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XRQTC (Reference Network on Theretical and Computational Chemistry)

Company Profile:
The Reference Network on Theoretical and Computational Chemistry (XRQTC) is the organization that coordinates research groups of excellence in this area of knowledge in Catalonia.

The XRQTC offers the services of more than 220 researchers to develop new ideas and projects assuring innovation, competitiveness and optimal results for companies.

Areas of knowledge and sectors for which we provide services:

• Biotechnology
• Chemistry
• Cosmetics
• Microelectronics and sensors
• Polymers
• Semiconductors
• The environment
• The food industry
• The petrochemical industry
• The pharmaceutical industry
Profiltitel

Polymorphism Prediction in Crystal Systems of Technological Interest

What we offer:
Predicting the most probable polymorphic forms of a molecular crystal is a field which has been studied extensively in recent years. As a result, a large number of predictive software applications have been developed and are currently available. However, the performance and the applicability of these emerging applications are still limited, as it has been demonstrated by the results of tests performed and published by the Cambridge Crystallographic Data Centre.

The research centre which is member of the Reference Network on Theoretical and Comptutaional Chemistry (XRQTC) has identified the source of error which is mainly caused by the use of atom-atom intermolecular potentials, which are limited when describing weak hydrogen bonds or Van der Waals interactions. Thus, the integration of intermolecular potential within the calculations delivers similar results to those obtained with advanced ab initio calculations. For the predictive studies Pixel intermolecular potentials are quantified. The code developed PixCryPar is an MPI-parallelized version that allows to predict in a cost-effective way the most likely crystal structures in space groups adopted by the substances.

To perform a prediction satisfactorily, one has to describe the interactions within the crystal, i.e. the intermolecular interactions. By means of PixCryPar these potential interactions are described using new generation algorithms, known as potential-pixel, which are based on the quantification of the molecular electron density concentrated ab initio for a given volume or pixel, and compute power as a sum of intermolecular interactions between pixels. This allows a very precise description of intermolecular energy for any molecular crystal or co-crystal.

The predictive method has been tested for a set of 36 molecular crystals of varied structure, complexity, and application (drugs, dyes, etc.). The results show excellent reproducibility and accordance with those obtained experimentally.

Currently, the team is optimizing the algorithm to gain a powerful and reliable software that would allow companies from the pharmaceutical sector, and from other sectors for which the solid state of a substance has a strong influence on the production processes, to predict the crystalline structure of solids.

What are we looking for:
We are looking for companies interested co-developing together the software and we are interested also in provide these services to companies.

Keywords:
  • ] Pharmaceutics
  • ] Computational chemistry


Collaboration sought:
  • Technical Co-operation


Responsible

Ms PhD Monica Fernandez

R&D Project Promoter
Profiltitel

Computer Aided Design of Drugs and Flavour Enhancers

What we offer:
A Catalan research group has developed a new methodology to enhance the efficiency of existing drugs, or to find out substances that could be used as flavour-enhancer.

It is possible to identify compounds of different chemical nature that could act as high affinity activators of the flavour receptors, and then develop new high intensity palatability enhancers.

The basic concept used to design new drugs and flavour enhancers is that the macromolecular response is governed by the direct (microscopic) interactions between the substrate (drug, taste enhancer) and the biochemical receptor. More strongly bound substrate corresponds to a stronger response and hence an enhanced taste perception.

The research group has developed a methodology of study to predict whether certain chemical substitutions on core molecules increase or decrease the interaction with flavour receptors, and therefore it predicts changes in taste perception. For this assessment, the system provides calculations of atomic contact based on force field interactions to obtain qualitative and quantitative data of the substrate-receptor binding energy. A wide variety of substrates of diverse chemical nature have been tested and classified through this method

This methodology has other possible applications, as the design of biomarkers and the study of other natural pathways which understanding could be achieved through the study of molecular interaction substrate-receptor (e.g. human neurodegenerative diseases originated through human aging).

What are we looking for:
We are looking for technical cooperation.

Potential applications areas of the technology are:
- development of new drugs and optimization of drugs candidates
- development and optimization of flavour enhancers
- development of new biomarkers

Keywords:
  • ] Pharmaceutics
  • ] Computational chemistry
  • ] Biology/Biotechnology
  • ] Biochemistry/Biophysics
  • ] Food additives / Ingredients / Fuctional Food


Collaboration sought:
  • FP7 Project
  • Technical Co-operation


Responsible

Ms PhD Monica Fernandez

R&D Project Promoter
Profiltitel

Modeling of silica supported catalyst as an additional tool for catalyst characterization and optimization

What we offer:
Nowadays many computational groups around the world perform systematic DFT (Density Functional Theory) studies of the factors that control the activity of a group of catalyst in a specific reaction in solution. The same is applicable for reactions catalyzed by heterogeneous catalyst, especially when using metallic or metal oxide surface. However, silica is still the most common support in heterogeneous catalysis and, due to its amorphous nature, only very few research groups have developed sufficiently realistic models for catalyst characterization.

