Accurate prediction of dynamic protein-ligand binding using P-score ranking.

Protein-ligand binding prediction typically relies on docking methodologies and associated scoring functions to propose the binding mode of a ligand in a biological target. Significant challenges are associated with this approach, including the flexibility of the protein-ligand system, solvent-mediated interactions, and associated entropy changes. In addition, scoring functions are only weakly accurate due to the short time required for calculating enthalpic and entropic binding interactions. The workflow described here attempts to address these limitations by combining supervised molecular dynamics with dynamical averaging quantum mechanics fragment molecular orbital. This combination significantly increased the ability to predict the experimental binding structure of protein-ligand complexes independent from the starting position of the ligands or the binding site conformation. We found that the predictive power could be enhanced by combining the residence time and interaction energies as descriptors in a novel scoring function named the P-score. This is illustrated using six different protein-ligand targets as case studies.

An Electromagnetic Vibration Energy Harvester with a Tunable Mass Moment of Inertia.

This paper presents a vibration-based electromagnetic energy harvester whose resonance frequency can be adjusted to match that of the excitation. Frequency adjustment is attained by controlling a rotatable arm, with tuning masses, at the tip of a cantilever-type energy harvester, thereby changing the effective mass moment of inertia of the system. The rotatable arm is mounted on a servomotor that is autonomously controlled through a microcontroller and a photo sensor to keep the device at resonance for maximum power generation. A mathematical model is developed to predict the system response for different design parameters and to estimate the generated power. The system is investigated analytically by a distributed-parameter model to study the natural frequency variation and dynamic response. The analytical model is verified experimentally where the frequency is tuned from 8 to 10.25 Hz. A parametric study is performed to study the effect of each parameter on the system behavior.

Discovery and characterization of noncanonical E2-conjugating enzymes.

E2-conjugating enzymes (E2s) play a central role in the enzymatic cascade that leads to the attachment of ubiquitin to a substrate. This process, termed ubiquitylation, is required to maintain cellular homeostasis and affects almost all cellular process. By interacting with multiple E3 ligases, E2s dictate the ubiquitylation landscape within the cell. Since its discovery, ubiquitylation has been regarded as a posttranslational modification that specifically targets lysine side chains (canonical ubiquitylation). We used Matrix-Assisted Laser Desorption/Ionization-Time Of Flight Mass Spectrometry to identify and characterize a family of E2s that are instead able to conjugate ubiquitin to serine and/or threonine. We used structural modeling and prediction tools to identify the key activity determinants that these E2s use to interact with ubiquitin as well as their substrates. Our results unveil the missing E2s necessary for noncanonical ubiquitylation, underscoring the adaptability and versatility of ubiquitin modifications.