Fighting against amyotrophic lateral sclerosis (ALS) with flavonoids: a computational approach to inhibit superoxide dismutase (SOD1) mutant aggregation

Protein aggregation is a biological process that occurs when proteins misfold. Misfolding and aggregation of human superoxide dismutase (hSOD1) cause a neurodegenerative disease called amyotrophic lateral sclerosis (ALS). Among the mutations occurring, targeting the E21K mutation could be a good choice to understand the pathological mechanism of SOD1 in ALS, whereof it significantly reduces life hopefulness in patients. Naturally occurring polyphenolic flavonoids have been suggested as a way to alleviate the amyloidogenic behavior of proteins. In this study, computational tools were used to identify promising flavonoid compounds that effectively inhibit the pathogenic behavior of the E21K mutant. Initial screening identified Pelargonidin, Curcumin, and Silybin as promising leads. Molecular dynamics (MD) simulations showed that the binding of flavonoids to the mutated SOD1 caused changes in the protein stability, hydrophobicity, flexibility, and restoration of lost hydrogen bonds. Secondary structure analysis indicated that the protein destabilization and the increased propensity of β-sheet caused by the mutation were restored to the wild-type state upon binding of flavonoids. Free energy landscape (FEL) analysis was also used to differentiate aggregation, and results showed that Silybin followed by Pelargonidin had the most therapeutic efficacy against the E21K mutant SOD1. Therefore, these flavonoids hold great potential as highly effective inhibitors in mitigating ALS's fatal and insuperable effects.Communicated by Ramaswamy H. Sarma.

Exploring bacterial key genes and therapeutic agents for breast cancer among the Ghanaian female population: Insights from In Silico analyses

Breast cancer (BC) is yet a significant global health challenge across various populations including Ghana, though several studies on host-genome associated with BC have been investigated molecular mechanisms of BC development and progression, and candidate therapeutic agents. However, a little attention has been given on microbial genome in this regard, although alterations in microbiota and epigenetic modifications are recognized as substantial risk factors for BC. This study focused on identifying bacterial key genes (bKGs) associated with BC infections in the Ghanaian population and exploring potential drug molecules by targeting these bKGs through in silico analyses. At first, 16S rRNA bacterial sequence data were downloaded from NCBI database comprising 520 samples from BC patients and 442 from healthy controls. Analysis of 16S rRNA-Seq data showed significant differences in bacterial abundance between BC and healthy groups and identified 26 differential genera with the threshold values at |log2FC|>2.0 and p-value≤0.05. It was observed that two genera Prevotella and Anaerovibria are significantly upregulated in BC patients and others are downregulated. Functional analysis based on all differential genera identified 19 MetaCyc signaling pathways, twelve of which were significantly enriched in BC patients by containing 165 genes Top-ranked 10 genes mdh, pykF, gapA, zwf, pgi, tpiA, pgk, pfkA, ppsA, and pykA were identified as BC-causing bacterial key genes (bKGs) through protein-protein interaction network analysis. Subsequently, the bKG-guided top ranked 10 drug molecules Digitoxin, Digoxin, Ledipasvir, Suramin, Ergotamine, Venetoclax, Nilotinib, Conivaptan, Dihydroergotamine, and Elbasvir were identified using molecular docking analysis. The stability of top-ranked three drug-target complexes (Digitoxin-pykA, Digoxin-mdh, and Ledipasvir-pgi) were confirmed through the molecular dynamics simulation studies. Therefore, these findings might be useful resources to the wet-lab researchers for further experimental validation on bacterial therapies against BC.

Discovery of key molecular signatures for diagnosis and therapies of glioblastoma by combining supervised and unsupervised learning approaches

Glioblastoma (GBM) is the most malignant brain cancer and one of the leading causes of cancer-related death globally. So, identifying potential molecular signatures and associated drug molecules are crucial for diagnosis and therapies of GBM. This study suggested GBM-causing ten key genes (ASPM, CCNB2, CDK1, AURKA, TOP2A, CHEK1, CDCA8, SMC4, MCM10, and RAD51AP1) from nine transcriptomics datasets by combining supervised and unsupervised learning results. Differential expression patterns of key genes (KGs) between GBM and control samples were verified by different independent databases. Gene regulatory network (GRN) detected some important transcriptional and post-transcriptional regulators for KGs. The KGs-set enrichment analysis unveiled some crucial GBM-causing molecular functions, biological processes, cellular components, and pathways. The DNA methylation analysis detected some hypo-methylated CpG sites that might stimulate the GBM development. From the immune infiltration analysis, we found that almost all KGs are associated with different immune cell infiltration levels. Finally, we recommended KGs-guided four repurposable drug molecules (Fluoxetine, Vatalanib, TGX221 and RO3306) against GBM through molecular docking, drug likeness, ADMET analyses and molecular dynamics simulation studies. Thus, the discoveries of this study could serve as valuable resources for wet-lab experiments in order to take a proper treatment plan against GBM.

Common molecular and pathophysiological underpinnings of delirium and Alzheimer's disease: molecular signatures and therapeutic indications

BACKGROUND

Delirium and Alzheimer's disease (AD) are common causes of cognitive dysfunction among older adults. These neurodegenerative diseases share a common and complex relationship, and can occur individually or concurrently, increasing the chance of permanent mental dysfunction. However, the common molecular pathophysiology, key proteomic biomarkers, and functional pathways are largely unknown, whereby delirium is superimposed on AD and dementia.

METHODS

We employed an integrated bioinformatics and system biology analysis approach to decipher such common key proteomic signatures, pathophysiological links between delirium and AD by analyzing the gene expression data of AD-affected human brain samples and comparing them with delirium-associated proteins. The present study identified the common drug target hub-proteins examining the protein-protein interaction (PPI) and gene regulatory network analysis. The functional enrichment and pathway analysis was conducted to reveal the common pathophysiological relationship. Finally, the molecular docking and dynamic simulation was used to computationally identify and validate the potential drug target and repurposable drugs for delirium and AD.

RESULTS

We detected 99 shared differentially expressed genes (sDEGs) associated with AD and delirium. The sDEGs-set enrichment analysis detected the transmission across chemical synapses, neurodegeneration pathways, neuroinflammation and glutamatergic signaling pathway, oxidative stress, and BDNF signaling pathway as the most significant signaling pathways shared by delirium and AD. The disease-sDEGs interaction analysis highlighted the other disease risk factors with delirium and AD development and progression. Among the sDEGs of delirium and AD, the top 10 hub-proteins including ALB, APP, BDNF, CREB1, DLG4, GAD1, GAD2, GFAP, GRIN2B and GRIN2A were found by the PPI network analysis. Based on the maximum molecular docking binding affinities and molecular dynamic simulation (100 ns) results, the ALB and GAD2 were found as prominent drug target proteins when tacrine and donepezil were identified as potential drug candidates for delirium and AD.

CONCLUSION

The study outlined the common key biomolecules and biological pathways shared by delirium and AD. The computationally reported potential drug molecules need a deeper investigation including clinical trials to validate their effectiveness. The outcomes from this study will help to understand the typical pathophysiological relationship between delirium and AD and flag future therapeutic development research for delirium.

