Data Management System for Distributed Virtual Screening

High throughput docking (HTD) using high performance computing platforms is a multidisciplinary challenge. To handle HTD data effectively and efficiently, we have developed a distributed virtual screening data management system (DVSDMS) in which the data handling and the distribution of jobs are realized by the open-source structured query language database software MySQL. The essential concept of DVSDMS is the separation of the data management from the docking and ranking applications. DVSDMS can be used to dock millions of molecules effectively, monitor the process in real time, analyze docking results promptly, and process up to 108 poses by energy ranking techniques. In an HTD campaign to identify kinase inhibitors a low cost Linux PC has allowed DVSDMS to efficiently assign the workload to more than 500 computing clients. Notably, in a stress test of DVSDMS that emulated a large number of clients, about 60 molecules per second were distributed to the clients for docking, which indicates that DVSDMS can run efficiently on very large compute cluster (up to about 40000 cores)

Free Energy Guided Sampling

A free energy-guided sampling (FEGS) method is proposed for accelerating exploration of conformational space in unbiased molecular dynamics. Using the cut-based free energy profile and Markov state models, FEGS speeds up sampling of the canonical ensemble by iteratively restarting multiple short simulations in parallel from regions of the free energy surface visited rarely. This exploration stage is followed by a refinement stage in which multiple independent runs are initiated from Boltzmann distributed conformations. Notably, FEGS does not require either collective variables or reaction coordinates and can control the kinetic distance from the starting conformation. We applied FEGS to the alanine dipeptide, which has a human-comprehensible two-dimensional free energy landscape, and a three-stranded antiparallel β-sheet peptide of 20 residues whose folding/unfolding process is governed by a delicate interplay of enthalpy and entropy. For these two systems, FEGS speeds up the exploration of conformational space by 1 to 2 orders of magnitude with respect to conventional sampling and preserves the basins and barriers on the free energy profile

Free Energy Guided Sampling

A free energy-guided sampling (FEGS) method is proposed for accelerating exploration of conformational space in unbiased molecular dynamics. Using the cut-based free energy profile and Markov state models, FEGS speeds up sampling of the canonical ensemble by iteratively restarting multiple short simulations in parallel from regions of the free energy surface visited rarely. This <i>exploration</i> stage is followed by a <i>refinement</i> stage in which multiple independent runs are initiated from Boltzmann distributed conformations. Notably, FEGS does not require either collective variables or reaction coordinates and can control the kinetic distance from the starting conformation. We applied FEGS to the alanine dipeptide, which has a human-comprehensible two-dimensional free energy landscape, and a three-stranded antiparallel β-sheet peptide of 20 residues whose folding/unfolding process is governed by a delicate interplay of enthalpy and entropy. For these two systems, FEGS speeds up the exploration of conformational space by 1 to 2 orders of magnitude with respect to conventional sampling and preserves the basins and barriers on the free energy profile

Distribution of Reciprocal of Interatomic Distances: A Fast Structural Metric

We present a structural metric based on the Distribution of Reciprocal of Interatomic Distances (DRID) for evaluating geometrical similarity between two conformations of a molecule. A molecular conformation is described by a vector of 3<i>N</i> orientation-independent DRID descriptors where <i>N</i> is the number of molecular centroids, for example, the non-hydrogen atoms in all nonsymmetric groups of a peptide. For two real-world applications (pairwise comparison of snapshots from an explicit solvent simulation of a protease/peptide substrate complex and implicit solvent simulations of reversible folding of a 20-residue β-sheet peptide), the DRID-based metric is shown to be about 5 and 15 times faster than coordinate root-mean-square deviation (cRMSD) and distance root-mean-square deviation (dRMSD), respectively. A single core of a mainstream processor can perform about 10⁸ DRID comparisons in one-half a minute. Importantly, the DRID metric has closer similarity to kinetic distance than does either cRMSD or dRMSD. Therefore, DRID is suitable for clustering molecular dynamics trajectories for kinetic analysis, for example, by Markov state models. Moreover, conformational space networks and free energy profiles derived by DRID-based clustering preserve the kinetic information

Is Quantum Mechanics Necessary for Predicting Binding Free Energy?

