Solving Molecular Docking Problems with Multi-Objective Metaheuristics

Abstract

Molecular docking is a hard optimization problem that has been tackled in the past with metaheuristics, demonstrating new and challenging results when looking for one objective: the minimum binding energy. However, only a few papers can be found in the literature that deal with this problem by means of a multi-objective approach, and no experimental comparisons have been made in order to clarify which of them has the best overall performance. In this paper, we use and compare, for the first time, a set of representative multi-objective optimization algorithms applied to solve complex molecular docking problems. The approach followed is focused on optimizing the intermolecular and intramolecular energies as two main objectives to minimize. Specifically, these algorithms are: two variants of the non-dominated sorting genetic algorithm II (NSGA-II), speed modulation multi-objective particle swarm optimization (SMPSO), third evolution step of generalized differential evolution (GDE3), multi-objective evolutionary algorithm based on decomposition (MOEA/D) and S-metric evolutionary multi-objective optimization (SMS-EMOA). We assess the performance of the algorithms by applying quality indicators intended to measure convergence and the diversity of the generated Pareto front approximations. We carry out a comparison with another reference mono-objective algorithm in the problem domain (Lamarckian genetic algorithm (LGA) provided by the AutoDock tool). Furthermore, the ligand binding site and molecular interactions of computed In addition, a case study of application for aeroplysinin-1 is performed, showing the effectiveness of our multi-objective approach in drug discovery.

Computer Simulations Reveal a Novel Blocking Mode of the hERG Ion Channel by the Antiarrhythmic Agent Clofilium

“…A rigid docking did indeed reveal a blocking model quite similar to the one predicted here, although in a much “kinked” manner, with the nitrogen atom placed lower, since docking was unable to allow the aliphatic tail to extend in between S6 and H5 . Therefore, this study only points again on the challenges faced by molecular docking in order to approximate the real binding features of hERG blocking but which is also generally seen in other models that have large binding sites with multiple flexible residues . Apart from docking, previous models of clofilium block used different hERG homology models based on distantly‐related templates, such as bacterial channel or Kv1.5, whose quality is arguable and dependent on modeling method .…”

“…[10] Therefore, this study only points again on the challenges faced by molecular docking in order to approximate the real binding features of hERG blocking [44] but which is also generally seen in other models that have large binding sites with multiple flexible residues. [45][46] Apart from docking, previous models of clofilium block used different hERG homology models based on distantly-related templates, such as bacterial channel or Kv1.5, whose quality is arguable and dependent on modeling method. [47] Nevertheless, this is seemingly the first study involving simulations of a hERG-clofilium complex, as it is highly recommended that such a methodology should be followed, in order to filter out false results from docking.…”

(+)-Aeroplysinin-1 inhibits Akt and Erk pathway signaling selectively in endothelial cells

“…Several reports provide evidence concerning the inhibitory effect of aeroplysinin-1 on EGF receptor [8], although this effect has been questioned by others [18]. A very recent docking study predicts that aeroplysinin-1 can interact with the EGFR catalytic kinase domain and suggests that similar interaction could be effective for inhibitory effects of aeroplysini-1 on other receptor tyrosine kinases such as VEGFR2, a key signalling molecule in angiongenesis [19]. Unfortunately, this does not seem to be the case in the real world according to the completely negative results obtained in our in vitro kinase inhibition screening testing the effect of both 2 and 20 µM (+)-aeroplysinin-1 on the in vitro activity of the 25 protein kinases listed in Table 1.…”

A Study of Archiving Strategies in Multi-objective PSO for Molecular Docking

“…Among these optimization techniques, a multi-objective swarm-intelligence approach, namely SMPSO [11], has emerged as one of the most prominent optimizers for molecular docking [4] [9]. This technique performs a limitation mechanism of particle's velocity to avoid the movement of particles in search regions out of the problem ranges.…”