Exploring the Reaction Mechanism of HIV Reverse Transcriptase with a Nucleotide Substrate

Combined Free-Energy Calculation and Machine Learning Methods for Understanding Ligand Unbinding Kinetics

The determination of drug residence times, which define the time an inhibitor is in complex with its target, is a fundamental part of the drug discovery process. Synthesis and experimental measurements of kinetic rate constants are, however, expensive and time consuming. In this work, we aimed to obtain drug residence times computationally. Furthermore, we propose a novel algorithm to identify molecular design objectives based on ligand unbinding kinetics. We designed an enhanced sampling technique to accurately predict the free-energy profiles of the ligand unbinding process, focusing on the free-energy barrier for unbinding. Our method first identifies unbinding paths determining a corresponding set of internal coordinates (ICs) that form contacts between the protein and the ligand; it then iteratively updates these interactions during a series of biased molecular dynamics (MD) simulations to reveal the ICs that are important for the whole of the unbinding process. Subsequently, we performed finite-temperature string simulations to obtain the free-energy barrier for unbinding using the set of ICs as a complex reaction coordinate. Importantly, we also aimed to enable the further design of drugs focusing on improved residence times. To this end, we developed a supervised machine learning (ML) approach with inputs from unbiased “downhill” trajectories initiated near the transition state (TS) ensemble of the string unbinding path. We demonstrate that our ML method can identify key ligand–protein interactions driving the system through the TS. Some of the most important drugs for cancer treatment are kinase inhibitors. One of these kinase targets is cyclin-dependent kinase 2 (CDK2), an appealing target for anticancer drug development. Here, we tested our method using two different CDK2 inhibitors for the potential further development of these compounds. We compared the free-energy barriers obtained from our calculations with those observed in available experimental data. We highlighted important interactions at the distal ends of the ligands that can be targeted for improved residence times. Our method provides a new tool to determine unbinding rates and to identify key structural features of the inhibitors that can be used as starting points for novel design strategies in drug discovery.

Molecular dynamics of the viral life cycle: progress and prospects

Molecular dynamics (MD) simulations across spatiotemporal resolutions are widely applied to study viruses and represent the central technique uniting the field of computational virology. We discuss the progress of MD in elucidating the dynamics of the viral life cycle, including the status of modeling intact extracellular virions and leveraging advanced simulations to mimic active life cycle processes. We further remark on the prospects of MD for continued contributions to the basic science characterization of viruses, especially given the increasing availability of high-quality experimental data and supercomputing power. Overall, integrative computational methods that are closely guided by experiments are unmatched in the level of detail they provide, enabling-now and in the future-new discoveries relevant to thwarting viral infection.

Catalytic Magnesium as a Door Stop for DNA Sliding

The protein HIV Reverse Transcriptase (HIV RT) synthesizes a DNA strand according to a template. During the synthesis, the polymerase slides on the double stranded DNA to allow the entry of a new nucleotide to the active site. We use Molecular Dynamics simulations to estimate the free energy profile and the time scale of the DNA-protein's relative displacement in the complex's closed state. We illustrate that the presence of the catalytic magnesium slows down the process. Upon removing the catalytic magnesium ion, the process is rapid and significantly faster than reopening the active site in preparation for the new substrate. We speculate that magnesium regulates DNA translocation. The magnesium locks the DNA into a specific orientation during the chemical addition of the nucleotide. The release of Mg²⁺ eases DNA sliding and the acceptance of a new substrate.

Structural Mechanism of ω-Currents in a Mutated Kv7.2 Voltage Sensor Domain from Molecular Dynamics Simulations

Activation of voltage-gated ion channels is regulated by conformational changes of the voltage sensor domains (VSDs), four water- and ion-impermeable modules peripheral to the central, permeable pore domain. Anomalous currents, defined as ω-currents, have been recorded in response to mutations of residues on the VSD S4 helix and associated with ion fluxes through the VSDs. In humans, gene defects in the potassium channel Kv7.2 result in a broad range of epileptic disorders, from benign neonatal seizures to severe epileptic encephalopathies. Experimental evidence suggests that the R207Q mutation in S4, associated with peripheral nerve hyperexcitability, induces ω-currents at depolarized potentials, but the fine structural details are still elusive. In this work, we use atom-detailed molecular dynamics simulations and a refined model structure of the Kv7.2 VSD in the active conformation in a membrane/water environment to study the effect of R207Q and four additional mutations of proven clinical importance. Our results demonstrate that the R207Q mutant shows the most pronounced increase of hydration in the internal VSD cavity, a feature favoring the occurrence of ω-currents. Free energy and kinetics calculations of sodium permeation through the native and mutated VSD indicate as more favorable the formation of a cationic current in the latter. Overall, our simulations establish a mechanistic linkage between genetic variations and their physiological outcome, by providing a computational description that includes both thermodynamic and kinetic features of ion permeation associated with ω-currents.

Optimized incorporation of an unnatural fluorescent amino acid affords measurement of conformational dynamics governing high-fidelity DNA replication

DNA polymerase from bacteriophage T7 undergoes large, substrate-induced conformational changes that are thought to account for high replication fidelity, but prior studies were adversely affected by mutations required to construct a Cys-lite variant needed for site-specific fluorescence labeling. Here we have optimized the direct incorporation of a fluorescent un-natural amino acid, (7-hydroxy-4-coumarin-yl)-ethylglycine, using orthogonal amber suppression machinery in Escherichia coli MS methods verify that the unnatural amino acid is only incorporated at one position with minimal background. We show that the single fluorophore provides a signal to detect nucleotide-induced conformational changes through equilibrium and stopped-flow kinetic measurements of correct nucleotide binding and incorporation. Pre-steady-state chemical quench methods show that the kinetics and fidelity of DNA replication catalyzed by the labeled enzyme are largely unaffected by the unnatural amino acid. These advances enable rigorous analysis to establish the kinetic and mechanistic basis for high-fidelity DNA replication.