Comparative Phylogeography of Central African Duikers Using Non-invasive Sampling Methods

The present study sets out to assess patterns of evolutionary diversification in central African duikers (subfamily Cephalophinae). The sampling strategy consisted of collecting geo-referenced duiker feces across 43 sites and seven countries. However, several challenges related to the use of non-invasive samples needed to be addressed prior to large scale DNA amplification. First, the best storage method for obtaining DNA from fecal samples needed to be established. Our study revealed that while silica is best for nuclear microsatellite analyses, RNAlater is the best storage medium for maximal mitochondrial amplification. Moreover, extracting DNA as early as possible always provided the best results. Second, since it is impossible to determine the species identity of duiker feces solely based on their morphology, a simple and reliable molecular method was needed. A tree-based approach based on ~650 base pairs of the control region amplified from reference samples was found to be the most reliable method to recover the identity of unknown samples. Third, for fine scale analyses of population genetic structure, a set of twelve nuclear microsatellites were assembled from existing bovid data. These microsatellites markers were chosen because they are very polymorphic, cross amplify among targeted taxa, co-amplify with combined markers of the same multiplex, and are powerful enough for individual identification. Patterns of mitochondrial and nuclear microsatellite variation were used to test two important hypotheses of diversification in the tropics: the Pleistocene refugia and the riverine barrier hypotheses. Analyses of historical and contemporary population genetic structure were carried out on the three most abundant species in our sampling area: the bay duiker (C. dorsalis), the Peter’s duiker (C. callipygus), and the blue duiker (P. monticola) using mitochondrial and nuclear markers described above. These data show that (1) southwest Nigeria and southwest Cameroon comprise genetically distinct populations in C. callipygus and P. monticola species, (2) signatures of demographic expansion for all three taxa are broadly coincident with the location of hypothesized upland refugia in Gabon and Equatorial Guinea and (3) the Sanaga, Ogooué, and Sangha rivers may constitute a partial riverine barrier and/or act as fluvial refugia for duikers

Application of Computer Modeling to Drug Discovery: Case Study of PRK1 Kinase Inhibitors as Potential Drugs in Prostate Cancer Treatment

Computer modeling of natural products (NPs) and NP scaffolds is increasingly gaining importance in drug discovery, particularly in hit/lead discovery programs and at the lead optimization stage. Even though industry had lost interest in the implication of NPs in hit/lead searches, recent reports still show that computer modeling could be a useful assert for the identification of starting scaffolds from nature, which could be further exploited by synthetic modifications. In this chapter, the focus is on some useful tools for computer modeling aimed at the discovery of anticancer drugs from NP scaffolds. We also focus on some recent developments toward the identification of potential anticancer agents by the application of computer modeling. The chapter will lay emphasis on natural sources of anticancer compounds, present some useful databases and computational tools for anticancer drug discovery, and show some recent case studies of the application of computational modeling in anticancer drug discovery, as well as some success stories in virtual screening applications in anticancer drug discovery, highlighting some useful results on the application of on lead discovery (including promising NP scaffolds) against an interesting anticancer drug target, the protein kinase C-related kinase (PRK1)

A survey of isatin hybrids and their biological properties

The emergence of diverse infections worldwide, which is a serious global threat to human existence, necessitates the urgent development of novel therapeutic candidates that can combat these diseases with efficacy. Molecular hybridization has been established as an efficient technique in designing bioactive molecules capable of fighting infections. Isatin, a core nucleus of an array of compounds with diverse biological properties can be modified at different positions leading to the creation of novel drug targets, is an active area of medicinal chemistry. This review containing published articles from 2005 to 2022 highlights isatin hybrids which have been synthesized and reported in the literature alongside a discussion on their biological properties. The enriched structure–activity relationship studies discussed provides insights for the rational design of novel isatin hybrids with tailored biological properties as effective therapeutic candidates inspired by nature

An in silico evaluation of the ADMET profile of the StreptomeDB database

BACKGROUND: Computer-aided drug design (CADD) often involves virtual screening (VS) of large compound datasets and the availability of such is vital for drug discovery protocols. This paper presents an assessment of the “drug-likeness” and pharmacokinetic profile of > 2,400 compounds of natural origin, currently available in the recently published StreptomeDB database. METHODS: The evaluation of “drug-likeness” was performed on the basis of Lipinski’s “Rule of Five”, while 46 computed physicochemical properties or molecular descriptors were used to predict the absorption, distribution, metabolism, elimination and toxicity (ADMET) of the compounds. RESULTS: This survey demonstrated that, of the computed molecular descriptors, about 28% of the compounds within the StreptomeDB database were compliant, having properties which fell within the range of ADMET properties of 95% of currently known drugs, while about 44% of the compounds had ≤ 2 violations. Moreover, about 50% of the compounds within the corresponding “drug-like” subset showed compliance, while >83% of the “drug-like” compounds had ≤ 2 violations. CONCLUSIONS: In addition to the previously verified range of measured biological activities, the compounds in the StreptomeDB database show interesting DMPK profiles and hence could represent an important starting point for hit/lead discovery from natural sources. The generated data are available and could be highly useful for natural product lead generation programs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/2193-1801-2-353) contains supplementary material, which is available to authorized users

