Towards a MIP‐based alignment and docking in computer‐aided drug design

Abstract

Structural alignment of ligands in their biological conformation is a crucial step in the building of pharmacophoric models in structure-based drug design. In addition, docking algorithms are limited in some cases by the quality of the scoring functions and the limited flexibility of the environment that the different programs allow. On the other hand, GRID molecular interaction potentials (MIPs) have been used for a long time in 3D-QSAR studies. However, in most of these studies the alignment of the molecules is performed on the basis of geometrical or physico-chemical criteria that differ from the MIPs used in the partial least squares statistical analysis. We have previously developed a method to use the same scoring function for the molecular alignment and for 3D-QSAR studies. This methodology, based on the use of GRID potentials, consists in the weighted averaging of similarities of the relevant MIPs of the molecules to be aligned. Here we present a method to obtain the weights for the different GRID probes in the average based on the structural information on protein-ligand complexes for relevant systems. The method, implemented in MIPSIM, is shown to yield good accuracy in the prediction of the alignments for two systems: a set of three inhibitors of dihydrofolate reductase and a set of fifteen non-nucleoside HIV-1 reverse transcriptase inhibitors (NNRTIs). The smooth GRID potentials are shown to capture the flexible character of the active site, as opposed to traditional docking scoring energy functions.

Multiscale Molecular Dynamics of Protein Aggregation

“…The contents of this review suggest that both approaches are going to be successful in the upcoming years, and we predict that the convergence of powerful machines and simulation algorithms, smart protocols for multiscaling and, although sometimes obscure by the technology but especially important, a deep understanding of the physico-chemical properties of protein and peptide interfaces [91] are going to produce accurate predictions of complex formation. In this direction, computational tools that are able to integrate different algorithms and facilitate the researcher's work are going to become central, as well as formats and protocols to share methods, systems and simulations.…”

BRUTUS: Optimization of a grid-based similarity function for rigid-body molecular superposition. II. Description and characterization

“…In BRUTUS, the shape match is favored over the electrostatic fit, and a value of five is assigned to grid points inside the van der Waals radius. However, the importance of shape and electrostatic fit may depend on the target [29], and this value might not be optimal for all targets.…”

The Similarity Principle – New Trends and Applications in Ligand-Based Drug Discovery and ADMET Profiling

“…Considering the fact, that MIMIC only operates The Similarity Principle -New Trends and Applications … 9 with steric and electrostatic fields and that H-bonds and π-π interactions play a dominant role in drug receptor interactions, a further improvement of using this 3D-SIBAR approach should be obtained when shape similarities are calculated on basis of molecular interaction fields utilising the full panel of probe atoms (H-bond acceptor, H-bond donor, hydrophobic, aromatic,…). This method is utilised in the software package MIPSIM, which compares 3D distribution of both molecular electrostatic potentials derived from quantum chemical calculations and molecular interaction fields of series of biomolecules [12,13]. Obviously, the computational costs are by far higher than those for MIMIC and require front-end computational tools.…”