Structural dynamics and quantum mechanical aspects of shikonin derivatives as CREBBP bromodomain inhibitors

Research progress in mechanism of anticancer action of shikonin targeting reactive oxygen species

Excessive buildup of highly reactive molecules can occur due to the generation and dysregulation of reactive oxygen species (ROS) and their associated signaling pathways. ROS have a dual function in cancer development, either leading to DNA mutations that promote the growth and dissemination of cancer cells, or triggering the death of cancer cells. Cancer cells strategically balance their fate by modulating ROS levels, activating pro-cancer signaling pathways, and suppressing antioxidant defenses. Consequently, targeting ROS has emerged as a promising strategy in cancer therapy. Shikonin and its derivatives, along with related drug carriers, can impact several signaling pathways by targeting components involved with oxidative stress to induce processes such as apoptosis, necroptosis, cell cycle arrest, autophagy, as well as modulation of ferroptosis. Moreover, they can increase the responsiveness of drug-resistant cells to chemotherapy drugs, based on the specific characteristics of ROS, as well as the kind and stage of cancer. This research explores the pro-cancer and anti-cancer impacts of ROS, summarize the mechanisms and research achievements of shikonin-targeted ROS in anti-cancer effects and provide suggestions for designing further anti-tumor experiments and undertaking further experimental and practical research.

Network pharmacology reveals the potential of Dolastatin 16 as a diabetic wound healing agent

Dolastatin 16, a marine cyclic depsipeptide, was initially isolated from the sea hare Dolabella Auricularia by Pettit et al. Due to the lack of information regarding its bioactivity, target identification becomes an indispensable strategy for revealing the potential targets and mechanisms of action of Dolastatin 16. Network pharmacology was utilized to identify targets associated with the disease, gene ontology, and KEGG pathways. The results highlighted Matrix Metalloproteinase-9 (MMP9) as a potential target of Dolastatin 16 through network pharmacology analysis. This target was found to be primarily involved in the TNF signaling pathway and in foot ulceration-associated diabetic polyneuropathy. Furthermore, the binding mode and dynamic behavior of the complex were investigated through molecular docking and molecular dynamics studies. In the docking study, a native ligand (a hydroxamate inhibitor) and (R)-ND-336 were employed as ligand controls, demonstrating binding energy values of - 6.6 and - 8.9 kcal/mol, respectively. The Dolastatin 16 complex exhibited a strong affinity for MMP9, with a binding energy value of - 9.7 kcal/mol, indicating its high potential as an inhibitor. Molecular dynamics also confirmed the stability of the MMP9-Dolastatin complex throughout the simulation process. Dolastatin 16 has the potential to act as an MMP9 inhibitor, offering promise for accelerating the wound healing process in diabetic foot conditions.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00161-5.

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.

Exploring Core Genes by Comparative Transcriptomics Analysis for Early Diagnosis, Prognosis, and Therapies of Colorectal Cancer

Colorectal cancer (CRC) is one of the most common cancers with a high mortality rate. Early diagnosis and therapies for CRC may reduce the mortality rate. However, so far, no researchers have yet investigated core genes (CGs) rigorously for early diagnosis, prognosis, and therapies of CRC. Therefore, an attempt was made in this study to explore CRC-related CGs for early diagnosis, prognosis, and therapies. At first, we identified 252 common differentially expressed genes (cDEGs) between CRC and control samples based on three gene-expression datasets. Then, we identified ten cDEGs (AURKA, TOP2A, CDK1, PTTG1, CDKN3, CDC20, MAD2L1, CKS2, MELK, and TPX2) as the CGs, highlighting their mechanisms in CRC progression. The enrichment analysis of CGs with GO terms and KEGG pathways revealed some crucial biological processes, molecular functions, and signaling pathways that are associated with CRC progression. The survival probability curves and box-plot analyses with the expressions of CGs in different stages of CRC indicated their strong prognostic performance from the earlier stage of the disease. Then, we detected CGs-guided seven candidate drugs (Manzamine A, Cardidigin, Staurosporine, Sitosterol, Benzo[a]pyrene, Nocardiopsis sp., and Riccardin D) by molecular docking. Finally, the binding stability of four top-ranked complexes (TPX2 vs. Manzamine A, CDC20 vs. Cardidigin, MELK vs. Staurosporine, and CDK1 vs. Riccardin D) was investigated by using 100 ns molecular dynamics simulation studies, and their stable performance was observed. Therefore, the output of this study may play a vital role in developing a proper treatment plan at the earlier stages of CRC.

