Sheikh Arslan Sehgal

Mitochondrial E3 ligase MARCH5 regulates FUNDC1 to fine‐tune hypoxic mitophagy

Mitophagy is an essential process for mitochondrial quality control and turnover. It is activated by two distinct pathways, one dependent on ubiquitin and the other dependent on receptors including FUNDC1. It is not clear whether these pathways coordinate to mediate mitophagy in response to stresses, or how mitophagy receptors sense stress signals to activate mitophagy. We find that the mitochondrial E3 ligase MARCH5, but not Parkin, plays a role in regulating hypoxia‐induced mitophagy by ubiquitylating and degrading FUNDC1. MARCH5 directly interacts with FUNDC1 to mediate its ubiquitylation at lysine 119 for subsequent degradation. Degradation of FUNDC1 by MARCH5 expression desensitizes mitochondria to hypoxia‐induced mitophagy, whereas knockdown of endogenous MARCH5 significantly inhibits FUNDC1 degradation and enhances mitochondrial sensitivity toward mitophagy‐inducing stresses. Our findings reveal a feedback regulatory mechanism to control the protein levels of a mitochondrial receptor to fine‐tune mitochondrial quality.

Mitophagy receptors sense stress signals and couple mitochondrial dynamic machinery for mitochondrial quality control.

Mitochondria are essential organelles for many fundamental cellular processes, including energy production, fatty acid β-oxidation, metabolite synthesis, iron and calcium homeostasis, and programmed cell death. Mitochondrial quality thus influences not only individual cell functions but also whole body metabolism. Dysregulated mitochondrial quality control is closely associated with the progression of aging related diseases, such as cancers and neurodegenerative disorders. Mitochondrial quality is monitored at the protein, organelle and sub-organelle levels. The critical issues are how stresses such as bioenergetic stress, oxidative stress and proteotoxic stress, are sensed and how the mitochondrial events are coordinated. Recently, several receptors were identified to mediate selective mitophagy, which is essential for mitochondrial quality control in yeast and mammalian cells. It is emerging that these receptors sense distinct stress signals and couple mitophagy machineries with mitochondrial fission/fusion machineries for mitochondrial quality control. Herein, we will review recent advances in receptors mediated mitophagy and mitochondrial dynamics for mitochondrial quality control, with attempt to have an integrative view on the molecular mechanisms for mitochondrial quality control.

Structural, phylogenetic and docking studies of D-amino acid oxidase activator ( DAOA ), a candidate schizophrenia gene

BackgroundSchizophrenia is a neurodegenerative disorder that occurs worldwide and can be difficult to diagnose. It is the foremost neurological disorder leading to suicide among patients in both developed and underdeveloped countries. D-amino acid oxidase activator (DAOA), also known as G72, is directly implicated in the glutamateric hypothesis of schizophrenia. It activates D-amino acid oxidase, which oxidizes D-serine, leading to modulation of the N-methyl-D-aspartate receptor.MethodsMODELLER (9v10) was utilized to generate three dimensional structures of the DAOA candidate gene. The HOPE server was used for mutational analysis. The Molecular Evolutionary Genetics Analysis (MEGA5) tool was utilized to reconstruct the evolutionary history of the candidate gene DAOA. AutoDock was used for protein-ligand docking and Gramm-X and PatchDock for protein-protein docking.ResultsA suitable template (1ZCA) was selected by employing BLASTp on the basis of 33% query coverage, 27% identity and E-value 4.9. The Rampage evaluation tool showed 91.1% favored region, 4.9% allowed region and 4.1% outlier region in DAOA. ERRAT demonstrated that the predicted model had a 50.909% quality factor. Mutational analysis of DAOA revealed significant effects on hydrogen bonding and correct folding of the DAOA protein, which in turn affect protein conformation. Ciona was inferred as the outgroup. Tetrapods were in their appropriate clusters with bifurcations. Human amino acid sequences are conserved, with chimpanzee and gorilla showing more than 80% homology and bootstrap value based on 1000 replications. Molecular docking analysis was employed to elucidate the binding mode of the reported ligand complex for DAOA. The docking experiment demonstrated that DAOA is involved in major amino acid interactions: the residues that interact most strongly with the ligand C28H28N3O5PS2 are polar but uncharged (Gln36, Asn38, Thr 122) and non-polar hydrophobic (Ile119, Ser171, Ser21, Ala31). Protein-protein docking simulation demonstrated two ionic bonds and one hydrogen bond involving DAOA. Lys-7 of the receptor protein interacted with Lys-163 and Asp-2037. Tyr-03 interacted with Arg-286 of the ligand protein and formed a hydrogen bond.ConclusionThe predicted interactions might serve to inhibit the disease-related allele. It is assumed that current bioinformatics methods will contribute significantly to identifying, analyzing and curing schizophrenia. There is an urgent need to develop effective drugs for schizophrenia, and tools for examining candidate genes more accurately and efficiently are required.

