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Persistence and prevalence of microbial diseases (pandemics, epidemics) is the most alarming threats to the human resulting in huge health and economic losses. Rapid detection and understanding of the disease dynamics by molecular biotechnology tools allow for robust reporting, treatment and control of diseases. As per WHO, the optimal diagnostic approach should be quick, specific, sensitive, without a stringed instrument, and low cost. The drawbacks of traditional detection techniques promote the use of CRISPR-mediated nucleic acid detection methods such as SHERLOCK as detection method. It takes advantage of the unexpected in vitro features of CRISPR-Cas system to develop field-deployable sensitive detection tools. Previously, CRISPR-mediated diagnostic methods have extensively been reviewed particularly for SARS-COV-2 detection, but it fails to provide the insight into advances of this technique. This study is the first attempt to review the advances of SHERLOCK approach as diagnostic tool for viral diseases detection. Variations of SHERLOCK mechanism for improved efficiency are discussed. Particularly integrated SHERLOCK approaches in terms of extraction-free assay and Bluetooth-enabled detection are reviewed to access their feasibility for the development of simpler and cost-effective diagnostic toolkits. Insight in to perks and limitations of diagnostic methods indicates its potential as ultimate diagnostic instrument for disease management.

I-motif or C4 is a four-stranded DNA structure with a protonated cytosine:cytosine base pair (C+:C) found in cytosine-rich sequences. We have found that oligodeoxynucleotides containing adenine and cytosine repeats form a stable secondary structure at a physiological pH with magnesium ion, which is similar to i-motif structure, and have named this structure ‘adenine:cytosine-motif (AC-motif)’. AC-motif contains C+:C base pairs intercalated with putative A+:C base pairs between protonated adenine and cytosine. By investigation of the AC-motif present in the CDKL3 promoter (AC-motifCDKL3), one of AC-motifs found in the genome, we confirmed that AC-motifCDKL3 has a key role in regulating CDKL3 gene expression in response to magnesium. This is further supported by confirming that genome-edited mutant cell lines, lacking the AC-motif formation, lost this regulation effect. Our results verify that adenine-cytosine repeats commonly present in the genome can form a stable non-canonical secondary structure with a non-Watson–Crick base pair and have regulatory roles in cells, which expand non-canonical DNA repertoires.

The membrane-bound O-acyltransferase domain-containing 7

The appearance of drug-resistant mutations in UL54 DNA polymerase and UL97 kinase genes is problematic for the treatment of human cytomegalovirus (HCMV) diseases. During treatment of HCMV infection in a pediatric hematopoietic cell transplant recipient, H600L and T700A mutations and E576G mutation were independently found in the UL54 gene. Foscarnet (FOS; phosphonoformic acid) resistance by T700A mutation is reported. Here, we investigated the role of novel mutations in drug resistance by producing recombinant viruses and a model polymerase structure. The H600L mutant virus showed an increase in resistance to ganciclovir (GCV) by 11-fold and to FOS and cidofovir (CDV) by 5-fold, compared to the wild type, while the E756G mutant virus showed an increase in resistance to FOS by 9-fold and modestly to CDV by 2-fold. With the FOS-resistant T700A mutation, only H600L produced increased FOS resistance up to 37-fold, indicating an additive effect of these mutations on FOS resistance. To gain insight into drug resistance mechanisms, a model structure for UL54 polymerase was constructed using the yeast DNA polymerase as a template. In this model, HCMV DNA polymerase contains a long palm loop domain of which H600 and T700 are located on each end and T700 interacts with the FOS binding pocket. Our results demonstrate that H600L and E756G mutations in UL54 polymerase are novel drug-resistant mutations and that the acquisition of both H600L and T700A mutations in the DNA-binding loop confers increased resistance to FOS treatment, providing novel insights for the mechanism acquiring foscarnet resistance.

Background:Although most nucleotides in the genome form canonical double-stranded B-DNA, many repeated sequences transiently present as non-canonical conformations (non-B DNA) such as triplexes, quadruplexes, Z-DNA, cruciforms, and slipped/hairpins. Those noncanonical DNAs (ncDNAs) are not only associated with many genetic events such as replication, transcription, and recombination, but are also related to the genetic instability that results in the predisposition to disease. Due to the crucial roles of ncDNAs in cellular and genetic functions, various computational methods have been implemented to predict sequence motifs that generate ncDNA.Objective:Here, we review strategies for the identification of ncDNA motifs across the whole genome, which is necessary for further understanding and investigation of the structure and function of ncDNAs.Conclusion:There is a great demand for computational prediction of non-canonical DNAs that play key functional roles in gene expression and genome biology. In this study, we review the currently available computational methods for predicting the non-canonical DNAs in the genome. Current studies not only provide an insight into the computational methods for predicting the secondary structures of DNA but also increase our understanding of the roles of non-canonical DNA in the genome.

