This document provides the program for a two-day conference on computational modeling of advanced materials. The program includes four sessions each day with speakers presenting on topics like titania in cement industry, multiscale modeling of energy storage materials, modeling electron transport in low-dimensional systems, modeling heterogeneous catalysts for Fischer-Tropsch synthesis and Ziegler-Natta systems, and modeling organic compounds on metal oxide surfaces. Coffee breaks are scheduled between sessions and a lunch and poster session are included each day. Chairpersons are designated for each session.

1. PROGRAM
Sponsored by

2. 2
THURSDAY OCTOBER 1ST
8:30-9:00 Registration
9:00-9:15 Opening session:
Dr. Jordi Alberch, Vice Chancellor, Universitat de Barcelona
Dr. Pere L. Cabot, Dean, faculty of Chemistry, universitat de
Barcelona
Dr. Francesc Illas, Universitat de Barcelona and XRQTC Director,
Spain
Session 1. Chairwoman: Dr. Nuria Lopez, Senior Group Leader, ICIQ, Spain
9:15-9:55 Titania in cement and construction industry: the contribution of
modeling
Dr Gianfranco Pacchioni, Professor, University of Milano Bicocca,
Italy.
9:55-10:35 Multiscale modelling of advanced materials with applications in
energy storage, military defence and carbon nanoscience
Dra. Elena Bichoutskaia, Professor, University of Nottingham,
United Kingdom
10:35-11:10 Electron transport in low-dimensional systems for electronic and
optoelectronic device simulations
Dr. Albert Cirera, Professor, University of Barcelona, Spain
11:15-11:45 Coffee-Break
Session 2. Chairman: Dr. Daniel Fernández Hevia, INAEL Electrycal Systems
S.A., Toledo, Spain
11:45-12:25 Modeling-Guided Catalyst Design for Fischer-Tropsch synthesis:
Structure, Activity, Selectivity and Stability
Dr. Mark Saeys, Professor, University of Ghent.
12:25-13:05 Modeling the industrially relevant heterogeneous Ziegler-Natta
catalytic systems
Dr. Luigi Cavallo, Professor, King Abdullah University of Science
and Technology

3. 3
13:05-13:45 DFT studies of organic compounds over metal oxide surfaces
Dr. Hicham Idriss, Research Fellow, SABIC Saudi Basic Industries
Corporation, Saudi Arabia.
13:45-15:15 Lunch networking and Poster Session
Session 3. Chairwoman: Dra. Mariona Sodupe, Professor, Universitat
Autònoma Barcelona, Spain
15:15-15:55 Quantum chemistry meets polymer reaction engineering.
Dr. Peter Deglmann, Manager research scientist, BASF SE,
Germany.
15:55-16.35 Molecular dynamics explorations of active site structure in
designed and evolved enzymes
Dra. Silvia Osuna, Research Scientist, IQCC Institute, University of
Girona, Spain
16:35-17:00 Coffee-Break
Session 4. Chairman: Dr. Ramón Crehuet, Scientist, IQAC-CSIC, Spain
17:00-17:40 Biohybrids as novel catalysts: On the role of molecular modeling
Dr. Jean Didier Marechal, Lecturer of Physical Chemistry,
Universitat Autonoma de Barcelona, Spain
17:40-18:20 Chemical interaction of DNA with complex minerals
(hydroxyapatite)
Dr. Pau Turon, R&D, Regulatory Affairs and Quality Director, B.
Braun Surgical, S.A, Spain.

4. 4
FRIDAY OCTOBER 2nd
9:00-9:30 Registration
Session 1. Chairwoman: Dr. Mireia Olivella García, Professor, Vic
University, Spain
9:30-10:10 Understanding ligand binding, receptor selectivity and
pharmacological profiles on GPCRs from computer simulations
Dr. Hugo Gutierrez de Teran, Researcher, Uppsala Universitet,
Sweden.
10:10-10:50 Structural and dynamic basis of G protein-coupled receptor
activation
Dr. Xavier Deupí, Senior Scientist, Paul Scherrer Institute,
Switzerland.
10:50-11:20 Coffee-Break
Session 2. Chairman: Dr. Leonardo Pardo, Professor, Universitat Autonoma
Barcelona, Spain
11:20-12:00 Integrating Chemical and Biological Data for Compound
Selection and Mode-of-Action Analysis
Dr. Andreas Bender, Lecturer, University of Cambridge, United
Kingdom.
12:00-12:40 Discovery of non-competitive pharmacological chaperones
using structure-based methods
Dra. Elena Cubero, Senior Scientist, Minoryx Therapeutics,
Barcelona, Spain
12:40-14:00 Cocktail Lunch networking and Poster Session
Session 2. Chairman: Dr. Gianni De Fabritiis, Associate Professor,
Universitat Pompeu Fabra, Spain
14:00-14:40 Structural chemogenomics databases to better understand
protein-ligand interactions
Dr. Iwan de Esch, Full Professor, Medicinal Chemistry, VU
University of Amsterdam.

