SPP1, a potential therapeutic target and biomarker for lung cancer: functional insights through computational studies.

NIH reported 128 different types of cancer of which lung cancer is the leading cause of mortality. Globally, it is estimated that on average one in every seventeen hospitalized patients was deceased. There are plenty of studies that have been reported on lung cancer draggability and therapeutics, but yet a protein that plays a central specific to cure the disease remains unclear. So, this study is designed to identify the possible therapeutic targets and biomarkers that can be used for the potential treatment of lung cancers. In order to identify differentially expressed genes, 39 microarray datasets of lung cancer patients were obtained from various demographic regions of the GEO database available at NCBI. After annotating statistically, 6229 up-regulated genes and 10324 down-regulated genes were found. Out of 17 up-regulated genes and significant genes, we selected SPP1 (osteopontin) through virtual screening studies. We found functional interactions with the other cancer-associated genes such as VEGF, FGA, JUN, EGFR, and TGFB1. For the virtual screening studies,198 biological compounds were retrieved from the ACNPD database and docked with SPP1 protein (PDBID: 3DSF). In the results, two highly potential compounds secoisolariciresinol diglucoside (-12.9 kcal/mol), and Hesperidin (-12.0 kcal/mol) showed the highest binding affinity. The stability of the complex was accessed by 100 ns simulation in an SPC water model. From the functional insights obtained through these computational studies, we report that SPP1 could be a potential biomarker and successive therapeutic protein target for lung cancer treatment.

A comprehensive review on human disease-causing bacterial proteases and their impeding agents.

Proteases are enzymes that catalyze the amide bond dissociation in polypeptide and protein peptide units. They are categorized into seven families and are responsible for a wide spectrum of human ailments, such as various types of cancers, skin infections, urinary tract infections etc. Specifically, the bacterial proteases cause a huge impact in the disease progression. Extracellular bacterial proteases break down the host defense proteins, while intracellular proteases are essential for pathogens virulence. Due to its involvement in disease pathogenesis and virulence, bacterial proteases are considered to be potential drug targets. Several studies have reported potential bacterial protease inhibitors in both Gram-positive and Gram-negative disease causing pathogens. In this study, we have comprehensively reviewed about the various human disease-causing cysteine, metallo, and serine bacterial proteases as well as their potential inhibitors.

A review on structural genomics approach applied for drug discovery against three vector-borne viral diseases: Dengue, Chikungunya and Zika.

Structural genomics involves the advent of three-dimensional structures of the genome encoded proteins through various techniques available. Numerous structural genomics research groups have been developed across the globe and they contribute enormously to the identification of three-dimensional structures of various proteins. In this review, we have discussed the applications of the structural genomics approach towards the discovery of potential lead-like molecules against the genomic drug targets of three vector-borne diseases, namely, Dengue, Chikungunya and Zika. Currently, all these three diseases are associated with the most important global public health problems and significant economic burden in tropical countries. Structural genomics has accelerated the identification of novel drug targets and inhibitors for the treatment of these diseases. We start with the current development status of the drug targets and antiviral drugs against these three diseases and conclude by describing challenges that need to be addressed to overcome the shortcomings in the process of drug discovery.

Screening of FDA-approved compound library identifies potential small-molecule inhibitors of SARS-CoV-2 non-structural proteins NSP1, NSP4, NSP6 and NSP13: molecular modeling and molecular dynamics studies.

COVID-19, the current global pandemic has caused immense damage to human lives and the global economy. It is instigated by the SARS-CoV-2 virus and there is an immediate need for the identification of effective drugs against this deadly virus. SARS-CoV-2 genome codes for four structural proteins, sixteen non-structural proteins (NSPs) and several accessory proteins for its survival inside the host cells. In the present study, through in silico approaches, we aim to identify compounds that are effective against the four NSPs namely, NSP1, NSP4, NSP6 and NSP13 of SARS-CoV-2. The selection criteria of these four NSP proteins are they are least explored and potential targets. First, we have modeled the 3D structures of these proteins using homology modeling methods. Further, through molecular docking studies, we have screened the FDA-approved compounds against these modeled proteins and reported their docking scores. To gain dynamic insights, molecular dynamics studies have also been carried out for the best scored ligand against the NSPs. This study can further pave way for exposing more number of compounds against these proteins and enhance COVID-19 treatment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s42485-021-00067-w.

Discovering mycobacterial lectins as potential drug targets and vaccine candidates for tuberculosis treatment: a theoretical approach.

