Synthesis, biological evaluation, X-ray molecular structure and molecular docking studies of RGD mimetics containing 6-amino-2,3-dihydroisoindolin-1-one fragment as ligands of integrin αIIbβ3

AbstractA series of novel RGD mimetics containing phthalimidine fragment was designed and synthesized. Their antiaggregative activity determined by Born’s method was shown to be due to inhibition of fibrinogen binding to αIIbβ3. Molecular docking of RGD mimetics to αIIbβ3 receptor showed the key interactions in this complex, and also some correlations have been observed between values of biological activity and docking scores. The single crystal X-ray data were obtained for five mimetics

QSAR Modeling: Where Have You Been? Where Are You Going To?

Quantitative Structure-Activity Relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limitations, successes, and failures. In this paper, we discuss: (i) the development and evolution of QSAR; (ii) the current trends, unsolved problems, and pressing challenges; and (iii) several novel and emerging applications of QSAR modeling. Throughout this discussion, we provide guidelines for QSAR development, validation, and application, which are summarized in best practices for building rigorously validated and externally predictive QSAR models. We hope that this Perspective will help communications between computational and experimental chemists towards collaborative development and use of QSAR models. We also believe that the guidelines presented here will help journal editors and reviewers apply more stringent scientific standards to manuscripts reporting new QSAR studies, as well as encourage the use of high quality, validated QSARs for regulatory decision making

EFFICIENCY STUDY APPLICATION OF CIRCULAR MOLECULAR MODEL TO QSAR ANALYSIS

New method of structural descriptors generation for the solving of QSAR tasks has been developed by authors. It is shown that mentioned approach allows generation of the set of structural parameters with the quite adequate level of description of molecules and their properties. Efficiency of developed approach was shown base on ACE ingibitors

The Investigation of Acute Toxicity of Esters on the Base 2D Simplex Representation of Molecular Structure

The investigation of influence of the molecular structure of esters on acute toxicity has been carried out by 2D simplex representation of molecular structure with help of approaches Partial Least Squares. The quite satisfactory QSAR (Quantitative Structure Activity Relationship) models has been obtained. On the basis of the obtained models the structural fragments raising toxicity are revealed. In addition relative influence of some physical-chemical factors on variation of acute toxicity estimated on the base of QSAR models.Исследовано влияние молекулярной структуры сложных эфиров на острую токсичность при помощи 2D-симплексного представления молекулярной структуры и метода Partial Least Squares. Были получены адекватные QSAR (Quantitative Structure-Activity Relationship) модели. На основе полученных моделей определены вклады структурных фрагментов в острую токсичность сложных эфиров. Кроме того, относительное влияние некоторых физико химических факторов на изменение острой токсичности было оценено на основе QSAR моделей

The Investigation of Acute Toxicity of Esters on the Base 2D Simplex Representation of Molecular Structure

The investigation of influence of the molecular structure of esters on acute toxicity has been carried out by 2D simplex representation of molecular structure with help of approaches Partial Least Squares. The quite satisfactory QSAR (Quantitative Structure Activity Relationship) models has been obtained. On the basis of the obtained models the structural fragments raising toxicity are revealed. In addition relative influence of some physical-chemical factors on variation of acute toxicity estimated on the base of QSAR models.Исследовано влияние молекулярной структуры сложных эфиров на острую токсичность при помощи 2D-симплексного представления молекулярной структуры и метода Partial Least Squares. Были получены адекватные QSAR (Quantitative Structure-Activity Relationship) модели. На основе полученных моделей определены вклады структурных фрагментов в острую токсичность сложных эфиров. Кроме того, относительное влияние некоторых физико химических факторов на изменение острой токсичности было оценено на основе QSAR моделей

QSAR Modeling and Prediction of Drug–Drug Interactions

Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in the U.S. with more than 100 000 deaths per year. As up to 30% of all ADRs are believed to be caused by drug–drug interactions (DDIs), typically mediated by cytochrome P450s, possibilities to predict DDIs from existing knowledge are important. We collected data from public sources on 1485, 2628, 4371, and 27 966 possible DDIs mediated by four cytochrome P450 isoforms 1A2, 2C9, 2D6, and 3A4 for 55, 73, 94, and 237 drugs, respectively. For each of these data sets, we developed and validated QSAR models for the prediction of DDIs. As a unique feature of our approach, the interacting drug pairs were represented as binary chemical mixtures in a 1:1 ratio. We used two types of chemical descriptors: quantitative neighborhoods of atoms (QNA) and simplex descriptors. Radial basis functions with self-consistent regression (RBF-SCR) and random forest (RF) were utilized to build QSAR models predicting the likelihood of DDIs for any pair of drug molecules. Our models showed balanced accuracy of 72–79% for the external test sets with a coverage of 81.36–100% when a conservative threshold for the model’s applicability domain was applied. We generated virtually all possible binary combinations of marketed drugs and employed our models to identify drug pairs predicted to be instances of DDI. More than 4500 of these predicted DDIs that were not found in our training sets were confirmed by data from the DrugBank database

Design, Virtual Screening, and Synthesis of Antagonists of α_IIbβ₃ as Antiplatelet Agents

This article describes design, virtual screening, synthesis, and biological tests of novel α_IIbβ₃ antagonists, which inhibit platelet aggregation. Two types of α_IIbβ₃ antagonists were developed: those binding either closed or open form of the protein. At the first step, available experimental data were used to build QSAR models and ligand- and structure-based pharmacophore models and to select the most appropriate tool for ligand-to-protein docking. Virtual screening of publicly available databases (BioinfoDB, ZINC, Enamine data sets) with developed models resulted in no hits. Therefore, small focused libraries for two types of ligands were prepared on the basis of pharmacophore models. Their screening resulted in four potential ligands for open form of α_IIbβ₃ and four ligands for its closed form followed by their synthesis and <i>in vitro</i> tests. Experimental measurements of affinity for α_IIbβ₃ and ability to inhibit ADP-induced platelet aggregation (IC₅₀) showed that two designed ligands for the open form <b>4c</b> and <b>4d</b> (IC₅₀ = 6.2 nM and 25 nM, respectively) and one for the closed form <b>12b</b> (IC₅₀ = 11 nM) were more potent than commercial antithrombotic Tirofiban (IC₅₀ = 32 nM)