Rational questing for potential novel inhibitors of FabK from Streptococcus pneumoniae by combining FMO calculation, CoMFA 3D-QSAR modeling and virtual screening

The search for novel treatment strategies for Streptococcus pneumoniae infections

This review provides an overview of the most important novel treatment strategies against Streptococcus pneumoniae infections published over the past 10 years. The pneumococcus causes the majority of community-acquired bacterial pneumonia cases, and it is one of the prime pathogens in bacterial meningitis. Over the last 10 years, extensive research has been conducted to prevent severe pneumococcal infections, with a major focus on (i) boosting the host immune system and (ii) discovering novel antibacterials. Boosting the immune system can be done in two ways, either by actively modulating host immunity, mostly through administration of selective antibodies, or by interfering with pneumococcal virulence factors, thereby supporting the host immune system to effectively overcome an infection. While several of such experimental therapies are promising, few have evolved to clinical trials. The discovery of novel antibacterials is hampered by the high research and development costs versus the relatively low revenues for the pharmaceutical industry. Nevertheless, novel enzymatic assays and target-based drug design, allow the identification of targets and the development of novel molecules to effectively treat this life-threatening pathogen.

Analyzing Interactions with the Fragment Molecular Orbital Method

Basic concepts in the analysis of binding using the fragment molecular orbital method are discussed at length: polarization, desolvation, and interaction. The components in the pair interaction energy decomposition analysis are introduced, and the analysis is illustrated for a water dimer and a protein-ligand complex.

Solvent Screening in Zwitterions Analyzed with the Fragment Molecular Orbital Method

Based on induced solvent charges, a new model of solvent screening is developed in the framework of the fragment molecular orbital combined with the polarizable continuum model. The developed model is applied to analyze interactions in a prototypical zwitterionic system, sodium chloride in water, and it is shown that the large underestimation of the interaction in the original solvent screening based on local charges is successfully corrected. The model is also applied to a complex of the Trp-cage (PDB: 1L2Y ) miniprotein with an anionic ligand, and the physical factors determined protein-ligand binding in solution are unraveled.

2D-SAR, Topomer CoMFA and molecular docking studies on avian influenza neuraminidase inhibitors

Avian influenza is a serious zoonotic infectious disease with huge negative impacts on local poultry farming, human health and social stability. Therefore, the design of new compounds against avian influenza has been the focus in this field. In this study, computational methods were applied to investigate the compounds with neuraminidase inhibitory activity. First, 2D-SAR model was built to recognize neuraminidase inhibitors (NAIs). As a result, the accuracy of 10 cross-validation and independent tests is 96.84% and 98.97%, respectively. Then, the Topomer CoMFA model was constructed to predict the inhibitory activity and analyses molecular fields. Two models were obtained by changing the cutting methods. The second model is employed to predict the activity (q2 = 0.784 and r2 = 0.982). Molecular docking was also used to further analyze the binding sites between NAIs and neuraminidase from human and avian virus. As a result, it is found that same binding Total Score has some differences, but the binding sites are basically the same. At last, some potential NAIs were screened and some optimal opinions were taken. It is expected that our study can assist to study and develop new types of NAIs.

Subsystem Analysis for the Fragment Molecular Orbital Method and Its Application to Protein-Ligand Binding in Solution

A subsystem analysis is derived incorporating interfragment interactions into the fragment properties, such as energies or charges. The relative stabilities of three alanine isomers, the α-helix, the β-turn, and the extended form are studied and the differences in fragment properties are elucidated. The analysis is further elaborated for studies of binding energies. The binding of the Trp-cage protein (PDB: 1L2Y ) to two ligands is studied in detail. Binding energies defined for each fragment can be used as a convenient descriptor for analyzing contributions to binding in solution.

The fragment molecular orbital method combined with density-functional tight-binding and the polarizable continuum model

The electronic gap in proteins is analyzed in detail, and it is shown that FMO-DFTB/PCM is efficient and accurate in describing the molecular structure of proteins in solution.

