Name
Title | ||
|---|---|---|
A multi-objective optimization energy approach to predict the ligand conformation in a docking process |
Abstract | ||
|---|---|---|
This work proposes a multi-objective algorithmic method for modelling the prediction of the conformation and configuration of ligands in receptor-ligand complexes by considering energy contributions of molecular interactions. The proposed approach is an improvement over others in the field, where the principle insight is that a Pareto front helps to understand the tradeoffs in the actual problem. The method is based on three main features: (i) Representation of molecular data using a trigonometric model; (ii) Modelling of molecular interactions with all-atoms force field energy functions and (iii) Exploration of the conformational space through a multi-objective evolutionary algorithm. The performance of the proposed model was evaluated and validated over a set of well known complexes. The method showed a promising performance when predicting ligands with high number of rotatable bonds. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-37207-0_16 | EuroGP |
Keywords | Field | DocType |
molecular interaction,multi-objective evolutionary algorithm,multi-objective algorithmic method,trigonometric model,ligand conformation,promising performance,all-atoms force field energy,molecular data,multi-objective optimization energy approach,energy contribution,docking process | Force field (physics),Trigonometry,Force field (chemistry),Evolutionary algorithm,Molecular interactions,Docking (dog),Computer science,Simulation,Algorithm,Theoretical computer science,Multi-objective optimization | Conference |
Citations | PageRank | References |
4 | 0.42 | 8 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Angelica Sandoval-Perez | 1 | 4 | 0.42 |
| David Becerra | 2 | 4 | 1.43 |
| Diana Vanegas | 3 | 4 | 0.76 |
| Daniel Restrepo-Montoya | 4 | 33 | 1.68 |
| Fernando Niño | 5 | 180 | 9.20 |