Theoretical Exploring of a Molecular Mechanism for Melanin Inhibitory Activity of Calycosin in Zebrafish.

Tyrosinase is an oxidase that is the rate-limiting enzyme for controlling the production of melanin in the human body. Overproduction of melanin can lead to a variety of skin disorders. Calycosin is an isoflavone from Astragali Radix, which is a traditional Chinese medicine that exhibits several pharmacological activities including skin whitening. In our study, the inhibitory effect of calycosin on melanin production is confirmed in a zebrafish in vivo model by comparing with hydroquinone, kojic acid, and arbutin, known as tyrosinase inhibitors. Moreover, the inhibitory kinetics of calycosin on tyrosinase and their binding mechanisms are determined using molecular docking techniques, molecular dynamic simulations, and free energy analysis. The results indicate that calycosin has an obvious inhibitory effect on zebrafish pigmentation at the concentration of 7.5 µM, 15 µM, and 30 µM. The IC50 of calycosin is 30.35 µM, which is lower than hydroquinone (37.35 µM), kojic acid (6.51 × 103 µM), and arbutin (3.67 × 104 µM). Furthermore, all the results of molecular docking, molecular dynamics simulations, and free energy analysis suggest that calycosin can directly bind to the active site of tyrosinase with very good binding affinity. The study indicates that the combination of computer molecular modeling and zebrafish in vivo assay would be feasible in confirming the result of the in vitro test and illustrating the target-binding information.

3D-QSAR, molecular docking, and molecular dynamics simulation of a novel thieno[3,4-d]pyrimidine inhibitor targeting human immunodeficiency virus type 1 reverse transcriptase.

Human immunodeficiency virus type 1 reverse transcriptase (HIV-1 RT) is one of the most attractive drug targets for the treatment of AIDS. In this study, 67 thieno[3,4-d]pyrimidine derivatives were selected as novel HIV-1 RT inhibitors to combat viral resistance, and were subjected to 3 D-QSAR studies using CoMFA, CoMSIA, and T-CoMFA. In the 3 D-QSAR study, two methods of ligand-based alignment and pharmacophore-based alignment were used. The results showed that CoMFA (n = 8; q2 = 0.594; r2 = 0.974) and CoMSIA (n = 7; q2 = 0.528; r2 = 0.965) have good stability and predictability. The molecular docking study showed that the hydrogen bonding and van der Waals interactions of key residues such as Leu100, Lys101, Val106, Phe227 and Pro236 play an important role in ligand-receptor binding. Based on these results, 12 new thieno[3,4-d]pyrimidines were designed and their activities were predicted; the results indicated that these compounds have good predictive activity and reasonably good ADME/T profiles. MD simulation analysis of 50 ns showed that compound 23j formed four hydrogen bonds with the residues (Lys101, Lys104, Val106 and Thr318), and binds more closely to HIV-1 RT than compound 23j. Furthermore, the group at the R1 position and the horseshoe-like conformation of these compounds are critical for the inhibitory activity and stability. These results provide useful insights for the discovery and design of a new generation of HIV-1 RT inhibitors.Communicated by Ramaswamy H. Sarma.

Structural insight into the serotonin (5-HT) receptor family by molecular docking, molecular dynamics simulation and systems pharmacology analysis.

Serotonin (5-HT) receptors are proteins involved in various neurological and biological processes, such as aggression, anxiety, appetite, cognition, learning, memory, mood, sleep, and thermoregulation. They are commonly associated with drug abuse and addiction due to their importance as targets for various pharmaceutical and recreational drugs. However, due to a high sequence similarity/identity among 5-HT receptors and the unavailability of the 3D structure of the different 5-HT receptor, no report was available so far regarding the systematical comparison of the key and selective residues involved in the binding pocket, making it difficult to design subtype-selective serotonergic drugs. In this work, we first built and validated three-dimensional models for all 5-HT receptors based on the existing crystal structures of 5-HT1B, 5-HT2B, and 5-HT2C. Then, we performed molecular docking studies between 5-HT receptors agonists/inhibitors and our 3D models. The results from docking were consistent with the known binding affinities of each model. Sequentially, we compared the binding pose and selective residues among 5-HT receptors. Our results showed that the affinity variation could be potentially attributed to the selective residues located in the binding pockets. Moreover, we performed MD simulations for 12 5-HT receptors complexed with ligands; the results were consistent with our docking results and the reported data. Finally, we carried out off-target prediction and blood-brain barrier (BBB) prediction for Captagon using our established hallucinogen-related chemogenomics knowledgebase and in-house computational tools, with the hope to provide more information regarding the use of Captagon. We showed that 5-HT2C, 5-HT5A, and 5-HT7 were the most promising targets for Captagon before metabolism. Overall, our findings can provide insights into future drug discovery and design of medications with high specificity to the individual 5-HT receptor to decrease the risk of addiction and prevent drug abuse.