Discovery of Bacterial Key Genes from 16S rRNA-Seq Profiles That Are Associated with the Complications of SARS-CoV-2 Infections and Provide Therapeutic Indications

SARS-CoV-2 infections, commonly referred to as COVID-19, remain a critical risk to both human life and global economies. Particularly, COVID-19 patients with weak immunity may suffer from different complications due to the bacterial co-infections/super-infections/secondary infections. Therefore, different variants of alternative antibacterial therapeutic agents are required to inhibit those infection-causing drug-resistant pathogenic bacteria. This study attempted to explore these bacterial pathogens and their inhibitors by using integrated statistical and bioinformatics approaches. By analyzing bacterial 16S rRNA sequence profiles, at first, we detected five bacterial genera and taxa (Bacteroides, Parabacteroides, Prevotella Clostridium, Atopobium, and Peptostreptococcus) based on differentially abundant bacteria between SARS-CoV-2 infection and control samples that are significantly enriched in 23 metabolic pathways. A total of 183 bacterial genes were found in the enriched pathways. Then, the top-ranked 10 bacterial genes (accB, ftsB, glyQ, hldD, lpxC, lptD, mlaA, ppsA, ppc, and tamB) were selected as the pathogenic bacterial key genes (bKGs) by their protein-protein interaction (PPI) network analysis. Then, we detected bKG-guided top-ranked eight drug molecules (Bemcentinib, Ledipasvir, Velpatasvir, Tirilazad, Acetyldigitoxin, Entreatinib, Digitoxin, and Elbasvir) by molecular docking. Finally, the binding stability of the top-ranked three drug molecules (Bemcentinib, Ledipasvir, and Velpatasvir) against three receptors (hldD, mlaA, and lptD) was investigated by computing their binding free energies with molecular dynamic (MD) simulation-based MM-PBSA techniques, respectively, and was found to be stable. Therefore, the findings of this study could be useful resources for developing a proper treatment plan against bacterial co-/super-/secondary-infection in SARS-CoV-2 infections.

Polyphenolic flavonoid compounds act as the inhibitory potential of aggregation process: Implications for the prevention and therapeutics against FALS-associated D101G SOD1 mutant

Aggregation of proteins is a biological phenomenon caused by misfolded proteins. Human superoxide dismutase (hSOD1) misfolding and aggregation underlie the neurological illness amyotrophic lateral sclerosis (ALS). The most significant contributing factor to ALS is genetic point mutations in SOD1. particularly, D101G mutant is the most harmful because it significantly reduces the life expectancy of patients. Subsequently, the use of natural polyphenolic flavonoids is strongly recommended to reduce the amyloidogenic behavior of protopathic proteins. In this study, using computational parameters such as protein-ligand interaction and molecular dynamics (MD) simulation analyses, we are trying to identify a pharmacodynamically promising flavonoid compound that can effectively inhibit the pathogenic behavior of the D101G mutant. Epigallocatechin-gallate (EGCG), Hesperidin, Isorhamnetin, and Diosmetin were identified as potential leads in a preliminary screening of flavonoids to anti-amyloid action. The results of MD showed that the binding of flavonoids to D101G mutant caused changes in stability, hydrophobicity of protein, and flexibility, as well as significantly led to the restoration of lost hydrogen bonds. Secondary structure analysis showed that protein destabilization and the increased propensity of β-sheet caused by the mutation were restored to the wild-type state upon binding of flavonoids. Besides, to differentiate aggregation, we elucidated alterations in the free energy landscape (FEL) and dynamic cross-correlation matrix (DCCM) of WT-SOD1 and mutant (unbound /bound) states. Among flavonoids, Epigallocatechin-gallate and Hesperidin had the most therapeutic efficacy against the D101G mutant. Therefore, Epigallocatechin-gallate and Hesperidin promise considerable therapeutic potential to develop highly effective inhibitors in reducing fatal and irreversible ALS.

In silico analysis of SOD1 aggregation inhibition modes of tertiary amine pyrazolone and pyrano coumarin ferulate as ALS drug candidates

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease, the familial form (fALS) of which is often cognate to mutations in the antioxidant enzyme Cu/Zn superoxide dismutase 1 (SOD1) leading to misfolding and aggregation. Two small molecules, a tertiary amine pyrazolone (TAP) and a pyrano coumarin ferulate (PCF) were suggested to be ALS drug candidates following experimental observation of their ability to inhibit SOD1 protein misfolding and aggregation. The present work aims at computational investigation of these experimentally proposed drug candidates to gain insight into their mechanism of SOD1 misfolding and aggregation inhibition. On the basis of molecular docking, molecular dynamics simulation, MM-PBSA and per-residue energy decomposition analysis, we examined the specific interactions of TAP and PCF with three probable binding sites of SOD1, namely, dimeric interface cavity, W32 and, UMP binding sites. Results suggest that the binding of TAP at W32 and at UMP sites are least probable due to absence of any favorable interaction. The binding of TAP to dimeric cavity is also unstable due to strong unfavorable interactions. In case of PCF, binding at the UMP site is least probable while binding at dimeric cavity is accompanied by unfavorable interactions. PCF, however, exhibits stable binding with the W32 binding site of SOD1 by stabilizing the solvent accessible hydrophobic residues, which otherwise would have acted as contact points for aggregation. Thus the results imply that compound PCF functions as an inhibitior of SOD1 misfolding/aggregation through direct interaction with the protein SOD1 at the W32 binding site. However, TAP is likely to act as an inhibitor through a different mechanism rather than direct interaction with the protein SOD1. These results apart from reinforcing previous experimental findings, shed light on the probable mechanism of action of the proposed drug candidates.

Exploring Prognostic Biomarkers of Acute Myeloid Leukemia to Determine Its Most Effective Drugs from the FDA-Approved List through Molecular Docking and Dynamic Simulation

Acute myeloid leukemia (AML) is a blood cancer caused by the abnormal proliferation and differentiation of hematopoietic stem cells in the bone marrow. The actual genetic markers and molecular mechanisms of AML prognosis are unclear till today. This study used bioinformatics approaches for identifying hub genes and pathways associated with AML development to uncover potential molecular mechanisms. The expression profiles of RNA-Seq datasets, GSE68925 and GSE183817, were retrieved from the Gene Expression Omnibus (GEO) database. These two datasets were analyzed by GREIN to obtain differentially expressed genes (DEGs), which were used for performing the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, protein-protein interaction (PPI), and survival analysis. The molecular docking and dynamic simulation were performed to identify the most effective drug/s for AML from the drug list approved by the Food and Drug Administration (FDA). By integrating the two datasets, 238 DEGs were identified as likely to be affected by AML progression. GO enrichment analyses exhibited that the upregulated genes were mainly associated with inflammatory response (BP) and extracellular region (CC). The downregulated DEGs were involved in the T-cell receptor signalling pathway (BP), an integral component of the lumenal side of the endoplasmic reticulum membrane (CC) and peptide antigen binding (MF). The pathway enrichment analysis showed that the upregulated DEGs were mainly associated with the T-cell receptor signalling pathway. Among the top 15 hub genes, the expression levels of ALDH1A1 and CFD were associated with the prognosis of AML. Four FDA-approved drugs were selected, and a top-ranked drug was identified for each biomarker through molecular docking studies. The top-ranked drugs were further confirmed by molecular dynamic simulation that revealed their binding stability and confirmed their stable performance. Therefore, the drug compounds, enasidenib and gilteritinib, can be recommended as the most effective drugs against the ALDH1A1 and CFD proteins, respectively.

Identification of host genomic biomarkers from multiple transcriptomics datasets for diagnosis and therapies of SARS-CoV-2 infections

The pandemic of COVID-19 is a severe threat to human life and the global economy. Despite the success of vaccination efforts in reducing the spread of the virus, the situation remains largely uncontrolled due to the random mutation in the RNA sequence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which demands different variants of effective drugs. Disease-causing gene-mediated proteins are usually used as receptors to explore effective drug molecules. In this study, we analyzed two different RNA-Seq and one microarray gene expression profile datasets by integrating EdgeR, LIMMA, weighted gene co-expression network and robust rank aggregation approaches, which revealed SARS-CoV-2 infection causing eight hub-genes (HubGs) including HubGs; REL, AURKA, AURKB, FBXL3, OAS1, STAT4, MMP2 and IL6 as the host genomic biomarkers. Gene Ontology and pathway enrichment analyses of HubGs significantly enriched some crucial biological processes, molecular functions, cellular components and signaling pathways that are associated with the mechanisms of SARS-CoV-2 infections. Regulatory network analysis identified top-ranked 5 TFs (SRF, PBX1, MEIS1, ESR1 and MYC) and 5 miRNAs (hsa-miR-106b-5p, hsa-miR-20b-5p, hsa-miR-93-5p, hsa-miR-106a-5p and hsa-miR-20a-5p) as the key transcriptional and post-transcriptional regulators of HubGs. Then, we conducted a molecular docking analysis to determine potential drug candidates that could interact with HubGs-mediated receptors. This analysis resulted in the identification of top-ranked ten drug agents, including Nilotinib, Tegobuvir, Digoxin, Proscillaridin, Olysio, Simeprevir, Hesperidin, Oleanolic Acid, Naltrindole and Danoprevir. Finally, we investigated the binding stability of the top-ranked three drug molecules Nilotinib, Tegobuvir and Proscillaridin with the three top-ranked proposed receptors (AURKA, AURKB, OAS1) by using 100 ns MD-based MM-PBSA simulations and observed their stable performance. Therefore, the findings of this study might be useful resources for diagnosis and therapies of SARS-CoV-2 infections.

