimicrobial target. Herein, we review drug discovery efforts targeting the outer membrane and the prospective antimicrobial leads identified.

Molecular Dynamics Simulation Framework to Probe the Binding Hypothesis of CYP3A4 Inhibitors

The Cytochrome P450 family of heme-containing proteins plays a major role in catalyzing phase I metabolic reactions, and the CYP3A4 subtype is responsible for the metabolism of many currently marketed drugs. Additionally, CYP3A4 has an inherent affinity for a broad spectrum of structurally diverse chemical entities, often leading to drug-drug interactions mediated by the inhibition or induction of the metabolic enzyme. The current study explores the binding of selected highly efficient CYP3A4 inhibitors by docking and molecular dynamics (MD) simulation protocols and their binding free energy calculated using the WaterSwap method. The results indicate the importance of binding pocket residues including Phe57, Arg105, Arg106, Ser119, Arg212, Phe213, Thr309, Ser312, Ala370, Arg372, Glu374, Gly481 and Leu483 for interaction with CYP3A4 inhibitors. The residue-wise decomposition of the binding free energy from the WaterSwap method revealed the importance of binding site residues Arg106 and Arg372 in the stabilization of all the selected CYP3A4-inhibitor complexes. The WaterSwap binding energies were further complemented with the MM(GB/PB)SA results and it was observed that the binding energies calculated by both methods do not differ significantly. Overall, our results could guide towards the use of multiple computational approaches to achieve a better understanding of CYP3A4 inhibition, subsequently leading to the design of highly specific and efficient new chemical entities with suitable ADMETox properties and reduced side effects.

Visualizing protein-ligand binding with chemical energy-wise decomposition (CHEWD): application to ligand binding in the kallikrein-8 S1 Site

Kallikrein-8, a serine protease, is a target for structure-based drug design due to its therapeutic potential in treating Alzheimer's disease and is also useful as a biomarker in ovarian cancer. We present a binding assessment of ligands to kallikrein-8 using a residue-wise decomposition of the binding energy. Binding of four putative inhibitors of kallikrein-8 is investigated through molecular dynamics simulation and ligand binding energy evaluation with two methods (MM/PBSA and WaterSwap). For visualization of the residue-wise decomposition of binding energies, chemical energy-wise decomposition or CHEWD is introduced as a plugin to UCSF Chimera and Pymol. CHEWD allows easy comparison between ligands using individual residue contributions to the binding energy. Molecular dynamics simulations indicate one ligand binds stably to the kallikrein-8 S1 binding site. Comparison with other members of the kallikrein family shows that residues responsible for binding are specific to kallikrein-8. Thus, ZINC02927490 is a promising lead for development of novel kallikrein-8 inhibitors.

Heteroleptic copper(i) halides with triphenylphosphine and acetylthiourea: synthesis, characterization and biological studies (experimental and molecular docking)

This manuscript presents the synthesis of acetylthiourea and triphenylphosphene based hetroleptic copper(i) halides and their biological activities. H-bonding and hydrophobic pi-interactions were found important for their biological activities.