5. 5
14:40-15:20 Fragment Libraries at Astex and their Application to PPI Targets
Dr. Gianni Chessari, Director of Computational Chemistry, Astex
Pharmaceuticals, Cambridge, UK.
15:20-15:30 Delivery of Prizes for the Poster Session Contest and Concluding
remarks

6. 6
Titania in cement and construction industry: the contribution
of modeling
Gianfranco Pacchoni
Dipartimento di Scienza dei Materiali, Università di Milano-Bicocca,
Via R. Cozzi, 55, 20125, Milano, Italy – gianfranco.pacchioni@unimib.it
Titania is an essential component of devices of new generation for
photocatalysis and solar energy conversion. Its special behavior under
illumination is at the basis of several practical applications like self-
cleaning and self-sterilizing surfaces, superhydrophilicity, corrosion
protection, etc. Most of these effects are observed under ultra-violet (UV)
light and efforts are now oriented to the preparation of visible light
photoactive titania via doping and nanostructuring. In this talk we will
review the most recent advances in this field, with particular attention to
concrete examples of applications of this material in buildings, roads,
hospitals, smart-windows for self-cleaning and energy savings. We will
address the basic mechanisms which are responsible for the photoactivity
of titania and the role of ab initio modeling for the cement industry. In
particular, we will discuss the current strategies to obtain doped titania
nanoparticles as additives for cement active under visible solar light.

7. 7
Multiscale modelling of advanced materials with applications
in energy storage, military defence and carbon nanoscience
Elena Bichoutskaia
School of Chemistry, University of Nottingham,
University Park, Nottingham NG7 2RD, Nottingham, United Kingdom
Elena.Bichoutskaia@nottingham.ac.uk; +44 115 846 8465
In this talk we overview recent advances in multiscale modelling of novel
materials with particular emphasis on applications in (1) selective sorption
of carbon dioxide and methane gas in metal-organic frameworks1,2; (2)
mechanical behavior of lightweight high performance ceramic/metal
composites under static and dynamic (shock wave propagation)
loading3,4; electron beam irradiation induced processes in transmission
electron microscopy5,6.
References
1) S. Yang, X. Lin, W. Lewis, M. Suyetin, E. Bichoutskaia et al. Nature
Materials 11, 710 (2012).
2) Y. Yan, M. Suyetin, E. Bichoutskaia, A. J. Blake, D. R. Allan, S. A. Barnett,
M. Schröder, Edge Article, Chemical Science 4, 1731 (2013).
3) E. I. Volkova, A. Jones, R. Brooks, Y. Zhu, E. Bichoutskaia, Physical
Review B 86, 104111 (2012).
4) E. I. Volkova, A. Jones, R. Brooks, Y. Zhu, E. Bichoutskaia, Composite
Structures 96, 601 (2013).
5) S. T. Skowron, I. Lebedeva, A. Popov, E. Bichoutskaia, Feature Article,
Nanoscale 5, 6677 (2013).
6) A. Santana, A. Zobelli, J. Kotakoski, A. Chuvilin, E. Bichoutskaia, Physical
Review B 87, 094110 (2013).