A convenient four-component one-pot synthesis of 2-amino-1,3,4-thiadiazoles in water.

A novel four-component one-pot approach for the synthesis of 2-amino-1,3,4-thiadiazoles from primary amines, carbon disulfide, hydrazine, and acyl chlorides has been developed. A series of 5-substituted-2-amino-1,3,4-thiadiazoles were synthesized in medium-to-good yields utilizing this newly developed method.

A facile in situ synthesis route for CuInS(2) quantum-dots/In(2)S(3) co-sensitized photoanodes with high photoelectric performance.

CuInS2 quantum-dot sensitized TiO2 photoanodes with In2S3 buffer layer were in situ prepared via chemical bath deposition of In2S3, where the Cd-free In2S3 layer then reacted with TiO2/CuxS which employed a facile SILAR process to deposit CuxS quantum dots on TiO2 film, followed by a covering process with ZnS layer. Polysulfide electrolyte and Cu2S on FTO glass counter electrode were used to provide higher photovoltaic performance of the constructed devices. The characteristics of the quantum dots sensitized solar cells were studied in more detail by optical measurements, photocurrent-voltage performance measurements, and impedance spectroscopy. On the basis of optimal CuxS SILAR cycles, the best photovoltaic performance with power conversion efficiency (η) of 1.62% (Jsc = 6.49 mA cm(-2), Voc = 0.50 V, FF = 0.50) under full one-sun illumination was achieved by using Cu2S counter electrode. Cu2S-FTO electrode exhibits superior electrocatalytic ability for the polysulfide redox reactions relative to that of Pt-FTO electrode.

QSAR study on MHC class I a alleles based on the novel parameters of amino acids.

MHC-epitope binding plays a key role in the cellular immune response. Accurate prediction of MHC-epitope binding affinity can greatly expedite epitope screening by reducing costs and experimental effort. In this paper, 13 T descriptors， which derived from 544 physicochemical properties of the natural amino acids, were used to characterize 4 MHC class I alleles epitope peptide sequences, the optimal QSAR models were constructed by using stepwise regression combines with multiple linear regression (STR-MLR). For HLA-A*0201, HLA-A*0203, HLA-A*0206 and HLA-A*1101 alleles, the leave one out cross validation values (Q(2)(train)) were 0.581, 0.553, 0.525 and 0.588, the correlation coefficients (R(2)(train)) of training datasets were 0.607, 0.582, 0.556 and 0.606, the correlation coefficients (R(2)(test)) of test datasets were 0.533, 0.506, 0.501 and 0.502, respectively. The results showed that all models can obtain good performance for prediction and explain the mechanism of interaction between MHC and epitope. The descriptors will be useful in structure characterization and activity prediction of peptide sequences.

New descriptors of amino acids and their application to peptide QSAR study.

A new set of descriptors was derived from a matrix of three structural variables of the natural amino acid, including van der Waal's volume, net charge index and hydrophobic parameter of side residues. They were selected from many properties of amino acid residues, which have been validated being the key factors to influence the interaction between peptides and its protein receptor. They were then applied to structure characterization and QSAR analysis on bitter tasting di-peptide, agiotensin-converting enzyme inhibitor and bactericidal peptides by using multiple linear regression (MLR) method. The leave one out cross validation values (Q(2)) were 0.921, 0.943 and 0.773. The multiple correlation coefficients (R(2)) were 0.948, 0.970 and 0.926, the root mean square (RMS) error for estimated error were 0.165, 0.154 and 0.41, respectively for bitter tasting di-peptide, angiotensin-converting enzyme inhibitor and bactericidal peptides. Test sets of peptides were used to validate the quantitative model, and it was shown that all these QSAR models had good predictability for outside samples. The results showed that, in comparison with the conventional descriptors, the new set of descriptors is a useful structure characterization method for peptide QSAR analysis, which has multiple advantages, such as definite physical and chemical meaning, easy to get, and good structural characterization ability.