Tumor necrosis factor receptor superfamily 10B (TNFRSF10B): an insight from structure modeling to virtual screening for designing drug against head and neck cancer

BackgroundHead and neck cancer (HNC) belongs to a group of heterogeneous disease with distinct patterns of behavior and presentation. TNFRSF10B, a tumor suppressor gene mapped on chromosome 8. Mutation in candidate gene is responsible for the loss of chromosome p arm which is frequently observed in head and neck tumors. TNFRSF10B inhibits tumor formation through apoptosis but deregulation encourages metastasis, migration and invasion of tumor cell tissues.ResultsStructural modeling was performed by employing MODELLER (9v10). A suitable template [2ZB9] was retrieved from protein databank with query coverage and sequence identity of 84% and 30% respectively. Predicted Model evaluation form Rampage revealed 93.2% residues in favoured region, 5.7% in allowed region while only 1 residue is in outlier region. ERRAT and ProSA demonstrated 51.85% overall quality with a −1.08 Z-score of predicted model. Molecular Evolutionary Genetics Analysis (MEGA 5) tool was executed to infer an evolutionary history of TNFRSF10B candidate gene. Orthologs and paralogs [TNFRSF10A & TNFRSF10D] protein sequences of TNFRSF10B gene were retrieved for developed ancestral relationship. Topology of tree presenting TNFRSF10A gene considered as outgroup. Human and gorilla shared more than 90% similarities with conserved amino acid sequence. Virtual screening approach was appliedfor identification of novel inhibitors. Library (Mcule) was screened for novel inhibitors and utilized the scrutinized lead compounds for protein ligand docking. Screened lead compounds were further investigated for molecular docking studies. STRING server was employed to explore protein-protein interactions of TNFRSF10B target protein. TNFSF10 protein showed highest 0.999 confidence score and selected protein-protein docking by utilizing GRAMM-X server. In-silico docking results revealed I-58, S-90 and A-62 as most active interacting residues of TNFRSF10B receptor protein with R-130, S-156 and R-130 of TNFSF10B ligand protein.ConclusionCurrent research may provide a backbone for understanding structural and functional insights of TNFRSF10B protein. The designed novel inhibitors and predicted interactions might serve to inhibit the disease. Effective in-vitro potent ligands are required which will be helpful in future to design a drug to against Head and neck cancer disease. There is an urgent need for affective drug designing of head and neck cancer and computational tools for examining candidate genes more efficiently and accurately are required.

Pharmacoinformatic and molecular docking studies reveal potential novel antidepressants against neurodegenerative disorders by targeting HSPB8

Charcot–Marie–Tooth (CMT) disease is an inherited peripheral neuromuscular disorder characterized by length-dependent and progressive degeneration of peripheral nerves, leading to muscular weakness. Research has shown that mutated HSPB8 may be responsible for depression, neurodegenerative disorders, and improper functioning of peripheral nerves, resulting in neuromuscular disorders like CMT. In the current work, a hybrid approach of virtual screening and molecular docking studies was followed by homology modeling and pharmacophore identification. Detailed screening analyses were carried out by 2-D similarity search against prescribed antidepressant drugs with physicochemical properties. LigandScout was employed to ascertain novel molecules and pharmacophore properties. In this study, we report three novel compounds that showed maximum binding affinity with HSPB8. Docking analysis elucidated that Met37, Ser57, Ser58, Trp60, Thr63, Thr114, Lys115, Asp116, Gly117, Val152, Val154, Leu186, Asp189, Ser190, Gln191, and Glu192 are critical residues for ligand–receptor interactions. Our analyses suggested paroxetine as a potent compound for targeting HSPB8. Selected compounds have more effective energy scores than the selected drug analogs. Additionally, site-directed mutagenesis could be significant for further analysis of the binding pocket. The novel findings based on an in silico approach may be momentous for potent drug design against depression and CMT.

Pharmacoinformatics elucidation of potential drug targets against migraine to target ion channel protein KCNK18.

Migraine, a complex debilitating neurological disorder is strongly associated with potassium channel subfamily K member 18 (KCNK18). Research has emphasized that high levels of KCNK18 may be responsible for improper functioning of neurotransmitters, resulting in neurological disorders like migraine. In the present study, a hybrid approach of molecular docking and virtual screening were followed by pharmacophore identification and structure modeling. Screening was performed using a two-dimensional similarity search against recommended migraine drugs, keeping in view the physicochemical properties of drugs. LigandScout tool was used for exploring pharmacophore properties and designing novel molecules. Here, we report the screening of four novel compounds that have showed maximum binding affinity against KCNK18, obtained through the ZINC database, and Drug and Drug-Like libraries. Docking studies revealed that Asp-46, Ile-324, Ile-44, Gly-118, Leu-338, Val-113, and Phe-41 are critical residues for receptor–ligand interaction. A virtual screening approach coupled with docking energies and druglikeness rules illustrated that ergotamine and PB-414901692 are potential inhibitor compounds for targeting KCNK18. We propose that selected compounds may be more potent than the previously listed drug analogs based on the binding energy values. Further analysis of these inhibitors through site-directed mutagenesis could be helpful for exploring the details of ligand-binding pockets. Overall, the findings of this study may be helpful for designing novel therapeutic targets to cure migraine.