8. 8
Optoelectronic Simulations for Quantum Dot based Devices
Illera S., Garcia N., Prades J. D and Cirera A.
MIND/IN2UB Departament d’Electrònica, Universitat de Barcelona, c/
Martí i Franquès 1, E-08028 Barcelona, Spain. acirera@ub.edu
Strong confined structures, such as the Quantum Dots (QDs), were used as
promising nanostructures to develop the third generation of photovoltaic
solar cells due to their size dependent energy band gap and the increased
optical absorption. These devices are composed by a large array of
embedded QDs in an insulator matrix as a top structure of a classical p-n
junction creating a tandem solar cell. Within this structure, two different
optical absorption energy edges are obtained increasing the efficiency of
the cell. However, the efficient extraction of the photogenerated carriers
in the QD matrix imposes new technological and material requirements.
Besides, an electron transport capable to deal with these large QDs arrays
is also necessary.
Here, we present an electronic transport model based on Transfer
Hamiltonian Formalism and rate equations to describe the ballistic charge
transport in QDs embedded in an insulator matrix1. This methodology was
compared to NEGFF reproducing the same theoretical trends (2) and it
also demonstrated that can be easily scalable for large systems (3). Two
unique features of this transport model are: (i) the model is based on just
a few basic material parameters and on the device geometry; (ii) it is
simple enough to tackle problems involving large number of Qd, which is
the case of real devices. Moreover, it is compatible with ab initio theories
taking advantage of the atomistic calculations in order to accurately
describe the Qd electrical properties as we have demonstrated (4,5).
Once the electronic transport model was presented and validated, the
light interaction was also included making possible to describe and
simulate optoelectronic QD based devices. Thus, a complete and valuable
theoretical tool based on low-level material and geometrical parameters
are developed which can be used to design and predict the optoelectronic
response of these devices.
1) S. Illera, J. D. Prades, A. Cirera and A. Cornet EPL 98, 17003 (2012).

9. 9
2) S. Illera, N. Garcia-Castello, J. D. Prades and A. Cirera, J. Appl. Phys 112,
093701 (2012).
3)S. Illera, J. D. Prades and A. Cirera, J. Appl. Phys. 117, 174307 (2015).
4)N. Garcia-Castello, S. Illera, R. Guerra, J. D. Prades, S. Ossicini and A.
Cirera, Phys. Rev B 88, 075322 (2013).
5)N. Garcia-Castello, S. Illera, J.D. Prades,, S. Ossicini, A. Cirera and R.
Guerra, Nanoscale 7, 12564 (2015).

10. 10
Modeling-Guided Catalyst Design for Fischer-Tropsch
synthesis: Structure, Activity, Selectivity and Stability
Mark Saeys
Laboratory for Chemical Technology, Ghent University, Belgium
Catalyst design and kinetic modeling often start from molecular-scale
hypotheses about the reaction mechanism, the structure of the active
sites and the nature of the rate and selectivity determining steps.
Computational catalysis has become a crucial tool to analyze molecular-
scale concepts and elucidate their electronic origin. In combination with
characterization and experimental kinetic validation, insights gained from
computational catalysis can be translated all the way to the industrial
scale. This pas-de-deux between experiment and theory is becoming the
new paradigm in catalyst design and kinetic modeling, both in academia
and in industry.
In this presentation, I will illustrate how this approach can contribute to
different aspect of catalysis research. The nature of catalytically active
sites under reaction conditions often differs dramatically from the clean
ideal surface. Using operando computational catalysis and insights into
chemical bonding, we showed that the spontaneous formation of Co
nano-islands during FT synthesis is driven by the stability of unusual sigma-
aromatic, square planar carbon species. Insight into the structure of the
active sites provides the basis to elucidate the reaction mechanism. Again
using operando computational catalysis, we developed a novel kinetic
model that agrees with the experimentally measured kinetic parameters.
This in turn forms the basis for to design catalyst with enhanced selectivity
and stability. The success of this approach is illustrated with the discovery
of a boron promotor that enhances the stability of cobalt catalysts during
Fischer-Tropsch synthesis of clean fuels by an order of magnitude.
References
Zhuo, Borgna, Saeys, J Catal 297, 217, (2013)
Banerjee, Kuipers, Van Bavel, Saeys, ACS Catal., (2015)
Tan, Chang, Borgna, Saeys, J. Catal., 280, 50 (2011)

