Dynamic Play between Human N-α-acetyltransferase D and H4-mutant Histones: Molecular Dynamics Study.

BACKGROUND: Many N-terminal acetyltransferases (NATs) play important role in the posttranslational modifications of histone tails. Research showed that these enzymes have been reported upregulated in many cancers. NatD is known to acetylate H4/H2A at the N-terminal. During lung cancer, this enzyme competes with the protein kinase CK2α and blocks the phosphorylation of H4 and, acetylates. It also, we observed that H4 has various mutations at the N-terminal and we considered only four mutations (S1C, R3C, G4D and G4S) to study the impacts of these mutations on H4 binding with NatD using MD simulation. OBJECTIVE: Our main objective in this study was to understand the structure and dynamics of hNatD under the influence of WT and MT H4 histones bindings. The previous experimental study reported that mutations on H4 N-terminus reduce the catalytic efficiency of N-Terminal acetylation. But here, we performed a molecular- level study thus, we can understand how these mutations (S1C, R3C, G4D and G4S) cause significant depletion in catalytic efficiency of hNatD. METHODS: Purely computational approaches were employed to investigate the impacts of four mutations in human histone H4 on its binding with the N-α-acetyltransferase D. Initially, molecular docking was used to dock the histone H4 peptide with the N-α-acetyltransferase. Next, all-atom molecular dynamics simulation was performed to probe the structural deviation and dynamics of N-α-acetyltransferase D under the binding of WT and MT H4 histones. RESULTS: Our results show that R3C stabilizes the NatD whereas the remaining mutations destabilize the NatD. Thus, mutations have significant impacts on NatD structure. Our finding supports the previous analysis also. Another interesting observation is that the enzymatic activity of hNatD is altered due to the considerably large deviation of acetyl-CoA from its original position (G4D). Further, simulation and correlation data suggest which regions of the hNatD are highly flexible and rigid and, which domains or residues have the correlation and anticorrelation. As hNatD is overexpressed in lung cancer, it is an important drug target for cancer hence, our study provides structural information to target hNatD. CONCLUSION: In this study, we examined the impacts of WT and MTs (S1C, R3C, G4D and G4S) histone H4 decapeptides on their bindings with hNatD by using 100 ns all-atom MD simulation. Our results support the previous finding that the mutant H4 histones reduce the catalytic efficiency of hNatD. The MD posttrajectory analyses revealed that S1C, G4S and G4D mutants remarkably alter the residue network in hNatD. The intramolecular hydrogen bond analysis suggested that there is a considerable number of loss of hydrogen bonds in hNatD of hNatD-H4_G4D and hNatD-H4_G4S complexes whereas a large number of hydrogen bonds were increased in hNatD of hNatD-H4_R3C complex during the entire simulations. This implies that R3C mutant binding to hNatD brings stability in hNatD in comparison with WT and other MTs complexes. The linear mutual information (LMI) and Betweenness centrality (BC) suggest that S1C, G4D and G4S significantly disrupt the catalytic site residue network as compared to R3C mutation in H4 histone. Thus, this might be the cause of a notable reduction in the catalytic efficiency of hNatD in these three mutant complexes. Further, interaction analysis supports that E126 is the important residue for the acetyltransferase mechanisms as it is dominantly found to have interactions with numerous residues of MTs histones in MD frames. Additionally, intermolecular hydrogen bond and RMSD analyses of acetyl-CoA predict the higher stability of acetyl-CoA inside the WT complex of hNatD and R3C complex. Also, we report here the structural and dynamic aspects and residue interactions network (RIN) of hNatD to target it to control cell proliferation in lung cancer conditions.

AMPA GluA2 subunit competitive inhibitors for PICK1 PDZ domain: Pharmacophore-based virtual screening, molecular docking, molecular dynamics simulation, and ADME studies.

