In silico identification and validation of phenolic lipids as potential inhibitor against bacterial and viral strains.

The recurrence of coronavirus disease and bacterial resistant strains has drawn attention to naturally occurring bioactive molecules that can demonstrate broad-spectrum efficacy against bacteria as well as viral strains. The drug-like abilities of naturally available "anacardic acids" (AA) and their derivatives against different bacterial and viral protein targets through in-silico tools were explored. Three viral protein targets [P DB: 6Y2E (SARS-CoV-2), 1AT3 (Herpes) and 2VSM (Nipah)] and four bacterial protein targets [P DB: 2VF5 (Escherichia coli), 2VEG (Streptococcus pneumoniae), 1JIJ (Staphylococcus aureus) and 1KZN (E. coli)] were selected to evaluate the activity of bioactive AA molecules. The potential ability to inhibit the progression of microbes has been discussed based on the structure, functionality and interaction ability of these molecules on the selected protein targets for multi-disease remediation. The number of interactions, full-fitness value and energy of the ligand-target system were determined from the docked structure in SwissDock and Autodock Vina. In order to compare the efficacy of these active derivatives to that of commonly used drugs against bacteria and viruses, a few of the selected molecules were subjected to 100 ns long MD simulations. It was found that the phenolic groups and alkyl chains of AA derivatives are more likely to bind with microbial targets, that could be responsible for the improved activity against these targets. The results suggest that the proposed AA derivatives have demonstrated potential to become active drug ingredients against microbial protein targets. Further, experimental investigations are essential for clinical verification of the drug-like abilities of AA derivatives.Communicated by Ramaswamy H. Sarma.

Novel insights into the structural changes induced by disease-associated mutations in TDP-43: a computational approach.

Over the last two decades, the pathogenic aggregation of TAR DNA-binding protein 43 (TDP-43) is found to be strongly associated with several fatal neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTD), etc. While the mutations and truncation in TDP-43 protein have been suggested to be responsible for TDP-43 pathogenesis by accelerating the aggregation process, the effects of these mutations on the bio-mechanism of pathological TDP-43 protein remained poorly understood. Investigating this at the molecular level, we formulized an integrated workflow of molecular dynamic simulation and machine learning models (MD-ML). By performing an extensive structural analysis of three disease-related mutations (i.e., I168A, D169G, and I168A-D169G) in the conserved RNA recognition motifs (RRM1) of TDP-43, we observed that the I168A-D169G double mutant delineates the highest packing of the protein inner core as compared to the other mutations, which may indicate more stability and higher chances of pathogenesis. Moreover, through our MD-ML workflow, we identified the biological descriptors of TDP-43 which includes the interacting residue pairs and individual protein residues that influence the stability of the protein and could be experimentally evaluated to develop potential therapeutic strategies.Communicated by Ramaswamy H. Sarma.

Spectroscopic investigation on the interaction of direct yellow-27 with protein (BSA).

Direct yellow 27 (DY-27) interaction with bovine serum albumin (BSA) was investigated using multi-spectroscopic techniques to understand the toxicity mechanism. Fluorescence quenching of BSA by DY-27 was observed as a result of the formation of a BSA-DY27 complex with a binding constant of 1.19 × 105M-1and followed a static quenching mechanism with a quenching constant Ksvof 7.25 × 104M-1. The far UV circular dichroism spectra revealed the conformational changes in the secondary structure of BSA in the presence of DY-27. The calculated average lifetime of BSA is 6.04 ns and is nearly constant (5.99 ns) in the presence of dye and supports the proposed quenching mechanism. The change in free energy (ΔG) was calculated to be -28.96 kJ mol-1and confirmed the spontaneity of the binding process. Further, docking studies have been conducted to gain more insights into the interactions between DY-27 and serum albumin.

High frequency of intron retention and clustered H3K4me3-marked nucleosomes in short first introns of human long non-coding RNAs.

