Axial Frequency Distribution Research Articles

Deciphering the role of sulfonamides and molecular basis of thioredoxin domain dynamics through comparative simulations

DsbA, a thioredoxin periplasmic protein was prioritized based on subtractive proteomics and immunoinformatics in-depth investigation of Providencia rettgeri proteome. It is an important member of the protein family thioredoxins that catalyzes disulfide bond formation and acts as a folding catalyst for multiple categories of virulence factors. Herein, we performed the molecular dynamics (MD) simulation analysis of synthetic analogues of ubiquinone (dimedone derivatives) that inhibit disulfide bond formation (IC50 ~ 1 μM) catalyzed by E. coli DsbA: DsbB and in comparison propose a sulfonamide comprising compound from the Chembridge library. Both the structures were confined to crystal water molecules and placed in a 5-Å shell of water. The enzyme in solution underwent ligand-induced conformational changes, which appeared to correspond to position shifts in the equilibrium in the crystallographically defined thioredoxin domains. Dimedone derivative eventually drifted away from the thioredoxin domain and shifted to the conserved hydrophobic patch exposing itself to interact preferably with the solvent or the membrane protein DsbB. Comparatively, a Chembridge compound 10,005,560 exhibited strong hydrogen bonding and π- π stacking with the residues ASN155 and PHE56 while moving towards the thioredoxin domain and revealing stability till 250 ns. This positional shift relative to the thioredoxin domain was further analyzed through advanced Radial distribution function (RDF) and Axial frequency distribution (AFD) analyses to confirm the substantial collaboration of sulfonamide core like structures, which could be a starting point into the development of potential DsbA: DsbB inhibitors.

A combine approach of chemical synthesis, biological evaluation and structural dynamics studies revealed thiazole substituted arylamine derivatives as potent FabH enzyme inhibitors

Bacterial FabH enzyme is a broad-spectrum antimicrobial target and can be used in the design of novel antibiotics. This study reports chemical synthesis of thiazole based amine compounds as FabH inhibitors, followed by biological evaluation, and computational drug designing analysis with ultimate objective to guide further biological optimization of the identified hits. The compounds were synthesized through Pd-PEPPSI catalyzed cross coupling strategy for the Buchwald-Hartwig amination of thiazole-substituted aryl bromide. Pd-PEPPSI pre-catalysts were utilized for the cross couple with the diverse range of functionalized electron-deficient and electron-rich anilines and aliphatic amines. The thiazole based heteroaryl bromide coupling was found to be challenging and only specialized Pd-PEPPSI-IPr and Pd-PEPPSI-IPent catalysts were found to be effective providing the coupling product yield in the range of 78% to 99%. Biological investigation depicted compound 3f to be effective against Bacillus subtilis, Staphylococcus aureus, Staphylococcus epidermis, and Escherichia coli with mean + standard deviation value of 9.6 ± 0.4, 11.6 ± 0.4, 15.6 ± 0.4, and 11.6 ± 0.4, respectively. This compound is also active against free radicals with EC90 value of 39.45 µg/ml. Comparative docking predictions unravel the 3f binding mode at FabH active tunnel as such to block complete access for the natural substrate and involved balanced hydrogen and hydrophobic interactions. FabH-3f complex dynamics in solution found the docked conformation between the protein and compound of higher stability with mean carbon alpha deviation of 1.87 Å and mean residual deviation of 0.88 Å. Intermolecular interactions analysis depicted Asn274 from FabH active pocket to be significant in compound holding and strengthening of interaction as the simulation progresses. This was supported further by radial distribution function (RDF) and axial frequency distribution (AFD) that demonstrated the high distribution of compound atoms in close proximity of Asn274 residue and decrease in interaction distance. Further, the docking and simulation findings were validated through MMPB/GBSA methods that complements the compound affinity for the said target. In a nutshell, the identified hit could be subjected to structure, biological and pharmacokinetic optimization for development of effective FabH inhibitors.

Insight into natural inhibitors and bridging docking to dynamic simulation against sugar Isomerase (SIS) domain protein.

