Criteria for Engineering Cutinases: Bioinformatics Analysis of Catalophores

Cutinases are bacterial and fungal enzymes that catalyze the hydrolysis of natural cutin, a three-dimensional inter-esterified polyester with epoxy-hydroxy fatty acids with chain lengths between 16 and 18 carbon atoms. Due to their ability to accept long chain substrates, cutinases are also effective in catalyzing in vitro both the degradation and synthesis of several synthetic polyesters and polyamides. Here, we present a bioinformatics study that intends to correlate the structural features of cutinases with their catalytic properties to provide rational basis for their effective exploitation, particularly in polymer synthesis and biodegradation. The bioinformatics study used the BioGPS method (Global Positioning System in Biological Space) that computed molecular descriptors based on Molecular Interaction Fields (MIFs) described in the GRID force field. The information was used to generate catalophores, spatial representations of the ability of each enzymatic active site to establish hydrophobic and electrostatic interactions. These tools were exploited for comparing cutinases to other serine-hydrolases enzymes, namely lipases, esterases, amidases and proteases, and for highlighting differences and similarities that might guide rational engineering strategies. Structural features of cutinases with their catalytic properties were correlated. The “catalophore” of cutinases indicate shared features with lipases and esterases.

3D-QSAR study of adenosine 5’-phosphosulfate (APS) analouges as ligands for APS reductase

Metabolism of sulfur (sulfur assimilation pathway, SAP) is one of the key pathways for the pathogenesis and survival of persistant bacterias, such as Mycobacterium tuberculosis (Mtb), in the latent period. Adenosine 5?-phospho-sulfate reductase (APSR) is an important enzyme involved in the SAP, absent from the human body, so it might represents a valid target for development of new antituberculosis drugs. This work aimed to develop 3D QSAR model based on the crystal structure of APSR from Pseudomonas aeruginosa, which shows high degree of homology with APSR from Mtb, in complex with its substrate, adenosine 5?-phosphosulfate (APS). 3D QSAR model was built from a set of 16 nucleotide analogues of APS using alignment-independent descriptors derived from molecular interaction fields (MIF). The model improves the understanding of the key characteristics of molecules necessary for the interaction with target, and enables the rational design of novel small molecule inhibitors of Mtb APSR.

Indole-Containing Phytoalexin-Based Bioisosteres as Antifungals: In Vitro and In Silico Evaluation against Fusarium oxysporum

There is a continuous search for more reliable and effective alternatives to control phytopathogens through different strategies. In this context, indole-containing phytoalexins are stimuli-induced compounds implicated in plant defense against plant pathogens. However, phytoalexins’ efficacy have been limited by fungal detoxifying mechanisms, thus, the research on bioisosteres-based analogs can be a friendly alternative regarding the control of Fusarium phytopathogens, but there are currently few studies on it. Thus, as part of our research on antifungal agents, a set of 21 synthetic indole-containing phytoalexin analogs were evaluated as inhibitors against the phyopathogen Fusarium oxysporum. Results indicated that analogs of the N,N-dialkylthiourea, N,S-dialkyldithiocarbamate and substituted-1,3-thiazolidin-5-one groups exhibited the best docking scores and interaction profiles within the active site of Fusarium spp. enzymes. Vina scores exhibited correlation with experimental mycelial growth inhibition using supervised statistics, and this antifungal dataset correlated with molecular interaction fields after CoMFA. Compound 24 (tert-butyl (((3-oxo-1,3-diphenylpropyl)thio)carbonothioyl)-l-tryptophanate), a very active analog against F. oxysporum, exhibited the best interaction with lanosterol 14α-demethylase according to molecular docking, molecular dynamics and molecular mechanic/poisson-boltzmann surface area (MM/PBSA) binding energy performance. After data analyses, information on mycelial growth inhibitors, structural requirements and putative enzyme targets may be used in further antifungal development based on phytoalexin analogs for controlling phytopathogens.

