We have developed a new methodology for protein-ligand docking and scoring, WScore, incorporating a flexible description of explicit water molecules. The locations and thermodynamics of the waters are derived from a WaterMap molecular dynamics simulation. The water structure is employed to provide an atomic level description of ligand and protein desolvation. WScore also contains a detailed model for localized ligand and protein strain energy and integrates an MM-GBSA scoring component with these terms to assess delocalized strain of the complex. Ensemble docking is used to take into account induced fit effects on the receptor conformation, and protein reorganization free energies are assigned via fitting to experimental data. The performance of the method is evaluated for pose prediction, rank ordering of self-docked complexes, and enrichment in virtual screening, using a large data set of PDB complexes and compared with the Glide SP and Glide XP models; significant improvements are obtained.

No abstract

Direction-of-arrival (DoA) estimation of incoming electromagnetic signals can play a critical role in surveillance, sensing, and cognitive radio applications. Typical DoA antenna arrays use an aperture measuring several wavelengths across to ensure reliable measurement of phase information. For a UHF application, such an array would need to be a few meters across-too large for a portable array. This work demonstrates a practical DoA array composed of antennas with diverse radiation patterns which is combined with an algorithm which relies primarily on amplitude information rather than phase information. This approach yields a much smaller array with similar direction-finding capabilities to larger ones. A calibration procedure captures the antenna responses, including the parasitic effects of the closely spaced antennas. The calibrated array and direction-finding algorithm then achieves measured accuracy with resolution of six degrees with no front-to-back or quadrant ambiguities. Index Terms-Direction-of-arrival (DoA), electrically small antenna, multiple signal classification (MuSiC), minimum-variance distortionless response (MVDR), vector sensor.

His interests include (but are not limited to) joyful teaching, empirically-sound educational research, campus and online courses, computer science, unlocking the potential of underrepresented minorities, improving accessibility and creating novel methods that encourage new learning opportunities and foster vibrant learning communities.

The authors propose an adaptive frequency hopping (AFH) algorithm, entitled robust adaptive frequency hopping (RAFH), for providing increased reliability of a wireless medical telemetry system (WMTS) under coexistence environment with non-medical devices. The conventional AFH scheme classifies channels into 'good' or 'bad' according to the threshold-based on-off decision by packet error rate (PER) measurement, and only uses good channels with a uniform hop probability. Unlike the conventional AFH scheme, RAFH is a novel technique, which solves a constrained entropy maximisation problem and assigns every channel a different hop probability as a decreasing function of the measured PER. The key novelty of RAFH over existing AFH schemes is that it reflects the relative channel condition by assigning non-uniform hop probabilities. By adopting constrained entropy maximisation, RAFH not only improves the average PER, but also reduces the PER fluctuation over time under a dynamic interference environment, both of which increase the reliability of WMTS. Through extensive simulation, we show that RAFH outperforms basic frequency hopping (FH) and the conventional AFH with respect to the PER under various scenarios of dynamic interference.