Robust identification of common genomic biomarkers from multiple gene expression profiles for the prognosis, diagnosis, and therapies of pancreatic cancer

Pancreatic cancer (PC) is one of the leading causes of cancer-related death globally. So, identification of potential molecular signatures is required for diagnosis, prognosis, and therapies of PC. In this study, we detected 71 common differentially expressed genes (cDEGs) between PC and control samples from four microarray gene-expression datasets (GSE15471, GSE16515, GSE71989, and GSE22780) by using robust statistical and machine learning approaches, since microarray gene-expression datasets are often contaminated by outliers due to several steps involved in the data generating processes. Then we detected 8 cDEGs (ADAM10, COL1A2, FN1, P4HB, ITGB1, ITGB5, ANXA2, and MYOF) as the PC-causing key genes (KGs) by the protein-protein interaction (PPI) network analysis. We validated the expression patterns of KGs between case and control samples by box plot analysis with the TCGA and GTEx databases. The proposed KGs showed high prognostic power with the random forest (RF) based prediction model and Kaplan-Meier-based survival probability curve. The KGs regulatory network analysis detected few transcriptional and post-transcriptional regulators for KGs. The cDEGs-set enrichment analysis revealed some crucial PC-causing molecular functions, biological processes, cellular components, and pathways that are associated with KGs. Finally, we suggested KGs-guided five repurposable drug molecules (Linsitinib, CX5461, Irinotecan, Timosaponin AIII, and Olaparib) and a new molecule (NVP-BHG712) against PC by molecular docking. The stability of the top three protein-ligand complexes was confirmed by molecular dynamic (MD) simulation studies. The cross-validation and some literature reviews also supported our findings. Therefore, the finding of this study might be useful resources to the researchers and medical doctors for diagnosis, prognosis and therapies of PC by the wet-lab validation.

In silico design of epitope-based peptide vaccine against non-typhoidal Salmonella through immunoinformatic approaches

Non-typhoidal Salmonella (NTS) is one of the leading bacterial causes of many invasive human infections with a high antibiotic resistance profile. With this concern, the current study aimed to design an effective epitope-based peptide vaccine against NTS species as a successive and substitutive protective measure of invasive NTS disease. To design rationally, the current study considered a comprehensive in silico workflow combination of both immunoinformatics and molecular modeling approaches, including molecular docking and molecular dynamics (MD) simulation. We identified the two most promising T cell epitopes KVLYGIFAI and YGIFAITAL, and three B cell epitopes AAPVQVGEAAGS, TGGGDGSNT, and TGGGDGSNTGTTTT, in the outer membrane of NTS. Using these epitopes, a multiepitope vaccine was subsequently constructed along with appropriate adjuvant and linkers, which showed a good binding affinity and stability with toll-like receptor 2 (TLR2) in both molecular docking and MD simulation. Furthermore, in silico immune simulation described a strong immune response with a high number of antibodies, interferon-γ, and activated B and T cells. This study collectively suggests that predicted vaccine constructs could be considered potential vaccine candidates against common NTS species.Communicated by Ramaswamy H. Sarma.

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.

Dynamic insights into the effects of nonsynonymous polymorphisms (nsSNPs) on loss of TREM2 function

Single nucleotide variations in Triggering Receptor Expressed on Myeloid Cells 2 (TREM2) are associated with many neurodegenerative diseases, including Nasu-Hakola disease (NHD), frontotemporal dementia (FTD), and late-onset Alzheimer's disease because they disrupt ligand binding to the extracellular domain of TREM2. However, the effects of nonsynonymous single nucleotide polymorphisms (nsSNPs) in TREM2 on disease progression remain unknown. In this study, we identified several high-risk nsSNPs in the TREM2 gene using various deleterious SNP predicting algorithms and analyzed their destabilizing effects on the ligand recognizing region of the TREM2 immunoglobulin (Ig) domain by molecular dynamics (MD) simulation. Cumulative prediction by all tools employed suggested the three most deleterious nsSNPs involved in loss of TREM2 function are rs549402254 (W50S), rs749358844 (R52C), and rs1409131974 (D104G). MD simulation showed that these three variants cause substantial structural alterations and conformational remodeling of the apical loops of the TREM2 Ig domain, which is responsible for ligand recognition. Detailed analysis revealed that these variants substantially increased distances between apical loops and induced conformation remodeling by changing inter-loop nonbonded contacts. Moreover, all nsSNPs changed the electrostatic potentials near the putative ligand-interacting region (PLIR), which suggested they might reduce specificity or loss of binding affinity for TREM2 ligands. Overall, this study identifies three potential high-risk nsSNPs in the TREM2 gene. We propose further studies on the molecular mechanisms responsible for loss of TREM2 function and the associations between TREM2 nsSNPs and neurodegenerative diseases.

