Highlighted works

Some of our latest publications.
Updated list here.

Directed Evolution of Artificial Imine Reductase

M. Hestericová, et al.
Angewandte, 2017 (IF: 11.9)

Design of an enantioselective artificial metallo-hydratase enzyme containing an unnatural metal-binding amino acid

L. Alonso-Cotchico, et al.
Chem Sci, 2017 (IF: 8.7)

Prediction of the interaction of metallic moieties with proteins: An update for protein-ligand docking techniques

G. Sciortino, et al.
J Comp Chem, 2017 (IF: 3.2)

Elucidating the 3D structures of Al (iii)–Aβ complexes: a template free strategy based on the pre-organization hypothesis

J. I. Mujika, et al.
Chem Sci, 2017 (IF: 8.7)

GaudiMM: A modular multi-objective platform for molecular modeling

J. Rodríguez-Guerra, et al.
J Comp Chem, 2017 (IF: 3.2)

PyChimera: Use UCSF Chimera modules in any Python 2.7 project

J. Rodríguez-Guerra, et al.
Bioinformatics, 2018 (IF: 7.3)

What is InSiliChem?

Led by Dr. Jean-Didier Maréchal, InsiliChem is a team that focuses on the modeling of systems at the interface between chemistry and biology. Our primary interests are chemobiological hybrids like artificial enzymes, biosensors and biomarkers and more particularly those involving transition metal moieties. We have a large network of collaborations worldwide both with experimental and theoretical groups leader in these fields.

We also intensively work on structural bioinformatics and computational chemistry methodological developments that could sustain our investigation and our multi-scale procedures. Most of our efforts are performed using Python as a principal scripting language. In the last months we have published more than 25 new modeling packages in GitHub. Most of them are GUIs designed for UCSF Chimera, with whom we have a long and strong collaboration.

InsiliChem is located at the Chemistry Department of the Universitat Autònoma de Barcelona (Spain).

The Mission

Our mission is to develop and apply molecular modeling tools for the design of pharmacologically or biotechnologically active molecules.

The Strategy

The computation of complex systems is generally a long shot. In most of our research, more than one method is needed for an accurate prediction i.e. Quantum Chemistry and large scale Molecular Dynamics.

Since feeding molecular modeling programs from one to another is of the most tedious and source of errors in computational chemistry, we and others are betting on multiscale/integrative/multilevel approaches that conveniently combine in a unique protocol.

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The Tools

Our software developments are centred on two axis:

  1. To accelerate our multiscale studies, we develop software and interfaces that could ease management of input and output files. In collaboration with the team of the UCSF Chimera, we are implementing novel interface between Homology Modeling, Molecular Dynamics, QM/MM, protein-ligand docking approaches.

  2. Most of our work also involve major exploration of chemical and conformational space. As current state-of-the-art programs do not consider both exploration spaces, we are intensively working on a genetic algorithm based architecture for this end.

The Systems

Artificial (Metallo)Enzymes

Biocatalysis aims at generating efficient, enantiospecific and environmentally friendly catalysts in order to surrogate standard organic protocols. The development of novel biocatalysts has therefore become a major focus of attention. We work on several key systems with potential applications in pharmacochemical and agrochemical industries. In particular, we work on artificial metaloenzyms obtained by the insertion of homogeneous catalysts into protein cavities (peroxidases, hydrogenases).


At the bridge between chemistry and biology, we recently entered in the particular areas of the recognition between metal cations and flexible ligands, more particularly natural or synthetic small size peptides (up to 20 residues). Our results are providing major molecular insights for the design of novel molecular scaffold enantioselective peptides as well as contributing to the worldwide effort in the fight against AD.

(Metalo)Drug Design and toxicology

We use our expertise on protein-ligand recognition processes on several biotechnological problems. One of our major objectives is to study and design metallodrugs. Another is to decode the fate of the drugs outside the standard drug-target framework. In particular, we are intending to decode off target interactions of anticancer compounds.

The Team

We are a young team of molecular modelers

Dr. Jean-Didier Maréchal

Team leader since 2009
Background: Physical Chemistry & Structural Bioinformatics
Field of research: Molecular modeling applied to Biotechnology.

Lur Alonso

PhD student since 2015
Background: Biology
Field of research: MM, QM and QM/MM applied to modeling of Cu catalysis and metaloenzymes.

Jaime Rodríguez-Guerra

PhD student since 2015
Background: Biotechnology
Field of research: Development a novel software platform for complex molecular design written in Python.

Giuseppe Sciortino

PhD student since 2016
Background: Chemistry
Field of research: Spectroscopy-integrated computational modeling of metallodrugs & enzymes.

Gantulga Norjmaa

PhD student since 2017
Background: Chemistry
Field of research: Molecular modeling of transition metal systems with QM/MM methods.

José Emilio Sánchez

PhD student since 2017
Background: Informatics
Field of research: Computational exploration of the chemical space in biomolecular systems.

Prof. Dr. Agustí Lledós

Group leader since 1990
Background: Chemistry
Field of research: Computational modeling of organometallic reactivity and homogeneous catalysis.

Current Students

Marta Gonzalvo (Chemistry Degree, UAB)
Daniel Viladrich (Maths & Physics Double Degree, UAB)
Mercè Alemany (M. Sc. in Bioinformatics, UAB)

Former Members

Daniel Soler
Martí Municoy
Jordi Guasp
Dr. Karel W. F. De Pourcq
Mireia Bertran
Laura Tiessler
Eric Mates
Lorea Velasco
Pablo Orenes


We work with institutions all around the world.

Contact us

You can drop us a message!

Molecular Modeling of Transition Metal Systems
Unitat de Química-Física, Department de Química
Facultat de Ciències, Universitat Autònoma de Barcelona
Barcelona, Spain