Alina Bora

ChemProt: a disease chemical biology database

Systems pharmacology is an emergent area that studies drug action across multiple scales of complexity, from molecular and cellular to tissue and organism levels. There is a critical need to develop network-based approaches to integrate the growing body of chemical biology knowledge with network biology. Here, we report ChemProt, a disease chemical biology database, which is based on a compilation of multiple chemical–protein annotation resources, as well as disease-associated protein–protein interactions (PPIs). We assembled more than 700 000 unique chemicals with biological annotation for 30 578 proteins. We gathered over 2-million chemical–protein interactions, which were integrated in a quality scored human PPI network of 428 429 interactions. The PPI network layer allows for studying disease and tissue specificity through each protein complex. ChemProt can assist in the in silico evaluation of environmental chemicals, natural products and approved drugs, as well as the selection of new compounds based on their activity profile against most known biological targets, including those related to adverse drug events. Results from the disease chemical biology database associate citalopram, an antidepressant, with osteogenesis imperfect and leukemia and bisphenol A, an endocrine disruptor, with certain types of cancer, respectively. The server can be accessed at http://www.cbs.dtu.dk/services/ChemProt/.

PLS-DA - Docking Optimized Combined Energetic Terms (PLSDA-DOCET) Protocol: A Brief Evaluation

Docking studies have become popular approaches in drug design, where the binding energy of the ligand in the active site of the protein is estimated by a scoring function. Many promising techniques were developed to enhance the performance of scoring functions including the fusion of multiple scoring functions outcomes into a so-called consensus scoring function. Hereby, we evaluated the target oriented consensus technique using the energetic terms of several scoring functions. The approach was denoted PLSDA-DOCET. Optimization strategies for consensus energetic terms and scoring functions based on ROC metric were compared to classical rigid docking and to ligand-based similarity search methods comprising 2D fingerprints and ROCS. The ROCS results indicate large performance variations depending on the biological target. The AUC-based strategy of PLSDA-DOCET outperformed the other docking approaches regarding simple retrieval and scaffold-hopping. The superior performance of PLSDA-DOCET protocol relative to single and combined scoring functions was validated on an external test set. We found a relative low mean correlation of the ranks of the chemotypes retrieved by the PLSDA-DOCET protocol and all the other methods employed here.

Mixed Quaternary Ammonium and Phosphonium Salts Bound to Macromolecular Supports for Removal Bacteria from Water

This paper deals with synthesis and characterization of mixed quaternary ammonium and phosphonium salts grafted on macromolecular supports by polymer-analogous trans-quaternization reactions. The degrees of functionalization with quaternary mixed ammonium and phosphonium groups are relatively high, ranging from 0.09 to 1.285 mmoles of functional groups/gram of copolymer, ensuring a sufficient concentration of active centers per unit mass of copolymer and being well suited for application as antibacterial agents.

Synthesis of Mixed Alkylphosphites and Alkylphosphates

Some mixed phosphites having two different alkyl chain were obtained as forerunners for mixed phosphates Mixed dialkyl phosphates were obtained in good yields (40-80%) by phase transfer catalysis in liquid-liquid sistem, starting from different dialkyl phosphites and aliphatic alcohols. The reaction conditions were optimized in order to obtain good yields in phosphites and phosphates respectively. Compounds were analyzed by IR, P 31 -NMR.

Wittig and Wittig-Horner reactions under phase transfer catalysis conditions

Wittig and Wittig-Horner reactions are favorite tools in preparative organic chemistry. These olefination methods enjoy widespread and recognition because of their simplicity, convenience, and effciency. Phase transfer catalysis (PTC) is a very important method in synthetic organic chemistry having many advantages over conventional, homogenous reaction procedures. In this paper, we attempt to summarize the aspects concerning Wittig and Wittig-Horner reactions that take place under phase transfer catalysis conditions.

ColBioS-FlavRC: A Collection of Bioselective Flavonoids and Related Compounds Filtered from High-Throughput Screening Outcomes

Flavonoids, the vastest class of natural polyphenols, are extensively investigated for their multiple benefits on human health. Due to their physicochemical or biological properties, many representatives are considered to exhibit low selectivity among various protein targets or to plague high-throughput screening (HTS) outcomes. The aim of this study is to highlight reliable, bioselective compounds sharing flavonoidic scaffolds in HTS experiments. A filtering scheme was applied to remove undesired flavonoids (and related compounds) from confirmatory PubChem bioassays. A number of 433 compounds addressing various protein targets form the core of the collection of bioselective flavonoids and related compounds (ColBioS-FlavRC). With an additional set of 2908 inactive related compounds, ColBioS-FlavRC offers the grounds for method optimization and validation. We exemplified the use of ColBioS-FlavRC by pharmacophore modeling, subsequently (externally) validated for virtual screening purposes. The early enrichment capabilities of the pharmacophore hypotheses were measured by means of the median exponential retriever operating curve enrichment (MeROCE), a suited metric in comparative evaluations of virtual screening methods. ColBioS-FlavRC is available in the Supporting Information and is freely accessible for further studies.

Retrospective group fusion similarity search based on eROCE evaluation metric.

In this study, a simple evaluation metric, denoted as eROCE was proposed to measure the early enrichment of predictive methods. We demonstrated the superior robustness of eROCE compared to other known metrics throughout several active to inactive ratios ranging from 1:10 to 1:1000. Group fusion similarity search was investigated by varying 16 similarity coefficients, five molecular representations (binary and non-binary) and two group fusion rules using two reference structure set sizes. We used a dataset of 3478 actives and 43,938 inactive molecules and the enrichment was analyzed by means of eROCE. This retrospective study provides optimal similarity search parameters in the case of ALDH1A1 inhibitors.

Predictive Models for Fast and Effective Profiling of Kinase Inhibitors

In this study we developed two-dimensional pharmacophore-based random forest models for the effective profiling of kinase inhibitors. One hundred seven prediction models were developed to address distinct kinases spanning over all kinase groups. Rigorous external validation demonstrates excellent virtual screening and classification potential of the predictors and, more importantly, the capacity to prioritize novel chemical scaffolds in large chemical libraries. The models built upon more diverse and more potent compounds tend to exert the highest predictive power. The analysis of ColBioS-FlavRC (Collection of Bioselective Flavonoids and Related Compounds) highlighted several potentially promiscuous derivatives with undesirable selectivity against kinases. The prediction models can be downloaded from www.chembioinf.ro .

PLS and shape-based similarity analysis of maleimides – GSK-3 inhibitors

Abstract Context: Glycogen synthase kinase-3 (GSK-3) overactivity was correlated with several pathologies including type 2 diabetes mellitus, Alzheimer’s disease, cancer, inflammation, obesity, etc. Objective: The aim of the current investigation was to model the inhibitory activity of maleimide derivatives – inhibitors of GSK-3, to evaluate the impact of alignment on statistical performances of the Quantitative Structure--Activity Relationship (QSAR) and the effect of the template on shape-similarity – binding affinity relationship. Materials and methods: Dragon descriptors were used to generate Projection to Latent Structures (PLS) models in order to identify the structural prerequisites of maleimides to inhibit GSK-3. Additionally, shape/volume structural analysis of binding site interactions was evaluated. Results: Reliable statistics  = 0.938/0.920,  = 0.866/0.838 for aligned and alignment free QSAR models and significant (Pearson, Kendall and Spearman) correlations between shape/volume similarity and affinities were obtained. Discussion and conclusions: The crucial structural features modulating the activity of maleimides include topology, charge, geometry, 2D autocorrelations, 3D-MoRSE as well as shape/volume and molecular flexibility.

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.