11. 11
Modeling the industrially relevant heterogeneous Ziegler-
Natta catalytic systems
Luigi Cavallo
King Abdullah University of Science and Technology (KAUST), Physical
Sciences and Engineering Division, Kaust Catalysis Center, Thuwal 23955-
6900, Saudi Arabia.
luigi.cavallo@kaust.edu.sa
Despite of polyolefin commodities have a huge economic impact, with
total yearly volume of 106 tons and a billionaire market, knowledge of the
active site of Ziegler-Natta (ZN) catalysts at molecular level remains
elusive. This limited comprehension is due to the complex nature of ZN-
catalysts, although only four ingredients are fundamental to compose an
industrial catalyst: i) the inert MgCl2 support; ii) the catalytically active
TiCl4 adsorbed on the MgCl2 surfaces; iii) an Al-alkyl, typically AlEt3, to
activate the adsorbed TiCl4; iv) a Lewis base, either monodentate or
bidentate, to improve catalytic performance by increasing the amount and
stereoregularity of the produced polypropylene.
Due to the difficulties in the experimental characterization of these
catalysts, remarkable advances in our comprehension of Ziegler-Natta
catalysts have been achieved via computational chemistry, which has been
used to test the validity of models proposed on the basis of experiments,
as well as to explore new models driven by computational evidences.
In this communication we will give an overview of the computational work
in the field, from the stability of different perfect and defective (104) and
(110) facets of the MgCl2 support, on the adsorption of Lewis bases on
these facets of the MgCl2 support with a possible impact on the
morphology of the formed MgCl2 crystallites, to the adsorption of TiCl4 on
perfect and defective facets of the MgCl2 support, to the stereoselectivity
of possible active sites on both perfect and defective surfaces.

12. 12
Figure 1. Model of a MgCl2 monolayer, with indication of the (104) and
(110) lateral cuts.

13. 13
DFT studies of organic compounds over metal oxide surfaces
Hamdan Al-Ghamdia, Y. Al-Salika, Paul Bagus (b) and Hicham Idriss (a)
a) SABIC-CRI at KAUST, Saudi Arabia.
b) University of Northern Texas, Denton, TX, USA
Surface reactions of metal oxides are relevant to many catalytic processes
related to renewables and petrochemical industries. In this work,
examples of our studies linking computational results to experimental
ones are given for metal oxides model surfaces. In particular, we are
focusing on TiO2, CeO2, and UO2 surface or bulk interactions with organic
compounds or water. TiO2 is used as it is the prototype semiconductor for
photocatalytic water splitting [1], CeO2 is mostly considered for its oxygen
transport properties [2] and UO2 because of its unique chemical reactions
(due in part to its 5f orbitals) [3]. The mode of interaction of organic
adsorbates, used as sacrificial agents, with the surface of TiO2, during
water splitting to hydrogen, is crucial to understand the relevant surface
coverage under reaction conditions and its effect on the overall reaction
rate. In the case of CeO2 we focus on the effect of doping with metal
cations in order to reduce the energy needed to create oxygen vacancies
via charge transfer mechanism [4, 5]. A correlation is established between
the effect of dopants on lowering the energy needed for the creation of
oxygen vacancies and thermal hydrogen production from water [6]. In
addition, an example of comparing the electronic core level of the Ce3d,4d
lines experimentally and those computed using ab initio methods [4, 7] is
given.
[1] A. Kudo, Y. Miseki, Chem. Soc. Rev., 2009, 38, 253–278
[2] M. B. Watkins, A. S. Foster, A. L. Shluger, J. Phys. Chem. C 2007, 111,
15337-15341
[3] H. Idriss, Surf. Sci. Rep. 2010, 5, 67-109
[4] Y. Al-Salik, I. Al-Shankiti, H. Idriss, J. Electron Spectrosc Relat Phenom,
2013, 194, 66–73
[5] B. E. Hanken, T. Y. Shvareva, N. Grønbech-Jensen, C. R. Stanek, M. Asta,
A. Navrotsky, Phys. Chem. Chem. Phys., 2012, 14, 5680–5685
[6] J. Scaranto, H. Idriss Top. Catal., 2015, 58, 143–148