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.

Phenolic compounds as α-glucosidase inhibitors: a docking and molecular dynamics simulation study

Phenolic compounds possess significant biological activity. Several pieces of research emphasize the medicinal importance of phenolic compounds, including diabetes. The present study investigated the α-glucosidase inhibitory activity of phenolic compounds reported from several plants. The phenolic compounds reported in different literature were collected. Molecular docking was carried out using AutoDock Vina. Various physicochemical properties such as size, LogP, molecular complexity, hydrogen bonding properties of phenolic compounds were correlated with the binding affinities. Furthermore, MD simulation was carried out to study the structural stability of the docking complexes. A total of 155 phenolic compounds were reported from different plants. Amentoflavone showed the strongest binding affinity with α-glucosidase, much more potent than reference acarbose. The binding energy showed a good correlation with the molecular complexity, hydrogen bond donor and acceptor property and heavy atom counts of the compounds. The polarity of the surface area also showed a positive correlation with the binding affinity of the compounds. The best docking phenolic compound, amentoflavone, showed stable binding affinity and conformation during the simulation period compared to apoprotein and acarbose-docking complex. The top ten phenolic compounds, including amentoflavone, showed considerable drug-likeness properties with fewer toxicity effects. The study suggests that the amentoflavone could be a potential therapeutic drug as an α-glucosidase inhibitor and help control postprandial hyperglycemia.Communicated by Ramaswamy H. Sarma.

Structural Consequence of Non-Synonymous Single-Nucleotide Variants in the N-Terminal Domain of LIS1

Disruptive neuronal migration during early brain development causes severe brain malformation. Characterized by mislocalization of cortical neurons, this condition is a result of the loss of function of migration regulating genes. One known neuronal migration disorder is lissencephaly (LIS), which is caused by deletions or mutations of the LIS1 (PAFAH1B1) gene that has been implicated in regulating the microtubule motor protein cytoplasmic dynein. Although this class of diseases has recently received considerable attention, the roles of non-synonymous polymorphisms (nsSNPs) in LIS1 on lissencephaly progression remain elusive. Therefore, the present study employed combined bioinformatics and molecular modeling approach to identify potential damaging nsSNPs in the LIS1 gene and provide atomic insight into their roles in LIS1 loss of function. Using this approach, we identified three high-risk nsSNPs, including rs121434486 (F31S), rs587784254 (W55R), and rs757993270 (W55L) in the LIS1 gene, which are located on the N-terminal domain of LIS1. Molecular dynamics simulation highlighted that all variants decreased helical conformation, increased the intermonomeric distance, and thus disrupted intermonomeric contacts in the LIS1 dimer. Furthermore, the presence of variants also caused a loss of positive electrostatic potential and reduced dimer binding potential. Since self-dimerization is an essential aspect of LIS1 to recruit interacting partners, thus these variants are associated with the loss of LIS1 functions. As a corollary, these findings may further provide critical insights on the roles of LIS1 variants in brain malformation.

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.

