AI-assisted Molecular Dynamics Simulation

With the improvement of computer performance and algorithm design, the prospect of computer-aided drug design is promising. As a computer simulation technique, molecular dynamics (MD) simulations are likely to play an increasingly important role in the development of novel pharmacological therapeutics. Biological function is based on molecular interactions, so studying macromolecular structures is key to understanding biology. MD can be used to explore conformational space, especially for macromolecules such as proteins. With the aid of numerical integration of Newton's equation of motion for a particular interatomic potential denoted by an initial condition and boundary condition, MD allows the prediction of the time evolution of an interacting specific system involving the generation of atomic trajectories of a system. Creative Biolabs has established the AI-assisted bioinformatics analysis platform to support our customers in molecular docking, molecular dynamics simulation, virtual screening, and quantitative structural activity relationship (QSAR) analysis.

Fig.1 Applications of molecular dynamics simulations. (Hollingsworth & Dror, 2018)

Molecular Dynamics Simulation for Virtual Screening

The process of virtual screening usually includes compound database preparation, molecular docking, and the selection of pretest compounds. Each step will influence the performance of virtual screening, which mainly depends on the enrichment factor of the virtual screening. By calculating the ratio of active compounds among the tested compounds to that in the original databases, the enrichment factor can quantify the effectiveness of the virtual screening method. To increase the enrichment factor of virtual screening, MD simulations can be used at every stage of the process. The rationality of the docking poses for the compounds and the accuracy of the binding ability evaluation between the target and ligands are the key factors influencing the hit ratio of the selected compounds in virtual screening. By considering the flexibility of the receptor and the combination with MM PBSA or MM-GBSA calculations to increase the accuracy of the binding ability evaluation, MD simulations can significantly enhance the performance of virtual screening. For example, the application of MD simulations to conformational refinement and the ranking of candidates in combination with binding free energy calculation and ensemble docking aided by MD simulations.

Fig.2 The virtual screening workflow combined with molecular dynamics simulations. (Karplus & Kuriyan, 2005)

Molecular Dynamics Simulation for Protein Function Study

The conformational dynamics of protein molecules are usually a crucial component of their activity and are encoded in their molecular structure. The three-dimensional (3D) structures of proteins are often so complicated that the mechanism of action is obscured. The division of a protein into domains connected by hinges and the availability of structures corresponding to various functional states can provide clues to the essential dynamics of the molecule, but it is difficult to infer the operation of these molecular machines from a visual inspection or straightforward calculations. Thus, a basic understanding of how proteins work requires an understanding of the connections between 3D structure and dynamics, which is much more difficult to probe experimentally. By enabling the exploration of the conformational energy landscape accessible to protein molecules, MD simulations can provide links between structure and dynamics. Moreover, MD simulations can also provide abundant information on the dynamic structure of biological macromolecules, and the energy information of protein-ligand interaction. Additionally, the ultimate details about the motion of individual atoms as a function of time can be known by MD simulations. Such information is important for understanding the structure-function relationships of targets and the nature of protein-ligand interactions, as well as guiding the drug discovery and design process. Thus, MD simulations are typically more effective than actual system tests at providing answers to specific questions about the characteristics of model systems.

Fig.3 Simulation of a solvated protein. (Karplus & Kuriyan, 2005)

As one of the leading bioinformatics companies, Creative Biolabs is opening to provide molecular dynamics simulation for our customers around the world. Based on the advanced MD simulation technology, we can facilitate conformational dynamics studies of protein and protein-ligand, and combine MD simulation with molecular docking methods for in silico virtual screening.

References

1. Hollingsworth, S.A.; Dror, R.O. Molecular dynamics simulation for all. Neuron. 2018, 99(6): 1129-1143.
2. Karplus, M.; Kuriyan, J. Molecular dynamics and protein function. Proceedings of the National Academy of Sciences. 2005, 102(19): 6679-6685.
3. Liu, X.; et al. Molecular dynamics simulations and novel drug discovery. Expert opinion on drug discovery. 2018, 13(1): 23-37.