Molecules in Action provides three stand-alone software packages: Eris, πDMD, and MiA Suite. Bundling of two or three software packages, as well as with the consulting, training, support, are available options. Academic pricing is also available for non-profit institutions. Please contact Molecules in Action for further details.
Eris, which takes the name of Greek goddess of discord, is protein stability prediction and design software. Eris can rapidly estimate a protein’s stability changes upon mutations, which are often introduced to manipulate its original function or to create new functions. Knowledge of the stability changes a priori can help avoid laborious exploratory experiments and help design stable functional proteins. Eris can also design protein sequence that increases a protein’s stability, which is required in the development of protein therapeutics, such as antibodies.
Comparative modeling of protein structure based on a homolog of known structure offers the most viable alternative to experimental structure determination. However, achieving the quality of the homology model comparable to experimental structures is a challenge. MIA suite provides two programs, Chiron and Loop that harness the efficient sampling capability of the physically accurate all-atom DMD simulations to ensure your homology models are of structural quality comparable to experimental structures.
Molecular Dynamics (MD) simulation is a key tool for the computational exploration of the dynamic and equilibrium properties of molecular systems. However, computational studies of large systems such as biological molecules pose a significant challenge because of their large size and wide range of characteristic time scales (from 10-12 seconds for chemical bond fluctuations to 106 seconds for molecular aggregation). For example, state-of-the art MD software has only recently achieved microsecond-scale simulations of relatively small proteins (~100 residues), employing hundreds of thousands of CPUs to do so. The πDMD software package addresses this issue by computing motion using discretized energy functions instead of integrating over continuous equations, allowing for a simpler description of interactions. The more efficient identification of interactions between particles allows for fewer necessary calculations, and hence a speed-up of MD simulation and increased sampling capabilities, especially in dilute systems.