Substrate-independent activation pathways of the CRISPR-Cas9 HNH nuclease.

A hallmark of tightly regulated high-fidelity enzymes is that they become activated only after encountering cognate substrates, often by an induced-fit mechanism rather than conformational selection. Upon analysis of molecular dynamics trajectories, we recently discovered that the Cas9 HNH domain exists in three conformations: 1) Y836 (which is two residues away from the catalytic D839 and H840 residues) is hydrogen bonded to the D829 backbone amide, 2) Y836 is hydrogen bonded to the backbone amide of D861 (which is one residue away from the third catalytic residue N863), and 3) Y836 is not hydrogen bonded to either residue. Each of the three conformers differs from the active state of HNH. The conversion between the inactive and active states involves a local unfolding-refolding process that displaces the Cα and side chain of the catalytic N863 residue by ∼5 Å and ∼10 Å, respectively. In this study, we report the two largest principal components of coordinate variance of the HNH domain throughout molecular dynamics trajectories to establish the interconversion pathways of these conformations. We show that conformation 2 is an obligate step between conformations 1 and 3, which are not directly interconvertible without conformation 2. The loss of hydrogen bonding of the Y836 side chain in conformation 3 likely plays an essential role in activation during local unfolding-refolding of an α-helix containing the catalytic N863. Three single Lys-to-Ala mutants appear to eliminate this substrate-independent activation pathway of the wild-type HNH nuclease, thereby enhancing the fidelity of HNH cleavage.

Molecular Basis for Polyketide Ketoreductase-Substrate Interactions.

Polyketides are a large class of structurally and functionally diverse natural products with important bioactivities. Many polyketides are synthesized by reducing type II polyketide synthases (PKSs), containing transiently interacting standalone enzymes. During synthesis, ketoreductase (KR) catalyzes regiospecific carbonyl to hydroxyl reduction, determining the product outcome, yet little is known about what drives specific KR-substrate interactions. In this study, computational approaches were used to explore KR-substrate interactions based on previously solved apo and mimic cocrystal structures. We found five key factors guiding KR-substrate binding. First, two major substrate binding motifs were identified. Second, substrate length is the key determinant of substrate binding position. Third, two key residues in chain length specificity were confirmed. Fourth, phosphorylation of substrates is critical for binding. Finally, packing/hydrophobic effects primarily determine the binding stability. The molecular bases revealed here will help further engineering of type II PKSs and directed biosynthesis of new polyketides.

Heterogeneous Dielectric Implicit Membrane Model for the Calculation of MMPBSA Binding Free Energies.

Membrane-bound protein receptors are a primary biological drug target, but the computational analysis of membrane proteins has been limited. In order to improve molecular mechanics Poisson-Boltzmann surface area (MMPBSA) binding free energy calculations for membrane protein-ligand systems, we have optimized a new heterogeneous dielectric implicit membrane model, with respect to free energy simulations in explicit membrane and explicit water, and implemented it into the Amber software suite. This new model supersedes our previous uniform, single dielectric implicit membrane model by allowing the dielectric constant to vary with depth within the membrane. We calculated MMPBSA binding free energies for the human purinergic platelet receptor (P2Y12R) and two of the muscarinic acetylcholine receptors (M2R and M3R) bound to various antagonist ligands using both membrane models, and we found that the heterogeneous dielectric membrane model has a stronger correlation with experimental binding affinities compared to the older model under otherwise identical conditions. This improved membrane model increases the utility of MMPBSA calculations for the rational design and improvement of future drug candidates.

Valproate-coenzyme A conjugate blocks opening of receptor binding domains in the spike trimer of SARS-CoV-2 through an allosteric mechanism.

The receptor-binding domains (RBDs) of the SARS-CoV-2 spike trimer exhibit "up" and "down" conformations often targeted by neutralizing antibodies. Only in the "up" configuration can RBDs bind to the ACE2 receptor of the host cell and initiate the process of viral multiplication. Here, we identify a lead compound (3-oxo-valproate-coenzyme A conjugate or Val-CoA) that stabilizes the spike trimer with RBDs in the down conformation. Val-CoA interacts with three R408 residues, one from each RBD, which significantly reduces the inter-subunit R408-R408 distance by ∼ 13 Å and closes the central pore formed by the three RBDs. Experimental evidence is presented that R408 is part of a triggering mechanism that controls the prefusion to postfusion state transition of the spike trimer. By stabilizing the RBDs in the down configuration, this and other related compounds can likely attenuate viral transmission. The reported findings for binding of Val-CoA to the spike trimer suggest a new approach for the design of allosteric antiviral drugs that do not have to compete for specific virus-receptor interactions but instead hinder the conformational motion of viral membrane proteins essential for interaction with the host cell. Here, we introduce an approach to target the spike protein by identifying lead compounds that stabilize the RBDs in the trimeric "down" configuration. When these compounds trimerize monomeric RBD immunogens as co-immunogens, they could also induce new types of non-ACE2 blocking antibodies that prevent local cell-to-cell transmission of the virus, providing a novel approach for inhibition of SARS-CoV-2.

Improved Poisson-Boltzmann Methods for High-Performance Computing.

Implicit solvent models based on the Poisson-Boltzmann equation (PBE) have been widely used to study electrostatic interactions in biophysical processes. These models often treat the solvent and solute regions as high and low dielectric continua, leading to a large jump in dielectrics across the molecular surface which is difficult to handle. Higher order interface schemes are often needed to seek higher accuracy for PBE applications. However, these methods are usually very liberal in the use of grid points nearby the molecular surface, making them difficult to use on high-performance computing platforms. Alternatively, the harmonic average (HA) method has been used to approximate dielectric interface conditions near the molecular surface with surprisingly good convergence and is well suited for high-performance computing. By adopting a 7-point stencil, the HA method is advantageous in generating simple 7-banded coefficient matrices, which greatly facilitate linear system solution with dense data parallelism, on high-performance computing platforms such as a graphics processing unit (GPU). However, the HA method is limited due to its lower accuracy. Therefore, it would be of great interest for high-performance applications to develop more accurate methods while retaining the simplicity and effectiveness of the 7-point stencil discretization scheme. In this study, we have developed two new algorithms based on the spirit of the HA method by introducing more physical interface relations and imposing the discretized Poisson's equation to the second order, respectively. Our testing shows that, for typical biomolecules, the new methods significantly improve the numerical accuracy to that comparable to the second-order solvers and with ∼65% overall efficiency gain on widely available high-performance GPU platforms.