Integrating sampling techniques and inverse virtual screening: toward the discovery of artificial peptide-based receptors for ligands

A novel heuristic using an iterative select-and-purge strategy is proposed. It combines statistical techniques for sampling and classification by rigid molecular docking through an inverse virtual screening scheme. This approach aims to the de novo discovery of short peptides that may act as docking receptors for small target molecules when there are no data available about known association complexes between them. The algorithm performs an unbiased stochastic exploration of the sample space, acting as a binary classifier when analyzing the entire peptides population. It uses a novel and effective criterion for weighting the likelihood of a given peptide to form an association complex with a particular ligand molecule based on amino acid sequences. The exploratory analysis relies on chemical information of peptides composition, sequence patterns, and association free energies (docking scores) in order to converge to those peptides forming the association complexes with higher affinities. Statistical estimations support these results providing an association probability by improving predictions accuracy even in cases where only a fraction of all possible combinations are sampled. False positives/false negatives ratio was also improved with this method. A simple rigid-body docking approach together with the proper information about amino acid sequences was used. The methodology was applied in a retrospective docking study to all 8000 possible tripeptide combinations using the 20 natural amino acids, screened against a training set of 77 different ligands with diverse functional groups. Afterward, all tripeptides were screened against a test set of 82 ligands, also containing different functional groups. Results show that our integrated methodology is capable of finding a representative group of the top-scoring tripeptides. The associated probability of identifying the best receptor or a group of the top-ranked receptors is more than double and about 10 times higher, respectively, when compared to classical random sampling methods.

Proteomic analysis on the antibacterial activity of a Ru(II) complex against Streptococcus pneumoniae

Streptococcus pneumoniae is a Gram-positive pathogen that causes a variety of infection diseases in human. In this project, we determined the antibacterial activity of a Ru(II) complex X-03 against S. pneumoniae in vitro, by comparing its toxicity to host cells A549 and HBE. We performed two-dimensional gel electrophoresis (2-DE)-based proteomic analysis to characterize the protein alterations in S. pneumoniae after treatment with X-03. In total, 50 proteins exhibiting significant differential expressions were identified. RT-PCR was used to confirm the expression differences for selected proteins. Bioinformatics analysis on the proteomic alterations suggested that Ru(II) complex X-03 may obstruct bacterial fatty acid synthesis and oxidation-reduction process to suppress the growth of S. pneumoniae. Metal-uptake experiments revealed that iron-acquisition pathway in the bacterium may be interfered by X-03. These results provide useful clues for further investigations on the mechanism of the antibacterial action of metal compounds.

BIOLOGICAL SIGNIFICANCE

The appearance of bacterial strains with broad antibiotic resistance is becoming an alarming global health concern. The development of novel efficient antibacterial compound is urgently needed. In the present study, we found that Ru(II) complex X-03 has a significant antibacterial activity and applied proteomic technology combined with bioinformatics analysis to investigate its antimicrobial mechanism in S. pneumoniae. Many proteins were found to be dysregulated, implicating that X-03 may affect various molecular pathways leading to the inhibition of bacterial growth. Metal-uptake experiments demonstrated that X-03 treatment reduced the iron content in the bacterium, suggesting the interference with iron acquisition systems by the complex. This disturbance in iron acquisition may directly or indirectly induce the proteomic response that involved many pathways. In addition, X-03 could selectively suppress Gram-positive bacteria but execute less cytotoxicity to Gram-negative bacteria, with almost no effect on human cells, implicating its potential to be developed as a specific antimicrobial agent. These results provide useful information for further investigations on the mechanism of the antibacterial action of metal drugs and development of efficient antibacterial drugs.

3D-QSAR studies of dihydropyrazole and dihydropyrrole derivatives as inhibitors of human mitotic kinesin Eg5 based on molecular docking

Human mitotic kinesin Eg5 plays an essential role in mitoses and is an interesting drug target against cancer. To find the correlation between Eg5 and its inhibitors, structure-based 3D-quantitative structure-activity relationship (QSAR) studies were performed on a series of dihydropyrazole and dihydropyrrole derivatives using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Based on the LigandFit docking results, predictive 3D-QSAR models were established, with cross-validated coefficient values (q²) up to 0.798 for CoMFA and 0.848 for CoMSIA, respectively. Furthermore, the CoMFA and CoMSIA models were mapped back to the binding sites of Eg5, which could provide a better understanding of vital interactions between the inhibitors and the kinase. Ligands binding in hydrophobic part of the inhibitor-binding pocket were found to be crucial for potent ligand binding and kinases selectivity. The analyses may be used to design more potent EG5 inhibitors and predict their activities prior to synthesis.