Impact of Plant-Derived Compounds on Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal illness characterized by progressive motor neuron degeneration. Conventional therapies for ALS are based on treatment of symptoms, and the disease remains incurable. Molecular mechanisms are unclear, but studies have been pointing to involvement of glia, neuroinflammation, oxidative stress, and glutamate excitotoxicity as a key factor. Nowadays, we have few treatments for this disease that only delays death, but also does not stop the neurodegenerative process. These treatments are based on glutamate blockage (riluzole), tyrosine kinase inhibition (masitinib), and antioxidant activity (edaravone). In the past few years, plant-derived compounds have been studied for neurodegenerative disorder therapies based on neuroprotection and glial cell response. In this review, we describe mechanisms of action of natural compounds associated with neuroprotective effects, and the possibilities for new therapeutic strategies in ALS.

Synergistic effects of dendrosomal nanocurcumin and oxaliplatin on oncogenic properties of ovarian cancer cell lines by down-expression of MMPs

BACKGROUND

Contrary to the advantageous anticancer activities of curcumin (Cur), limited bioavailability and solubility hindered its efficacy. Here, nontoxic dendrosomal nano carrier with Cur was used to overcome these problems. Despite considerable antitumor properties of Oxaliplatin (Oxa), the limiting factors are drug resistance and adverse side-effects. The hypothesis of this study was to evaluate the possible synergism between dendrosomal nanocurcumin (DNC) and Oxa and these agents showed growth regulatory effects on SKOV3 and OVCAR3 cells.

METHODS AND MATERIALS

In the present study, colony formation, wound healing motility, cell adhesion, transwell invasion and migration assay and cell cycle arrest with or without DNC, Oxa and Combination were defined. In addition to, real time PCR and Western blot were used to analyze AKT, PI3K, PKC, JNK, P38 and MMPs mRNAs and proteins expressions. Docking of MMP-2-Cur, MMP-2-DNC and MMP-2-Oxa was performed and the results of all three complexes were simulated by molecular dynamics.

RESULTS

Our findings illustrated that DNC had the greatest effect on cell death as compared to the Cur alone. Moreover, the growth inhibitory effects (such as cell death correlated to apoptosis) were more intense if Oxa was added followed by DNC at 4 h interval. However, insignificant effects were observed upon simultaneous addition of these two agents in both cell lines. Besides, a combination of agents synergistically alters the relative expression of MMP-9.

CONCLUSIONS

The docking results showed that His70 and Asp100 may play a key role at the MMP-2 binding site. The matrigel invasion as well as cell viability of ovarian cancer cell lines SKOV3 and OVCAR3 by DNC alone or in combination with Oxa was inhibited significantly. The inhibitory effects of these agents were due to the differential expression levels of MMP 2 and MMP 9 regulated by multiple downstream signaling cascades. From the molecular dynamic simulation studies, it was confirmed that DNC established a strong interaction with MMP-2.

Advances in the understanding of protein misfolding and aggregation through molecular dynamics simulation

Aberrant protein folding known as protein misfolding is counted as one of the striking factors of neurodegenerative diseases. The extensive range of pathologies caused by protein misfolding, aggregation and subsequent accumulation are mainly classified into either gain of function diseases or loss of function diseases. In order to seek for novel strategies for treatment and diagnosis of neurodegenerative diseases, insights into the mechanism of misfolding and aggregation is essential. A comprehensive knowledge on the factors influencing misfolding and aggregation is required as well. An extensive experimental study on protein aggregation is somewhat challenging due to the insoluble and noncrystalline nature of amyloid fibrils. Thus there has been a growing use of computational approaches including Monte Carlo simulation, docking simulation, molecular dynamics simulation in the study of protein misfolding and aggregation. The review presents a discussion on molecular dynamics simulation alone as to how it has emerged as a promising tool in the understanding of protein misfolding and aggregation in general, detailing upon three different aspects considering four misfold prone proteins in particular. It is noticeable that all four proteins considered in this review i.e prion, superoxide dismutase1, huntingtin and amyloid β are linked to chronic neurodegenerative diseases with debilitating effects. Initially the review elaborates on the factors influencing the misfolding and aggregation. Next, it addresses our current understanding of the amyloid structures and the associated aggregation mechanisms, finally, summarizing the contribution of this computational tool in the search for therapeutic strategies against the respective protein-deposition diseases.

Metadata analysis to explore hub of the hub-genes highlighting their functions, pathways and regulators for cervical cancer diagnosis and therapies

Cervical cancer (CC) is considered as the fourth most common women cancer globally.that shows malignant features of local infiltration and invasion into adjacent organs and tissues. There are several individual studies in the literature that explored CC-causing hub-genes (HubGs), however, we observed that their results are not so consistent. Therefore, the main objective of this study was to explore hub of the HubGs (hHubGs) that might be more representative CC-causing HubGs compare to the single study based HubGs. We reviewed 52 published articles and found 255 HubGs/studied-genes in total. Among them, we selected 10 HubGs (CDK1, CDK2, CHEK1, MKI67, TOP2A, BRCA1, PLK1, CCNA2, CCNB1, TYMS) as the hHubGs by the protein-protein interaction (PPI) network analysis. Then, we validated their differential expression patterns between CC and control samples through the GPEA database. The enrichment analysis of HubGs revealed some crucial CC-causing biological processes (BPs), molecular functions (MFs) and cellular components (CCs) by involving hHubGs. The gene regulatory network (GRN) analysis identified four TFs proteins and three miRNAs as the key transcriptional and post-transcriptional regulators of hHubGs. Then, we identified hHubGs-guided top-ranked FDA-approved 10 candidate drugs and validated them against the state-of-the-arts independent receptors by molecular docking analysis. Finally, we investigated the binding stability of the top-ranked three candidate drugs (Docetaxel, Temsirolimus, Paclitaxel) by using 100 ns MD-based MM-PBSA simulations and observed their stable performance. Therefore the finding of this study might be the useful resources for CC diagnosis and therapies.

Designing potential siRNA molecules for silencing the gene of the nucleocapsid protein of Nipah virus: A computational investigation

Nipah virus (NiV), a zoonotic virus, engenders severe infections with noticeable complications and deaths in humans and animals. Since its emergence, it is frightening, this virus has been causing regular outbreaks in various countries, particularly in Bangladesh, India, and Malaysia. Unfortunately, no efficient vaccine or drug is available now to combat this baneful virus. NiV employs its nucleocapsid protein for genetic material packaging, which is crucial for viral replication inside the host cells. The small interfering RNAs (siRNAs) can play a central role in inhibiting the expression of disease-causing viral genes by hybridization and subsequent inactivation of the complementary target viral mRNAs through the RNA interference (RNAi) pathway. Therefore, potential siRNAs as molecular therapeutics against the nucleocapsid protein gene of NiV were designed in this study. First, ten prospective siRNAs were identified using the conserved nucleocapsid gene sequences among all available NiV strains collected from various countries. After that, off-target binding, GC (guanine-cytosine) content, secondary structure, binding affinity with the target, melting temperature, efficacy analysis, and binding capacity with the human argonaute protein 2 (AGO2) of these siRNAs were evaluated to predict their suitability. These designed siRNA molecules bear promise in silencing the NiV gene encoding the nucleocapsid protein and thus can alleviate the severity of this dangerous virus. Further in vivo experiments are recommended before using these designed siRNAs as alternative and effective molecular therapeutic agents against NiV.