PICK1 (Protein interacting with C kinase-1) plays a key role in the regulation of intracellular trafficking of AMPA GluA2 subunit that is linked with synaptic plasticity. PICK1 is a scaffolding protein and binds numerous proteins through its PDZ domain. Research showed that synaptic plasticity is altered upon disrupting the GluA2-PDZ interactions. Inhibiting PDZ and GluA2 binding lead to beneficial effects in the cure of neurological diseases thus, targeting PDZ domain is proposed as a novel therapeutic target in such diseases. For this, various classes of synthetic peptides were tested. Though small organic molecules have been utilized to prevent these interactions, the number of such molecules is inadequate. Hence, in this study, ten molecular libraries containing large number of molecules were screened against the PDZ domain using pharmacophore-based virtual screening to find the best hits for the PDZ domain. Molecular docking and molecular dynamics simulation studies revealed that Hit_II is a potent inhibitor for the PDZ domain and confirm the allosteric nature of Hit_III. Additionally, ADME analysis suggests the drug-likeness of both Hit_II and Hit_III. This study suggests that tested hits may have potency against the PDZ domain and can be considered effective to treat neurological disorders.Communicated by Ramaswamy H. Sarma.

Time Series Analysis of SARS-CoV-2 Genomes and Correlations among Highly Prevalent Mutations.

The efforts of the scientific community to tame the recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seem to have been diluted by the emergence of new viral strains. Therefore, it is imperative to understand the effect of mutations on viral evolution. We performed a time series analysis on 59,541 SARS-CoV-2 genomic sequences from around the world to gain insights into the kinetics of the mutations arising in the viral genomes. These 59,541 genomes were grouped according to month (January 2020 to March 2021) based on the collection date. Meta-analysis of these data led us to identify significant mutations in viral genomes. Pearson correlation of these mutations led us to the identification of 16 comutations. Among these comutations, some of the individual mutations have been shown to contribute to viral replication and fitness, suggesting a possible role of other unexplored mutations in viral evolution. We observed that the mutations 241C>T in the 5' untranslated region (UTR), 3037C>T in nsp3, 14408C>T in the RNA-dependent RNA polymerase (RdRp), and 23403A>G in spike are correlated with each other and were grouped in a single cluster by hierarchical clustering. These mutations have replaced the wild-type nucleotides in SARS-CoV-2 sequences. Additionally, we employed a suite of computational tools to investigate the effects of T85I (1059C>T), P323L (14408C>T), and Q57H (25563G>T) mutations in nsp2, RdRp, and the ORF3a protein of SARS-CoV-2, respectively. We observed that the mutations T85I and Q57H tend to be deleterious and destabilize the respective wild-type protein, whereas P323L in RdRp tends to be neutral and has a stabilizing effect. IMPORTANCE We performed a meta-analysis on SARS-CoV-2 genomes categorized by collection month and identified several significant mutations. Pearson correlation analysis of these significant mutations identified 16 comutations having absolute correlation coefficients of >0.4 and a frequency of >30% in the genomes used in this study. The correlation results were further validated by another statistical tool called hierarchical clustering, where mutations were grouped in clusters on the basis of their similarity. We identified several positive and negative correlations among comutations in SARS-CoV-2 isolates from around the world which might contribute to viral pathogenesis. The negative correlations among some of the mutations in SARS-CoV-2 identified in this study warrant further investigations. Further analysis of mutations such as T85I in nsp2 and Q57H in ORF3a protein revealed that these mutations tend to destabilize the protein relative to the wild type, whereas P323L in RdRp is neutral and has a stabilizing effect. Thus, we have identified several comutations which can be further characterized to gain insights into SARS-CoV-2 evolution.

In silico characterization of mutations circulating in SARS-CoV-2 structural proteins.

