In this study, we aimed to develop a new ligand-based virtual screening approach using an effective shape-overlapping procedure and a more robust scoring function (denoted by the HWZ score for convenience). The HWZ score-based virtual screening approach was tested against the compounds for 40 protein targets available in the Database of Useful Decoys (DUD) (dud.docking.org/jahn/), and the virtual screening performance was evaluated in terms of the area under the ROC curve (AUC), Enrichment Factor (EF), and Hit Rate (HR), demonstrating an improved overall performance compared to other popularly used approaches examined. In particular, the HWZ score-based virtual screening led to an average AUC value of 0.84 ± 0.02 (95% confidence interval) for the 40 targets. The average HR values at top 1% and 10% of the active compounds for the 40 targets were 46.3% ± 6.7% and 59.2% ± 4.7%, respectively. In addition, the performance of the HWZ score-based virtual screening approach is less sensitive to the choice of the target.

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We present an efficient and rational ligand/structure shape-based virtual screening approach combining our previous ligand shape-based similarity SABRE (shape-approach-based routines enhanced) and the 3D shape of the receptor binding site. Our approach exploits the pharmacological preferences of a number of known active ligands to take advantage of the structural diversities and chemical similarities, using a linear combination of weighted molecular shape density. Furthermore, the algorithm generates a consensus molecular-shape pattern recognition that is used to filter and place the candidate structure into the binding pocket. The descriptor pool used to construct the consensus molecular-shape pattern consists of four dimensional (4D) fingerprints generated from the distribution of conformer states available to a molecule and the 3D shapes of a set of active ligands computed using SABRE software. The virtual screening efficiency of SABRE was validated using the Database of Useful Decoys (DUD) and the filtered version (WOMBAT) of 10 DUD targets. The ligand/structure shape-based similarity SABRE algorithm outperforms several other widely used virtual screening methods which uses the data fusion of multiscreening tools (2D and 3D fingerprints) and demonstrates a superior early retrieval rate of active compounds (EF(0.1%) = 69.0% and EF(1%) = 98.7%) from a large size of ligand database (∼95,000 structures). Therefore, our developed similarity approach can be of particular use for identifying active compounds that are similar to reference molecules and predicting activity against other targets (chemogenomics). An academic license of the SABRE program is available on request.

The time-dependent density functional theory (TDDFT) method has been carried out to investigate the excited-state hydrogen-bonding dynamics of 4-aminophthalimide (4AP) in hydrogen-donating water solvent. The infrared spectra of the hydrogen-bonded solute-solvent complexes in electronically excited state have been calculated using the TDDFT method. We have demonstrated that the intermolecular hydrogen bond C= O...H-O and N-H...O-H in the hydrogen-bonded 4AP-(H(2)O)(2) trimer are significantly strengthened in the electronically excited state by theoretically monitoring the changes of the bond lengths of hydrogen bonds and hydrogen-bonding groups in different electronic states. The hydrogen bonds strengthening in the electronically excited state are confirmed because the calculated stretching vibrational modes of the hydrogen bonding C=O, amino N-H, and H-O groups are markedly red-shifted upon photoexcitation. The calculated results are consistent with the mechanism of the hydrogen bond strengthening in the electronically excited state, while contrast with mechanism of hydrogen bond cleavage. Furthermore, we believe that the transient hydrogen bond strengthening behavior in electroniclly excited state of chromophores in hydrogen-donating solvents exists in many other systems in solution.

In this work, we extend our previous ligand shape-based virtual screening approach by using the scoring function Hamza-Wei-Zhan (HWZ) score and an enhanced molecular shape-density model for the ligands. The performance of the method has been tested against the 40 targets in the Database of Useful Decoys and compared with the performance of our previous HWZ score method. The virtual screening results using the novel ligand shape-based approach demonstrated a favorable improvement (area under the receiver operator characteristics curve AUC = .89 ± .02) and effectiveness (hit rate HR(1%) = 53.0% ± 6.3 and HR(10%) = 71.1% ± 4.9). The comparison of the overall performance of our ligand shape-based method with the highest ligand shape-based virtual screening approach using the data fusion of multi queries showed that our strategy takes into account deeper the chemical information of the set of active ligands. Furthermore, the results indicated that our method are suitable for virtual screening and yields superior prediction accuracy than the other study derived from the data fusion using five queries. Therefore, our novel ligand shape-based screening method constitutes a robust and efficient approach to the 3D similarity screening of small compounds and open the door to a whole new approach to drug design by implementing the method in the structure-based virtual screening.

Anilido-oxazoline-ligated rare-earth metal complexes show strong fluorescence emissions and good catalytic performance on isoprene polymerization with high cis-1,4-selectivity.

The time-dependent density functional theory (TDDFT) method has been carried out to investigate the hydrogen-bonding dynamics of methyl acetate ( CH 3 CO 2 CH 3) in hydrogen-donating water solvent. The ground-state geometry optimizations, electronic transition energies and corresponding oscillation strengths of the low-lying electronically-excited states for the isolated CH 3 CO 2 CH 3 and H2O monomers, the hydrogen-bonded CH3CO2CH3-(H2O)1, 2 complexes have been calculated using DFT and TDDFT methods respectively. One intermolecular hydrogen bond C=O⋯H–O is formed between CH3CO2CH3 and one water molecule in CH3CO2CH3-H2O dimer. Meanwhile, in CH3CO2CH3-(H2O)2 trimer, two intermolecular hydrogen bonds C=O⋯H–O are formed between CH3CO2CH3 and two water molecules. By theoretically monitoring the excitation energy changes among the CH3CO2CH3 monomer, the CH3CO2CH3-H2O dimer, and the CH3CO2CH3-(H2O)2 trimer, we have demonstrated interestingly that in some electronically-excited states, the intermolecular hydrogen bonds are strengthened inducing electronic spectral redshifts, while in others weakened with electronic spectral blueshifts. The phenomenon that hydrogen bonds are strengthened in some electronic states while weakened in others can arouse further probe into CH3CO2CH3-(H2O)1, 2 complexes.

Two factors contribute to the inefficiency associated with screening pharmaceutical library collections as a means of identifying new drugs: [1] the limited success of virtual screening (VS) methods in identifying new scaffolds; [2] the limited accuracy of computational methods in predicting off-target effects. We recently introduced a 3D shape-based similarity algorithm of the SABRE program, which encodes a consensus molecular shape pattern of a set of active ligands into a 4D fingerprint descriptor. Here, we report a mathematical model for shape similarity comparisons and ligand database filtering using this 4D fingerprint method and benchmarked the scoring function HWK (Hamza–Wei–Korotkov), using the 81 targets of the DEKOIS database. Subsequently, we applied our combined 4D fingerprint and HWK scoring function VS approach in scaffold-hopping and drug repurposing using the National Cancer Institute (NCI) and Food and Drug Administration (FDA) databases, and we identified new inhibitors with different scaffolds of MycP1 protease from the mycobacterial ESX-1 secretion system. Experimental evaluation of nine compounds from the NCI database and three from the FDA database displayed IC50 values ranging from 70 to 100 μM against MycP1 and possessed high structural diversity, which provides departure points for further structure–activity relationship (SAR) optimization. In addition, this study demonstrates that the combination of our 4D fingerprint algorithm and the HWK scoring function may provide a means for identifying repurposed drugs for the treatment of infectious diseases and may be used in the drug-target profile strategy.