A5022767991- Protein Structure and Dynamics
- Advanced Thermodynamics and Statistical Mechanics
- Micro and Nano Robotics
- Machine Learning in Materials Science
- Computational Drug Discovery Methods
- Spectroscopy and Quantum Chemical Studies
- Photoreceptor and optogenetics research
- Advanced Chemical Physics Studies
- Hemoglobin structure and function
- Advanced NMR Techniques and Applications
- Malaria Research and Control
- Molecular Junctions and Nanostructures
- Quantum, superfluid, helium dynamics
- HIV/AIDS drug development and treatment
- Nanomaterials for catalytic reactions
- Pharmacogenetics and Drug Metabolism
- Nanoparticle-Based Drug Delivery
- Trypanosoma species research and implications
- High-pressure geophysics and materials
- Innovative Microfluidic and Catalytic Techniques Innovation
- HIV Research and Treatment
University of California, San Diego
2018-2023
University of Montana
2018-2023
UC San Diego Health System
2020
Center for Life Sciences
2018
Peking University
2018
Beijing National Laboratory for Molecular Sciences
2018
Due to diverse reasons, most drug candidates can not eventually become marketed drugs. Developing reliable computational methods for prediction of druglikeness candidate compounds is vital importance improve the success rate discovery and development. In this study, we used deep autoencoder neural networks construct classification models. We collected datasets drugs (represented by ZINC World Drug), bioactive molecules MDDR WDI), common All Purchasable ACD). Compounds were encoded with MOLD2...
We determined the effectiveness of absolute binding free energy (ABFE) calculations to refine selection active compounds in virtual compound screening, a setting where more commonly used relative approach is not readily applicable. To do this, we conducted baseline docking structurally diverse DUD-E database for three targets, BACE1, CDK2 and thrombin, followed by ABFE with high scores. The alone achieved solid enrichment over decoys. Encouragingly, then improved on this baseline. Analysis...
The parameterization of torsional/dihedral angle potential energy terms is a crucial part developing molecular mechanics force fields. Quantum mechanical (QM) methods are often used to provide samples the surface (PES) for fitting empirical parameters in these field terms. To ensure that sampled configurations thermodynamically feasible, constrained QM geometry optimizations typically carried out, which relax orthogonal degrees freedom while fixing target torsion angle(s) on grid values....
Here, we present remarkable epoxyketone-based proteasome inhibitors with low nanomolar in vitro potency for blood-stage Plasmodium falciparum and cytotoxicity human cells. Our best compound has more than 2,000-fold greater selectivity erythrocytic-stage P. over HepG2 H460 cells, which is largely driven by the accommodation of parasite a D-amino acid P3 position preference difluorobenzyl group P1 position. We isolated from cell extracts determined that 171-fold potent at inhibiting β5 subunit...
<div>The parameterization of torsional / dihedral angle potential energy terms is a crucial part developing molecular mechanics force fields.</div><div>Quantum mechanical (QM) methods are often used to provide samples the surface (PES) for fitting empirical parameters in these field terms.</div><div>To ensure that sampled configurations thermodynamically feasible, constrained QM geometry optimizations typically carried out, which relax orthogonal degrees freedom...
Generation of drug-like molecules with high binding affinity to target proteins remains a difficult and resource-intensive task in drug discovery. Existing approaches primarily employ reinforcement learning, Markov sampling, or deep generative models guided by Gaussian processes, which can be prohibitively slow when generating calculated computationally-expensive physics-based methods. We present Latent Inceptionism on Molecules (LIMO), significantly accelerates molecule generation an...
We analyze light-driven overcrowded alkene-based molecular motors, an intriguing class of small molecules that have the potential to generate MHz-scale rotation rates. The full process is simulated at multiple scales by combining quantum surface-hopping dynamics (MD) simulations for photoisomerization step with classical MD thermal helix inversion step. A Markov state analysis resolves conformational substates, their interconversion kinetics, and roles in motor's process. Furthermore, motor...
Abstract A number of enzymes reportedly exhibit enhanced diffusion in the presence their substrates, with a Michaelis-Menten-like concentration dependence. Although no definite explanation this phenomenon has emerged, physical picture enzyme self-propulsion using energy from catalyzed reaction been widely considered. Here, we present kinematic and thermodynamic analysis that is independent any specific propulsion mechanism. Using theory, along biophysical data compiled for all so far shown...
The parameterization of torsional / dihedral angle potential energy terms is a crucial part developing molecular mechanics force fields.Quantum mechanical (QM) methods are often used to provide samples the surface (PES) for fitting empirical parameters in these field terms.To ensure that sampled configurations thermodynamically feasible, constrained QM geometry optimizations typically carried out, which relax orthogonal degrees freedom while fixing target torsion angle(s) on grid...
We analyze light-driven overcrowded alkene-based molecular motors, an intriguing class of small molecules that have the potential to generate MHz-scale rotation rates. The full process is simulated at multiple scales by combining quantum surface-hopping dynamics (MD) simulations for photoisomerization step with classical MD thermal helix inversion step. A Markov state analysis resolves conformational substates, their interconversion kinetics, and roles in motor’s process. Furthermore, motor...
Many enzymes appear to diffuse faster in the presence of substrate and drift either up or down a concentration gradient their substrate. Observations these phenomena, termed enhanced enzyme diffusion (EED) chemotaxis, respectively, lead novel view as active matter. Enzyme chemotaxis EED may be important biology, they could have practical applications biotechnology nanotechnology. They also are considerable biophysical interest; indeed, physical mechanisms still quite uncertain. This review...
We analyze light-driven overcrowded alkene-based molecular motors, an intriguing class of small molecules that have the potential to generate MHz-scale rotation rates. The full process is simulated at multiple scales by combining quantum surface-hopping dynamics (MD) simulations for photoisomerization step with classical MD thermal helix inversion step. A Markov state analysis resolves conformational substates, their interconversion kinetics, and roles in motor’s process. Furthermore, motor...
We determined the effectiveness of absolute binding free energy (ABFE) calculations to refine selection active compounds in virtual compound screening, a setting where more commonly used relative approach is not readily applicable. To do this, we conducted base- line docking structurally diverse DUD-E database for three targets, BACE1, CDK2 and thrombin, followed by ABFE with high scores. The alone achieved solid enrichment over decoys. Encour- agingly, then improved on this baseline....
ABSTRACT Here we present remarkable epoxyketone-based proteasome inhibitors with low nanomolar in vitro potency for blood-stage Plasmodium falciparum and cytotoxicity human cells. Our best compound has more than 2,600-fold greater selectivity erythrocytic-stage P. over HepG2 cells, which is largely driven by the accommodation of parasite a d -amino acid P3 position preference difluorobenzyl group P1 position. These compounds also significantly reduce parasitemia berghei mouse infection model...