Adaptive evolution and elucidating the potential inhibitor against schizophrenia to target DAOA (G72) isoforms

Schizophrenia (SZ), a chronic mental and heritable disorder characterized by neurophysiological impairment and neuropsychological abnormalities, is strongly associated with D-amino acid oxidase activator (DAOA, G72). Research studies emphasized that overexpression of DAOA may be responsible for improper functioning of neurotransmitters, resulting in neurological disorders like SZ. In the present study, a hybrid approach of comparative modeling and molecular docking followed by inhibitor identification and structure modeling was employed. Screening was performed by two-dimensional similarity search against selected inhibitor, keeping in view the physiochemical properties of the inhibitor. Here, we report an inhibitor compound which showed maximum binding affinity against four selected isoforms of DAOA. Docking studies revealed that Glu-53, Thr-54, Lys-58, Val-85, Ser-86, Tyr-87, Leu-88, Glu-90, Leu-95, Val-98, Ser-100, Glu-112, Tyr-116, Lys-120, Asp-121, and Arg-122 are critical residues for receptor–ligand interaction. The C-terminal of selected isoforms is conserved, and binding was observed on the conserved region of isoforms. We propose that selected inhibitor might be more potent on the basis of binding energy values. Further analysis of this inhibitor through site-directed mutagenesis could be helpful for exploring the details of ligand-binding pockets. Overall, the findings of this study may be helpful in designing novel therapeutic targets to cure SZ.

Comparative Modeling, Molecular Docking, and Revealing of Potential Binding Pockets of RASSF2; a Candidate Cancer Gene

RASSF2, potential tumor suppressor gene, acts as a KRAS-specific effectors protein and may promote apoptosis and cell cycle arrest. It stabilizes STK3/MST2 by protecting it from proteasomal degradation. RASSF2 plays a significant role against the inhibition of cancer. MODELLER (9v15) and online servers (I-Tasser, SwissModel, 3D-JigSaw, ModWeb) were utilized to generate 3D structures of the RASSF2 based on homology modeling. A comparison between models predicted by MODELLER (9v15) and Web servers had been checked through utilized evaluation tools. The most potent model for RASSF2 was analyzed and selected for molecular docking studies. The binding pockets were revealed for binding studies through Site Hound. AutoDock Vina and AutoDock4 were utilized for molecular docking, and the attempt of this experiment was to identify the ligands for RASSF2. The selected compounds may act as regulators and regulate the normal activity of RASSF2. It was also analyzed and observed that the selected compounds showed least binding energy and high-affinity binding in predicted top binding domain. The determination of protein function is based on accurate identification of binding sites in protein structures. The binding site is known, and it may allow the ligand type and protein function to be determined by performing in silico and experimental procedures. The detection, comparison, and analysis of binding pockets are pivotal to drug discovery. It proposed that predicted structure is reliable for the structural insights and functional studies. The predicted binding pockets may lead to further analysis (drug discovery), used against cancer study.

Pharmacoinformatics and molecular docking studies reveal potential novel Proline Dehydrogenase (PRODH) compounds for Schizophrenia inhibition

Studies on Schizophrenia, so far reveal a complex picture of neurological malfunctioning reported to be strongly associated with proline dehydrogenase (PRODH). This study employs in silico hybrid approach for virtual screening and molecular docking followed by pharmacophore identification and structural modeling. Docking studies revealed critical residues for receptor-ligand interaction. Virtual screening approach coupled with docking energies and drug likeness rules, suggested that of 8 compounds, Clozapine, MCULE-1620364835-0 (Drug Score 88 %) and PB-752728400 (Drug Score 85 % and Binding energy 8.1 kcal/mol) observed as potential inhibitor compounds for targeting PRODH. Energy score of selected compounds were better than the previous listed drug analogs. ALDH4A1, functional partner of PRODH showed strong interactions with PRODH.

Molecular Modeling and Docking Analysis of CYP1A1 Associated with Head and Neck Cancer to Explore its Binding Regions

Cytochrome P450, family 1, subfamily A, polypeptide 1 is a phase I enzyme of cytochrome super family P-450 (CYP) involved in detoxification or conversion of carcinogens into a more electrophilic form, metabolized by phase II enzymes. These detoxifying enzymes have been widely studied in association with head and neck cancer. Multiple bioinformatics tools are applied for CYP1A1 modeling and its assessment. Homology based modeling from 2HI4 template was carried out by MODELLER 9v10 bioinformatics software. All evaluation tools confirmed the reliability of predicted model. The binding pockets were revealed for binding studies. Inhibitor (C6H13FN2O2) showed maximum binding affinity against CYP1A1. Docking studies revealed that Leu-21, Val-22, Phe-23, Gly-42, Pro-43, Gly-45, His-51, Gln-75 and Ile-76 are critical residues for receptor-ligand interaction. We propose that predicted structure is reliable for the structural insights and functional studies and selected inhibitor might be more potent for Head and Neck Cancer. Further analysis of this inhibitor through site-directed mutagenesis could be helpful for exploring the details of ligand binding pockets. Overall, findings of this study may be helpful in designing the novel therapeutic targets to cure Head and Neck cancer.