Hybrid Quantum Mechanics/Molecular Mechanics (QM/MM) Simulation: A Tool for Structure-based Drug Design and Discovery

Quantum mechanics (QM) is physics based theory which explains the physical properties of nature at the level of atoms and sub-atoms. Molecular mechanics (MM) construct molecular systems through the use of classical mechanics. So, hybrid quantum mechanics and molecular mechanics (QM/MM) when combined together can act as computer-based methods which can be used to calculate structure and property data of molecular structures. Hybrid QM/MM combines the strengths of QM with accuracy and MM with speed. QM/MM simulation can also be applied for the study of chemical process in solutions as well as in the proteins, and has a great scope in structure-based drug design (CADD) and discovery. Hybrid QM/MM also applied to HTS, to derive QSAR models and due to availability of many protein crystal structures; it has a great role in computational chemistry, especially in structure- and fragment-based drug design. Fused QM/MM simulations have been developed as a widespread method to explore chemical reactions in condensed phases. In QM/MM simulations, the quantum chemistry theory is used to treat the space in which the chemical reactions occur; however the rest is defined through molecular mechanics force field (MMFF). In this review, we have extensively reviewed recent literature pertaining to the use and applications of hybrid QM/MM simulations for ligand and structure-based computational methods for the design and discovery of therapeutic agents.

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.

Biofunctionalities of unprocessed and processed flours of Australian lupin cultivars: Antidiabetic and organ protective potential studies

As lupin has emerged popularity as dietary protein and nutritional source, our present research was aimed to demonstrate the antidiabetic and organ-protective activities of nine cultivars of Australian sweet lupin seed flours by means of in vitro and in vivo assays accompanied by identification of their bioactive phytocompounds and exploration of underlying mechanisms of their hypoglycemic activity using in silico approach. In vitro α-amylase and α-glucosidase activities inhibition and glucose uptake assays identified Jenabillup seed flours for exhibiting the most potential antidiabetic activity amongst the nine cultivars. In vivo antidiabetic and major organ-protective activities were investigated on streptozotocin-induced hyperglycemia and organ damages in Wister rat model. Along with attenuating hyperglycemia and retreating major organ damages, the biochemical imbalance in cardiac, hepatic and renal markers were well-balanced by Jenabillup seed flours treatment. These activities of lupin seed flours were insignificantly affected by thermal processing. Moreover, in silico investigation of 106 phytochemicals identified by gas chromatography-mass spectroscopy (GC-MS) analysis of the seed flour extracts of nine cultivars revealed that more than 35% of compounds possess moderate to high binding affinity to α-amylase and α-glucosidase enzymes. These bioactive compounds act synergistically to exert potential hypoglycemic activity. Cross-docking and binding energy calculation by molecular mechanics/generalized Born volume integration (MM/GBVI) model suggest actinomycin C2 as a potential inhibitor of both α-amylase and α-glucosidase enzymes. These findings acclaim that Australian sweet lupin seed flours may be considered not only as functional food, but also for further development of effective drugs in pharmaceuticals in the treatment of diabetes mellitus and resultant organ damages.

Computational Insights into the Deleterious Impacts of Missense Variants on N-Acetyl-d-glucosamine Kinase Structure and Function

An enzyme of the mammalian amino-sugar metabolism pathway, N-acetylglucosamine kinase (NAGK), that synthesizes N-acetylglucosamine (GlcNAc)-6-phosphate, is reported to promote dynein functions during mitosis, axonal and dendritic growth, cell migration, and selective autophagy, which all are unrelated to its enzyme activity. As non-enzymatic structural functions can be altered by genetic variation, we made an effort in this study aimed at deciphering the pathological effect of nonsynonymous single-nucleotide polymorphisms (nsSNPs) in NAGK gene. An integrated computational approach, including molecular dynamics (MD) simulation and protein-protein docking simulation, was used to identify the damaging nsSNPs and their detailed structural and functional consequences. The analysis revealed the four most damaging variants (G11R, G32R, G120E, and A156D), which are highly conserved and functional, positioned in both small (G11R and G32R) and large (G120E and A156D) domains of NAGK. G11R is located in the ATP binding region, while variants present in the large domain (G120E and A156D) were found to induce substantial alterations in the structural organizations of both domains, including the ATP and substrate binding sites. Furthermore, all variants were found to reduce binding energy between NAGK and dynein subunit DYNLRB1, as revealed by protein-protein docking and MM-GBSA binding energy calculation supporting their deleteriousness on non-canonical function. We hope these findings will direct future studies to gain more insight into the role of these variants in the loss of NAGK function and their role in neurodevelopmental disorders.