14. 14
[7] P. S. Bagus, C. J. Nelin, Y. Al-Salik, E. S. Ilton, H. Idriss, Surf. Sci. in press
doi:10.1016/j.susc.2015.06.002
Quantum Chemistry Meets Polymer Reaction Engineering
Peter Deglmann, Volker Settels
BASF SE, Advanced Materials & Systems Research,
Carl-Bosch-Str. 38, 67056 Ludwigshafen, Germany
The architecture and thus the properties of a polymer depend in a
complex way on the conditions applied within the polymerization process,
e.g. temperature, reaction medium, feed of reactants, reactor type (batch,
semibatch, continuous). Therefore it is not surprising that a simulation of
polymerization processes is of enormous industrial importance. One key
ingredient in such simulations represents the knowledge of rate
coefficients of all potentially relevant elementary reactive steps involved.
Whereas it is a standard task to monitor quantities like the overall
conversion during a polymerization process, it is highly difficult – if not
impossible – to experimentally measure all elementary rate coefficients
individually. For this reason it is very desirable to be able to predict them
via ab-initio calculations.
In this presentation, strategies and challenges for such a computation of
rate coefficients in the condensed phase (encountered e.g. upon solution
or bulk polymerization) are discussed. One huge obstacle for a direct
quantitative prediction of reaction kinetics represent the exponential
dependence on both energy and entropy of activation. Whereas for gas
phase reactions of small molecules quantum chemical predictions have
reached and even well bypassed the limit of chemical accuracy (1
kcal/mol), this is typically not the case for reactions in solution. Thus, a
reliable calculation of solvation thermodynamics represents a critical issue
when applying quantum chemistry to real world problems. The COSMO-RS
method is presented here as a convenient access to Gibbs free energies of
solvation as – like the quantum chemical calculation itself – it does not
require any chemistry specific parameterization. Furthermore, as will be
shown, automation of the resulting elaborate workflows represents an
important feature to productively employ quantum chemistry in an
industrial environment.

15. 15

16. 16
Molecular Dynamics Investigations of Active Site Structure in
Designed and Laboratory-generated Enzymes
Sílvia Osuna,a,b) Gonzalo Jiménez-Osés,b) and K.N. Houkb)
a) Institut de Química Computacional i Catàlisi and Departament de
Química, Universitat De Girona, Spain
b) Department of Chemistry and Biochemistry, University of California, Los
Angeles (UCLA), USA
In this study, the use of molecular dynamics (MD) simulations to reveal
how mutations alter the structure and organization of enzyme active sites
is presented.[1] As initially proposed by Pauling, and elaborated by many
others since then, biocatalysis is efficient when the catalytic residues in
the active site of an enzyme are in optimal positions for transition state
stabilization. Using MD simulations, we explore the dynamical pre-
organization of the active sites of designed and evolved enzymes, by
analyzing the fluctuations between active and inactive conformations
normally concealed to static crystallography. MD shows how the various
arrangements of active site residues influence the free energy of the
transition state, and relates the populations of the catalytic
conformational ensemble to enzyme activity (see Figure 1). The
importance of dynamics in evaluating a series of computationally designed
and experimentally evolved enzymes for the Kemp elimination, a popular
subject in the enzyme design field, is first presented. Finally, we show how
microsecond MD has been used to uncover the role of remote mutations
on the active site dynamics and catalysis of a transesterase, LovD, a useful
commercial catalyst for the production of the drug simvastatin.[2]

17. 17
Figure 1: Correlation between the population of the triad in catalytically
competent conformations, and catalytic activities of the LovD mutants.
[1] S. Osuna, G. Jiménez-Osés, E. L. Noey, K. N. Houk, Acc. Chem. Res.
2015, 48, 1080-1089.
[2] G. Jiménez-Osés, S. Osuna, X. Gao, M. R. Sawaya, L. Gilson, S. J. Collier,
G. W. Huisman, T. O. Yeates, Y. Tang, K. N. Houk, Nat. Chem. Biol. 2014,
10, 431-436.