Novel Galactopyranoside Esters: Synthesis, Mechanism, In Vitro Antimicrobial Evaluation and Molecular Docking Studies

One-step direct unimolar valeroylation of methyl α-D-galactopyranoside (MDG) mainly furnished the corresponding 6-O-valeroate. However, DMAP catalyzed a similar reaction that produced 2,6-di-O-valeroate and 6-O-valeroate, with the reactivity sequence as 6-OH > 2-OH > 3-OH,4-OH. To obtain novel antimicrobial agents, 6-O- and 2,6-di-O-valeroate were converted into several 2,3,4-tri-O- and 3,4-di-O-acyl esters, respectively, with other acylating agents in good yields. The PASS activity spectra along with in vitro antimicrobial evaluation clearly indicated that these MDG esters had better antifungal activities than antibacterial agents. To rationalize higher antifungal potentiality, molecular docking was conducted with sterol 14α-demethylase (PDB ID: 4UYL, Aspergillus fumigatus), which clearly supported the in vitro antifungal results. In particular, MDG ester 7−12 showed higher binding energy than the antifungal drug, fluconazole. Additionally, these compounds were found to have more promising binding energy with the SARS-CoV-2 main protease (6LU7) than tetracycline, fluconazole, and native inhibitor N3. Detailed investigation of Ki values, absorption, distribution, metabolism, excretion, and toxicity (ADMET), and the drug-likeness profile indicated that most of these compounds satisfy the drug-likeness evaluation, bioavailability, and safety tests, and hence, these synthetic novel MDG esters could be new antifungal and antiviral drugs.

Probing the polyphenolic flavonoid, morin as a highly efficacious inhibitor against amyloid(A4V) mutant SOD1 in fatal amyotrophic lateral sclerosis

Deposition of misfolded protein aggregates in key areas of human brain is the quintessential trait of various pertinent neurodegenerative disorders including amyotrophic lateral sclerosis (ALS). Genetic point mutations in Cu/Zn superoxide dismutase (SOD1) are found to be the most important contributing factor behind familial ALS. Especially, single nucleotide polymorphism (SNP) A4V is the most nocuous since it substantially decreases life expectancy of patients. Besides, the use of naturally occurring polyphenolic flavonoids is profoundly being advocated for palliating amyloidogenic behavior of proteopathic proteins. In the present analysis, through proficient computational tools, we have attempted to ascertain a pharmacodynamically promising flavonoid compound that effectively curbs the pathogenic behavior of A4V SOD1 mutant. Initial screening of flavonoids that exhibit potency against amyloids identified morin, myricetin and epigallocatechin gallate as promising leads. Further, with the help of feasible and yet adept protein-ligand interaction studies and stalwart molecular simulation analyses, we were able to observe that aforementioned flavonoids were able to considerably divert mutant A4V SOD1 from its distinct pathogenic behavior. Among which, morin showed the most curative potential against A4V SOD1. Therefore, morin holds a great therapeutic potential in contriving highly efficacious inhibitors in mitigating fatal and insuperable ALS.

Inactivation Mechanism and Efficacy of Grape Seed Extract for Human Norovirus Surrogate

Proper disinfection of harvested food and water is critical to minimize infectious disease. Grape seed extract (GSE), a commonly used health supplement, is a mixture of plant-derived polyphenols. Polyphenols possess antimicrobial and antifungal properties, but antiviral effects are not well-known. Here we show that GSE outperformed chemical disinfectants (e.g., free chlorine and peracetic acids) in inactivating Tulane virus, a human norovirus surrogate. GSE induced virus aggregation, a process that correlated with a decrease in virus titers. This aggregation and disinfection were not reversible. Molecular docking simulations indicate that polyphenols potentially formed hydrogen bonds and strong hydrophobic interactions with specific residues in viral capsid proteins. Together, these data suggest that polyphenols physically associate with viral capsid proteins to aggregate viruses as a means to inhibit virus entry into the host cell. Plant-based polyphenols like GSE are an attractive alternative to chemical disinfectants to remove infectious viruses from water or food. IMPORTANCE Human noroviruses are major food- and waterborne pathogens, causing approximately 20% of all cases of acute gastroenteritis cases in developing and developed countries. Proper sanitation or disinfection are critical strategies to minimize human norovirus-caused disease until a reliable vaccine is created. Grape seed extract (GSE) is a mixture of plant-derived polyphenols used as a health supplement. Polyphenols are known for antimicrobial, antifungal, and antibiofilm activities, but antiviral effects are not well-known. In studies presented here, plant-derived polyphenols outperformed chemical disinfectants (i.e., free chlorine and peracetic acids) in inactivating Tulane virus, a human norovirus surrogate. Based on data from molecular assays and molecular docking simulations, the current model is that the polyphenols in GSE bind to the Tulane virus capsid, an event that triggers virion aggregation. It is thought that this aggregation prevents Tulane virus from entering host cells.

Probing the competitive inhibitor efficacy of frog-skin alpha helical AMPs identified against ACE2 binding to SARS-CoV-2 S1 spike protein as therapeutic scaffold to prevent COVID-19

In COVID-19 infection, the SARS-CoV-2 spike protein S1 interacts to the ACE2 receptor of human host, instigating the viral infection. To examine the competitive inhibitor efficacy of broad spectrum alpha helical AMPs extracted from frog skin, a comparative study of intermolecular interactions between viral S1 and AMPs was performed relative to S1-ACE2p interactions. The ACE2 binding region with S1 was extracted as ACE2p from the complex for ease of computation. Surprisingly, the Spike-Dermaseptin-S9 complex had more intermolecular interactions than the other peptide complexes and importantly, the S1-ACE2p complex. We observed how atomic displacements in docked complexes impacted structural integrity of a receptor-binding domain in S1 through conformational sampling analysis. Notably, this geometry-based sampling approach confers the robust interactions that endure in S1-Dermaseptin-S9 complex, demonstrating its conformational transition. Additionally, QM calculations revealed that the global hardness to resist chemical perturbations was found more in Dermaseptin-S9 compared to ACE2p. Moreover, the conventional MD through PCA and the torsional angle analyses indicated that Dermaseptin-S9 altered the conformations of S1 considerably. Our analysis further revealed the high structural stability of S1-Dermaseptin-S9 complex and particularly, the trajectory analysis of the secondary structural elements established the alpha helical conformations to be retained in S1-Dermaseptin-S9 complex, as substantiated by SMD results. In conclusion, the functional dynamics proved to be significant for viral Spike S1 and Dermaseptin-S9 peptide when compared to ACE2p complex. Hence, Dermaseptin-S9 peptide inhibitor could be a strong candidate for therapeutic scaffold to prevent infection of SARS-CoV-2.

Bioinformatics Screening of Potential Biomarkers from mRNA Expression Profiles to Discover Drug Targets and Agents for Cervical Cancer

Bioinformatics analysis has been playing a vital role in identifying potential genomic biomarkers more accurately from an enormous number of candidates by reducing time and cost compared to the wet-lab-based experimental procedures for disease diagnosis, prognosis, and therapies. Cervical cancer (CC) is one of the most malignant diseases seen in women worldwide. This study aimed at identifying potential key genes (KGs), highlighting their functions, signaling pathways, and candidate drugs for CC diagnosis and targeting therapies. Four publicly available microarray datasets of CC were analyzed for identifying differentially expressed genes (DEGs) by the LIMMA approach through GEO2R online tool. We identified 116 common DEGs (cDEGs) that were utilized to identify seven KGs (AURKA, BRCA1, CCNB1, CDK1, MCM2, NCAPG2, and TOP2A) by the protein–protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of KGs revealed some important functions and signaling pathways that were significantly associated with CC infections. The interaction network analysis identified four TFs proteins and two miRNAs as the key transcriptional and post-transcriptional regulators of KGs. Considering seven KGs-based proteins, four key TFs proteins, and already published top-ranked seven KGs-based proteins (where five KGs were common with our proposed seven KGs) as drug target receptors, we performed their docking analysis with the 80 meta-drug agents that were already published by different reputed journals as CC drugs. We found Paclitaxel, Vinorelbine, Vincristine, Docetaxel, Everolimus, Temsirolimus, and Cabazitaxel as the top-ranked seven candidate drugs. Finally, we investigated the binding stability of the top-ranked three drugs (Paclitaxel, Vincristine, Vinorelbine) by using 100 ns MD-based MM-PBSA simulations with the three top-ranked proposed receptors (AURKA, CDK1, TOP2A) and observed their stable performance. Therefore, the proposed drugs might play a vital role in the treatment against CC.

