Machine learning-driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins.

RAS is a signaling protein associated with the cell membrane that is mutated in up to 30% of human cancers. RAS signaling has been proposed to be regulated by dynamic heterogeneity of the cell membrane. Investigating such a mechanism requires near-atomistic detail at macroscopic temporal and spatial scales, which is not possible with conventional computational or experimental techniques. We demonstrate here a multiscale simulation infrastructure that uses machine learning to create a scale-bridging ensemble of over 100,000 simulations of active wild-type KRAS on a complex, asymmetric membrane. Initialized and validated with experimental data (including a new structure of active wild-type KRAS), these simulations represent a substantial advance in the ability to characterize RAS-membrane biology. We report distinctive patterns of local lipid composition that correlate with interfacially promiscuous RAS multimerization. These lipid fingerprints are coupled to RAS dynamics, predicted to influence effector binding, and therefore may be a mechanism for regulating cell signaling cascades.

ddcMD: A fully GPU-accelerated molecular dynamics program for the Martini force field.

We have implemented the Martini force field within Lawrence Livermore National Laboratory's molecular dynamics program, ddcMD. The program is extended to a heterogeneous programming model so that it can exploit graphics processing unit (GPU) accelerators. In addition to the Martini force field being ported to the GPU, the entire integration step, including thermostat, barostat, and constraint solver, is ported as well, which speeds up the simulations to 278-fold using one GPU vs one central processing unit (CPU) core. A benchmark study is performed with several test cases, comparing ddcMD and GROMACS Martini simulations. The average performance of ddcMD for a protein-lipid simulation system of 136k particles achieves 1.04 µs/day on one NVIDIA V100 GPU and aggregates 6.19 µs/day on one Summit node with six GPUs. The GPU implementation in ddcMD offloads all computations to the GPU and only requires one CPU core per simulation to manage the inputs and outputs, freeing up remaining CPU resources on the compute node for alternative tasks often required in complex simulation campaigns. The ddcMD code has been made open source and is available on GitHub at https://github.com/LLNL/ddcMD.

TeraChem: Accelerating electronic structure and ab initio molecular dynamics with graphical processing units.

Developed over the past decade, TeraChem is an electronic structure and ab initio molecular dynamics software package designed from the ground up to leverage graphics processing units (GPUs) to perform large-scale ground and excited state quantum chemistry calculations in the gas and the condensed phase. TeraChem's speed stems from the reformulation of conventional electronic structure theories in terms of a set of individually optimized high-performance electronic structure operations (e.g., Coulomb and exchange matrix builds, one- and two-particle density matrix builds) and rank-reduction techniques (e.g., tensor hypercontraction). Recent efforts have encapsulated these core operations and provided language-agnostic interfaces. This greatly increases the accessibility and flexibility of TeraChem as a platform to develop new electronic structure methods on GPUs and provides clear optimization targets for emerging parallel computing architectures.

An Ab Initio Exciton Model Including Charge-Transfer Excited States.

The Frenkel exciton model is a useful tool for theoretical studies of multichromophore systems. We recently showed that the exciton model could be used to coarse-grain electronic structure in multichromophoric systems, focusing on singly excited exciton states [ Acc. Chem. Res. 2014 , 47 , 2857 - 2866 ]. However, our previous implementation excluded charge-transfer excited states, which can play an important role in light-harvesting systems and near-infrared optoelectronic materials. Recent studies have also emphasized the significance of charge-transfer in singlet fission, which mediates the coupling between the locally excited states and the multiexcitonic states. In this work, we report on an ab initio exciton model that incorporates charge-transfer excited states and demonstrate that the model provides correct charge-transfer excitation energies and asymptotic behavior. Comparison with TDDFT and EOM-CC2 calculations shows that our exciton model is robust with respect to system size, screening parameter, and different density functionals. Inclusion of charge-transfer excited states makes the exciton model more useful for studies of singly excited states and provides a starting point for future construction of a model that also includes double-exciton states.

Characterization of the Azirinyl Cation and Its Isomers.

The azirinyl cation (C2H2N(+)) and its geometrical isomers could be present in the interstellar medium. The C2H2N(+) isomers are, however, difficult to identify in interstellar chemistry because of the lack of high-resolution spectroscopic data from laboratory experiments. Ab initio quantum chemical methods were used to characterize the structures, relative energies, and spectroscopic and physical properties of the low energy isomers of the azirinyl cation. We have employed second-order Møller-Plesset perturbation theory (MP2), second-order Z-averaged perturbation theory (ZAPT2), and coupled cluster theory with singles and doubles with perturbative triples CCSD(T) methods along with large correlation consistent basis sets such as cc-pVTZ, cc-pCVTZ, cc-pVQZ, cc-pCVQZ, and cc-pV5Z. Harmonic vibrational frequencies, dipole moments, rotational constants, and proton affinities for the lowest energy isomers were calculated using the CCSD(T) method. Azirinyl cation, a cyclic isomer, is lowest in energy at all levels of theory employed. Azirinyl cation is followed by the cyanomethyl cation (H2CCN)(+), isocyanomethyl cation (H2CNC)(+), and a quasilinear HCCNH(+) cation, which are 13.8, 17.3, and 21.5 kcal mol(-1) above the cyclic isomer, respectively, at the CCSD(T)/cc-pV5Z level of theory. The lowest three isomers all have C2v symmetry and (1)A1 ground electronic states. The quasilinear HCCNH(+) cation has a Cs symmetry planar structure, and a (3)A″ electronic ground state, unlike what some previous work suggested.