18 resultados para combinatorial chemistry
Resumo:
It is well known that ageing and cancer have common origins due to internal and environmental stress and share some common hallmarks such as genomic instability, epigenetic alteration, aberrant telomeres, inflammation and immune injury. Moreover, ageing is involved in a number of events responsible for carcinogenesis and cancer development at the molecular, cellular, and tissue levels. Ageing could represent a “blockbuster” market because the target patient group includes potentially every person; at the same time, oncology has become the largest therapeutic area in the pharmaceutical industry in terms of the number of projects, clinical trials and research and development (R&D) spending, but cancer remains one of the leading causes of mortality worldwide. The overall aim of the work presented in this thesis was the rational design of new compounds able to modulate activity of relevant targets involved in cancer and aging-related pathologies, namely proteasome and immunoproteasome, sirtuins and interleukin 6. These three targets play different roles in human cells, but the modulation of its activity using small molecules could have beneficial effects on one or more aging-related diseases and cancer. We identified new moderately active and selective non-peptidic compounds able to inhibit the activity of both standard and immunoproteasome, as well as novel and selective scaffolds that would bind and inhibit SIRT6 selectively and can be used to sensitize tumor cells to commonly used anticancer agents such gemcitabine and olaparib. Moreover, our virtual screening approach led us also to the discovery of new putative modulators of SIRT3 with interesting in-vitro and cellular activity. Although the selectivity and potency of the identified chemical scaffolds are susceptible to be further improved, these compounds can be considered as highly promising leads for the development of future therapeutics.
Resumo:
Combinatorial Optimization is becoming ever more crucial, in these days. From natural sciences to economics, passing through urban centers administration and personnel management, methodologies and algorithms with a strong theoretical background and a consolidated real-word effectiveness is more and more requested, in order to find, quickly, good solutions to complex strategical problems. Resource optimization is, nowadays, a fundamental ground for building the basements of successful projects. From the theoretical point of view, Combinatorial Optimization rests on stable and strong foundations, that allow researchers to face ever more challenging problems. However, from the application point of view, it seems that the rate of theoretical developments cannot cope with that enjoyed by modern hardware technologies, especially with reference to the one of processors industry. In this work we propose new parallel algorithms, designed for exploiting the new parallel architectures available on the market. We found that, exposing the inherent parallelism of some resolution techniques (like Dynamic Programming), the computational benefits are remarkable, lowering the execution times by more than an order of magnitude, and allowing to address instances with dimensions not possible before. We approached four Combinatorial Optimization’s notable problems: Packing Problem, Vehicle Routing Problem, Single Source Shortest Path Problem and a Network Design problem. For each of these problems we propose a collection of effective parallel solution algorithms, either for solving the full problem (Guillotine Cuts and SSSPP) or for enhancing a fundamental part of the solution method (VRP and ND). We endorse our claim by presenting computational results for all problems, either on standard benchmarks from the literature or, when possible, on data from real-world applications, where speed-ups of one order of magnitude are usually attained, not uncommonly scaling up to 40 X factors.
Resumo:
This doctorate was funded by the Regione Emilia Romagna, within a Spinner PhD project coordinated by the University of Parma, and involving the universities of Bologna, Ferrara and Modena. The aim of the project was: - Production of polymorphs, solvates, hydrates and co-crystals of active pharmaceutical ingredients (APIs) and agrochemicals with green chemistry methods; - Optimization of molecular and crystalline forms of APIs and pesticides in relation to activity, bioavailability and patentability. In the last decades, a growing interest in the solid-state properties of drugs in addition to their solution chemistry has blossomed. The achievement of the desired and/or the more stable polymorph during the production process can be a challenge for the industry. The study of crystalline forms could be a valuable step to produce new polymorphs and/or co-crystals with better physical-chemical properties such as solubility, permeability, thermal stability, habit, bulk density, compressibility, friability, hygroscopicity and dissolution rate in order to have potential industrial applications. Selected APIs (active pharmaceutical ingredients) were studied and their relationship between crystal structure and properties investigated, both in the solid state and in solution. Polymorph screening and synthesis of solvates and molecular/ionic co-crystals were performed according to green chemistry principles. Part of this project was developed in collaboration with chemical/pharmaceutical companies such as BASF (Germany) and UCB (Belgium). We focused on on the optimization of conditions and parameters of crystallization processes (additives, concentration, temperature), and on the synthesis and characterization of ionic co-crystals. Moreover, during a four-months research period in the laboratories of Professor Nair Rodriguez-Hormedo (University of Michigan), the stability in aqueous solution at the equilibrium of ionic co-crystals (ICCs) of the API piracetam was investigated, to understand the relationship between their solid-state and solution properties, in view of future design of new crystalline drugs with predefined solid and solution properties.