We present a new simple extension of multiple walker metadynamics which makes it possible to simulate simultaneously multiple different molecular systems and to predict their free energy surfaces, named Altruistic metadynamics. Similarly to basic metadynamics, it uses a bias potential in the form of hills summed over the simulation. Each system adds a big hill to its "own" bias potential and smaller hills to bias potentials of other systems, hence, each system enhances sampling of other systems. This makes it possible to achieve either faster reaching of the stationary point or higher accuracy of the calculated free energy surfaces. This should be efficient in modeling of series of chemically similar systems, for example, in computational drug screening by metadynamics. The method was tested on model energy surfaces, alanine dipeptide modeled in different force fields and monosaccharides of D-hexopyranose series.
Metadynamics method has been widely used to enhance sampling in molecular simulations. Its original form suffers two major drawbacks, poor convergence in complex (especially biomolecular) systems and its serial nature. The first drawback has been addressed by introduction of a convergent variant known as well-tempered metadynamics. The second was addressed by introduction of a parallel multisystem metadynamics referred to as altruistic metadynamics. Here, we combine both approaches into well-tempered altruistic metadynamics. We provide mathematical arguments and trial simulations to show that it accurately predicts free energy surfaces.
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