Cholinesterase inhibitory activity of tinosporide and 8-hydroxytinosporide isolated from Tinospora cordifolia: In vitro and in silico studies targeting management of Alzheimer's disease

Tinosporide and 8-hydroxytinosporide isolated from Tinospora cordifolia were evaluated for acetylcholinesterase (AChE) and butylcholinesterase (BuChE) inhibitory activities. The structure of the compound was confirmed by spectroscopic analysis, whereas cholinesterase inhibition was investigated by Ellman method using donepezil as standard drug and the data were presented as IC₅₀ (μg/ml ± SEM). Furthermore, donepezil, tinosporide and 8-hydroxytinosporide were executed for docking analysis. The results from the isolated compounds TC-16R confirmed as tinosporide promisingly inhibited AChE with IC₅₀ value of 13.45 ± 0.144, whereas TC-19R confirmed as 8-hydroxytinosporide moderately inhibited AChE with IC₅₀ value of 46.71 ± 0.511. In case of BuChE inhibition, the IC₅₀ values were found to be 408.50 ± 17.197 and 317.26 ± 6.918 for tinosporide and 8-hydroxytinosporide, respectively. The in silico studies revealed that the ligand tinosporide fit with the binding sites and inhibited AChE. Overall, the study findings suggested that tinosporide would be a complementary noble molecule of donepezil which is correlated with its pharmacological activity through in vitro studies, while 8-hydroxytinosporide modestly inhibited BuChE and the results are very close to the standard donepezil.

N-Acetyl-D-Glucosamine Kinase Interacts with NudC and Lis1 in Dynein Motor Complex and Promotes Cell Migration

Recently, we showed that N-acetylglucosamine kinase (NAGK), an enzyme of amino sugar metabolism, interacts with dynein light chain roadblock type 1 (DYNLRB1) and promotes the functions of dynein motor. Here, we report that NAGK interacts with nuclear distribution protein C (NudC) and lissencephaly 1 (Lis1) in the dynein complex. Yeast two-hybrid assays, pull-down assays, immunocytochemistry, and proximity ligation assays revealed NAGK-NudC-Lis1-dynein complexes around nuclei, at the leading poles of migrating HEK293T cells, and at the tips of migratory processes of cultured rat neuroblast cells. The exogenous expression of red fluorescent protein (RFP)-tagged NAGK accelerated HEK293T cell migration during in vitro wound-healing assays and of neurons during in vitro neurosphere migration and in utero electroporation assays, whereas NAGK knockdown by short hairpin RNA (shRNA) delayed migration. Finally, a small NAGK peptide derived from the NudC interacting domain in in silico molecular docking analysis retarded the migrations of HEK293T and SH-SY5Y cells. These data indicate a functional interaction between NAGK and dynein-NudC-Lis1 complex at the nuclear envelope is required for the regulation of cell migration.

Molecular simulation studies to reveal the binding mechanisms of shikonin derivatives inhibiting VEGFR-2 kinase

Traditional vascular endothelial growth factor receptor 2 (VEGFR-2) inhibitors can manage angiogenesis; however, severe toxicity and resistance limit their long-term applications in clinical therapy. Shikonin (SHK) and its derivatives could be promising to inhibit the VEGFR-2 mediated angiogenesis, as they are reported to bind in the catalytic kinase domain with low affinity. However, the detailed molecular insights and binding dynamics of these natural inhibitors are unknown, which is crucial for potential SHK based lead design. Therefore, the present study employed molecular modeling and simulations techniques to get insight into the binding behaviors of SHK and its two derivates, β-hydroxyisovalerylshikonin (β-HIVS) and acetylshikonin (ACS). Here the intermolecular interactions between protein and ligands were studied by induced fit docking approach, which were further evaluated by treating QM/MM (quantum mechanics/molecular mechanics) and molecular dynamics (MD) simulation. The result showed that the naphthazarin ring of the SHK derivates is vital for strong binding to the catalytic domain; however, the binding stability can be modulated by the side chain modification. Because of having electrostatic potential, this ring makes essential interactions with the DFG (Asp1046 and Phe1047) motif and also allows interacting with the allosteric binding site. Taken together, the studies will advance our knowledge and scope for the development of new selective VEGFR-2 inhibitors based on SHK and its analogs.