Cancer is the sum of about 277 different forms of cancer disease. It has been found that gene mutations or genetic disorders caused by genetic and epigenetic factors lead toward abnormal cell proliferation which is said to be cancer. Advances in technology have provided us with increases knowledge of DNA, RNA, and proteins being studied in cancer tissues through advanced bioinformatics tools. This chapter provides an overview of bioinformatics techniques being used in cancer research. There was a need to understand different cancer types, diagnosis, and cure; for which bioinformatics could be a much better tool. Cancer being the most devastating disease is spreading fast in our communities. Modern-day techniques produce a large amount of data that needs high-throughput techniques to arrange, handle and analyze. Bioinformatics tools provide this platform to better understand, analyze and interpret this data. At the end of the chapter, the techniques have been explained with some examples where these were used successfully.

Autophagy is a catabolic process through which cytoplasmic components are degraded and recycled in response to various stresses including starvation. Recently, transcriptional and epigenetic regulations of autophagy have emerged as essential mechanisms for maintaining homeostasis. Here, we identify that coactivator-associated arginine methyltransferase 1 (CARM1) methylates Pontin chromatin-remodeling factor under glucose starvation, and methylated Pontin binds Forkhead Box O 3a (FOXO3a). Genome-wide analyses and biochemical studies reveal that methylated Pontin functions as a platform for recruiting Tip60 histone acetyltransferase with increased H4 acetylation and subsequent activation of autophagy genes regulated by FOXO3a. Surprisingly, CARM1-Pontin-FOXO3a signaling axis can work in the distal regions and activate autophagy genes through enhancer activation. Together, our findings provide a signaling axis of CARM1-Pontin-FOXO3a and further expand the role of CARM1 in nuclear regulation of autophagy., Epigenetic regulations of autophagy have emerged as mechanisms for maintaining cellular homeostasis. Here the authors reveal that the CARM1-Pontin-FOXO3a signaling axis can activate autophagy related genes through enhancer activation.

DNA crystallography provides essential structural information to understand the biochemical and biological functions of oligonucleotides. Therefore, it is necessary to understand the factors affecting crystallization of DNA to develop a strategy for production of diffraction-quality DNA crystals. We analyzed key factors affecting intermolecular interactions in 509 DNA crystals from the Nucleic Acid Database and Protein Databank. Packing interactions in DNA crystals were classified into four categories based on the intermolecular hydrogen bonds in base or backbone, and their correlations with other factors were analyzed. From this analysis, we confirmed that hydrogen bonding between terminal end and mid-region is most common in crystal packing and in high-resolution crystal structures. Interestingly, P212121 is highly preferred in DNA crystals in general, but the P61 space group is relatively abundant in A-DNA crystals. Accordingly, P212121 contains more terminal end-mid-region interactions than other space groups, confirming the significance of this interaction. While metals play a role in the production of a good crystal in B-DNA conformation, their effect is not significant in other conformations. From these analyses, we found that packing interaction and other factors have a strong influence on the quality of DNA crystals and provide key information to predict crystal growth of candidate oligonucleotides.

I-Motif is a tetrameric cytosine-rich DNA structure with hemi-protonated cytosine: cytosine base pairs. Recent evidence showed that i-motif structures in human cells play regulatory roles in the genome. Therefore, characterization of novel i-motifs and investigation of their functional implication are urgently needed for comprehensive understanding of their roles in gene regulation. However, considering the complications of experimental investigation of i-motifs and the large number of putative i-motifs in the genome, development of an in silico tool for the characterization of i-motifs in the high throughput scale is necessary. We developed a novel computation method, MD-TSPC4, to predict the thermal stability of i-motifs based on molecular modeling and molecular dynamic simulation. By assuming that the flexibility of loops in i-motifs correlated with thermal stability within certain temperature ranges, we evaluated the correlation between the root mean square deviations (RMSDs) of model structures and the thermal stability as the experimentally obtained melting temperature (Tm). Based on this correlation, we propose an equation for Tm prediction from RMSD. We expect this method can be useful for estimating the overall structure and stability of putative i-motifs in the genome, which can be a starting point of further structural and functional studies of i-motifs.

