Prediction of Selective Neuroprotective JNK3 Inhibitory Activity of Plumbagin and Its derivatives using Insilico Computational Methods

In the present work, rational approach combining e- pharmacophore modelling and structure based virtual screening was employed on the target JNK3 to identify potential JNK3 inhibitors. The pharmacophore-based approaches are well known for their strength to propose a diverse set of molecules having diverse molecular frameworks but owing to a desired biological activity for one target. The hits were further analyzed and ranked by using dock score, binding energy, ADME parameters and MD simulations. Plumbagin derivatives have shown good potential of binding with the targeted protein as indicated by ΔGbind score. They also possessed desired ADME properties. Thereafter, MD simulation studies were carried out two best docked complexes. Based on the key amino acid residues interactions, molecular dynamics simulation sindicates that the docked complex of 5-Methoxy-2-methyl-(4(trifluoromethyl) benzylamino) naphthalene1, 4-dione and shikonin with JNK3 protein (3OY1) have a good stability in the binding pocket. The significant interaction with residue MET 149 was observed in both molecular docking and molecular dynamics simulations studies. By confirm the binding affinities of the ligand and the accurate interactions, molecular dynamics simulations valid the results of molecular docking. The results showed that the best classified compounds 5-Methoxy- 2-methyl-3-(4(trifluoromethyl)benzylamino) naphthalene1, 4-dione and shikonin with highest docking score and binding affinity and stable hydrogen bond with MET149 and hydrophobic interactions with Met146, Val79, Val145, Leu144, Ala91, Ile92, Ile124, and Leu128. relative to reference compounds. The outcome reveal that this study provides evidence for the consideration of plumbagin derivatives as pontential JNK3 inhibitors. Therefore, reliable computer-aided drug design methods could play an increasingly important role in the future drug discovery process. The Insilico studies results revealed that 5-Methoxy-2-methyl-3-(4 (trifluoromethyl) benzylamino) naphthalene1,4-dione and Shikonin as a potent, selective JNK3 inhibitors. This was found out by screening of generated pharmacophore hypothesis, molecular docking and molecular dynamics study of plumbagin and its derivatives. Further, in vitro evaluation of 5-Methoxy-2-methyl-3-(4-(trifluoromethyl) benzylamino) naphthalene1,4-dione and Shikonin is the futuristic requirement in order to perceive additional activity validation

Cancer and aging: a multidisciplinary medicinal chemistry approach on relevant biological targets such as proteasome, sirtuins and interleukin 6

It is well known that ageing and cancer have common origins due to internal and environmental stress and share some common hallmarks such as genomic instability, epigenetic alteration, aberrant telomeres, inflammation and immune injury. Moreover, ageing is involved in a number of events responsible for carcinogenesis and cancer development at the molecular, cellular, and tissue levels. Ageing could represent a “blockbuster” market because the target patient group includes potentially every person; at the same time, oncology has become the largest therapeutic area in the pharmaceutical industry in terms of the number of projects, clinical trials and research and development (R&D) spending, but cancer remains one of the leading causes of mortality worldwide. The overall aim of the work presented in this thesis was the rational design of new compounds able to modulate activity of relevant targets involved in cancer and aging-related pathologies, namely proteasome and immunoproteasome, sirtuins and interleukin 6. These three targets play different roles in human cells, but the modulation of its activity using small molecules could have beneficial effects on one or more aging-related diseases and cancer. We identified new moderately active and selective non-peptidic compounds able to inhibit the activity of both standard and immunoproteasome, as well as novel and selective scaffolds that would bind and inhibit SIRT6 selectively and can be used to sensitize tumor cells to commonly used anticancer agents such gemcitabine and olaparib. Moreover, our virtual screening approach led us also to the discovery of new putative modulators of SIRT3 with interesting in-vitro and cellular activity. Although the selectivity and potency of the identified chemical scaffolds are susceptible to be further improved, these compounds can be considered as highly promising leads for the development of future therapeutics

Literature-based discovery of known and potential new mechanisms for relating the status of cholesterol to the progression of breast cancer

Breast cancer has been studied for a long period of time and from a variety of perspectives in order to understand its pathogeny. The pathogeny of breast cancer can be classified into two groups: hereditary and spontaneous. Although cancer in general is considered a genetic disease, spontaneous factors are responsible for most of the pathogeny of breast cancer. In other words, breast cancer is more likely to be caused and deteriorated by the dysfunction of a physical molecule than be caused by germline mutation directly. Interestingly, cholesterol, as one of those molecules, has been discovered to correlate with breast cancer risk. However, the mechanisms of how cholesterol helps breast cancer progression are not thoroughly understood. As a result, this study aims to study known and discover potential new mechanisms regarding to the correlation of cholesterol and breast cancer progression using literature review and literature-based discovery. The known mechanisms are further classified into four groups: cholesterol membrane content, transport of cholesterol, cholesterol metabolites, and other. The potential mechanisms, which are intended to provide potential new treatments, have been identified and checked for feasibility by an expert