To take into account polarization effects, the linear interaction energy model with continuum electrostatic solvation (LIECE) is supplemented by the linear-scaling semiempirical quantum mechanical calculation of the intermolecular electrostatic energy (QMLIECE). QMLIECE and LIECE are compared on three enzymes belonging to different classes: the West Nile virus NS3 serine protease (WNV PR), the aspartic protease of the human immunodeficiency virus (HIV-1 PR), and the human cyclin-dependent kinase 2 (CDK2). QMLIECE is superior for 44 peptidic inhibitors of WNV PR because of the different amount of polarization due to the broad range of formal charges of the inhibitors (from 0 to 3). On the other hand, QMLIECE and LIECE show similar accuracy for 24 peptidic inhibitors of HIV-1 PR (20 neutral and 4 with one formal charge) and for 73 CDK2 inhibitors (all neutral). These results indicate that quantum mechanics is essential when the inhibitor/protein complexes have highly variable charge−charge interactions

Supplementary document for Effect of NIR light on the permeability of the blood-brain barriers in vitro models - 5362368.pdf

supporting dat

Online Pressure Change Focusing-Supercritical Fluid Selective Extraction Chromatography for Analyzing Chiral Drugs in Microliter-Scale Plasma Samples

The online coupling technique of sample preparation with chromatography is a frontier topic in analytical chemistry since it minimizes errors caused by sample loss, shortens analysis time, and reduces solvent consumption. An online pressure change focusing-supercritical fluid selective extraction chromatography (PCF-SFSEC) technique was developed in this study, realizing extraction, purification, separation, and detection in a single run with only microliter-scale samples. The pressure change focusing strategy achieved column-head stacking by decreasing the dissolving capacity of the supercritical fluid, enabling the large volume introduction of extractants into supercritical fluid chromatography without causing peak broadening or distortion. All the extracts could be directly loaded into the chromatography system without split flow. Based on the supercritical fluid selective extraction (SFSE) strategy, the sorbents removed interferences and water from samples, effectively alleviating matrix effects and realizing the direct aqueous sample analysis. The efficiency of online PCF-SFSEC was demonstrated by the enantioselective analysis of 22 chiral drugs in rat plasma, covering eight categories with different pharmacological effects. The entire analysis took 25 min, consuming only 5 μL samples. All analytes in PCF-SFSEC obtained sharp and symmetrical peaks with resolutions higher than 1.0, and 86% had resolutions higher than 1.5. Limits of quantification (LOQs) ranged from 0.0600 to 32.1 μg/L. Recoveries were in the range of 75.8–117.2%. In addition, the developed approach obtained more satisfactory repeatability and significantly reduced matrix effects than conventional methods. The newly established online PCF-SFSEC technique is believed to be a green and powerful tool for the chiral analysis of complex samples

Supplementary document for Effect of NIR light on the permeability of the blood-brain barriers in vitro models - 5362368.pdf

supporting dat

Supplementary document for Effect of NIR light on the permeability of the blood-brain barriers in vitro models - 5511799.pdf

supplemental dat

Microwave Accelerated Selective Soxhlet Extraction for the Determination of Organophosphorus and Carbamate Pesticides in Ginseng with Gas Chromatography/Mass Spectrometry

Microwave accelerated selective Soxhlet extraction (MA-SSE), a novel selective extraction technique, was investigated in this study. A Soxhlet extraction system containing a glass filter was designed as an extractor. During the procedure of MA-SSE, both the target analytes and the interfering components were extracted from the sample into the extraction solvent enhanced by microwave irradiation. After the solvent flowed though the sorbent, the interfering components were adsorbed by the sorbent, and the target analytes remaining in the solvent were collected in the extraction bottle. No cleanup or filtration was required after extraction. The efficiency of the MA-SSE approach was demonstrated in the determination of organophosphorus and carbamate pesticide residues in ginseng by gas chromatography/mass spectrometry (GC/MS). Under the optimized conditions, low limits of detection (0.050–0.50 μg/kg) were obtained. The recoveries were in the range of 72.0–110.1% with relative standard deviations less than 7.1%. Because of the effect of microwave irradiation, MA-SSE showed significant advantage compared with other extraction techniques. The sorbent used in this study showed good cleanup ability. The mechanism of MA-SSE was demonstrated to be based on the rupture of the cell walls according to the structural changes of ginseng samples. On the basis of the results, MA-SSE as a simple and effective sample preparation technique for the analysis of pesticide residues in complex matrixes shows great promise