18. 18
Biohybrids as novel catalysts: On the role of molecular
modeling
Jean-Didier Maréchal
Departament de Química, Universitat Autònoma de Barcelona, Edifici C.n.,
08193 Bellaterra, Spain
Merging synthetic compounds with biological entities is a concept
increasingly explored to expand the scope of enzymatic reactions.
Amongst the most interesting biohybrids constructed to date are those
that consist in the integration of organometallic scaffolds into biological
frameworks (i.e., protein, DNA or peptides). The resulting artificial
metalloenzymes are interesting at least in two aspects: 1) they lead to
biocompatible catalysts that absent from the biological reign and 2) they
allow catalytic specificities and selectivities that are unreachable by
standard homogenous approaches. Both advantages are opening new
horizons for greener approaches in chemical synthesis.
Despite the major successes of several groups in developing efficient
biometallic hybrids, the prediction and analysis of their molecular
behavior still represents a complex exercise. The lack of evolutionary
pressure generally leads to a first generation of molecules with relatively
low stability and difficult structural characterization. Moreover, the
identification of the best complementarities among biological receptor,
organometallic cofactors and substrates implies a major combinatorial
space that challenges biochemical and chemical intuitions. Virtually,
molecular modeling could be of the best allies in this field since
computational methodologies can deal with processes related to
molecular recognition and catalytic mechanisms. However, the modeling
of artificial metaloenzymes stands out of the scope of standard
approaches and novel methodologies are needed.
In the recent years, our group designed, tested and applied a series of
computational strategies in the field of artificial bioinorganics. From
protein-ligand dockings to multi-scale approaches, our work allowed to
better understand the molecular mechanism of artificial metalloenzymes,
provided information on how they mechanistically diverge from natural

19. 19
ones and gave some hints on how we could computationally guide the
design of new candidates. In this talk, I will briefly present the
underpinning concepts of our strategies and the most important results
obtained so far both from pure computational works and in collaboration
with experimentalists.
Literature:
V. Muñoz Robles, E. Ortega-Carrasco, L. Alonso-Cotchico, J. Rodríguez-
Guerra, A. Lledós, A. and J.-D. Maréchal, ACS Catal. 2015, 5, 2469.

20. 20
Chemical interaction of DNA with complex minerals
(hydroxyapatite)
Pau Turon Dols
Research and Development, Regulatory Affairs and Quality Managament
dept.
Centre of Excellence Closure Technologies. B. Braun Surgical, S.A.
Ctra. Terrassa, 121, Rubí, Barcelona, Spain – pau.turon@bbraun.com
In the last decade, the combination of hydroxyapatite (HAp) with
biopolymers has captured the attention of the researchers, mainly due to
its medical applications. The system DNA-HAp (hydroxyolite) presents
outstanding features. Recently, it has been confirmed at atomistic level
that DNA templates HAp crystal and, additionally, HAp includes ions in its
lattice, such as Mg2+, that are able to stabilize DNA modulating its
structure and dynamics. We highlight that hydroxyapatite encapsulates
DNA and protects it against environmental aggressions. The main
consequence is that the information that DNA contains is preserved
through time. DNA remains functional, encapsulated inside HAp, ready to
be reintroduced into the mainstream of life. Cell transfection process,
intended to incorporate a plasmid into the cell nucleus, can be achieved
through hydroxyolites but its efficiency is low. Atomistic molecular
dynamics simulations can shed light on how these processes work and
how they can be improved.

21. 21
Understanding ligand binding, receptor selectivity and
pharmacological profiles on GPCRs from computer
simulations
Hugo Gutiérrez de Terán
Department of Cell and Molecular Biology, Uppsala University. BMC, Box
596, 751 24, Uppsala (Sweden). Hugo.gutierrez@icm.uu.se
Receptors belonging to the superfamily of G-protein-coupled receptors
(GPCRs) play a key role in the cellular communication, a reason why they
are of the highest interest as drug targets in a widespread repertoire of
diseases. The recent availability of crystal structures, combined with the
outcome of molecular biology experiments such as site-directed
mutagenesis, provide excellent starting points to examine in deep detail
the molecular determinants of ligand binding.
In our research group, we combine homology modeling, protein-ligand
docking and molecular dynamics simulations to assess in the design of
compounds with specific selectivity and pharmacological profiles for
different GPCRs. In this presentation, I will introduce our recently
developed computational scheme, based on free energy perturbation
(FEP) simulations, to evaluate the effects of single point mutations on
ligand binding.1-3 This method is generalized to deal with any amino acid
mutation, and is illustrated in the investigation of both agonist and
antagonist binding in different GPCRs, namely adenosine A2A receptor
and the neuropeptide Y1 receptor, with excellent results. This
computational protocol is useful not only for the characterization of ligand
selectivity in GPCRs, but also to address problems of drug resistance in
pathogens as well as individual responses to drug treatment due to
genetic variation.
Finally, I will show how a combination of accurate homology modeling,
ligand docking and molecular dynamics simulations can successfully
explain the pharmacological profiles (i.e., agonist versus antagonist) and
selectivity issues on GPCRs, which is illustrated in the case of angiotensin
receptors.4