In Silico Strategies for Prospective Drug Repositionings

The discovery of new drugs is one of pharmaceutical research's most exciting and challenging tasks. Unfortunately, the conventional drug discovery procedure is chronophagous and seldom successful; furthermore, new drugs are needed to address our clinical challenges (e.g., new antibiotics, new anticancer drugs, new antivirals).Within this framework, drug repositioning—finding new pharmacodynamic properties for already approved drugs—becomes a worthy drug discovery strategy.Recent drug discovery techniques combine traditional tools with in silico strategies to identify previously unaccounted properties for drugs already in use. Indeed, big data exploration techniques capitalize on the ever-growing knowledge of drugs' structural and physicochemical properties, drug–target and drug–drug interactions, advances in human biochemistry, and the latest molecular and cellular biology discoveries.Following this new and exciting trend, this book is a collection of papers introducing innovative computational methods to identify potential candidates for drug repositioning. Thus, the papers in the Special Issue In Silico Strategies for Prospective Drug Repositionings introduce a wide array of in silico strategies such as complex network analysis, big data, machine learning, molecular docking, molecular dynamics simulation, and QSAR; these strategies target diverse diseases and medical conditions: COVID-19 and post-COVID-19 pulmonary fibrosis, non-small lung cancer, multiple sclerosis, toxoplasmosis, psychiatric disorders, or skin conditions

IN SILICO METHODS FOR DRUG DESIGN AND DISCOVERY

Computer-aided drug design (CADD) methodologies are playing an ever-increasing role in drug discovery that are critical in the cost-effective identification of promising drug candidates. These computational methods are relevant in limiting the use of animal models in pharmacological research, for aiding the rational design of novel and safe drug candidates, and for repositioning marketed drugs, supporting medicinal chemists and pharmacologists during the drug discovery trajectory.Within this field of research, we launched a Research Topic in Frontiers in Chemistry in March 2019 entitled “In silico Methods for Drug Design and Discovery,” which involved two sections of the journal: Medicinal and Pharmaceutical Chemistry and Theoretical and Computational Chemistry. For the reasons mentioned, this Research Topic attracted the attention of scientists and received a large number of submitted manuscripts. Among them 27 Original Research articles, five Review articles, and two Perspective articles have been published within the Research Topic. The Original Research articles cover most of the topics in CADD, reporting advanced in silico methods in drug discovery, while the Review articles offer a point of view of some computer-driven techniques applied to drug research. Finally, the Perspective articles provide a vision of specific computational approaches with an outlook in the modern era of CADD

In vitro cytotoxicity of Withania somnifera (L.) roots and fruits on oral squamous cell carcinoma cell lines: a study supported by flow cytometry, spectral, and computational investigations

Oral cancer is a severe health problem that accounts for an alarmingly high number of fatalities worldwide. Withania somnifera (L.) Dunal has been extensively studied against various tumor cell lines from different body organs, rarely from the oral cavity. We thus investigated the cytotoxicity of W. somnifera fruits (W-F) and roots (W-R) hydromethanolic extracts and their chromatographic fractions against oral squamous cell carcinoma (OSCC) cell lines [Ca9-22 (derived from gingiva), HSC-2, HSC-3, and HSC-4 (derived from tongue)] and three normal oral mesenchymal cells [human gingival fibroblast (HGF), human periodontal ligament fibroblast (HPLF), and human pulp cells (HPC)] in comparison to standard drugs. The root polar ethyl acetate (W-R EtOAc) and butanol (W-R BuOH) fractions exhibited the strongest cytotoxicity against the Ca9-22 cell line (CC50 = 51.8 and 40.1 μg/mL, respectively), which is relatively the same effect as 5-FU at CC50 = 69.4 μM and melphalan at CC50 = 36.3 μM on the same cancer cell line. Flow cytometric analysis revealed changes in morphology as well as in the cell cycle profile of the W-R EtOAc and W-R BuOH-treated oral cancer Ca9-22 cells compared to the untreated control. The W-R EtOAc (125 μg/mL) exerted morphological changes and induced subG1 accumulation, suggesting apoptotic cell death. A UHPLC MS/MS analysis of the extract enabled the identification of 26 compounds, mainly alkaloids, withanolides, withanosides, and flavonoids. Pharmacophore-based inverse virtual screening proposed that BRD3 and CDK2 are the cancer-relevant targets for the annotated withanolides D (18) and O (12), and the flavonoid kaempferol (11). Molecular modeling studies highlighted the BRD3 and CDK2 as the most probable oncogenic targets of anticancer activity of these molecules. These findings highlight W. somnifera’s potential as an affordable source of therapeutic agents for a range of oral malignancies

