Travel Light: Reductive Genome Evolution in Free-Living Eukaryotes

Technologies that measure characteristics of large families of cellular molecules (e.g., genes, proteins, metabolites), have been collectively described by using the suffix ‘-omics’at the end of the name of the characteristic measured. Etymology of the suffix comes from the Latin suffix ‘-ome’, derived from mass or many.

Botulinum Neurotoxins (BoNTs) bind the neuronal membrane of the host cell via dual interactions with both protein receptors and gangliosides. In order to decipher the molecular determinants for recognition of cell surface protein receptor synaptotagmins II (Syt-II) by the BoNT serotype B (BoNT/B), a high-level quantum chemical analysis was performed, on the basis of the 2.15 Å resolution x-ray crystal structure of the BoNT/B – Syt-II complex. The work resulted in the discovery of two interfaces of molecular recognition; the amphipathic α-helix of the protein receptor Syt-II interacts with BoNT/B by forming a hydrophobic interface on one side of the helix and a hydrophilic interface on the other side. The hydrophobic interface consists of residues Phe47, Leu50, Phe54, Phe55 and Ile58 of Syt-II interacting with residues Trp1178, Tyr1181, Tyr1183, Phe1194 and Phe1204 of BoNT/B. The hydrophilic interface is composed of residues Lys53 and Glu57 of Syt-II interacting with residues Lys1113, Asp1115, Ser1116 and Lys1192 of BoNT/B. Intermolecular interaction energies between BoNT/B and Syt-II were calculated by means of the supermolecular approach at the MP2 level with subsequent solvation energy correction. It was found that the energetic contribution of the hydrophobic interface toward binding of BoNT/B with Syt-II (-9.49 kcal/mol) is much stronger than that of the hydrophilic interface (-2.58 kcal/ mol). Furthermore, pair-wise intermolecular interaction analysis led to the findings that π-π stacking interactions among aromatic residues are the major molecular determinants for recognition of cell surface protein receptor Syt-II by the botulinum neurotoxin BoNT/B. These findings are significant since it was widely believed that the extreme toxicities of BoNTs have a lot to do with the high affinity and specificity of their binding to the neuronal membrane. It is expected that a detailed understanding of the intermolecular interactions responsible for the extreme specificity of molecular recognition between BoNT and its protein receptor as reported here will have far reaching implication for not only the rational design of potent protein toxin inhibitors targeting toxin-protein receptor binding interface but also the development of more suitable therapeutic neurotoxins.

Incorporating digital and online tools to increase the options and flexibility in education is a rapidly growing area of pedagogy. Students can collaborate on projects without being in the same vicinity and download archived live lectures for further review, or access recorded lectures in case they missed it.

Next Generation Sequencing (NGS) technology is becoming very popular in generating the short reads genomic or transcriptome data. Based on the type of sequencing technology, it offers diverse applications varying from genome assembly, gene expression analysis to epigenetic changes.

Bioseqeunces such as protein, RNA and DNA, are made up of sequences of amino acids/nucleotides. The binding of biosequences among themselves is important for governing many biological processes of a living organism. The bindings are maintained by short segments of these biosequences, known as functional elements. Due to the importance of these functional elements, their presence is well conserved throughout evolution, allowing them to be discovered as patterns. As sequencing technologies continue to improve, the amount of biosequences is available in abundance. It is thus convenient and cost-effective if functional elements can be discovered from biosequences data computationally in an unsupervised manner without the need of prior knowledge or costly pre-preprocessing. In this paper, we aim to give a brief review of an unsupervised pattern discovery tool known as Aligned Pattern Clustering (or its software WeMineTM). It is developed to facilitate the discovery and analysis of patterns in biosequences, and has been applied in1) unsupervised identification of protein binding sites; 2) revealing functioning subgroup characteristics; and 3) identification of intra-protein, inter-protein and protein- DNA binding sites. In the era of ever-expanding biosequence data, we believe that this unsupervised pattern discovery approach would render a reliable, robust, and scalable method for scientific discovery and applications through leveraging the ever expanding volume of biosequences.

Biofilms keep the intimate relationship between human body and resident microbes. According to National Institutes of Health (NIH), the development of extracellular microbial communities, called biofilms contribute approximately 75% of pathogenic infections to human. The formation of biofilm confers several advantages during pathogen colonization and tolerates extreme conditions like exogenous stress caused by anti-infective agents. The interpretation and exploitation of anti-biofilm properties would help in future challenges, particularly in the control of human infections. The proven scientific evidence with regard to cellular association and exopolysaccharide production by probiotic bacteria could play an important role as anti-biofilm tools. These extracellular components may directly interact with the biofilms as they are actively transported to the bacterial environments via cytoplasmic membrane. The interactive ability of these extracellular metabolites to treat pathogenic biofilms is gaining significant research interest and their possibility to use as anti-biofilm agents. In this review, the extracellular probiotic bacterial markers and molecular approaches to control pathogenic biofilms have been reviewed and future perspectives and research interests are discussed as well.

Children with Attention Deficit Hyperactivity Disorder (ADHD) show large variations in response to methylphenidate (MPH) treatment, which may result from genetic factors associated with MPH metabolism. We aimed at investigating a possible link between the -75 T>G polymorphism in the 5’ untranslated region of the gene coding for carboxylesterase 1 (CES1) and a common adverse effect, weight loss, during the first three months of MPH treatment.