BACKGROUND: It is established that protein-coding exons are preferentially localized in nucleosomes. To examine whether the same is true for non-coding exons, we analysed nucleosome occupancy in and adjacent to internal exons in genes encoding long non-coding RNAs (lncRNAs) in human CD4+ T cells and K562 cells. RESULTS: We confirmed that internal exons in lncRNAs are preferentially associated with nucleosomes, but also observed an elevated signal from H3K4me3-marked nucleosomes in the sequences upstream of these exons. Examination of 200 genomic lncRNA loci chosen at random across all chromosomes showed that high-density regions of H3K4me3-marked nucleosomes, which we term 'slabs', are associated with genomic regions exhibiting intron retention. These retained introns occur in over 50% of lncRNAs examined and are mostly first introns with an average length of just 354 bp, compared to the average length of all human introns of 6355 and 7987 bp in mRNAs and lncRNAs, respectively. Removal of short introns from the dataset abrogated the high upstream H3K4me3 signal, confirming that the association of slabs and short lncRNA introns with intron retention holds genome-wide. The high upstream H3K4me3 signal is also associated with alternatively spliced exons, known to be prominent in lncRNAs. This phenomenon was not observed with mRNAs. CONCLUSIONS: There is widespread intron retention and clustered H3K4me3-marked nucleosomes in short first introns of human long non-coding RNAs, which raises intriguing questions about the relationship of IR to lncRNA function and chromatin organization.

A machine learning approach to unmask novel gene signatures and prediction of Alzheimer's disease within different brain regions.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder whose aetiology is currently unknown. Although numerous studies have attempted to identify the genetic risk factor(s) of AD, the interpretability and/or the prediction accuracies achieved by these studies remained unsatisfactory, reducing their clinical significance. Here, we employ the ensemble of random-forest and regularized regression model (LASSO) to the AD-associated microarray datasets from four brain regions - Prefrontal cortex, Middle temporal gyrus, Hippocampus, and Entorhinal cortex- to discover novel genetic biomarkers through a machine learning-based feature-selection classification scheme. The proposed scheme unraveled the most optimum and biologically significant classifiers within each brain region, which achieved by far the highest prediction accuracy of AD in 5-fold cross-validation (99% average). Interestingly, along with the novel and prominent biomarkers including CORO1C, SLC25A46, RAE1, ANKIB1, CRLF3, PDYN, numerous non-coding RNA genes were also observed as discriminator, of which AK057435 and BC037880 are uncharacterized long non-coding RNA genes.

Molecular dynamics simulations and biochemical characterization of Pf14-3-3 and PfCDPK1 interaction towards its role in growth of human malaria parasite.

Scaffold proteins play pivotal role as modulators of cellular processes by operating as multipurpose conformation clamps. 14-3-3 proteins are gold-standard scaffold modules that recognize phosphoSer/Thr (pS/pT) containing conserved motifs, and confer conformational changes leading to modulation of functional parameters of their target proteins. Modulation in functional activity of kinases has been attributed to their interaction with 14-3-3 proteins. Herein, we have annotated and characterized PF3D7_0818200 as 14-3-3 isoform I in Plasmodium falciparum 3D7, and its interaction with one of the key kinases of the parasite, Calcium-Dependent Protein Kinase 1 (CDPK1) by performing various analytical biochemistry and biophysical assays. Molecular dynamics simulation studies indicated that CDPK1 polypeptide sequence (61KLGpS64) behaves as canonical Mode I-type (RXXpS/pT) consensus 14-3-3 binding motif, mediating the interaction. The 14-3-3I/CDPK1 interaction was validated in vitro with ELISA and SPR, which confirmed that the interaction is phosphorylation dependent, with binding affinity constant of 670 ± 3.6 nM. The interaction of 14-3-3I with CDPK1 was validated with well characterized optimal 14-3-3 recognition motifs: Mode I-type ARSHpSYPA and Mode II-type RLYHpSLPA, by simulation studies and ITC. This interaction was found to marginally enhance CDPK1 functional activity. Furthermore, interaction antagonizing peptidomimetics showed growth inhibitory impact on the parasite indicating crucial physiological role of 14-3-3/CDPK1 interaction. Overall, this study characterizes 14-3-3I as a scaffold protein in the malaria parasite and unveils CDPK1 as its previously unidentified target. This sets a precedent for the rational design of 14-3-3 based PPI inhibitors by utilizing 14-3-3 recognition motif peptides, as a potential antimalarial strategy.

Structural Basis of Enhanced Facilitated Diffusion of DNA-Binding Protein in Crowded Cellular Milieu.

