Luc C. Owono

CamMedNP: Building the Cameroonian 3D structural natural products database for virtual screening

BackgroundComputer-aided drug design (CADD) often involves virtual screening (VS) of large compound datasets and the availability of such is vital for drug discovery protocols. We present CamMedNP - a new database beginning with more than 2,500 compounds of natural origin, along with some of their derivatives which were obtained through hemisynthesis. These are pure compounds which have been previously isolated and characterized using modern spectroscopic methods and published by several research teams spread across Cameroon.DescriptionIn the present study, 224 distinct medicinal plant species belonging to 55 plant families from the Cameroonian flora have been considered. About 80 % of these have been previously published and/or referenced in internationally recognized journals. For each compound, the optimized 3D structure, drug-like properties, plant source, collection site and currently known biological activities are given, as well as literature references. We have evaluated the “drug-likeness” of this database using Lipinski’s “Rule of Five”. A diversity analysis has been carried out in comparison with the ChemBridge diverse database.ConclusionCamMedNP could be highly useful for database screening and natural product lead generation programs.

Cameroonian medicinal plants: a bioactivity versus ethnobotanical survey and chemotaxonomic classification

BackgroundIn Cameroon herbs are traditionally used to meet health care needs and plans are on the way to integrate traditional medicine in the health care system, even though the plans have not been put into action yet. The country however has a rich biodiversity, with ~8,620 plant species, some of which are commonly used in the treatment of several microbial infections and a range of diseases (malaria, trypanosomiasis, leishmaniasis, diabetes and tuberculosis).MethodsOur survey consisted in collecting published data from the literature sources, mainly from PhD theses in Cameroonian university libraries and also using the author queries in major natural product and medicinal chemistry journals. The collected data includes plant sources, uses of plant material in traditional medicine, plant families, region of collection of plant material, isolated metabolites and type (e.g. flavonoid, terpenoid, etc.), measured biological activities of isolated compounds, and any comments on significance of isolated metabolites on the chemotaxonomic classification of the plant species. This data was compiled on a excel sheet and analysed.ResultsIn this study, a literature survey led to the collection of data on 2,700 secondary metabolites, which have been previously isolated or derived from Cameroonian medicinal plants. This represents distinct phytochemicals derived from 312 plant species belonging to 67 plant families. The plant species are investigated in terms of chemical composition with respect to the various plant families. A correlation between the known biological activities of isolated compounds and the ethnobotanical uses of the plants is also attempted. Insight into future direction for natural product search within the Cameroonian forest and Savanna is provided.ConclusionsIt can be verified that a phytochemical search of active secondary metabolites, which is inspired by knowledge from the ethnobotanical uses of medicinal plants could be very vital in a drug discovery program from plant-derived bioactive compounds.

In silico drug metabolism and pharmacokinetic profiles of natural products from medicinal plants in the Congo basin.

PurposeDrug metabolism and pharmacokinetics (DMPK) assessment has come to occupy a place of interest during the early stages of drug discovery today. The use of computer modelling to predict the DMPK and toxicity properties of a natural product library derived from medicinal plants from Central Africa (named ConMedNP). Material from some of the plant sources are currently employed in African Traditional Medicine.MethodsComputer-based methods are slowly gaining ground in this area and are often used as preliminary criteria for the elimination of compounds likely to present uninteresting pharmacokinetic profiles and unacceptable levels of toxicity from the list of potential drug candidates, hence cutting down the cost of discovery of a drug.In the present study, we present an in silico assessment of the DMPK and toxicity profile of a natural product library containing ~3,200 compounds, derived from 379 species of medicinal plants from 10 countries in the Congo Basin forests and savannas, which have been published in the literature. In this analysis, we have used 46 computed physico-chemical properties or molecular descriptors to predict the absorption, distribution, metabolism and elimination and toxicity (ADMET) of the compounds.ResultsThis survey demonstrated that about 45% of the compounds within the ConMedNP compound library are compliant, having properties which fall within the range of ADME properties of 95% of currently known drugs, while about 69% of the compounds have ≤ 2 violations. Moreover, about 73% of the compounds within the corresponding “drug-like” subset showed compliance.ConclusionsIn addition to the verified levels of “drug-likeness”, diversity and the wide range of measured biological activities, the compounds from medicinal plants in Central Africa show interesting DMPK profiles and hence could represent an important starting point for hit/lead discovery.

ConMedNP: a natural product library from Central African medicinal plants for drug discovery

We assess the medicinal value and “drug-likeness” of ∼3200 compounds of natural origin, along with some of their derivatives which were obtained through hemisynthesis. In the present study, 376 distinct medicinal plant species belonging to 79 plant families from the Central African flora have been considered, based on data retrieved from literature sources. For each compound, the optimised 3D structure has been used to calculate physicochemical properties which determine oral availability on the basis of Lipinskis “Rule of Five”. A comparative analysis has been carried out with the “drug-like”, “lead-like”, and “fragment-like” subsets, containing respectively 1726, 738 and 155 compounds, as well as with our smaller previously published CamMedNP library and the Dictionary of Natural products. A diversity analysis has been carried out in comparison with the DIVERSet™ Database (containing 48 651 compounds) from ChemBridge. Our results prove that drug discovery, beginning with natural products from the Central African flora, could be promising. The 3D structures are available and could be useful for virtual screening and natural product lead generation programs.