The pathogen Legionella longbeachae is a causative agent of legionellosis. The antibiotic resistance is the major problem of this modern world. Thus, selective pressure warrants the need for identification of newer drug target. In current study, subtractive proteomics approach screen out SIS (sugar isomerase) domain protein as an attractive receptor molecule for rational drug design. This protein is involved in lipopolysaccharide biosynthesis and catalyzes the isomerization of sedoheptulose 7-phosphate in D-glycero-D-manno-heptose 7-phosphate. Molecular docking revealed compound 1 (2-(6-(N,N-dimethyl sulfamoyl)pipridin-4-yl)pyrazin-2-yl)imidazol-3-ium-1-ide) as the potent inhibitor having GOLD fitness score of 69. The complex is affirmed by half-site effect via simulation analysis. Complex stability was investigated via several approaches that follows dynamic simulation and binding energies. Trajectory analysis revealed slight change in ring positioning of inhibitor inside the active pocket during 130ns (nanosecond). Interestingly, it was affirmed via binding interactions' density distribution. Hence, radial distribution function (RDF) inferred that SER55 and SER83 are the major residues that take part in hydrogen bonding and complex stability. Furthermore, an indigenously developed method axial frequency distribution (AFD) has revealed that ligand moved closer to the active site with both the residues SER55 and SER83 binding to the ligand. The phenomena was observed via rotating motion with respect to receptor center cavity. Thus, inhibitor movement towards allosteric site was observed at the end of simulations. Finally, binding free energy calculations by MMPB/GBSA predicts high compound affinity for the complex. Hence, findings from the current study will aid in the novel drug discovery and future experimental studies. Graphical abstract.

Deciphering the Inhibition Mechanism of under Trial Hsp90 Inhibitors and Their Analogues: A Comparative Molecular Dynamics Simulation.

Heat shock protein 90 (Hsp90) performs functions in cellular activities together with other signaling pathways. Hsp90 is evolutionarily conserved and universally articulated as a human cancer-causing agent involved in lung cancer and breast cancer followed by colon and rectum cancers. It has emerged as an effective drug candidate, and inhibition may affect several signaling pathways associated with cancer spread. Therefore, in-silico approaches, molecular docking, molecular dynamics simulation, and binding free energy calculations were applied to create insights into the inhibition mechanism against Hsp90 to identify new cancer therapeutic drugs. Top-docked Hsp90-inhibitor complexes with their analogues were selected as the best complexes based on the GOLD fitness score and orientation. The significant interaction of Hsp90 inhibitors and their analogues were observed to be bound with active site residues as well as residing within the same cavity region. System stability factors RMSD, RMSF, beta-factor, and radius of gyration were analyzed for top-docked complexes and ensure strong binding interaction between inhibitors and the Hsp90 cavity. Cavity bound inhibitors were found to retain consistent hydrogen bonding during the simulation. The radial distribution function (RDF) illustrated that interacting active site residues drive the binding and stability of the inhibitors. Similarly, the axial frequency distribution, which is an indigenously developed analytical tool, produced noteworthy knowledge of the hydrogen-bonding pattern. Results yielded new insights into the design of cancer therapeutic drugs against Hsp90. This finding suggests that under trial Hsp90 inhibitors MPC-3100 could be a potential starting point into the development of potential anticancer agents with the possibility of future directions for the improvement of early existing Hsp90 inhibitors CNF-2024 and SNX-5422 as an anticancer agent.

Immunoinformatics characterization of SARS-CoV-2 spike glycoprotein for prioritization of epitope based multivalent peptide vaccine