First records of leucism in two species of duiker (Cephalophinae) in Gabon

The present study aimed to describe partial leucism, which is a pigmentation disorder, in two duiker species: Philantomba monticola and Sylvicapra grimmia. Leucism is a condition characterized by partial loss of pigmentation, resulting in white or pale patches on the animal's body. This is the first report of leucism in the subfamily Cephalophinae, which includes duikers, and similar occurrences may exist in other duiker species across their sub-Saharan distribution range. This finding highlights the potential for further research on pigmentation disorders in duikers and their prevalence in different species within the subfamily

Fragment-based virtual screening discovers potential new Plasmodium PI4KIIIβ ligands

Type III beta phosphatidylinositol 4-kinase (PI4KIIIβ) is the only clinically validated drug target in Plasmodium kinases and therefore a critical target in developing novel drugs for malaria. Current PI4KIIIβ inhibitors have solubility and off-target problems. Here we set out to identify new Plasmodium PI4K ligands that could serve as leads for the development of new antimalarial drugs by building a PPI4K homology model since there was no available three-dimensional structure of PfPI4K and virtually screened a small library of ~ 22 000 fragments against it. Sixteen compounds from the fragment-based virtual screening (FBVS) were selected based on ≤ − 9.0 kcal/mol binding free energy cut-off value. These were subjected to similarity and sub-structure searching after they had passed PAINS screening and the obtained derivatives showed improved binding affinity for PfPI4K (− 10.00 to − 13.80 kcal/mol). Moreover, binding hypothesis of the top-scoring compound (31) was confirmed in a 100 ns molecular dynamics simulation and its binding pose retrieved after the system had converged at about 10 ns into the evolution was described to lay foundation for a rationale chemical-modification to optimize binding to PfPI4K. Overall, compound 31 appears to be a viable starting point for the development of PPI4K inhibitors with antimalarial activity.Publikationsfonds ML

Computational Studies and Biosynthesis of Natural Products with Promising Anticancer Properties

We present an overview of computational approaches for the prediction of metabolic pathways by which plants biosynthesise compounds, with a focus on selected very promising anticancer secondary metabolites from floral sources. We also provide an overview of databases for the retrieval of useful genomic data, discussing the strengths and limitations of selected prediction software and the main computational tools (and methods), which could be employed for the investigation of the uncharted routes towards the biosynthesis of some of the identified anticancer metabolites from plant sources, eventually using specific examples to address some knowledge gaps when using these approaches

The chemical space spanned by manually curated datasets of natural and synthetic compounds with activities against SARS-CoV-2

Diseases caused by viruses are challenging to contain, as their outbreak and spread could be very sudden, compounded by rapid mutations, making the development of drugs and vaccines a continued endeavour that requires fast discovery and preparedness. Targeting viral infections with small molecules remains one of the treatment options to reduce transmission and the disease burden. A lesson learned from the recent coronavirus disease (COVID-19) is to collect ready-to-screen small molecule libraries in preparation for the next viral outbreak, and potentially find a clinical candidate before it becomes a pandemic. Public availability of diverse compound libraries, well annotated in terms of chemical structures and scaffolds, modes of action, and bioactivities are, therefore, crucial to ensure the participation of academic laboratories in these screening efforts, especially in resource-limited settings where synthesis, testing and computing capacity are scarce. Here, we demonstrate a low-resource approach to populate the chemical space of naturally occurring and synthetic small molecules that have shown in vitro and/or in vivo activities against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its target proteins. We have manually curated two datasets of small molecules (naturally occurring and synthetically derived) by reading and collecting (hand-curating) the published literature. Information from the literature reveals that a majority of the reported SARS-CoV-2 compounds act by inhibiting the main protease, while 25% of the compounds currently have no known target. Scaffold analysis and principal component analysis revealed that the most common scaffolds in the datasets are quite distinct. We then expanded the initially manually curated dataset of over 1200 compounds via an ultra-large scale 2D and 3D similarity search, obtaining an expanded collection of over 150 k purchasable compounds. The spanned chemical space significantly extends beyond that of a commercially available coronavirus library of more than 20 k small molecules and constitutes a good starting collection for virtual screening campaigns given its manageable size and proximity to hand-curated compounds