Chromodomain-helicase-DNA-binding protein 1-like is a chromodomain-containing protein in the SNF2-like family of ATPases. It has the capability to sustain proliferation in cell, encourage tumor growth and prevent apoptosis of cell. The goal of the current study is to build an in silico homology model further to identify the structural features that influence the inhibitory activity of chromodomain-helicase-DNA-binding protein 1-like protein grounded on a variety of 103 set of compounds. GOLD program is used to carry out molecular docking studies to ascertain the binding mode of structurally varied inhibitors of chromodomain-helicase-DNA-binding protein 1-like protein. Most active residues docked with chromodomain-helicase-DNA-binding protein 1-like protein are compound 20, 103 and 22 with their GOLD Scores 90.5, 81.01 and 79.2, respectively. These docked residues exhibited substantial interaction with active site residues of the protein. Ligand-protein binding is further elucidated with the extensive hydrogen bonding and other hydrophobic interactions. Chromodomain-helicase-DNA-binding protein 1-like protein belongs to Snf2 family of proteins with conserved evolutionary function. Another interesting aspect of this study is the presence of a conserved Snf2 N-terminal domain observed in chromodomain-helicase-DNA-binding protein 1-like protein. It controls the catalytic and the helicase activity which is crucial in regulating tumor progression. A hundred nanosecond molecular dynamics simulation of docked chromodomain-helicase-DNA-binding protein 1-like illustrated a stable binding pattern of ligand in the protein’s active site. Furthermore, trajectory analysis was performed to assess various characteristics of the docked system in terms of function of time. This study pinpoints potential novel inhibitors against chromodomain-helicase-DNA-binding protein 1-like protein which have not been reported previously but are involved in the overexpression in different cancers. This finding will help to design a prospective drug for varied number of cancers.

β-Ketoacyl-ACP-synthase III (FabH or KAS III) has become an attractive target for the development of new antibacterial agents which can overcome the multidrug resistance. Unraveling the fatty acid biosynthesis (FAB) metabolic pathway and understanding structural coordinates of FabH will provide valuable insights to target Streptococcus gordonii for curing oral infection. In this study, we designed inhibitors against therapeutic target FabH, in order to block the FAB pathway. As compared to other targets, FabH has more interactions with other proteins, located on the leading strand with higher codon adaptation index value and associated with lipid metabolism category of COG. Current study aims to gain in silico insights into the structural and dynamical aspect of S. gordonii FabH via molecular docking and molecular dynamics (MD) simulations. The FabH protein is catalytically active in dimerization while it can lock in monomeric state. Current study highlights two residues Pro88 and Leu315 that are close to each other by dimerization. The active site of FabH is composed of the catalytic triad formed by residues Cys112, His249, and Asn279 in which Cys112 is involved in acetyl transfer, while His249 and Asn279 play an active role in decarboxylation. Docking analysis revealed that among the studied compounds, methyl-CoA disulfide has highest GOLD score (82.75), binding affinity (-11 kcal/mol) and exhibited consistently better interactions. During MD simulations, the FabH structure remained stable with the average RMSD value of 1.7 A and 1.6 A for undocked protein and docked complex, respectively. Further, crucial hydrogen bonding of the conserved catalytic triad for exhibiting high affinity between the FabH protein and ligand is observed by RDF analysis. The MD simulation results clearly demonstrated that binding of the inhibitor with S. gordonii FabH enhanced the structure and stabilized the dimeric FabH protein. Therefore, the inhibitor has the potential to become a lead compound.

The discovery of novel drug targets of a genome that can bind with high affinity to drug-like compounds is a significant challenge in drug development. Streptococcus gordonii initiates dental plaque formation and endocarditis by entering into the blood stream, usually after oral trauma. The prolonged use of antibiotics is raising a problem of multi-drug resistance and lack of an optimal therapeutic regime that necessitates the drug discovery of vital importance in curing various infections. To overcome this dilemma, the in silico approach paves the way for identification and qualitative characterization of promising drug targets for S. gordonii that encompass three phases of analyses. The present study deciphers drug target genomes of S. gordonii in which 93 proteins were identified as potential drug targets and 16 proteins were found to be involved in unique metabolic pathways. Highlighted information will convincingly render to facilitate selection of S. gordonii proteins for successful entry into drug design pipelines.