22. 22
References
1. Keranen, H.; Åqvist, J.; Gutiérrez-de-Terán, H. ChemComm (2015),
51:3522
2. Keranen, H.; Gutiérrez-de-Terán, H.; Åqvist, J. PlOS One (2014)
9:e108492
3. Boukharta, L.; Gutiérrez-de-Terán, H.; Åqvist, J. PlOS Comp. Biol (2014)
10:e1003585.
4. Sallander, J.; Wallinder, C.; Hallberg, A.; Åqvist, J.; Gutiérrez-de-Terán,
H.; submitted.

23. 23
Detection of ligand-induced conformational changes in GPCR
activation by NMR
Xavier Deupi
Condensed Matter Theory Group and Laboratory of Biomolecular
Research, Paul Scherrer Institute, WHGA/114, 5232 Villigen PSI,
Switzerland.
G protein-coupled receptors (GPCRs) are a large family of transmembrane
proteins that trigger cellular signaling responses upon binding of
extracellular ligands. Thus, GPCRs act as transmission devices between the
environment and the cell interior and, due to this key physiological role,
they constitute one of the most important pharmaceutical targets.
However, despite recent breakthroughs in GPCR crystallography, the
structural and mechanistic aspects of GPCR activation by drugs are not yet
well understood. This is partly due to missing dynamical information,
which can, in principle, be provided by NMR. However, only limited
information of functional relevance on few side chain sites of eukaryotic
GPCRs has been obtained to date.
Together with the group of Prof. Grzesiek (Biozentrum, University of
Basel), we have recently shown that receptor motions can be followed in
stabilized mutants of the β1-adrenergic receptor (β1AR). We observe that
the response to various ligands is heterogeneous in the vicinity of the
extracellular binding pocket, but gets transformed into a homogeneous
readout at the intracellular side of the receptor.
By analyzing the effect of several mutations, we conclude that even a fully
stabilized receptor is able to undergo certain activating motions, but the
fully active state is only reached in presence of (a) two specific key
residues (Y5.58 and Y7.53), and (b) a stabilizing partner in the cytoplasmic
side (e.g. an antibody that mimics the cognate G protein).
Our analysis allows us to identify crucial connections in the allosteric signal
transmission pathway of ligand-induced GPCR activation, and represents a
general experimental method to delineate signal transmission networks at
high-resolution in GPCRs.

24. 24
Integrating Chemical and Biological Data for Compound
Selection and Mode-of-Action Analysis
Andreas Bender
Centre for Molecular Informatics, Department of Chemistry, University of
Cambridge, Lensfield Road, Cambridge CB2 1EW. ab454@cam.ac.uk
Recent technological advancement in the field of health science brought
with it a deluge of both chemical and biological data that is in need of
interpretation. This information can be used to generate better
understanding of drivers of disease – such as chemical, biological and/or
genetic markers – but possibly even more importantly it can be used to
design more efficacious and safe medicines prospectively. Still, currently
data is often not used effectively to reach this goal, partly due to technical
reasons (the sheer amount of data), but even more fundamentally also
due to lack of data integration (e.g. inconsistent identifiers), and our often
crude understanding of what in particular biological readouts actually
mean in order to make better decisions based on them.
In our research group, which currently comprises about 20 members, we
aim to address the above point by integrating data from across the
chemical and biological domains in order to improve decision making in
the drug discovery process. To this end, project-specific data is employed
(often in collaboration with pharmaceutical companies, such as
AstraZeneca, Johnson&Johnson, Eli Lilly, BASF, Unilever, Aboca, and
others) in order to address one of two principal aims:
Firstly, we aim to decide which compound is most likely to possess desired
efficacy and the relatively best side effect profile, given the data at hand.
Secondly, we aim to understand the mode-of-action, or more generally
biomodulatory capabilities, of a small molecule by integrating diverse data
(such as on-target bioactivity data and RNA-Seq data, but also others).
Given a large number of collaborations with both academic groups as well
as pharmaceutical, chemical, and consumer goods companies we have
accumulated significant expertise in the area of chemical and biological

25. 25
data integration in order to support decision making in the drug discovery
process in the above two areas (but also beyond).
Our presentation will conceptually describe which types of data we are
currently integrating, our plans for future projects, as well as case studies
where data from across the chemical and biological domains was able to
improve compound design, as well as enhance our understanding of a
more complete bioactivity profile of chemical structures.

