<i>N,N</i>-bis-(dimethylfluorosilylmethyl)amides of <i>N</i>-organosulfonylproline and sarcosine: synthesis, structure, stereodynamic behaviour and <i>in silico</i> studies

(O→Si)-Chelate difluorides R3R2NCH(R1)C(O)N(CH2SiMe2F)2 (9a–c, R1R2 = (CH2)3, R3 = Ms (a), Ts (b); R1 = H, R2 = Me, R3 = Ms (c)), containing one penta- and one tetracoordinate silicon atoms were synthesized by silylmethylation of amides R3R2NCH(R1)C(O)NH2, subsequent hydrolysis of unstable intermediates R3R2NCH(R1)C(O)N(CH2SiMe2Cl)2 (7a–c) into 4-acyl-2,6-disilamorpholines R3R2NCH(R1)C(O)N(CH2SiMe2O)2 (8a–c) and the reaction of the latter compounds with BF3·Et2O. The structures of disilamorpholines 8a,c and difluoride 9a were confirmed by an X-ray diffraction study. According to the IR and NMR data, the O→Si coordination in solutions of these compounds was weaker than that in the solid state due to effective solvation of the Si–F bond. A permutational isomerisation involving an exchange of equatorial Me groups at the pentacoordinate Si atom in complexes 9a–c was detected, and its activational parameters were determined by 1H DNMR. In silico estimation of possible pharmacological effects and acute rat toxicity by PASS Online and GUSAR Online services showed a potential for their further pharmacological study

PREDICTION OF THE METABOLIC NETWORK FOR XENOBIOTICS IN THE HUMAN ORGANISM

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HOW SHOULD ONE USE AVAILABLE DATA TO BE SUCCESSFUL IN COMPUTER-AIDED SEARCH FOR NOVEL KINASE INHIBITORS?

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WAY2DRUG CHEMINFORMATICS PLATFORM FOR DRUG REPURPOSING

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Functional classification of proteins based on projection of amino acid sequences: application for prediction of protein kinase substrates

<p>Abstract</p> <p>Background</p> <p>The knowledge about proteins with specific interaction capacity to the protein partners is very important for the modeling of cell signaling networks. However, the experimentally-derived data are sufficiently not complete for the reconstruction of signaling pathways. This problem can be solved by the network enrichment with predicted protein interactions. The previously published <it>in silico </it>method PAAS was applied for prediction of interactions between protein kinases and their substrates.</p> <p>Results</p> <p>We used the method for recognition of the protein classes defined by the interaction with the same protein partners. 1021 protein kinase substrates classified by 45 kinases were extracted from the Phospho.ELM database and used as a training set. The reasonable accuracy of prediction calculated by leave-one-out cross validation procedure was observed in the majority of kinase-specificity classes. The random multiple splitting of the studied set onto the test and training set had also led to satisfactory results. The kinase substrate specificity for 186 proteins extracted from TRANSPATH^®database was predicted by PAAS method. Several kinase-substrate interactions described in this database were correctly predicted. Using the previously developed ExPlain™ system for the reconstruction of signal transduction pathways, we showed that addition of the newly predicted interactions enabled us to find the possible path between signal trigger, TNF-alpha, and its target genes in the cell.</p> <p>Conclusions</p> <p>It was shown that the predictions of protein kinase substrates by PAAS were suitable for the enrichment of signaling pathway networks and identification of the novel signaling pathways. The on-line version of PAAS for prediction of protein kinase substrates is freely available at <url>http://www.ibmc.msk.ru/PAAS/</url>.</p

Collaborative development of predictive toxicology applications

OpenTox provides an interoperable, standards-based Framework for the support of predictive toxicology data management, algorithms, modelling, validation and reporting. It is relevant to satisfying the chemical safety assessment requirements of the REACH legislation as it supports access to experimental data, (Quantitative) Structure-Activity Relationship models, and toxicological information through an integrating platform that adheres to regulatory requirements and OECD validation principles. Initial research defined the essential components of the Framework including the approach to data access, schema and management, use of controlled vocabularies and ontologies, architecture, web service and communications protocols, and selection and integration of algorithms for predictive modelling. OpenTox provides end-user oriented tools to non-computational specialists, risk assessors, and toxicological experts in addition to Application Programming Interfaces (APIs) for developers of new applications. OpenTox actively supports public standards for data representation, interfaces, vocabularies and ontologies, Open Source approaches to core platform components, and community-based collaboration approaches, so as to progress system interoperability goals

Calculation of substructural analysis weights using a genetic algorithm

This paper describes a genetic algorithm for the calculation of substructural analysis for use in ligand-based virtual screening. The algorithm is simple in concept and effective in operation, with simulated virtual screening experiments using the MDDR and WOMBAT datasets showing it to be superior to substructural analysis weights based on a naive Bayesian classifier

Combined effects of antihypertensive medications: computer prognosis

Modern concept of arterial hypertension (AH) combined therapy is based on using agents with various pharmacotherapeutic mechanisms of action. Despite the impressive number of clinical trials conducted, the real-life basis for combined therapy is mostly clinician’s empirical experience. Computer program and database PASS (Prediction of Activity Spectra of Substances; website http://www.ibmc.msk.ru/PASS) gives an opportunity to predict potential activity spectra for specific chemical structures. PASS could be used for assessment of: a) main pharmaco-therapeutic effects; b) biochemical mechanisms underlying these effects; c) possible adverse (toxic) effects. Using this approach for some antihypertensives (lisinopril, amlodipine, trandolapril, etc.) provided information on medication action spectra and cellular-biochemical mechanisms. Reliable prognostic data were obtained for additional, unstudied before, pharmaco-therapeutic effects. These vasodilatation-independent effects are linked to chemical structure specifics. PASS program provides clinicians with unique information on potential medication polymodality and adverse effects in treating AH and its complications