Molecular Modeling of Potential Anticancer Agents from African Medicinal Plants

Ntie‐Kang, Fidele; Nwodo, Justina N.; Ibezim, Akachukwu; Simoben, Conrad V.; Karaman, Berin; Fuh-Ngwa, Valery; Sippl, Wolfgang; Adikwu, M. U.; Mbaze, Luc Meva’a

doi:10.1021/ci5003697

Cited by 79 publications

(55 citation statements)

References 105 publications

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“…Studies in silico have been published for Ebola VP35 and VP40, and, very recently, a machine learning method that uses Bayesian and Support Vector Machine (SVM) algorithms was proposed by Ekin et al [25] for the identification of novel Ebola inhibitors from already reported antiviral data. Over the past decade, there has been significant interest in the exploitation of phytochemicals for pharmaceutical use, many of which have antiviral or anticancer activities; a few studies have focused on the potential of phytochemicals as possible parental compounds for the treatment of haemorrhagic fever [34,35]. Kolokoltsov et al demonstrated that a cocktail of genistein and tyrphostin AG1478, both of which are kinase inhibitors, forms a broad spectrum antiviral agent that can be used for the treatment of both arenavirus and filovirus haemorrhagic fevers [36].…”

Section: Introductionmentioning

confidence: 99%

Integrated Computational Approach for Virtual Hit Identification against Ebola Viral Proteins VP35 and VP40

Mirza

Ikram

2016

IJMS

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The Ebola virus (EBOV) has been recognised for nearly 40 years, with the most recent EBOV outbreak being in West Africa, where it created a humanitarian crisis. Mortalities reported up to 30 March 2016 totalled 11,307. However, up until now, EBOV drugs have been far from achieving regulatory (FDA) approval. It is therefore essential to identify parent compounds that have the potential to be developed into effective drugs. Studies on Ebola viral proteins have shown that some can elicit an immunological response in mice, and these are now considered essential components of a vaccine designed to protect against Ebola haemorrhagic fever. The current study focuses on chemoinformatic approaches to identify virtual hits against Ebola viral proteins (VP35 and VP40), including protein binding site prediction, drug-likeness, pharmacokinetic and pharmacodynamic properties, metabolic site prediction, and molecular docking. Retrospective validation was performed using a database of non-active compounds, and early enrichment of EBOV actives at different false positive rates was calculated. Homology modelling and subsequent superimposition of binding site residues on other strains of EBOV were carried out to check residual conformations, and hence to confirm the efficacy of potential compounds. As a mechanism for artefactual inhibition of proteins through non-specific compounds, virtual hits were assessed for their aggregator potential compared with previously reported aggregators. These systematic studies have indicated that a few compounds may be effective inhibitors of EBOV replication and therefore might have the potential to be developed as anti-EBOV drugs after subsequent testing and validation in experiments in vivo.

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Section: Introductionmentioning

confidence: 99%

Integrated Computational Approach for Virtual Hit Identification against Ebola Viral Proteins VP35 and VP40

Mirza

Ikram

2016

IJMS

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“…The docking protocol explained in experimental section gave an rmsd of 2.09 Å which is within the recommended range and hence was implemented in this study (Fig 2) [36]. …”

Section: Resultsmentioning

confidence: 99%

“…The crystal structures of the bacteria DNA gyrase (PDB code: 1KZN) with its cocrystallized inhibitor (chlorobiocin) were downloaded from RCSB protein data bank [35]. The enzyme-inhibitor complexes were prepared according to standard for use in docking calculation [36]. Both the ligands and protein were energy minimized to a gradient of 0.001 kcal/mol using Merck Molecular (MMFF94) Force field [37].…”

Section: Methodsmentioning

confidence: 99%

Experimental and In-Silico Investigation of Anti-Microbial Activity of 1-Chloro-2-Isocyanatoethane Derivatives of Thiomorpholine, Piperazine and Morpholine