Studies on the Dual Activity of EGFR and HER-2 Inhibitors Using Structure-Based Drug Design Techniques

HER-2 and EGFR are biological targets related to the development of cancer and the discovery and/or development of a dual inhibitor could be a good strategy to design an effective drug candidate. In this study, analyses of the chemical properties of a group of substances having affinity for both HER-2 and EGFR were carried out with the aim of understanding the main factors involved in the interaction between these inhibitors and the biological targets. Comparative analysis of molecular interaction fields (CoMFA) and comparative molecular similarity index analysis (CoMSIA) techniques were applied on 63 compounds. From CoMFA analyses, we found for both HER-2 (r2 calibration = 0.98 and q2cv = 0.83) and EGFR (r2 calibration = 0.98 and q2cv = 0.73) good predictive models. Good models for CoMSIA technique have also been found for HER-2 (r2 calibration = 0.92 and q2cv = 0.74) and EGFR (r2 calibration = 0.97 and q2cv = 0.72). The constructed models could indicate some important characteristics for the inhibition of the biological targets. New compounds were proposed as candidates to inhibit both proteins. Therefore, this study may guide future projects for the development of new drug candidates for the treatment of breast cancer.

Truly Target-Focused Pharmacophore Modeling: A Novel Tool for Mapping Intermolecular Surfaces

Pharmacophore models are an accurate and minimal tridimensional abstraction of intermolecular interactions between chemical structures, usually derived from a group of molecules or from a ligand-target complex. Only a limited amount of solutions exists to model comprehensive pharmacophores using the information of a particular target structure without knowledge of any binding ligand. In this work, an automated and customable tool for truly target-focused (T²F) pharmacophore modeling is introduced. Key molecular interaction fields of a macromolecular structure are calculated using the AutoGRID energy functions. The most relevant points are selected by a newly developed filtering cascade and clustered to pharmacophore features with a density-based algorithm. Using five different protein classes, the ability of this method to identify essential pharmacophore features was compared to structure-based pharmacophores derived from ligand-target interactions. This method represents an extremely valuable instrument for drug design in a situation of scarce ligand information available, but also in the case of underexplored therapeutic targets, as well as to investigate protein allosteric pockets and protein-protein interactions.

Computational and Metabolic Studies on a Set of N-Myristoyltransferase Inhibitors Against Trypanosoma Brucei

This article describes how the Human African trypanosomiasis (HAT) is a neglected disease caused by Trypanosoma brucei. Only four drugs are available for treating HAT. Despite years of effort, little progress has been made in identifying orally available chemotypes active against the parasite. In this study, chemometric tools, such as, Principal Component Analysis (PCA) and Partial Least Squares Regression (PLS), were applied to a set of active trypanocidal N-Myristoyltransferase inhibitors. These tools were generated using the Pentacle software. The algorithm (AMANDA), the descriptors are calculated through the molecular interaction fields with the blocks: N1, O, TIP and N1, which allow extracting from them the most interesting regions. The PCA selected 507 descriptors and the scores plot clearly separated more active compounds from others. The first two PCs account for over 70% of data variance. The best PLS model, exhibits q2 = 0.762 and r2 = 0.867 and rext2 = 0.69. The results highlight the importance of acceptor hydrogen bonds regions. The importance of the metabolic cleavage of the methyl group attached to the nitrogen of pyrrole ring by N-dealkylation was observed.

Predicting Degradation Half-life of Organophosphorus Pesticides in Soil Using Three-Dimensional Molecular Interaction Fields

A simple and strong model, based on an alignment independent three-dimensional quantitative- structure activity relationships (3D-QSAR), is developed for prediction of degradation half-life (DT50) of 47 organophosphorus pesticides in soil. Molecular descriptors derived from 3D molecular interaction fields (MIF) were calculated using the GRIND methodology. Fractional factorial design (FFD) applied to feature selection and modeling of the relationship between selected descriptors and DT50 data was achieved using partial least squares regression. Validation and reliability of the obtained model were checked by the prediction of external test set cross-validation and chance correlation. The value of the determination coefficient (R2) was 0.817 for leave-one-out cross-validation procedure. The R2 values for the training and test sets were 0.951 and 0.893 respectively. The obtained model confirmed that size and shape of the molecules as well as hydrophobic interactions are the main parameters influencing the degradation half-life of organophosphorus pesticides in soil.