26. 26
Discovery of non-competitive pharmacological chaperones
using structure-based methods
Dra. Elena Cubero, Senior Scientist, Minoryx Therapeutics, Barcelona,
Spain
Many monogenic diseases are characterized by the presence of missense
mutations which affect the folding and stability of a key enzyme, which is
then degraded by the quality control machinery of the cell. This deficiency
of enzymatic activity is what originates the diseases. Pharmacological
chaperones are a new class of small molecule drugs, which showed great
potential for the treatment of such genetic diseases. They prevent the
degradation of unstable enzymes with missense mutations, thus
producing an enzyme enhancement effect normalizing enzymatic activity,
which reverses and/or prevents disease progression.
There are several examples where pharmacological chaperones showed
excellent efficacy in preclinical models. Nonetheless, success in clinical
development has been somehow modest. Pharmacological chaperone
therapy has been largely experimented on the lysosomal storage diseases,
starting with the pioneer work on Fabry disease in 1999.
Most Pharmacological chaperones (PC’s) described until now are substrate
analogues which bind to the active site of the target protein.
Consequently, such PC’s also inhibit the target protein at higher
concentrations thus rendering a narrow therapeutic window and have
poor drug-like properties. Through our proprietary technology platform
SEE-Tx™, we identify a new generation of non-substrate competitive
pharmacological chaperones which potentially offer a much broader
therapeutic window. What’s more, such compounds are not substrate
analogues, thus presenting much better drug-like properties, particularly
for indications with CNS involvement. Here we present our methodology
to identify non-competitive pharmacological chaperones applied to the
enzyme beta-galactosidase, whose deficiency is related with GM1
Gangliosidosis and Morquio B.

27. 27
Structural chemogenomics databases to better understand
protein-ligand interactions
Iwan de Esch
Faculteit der exacte wetenschappen, VU University of Amsterdam,
Netherland. i.de.esch@vu.nl
The high number of protein structures that are co-crystallized with ligands
makes it possible to study cross-family ligand binding features in
unprecedented detail. We present a thorough analysis of kinase-ligand
and phosphodiesterase-ligand interaction patterns. For this extensive
analysis, we have constructed a database of all available aligned human
kinase-ligand co-crystal structures and all phosphodiesterase-ligand co-
crystal structures that are present in the Protein Data Bank (PDB). Next,
we used molecular Interaction Finger Prints (IFP) to annotate the different
protein-ligand interaction features. The resulting databases contain
consistent alignments and numbering these two protein classes and
enable the identification of family- or group-specific interaction features
and classification of ligands according to their binding modes. We will
illustrate how systematic mining of protein-ligand interaction space gives
novel insights into how conserved and selective interaction hot spots can
accommodate the large diversity of chemical scaffolds. These studies lead
to an improved understanding of the structural requirements of ligand
binding that will be useful in future drug discovery, drug design studies
and poly-pharmacology approaches.

28. 28
Fragment libraries at Astex and their application to protein-
protein interaction targets
Gianni Chessari
Astex Pharmaceuticals, 436 Cambridge Science Park, Milton Road,
Cambridge, CB4 0QA, UK
Fragment-based methods are now well established for medicinal
chemistry programmes and small molecule drug discovery campaigns.
Successful Fragment-Based Drug Discovery (FBDD) requires a reliable and
effective fragment library, sensitive screening methods and expertise in
structure based drug design to transform weak fragment hits into potent
leads. At Astex we have invested time and resources to optimise and
integrate each key aspect of FBDD into our screening platform, which has
delivered several compounds into the clinic. Here we describe how we
have evolved and improved our fragment library over time using
information from multiple fragment screening campaigns and thousands
of proprietary protein-fragment crystal structures. We will show how the
fragment hit rate varies with lipophilicity and heavy atom count. We will
also discuss the concept of minimal binding pharmacophore elements for
fragments and show how they have been used to drive library
enhancement. Finally, we will present examples of Astex Protein-Protein
Interaction projects, where fragment hits have been developed into
potent lead molecules.

29. 29