The COVID-19 pandemic caused by SARS-CoV-2 is a public health emergency of international concern and thus calling for the development of effective and safe therapeutics and prophylactics particularly a vaccine to protect against the infection. SARS-CoV-2 spike glycoprotein is an attractive candidate for a vaccine, antibodies, and inhibitors development because of the many roles it plays in attachment, fusion and entry into the host cell. In the present investigation, we characterized the SARS-CoV-2 spike glycoprotein by immunoinformatics techniques to put forward potential B and T cell epitopes, followed by the use of epitopes in construction of a multi-epitope peptide vaccine construct (MEPVC). The MEPVC revealed robust host immune system simulation with high production of immunoglobulins, cytokines and interleukins. Stable conformation of the MEPVC with a representative innate immune TLR3 receptor was observed involving strong hydrophobic and hydrophilic chemical interactions, along with enhanced contribution from salt-bridges towards inter-molecular stability. Molecular dynamics simulation in aqueous milieu aided further in interpreting strong affinity of the MEPVC for TLR3. This stability is the attribute of several vital residues from both TLR3 and MEPVC as shown by radial distribution function (RDF) and a novel axial frequency distribution (AFD) analytical tool. Comprehensive binding free energies estimation was provided at the end that concluded major domination by electrostatic and minor from van der Waals. Summing all, the designed MEPVC has tremendous potential of providing protective immunity against COVID-19 and thus could be considered in experimental studies.

Relational dynamics obtained through simulation studies of thioredoxin reductase: From a multi-drug resistant Entamoeba histolytica

Abstract Microbial enteric infections cause diarrhea, dysentery, and fever that constitute huge health problems worldwide. Entamoeba histolytica is a multi-drug resistant bacterial pathogen involves in instigating enteric infections. Multi-drug resistant E. histolytica is responsible for higher rate of mortality and morbidity. In the present study, a systematic in-silico pipeline applied to screen potential drug targets that are considered essential for pathogen survival. Thioredoxin reductase (TrxR) enzyme is concluded as a potential drug target bearing features of drug-ability, three-dimensional structure availability, favorable physiochemical properties, involvement in core pathways, rich interactome and broad-spectrum conservation. A library of antibacterial compounds was virtually screened against TrxR via molecular docking. The best docked complexes subjected to molecular dynamics simulation to observe dynamic behavior of complex. Root mean square deviation deduced interconversions helix-coil-helix-coil, and beta-turn-beta in TrxR and are highly flexible. Transitional changes observed in protein as a result of “relational dynamics” have a significant influence on the binding mechanism of inhibitor with in the protein cavity. Other factors: root mean square fluctuation, beta-factor and radius of gyration values show coherence with root mean square deviation results. Furthermore, crucial hydrogen bonds of residues Glu33 and Ala115 with inhibitor revealed through hydrogen bond analysis. Axial frequency distribution revealed residues Glu33 and Ala115 atoms showing high affinity for inhibitor though a minor tilting behavior was observed. Poisson Boltzmann or Generalized Born Surface Area Continuum Solvation (MM (PB/GB) SA) methods indicate van der Waal interactions as dominant interactions. These analyses revealed (1-(carboxymethyl)-4-(4-methylthiazole-5-carboxamido)-3H-pyrazol-1-ium-3-ide) as the potential lead compound. This study will facilitate researchers to discover and develop more effective leads compounds against E. histolytica.

Identification of natural inhibitors against Acinetobacter baumanniid-alanine-d-alanine ligase enzyme: A multi-spectrum in silico approach

d-Alanine-d-alanine ligase (Ddl), an enzyme that catalyzes the d-ala-d-ala dipeptide formation in UDPMurNAc pentapeptide, is a part of peptidoglycan biosynthesis machinery. Inhibition of enzyme leads to bacterial growth arrest making it a viable and attractive target for screening of potent antibacterial drugs. Combination of virtual screening, molecular docking, in silico pharmacokinetics, molecular dynamics (MD) simulation, and binding free energy calculations based on Molecular Mechanics Generalized Born and Surface Area (MMGBSA) and WaterSwap were applied in the current framework for the detailed analysis of potent natural inhibitors against Ddl enzyme. Comparative molecular docking supported with computational druglikeness revealed compound-331 (6-(4-((3-methoxyphenylsulfonamido) methyl) phenyl)-2-methylnicotinamide) as the best docked inhibitor. The inhibitor has Genetic Optimization for Ligand Docking (GOLD) fitness score of 84.2 and AutoDock Vina binding energy of −7.2 kcal/mol. The inhibitor exhibited to have a better druglikeness by adhering to Lipinski rule of five, Ghose rule, Veber filter, Egan filter, and Muegge filter in contrast to d-cycloserine, which violates Ghose and Muegge rule. MD simulation unravels that in complex over the course of 100-ns, the enzyme remained highly stable with mean Root Mean Square Deviation (RMSD) of 1.4 Å when compared to an undocked structure having RMSD of 1.6 Å. Root Mean Square Fluctuation (RMSF) predicted stable behaviour of the active site residues in both undocked and docked system with average RMSD values of 1.2 Å and 0.7 Å, respectively. Radial Distribution Function (RDF) and Axial Frequency Distribution (AFD) demonstrated Lys176 and Trp177 as critical residues of enzyme for binding, anchoring and bridging strong hydrogen and hydrophobic contacts between enzyme and the inhibitor. The estimated MMGBSA based binding free energy for the complex is −47.36 kcal/mol, signifying its stable nature. WaterSwap further indicated a worthy agreement on the affinity of inhibitor towards enzyme active pocket. This newly discovered natural inhibitor might serve a parent structure for the development of more potent derivatives with encouraging biological activity.