Design, Synthesis and Anti- Cancer Activity of Some Novel Thiazolidinedione Mannich Bases

The novel furfuryl thiazolidinedione Mannich bases were designed manually using Molgro Virtual Docker. The designed compounds were analyzed in order to predict the best score compounds . Based on the in silico docking studies, the best scored compounds were selected for the synthesis using scheme 1. The synthesized compounds were characterized by their FT-IR, 1H NMR and their Mass spectra. The confirmed compounds were subjected to in vitro anti-cancer activity with U937 using MTT method. All the compounds showed good anicancer activity. Among them, the compound TZD 36 [(5E)-3-[(diphenylamino)methyl]-5- [(furan-2-yl)methylidene]- 1,3-thiazolidine-2,4-dione] showed better anti-cancer activity with a cell viability of 23.89% and IC50 value of 62.5 μg/ml. The anti-cancer activity compound TZD 36 was subjected to in silico docking studies in order to predict the probable binding site against anaplastic lymphoma kinase (PDB code: 2XB7). From the in silico studies, compound 36 showed amino acids are linked via hydrogen bonding wit the ligand and amino acids like were shoed stearic interaction with the ligand. From the above results, we conclude that these interactions maybe the reason for the better activity than the other synthesized compounds. Moreover, we planned to analyze further all the compounds for other ailments

Computational Modeling of Protein Structure, Function, and Binding Hotspots

Mixed-solvent molecular dynamics (MixMD) is a cosolvent mapping technique for structure-based drug design. MixMD simulations are performed with a solvent mixture of small molecule probes and water, which directly compete for binding to the protein’s surface. MixMD has previously been shown to identify active and allosteric sites based on the time-averaged occupancy of the probe molecules over the course of the simulation. Sites with the highest maximal occupancy identified known biologically relevant sites for a wide range of targets. This is consistent with previous experimental work identifying hotspots on protein surfaces based on the occupancy of multiple organic-solvent molecules. However, previous MixMD analysis required extensive manual interpretation to identify and rank sites. MixMD Probeview was introduced to automate this analysis, thereby facilitating the application of MixMD. Implemented as a plugin for the freely available, open-source version of PyMOL, MixMD Probeview successfully identified binding sites for several test systems using three different cosolvent simulation procedures. Following identification of binding sites, the occupancy maps from the MixMD simulations can be converted into pharmacophore models for prospective screening of inhibitors. We have developed a pharmacophore generation procedure to convert MixMD occupancy maps into pharmacophore models. Validation of this procedure on ABL kinase showed good performance. Additionally, we have identified characteristic occupancy levels for non-displaceable water molecules so that these sites may be incorporated into structure-based drug design efforts. Lastly, we have explored the potential for accelerated sampling methods to be used in tandem with MixMD to simultaneously capture conformational changes while mapping favorable interactions within binding sites. These developments greatly extend the utility of MixMD while also simplifying its application. In addition, two exploratory studies were completed. First, traditional MD simulations were performed to understand the dynamics of NSD1. Crystal structures of NSD1 capture the post-SET loop in an autoinhibitory position. MD simulations allow conformational sampling of this loop, yielding insight into its dynamic behavior in solution. Second, an epidemiological study was conducted which was aimed at understanding the transmission and sequence variation of CTX-M-type β-lactamases, in fulfillment of the clinical research component of the MICHR Translational Research Education Certificate.PHDBiophysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138744/1/sarahgra_1.pd

Marine Drug Research in China: Selected Papers from the 15-NASMD Conference

The Book covers this whole field, from the discovery of structurally new and bioactive natural products (including biomacromolecules), from marine macro-/micro-organisms, to the pharmacodynamics, pharmacokinetics, metabolisms, and mechanisms of marine-derived lead compounds, both in vitro and in vivo, along with the synthesis and/or structural optimization of marine-derived lead compounds and their structure–activity relationships. Taken together, this Special Issue reprint not only provides inspiration for the discovery of marine-derived novel bioactive compounds, but also sheds light on the further research and development of marine candidate drugs