Computational identification of host genomic biomarkers highlighting their functions, pathways and regulators that influence SARS-CoV-2 infections and drug repurposing

The pandemic threat of COVID-19 has severely destroyed human life as well as the economy around the world. Although, the vaccination has reduced the outspread, but people are still suffering due to the unstable RNA sequence patterns of SARS-CoV-2 which demands supplementary drugs. To explore novel drug target proteins, in this study, a transcriptomics RNA-Seq data generated from SARS-CoV-2 infection and control samples were analyzed. We identified 109 differentially expressed genes (DEGs) that were utilized to identify 10 hub-genes/proteins (TLR2, USP53, GUCY1A2, SNRPD2, NEDD9, IGF2, CXCL2, KLF6, PAG1 and ZFP36) by the protein–protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of hub-DEGs revealed some important functions and signaling pathways that are significantly associated with SARS-CoV-2 infections. The interaction network analysis identified 5 TFs proteins and 6 miRNAs as the key regulators of hub-DEGs. Considering 10 hub-proteins and 5 key TFs-proteins as drug target receptors, we performed their docking analysis with the SARS-CoV-2 3CL protease-guided top listed 90 FDA approved drugs. We found Torin-2, Rapamycin, Radotinib, Ivermectin, Thiostrepton, Tacrolimus and Daclatasvir as the top ranked seven candidate drugs. We investigated their resistance performance against the already published COVID-19 causing top-ranked 11 independent and 8 protonated receptor proteins by molecular docking analysis and found their strong binding affinities, which indicates that the proposed drugs are effective against the state-of-the-arts alternatives independent receptor proteins also. Finally, we investigated the stability of top three drugs (Torin-2, Rapamycin and Radotinib) by using 100 ns MD-based MM-PBSA simulations with the two top-ranked proposed receptors (TLR2, USP53) and independent receptors (IRF7, STAT1), and observed their stable performance. Therefore, the proposed drugs might play a vital role for the treatment against different variants of SARS-CoV-2 infections.

Decoding Conformational Imprint of Convoluted Molecular Interactions Between Prenylflavonoids and Aggregated Amyloid-Beta42 Peptide Causing Alzheimer's Disease

Protein misfolding occurs due to the loss of native protein structure and adopts an abnormal structure, wherein the misfolded proteins accumulate and form aggregates, which result in the formation of amyloid fibrils that are associated with neurodegenerative diseases. Amyloid beta (Aβ42) aggregation or amyloidosis is contemplated as a unique hallmark characteristic of Alzheimer’s disease (AD). Due to aberrant accrual and aggregation of Aβ42 in extracellular space, the formation of senile plaques is found in AD patients. These senile plaques occur usually in the cognitive and memory region of the brain, enfeebles neurodegeneration, hinders the signaling between synapse, and disrupts neuronal functioning. In recent years, herbal compounds are identified and characterized for their potential as Aβ42 inhibitors. Thus, understanding their structure and molecular mechanics can provide an incredible finding in AD therapeutics. To describe the structure-based molecular studies in the rational designing of drugs against amyloid fibrils, we examined various herbal compounds that belong to prenylflavonoids. The present study characterizes the trends we identified at molecular docking studies and dynamics simulation where we observed stronger binding orientation of bavachalcone, bavachin, and neobavaisoflavone with the amyloid-beta (Aβ42) fibril structure. Hence, we could postulate that these herbal compounds could be potential inhibitors of Aβ42 fibrils; these anti-aggregation agents need to be considered in treating AD.

Screening of natural compounds against SOD1 as a therapeutic target for Amyotrophic lateral sclerosis

Background:

Amyotrophic lateral sclerosis (ALS) is an uncommon and progressive neurological illness that predominantly includes the neurons liable for voluntary muscular activities. Starting from weakness or stiffness in muscles, this gradually exploits the strength and ability to speak, eat, move and even breathe. Its exact mechanism is still not clear, but mutations in the SOD1 gene have been reported to cause ALS, and some studies also found involvement of SOD1 overexpression in the pathogenesis of ALS. As of now, there is no remedy available for its cure.

Objective:

To identify the potential inhibitors for wild type 1HL5, l113T mutant, and A4V mutant of SOD1 (Superoxide Dismutase 1) protein. Methods: In this study, in silico approaches like virtual screening, molecular docking, pharmacokinetic parameters study, and molecular dynamics simulation were used to identify the best potential inhibitors against wild type and mutant SOD1 protein.

Methods:

In this study, in silico approaches like virtual screening, molecular docking, pharmacokinetic parameters study, and molecular dynamics simulation were used to identify the best potential inhibitors against wild type and mutant SOD1 protein.

Results:

On the basis of binding affinity and binding energy, the top three compounds ZINC000095486263, ZINC000095485989, and ZINC000028462577, were observed as the best compounds. In the case of 1HL5, ZINC000095486263 had the highest binding affinity with docking score -10.62 Kcal/mol, 1UXM with ZINC000095485989 had the highest docking score -12.03 Kcal/mol, and 4A7V with ZINC000028462577 was found -11.72 Kcal/mol. Further, Molecular Dynamic simulations (MDS) results showed that the ZINC000095486263, ZINC000095485989, and ZINC000095485956 compounds were formed a stable complex with 1HL5, 1UXM, and 4A7V, respectively

Conclusions:

: After analyzing the results, we hereby conclude that naturals compounds such as ZINC000095486263, ZINC000095485989, and ZINC000095485956 could be used as a potential inhibitor of 1HL5, 1UXM, and 4A7V, respectively, for ALS treatment and could be used as a drug. Further, In vivo/vitro study of these compounds could be a future direction in the field of drug discovery.

Alpha-Synuclein Aggregation in Parkinson's Disease

Parkinson's disease (PD), a neurodegenerative disorder characterized by distinct aging-independent loss of dopaminergic neurons in substantia nigra pars compacta (SNpc) region urging toward neuronal loss. Over the decade, various key findings from clinical perspective to molecular pathogenesis have aided in understanding the genetics with assorted genes related with PD. Subsequently, several pathways have been incriminated in the pathogenesis of PD, involving mitochondrial dysfunction, protein aggregation, and misfolding. On the other hand, the sporadic form of PD cases is found with no genetic linkage, which still remain an unanswered question? The exertion in ascertaining vulnerability factors in PD considering the genetic factors are to be further dissevered in the forthcoming decades with advancement in research studies. One of the major proponents behind the prognosis of PD is the pathogenic transmutation of aberrant alpha-synuclein protein into amyloid fibrillar structures, which actuates neurodegeneration. Alpha-synuclein, transcribed by SNCA gene is a neuroprotein found predominantly in brain. It is implicated in the modulation of synaptic vesicle transport and eventual release of neurotransmitters. Due to genetic mutations and other elusive factors, the alpha-synuclein misfolds into its amyloid form. Therefore, this review aims in briefing the molecular understanding of the alpha-synuclein associated with PD.

