Exploring DrugCentral: from molecular structures to clinical effects.

DrugCentral, accessible at https://drugcentral.org , is an open-access online drug information repository. It covers over 4950 drugs, incorporating structural, physicochemical, and pharmacological details to support drug discovery, development, and repositioning. With around 20,000 bioactivity data points, manual curation enhances information from several major digital sources. Approximately 724 mechanism-of-action (MoA) targets offer updated drug target insights. The platform captures clinical data: over 14,300 on- and off-label uses, 27,000 contraindications, and around 340,000 adverse drug events from pharmacovigilance reports. DrugCentral encompasses information from molecular structures to marketed formulations, providing a comprehensive pharmaceutical reference. Users can easily navigate basic drug information and key features, making DrugCentral a versatile, unique resource. Furthermore, we present a use-case example where we utilize experimentally determined data from DrugCentral to support drug repurposing. A minimum activity threshold t should be considered against novel targets to repurpose a drug. Analyzing 1156 bioactivities for human MoA targets suggests a general threshold of 1 µM: t = 6 when expressed as - log[Activity(M)]). This applies to 87% of the drugs. Moreover, t can be refined empirically based on water solubility (S): t = 3 - logS, for logS < - 3. Alongside the drug repurposing classification scheme, which considers intellectual property rights, market exclusivity protections, and market accessibility, DrugCentral provides valuable data to prioritize candidates for drug repurposing programs efficiently.

DrugCentral 2023 extends human clinical data and integrates veterinary drugs.

DrugCentral monitors new drug approvals and standardizes drug information. The current update contains 285 drugs (131 for human use). New additions include: (i) the integration of veterinary drugs (154 for animal use only), (ii) the addition of 66 documented off-label uses and iii) the identification of adverse drug events from pharmacovigilance data for pediatric and geriatric patients. Additional enhancements include chemical substructure searching using SMILES and 'Target Cards' based on UniProt accession codes. Statistics of interests include the following: (i) 60% of the covered drugs are on-market drugs with expired patent and exclusivity coverage, 17% are off-market, and 23% are on-market drugs with active patents and exclusivity coverage; (ii) 59% of the drugs are oral, 33% are parenteral and 18% topical, at the level of the active ingredients; (iii) only 3% of all drugs are for animal use only; however, 61% of the veterinary drugs are also approved for human use; (iv) dogs, cats and horses are by far the most represented target species for veterinary drugs; (v) the physicochemical property profile of animal drugs is very similar to that of human drugs. Use cases include azaperone, the only sedative approved for swine, and ruxolitinib, a Janus kinase inhibitor.

Homology Modeling and Molecular Docking Approaches for the Proposal of Novel Insecticides against the African Malaria Mosquito (Anopheles gambiae).

Vector-borne infectious diseases are responsible for the deaths of over 700,000 people annually, than 400,000 of them resulting from malaria. The mosquito Anopheles gambiae is one of the dominant vector species of human malaria transmission. A significant issue of the conventional insecticides which target the arthropod borne infectious diseases is their induced resistance. To overcome this inconvenience, insecticides with new modes of action are required. One of the most promising targets for the development of new potential insecticides as evidenced by current studies is the D1-like dopamine receptor (DAR). To get a deeper understanding of the structural information of this receptor, the 3D homology model was built. The possible sites within the protein were identified and the most probable binding site was highlighted. The homology model along with a series of DAR antagonists with known activity against Anopheles gambiae larvae were used in docking experiments to gain insight into their intermolecular interactions. Furthermore, virtual screening of the natural compounds from the SPECS database led to the prediction of toxicity and environmental hazards for one potential new insecticide against the Anopheles gambiae mosquito.

Application of Molecular Docking, Homology Modeling, and Chemometric Approaches to Neonicotinoid Toxicity against Aphis craccivora.

Neonicotinoids are known as effective pesticides against various insect species. They can harm useful insects including honeybees, with a relatively low threat to nontarget organisms and the environment. This paper presents combined methods to explore the insecticidal activity of neonicotinoids with diverse scaffolds, active against Aphis craccivora. Pharmacophore, molecular docking into the active site of nicotinic acetylcholine receptor homology model, and linear and non-linear regression approaches were used to find new insecticide candidates. The potential toxic effects against honeybees were evaluated using the molecular docking in the active site of the new Aphis mellifera homology model. Four new untested compounds were assigned as insecticide candidates, active against Aphis craccivora with less potential toxic effects for honeybees. This approach may be an effective strategy to design environmentally friendly insecticides against the cowpea aphid.