Computational SNP Analysis and Molecular Simulation Revealed the Most Deleterious Missense Variants in the NBD1 Domain of Human ABCA1 Transporter

The ATP-binding cassette transporter A1 (ABCA1) is a membrane-bound exporter protein involved in regulating serum HDL level by exporting cholesterol and phospholipids to load up in lipid-poor ApoA-I and ApoE, which allows the formation of nascent HDL. Mutations in the ABCA1 gene, when presents in both alleles, disrupt the canonical function of ABCA1, which associates with many disorders related to lipid transport. Although many studies have reported the phenotypic effects of a large number of ABCA1 variants, the pathological effect of non-synonymous polymorphisms (nsSNPs) in ABCA1 remains elusive. Therefore, aiming at exploring the structural and functional consequences of nsSNPs in ABCA1, in this study, we employed an integrated computational approach consisting of nine well-known in silico tools to identify damaging SNPs and molecular dynamics (MD) simulation to get insights into the magnitudes of the damaging effects. In silico tools revealed four nsSNPs as being most deleterious, where the two SNPs (G1050V and S1067C) are identified as the highly conserved and functional disrupting mutations located in the NBD1 domain. MD simulation suggested that both SNPs, G1050V and S1067C, changed the overall structural flexibility and dynamics of NBD1, and induced substantial alteration in the structural organization of ATP binding site. Taken together, these findings direct future studies to get more insights into the role of these variants in the loss of the ABCA1 function.

Current development of CBP/p300 inhibitors in the last decade

CBP/p300, functioning as histone acetyltransferases and transcriptional co-factors, represents an attractive target for various diseases, including malignant tumor. The development of small-molecule inhibitors targeting the bromodomain and HAT domains of CBP/p300 has aroused broad interests of medicinal chemist in expectation of providing new hope for anti-cancer treatment. In particular, the CBP/p300 bromodomain inhibitor CCS1477, identified by CellCentric, is currently undergone clinical evaluation for the treatment of haematological malignancies and prostate cancer. In this review, we depict the development of CBP/p300 inhibitors reported from 2010 to 2020 and particularly highlight their structure-activity relationships (SARs), binding modes, selectivity and pharmacological functions with the aim to facilitate rational design and development of CBP/p300 inhibitors.

Molecular Structure, Binding Affinity, and Biological Activity in the Epigenome

Development of valid structure–activity relationships (SARs) is a key to the elucidation of pathomechanisms of epigenetic diseases and the development of efficient, new drugs. The present review is based on selected methodologies and applications supplying molecular structure, binding affinity and biological activity data for the development of new SARs. An emphasis is placed on emerging trends and permanent challenges of new discoveries of SARs in the context of proteins as epigenetic drug targets. The review gives a brief overview and classification of the molecular background of epigenetic changes, and surveys both experimental and theoretical approaches in the field. Besides the results of sophisticated, cutting edge techniques such as cryo-electron microscopy, protein crystallography, and isothermal titration calorimetry, examples of frequently used assays and fast screening techniques are also selected. The review features how different experimental methods and theoretical approaches complement each other and result in valid SARs of the epigenome.

Mechanistic insights into the deleterious roles of Nasu-Hakola disease associated TREM2 variants

Recently, the critical roles played by genetic variants of TREM2 (Triggering Receptor Expressed on Myeloid cells 2) in Alzheimer's disease have been aggressively highlighted. However, few studies have focused on the deleterious roles of Nasu-Hakola disease (NHD) associated TREM2 variants. In order to get insights into the contributions made by these variants to neurodegeneration, we investigated the influences of four NHD associated TREM2 mutations (Y38C, W50C, T66M, and V126G) on loss-of-function, and followed this with in silico prediction and conventional molecular dynamics simulation. NHD mutations were predicted to be highly deleterious by eight different in silico bioinformatics tools and found to induce conformational changes by molecular dynamics simulation. As compared with the wild-type, the four variants produced substantial differences in the collective motions of loop regions, which not only promoted structural remodeling in the CDR2 (complementarity-determining region 2) loop but also in the CDR1 loop, by changing inter- and intra-loop hydrogen bonding networks. In addition, structural studies in a free energy landscape analysis showed that Y38, T66, and V126 are crucial for maintaining the structural features of CDR1 and CDR2 loops, and that mutations in these positions produced steric clashes and loss of ligand binding. These results showed the presence of mutations in the TREM2 ectodomain induced flexibility and caused structural alterations. Dynamical scenarios, as provided by the present study, may be critical to our understanding of the roles of these TREM2 mutations in neurodegenerative diseases.