AFD: an application for bi-molecular interaction using axial frequency distribution

Conformational flexibility and generalized structural features are responsible for specific phenomena existing in biological pathways. With advancements in computational chemistry, novel approaches and new methods are required to compare the dynamic nature of biomolecules, which are crucial not only to address dynamic functional relationships but also to gain detailed insights into the disturbance and positional fluctuation responsible for functional shifts. Keeping this in mind, axial frequency distribution (AFD) has been developed, designed, and implemented. AFD can profoundly represent distribution and density of ligand atom around a particular atom or set of atoms. It enabled us to obtain an explanation of local movements and rotations, which are not significantly highlighted by any other structural and dynamical parameters. AFD can be implemented on biological models representing ligand and protein interactions. It shows a comprehensive view of the binding pattern of ligand by exploring the distribution of atoms relative to the x-y plane of the system. By taking a relative centroid on protein or ligand, molecular interactions like hydrogen bonds, van der Waals, polar or ionic interaction can be analyzed to cater the ligand movement, stabilization or flexibility with respect to the protein. The AFD graph resulted in the residual depiction of bi-molecular interaction in gradient form which can yield specific information depending upon the system of interest.

Binding mode analysis, dynamic simulation and binding free energy calculations of the MurF ligase from Acinetobacter baumannii

MurF ligase catalyzes the final cytoplasmic step of bacterial peptidoglycan biosynthesis and, as such, is a validated target for therapeutic intervention. Herein, we performed molecular docking to identify putative inhibitors of Acinetobacter baumannii MurF (AbMurF). Based on comparative docking analysis, compound 114 (ethyl pyridine substituted 3-cyanothiophene) was predicted to potentially be the most active ligand. Computational pharmacokinetic characterization of drug-likeness of the compound showed it to fulfil all the parameters of Muegge and the MDDR rule. A molecular dynamic simulation of 114 indicated the complex to be stable on the basis of an average root mean square deviation (RMSD) value of 2.09Å for the ligand. The stability of the complex was further supported by root mean square fluctuation (RMSF), beta factor and radius of gyration values. Analyzing the complex using radial distribution function (RDF) and a novel analytical tool termed the axial frequency distribution (AFD) illustrated that after simulation the ligand is positioned in close vicinity of the protein active site where Thr42 and Asp43 participate in hydrogen bonding and stabilization of the complex. Binding free energy calculations based on the Poisson-Boltzmann or Generalized–Born Surface Area Continuum Solvation (MM(PB/GB)SA) method indicated the van der Waals contribution to the overall binding energy of the complex to be dominant along with electrostatic contributions involving the hot spot amino acids from the protein active site. The present results indicate that the screened compound 114 may act as a parent structure for designing potent derivatives against AbMurF in specific and MurF of other bacterial pathogens in general.