M. tuberculosis proliferates within the macrophages during infection and they are bounded by carbohydrates in the cell wall, called lectins. Despite their surface localization, the studies on exact functions of lectins are unexplored. Hence, in our study, using insilico approaches, 11 potential lectins of Mtb was explored as potential drug targets and vaccine candidates. Initially, a gene interaction network was constructed for the 11 potential lectins and identified its functional partners. A gene ontology analysis was also performed for the 11 mycobacterial lectins along with its functional partners and found most of the proteins are present in the extracellular region of the bacterium and belongs to the PE/PPE family of proteins. Further, molecular docking studies were performed for two of the potential lectins (Rv2075c and Rv1917c). A novel series of quinoxalinone and fucoidan derivatives have been made to dock against these selected lectins. Molecular docking study reveals that quinoxalinone derivatives showed better affinity against Rv2075c, whereas fucoidan derivatives have good binding affinity against Rv1917c. Moreover, the mycobacterial lectins can interact with the host and they are considered as potential vaccine candidates. Hence, immunoinformatics study was carried out for all the 11 potential lectins. B-cell and T-cell binding epitopes were predicted using insilico tools. Further, an immunodominant epitope 1062SIPAIPLSVEV1072 of Rv1917c was identified, which was predicted to bind B-cell and most of the MHC alleles. Thus, the study has explored that mycobacterial lectins could be potentially used as drug targets and vaccine candidates for tuberculosis treatment. Supplementary Information: The online version contains supplementary material available at 10.1007/s42485-021-00065-y.

Computational identification of significant immunogenic epitopes of the putative outer membrane proteins from Mycobacterium tuberculosis.

Novel vaccines are required to effectively combat the epidemic spread of tuberculosis. Using in silico approaches, this study focuses on prediction of potential B cell and T cell binding immunogenic epitopes for 30 putative outer membrane proteins of Mtb. Among these, certain immunodominant epitopes of Rv0172, Rv0295c, Rv1006, Rv2264c, and Rv2525c were found, which are capable of binding B-cell and a maximum number of MHC alleles. The selected immunodominant epitopes were screened for their allergenic and antigenic properties, their percentage identity against the human proteome and their structural properties. Further, the binding efficacy of the immunodominant epitopes of Rv0295c and Rv1006 with HLA-DRB1*04:01 was analyzed using molecular docking and molecular dynamics studies. Hence, the in silico-derived immunogenic peptides (epitopes) could potentially be used for the design of subunit vaccines against tuberculosis.

Rv0807, a putative phospholipase A2 of Mycobacterium tuberculosis; Elucidation through sequence analysis, homology modeling, molecular docking and molecular dynamics studies of potential substrates and inhibitors.

Mycobacterium tuberculosis (Mtb) has the ability to scrounge off the host macrophages and create a cordial environment for its survival. Identification of mechanisms favoring this purpose leads to novel treatment strategies for tuberculosis. In this study through in silico approaches, we intend to identify the putative role for Rv0807 from Mtb and its essentiality for mycobacterium survival within the macrophages. Through sequence analysis, we hypothesize that Rv0807 could be a Phospholipase A2 of Mtb. Moreover, through in silico mutation studies we have predicted certain residues to be a part of the catalytic process of the Rv0807 homodimer. Rv0807 could be a potential drug target as it binds phosphatidylinositol-3-phosphate (PI3P) and could be involved in processing the host cell PI3Ps, thereby blocking the phagosomal maturation. A pharmacophore hypothesis was generated for the Rv0807 homodimer based on the ligand binding site and a set of Pretomanid related compounds were screened against the Rv0807 homodimer. The top five compounds which had better docking scores and good ADME properties were selected as best inhibitory compounds and analyzed further. Molecular dynamics (MD) studies of Rv0807 homodimer with PI3P and with the top scored compound in docking studies, demonstrated a lot of conformational changes in the protein structure as it gets occluded through the course of simulation. The movement of a loop atop the ligand binding site, suggests of a lid-like region as seen in many other phospholipases. MD simulation of the mutant structures was also performed and its effect on the protein conformational changes was discussed.Communicated by Ramaswamy H. Sarma.

Functional insights from a comparative study on the dynamics of Antigen85 proteins and MPT51 from Mycobacterium tuberculosis.

Antigen85 (Ag85) proteins of Mycobacterium tuberculosis are mycolyl transferases that aid in cell wall biosynthesis. MPT51 (Ag85D) is closely related to Ag85 proteins. We have performed a comparative molecular dynamics (MD) simulation study of Ag85 proteins (Ag85A, Ag85B, and Ag85C) and MPT51. We observe that helix α5, ß7-α9 loop, and N-terminal region of helix α9 of Ag85 proteins are mobile, suggestive of lid like movement over the active site. Further, in Ag85B, we observe the proposed scooting mode of the hydrophobic gating residue Phe232. Our simulations also show a similar scooting mode for Phe232 of Ag85A and Trp158 of Ag85C. We also found aromatic residue clusters at the ends of the hydrophobic channel of Ag85 proteins, which may have functional significance. Although MPT51 lacks the tunnel, it has the aromatic clusters. The aromatic cluster region has the ability to bind trehalose. From an immunoinformatics study, a promiscuous linear epitope was identified in MPT51 which could be useful in subunit vaccine studies. Recent studies have shown that a mycobacterial protein HupB, interacts with Ag85 proteins and has a regulatory role in cell wall biogenesis, with implications in growth rate and latency. We performed molecular docking studies of HupB protein with Ag85 proteins and predicted potential sites of interaction in Ag85 proteins. The insights gained through the current study can potentially pave way for newer therapeutic interventions. Graphical Abstract Dynamics of antigen85 proteins and MPT51 from Mycobacterium tuberculosis.