Unveiling the Structural Insights into the Selective Inhibition of Protein Kinase D1

BACKGROUND

Although protein kinase D1 (PKD1) has been proved to be an efficient target for anticancer drug development, lack of structural details and substrate binding mechanisms are the main obstacles for the development of selective inhibitors with therapeutic benefits.

OBJECTIVE

The present study described the in silico dynamics behaviors of PKD1 in binding with selective and non-selective inhibitors and revealed the critical binding site residues for the selective kinase inhibition.

METHODS

Here, the three dimensional model of PKD1 was initially constructed by homology modeling along with binding site characterization to explore the non-conserved residues. Subsequently, two known inhibitors were docked to the catalytic site and the detailed ligand binding mechanisms and post binding dyanmics were investigated by molecular dynamics simulation and binding free energy calculations.

RESULTS

According to the binding site analysis, PKD1 serves several non-conserved residues in the G-loop, hinge and catalytic subunits. Among them, the residues including Leu662, His663, and Asp665 from hinge region made polar interactions with selective PKD1 inhibitor in docking simulation, which were further validated by the molecular dynamics simulation. Both inhibitors strongly influenced the structural dynamics of PKD1 and their computed binding free energies were in accordance with experimental bioactivity data.

CONCLUSION

The identified non-conserved residues likely to play critical role on molecular reorganization and inhibitor selectivity. Taken together, this study explained the molecular basis of PKD1 specific inhibition, which may help to design new selective inhibitors for better therapies to overcome cancer and PKD1 dysregulated disorders.

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.

Deciphering Molecular Mechanism of the Neuropharmacological Action of Fucosterol through Integrated System Pharmacology and In Silico Analysis

Fucosterol is an algae-derived unique phytosterol having several medicinal properties, including antioxidant, anti-inflammatory, anticholinesterase, neuroprotective, and so on. Accumulated evidence suggests a therapeutic promise of fucosterol in neurodegeneration; however, the in-depth pharmacological mechanism of its neuroprotection is poorly understood. Here, we employed system pharmacology and in silico analysis to elucidate the underlying mechanism of neuropharmacological action of fucosterol against neurodegenerative disorders (NDD). Network pharmacology revealed that fucosterol targets signaling molecules, receptors, enzymes, transporters, transcription factors, cytoskeletal, and various other proteins of cellular pathways, including tumor necrosis factor (TNF), mitogen-activated protein kinase (MAPK), phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt), neurotrophin, and toll-like receptor (TLR) signaling, which are intimately associated with neuronal survival, immune response, and inflammation. Moreover, the molecular simulation study further verified that fucosterol exhibited a significant binding affinity to some of the vital targets, including liver X-receptor-beta (LXR-β), glucocorticoid receptor (GR), tropomyosin receptor kinase B (TrkB), toll-like receptor 2/4 (TLR2/4), and β-secretase (BACE1), which are the crucial regulators of molecular and cellular processes associated with NDD. Together, the present system pharmacology and in silico findings demonstrate that fucosterol might play a significant role in modulating NDD-pathobiology, supporting its therapeutic application for the prevention and treatment of NDD.

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.

Shikonin derivatives for cancer prevention and therapy

Phytochemicals gained considerable interest during the past years as source to develop new treatment options for chemoprevention and cancer therapy. Motivated by the fact that a majority of established anticancer drugs are derived in one way or another from natural resources, we focused on shikonin, a naphthoquinone with high potentials to be further developed as preventive or therapeutic drug to fight cancer. Shikonin is the major chemical component of Lithospermum erythrorhizon (Purple Cromwell) roots. Traditionally, the root extract has been applied to cure dermatitis, burns, and wounds. Over the past three decades, the anti-inflammatory and anticancer effects of root extracts, isolated shikonin as well as semi-synthetic and synthetic derivatives and nanoformulations have been described. In vitro and in vivo experiments were conducted to understand the effect of shikonin at cellular and molecular levels. Preliminary clinical trials indicate the potential of shikonin for translation into clinical oncology. Shikonin exerts additive and synergistic interactions in combination with established chemotherapeutics, immunotherapeutic approaches, radiotherapy and other treatment modalities, which further underscores the potential of this phytochemical to be integrated into standard treatment regimens.

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.