A Catalan research group member of the Reference Network on Theoretical and Computational Chemistry (XRQTC) has developed a new methodology to characterize and optimize all types of silica supported catalyst.

Catalyst characterization out of experimental results is difficult to the low catalyst concentration and the amorphous nature of the support. They have constructed a solid model for amorphous silica surfaces that, combined with the experimental data, facilitates the identification of the active species characteristics, including its electronic structure.

Moreover, the group has developed small scaled but still reliable models suitable for the exploration of the full reaction mechanism including, if necessary, the most relevant deactivation pathways. This allows them to determine the key factors controlling catalyst activity and proposing basic principles for further developing the catalyst. The group is also able to model metal cations and transition metal complexes and their reactivity which give them the capabilities of studying supported metal cations and transition metal complexes on surfaces and their reactivity

As an added value, the group works closely with experimentalist with deep knowledge in this field who are able to suggest and advice what strategies to follow in order to achieve a catalyst of favorable characteristics.
.

What are we looking for:
The group is seeking technical cooperation to further develop the methodology or to look for field applications.

Responsible

Ms PhD Monica Fernandez

R&D Project Promoter
Profiltitel

Design and optimization of catalysers for enantio-selective processes via quantum-mechanical calculations

What we offer:
It can be used to design more efficient catalysers or catalysers than can treat particularly tricky substrates.
It is compatible with a great variety of methods for producing thin films (evaporation techniques as well as drop-casting or spin-coating processes) and Langmuir-Blodgett films.
They can be absorbed into a nanocrystalline
semiconductor or anchored in polymeric substrates without aggregation.
No parameterization is required: no empirical
or semi-empirical data are necessary.
It avoids the alignment stage that is necessary in many CoMFA approximations, and which require knowledge of the interactions between the catalyser
and the substrate, and can be problematic with structures that are highly flexible.
It successfully predicts R- and S configurations.
It successfully predicts enantiomeric excesses.

What are we looking for:
We are looking to collaborate with the pharmaceutical industry and the fine chemistry sector.

Keywords:
  • ] Computational chemistry


Collaboration sought:
  • FP7 Project
  • Research and development
  • Technical Co-operation


Responsible

Ms PhD Monica Fernandez

R&D Project Promoter
Profiltitel

OPTIMIZATION OF PROCESSES AND MATERIALS RELATED TO THE ENVIRONMENT AND NANOTECHNOLOGY THROUGH MOLECULAR MODELLING

What we offer:
The molecular modeling tools (theory and simulation) are applied to the systematic improvement of certain processes and materials related to the environment and nanotechnology. These techniques are used to optimize processes and products understanding the microscopic phenomena that govern the macroscopic behavior of the system.

What is it for?
• To discriminate between different processes or materials for any application specified a priori.
• For a more detailed design and optimization.

Description of the technology
• Use of alternative solvents for different applications, including ionic liquids and supercritical fluids.
• Systematic search of new adsorbents for optimal gas barriers separation, with particular emphasis on adsorption / separation of CO2 and other greenhouse gases.
• Design, characterization and applications of nanoparticles and self-assembly of molecules on surfaces and other materials for various industrial applications.

What are we looking for:
We are looking for partners interested in the technology.

Keywords:
  • ] Materials technology
  • ] Computational chemistry


Collaboration sought:
  • FP7 Project
  • Research and development
  • Technical Co-operation


Responsible

Ms PhD Monica Fernandez

R&D Project Promoter
Profiltitel

Computational Advice on the toxicity of substances for REACH compliance

What we offer:
Services are offered at the netx three levels:
Level I:
Library Search for Data
Level II:
prediction of Endpoints system experts or published models.
Level III:
development of new levels

What are we looking for:
We are looking for companies interested or companies or research centres interested in further development.

Keywords:
  • ] Computational chemistry


Collaboration sought:
  • FP7 Project
  • Research and development
  • Technical Co-operation


Responsible

Ms PhD Monica Fernandez

R&D Project Promoter
Profiltitel

Biomedical informatics /System Biology

What we offer:
Advanced statistics for clinical decision. Data clasification. Active participation in the design of the system for information retrieval from the whole set of different data inputs. Multivariate statistical analysis design. Implementation and testing of multicriteria decision analysis (MCDA) techniques. Automatic workflow and pipelines creation.
Deterministic and stochastic modelling of biological networks. Interest in multiscale problems. Advanced statistical tools for network analysis.

What are we looking for:
Research groups or companies interested on this service.

