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McCammon, J. A.

Publications and source records attributed to McCammon, J. A..

2 recordsLinked to original sources

Molecular mechanism of off-target effects in CRISPR-Cas9

CRISPR-Cas9 is the state-of-the-art technology for editing and manipulating nucleic acids. However, the occurrence of off-target mutations can limit its applicability. Here, all-atom enhanced molecular dynamics (MD) simulations - using Gaussian accelerated MD (GaMD) - are used to decipher the mechanism of off-target binding at the molecular level. GaMD reveals that base pair mismatches in the target DNA at specific distal sites with respect to the Protospacer Adjacent Motif (PAM) induce an extended opening of the RNA:DNA heteroduplex, which leads to newly discovered interactions between the unwound nucleic acids and the protein counterpart. The conserved interactions between the target DNA strand and the L2 loop of the catalytic HNH domain constitute a \"lock\" effectively decreasing the conformational freedom of the HNH domain and its activation for cleavage. Remarkably, depending on their position at PAM distal sites, DNA mismatches leading to off-target cleavages are unable to \"lock\" the HNH domain, thereby identifying the ability to \"lock\" HNH as a key determinant. Consistently, off-target sequences hampering the catalysis have been shown to \"trap\" somehow the HNH domain in an inactive \"conformational checkpoint\" state (Dagdas et al. Sci Adv, 2017). As such, this mechanism identifies the molecular basis underlying off-target cleavages and contributes in clarifying a long-lasting open issue of the CRISPR-Cas9 function. It also poses the foundation for designing novel and more specific Cas9 variants, which could be obtained by magnifying the \"locking\" interactions between HNH and the target DNA in the presence of any incorrect off-target sequence, thus preventing undesired cleavages.

biophysics

Fast and Flexible GPU Accelerated Binding Free Energy Calculations within the AMBER Molecular Dynamics Package

Alchemical free energy calculations (AFE) based on molecular dynamics (MD) simulations are key tools in both improving our understanding of a wide variety of biological processes and accelerating the design and optimization of therapeutics for numerous diseases. Computing power and theory have, however, long been insufficient to enable AFE calculations to be routinely applied in early stage drug discovery. One of the major difficulties in performing AFE calculations is the length of time required for calculations to converge to an ensemble average. CPU implementations of MD based free energy algorithms can effectively only reach tens of nanoseconds per day for systems on the order of 50,000 atoms, even running on massively parallel supercomputers. Therefore, converged free energy calculations on large numbers of potential lead compounds are often untenable, preventing researchers from gaining crucial insight into molecular recognition, potential druggability, and other crucial areas of interest. Graphics Processing Units (GPUs) can help address this. We present here a seamless GPU implementation, within the PMEMD module of the AMBER molecular dynamics package, of thermodynamic integration (TI) capable of reaching speeds of >140 ns/day for a 44,907-atom system, with accuracy equivalent to the existing CPU implementation in AMBER. The implementation described here is currently part of the AMBER 18 beta code and will be an integral part of the upcoming version 18 release of AMBER.

biophysics