Welcome to the website (under permanent construction) of the Molecular Modeling Lab of the University of Alcalá (Spain).




A Scoring Function for Protein-Protein and Protein-Ligand Docking and Molecular Dynamics. 



A graphical user interface to perform structure-based comparative binding energy (COMBINE) analysis on a set of ligand-receptor complexes.



cGRILL: an unsophisticated affinity map generator


cGRILL calculates 4 affinity maps: lipophilic (CH3), hydrogen bond acceptor (=O), hydrogen bond donor (NH4+) and mixed hydrogen bond donor-acceptor (OH). It implements AMBER force field van der Waals and electrostatic terms and a custom hydrogen bond. The code is not pretty but it is licensed under GPL v3.




CRDOCK is a protein-ligand docking program similar to Glide, DOCK or AutoDock. It uses a hybrid scoring function based on GlideScore(tm) using a molecular mechanics energy function (AMBER-like) and the ChemScore function to score interactions. The docking program is particularly well suited to generate molecular models of ligand-receptor complexes for further use in COMBINE analysis.


Here you can find some tricks that worked for us and can make your life as a Computational Scientist easier :)



An ultrafast and accurate scoring function for protein−protein and protein-ligand docking is presented. It includes (1) a molecular mechanics (MM) part based on a 12−6 Lennard-Jones potential; (2) an electrostatic component based on an implicit solvent model (ISM) with individual desolvation penalties for each partner in the protein−protein complex plus a hydrogen bonding term; and (3) a surface area (SA) contribution to account for the loss of water contacts upon protein−protein complex formation. The accuracy and performance of the scoring function, termed MM-ISMSA, have been assessed by (1) comparing the total binding energies, the electrostatic term, and its components (charge−charge and individual desolvation energies), as well as the per residue contributions, to results obtained with well-established methods such as APBSA or MM-PB(GB)SA for a set of 1242 decoy protein−protein complexes and (2) testing its ability to recognize the docking solution closest to the experimental structure as that providing the most favorable total binding energy. For this purpose, a test set consisting of 15 protein−rotein complexes with known 3D structure mixed with 10 decoys for each complex was used. The correlation between the values afforded by MM-ISMSA and those from the other methods is quite remarkable (r2 ∼ 0.9), and only 0.2−5.0 s (depending on the number of residues) are spent on a single calculation including an all vs all pairwise energy decomposition. On the other hand, MM-ISMSA correctly identifies the best docking solution as that closest to the experimental structure in 80% of the cases. Finally, MM-ISMSA can process molecular dynamics trajectories and reports the results as averaged values with their standard deviations.

MM-ISMSA has been implemented as a plugin to the widely used molecular graphics program PyMOL, although it can also be executed in command-line mode.

MM-ISMSA is free distributed for non commercial purposes. Brougth to you by: Javier Klett, Alvaro Cortes Cabrera, Antonio Morreale and the rest of the crew


MM-ISMSA is ready for computing systems with NO WATER molecules in the following formats:

  • PDB with charge and radii: Electrostatic Contribution
  • Amber (top/crd) (Static Structure or Molecular dynamics): Whole Contribution

Downloads & Support

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Usage and installation

Guide-lines and Documentation: Download


MM-ISMSA Examples

Guide-lines and documentation: Download

Protein-Protein Data

  • RMSD and Global energy values of the docking solutions Download
  • Protein-Protein Examples Download

Protein-Ligand Data

  • Global energy results raw complexes Download
  • Global energy results minimized complexes - Download
  • Protein-Ligand Examples Download

Molecular Dynamic Data


  1. Javier Klett, Alfonso Núñez-Salgado, Helena G. Dos Santos, Álvaro Cortés-Cabrera, Almudena Perona, Rubén Gil-Redondo, David Abia, Federico Gago, and Antonio Morreale
    MM-ISMSA: an ultra-fast and accurate scoring function for protein-protein docking.
    J. Chem. Theory Comput., 8, 3395-3408 (2012)

  2. Morreale, A.; Gil-Redondo, R.; Ortiz, A.R.
    A new implicit solvent model for protein-ligand docking.
    Proteins 2007 May, 67: 606-16.