Keywords:
  • ] Biology/Biotechnology


Responsible

Ms PhD Monica Fernandez

R&D Project Promoter
Profiltitel

Predicción asistida por ordenador del metabolismo de fármacos

What we offer:
Las propiedades ADMEs (de Adsorption, Disposition, Metabolism and Excretion) de compuestos químicos candidatos a fármacos son unas de las variables fundamentales para definir falta de actividad clínica así que parte de sus posibles efectos adversos. Fuerte de una gran experiencia en el uso de técnicas de modelización molecular en este ámbito, ofrecemos un acercamiento basado en el uso de técnicas de dockings proteína-ligando para la predicción de los perfiles metabólicos de compuestos químicos.
La particularidad de los acercamientos que se utilizaron en estos estudios reside en el uso de técnicas computacionales de docking proteína-ligando. Estas técnicas que simulan explícitamente los complejos enzima-ligando (métodos de tipo structure based), son relativamente más lento que las de tipo QSAR (ligand based) en que descriptores fisicoquímicos de los compuestos se relacionan con valores fisiológicos o in vitro. No obstante, no solo permiten la predicción de los valores de fijación o de los productos de metabolismos sino también de estipular sobre posibles optimizaciones de los fármacos, facilitar el entendimiento de aquellas interacciones claves en los fenómenos de reconocimientos proteína-ligando así que dar una base molecular a los perfiles farmacogenómicos de los fármacos (o compuestos candidatos a serlo). En este sentido cabe destacar que estas técnicas son más eficientes para hacer una relación entre genoma y metabolismo o en predecir posible interacciones fármaco-fármaco. Para esta propuesta, es también importante mencionar que las técnicas que se usan son cálculos de energía muy afinados.

What are we looking for:
La presente propuesta puede ser de interés para cualquier grupo que decidiera entender los mecanismos de metabolismo de su compuesto al nivel molecular, efectuar un screening pre-síntesis o pre-clínico de sus compuestos con enzimas metabólicas o bien generar el perfil metabólico de sus compuestos. Además, es posible disponer de perfiles farmacogenómicas de compuestos de interés. Finalmente, es de destacar que el acercamiento actual, centrado en metabolismo de fase I, se puede extender a otras fases del metabolismo de fármacos. Proponemos ayudar aquellos grupos que estén interesados en disponer de tales perfiles antes o en paralelo de trabajos experimentales.

Keywords:
  • ] Pharmaceutics
  • ] Computational chemistry


Collaboration sought:
  • FP7 Project
  • Research and development
  • Technical Co-operation


Responsible

Ms PhD Monica Fernandez

R&D Project Promoter
Profiltitel

Theoretical Photocatalysis

What we offer:
Theoretical and computationals studies
on the systems of interest can be carried out which will help to understand and to develop new and more
efficient photocatalyst for CO2 reduction.
We have extensive expertise in the study of the electronic structure of oxides including non reducible oxides such as MgO or SiO2, reducible oxide such as CeO2 and TiO2 and magnetic oxides such as NiO or Fe2O3. Our expertise is related to bulk properties but also to surfaces including the theoretical study of reactions ocurring at surfaces. In the past few years we have developed expertise in modelling atomic and electronic structure of oxide nanoparticles (TiO2, SiO2 and CeO2) which, together to our knowledge on the study of excited stated provide a unique and excellent way to analyze the properties of photocatalytic systems. In this sense we will be able to study metal doping , size and morphology of nanoparticles and to provide information about the nature of the relevant excited states.

What are we looking for:
We would like to join a project with a research institution or a company where we can prove our models.

Responsible

Ms PhD Monica Fernandez

R&D Project Promoter
Profiltitel

Heterogeneous Catalysis

What we offer:
The aim is to employ atomistic simulations to understand the mechanisms that govern chemical processes in heterogeneous catalysis. The analysis of reaction networks, activity/selectivity and stability issues and the final tests on the stability of the potential materials are fundamental to establish a solid background to determine when it can be considered as a catalyst candidate for a given chemical transformation.
We can provide databases for interesting materials including chemical properties and descriptors.

We are active in the following fields:
1) Atomistic simulations of reactions on metals, alloys, oxides, carbides, nitrides and mixed species: Activity and Selectivity of Catalysts as main research targets.

2) Micro-kinetic modelling of reactions.
3) Descriptor determination, database generation and high throughput computational screening for heterogeneous catalysts.
4) Descriptor determination, database generation and high throughput computational screening for molecular sensors and dyes for solar cells.
5) Stability indicators: Most likely composition under reaction conditions, lifetime indicators.

What are we looking for:
We are looking for companies or research groups interested in joint projects.

Keywords:
  • ] Materials technology
  • ] Computational chemistry


Collaboration sought:
  • FP7 Project
  • Research and development
  • Technical Co-operation


Responsible

Ms PhD Monica Fernandez

R&D Project Promoter
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