We analyzed the association between a CES1 polymorphism and longitudinal clinical data based on retrospective analysis of medical records, from first to last recorded visit at the clinic. By use of poly chain reaction and the Sanger method we genotyped the -75 T>G gene polymorphism and examined the association to clinical response, which was based on retrospective analysis of longitudinal clinical data from medical records. The primary clinical outcome measure was weight loss during the first 3 months of MPH treatment.

Data from 74 MPH treated children with ADHD, mean age 8.6 years, 57% males, were analysed. There were n=26 G-carriers (heterozygote TG and homozygote GG) and n=48 TT-homozygotes. The proportion of weight loss and mean weight change differed significantly in G-carriers (88% / -0.279 kg) compared with TT-homozygotes (31% / +0.157 kg). This study shows an association between the -75 T>G polymorphism in CES1 and MPH treatment response, demonstrated by a significantly higher frequency and extent of weight loss in G-carriers compared to TT-homozygotes.

Plasmodium falciparum the agent of malignant form of malaria and in particularly its ability to generate mutant variants makes it a successful pathogen. Due to the increasing drug resistance problem, an effective malaria vaccine is highly desirable. Peptide based vaccine can also be utilized to control malaria but HLA polymorphism is major hurdle in development of peptide based vaccine. Nevertheless promiscuous peptides which have potential to bind with more than one HLA alleles can be utilized to develop vaccine against malaria. Identification of an appropriate T-cell epitope for activation of immune system is of great importance before a strategy for development or trial of malaria vaccine is formulated. In the present study five different in silico tools were employed to predict promiscuous peptides by using protein sequence of promoter region of Pfs-25 gene. A total 303 peptides were predicted and by adopting different selection criteria’s only 4 peptides were selected for 3D homology modelling. The constructed 3D models of promiscuous peptides and HLA-alleles were further utilized to test for their binding affinity towards HLA alleles by means of peptide protein docking analysis. Docking analysis of these four potential vaccine candidate epitopes revealed that the promiscuous peptide P9 (FLCFLQFIHFFRYLF) showed highest docking affinity with all HLA-alleles and this epitopic region may be utilize as potential vaccine candidate antigen for development of peptide based vaccine against P. falciparum.

Khejur palm (Phoenix sylvestris L. Roxb.) sometimes called the date palm is a very important and well-known source of sugar and is one of the most popular palms of Bangladesh. It is used to treat back pain, toothache, headache, arthritis, nervous debility and as a sedative. Our aim of the study to performed molecular docking studies to identify potential binding affinities of the phytocompounds from Phoenix sylvestris, namely 2, 3-Dihydro-3,5-dihydroxy-6-methyl-4H-pyran-4-one and 2,4-Di-tert-butyl phenol COX-1 and COX-2 for searching of the lead molecule against pain. A wide range of docking score found during molecular docking by Schrodinger. 2, 3-Dihydro-3,5-dihydroxy 6-methyl-4H-pyran-4-one showed the docking score -5.393 kJ/mol against COX-1 & 2,4-Di-tert-butyl phenol showed the docking score -7.692 kj/ mol against COX-2. Between all the compounds 2, 3-Dihydro-3,5-dihydroxy-6-methyl-4H-pyran-4-one showed the best docking score towards COX-1 & 2,4-Di-tert-butyl phenol showed the best docking score towards COX-2. So, 2, 3-Dihydro-3,5-dihydroxy-6-methyl 4H-pyran-4-one and 2,4-Di-tert-butyl phenol is the best compound respectively for COX-1and COX-2 enzyme inhibition, as it possessed the best value in Molecular Docking. Further, in vivo investigation need to identify COX-1& COX-2 enzyme inhibitory activity of isolated compounds from Phoenix sylvestris.

The past decade has witnessed a transformative “cryoEM revolution” characterized by exponential growth in high-resolution structural data, driven by advances in cryogenic electron microscopy (cryoEM), and cryogenic electron tomography (cryoET). The integration of deep learning technologies into structural proteomics workflows has emerged as a pivotal force in addressing longstanding challenges, including low signal-to-noise ratios, preferred orientation artifacts, and missing-wedge problems that have historically limited efficiency and scalability. This review article examines the application of Artificial Intelligence (AI) across the entire cryoEM pipeline, from automated particle picking using convolutional neural networks (Topaz, crYOLO, CryoSegNet), to computational solutions for preferred orientation bias (spIsoNet, cryoPROS), and advanced denoising algorithms (Topaz-Denoise). In cryoET, tools such as IsoNet employ U-Net architectures for simultaneous missing-wedge correction and noise reduction, while TomoNet streamlines subtomogram averaging through AI-driven particle detection. The workflow culminates with automated atomic model building using sophisticated tools like ModelAngelo, DeepTracer, and CryoREAD that translate density maps into interpretable biological structures. These AI-enhanced approaches have demonstrated remarkable achievements, including near-atomic resolution reconstructions with minimal manual intervention, resolution of previously intractable datasets suffering from severe orientation bias, and successful application to diverse biological systems from HIV virus like particles to in situ ribosomal complexes. As deep learning continues to evolve, particularly with the emergence of large language models and vision transformers, the future promises even more sophisticated automation and accessibility in structural biology, potentially revolutionizing our understanding of macromolecular architecture and function