The PE-PPE Domain in Mycobacterium Reveals a Serine α/β Hydrolase Fold and Function: An In-Silico Analysis

The PE and PPE proteins first reported in the genome sequence of Mycobacterium tuberculosis strain H37Rv are now identified in all mycobacterial species. The PE-PPE domain (Pfam ID: PF08237) is a 225 amino acid residue conserved region located towards the C-terminus of some PE and PPE proteins and hypothetical proteins. Our in-silico sequence analysis revealed that this domain is present in all Mycobacteria, some Rhodococcus and Nocardia farcinica genomes. This domain comprises a pentapeptide sequence motif GxSxG/S at the N-terminus and conserved amino acid residues Ser, Asp and His that constitute a catalytic triad characteristic of lipase, esterase and cutinase activity. The fold prediction and comparative modeling of the 3-D structure of the PE-PPE domain revealed a “serine α/β hydrolase” structure with a central β-sheet flanked by α-helices on either side. The structure comprises a lid insertion with a closed structure conformation and has a solvent inaccessible active site. The oxyanion hole that stabilizes the negative charge on the tetrahedral intermediate has been identified. Our findings add to the growing list of serine hydrolases in mycobacterium, which are essential for the maintenance of their impermeable cell wall and virulence. These results provide the directions for the design of experiments to establish the function of PE and PPE proteins

AIE_COV2_binding

This data is supporting data for the manuscript entitled "Assessing differential binding of aggregation induced emission-based luminogens to host interacting surface proteins of SARS-CoV-2 and influenza virus- an in silico approach". The PDB coordinates of TPE-P and TPE-S docked onto the SARS-COV2 spike proteins, and hemagglutinin protein of influenza virus, and the molecular dynamics simulations average structure of last 3 nano seconds of total 20 nano seconds coordinates files can hep in describing the binding molecules.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Structure alignment of imatinib bound BCR-ABL kinase (PDB_ID: 1IEP) (green) and ponatinib bound BCR-ABL kinase (PDB_ID: 3OXZ) (blue).

<p>The imatinib and ponatinib are represented in ball and stick models covered by solvent accessible surface (orange).</p

Developmental Encodings in Neuroevolution - No Free Lunch but a Peak at the Menu is Allowed

NeuroEvolution besides deep learning is considered the most promising method to train and optimize neural networks. Neuroevolution uses genetic algorithms to train the controller of an agent performing various tasks. Traditionally, the controller of an agent will be encoded in a genome which will be directly translated into the neural network of the controller. All weights and the connections will be described by their elements in the genome of the agent. Direct Encoding – states if there is a single change in the genome it directly affects a change in the brain. Over time, different forms of encoding have been developed, such as Indirect and Developmental Encodings. This paper mainly concentrates on Developmental Encoding and how it could improve NeuroEvolution. The No-Free Lunch theorem states that there is no specific optimization method that would outperform any other. This does not mean that the genetic encodings could not outperform other methods on specific neuroevolutionary tasks. However, we do not know what tasks this might be. Thus here a range of different tasks is tested using different encodings. The hope is to find in which task domains developmental encodings perform best

Impact of chronic infections (periodontic and endodontic) in implant dentistry

Dental implant plays an important role in oral rehabilitation. In recent decades, the concept of restoratively driven implant placement has become well-accepted. Thus, an increasing number of patients, especially those with past or present periodontitis or with periapical infections, desire to receive dental implants to restore their lost teeth. This review discusses the relationship between chronic periodontal and periapical infections with periimplantitis, with a focus on implant outcome. The studies considered for the inclusion were searched in MEDLINE (pubmed). The search was restricted to studies published in English from 1980 to 2015. Screening of eligible studies and data extraction were carried out by the reviewers. The articles included in the review comprised in vitro studies, in vivo studies (animals and humans), abstracts, and review articles

The contribution from van der Waals (vdW) and coulombic (Coul) interaction energies to SIE binding free energy of ponatinib for different mutants from selected binding site residues.

<p>The vdW and coulomb energies are calculated in kcal/mol.</p

Ponatinib Is a Pan-BCR-ABL Kinase Inhibitor: MD Simulations and SIE Study

<div><p>BCR-ABL kinase domain inhibition can be used to treat chronic myeloid leukemia. The inhibitors such as imatinib, dasatinib and nilotinib are effective drugs but are resistant to some BCR-ABL mutations. The pan-BCR-ABL kinase inhibitor ponatinib exhibits potent activity against native, T315I, and all other clinically relevant mutants, and showed better inhibition than the previously known inhibitors. We have studied the molecular dynamics simulations and calculated solvated interaction energies of native and fourteen mutant BCR-ABL kinases (M244V, G250E, Q252H, Y253F, Y253H, E255K, E255V, T315A, T315I, F317L, F317V, M351T, F359V and H396P) complexed with ponatinib. These studies revealed that the interactions between ponatinib and individual residues in BCR-ABL kinase are also affected due to the remote residue mutations. We report that some residues, Met244, Lys245, Gln252, Gly254, Leu370 and Leu298 do not undergo any conformational changes, while the fluctuations in residues from P-loop, β3-, β5- strands and αC- helix are mainly responsible for ponatinib binding to native and all mutant BCR-ABL kinases. Our work provides the molecular mechanisms of native and mutant BCR-ABL kinases inhibition by ponatinib at atomic level that has not been studied before.</p></div

Developmental Encodings in Neuroevolution - No Free Lunch but a Peak at the Menu is Allowed

NeuroEvolution besides deep learning is considered the most promising method to train and optimize neural networks. Neuroevolution uses genetic algorithms to train the controller of an agent performing various tasks. Traditionally, the controller of an agent will be encoded in a genome which will be directly translated into the neural network of the controller. All weights and the connections will be described by their elements in the genome of the agent. Direct Encoding – states if there is a single change in the genome it directly affects a change in the brain. Over time, different forms of encoding have been developed, such as Indirect and Developmental Encodings. This paper mainly concentrates on Developmental Encoding and how it could improve NeuroEvolution. The No-Free Lunch theorem states that there is no specific optimization method that would outperform any other. This does not mean that the genetic encodings could not outperform other methods on specific neuroevolutionary tasks. However, we do not know what tasks this might be. Thus here a range of different tasks is tested using different encodings. The hope is to find in which task domains developmental encodings perform best

The amino acid residues of BCR-ABL kinase in the ponatinib binding site.

<p>Amino acid side chain carbons are shown in orange and ponatinib carbons are show in green; oxygen-red; nitrogen-blue; fluorine-cyan.</p

The RMSD plots of the native and mutant BCR-ABL kinases (black) complexed with ponatinib (red).

<p>The RMSD plots of the native and mutant BCR-ABL kinases (black) complexed with ponatinib (red).</p