SARS-CoV-2 has recently emerged as a pandemic that has caused more than 2.4 million deaths worldwide. Since the onset of infections, several full-length sequences of viral genome have been made available which have been used to gain insights into viral dynamics. We utilised a meta-data driven comparative analysis tool for sequences (Meta-CATS) algorithm to identify mutations in 829 SARS-CoV-2 genomes from around the world. The algorithm predicted sixty-one mutations among SARS-CoV-2 genomes. We observed that most of the mutations were concentrated around three protein coding genes viz nsp3 (non-structural protein 3), RdRp (RNA-directed RNA polymerase) and Nucleocapsid (N) proteins of SARS-CoV-2. We used various computational tools including normal mode analysis (NMA), C-α discrete molecular dynamics (DMD) and all-atom molecular dynamic simulations (MD) to study the effect of mutations on functionality, stability and flexibility of SARS-CoV-2 structural proteins including envelope (E), N and spike (S) proteins. PredictSNP predictor suggested that four mutations (L37H in E, R203K and P344S in N and D614G in S) out of seven were predicted to be neutral whilst the remaining ones (P13L, S197L and G204R in N) were predicted to be deleterious in nature thereby impacting protein functionality. NMA, C-α DMD and all-atom MD suggested some mutations to have stabilizing roles (P13L, S197L and R203K in N protein) where remaining ones were predicted to destabilize mutant protein. In summary, we identified significant mutations in SARS-CoV-2 genomes as well as used computational approaches to further characterize the possible effect of highly significant mutations on SARS-CoV-2 structural proteins.Communicated by Ramaswamy H. Sarma.

Peptide modelling and screening against human ACE2 and spike glycoprotein RBD of SARS-CoV-2.

Outbreak of Coronavirus Disease 2019 (COVID-19) has become a great challenge for scientific community globally. Virus enters cell through spike glycoprotein fusion with ACE2 (Angiotensin-Converting Enzyme 2) human receptor. Hence, spike glycoprotein of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a potential target for diagnostics, vaccines, and antibodies. Also, virus entry can be prevented by blocking ACE2 thus, ACE2 can be considered potential target for therapeutics. As being highly specific, safe and efficacious, peptides hold their place in therapeutics. In present study, we retrieved sequence of 70 peptides from Antiviral Peptide Database (AVPdb), modelled them using 3D structure predicting web tool and docked them with receptor binding domain (RBD) of spike protein and human host receptor ACE2 using peptide-protein docking. It was observed that peptides have more affinity towards ACE2 in comparison with spike RBD. Interestingly it was noticed that most of the peptides bind to RBM (residue binding motif) which is responsible for ACE2 binding at the interface of RBD while, for ACE2, peptides prefer to bind the core cavity rather than RBD binding interface. To further investigate how peptides at the interface of RBD or ACE2 alter the binding between RBD and ACE2, protein-protein docking of RBD and ACE2 with and without peptides was performed. Peptides, AVP0671 at RBD and AVP1244 at ACE2 interfaces significantly reduce the binding affinity and change the orientation of RBD and ACE2 binding. This finding suggests that peptides can be used as a drug to inhibit virus entry in cells to stop COVID-19 pandemic in the future after experimental evidences.

Self-assembled chitosan-zirconium phosphate nanostructures for adsorption of chromium and degradation of dyes.

Nano zirconium phosphate (ZrP) was synthesized hydrothermally using an autoclave and was further self-assembled with chitosan to form bionanocomposite CZrP. The structural characteristics of ZrP and CZrP were investigated by Fourier Transform Infrared (FT-IR), X-Ray Diffraction (XRD), Energy Dispersive X-Ray (EDX), X-Ray Photelectron Spectroscopy (XPS), Electron Spin Resonance (ESR), Raman spectroscopy and Transmission Electron Microscopy (TEM) techniques. During the course of characterization, unique surface defects and superoxide anions stabilized on ZrP and CZrP were observed for the first time. The potential of the synthesized nanocomposite was investigated for adsorption of Cr(VI), a copper phthalocynanine dye- Reactive blue-21 (RB-21), azo dye- Reactive Red 141 (RR-141), a xanthene dye-Rhodamine-6G as well as binary mixtures of the dyes. Further the potential of CZRP as catalyst for the hydrogen peroxide degradation of dyes was investigated. The dyes were degraded in ˜10 min and CZrP exhibited stability during multiple runs of degradation of the dyes.