Understanding the resistance mechanism of penicillin binding protein 1a mutant against cefotaxime using molecular dynamic simulation

<p>Antibiotic resistance is a threatening challenge for global health, as the expansion of resistance to current antibiotics has made serious therapeutic problems. Genome mutations are key evolutionary mechanisms conferring antibiotic resistance in bacterial pathogens. For example, penicillin and cephalosporins resistance is mostly mediated by mutations in penicillin binding proteins to change the affinity of the drug. Accordingly, threonine point mutations were reported to develop antibiotic resistance in various bacterial infections including pneumococcal infections. In this study, conventional molecular dynamics simulations, umbrella sampling simulations and MM/GBSA free energy calculations were applied to figure out how the Threonine to Alanine mutation (T to A) at STMK motif affects the binding of cefotaxime to Penicillin Binding Protein 1a and to reveal the resistance mechanism induced by the T to A mutation. The results obtained from the computational methods demonstrate that the T to A mutation increases the flexibility of the binding pocket and changes its conformation, which leads to increased conformational entropy change (−<i>T</i>Δ<i>S</i>) and attenuates the bonds between the ligand and the receptor. In brief, our findings indicate that both of the alterations of the conformational enthalpy and entropy contribute to the T to A-induced resistance in the binding of cefotaxime into penicillin binding protein 1a.</p

Identification of novel metallo-β-lactamases inhibitors using ligand-based pharmacophore modelling and structure-based virtual screening

Metallo-β-lactamases (MBLs) are a group of enzymes that hydrolyze the most commonly used β-lactam-based antibiotics, leading to the development of multi-drug resistance. The three main clinically relevant groups of these enzymes are IMP, VIM, and NDM. This study aims to introduce potent novel overlapped candidates from a ZINC database retrieved from the 200,583-member natural library against the active sites of IMP-1, VIM-2, and NDM-1 through a straightforward computational workflow using virtual screening approaches. The screening pipeline started by assessing Lipinski’s rule of five (RO5), drug-likeness, and pan-assay interference compounds (PAINS) which were used to generate a pharmacophore model using D-captopril as a standard inhibitor. The process was followed by the consensus docking protocol and molecular dynamic (MD) simulation combined with the molecular mechanics Poisson-Boltzmann Surface Area (MM-PBSA) method to compute the total binding free energy and evaluate the binding characteristics. The absorption, distribution, metabolism, elimination, and toxicity (ADMET) profiles of the compounds were also analyzed, and the search space decreased to the final two inhibitory candidates for B1 subclass MBLs, which fulfilled all criteria for further experimental evaluation. Communicated by Ramaswamy H. Sarma</p

Detection of Critical Genes Associated with Overall Survival (OS) and Progression-Free Survival (PFS) in Reconstructed Canine B-Cell Lymphoma Gene Regulatory Network (GRN)

<p>Canine B-cell lymphoma GRN was reconstructed from gene expression data in the STRING and MiMI databases. Critical genes of networks were identified and correlations of critical genes with overall survival (OS) and progression-free survival (PFS) were evaluated. Significant changes were detected in the expressions of <i>GLUL, CD44, CD79A, ARF3, FOS, BLOC1S1, FYN, GZMB, GALNT3, IFI44, CD3G, GNG2, ESRP1</i>, and <i>CCND1</i> in the STRING network and of <i>PECAM1, GLUL, CD44, GDI1, E2F4, TLE1, CD79A, UCP2, CCND1, FYN, RHOQ, BIN1</i>, and <i>A2M</i> in the MiMI network. Final survival analysis highlighted <i>CCND1</i> and <i>FOS</i> as genes with significant correlations with OS and PFS.</p

The proposed pathway of airway remodeling in mustard lung.

<p>Pathway nodes are indicated by color coding; Green: single protein; White: protein complex; Yellow box: gene; Bisque: receptor protein; Purple: biological process. The pathway illustrates several paths such as ERK/MAPK, ERBB1/ERBB2 complex activation via TFF3, and EPAS1/ARNT transcription factor activation. Different paths were extracted from pathway databases (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100094#pone-0100094-t001" target="_blank">table 1</a>) and then were curated and reconstructed manually in the CellDesigner graphical interface.</p

Major disease-risk modules in mustard lung network.

<p>Colored nodes are selected based on fold change ranking in microarray gene list and previous reports. They have a central role in these modules as driver nodes. The A, B, and C sub-networks extract from the mustard lung network using Hubba, a plugin in Cytoscape software.</p

Pathway Reconstruction of Airway Remodeling in Chronic Lung Diseases: A Systems Biology Approach

<div><p>Airway remodeling is a pathophysiologic process at the clinical, cellular, and molecular level relating to chronic obstructive airway diseases such as chronic obstructive pulmonary disease (COPD), asthma and mustard lung. These diseases are associated with the dysregulation of multiple molecular pathways in the airway cells. Little progress has so far been made in discovering the molecular causes of complex disease in a holistic systems manner. Therefore, pathway and network reconstruction is an essential part of a systems biology approach to solve this challenging problem. In this paper, multiple data sources were used to construct the molecular process of airway remodeling pathway in mustard lung as a model of airway disease. We first compiled a master list of genes that change with airway remodeling in the mustard lung disease and then reconstructed the pathway by generating and merging the protein-protein interaction and the gene regulatory networks. Experimental observations and literature mining were used to identify and validate the master list. The outcome of this paper can provide valuable information about closely related chronic obstructive airway diseases which are of great importance for biologists and their future research. Reconstructing the airway remodeling interactome provides a starting point and reference for the future experimental study of mustard lung, and further analysis and development of these maps will be critical to understanding airway diseases in patients.</p></div

Basic network parameters of the two generated networks, compared with simulated randomized model networks.

<p>Basic network parameters of the two generated networks, compared with simulated randomized model networks.</p

Pathway and interactome databases used to identify interaction (edge) between genes in the master list.

<p>Pathway and interactome databases used to identify interaction (edge) between genes in the master list.</p

Analysis of mustard lung network with 172 nodes and 1169 edges.

<p>These graphs were generated using NetworkAnalyzer plugin of Cytoscape. The scatter plot of betweenness centrality vs. number of neighbors (left) indicates that a limited number of nodes control the information flow between other nodes within the biological network. This means that a limited number of nodes with high interactions (hubs) control other nodes with lower interactions. The node degree distribution (right) shows that the network is scale-free considering the power-law degree distribution <i>P(k)∼k^γ</i> (fitting result is γ = 0. 790 and R-squared = 0.667). This means that the mustard lung network is a biological network which differs from random networks.</p

Additional file 4: of Dynamic modeling of folliculogenesis signaling pathways in the presence of miRNAs expression

SBML S3 (DF+miRNAs model). (XML 163 kb