What has been achieved in Molecular Dynamics and Acellera contribution.
Acellera celebrates its 10th anniversary. A decade focusing on molecular dynamics (MD) and dedicated to improve this technique as a strong partner of biophysical approaches. Objectively, molecular dynamics is the only technique allowing to study conformational changes and interaction at atomistic level, to quantify binding energies, binding kinetics for any kind of molecules since a force field has been defined for these. It represents an adequate combination with NMR, Crystallography, ITC, Surface plasmon resonance, Thermal shift that are already widely used in Drug Discovery.
What makes MD so interesting now?
In 10 years, we have seen how calculations done on cluster of CPU can now be done now on GPU cluster or in the Cloud. The first GPU offered already a large improvement on yield (ns/day) obtained. Where ns was the goal, nowadays it is a simple unit. In 2009, we ran microsecond, last year, 2 milliseconds (cumulated time) were obtained when performing a fragment screening (Ferruz et al, J. Chem. Inf. Model. 2015). If this rhythm is followed within the next 6 years, a second will probably be attained and maybe required for high index journal publication. Basically, we can simulate long process from side chain flip to domain motion and binding of fast Kon molecules for example.
The speed of GPU was undeniable in the achievement of long MD but they also generate higher amount of data to analyze. Where we needed Hard disk to store Gigabytes of data, we can count in terabyte…generated weekly. Storage is maybe the next challenge.
So it is possible to simulate the binding of benzamidine to Trypsin from scratch (Buch et al, PNAS 2011), to perform fragment screening, to study conformational change of antibodies, to analyze multibody cofactor and substrate molecular recognition…This has been possible not only thanks to the GPU development but also thanks to a huge work that contributed to innovative approach to sample the conformational space and energy of the system (Doerr et al, J. Chem. Theory Comput. 2014) and to the correct analysis of the trajectories.
What can be expected now from MD in Drug Discovery?
As solvation/desolvation processes are critical parameters for interaction studies, all atoms simulations represent an adequate method. During the simulations, at each step, the forces on each atom are computed and the atomic position and velocity are updated according to Newton’s laws of motion. This means millions of calculations magnified by the number of atoms composing your system. A 25000 atoms system can be simulated at 500 ns/day. If we take 100 GPU, after 20 days we have a millisecond of calculation which may be enough for micro molar affinity ligand. When studying larger system, the time needed to sample the interaction increase and the throughput we can expect decreases.
A category of molecules enters this affinity range and offers advantage when calculating compound parameters: fragment. MD is well suited for fragment interaction and low to medium throughput screening. Brute throughput will depend on the resources assigned, but in a single analysis binding kinetics, energy and pathway can be determined. The accuracy of low energy pose description reaches crystallography resolution.
What can be improved?
Improvements are needed in the timescale MD can reach, in reproducing experimental binding and throughput, meaning the number of molecules we can test. At the end of the day, we want to explore the chemical space and we are still far from scratching its surface. So, Speed of calculations, sampling and analysis are the main parameters where we can still gain time and open the way to build and test molecules newly designed and not yet synthesized.
Blue Waters, Anton, MDGRAPE are synonyms of (impressive) fast calculations. A more affordable solution has been developed at Acellera: the workstation Metrocubo equipped with 4 GPU; it allows to simulate a 2 microsecond/day (based on DHFR benchmark).
Sampling approaches are also being optimized (metadynamics, replica exchange, umbrella sampling, accelerated MD). At Acellera, we use Adaptive Sampling with ACEMD. Finally, analysis protocols have been largely improved and is still an active field of development.
In the last 10 years, Acellera developed ACEMD, enhancing the execution of MD simulations. These can now be run on GPU (workstation like Metrocubo or cluster) or in the cloud. For this purpose, we developed AceCloud, a tool allowing to run calculations on AWS. Finally, on top of all, a new interface providing a unified environment for molecular discovery has been designed for both computational and medicinal chemistry groups: HTMD. This tool allows encoding best practices, hiding complexity, from start to end: PDB to free energy calculations, to solve biological problem.
Fragment screening, GPCR ligand binding, protein folding, nucleic acids complex interaction are only few of the topics studied successfully by high throughput molecular dynamics and we hope its use will be generalized within the next decade.