Mollusc-Derived Brominated Indoles for the Selective Inhibition of Cyclooxygenase: A Computational Expedition

Inflammation plays an important role in different chronic diseases. Brominated indoles derived from the Australian marine mollusk Dicathais orbita (D. orbita) are of interest for their anti-inflammatory properties. This study evaluates the binding mechanism and potentiality of several brominated indoles (tyrindoxyl sulfate, tyrindoleninone, 6-bromoisatin, and 6,6′-dibromoindirubin) against inflammatory mediators cyclooxygenases-1/2 (COX-1/2) using molecular docking, followed by molecular dynamics simulation, along with physicochemical, drug-likeness, pharmacokinetic (pk), and toxicokinetic (tk) properties. Molecular docking identified that these indole compounds are anchored, with the main amino acid residues, positioned in the binding pocket of the COX-1/2, required for selective inhibition. Moreover, the molecular dynamics simulation based on root mean square deviation (RMSD), radius of gyration (Rg), solvent accessible surface area (SASA), and root mean square fluctuation (RMSF) analyses showed that these natural brominated molecules transit rapidly to a progressive constant configuration during binding with COX-1/2 and seem to accomplish a consistent dynamic behavior by maintaining conformational stability and compactness. The results were comparable to the Food and Drug Administration (FDA)-approved selective COX inhibitor, aspirin. Furthermore, the free energy of binding for the compounds assessed by molecular mechanics–Poisson–Boltzmann surface area (MM–PBSA) confirmed the binding capacity of indoles towards COX-1/2, with suitable binding energy values except for the polar precursor tyrindoxyl sulfate (with COX-1). The physicochemical and drug-likeness analysis showed zero violations of Lipinski’s rule, and the compounds are predicted to have excellent pharmacokinetic profiles. These indoles are projected to be non-mutagenic and free from hepatotoxicity, with no inhibition of human ether-a-go–go gene (hERG) I inhibitors, and the oral acute toxicity LD₅₀ in rats is predicted to be similar or lower than aspirin. Overall, this work has identified a plausible mechanism for selective COX inhibition by natural marine indoles as potential therapeutic candidates for the mitigation of inflammation.

Molecular simulation probes the potency of resveratrol in regulating the toxic aggregation of mutant V30M TTR fibrils in Transthyretin mediated amyloidosis

Transthyretin (TTR) mediated amyloidosis is a highly ruinous illness that affects various organs by aggravating the deposition of misfolded or mutated TTR protein aggregates in tissues. Hence, hindering the formation of TTR amyloid aggregates could be a key strategy in finding an effective cure towards the aggravating disorder. In this analysis, we examined the subversive nature of point mutation, V30M, in TTR that promotes amyloidogenicity using discrete molecular dynamics (DMD) simulations. Besides, we probed the association of naturally occurring polyphenols: EGCG (a proven anti TTR aggregation agent as positive control), resveratrol and curcumin in mitigating the pathogenic repercussions of mutant TTR. Results from the computational studies endorsed that the resveratrol constitutes a restorative potential to subjugate TTR mediated amyloidosis, besides EGCG. Hence, this study could be a reminiscent aspect in understanding the inhibitory role of key polyphenols against the mutant TTR aggregates, which could be an aid towards structure-based drug design in the upcoming research era on familial amyloid disorders.

Computer analysis of the relation between hydrogen bond stability in SOD1 mutants and the survival time of amyotrophic lateral sclerosis patients

BACKGROUND AND OBJECTIVE

Mutations in the SOD1 protein can lead to the death of motor neurons, which, in turn, causes an incurable disease called amyotrophic lateral sclerosis (ALS). At the same time, the mechanism of the onset and development of this disease is not fully understood and is often contradictory.

METHODS

Accelerated Molecular Dynamics as implemented in the OpenMM library, principal component analysis, regression analysis, random forest method.

RESULTS

The stability of hydrogen bonds in 72 mutants of the SOD1 protein was calculated. Principal component analysis was carried out. Based on ten principal components acting as predictors, a multiple linear regression model was constructed. An analysis of the correlation of these ten principal components with the initial values of the stability of hydrogen bonds made it possible to characterize the contribution of known structurally and functionally important sites in the SOD1 to the scatter of ALS patients' survival time.

CONCLUSION

Such an analysis made it possible to put forward hypotheses about the relationship between the stabilizing and destabilizing effects of mutations in different structurally and functionally important regions of SOD1 with the patients's survival time.

Antiviral peptides against the main protease of SARS-CoV-2: A molecular docking and dynamics study

The recent coronavirus outbreak has changed the world's economy and health sectors due to the high mortality and transmission rates. Because the development of new effective vaccines or treatments against the virus can take time, an urgent need exists for the rapid development and design of new drug candidates to combat this pathogen. Here, we obtained antiviral peptides obtained from the data repository of antimicrobial peptides (DRAMP) and screened their predicted tertiary structures for the ability to inhibit the main protease of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using multiple combinatorial docking programs, including PatchDock, FireDock, and ClusPro. The four best peptides, DRAMP00877, DRAMP02333, DRAMP02669, and DRAMP03804, had binding energies of -1125.3, -1084.5, -1005.2, and -924.2 Kcal/mol, respectively, as determined using ClusPro, and binding energies of -55.37, -50.96, -49.25, -54.81 Kcal/mol, respectively, as determined using FireDock, which were better binding energy values than observed for other peptide molecules. These peptides were found to bind with the active cavity of the SARS-CoV-2 main protease; at Glu166, Cys145, Asn142, Phe140, and Met165, in addition to the substrate-binding sites, Domain 2 and Domain 3, whereas fewer interactions were observed with Domain 1. The docking studies were further confirmed by a molecular dynamics simulation study, in which several descriptors, including the root-mean-square difference (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), radius of gyration (Rg), and hydrogen bond formation, confirmed the stable nature of the peptide-main protease complexes. Toxicity and allergenicity studies confirmed the non-allergenic nature of the peptides. This present study suggests that these identified antiviral peptide molecules might inhibit the main protease of SARS-CoV-2, although further wet-lab experiments remain necessary to verify these findings.

Molecular docking and dynamics study to explore phytochemical ligand molecules against the main protease of SARS-CoV-2 from extensive phytochemical datasets

BACKGROUND

The high transmission and pathogenicity of SARS-CoV-2 has led to a pandemic that has halted the world's economy and health. The newly evolved strains and scarcity of vaccines has worsened the situation. The main protease (M^pro) of SARS-CoV-2 can act as a potential target due to its role in viral replication and conservation level.

METHODS

In this study, we have enlisted more than 1100 phytochemicals from Asian plants based on deep literature mining. The compounds library was screened against the M^pro of SARS-CoV-2.

RESULTS

The selected three ligands, Flemichin, Delta-Oleanolic acid, and Emodin 1-O-beta-D-glucoside had a binding energy of -8.9, -8.9, -8.7 KJ/mol respectively. The compounds bind to the active groove of the main protease at; Cys145, Glu166, His41, Met49, Pro168, Met165, Gln189. The multiple descriptors from the simulation study; root mean square deviation, root mean square fluctuation, radius of gyration, hydrogen bond, solvent accessible surface area confirms the stable nature of the protein-ligand complexes. Furthermore, post-md analysis confirms the rigidness in the docked poses over the simulation trajectories.

CONCLUSIONS

Our combinatorial drug design approaches may help researchers to identify suitable drug candidates against SARS-CoV-2.

Advances in Applying Computer-Aided Drug Design for Neurodegenerative Diseases

Neurodegenerative diseases (NDs) including Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease are incurable and affect millions of people worldwide. The development of treatments for this unmet clinical need is a major global research challenge. Computer-aided drug design (CADD) methods minimize the huge number of ligands that could be screened in biological assays, reducing the cost, time, and effort required to develop new drugs. In this review, we provide an introduction to CADD and examine the progress in applying CADD and other molecular docking studies to NDs. We provide an updated overview of potential therapeutic targets for various NDs and discuss some of the advantages and disadvantages of these tools.

Amyloid Oligomers: A Joint Experimental/Computational Perspective on Alzheimer's Disease, Parkinson's Disease, Type II Diabetes, and Amyotrophic Lateral Sclerosis

Protein misfolding and aggregation is observed in many amyloidogenic diseases affecting either the central nervous system or a variety of peripheral tissues. Structural and dynamic characterization of all species along the pathways from monomers to fibrils is challenging by experimental and computational means because they involve intrinsically disordered proteins in most diseases. Yet understanding how amyloid species become toxic is the challenge in developing a treatment for these diseases. Here we review what computer, in vitro, in vivo, and pharmacological experiments tell us about the accumulation and deposition of the oligomers of the (Aβ, tau), α-synuclein, IAPP, and superoxide dismutase 1 proteins, which have been the mainstream concept underlying Alzheimer's disease (AD), Parkinson's disease (PD), type II diabetes (T2D), and amyotrophic lateral sclerosis (ALS) research, respectively, for many years.