Molecular dynamics simulation studies of novel β-lactamase inhibitor

New Delhi Metallo-β-Lactamase-1 (NDM-1) has drawn great attention due to its diverse antibiotic resistant activity. It can hydrolyze almost all clinically available β-lactam antibiotics. To inhibit the activity of NDM-1 a new strategy is proposed using computational methods. Molecular dynamics (MD) simulations are used to analyze the molecular interactions between selected inhibitor candidates and NDM-1 structure. The enzyme-ligand complex is subject to binding free energy calculations using MM(PB/GB)SA methods. The role of each residue of the active site contributing in ligand binding affinity is explored using energy decomposition analysis. Furthermore, a hydrogen bonding network between ligand and enzyme active site is observed and key residues are identified ensuring that the ligand stays inside the active site and maintains its movement towards the active site pocket. A production run of 150ns is carried out and results are analyzed using root mean square deviation (RMSD), root mean square fluctuation (RMSF), and radius of gyration (Rg) to explain the stability of enzyme ligand complex. Important active site residue e.g. PHE70, VAL73, TRP93, HIS122, GLN123, ASP124, HIS189, LYS216, CYS208, LYS211, ALA215, HIS250, and SER251 were observed to be involved in ligand attachemet inside the active site pocket, hence depicting its inhibitor potential. Hydrogen bonds involved in structural stability are analyzed through radial distribution function (RDF) and contribution of important residues involved in ligand movement is explained using a novel analytical tool, axial frequency distribution (AFD) to observe the role of important hydrogen bonding partners between ligand atoms and active site residues.

Interaction mechanisms of a melatonergic inhibitor in the melatonin synthesis pathway

Acetylserotonin-O-methyltransferase (ASMT) catalyzes the conversion of nor-melatonin to melatonin. Different levels of melatonin have been employed as a trait marker for psychiatric conditions, for this reason ASMT is thought to be an ideal target for developing novel therapeutic agents for the treatment of several mood disorders. In current study, the structural and functional details of the ASMT-B22 complex have been studied using docking and molecular dynamics (MD) simulation. Molecular docking results illustrated that both hydrogen bonding interactions as well as hydrophobic interactions made significant contributions for ligand binding and Arg210 appeared to be the anchor amino acid for the recognition of the receptor. Two hundred nanoseconds MD simulations using AMBER12 were performed to explore the behavior of the ASMT-B22 complex in aqueous solution, focusing on the structural changes induced as a result of inhibitor binding. From root mean square deviation, it was observed that the N-terminal residues endured a conformational change at 11th and 20th ns time scale. The root mean square fluctuation showed high motional flexibility at N-terminal residues because of structural alterations whereas the active site region comprising of a loop was comparatively stable and showed low fluctuations. Radial distribution functions calculated on the major interacting residues of the pocket revealed strengthening of the ASMT-B22 complex indicating the increase in the hydrogen bond interactions. Axial frequency distribution analysis is applied on trajectories for a vivid explanation of hydrogen bonding patterns. Results yielded will be useful in the design of more potent inhibitors of ASMT for normalizing the melatonin levels.

Binding pattern analysis and structural insight into the inhibition mechanism of Sterol 24-C methyltransferase by docking and molecular dynamics approach

Sterol 24-C methyltransferase (SMT) plays a major role during the production of steroids, especially in the biosynthesis of ergosterol, which is the major membrane sterol in leishmania parasite, and the etiological basis of leishmaniasis. Mechanism-based inactivators bind irreversibly to SMT and interfere with its activity to provide leads for the design of antileishmanial inhibitors. In this study, computational methods are used for studying enzyme–inhibitor interactions. fifty-seven mechanism-based inactivators are docked using 3 docking/scoring approaches (FRED, GoldScore, and ChemScore). A consensus is generated from the results of different scoring functions which are also validated with already reported experimental values. The most active compound thus obtained is subjected to molecular dynamics simulation of length 20 ns. Stability of simulation is analyzed through root-mean-square deviation, beta factor (B-factor), and radius of gyration (Rg). Hydrogen bonds and their involvement in the structural stability of the enzyme are evaluated through radial distribution function. Newly developed application of axial frequency distribution that determines three-particle correlation on frequency distributions before and after simulation has provided a clear evidence for the movement of the inhibitor into active pocket of the enzyme. Results yielded strong interaction between enzyme and the inhibitor throughout the simulation. Binding of the inhibitor with enzyme has stabilized the enzyme structure; thus, the inhibitor has the potential to become a lead compound.