ADME Profiling in Drug Discovery and a New Path Paved on Silica

The drug discovery and development pipeline have more and more relied on in vitro testing and in silico predictions to reduce investments and optimize lead compounds. A comprehensive set of in vitro assays is available to determine key parameters of absorption, distribution, metabolism, and excretion, for example, lipophilicity, solubility, and plasma stability. Such test systems aid the evaluation of the pharmacological properties of a compound and serve as surrogates before entering in vivo testing and clinical trials. Nowadays, computer-aided techniques are employed not just in the discovery of new lead compounds but embedded as part of the entire drug development process where the ADME profiling and big data analyses add a new layer of complexity to those systems. Herein, we give a short overview of the history of the drug development pipeline presenting state-of-the-art ADME in vitro assays as established in academia and industry. We will further introduce the underlying good practices and give an example of the compound development pipeline. In the next step, recent advances at in silico techniques will be highlighted with special emphasis on how pharmacogenomics and in silico PK profiling can enhance drug monitoring and individualization of drug therapy

Molecular properties of fatty acids related to PPAR binding and metabolic diseases

Peroxisome proliferator-activated receptor (PPAR) is a class of nuclear receptors responsible for the transcription of genes that regulate the metabolism of carbohydrates and lipids. The main endogenous ligands of PPARs are fatty acids, leukotrienes and derivatives. The PPAR family has three isoforms: α, γ, and δ. To understand the main interactions responsible for the PPAR selectivity of a subset of ligands, we performed molecular modeling studies on a set of 16 fatty acids. From the results obtained, we found that stereochemical, hydrophobic, and polar properties are correlated with PPAR selectivity and can be used to design new ligands with improved biological selectivity.FAPESPCNPqCAPE

MASSA Algorithm: automated rational sampling of training and test subsets for QSAR modelling

QSAR models capable of predicting biological, toxicity, and pharmacokinetic properties were widely used to search lead bioactive molecules in chemical databases. The dataset’s preparation to build these models has a strong influence on the quality of the generated models, and sampling requires that the original dataset be divided into training (for model training) and test (for statistical evaluation) sets. This sampling can be done randomly or rationally, but the rational division is superior. In this paper, we present MASSA, a Python tool that can be used to automatically sample datasets by exploring the biological, physicochemical, and structural spaces of molecules using PCA, HCA, and K-modes. The proposed algorithm is very useful when the variables used for QSAR are not available or to construct multiple QSAR models with the same training and test sets, producing models with lower variability and better values for validation metrics. These results were obtained even when the descriptors used in the QSAR/QSPR were different from those used in the separation of training and test sets, indicating that this tool can be used to build models for more than one QSAR/QSPR technique. Finally, this tool also generates useful graphical representations that can provide insights into the data

The Brazilian Compound Library (BraCoLi) Database: A Brazilian Repository of Chemical and Biological Information for Drug Design

The Brazilian Compound Library (BraCoLi) is a novel open access and manually curated electronic library of compounds developed by Brazilian research groups to support further computer-aided drug design works. Herein, the first version of the database is described comprising 1,176 compounds. Also, the chemical diversity and drug-like profiles of BraCoLi were defined to analyze its chemical space. A significant amount of the compounds fitted Lipinski and Veber’s rules, alongside other drug-likeness properties. A comparison using principal component analysis showed that BraCoLi is similar to other databases (FDA-approved drugs and NuBBEDB) regarding structural and physicochemical patterns. Furthermore, a scaffold analysis showed that BraCoLi presents several privileged chemical skeletons with great diversity. Despite the similar distribution in the structural and physicochemical spaces, similarity analysis indicated that compounds present in the BraCoLi are generally different from the two other databases showing an interesting innovative aspect, which is a desirable feature for novel drug design purposes

Molecular cloning and characterization of pirarucu (<i>Arapaima gigas</i>) follicle-stimulating hormone and luteinizing hormone β-subunit cDNAs

<div><p>The common gonadotrophic hormone α-subunit (GTHα) has been previously isolated by our research group from <i>A</i>. <i>gigas</i> pituitaries; in the present work the cDNA sequences encoding FSHβ and LHβ subunits have also been isolated from the same species of fish. The FSH β-subunit consists of 126 amino acids with a putative 18 amino acid signal peptide and a 108 amino acid mature peptide, while the LH β-subunit consists of 141 amino acids with a putative 24 amino acid amino acid signal peptide and a 117 amino acid mature peptide. The highest identity, based on the amino acid sequences, was found with the order of Anguilliformes (61%) for FSHβ and of Cypriniformes (76%) for LHβ, followed by Siluriformes, 53% for FSHβ and 75% for LHβ. Interestingly, the identity with the corresponding human amino acid sequences was still remarkable: 45.1% for FSHβ and 51.4% for LHβ. Three dimensional models of ag-FSH and ag-LH, generated by using the crystal structures of h-FSH and h-LH as the respective templates and carried out via comparative modeling and molecular dynamics simulations, suggested the presence of the so-called “seat-belt”, favored by a disulfide bond formed between the 3^rd and 12^th cysteine in both β-subunits. The sequences found will be used for the biotechnological synthesis of <i>A</i>. <i>gigas</i> gonadotrophic hormones (ag-FSH and ag-LH). In a first approach, to ascertain that the cloned transcripts allow the expression of the heterodimeric hormones, ag-FSH has been synthesized in human embryonic kidney 293 (HEK293) cells, preliminarily purified and characterized.</p></div

Virtual Screening of Adenylate Kinase 3 Inhibitors Employing Pharmacophoric Model, Molecular Docking, and Molecular Dynamics Simulations as Potential Therapeutic Target in Chronic Lymphocytic Leukemia

Adenylate kinase 3 (AK3) is an enzyme located in the mitochondrial matrix involved in purine homeostasis. This protein has been considered a potential therapeutic target in chronic lymphocytic leukemia (CLL), because the silencing of the AK3 gene has inhibited cell growth in CLL in vitro models. This study aimed to design potential AK3 inhibitors by applying molecular modeling techniques. Through the mapping of AK3 binding sites, essential interaction fields for pharmacophore design were identified. Online libraries were virtually screened by using a pharmacophore model, and 6891 compounds exhibited the functional groups for interaction with the target. These compounds underwent molecular docking simulations through Surflex and GOLD programs. After visual inspection, we selected 13 compounds for pharmacokinetic properties toxicology prediction via admetSAR and Protox web servers. Finally, six compounds were chosen for further analysis

Percentage identity of FSHβ and LHβ peptides among fish orders (FSHβ above the diagonal).

<p>Percentage identity of FSHβ and LHβ peptides among fish orders (FSHβ above the diagonal).</p

RP-HPLC, run under dissociating conditions as described [64], after application of a sample of ag-FSH obtained from HPSEC (see Fig 8) and incubated overnight with 5M acetic acid at 37°C.

<p>RP-HPLC, run under dissociating conditions as described [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0183545#pone.0183545.ref064" target="_blank">64</a>], after application of a sample of ag-FSH obtained from HPSEC (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0183545#pone.0183545.g008" target="_blank">Fig 8</a>) and incubated overnight with 5M acetic acid at 37°C.</p

First purification step of HEK293F conditioned medium via RP-HPLC.

<p>The chromatogram is derived from the application of 5 ml of ag-FSH transfection conditioned medium, in comparison with an analogous chromatogram derived from the application of 5 ml of the negative control of transfection.</p