Whole proteome screening and identification of potential epitopes of SARS-CoV-2 for vaccine design-an immunoinformatic, molecular docking and molecular dynamics simulation accelerated robust strategy

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the most cryptic pandemic outbreak of the 21st century, has gripped more than 1.8 million people to death and infected almost eighty six million. As it is a new variant of SARS, there is no approved drug or vaccine available against this virus. This study aims to predict some promising cytotoxic T lymphocyte epitopes in the SARS-CoV-2 proteome utilizing immunoinformatic approaches. Firstly, we identified 21 epitopes from 7 different proteins of SARS-CoV-2 inducing immune response and checked for allergenicity and conservancy. Based on these factors, we selected the top three epitopes, namely KAYNVTQAF, ATSRTLSYY, and LTALRLCAY showing functional interactions with the maximum number of MHC alleles and no allergenicity. Secondly, the 3D model of selected epitopes and HLA-A*29:02 were built and Molecular Docking simulation was performed. Most interestingly, the best two epitopes predicted by docking are part of two different structural proteins of SARS-CoV-2, namely Membrane Glycoprotein (ATSRTLSYY) and Nucleocapsid Phosphoprotein (KAYNVTQAF), which are generally target of choice for vaccine designing. Upon Molecular Docking, interactions between selected epitopes and HLA-A*29:02 were further validated by 50 ns Molecular Dynamics (MD) simulation. Analysis of RMSD, Rg, SASA, number of hydrogen bonds, RMSF, MM-PBSA, PCA, and DCCM from MD suggested that ATSRTLSYY is the most stable and promising epitope than KAYNVTQAF epitope. Moreover, we also identified B-cell epitopes for each of the antigenic proteins of SARS CoV-2. Findings of our work will be a good resource for wet lab experiments and will lessen the timeline for vaccine construction.Communicated by Ramaswamy H. Sarma.

Structural and Dynamic Characterizations Highlight the Deleterious Role of SULT1A1 R213H Polymorphism in Substrate Binding

Sulfotransferase 1A1 (SULT1A1) is responsible for catalyzing various types of endogenous and exogenous compounds. Accumulating data indicates that the polymorphism rs9282861 (R213H) is responsible for inefficient enzymatic activity and associated with cancer progression. To characterize the detailed functional consequences of this mutation behind the loss-of-function of SULT1A1, the present study deployed molecular dynamics simulation to get insights into changes in the conformation and binding energy. The dynamics scenario of SULT1A1 in both wild and mutated types as well as with and without ligand showed that R213H induced local conformational changes, especially in the substrate-binding loop rather than impairing overall stability of the protein structure. The higher conformational changes were observed in the loop3 (residues, 235-263), turning loop conformation to A-helix and B-bridge, which ultimately disrupted the plasticity of the active site. This alteration reduced the binding site volume and hydrophobicity to decrease the binding affinity of the enzyme to substrates, which was highlighted by the MM-PBSA binding energy analysis. These findings highlight the key insights of structural consequences caused by R213H mutation, which would enrich the understanding regarding the role of SULT1A1 mutation in cancer development and also xenobiotics management to individuals in the different treatment stages.

Exploring the potent inhibitors and binding modes of phospholipase A2 through in silico investigation

Snake venom of Naja naja comprises of several types of enzymes, and among them, water-soluble proteolytic enzyme, phospholipase A2 (PLA₂), is noteworthy for its numerous adverse effects, such as cytotoxicity, cardiotoxicity, hemolytic, anti-coagulant, and hypotensive effects, including being highly potent as a neurotoxin. Limited anti-venom therapy (with their lower efficacy) has attracted considerable pharmacological interest to develop potent inhibitors of PLA₂. Thus, 34 experimentally proven and diverse synthetic inhibitors of PLA₂ were screened primarily on the basis of Glide extra precision docking and MM-GBSA rescoring function. Then, ten potential hits were subjected to induced fit docking, in which top three potential inhibitors were considered, and those were found to interact with Ca²⁺, disulfide binding site, and phosphatidylcholine activation sites, thereby, possibly disrupting the catalytic activity of Ca²⁺ as well as the inflammatory functions of PLA₂. These compounds showed positive remarks on various physiochemical properties and pharmacologically relevant descriptors. Gap energy and thermodynamic properties were investigated by employing density functional theory for all compounds to understand their chemical reactivity and thermodynamic stability. Molecular dynamics simulation was performed for 100 ns in order to evaluate the stability and binding modes of docked complexes, and the energy of binding was calculated through MM-PBSA analysis. On the whole, the proposed compounds could be used for targeted inhibition. Communicated by Ramaswamy H. Sarma.

Rational design of linear tripeptides against the aggregation of human mutant SOD1 protein causing amyotrophic lateral sclerosis

Formation of protein aggregation is considered a hallmark feature of various neurological diseases. Amyotrophic lateral sclerosis is one such devastating neurodegenerative disorder characterized by mutation in Cu/Zn superoxide dismutase protein (SOD1). In our study, we contemplated the most aggregated and pathogenic mutant A4V in a viewpoint of finding a therapeutic regime by inhibiting the formation of the aggregates with the aid of tripeptides since new perspectives in the field of drug design in the current era are being focused on peptide-based drugs. Reports from the experimental study have stipulated that the SOD1 derived peptide, "LSGDHCIIGRTLVVHEKADD" was found to have the inhibitory activity against aggregated SOD1 protein. Moreover, it was determined that the hexapeptide, "LSGDHC" was the key factor in inhibiting the aggregates of SOD1. Accordingly, we utilized the computerized algorithms and programs on determining the binding efficiency and inhibitory activity of hexapeptide on mutant SOD1. Following that, we incorporated a cutting-edge methodology with the use of molecular docking, affinity predictions, alanine scanning, steered molecular dynamics (SMD) and discrete molecular dynamics (DMD) in designing the de novo tripeptides, which could act against the aggregated mutant SOD1 protein. Upon examining the results from the various conformational studies, we identified that CGH had an enhanced binding affinity and inhibitory activity against the aggregated mutant SOD1 protein than other tripeptides and hexapeptide. Thus, our study could be a lead for state-of-the-art design in peptide-based drugs for doctoring the cureless ALS disorder.

SOD1 in amyotrophic lateral sclerosis development - in silico analysis and molecular dynamics of A4F and A4V variants

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that is characterized by the selective loss of motor neurons. Approximately 5% to 10% of patients with ALS have a family history of the disease, and approximately 20% of familial amyotrophic lateral sclerosis (fALS) cases are associated with mutations in Cu/Zn superoxide dismutase (SOD1). In this study, we evaluated the structural and functional effects of human A4F and A4V SOD1 protein mutations. We performed an in silico analysis using prediction algorithms of nonsynonymous single-nucleotide polymorphisms (nsSNPs) associated with the fALS development. Our structural conservation results show that the mutations analyzed (A4V and A4F) were in a highly conserved region. Molecular dynamics simulations using the Linux GROMACS package revealed how these mutations affect protein structure, protein stability, and aggregation. These results suggest that there might be an effect on the SOD1 function. Understanding the molecular basis of disease provides new insights useful for rational drug design and advancing our understanding of the ALS development.

Structure-based identification of potent VEGFR-2 inhibitors from in vivo metabolites of a herbal ingredient

Vascular endothelial growth factor receptor-2 (VEGFR-2) is one of the regulatory elements of angiogenesis that is expressed highly in various diseases and is also essential for solid tumor growth. The present study was aimed at identifying potent inhibitors of VEGFR-2 by considering herbal secondary metabolites; as natural molecules are less toxic than synthetic derivatives. A structure-based virtual screening protocol consisting of molecular docking, MM-GBSA and ADME/T analysis was initially used to screen a library of in vivo metabolites of the herbal ingredient. Using a fixed cutoff value, four potent virtual hits were identified from molecular docking, ADME/T and binding affinity calculations, which were considered further for molecular dynamics (MD) simulation to broadly describe the binding mechanisms to VEGFR-2. The results suggested that these molecules have high affinity for the catalytic region of VEGFR-2, and form strong hydrophobic and polar interactions with the amino acids involved in the binding site of ATP and linker regions of the catalytic site. Subsequently, the stability of the docked complexes and binding mechanisms were evaluated by MD simulations, and the energy of binding was calculated through MM-PBSA analysis. The results uncovered two virtual hits, designated ZINC14762520 and ZINC36470466, as VEGFR-2 inhibitors, and suggested that they bind to kinase domain in an ATP-competitive manner. These virtual hits will offer a suitable starting point for the further design of their various analogs, allowing a rational search for more effective inhibitors in the future. Graphical abstract.