et al. 2017

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The Antibiogram properties of 1-chloro-2-isocyanatoethane derivatives of thiomorpholine (CTC), piperazine (CPC) and morpholine (CMC) were evaluated by the approved agar well diffusion, the minimum inhibitory concentration (MIC) and in silico techniques. A total of fourteen microbial cultures consisting of ten bacteria and four yeast strains were used in the biological study while affinity of the compounds for DNA gyrase, a validated antibacterial drug target, was investigated by docking method. Results indicate that both thiomorpholine and piperazine had zero activity against the Gram negative organisms tested. With morpholine, similar result was obtained except that cultures of Escherichia coli (ATCC 15442) and Salmonella typhi (ATCC 6539) presented with weak sensitivity (7–8 mm) as shown by the inhibition zone diameter (IZD) measurement. The Gram positive organisms were more sensitive to morpholine than the other compounds. The highest IZD values of 15–18 mm were achieved except for Streptococcus pneumoniae (ATCC 49619) in which mobility of the compound stopped after 12 mm. S. pneumoniae was resistant to both thiomorpholine and piperazine. The yeast strains were not sensitive to any of the studied compounds investigated. The MIC tests evaluated against a reference antibiotic show that while morpholine was most active at 4 μg.ml-1 against both B. cereus ATCC (14579) and B. subtilis, the least active compound was thiomorpholine which inhibited S. aureus (ATCC 25923) at 64 μg.ml-1. The three compounds demonstrated high affinity for the target protein (DNA gyrase) ranging from -4.63 to -5.64 Kcal/mol and even showed better ligand efficiencies than three known antibiotics; chlorobiocin, ciprofloxacin and tetracycline. This study identified the studied compounds as potential antibiotic leads with acceptable physicochemical properties and gave the molecular basis for the observed interactions between the compounds and the target protein which can be harnessed in structural optimization process.

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“…Interestingly, within last four to five years, a huge number of public repositories have been established for medicinal plants and their derived phytochemicals. The list includes, but is not limited to MPD3 [21], Phytochemica [22], SerpentinaDB [23], FERN Ethnomedicinal Plant Database [24], Naturally Occurring Plant-based Anti-Cancer Compound-Activity-Target Database (NPACT) [25], SuperNatural [26], Herb Ingredients' Targets (HIT) [27], Cancer Resource-dataset of compound-target interactions [13], Traditional Chinese medicine database (TCMD) [28], China natural products database (CNPD) [29], Chinese herb constituents database (CHCD) [30], Bioactive plant compounds database (BPCD) [30], Nuclei of Bioassays, Ecophysiology and Biosynthesis of Natural Products Database (NuBBEDB) [31,32], Northern African Natural Products Database (NANPDB) [33], Highly potent and diverse natural product library from African medicinal plants (AfroDb) [34], Molecular modeling of potential anticancer agents from African medicinal plants (AfroCancer) [35], Database of Volatile Organic Compounds in Cancer (VOCC) [36], and Nutrient Use Efficiency (NtUE) Web-Resource [37]. However, a similar comprehensive database for Uttarakhand medicinal plants is still not available despite a recent database development by the ENVIS center on Forestry with very limited scope and information.…”

Section: Introductionmentioning

confidence: 99%

Uttarakhand Medicinal Plants Database (UMPDB): A Platform for Exploring Genomic, Chemical, and Traditional Knowledge

Kumar

Sharma

et al. 2018

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Abstract:Medicinal plants are the main natural pools for the primary health care system, ethno-medicine, as well as traditional Indian system of several medicines. Uttarakhand also known as 'Herbal State', is a rich source of medicinal plants and traditional medicinal knowledge. A great deal of information about medicinal plants of Uttarakhand is scattered in different forms. Although many medicinal plant databases are available, currently there is no cohesive manually curated database of medicinal plants widely distributed in Uttarakhand state. A comprehensive database has been developed, known as the Uttarakhand Medicinal Plants Database (UMPDB). UMPDB provides extensive information on botanical name, common name, taxonomy, genomic taxonomy id, habit, habitat, location in Uttarakhand, part use, medicinal use, genomic information (including number of nucleotides, proteins, ESTs), chemical information, and scientific literature. Annotated medicinal plants integrated in the current version of the database were collected from the existing books, databases, and available literature. The current version of UMPDB contains the 1127 records of medicinal plants which belong to 153 plant families distributed across 13 districts of Uttarakhand. The primary goal of developing this database is to provide traditional, genomic, and chemical descriptions of the medicinal plants exclusively found in various regions of Uttarakhand. We anticipate that embedded information in the database would help users to readily obtain desired information.

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Molecular Modeling of Potential Anticancer Agents from African Medicinal Plants

Cited by 79 publications

References 105 publications

Integrated Computational Approach for Virtual Hit Identification against Ebola Viral Proteins VP35 and VP40

Integrated Computational Approach for Virtual Hit Identification against Ebola Viral Proteins VP35 and VP40

Experimental and In-Silico Investigation of Anti-Microbial Activity of 1-Chloro-2-Isocyanatoethane Derivatives of Thiomorpholine, Piperazine and Morpholine

Uttarakhand Medicinal Plants Database (UMPDB): A Platform for Exploring Genomic, Chemical, and Traditional Knowledge

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