New Efficient Adsorbent Materials for the Removal of Cd(II) from Aqueous Solutions.

The rapid increase of industrial activities leads to serious environmental pollution, especially, in aqueous systems and particularly with heavy metals. Cadmium, one of the most poisonous elements, is rapidly accumulated in the human body, therefore, the efficient removal of cadmium ions from wastewater is an urgent need. Coordination networks (CNs) and its subdivision metal-organic frameworks (MOFs), are structured porous composites which present various special properties. In this work two CNs were used as adsorbent materials for the removal of Cd(II) ions from aqueous solutions. By the reaction of CoSO4·7H2O and NiSO4·7H2O with N,N-bis(phosphonomethyl)glycine (Gly) in hydrothermal conditions two CNs-Co-Gly and Ni-Gly- were synthesized, respectively. Cadmium adsorption onto the studied CNs was conducted in batch mode, and the effect of pH, initial concentration, contact time, temperature and sorbent weight on the sorption process were investigated. Parametric Method 3 (PM3)semi-empirical analyses of the CNs' structural properties were performed in order to predict the adsorption properties. For this reason, two octahedral models were calculated and computational predictions were compared with the experimental results. Both computational and experimental adsorption studies found that Ni-Gly presents higher affinity for cadmium ions. Moreover, the adsorbent materials can be readily regenerated and recycled without significant loss of cadmium uptake capacity.

Combined Experimental and Theoretical Insights into the Corrosion Inhibition Activity on Carbon Steel Iron of Phosphonic Acids.

The inhibition effect of N,N'-phosphonomethylglycine (PMG) and vinyl phosphonic acid (VPA) on the 3% NaCl acidic solution corrosion of carbon steel iron was studied at different immersion times by potentiodynamic polarization, electrochemical impedance spectroscopy, attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, and computational methods. It is found from the polarization studies that PMG and VPA behave as mixed-type inhibitors in NaCl. Values of charge transfer resistance (Rct) and double layer capacitance (Cdl) in the absence and presence of inhibitors are determined. The PMG and VPA inhibitors were capable of inhibiting the corrosion process up to ≈91% and ≈85%, respectively. In the presence of PMG, the synergic effect of chlorine ions was observed. Density functional theory (DFT) was engaged to establish the adsorption site of PMG, VPA, and their deprotonated states. For studied compounds, the resulted values of ELUMO, EHOMO, energy gap (∆E), dipole moment (µ), electronic hardness (η), global softness (σ), electrophilic index (ω), and the electronic potential map are in concordance with the experimental data results regarding their corrosion inhibition behavior and adsorption on the metal surface.

An Approach to Identify New Insecticides Against Myzus Persicae. In silico Study Based on Linear and Non-linear Regression Techniques.

Neonicotinoids are known to have high insecticidal potency, low mammalian toxicity and relatively tough activity for the development of resistance against aphids. A series of guadipyr insecticides, active against Myzus persicae was engaged in silico studies, based on Multiple Linear Regression (MLR), Partial Least Squares regression (PLS), Artificial Neural Networks (ANN), Support Vector Machine (SVM) and Pharmacophore modeling. Robust and predictive models were built using correlations between the insecticidal profile, expressed by experimental pLC50 values, and molecular descriptors, calculated from the energy optimized structures. Four new potential insecticides active against Myzus persicae and their predicted pLC50 toxicity values were reported for the first time. The models presented here can be used as an approach in the screening and prioritization of chemicals in a scientific and regulatory frame and for toxicity prediction.

Combined molecular docking and QSAR study of fused heterocyclic herbicide inhibitors of D1 protein in photosystem II of plants.