Although the fast association between DNA-binding proteins (DBPs) and DNA is explained by a facilitated diffusion mechanism, in which DBPs adopt a weighted combination of three-dimensional diffusion and one-dimensional (1D) sliding and hopping modes of transportation, the role of cellular environment that contains many nonspecifically interacting proteins and other biomolecules is mostly overlooked. By performing large-scale computational simulations with an appropriately tuned model of protein and DNA in the presence of nonspecifically interacting bulk and DNA-bound crowders (genomic crowders), we demonstrate the structural basis of the enhanced facilitated diffusion of DBPs inside a crowded cellular milieu through, to our knowledge, novel 1D scanning mechanisms. In this one-dimensional scanning mode, the protein can float along the DNA under the influence of nonspecific interactions of bulk crowder molecules. The search mode is distinctly different compared to usual 1D sliding and hopping dynamics in which protein diffusion is regulated by the DNA electrostatics. In contrast, the presence of genomic crowders expedites the target search process by transporting the protein over DNA segments through the formation of a transient protein-crowder bridged complex. By analyzing the ruggedness of the associated potential energy landscape, we underpin the molecular origin of the kinetic advantages of these search modes and show that they successfully explain the experimentally observed acceleration of facilitated diffusion of DBPs by molecular crowding agents and crowder-concentration-dependent enzymatic activity of transcription factors. Our findings provide crucial insights into gene regulation kinetics inside the crowded cellular milieu.

Mechanism of Facilitated Diffusion of DNA Repair Proteins in Crowded Environment: Case Study with Human Uracil DNA Glycosylase.

Preserving the genomic integrity is a fundamental requirement, primarily achieved by the DNA repair proteins through their continuous patrolling on the DNA in search of lesions. Human uracil DNA glycosylase (hUNG) is one such DNA repair protein that recognizes uracil in the duplex DNA and excises it using the extrahelical base recognition mechanism. Recent site transfer assay experiments based on full-length hUNG suggest that a crowded environment facilitates its search efficiency, which is enhanced further in the presence of a 93 residue disordered tail associated with its N-terminal. In this study, by performing extensive molecular dynamics simulations with an appropriately tuned model of protein and DNA in the presence of inert crowding agents, we probe the role of cellular crowding and the disordered region in the target search efficiency of the enzyme. Our analysis highlights a complex interplay among the shape of the enzyme, the presence of a disordered tail, and the macromolecular crowding agents that work in harmony to enhance the facilitated diffusion of hUNG protein in a crowded environment. The findings provide novel insights into the in vivo target search mechanism of DNA repair proteins.

Disparity in anomalous diffusion of proteins searching for their target DNA sites in a crowded medium is controlled by the size, shape and mobility of macromolecular crowders.

Using extensive computer simulations, we analyzed the role of physical properties of molecular crowding agents such as size, shape and mobility in the target search dynamics of DNA binding proteins. Our main result is that the sub-diffusive dynamics of a protein inside a crowded medium strongly depends on the crowder properties and also on the protein's mode of diffusion. For instance, while scanning the DNA one-dimensionally, the protein dynamics does not vary with the change in crowder properties. Conversely, the diffusion exponent varies non-monotonically during 3D diffusion and is maximally affected when the crowders match the protein physically. The investigation shows that the effect stems from the ruggedness of the associated potential energy landscape, which is regulated by the protein-crowder and DNA-crowder interactions. Our findings have broad significance in understanding the target search dynamics of proteins on DNA in crowded cellular milieu and selecting appropriate crowding agents when designing in vitro experiments.

Role of Macromolecular Crowding on the Intracellular Diffusion of DNA Binding Proteins.

Recent experiments suggest that cellular crowding facilitates the target search dynamics of proteins on DNA, the mechanism of which is not yet known. By using large scale computer simulations, we show that two competing factors, namely the width of the depletion layer that separates the crowder cloud from the DNA molecule and the degree of protein-crowder crosstalk, act in harmony to affect the target search dynamics of proteins. The impacts vary from nonspecific to specific target search regime. During a nonspecific search, dynamics of a protein is only minimally affected, whereas, a significantly different behaviour is observed when the protein starts forming a specific protein-DNA complex. We also find that the severity of impacts largely depends upon physiological crowder concentration and deviation from it leads to attenuation in the binding kinetics. Based on extensive kinetic study and binding energy landscape analysis, we further present a comprehensive molecular description of the search process that allows us to interpret the experimental findings.