Computational Investigation on Electrostatic Loop Mutants Instigating Destabilization and Aggregation on Human SOD1 Protein Causing Amyotrophic Lateral Sclerosis

Mutations in the gene encoding Cu/Zn Superoxide Dismutase 1 (SOD1) protein are contemplated to be a protruding reason for Amyotrophic lateral sclerosis (ALS), which leads towards protein aggregation, misfolding and destabilization. Thus, we investigated the systematic action of entire mutations reported on electrostatic loop of SOD1 protein through thermodynamical and discrete molecular dynamics (DMD) studies. Accordingly, we analyzed the outcomes distinctly for screening the mutant structures having both, deleterious and destabilizing effect. Progressively, the impacts of those mutations on SOD1 were studied using DMD program. Surprisingly, our results predicted that the mutants viz., L126S, N139H and G141A to be the most destabilizing, misfolded and disease-causing compared to other mutants. Besides, the outcomes from secondary structural propensities and free energy landscapes, together assertively suggested that L126S, N139H and G141A tend to increase the formation of aggregates in SOD1 relative to other mutants. Hence, this study could provide an insight into the sprouting neurodegenerative disorder distressing the humans.

Molecular binding response of naringin and naringenin to H46R mutant SOD1 protein in combating protein aggregation using density functional theory and discrete molecular dynamics

Amyotrophic lateral sclerosis (ALS) is a calamitous neurodegenerative disorder characterized by denervation of upper and lower motor neurons. Numerous hypotheses suggest that toxic protein misfolding and aggregation cause ALS, similar to that of other neurodegenerative diseases, such as Alzheimers and Parkinsons. Protruding causes of familial ALS are mutations in the gene encoding Cu/Zn superoxide dismutase-1 (SOD1), which decrease protein stability and endorse protein aggregation. Thus, the interference concerning aggregate formation and destabilization in SOD1 is considered to be an impending therapeutic strategy. In this work, we utilized computational chemistry methods to initially study the effect of substitution mutation, His46Arg on SOD1 protein. Further, we described the interaction of two naturally occurring polyphenol compounds, naringin and naringenin with mutant SOD1 that is regarded to hinder the protein aggregation. Subsequently, the use of quantum chemical and molecular mechanics calculations speculated that naringin had a strong binding affinity with mutant SOD1 and impeded the formation of toxic aggregates than that of naringenin. Ultimately, we could conjecture that ingesting of polyphenol-rich foods in ALS patients may be regarded to improvise their living. Moreover, the findings from our study could pave a way in the field of structure-based drug design in developing potential anti-aggregation inhibitors against incurable ALS, affecting the human population.

Improved regression model to predict an impact of SOD1 mutations on ALS patients survival time based on analysis of hydrogen bond stability

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease characterised by the inevitable degeneration of central and peripheral motor neurons. Aggregation of mutant SOD1 is one of the molecular mechanisms underlying the onset of the disease. There are a number of regression models designed to predict the survival of patients based on an analysis of experimental data on thermostability, heterodimerisation energy, and changes in the hydrophobicity of SOD1 mutants. Previously, we proposed regression models linking the change in the stability of hydrogen bonds in mutant SOD1 calculated using molecular dynamics and elastic networks with patients survival time. In this study, these models were improved in terms of accuracy of survival time prediction by taking into account the variance of survival time values relative to the mean, the number of patients carrying each specific mutation, and the use of random forest regression as a regression method. The accuracy of the previous models was roughly 5.2 years while the accuracy of the new ones are up to 4 years. The model is also superior to those published by other authors. It was found that the hydrogen bonds important for prediction of survival time are formed by residues at positions located in the regions of the protein responsible for aggregation as well as in structural and functionally important sites.

Comparative binding of kaempferol and kaempferide on inhibiting the aggregate formation of mutant (G85R) SOD1 protein in familial amyotrophic lateral sclerosis: A quantum chemical and molecular mechanics study

Mutation in Cu/Zn superoxide dismutase (SOD1) at position 85 from glycine to arginine was found to be a prominent cause of aggregation characterized by an increased content of β-sheets in familial amyotrophic lateral sclerosis (fALS). Various literatures reported that natural polyphenols could act as a β-sheet breaker and therefore, treated as a potential therapeutics against various aggregated proteins involved in neurodegenerative disorders. Through computational perspective, molecular docking, quantum chemical studies, and discrete molecular dynamics were implemented to study the binding and structural effect of natural polyphenols, kaempferol, and kaempferide on mutant SOD1. Kaempferol exhibited significant binding and greater residual energy contribution with mutant SOD1 than kaempferide. More interestingly, kaempferol was found to reduce the β-sheet content augmenting the mutant conformational stability and flexibility relative to that of kaempferide. Hence, the inhibition of mutant SOD1 aggregation by kaempferol was explored, thereby suggesting kaempferol could act as a drug candidate for the design of the natural therapeutics against fALS. © 2018 BioFactors, 44(5):431-442, 2018.

Structural distortions due to missense mutations in human formylglycine-generating enzyme leading to multiple sulfatase deficiency

The major candidate for multiple sulfatase deficiency is a defective formylglycine-generating enzyme (FGE). Though adequately produced, mutations in FGE stall the activation of sulfatases and prevent their activity. Missense mutations, viz. E130D, S155P, A177P, W179S, C218Y, R224W, N259I, P266L, A279V, C336R, R345C, A348P, R349Q and R349W associated with multiple sulfatase deficiency are yet to be computationally studied. Aforementioned mutants were initially screened through ws-SNPs&GO^3D program. Mutant R345C acquired the highest score, and hence was studied in detail. Discrete molecular dynamics explored structural distortions due to amino acid substitution. Therein, comparative analyses of wild type and mutant were carried out. Changes in structural contours were observed between wild type and mutant. Mutant had low conformational fluctuation, high atomic mobility and more compactness than wild type. Moreover, free energy landscape showed mutant to vary in terms of its conformational space as compared to wild type. Subsequently, wild type and mutant were subjected to single-model analyses. Mutant had lesser intra molecular interactions than wild type suggesting variations pertaining to its secondary structure. Furthermore, simulated thermal denaturation showed dissimilar pattern of hydrogen bond dilution. Effects of these variations were observed as changes in elements of secondary structure. Docking studies of mutant revealed less favourable binding energy towards its substrate as compared to wild type. Therefore, theoretical explanations for structural distortions of mutant R345C leading to multiple sulfatase deficiency were revealed. The protocol of the study could be useful to examine the effectiveness of pharmacological chaperones prior to experimental studies.

Cysteine to Serine Conversion at 111th Position Renders the Disaggregation and Retains the Stabilization of Detrimental SOD1 A4V Mutant Against Amyotrophic Lateral Sclerosis in Human-A Discrete Molecular Dynamics Study

Protein aggregation is a hallmark of various neurodegenerative disorders, such as amyotrophic lateral sclerosis (ALS) in humans. Mutations in Cu/Zn superoxide dismutase (SOD1) protein were found to be a prominent cause behind the majority of the familial ALS cases with abnormal protein aggregates. Herein, we report the biophysical characterization of the beneficial mutation C111S that stabilizes the SOD1 harboring A4V mutation, one of the most lethal diseases causing mutant that leads to protein destabilization and aggregation. In this study, we utilized discrete molecular dynamics (DMD) simulations, which stipulated an outlook over the systematic action of C111S mutation in the A4V mutant that stabilizes the protein and impedes the formation of protein aggregation. Herewith, the findings from our study manifested that the mutation of C111S in SOD1 could aid in regaining the protein structural conformations that protect against the formation of toxic aggregates, thereby hindering the disease pathogenicity subtly. Hence, our study provides a feasible pharmaceutical strategy in developing the treatment for incurable ALS affecting the mankind.