Cinnoline, pyridine, pyrimidine, and triazine herbicides were found be inhibitors of the D1 protein in photosystem II (D1 PSII) electron transport of plants. The photosystem II inhibitory activity of these herbicides, expressed by experimental [Formula: see text] values, was modeled by a docking and quantitative structure-activity relationships study. A conformer ensemble for each of the herbicide structure was generated using the MMFF94s force field. These conformers were further employed in a docking approach, which provided new information about the rational "active conformations" and various interaction patterns of the herbicide derivatives with D1 PSII. The most "active conformers" from the docking study were used to calculate structural descriptors, which were further related to the inhibitory experimental [Formula: see text] values by multiple linear regression (MLR). The dataset was divided into training and test sets according to the partition around medoids approach, taking 27% of the compounds from the entire series for the test set. Variable selection was performed using the genetic algorithm, and several criteria were checked for model performance. WHIM and GETAWAY geometrical descriptors (position of substituents and moieties in the molecular space) were found to contribute to the herbicidal activity. The derived MLR model is statistically significant, shows very good stability and was used to predict the herbicidal activity of new derivatives having cinnoline, indeno[1.2-c]cinnoline-ll-one, triazolo[1,5-a] pyridine, imidazo[1,2-a]pyridine, triazine and triazolo[1,5-a] pyrimidine scaffolds whose experimental inhibitory activity against D1 PSII had not been determined up to now.

Quantitative estimation of pesticide-likeness for agrochemical discovery.

BACKGROUND: The design of chemical libraries, an early step in agrochemical discovery programs, is frequently addressed by means of qualitative physicochemical and/or topological rule-based methods. The aim of this study is to develop quantitative estimates of herbicide- (QEH), insecticide- (QEI), fungicide- (QEF), and, finally, pesticide-likeness (QEP). In the assessment of these definitions, we relied on the concept of desirability functions. RESULTS: We found a simple function, shared by the three classes of pesticides, parameterized particularly, for six, easy to compute, independent and interpretable, molecular properties: molecular weight, logP, number of hydrogen bond acceptors, number of hydrogen bond donors, number of rotatable bounds and number of aromatic rings. Subsequently, we describe the scoring of each pesticide class by the corresponding quantitative estimate. In a comparative study, we assessed the performance of the scoring functions using extensive datasets of patented pesticides. CONCLUSIONS: The hereby-established quantitative assessment has the ability to rank compounds whether they fail well-established pesticide-likeness rules or not, and offer an efficient way to prioritize (class-specific) pesticides. These findings are valuable for the efficient estimation of pesticide-likeness of vast chemical libraries in the field of agrochemical discovery. Graphical AbstractQuantitative models for pesticide-likeness were derived using the concept of desirability functions parameterized for six, easy to compute, independent and interpretable, molecular properties: molecular weight, logP, number of hydrogen bond acceptors, number of hydrogen bond donors, number of rotatable bounds and number of aromatic rings.

Modeling of 2-pyridin-3-yl-benzo[d][1,3]oxazin-4-one derivatives by several conformational searching tools and molecular docking.

Neutrophil elastase, a serine proteinase from the chymotrypsin family, has been the object of comprehensive experimental and theoretical studies to develop efficient human neutrophil elastase inhibitors. The serine protease has been linked to the pathology of a variety of inflammatory diseases, making it an attractive target for the development of anti-inflammatory compounds. In this work, we have built a common binding model of the 2-pyridin-3-yl-benzo[d][1,3]oxazin-4-one derivatives into the human neutrophil elastase binding site. This was accomplished through a comparative conformational analysis (using OMEGA, HYPERCHEM, and MOPAC software) of 2-pyridin-3-yl-benzo[d][1,3]oxazin-4-one inhibitors followed by rigid and flexible molecular docking (by the FRED and GLIDE programs) into the target protein. We conclude that OMEGA software generates the most representative conformers to model the protein-ligand interactions.

A QSAR study using MTD method and Dragon descriptors for a series of selective ligands of α2C adrenoceptor.

A QSAR (quantitative structure-activity relationship) analysis of the binding affinities for a series of 43 quinoline derivatives active against the alpha2C adrenergic receptor was performed. Multiple linear regressions (MLR) were obtained using the minimum topological difference (MTD) descriptor and various descriptors which were calculated with Dragon3.0. The variable selection was performed either through the forward stepwise method or backward stepwise combined with forward stepwise methods, providing two satisfactory models. The first one, obtained as a result of the forward stepwise method, contains MTD, Mor24v, MATS5m, MATS7m, G3m, L1s, G_N_N descriptors, while the other one obtained through the combination of backward and forward stepwise methods contains the following descriptors: MTD, ZM2V, X5V, IC5, MATS4v, and E2u. Both models highlight the importance of steric interactions and can be used as tools for predicting the binding affinity of related compounds.