Perspectives on tuberculosis pathogenesis and discovery of anti- tubercular drugs.

Based on the global burden of tuberculosis and resistant strains that have recently emerged, not responding to existing therapies, it has become urgent to search for new remedies against this global human plague that has been compounded by HIV co-infection. Thus, the search for new drugs against the disease-causing agent, Mycobacterium tuberculosis (MTB), is an ongoing effort. This review discusses the state-of-the-art in anti-tuberculosis pathogenesis and anti-TB drug research, identifying some of the challenges being faced by researchers in the field and sheds light on possible ways forward, particularly in low-income countries.

Virtually Designed Triclosan-Based Inhibitors of Enoyl-Acyl Carrier Protein Reductase of Mycobacterium tuberculosis and of Plasmodium falciparum

We report here new chemical structures of predicted nanomolar triclosan‐based inhibitors (TCLs) of Mycobacterium tuberculosis enoyl‐acyl carrier protein reductase (InhA) virtually proposed by computer‐assisted molecular design. 3D models of InhA‐TCL complexes were prepared by in situ modifications of the reference crystal structure (PDB entry 1P45) for a training set of 15 TCLs with known InhA inhibitory activities. A QSAR model was built leading to linear correlation between the calculated free energies of complexation (ΔΔGcom) and experimental values IC50exp: pIC50=−0.0657×ΔΔGcom+3.0502, R2=0.96. In addition, ligand‐based quantitative pharmacophore model (PH4) was built from bound conformations of the training set compounds and confirmed the correlation between molecular models and observed activities: pIC50exp=0.8929×pIC50pre−0.441, R2=0.95. Structural information from both models helped us to propose new TCL analogues. A virtual library of TCLs with known predicted activities against enoyl‐acyl carrier protein reductase of Plasmodium falciparum (PfENR) was evaluated, revealing dual target TCLs. Moreover, analysis of binding site interactions suggested enriching substitutions, which led to more potent TCLs with predicted pIC50pre as low as 7 nM. The computational approach, which used both free energy estimated from molecular modeling and 3D‐QSAR pharmacophore model, was helpful in virtually proposing the dual‐targeted drugs and provided valuable information for the design of novel potential antituberculotic agents.

Design of Thymidine Analogues Targeting Thymidilate Kinase of Mycobacterium tuberculosis.

We design here new nanomolar antituberculotics, inhibitors of Mycobacterium tuberculosis thymidine monophosphate kinase (TMPKmt), by means of structure-based molecular design. 3D models of TMPKmt-inhibitor complexes have been prepared from the crystal structure of TMPKmt cocrystallized with the natural substrate deoxythymidine monophosphate (dTMP) (1GSI) for a training set of 15 thymidine analogues (TMDs) with known activity to prepare a QSAR model of interaction establishing a correlation between the free energy of complexation and the biological activity. Subsequent validation of the predictability of the model has been performed with a 3D QSAR pharmacophore generation. The structural information derived from the model served to design new subnanomolar thymidine analogues. From molecular modeling investigations, the agreement between free energy of complexation (ΔΔG com) and K i values explains 94% of the TMPKmt inhibition (pK i = −0.2924ΔΔG com + 3.234; R 2 = 0.94) by variation of the computed ΔΔG com and 92% for the pharmacophore (PH4) model (pK i = 1.0206 × pK i pred − 0.0832, R 2 = 0.92). The analysis of contributions from active site residues suggested substitution at the 5-position of pyrimidine ring and various groups at the 5′-position of the ribose. The best inhibitor reached a predicted K i of 0.155 nM. The computational approach through the combined use of molecular modeling and PH4 pharmacophore is helpful in targeted drug design, providing valuable information for the synthesis and prediction of activity of novel antituberculotic agents.

Targeting cysteine proteases from Plasmodium falciparum: A general overview, rational drug design and computational approaches for drug discovery.

BACKGROUND The Plasmodium falciparum cysteine proteases, also known as falcipains, are involved in different erythrocytic cycle processes of the malaria parasite, e.g. hydrolysis of host haemoglobin, erythrocyte invasion, and erythrocyte rupture. With the biochemical characterization of four falcipains so far, FP-2 (falcipain-2) and FP-3 (falcipain-3), members of the papain-like CAC1 family, are essential haemoglobinases. They could therefore be referred to as potential anti-malarial drug targets in the search for novel therapies, which could ease the burden caused by the increasing resistance to current antimalarial drugs. OBJECTIVES This review provides a summary of the most important results, highlighting the drug design approaches essential for the understanding of the mechanism of inhibition and discovery of inhibitors against cysteine proteases from P. falciparum. RESULTS Rational and computer-aided drug discovery approaches for the design of promising falcipain inhibitors are described herein, with a focus on a variety of structure-based and ligand-based modeling approaches. Moreover, the key features of ligand recognition against these targets are emphasized. CONCLUSION This review would be of interest to scientists engaged in the development of drug design strategies to target the cysteine proteases, FP-2 and FP-3.