Synthesis,Molecular Modeling,and Biological Evaluation of Novel Chiral Thiosemicarbazone Derivatives as Potent Anticancer Agents

A series of new chiral thiosemicarbazones derived from homochiral amines in both enantiomeric forms were synthesized and evaluated for their in vitro antiproliferative activity against A549 (human alveolar adenocarcinoma), MCF‐7 (human breast adenocarcinoma), HeLa (human cervical adenocarcinoma), and HGC‐27 (human stomach carcinoma) cell lines. Some of compounds showed inhibitory activities on the growth of cancer cell lines. Especially, compound 17b exhibited the most potent activity (IC₅₀ 4.6 μM) against HGC‐27 as compared with the reference compound, sindaxel (IC₅₀ 10.3 μM), and could be used as a lead compound to search new chiral thiosemicarbazone derivatives as antiproliferative agents. Chirality 27:177–188, 2015. © 2014 Wiley Periodicals, Inc.     

The pharmacophore of the human C5a anaphylatoxin.

We have determined which amino acids contribute to the pharmacophore of human C5a, a potent inflammatory mediator. A systematic mutational analysis of this 74-amino acid protein was performed and the effects on the potency of receptor binding and of C5a-induced intracellular calcium ion mobilization were measured. This analysis included the construction of hybrids between C5a and the homologous but unreactive C3a protein and site-directed mutagenesis. Ten noncontiguous amino acids from the structurally well-defined 4-helix core domain (amino acids 1-63) and the C-terminal arginine-containing tripeptide were found to contribute to the pharmacophore of human C5a. The 10 mostly charged amino acids from the core domain generally made small incremental contributions toward binding affinity, some of which were independent. Substitutions of the C-terminal amino acid Arg 74 produced the largest single effect. We also found the connection between these 2 important regions to be unconstrained.     

Conformational analysis of a potent SSTR3-selective somatostatin analogue by NMR in water solution.

The three-dimensional structure of a potent SSTR3-selective analogue of somatostatin, cyclo(3-14)H-Cys(3)-Phe(6)-Tyr(7)-D-Agl(8)(N(beta) Me, 2-naphthoyl)-Lys(9)-Thr(10)-Phe(11)-Cys(14)-OH (des-AA(1, 2, 4, 5, 12, 13)[Tyr(7), D-Agl(8)(N(beta) Me, 2-naphthoyl)]-SRIF) (peptide 1) has been determined by (1)H NMR in water and molecular dynamics (MD) simulations. The peptide exists in two conformational isomers differing mainly by the cis/trans isomerization of the side chain in residue 8. The structure of 1 is compared with the consensus structural motifs of other somatostatin analogues that bind predominantly to SSTR1, SSTR2/SSTR5 and SSTR4 receptors, and to the 3D structure of a non-selective SRIF analogue, cyclo(3-14)H-Cys(3)-Phe(6)-Tyr(7)-D-2Nal(8)-Lys(9)-Thr(10)-Phe(11)-Cys(14)-OH (des-AA(1, 2, 4, 5, 12, 13)[Tyr(7), D-2Nal(8)]-SRIF) (peptide 2). The structural determinant factors that could explain selectivity of peptide 1 for SSTR3 receptors are discussed.     

A Series of Benzylidenes Linked to Hydrazine‐1‐carbothioamide as Tyrosinase Inhibitors: Synthesis,Biological Evaluation and Structure−Activity Relationship

Tyrosinase is a type 3 copper enzyme responsible for skin pigmentation disorders, skin cancer, and enzymatic browning of vegetables and fruits. In the present article, 12 small molecules of 2‐benzylidenehydrazine‐1‐carbothioamide were designed, synthesized and evaluated for their anti‐tyrosinase activities followed by molecular docking and pharmacophore‐based screening. Among synthesized thiosemicarbazone derivatives, one compound, (2E)‐2‐[(4‐nitrophenyl)methylidene]hydrazine‐1‐carbothioamide, is the strongest inhibitor of mushroom tyrosinase with IC₅₀ of 0.05 μM which demonstrated a 128‐fold increase in potency compared to the positive control. Kinetic studies also revealed mix type inhibition by this compound. Docking studies confirmed the complete fitting of the synthesized compounds into the tyrosinase active site. The results underline the potential of 2‐benzylidenehydrazine‐1‐carbothioamides as potent pharmacophore to extend the tyrosinase inhibition in drug discovery.     

Pharmacophore mapping and in silico screening to identify new potent leads for A2A adenosine receptor as antagonists

A_2A adenosine receptor (AR) antagonists play an important role in neurodegenerative diseases like Parkinson’s disease. A 3D-QSAR study of A_2A AR antagonists, was taken up to design best pharmacophore model. The pharmacophoric features (ADHRR) containing a hydrogen bond acceptor (A), a hydrogen bond donor (D), a hydrophobic group (H) and two aromatic rings (R), is projected as the best predictive pharmacophore model. The QSAR model was further treated as a template for in silico search of databases to identify new scaffolds. The binding patterns of the leads with A_2A AR are analysed using docking studies and novel potent ligands of A_2A AR are projected.     

In silico insights into the identification of potential novel angiogenic inhibitors against human VEGFR-2: a new SAR-based hierarchical clustering approach

Abstract

In this study, binding efficiency of new pyrrolopyrimidine structural analogs against human vascular endothelial growth factor receptor-2 (VEGFR-2) were elucidated using integrated in silico methods. Optimized high-resolution model of VEGFR-2 was generated and adopted for structure-based virtual screening approaches. Pyrrolopyrimidine inhibitor (CP15) associated compounds were screened from PubChem database and subjected to virtual screening and comparative docking methods against the receptor ligand-binding domain. Accordingly, high efficient compounds were clustered with similarity indices through PubChem structure cluster module using single-linkage algorithm. Moreover, pharmacokinetics including drug metabolism activities of high-binding leads under investigation was portrayed using ADMET and similarity ensemble analysis. Optimal energy orientations of the selected protein model have been shown to be reliable, and highly recommended for screening and docking studies. Docking and clustering strategies were shown that nineteen candidates as most effective binders for VEGFR-2 than CP15, and are grouped as three classes. Lys⁸⁶⁸, Glu⁸⁸⁵, Cys⁹¹⁹, His¹⁰²⁶, Arg¹⁰²⁷, Asp¹⁰⁴⁶, and Gly¹⁰⁴⁸ residues were predicted as novel hotspot residues, and participate in H-bonds, π-cation, π-stacking, halogen bonds, and salt-bridges formation with ligands. These additional bonds are contributing extent stability that holds the receptor structure at flexible state, this make difficult to any further conformational changes for evoking angiogenic signals. The ADMET and similarity ensemble analysis results were strongly indicated that thirteen candidates as best ligands for angiogenesis targets. Altogether, these findings indicate potential angiogenic templates and their binding levels with VEGFR-2; sorted viewpoints could be useful as a promising way to describe potential angiogenesis inhibitors with related molecular targets.     

Structural insights of JAK2 inhibitors: pharmacophore modeling and ligand-based 3D-QSAR studies of pyrido-indole derivatives

Abstract

In this study we have performed pharmacophore modeling and built a 3D QSAR model for pyrido-indole derivatives as Janus Kinase 2 inhibitors. An efficient pharmacophore has been identified from a data set of 51 molecules and the identified pharmacophore hypothesis consisted of one hydrogen bond acceptor, two hydrogen bond donors and three aromatic rings, i.e. ADDRRR. A powerful 3D-QSAR model has also been constructed by employing Partial Least Square regression analysis with a regression coefficient of 0.97 (R²) and Q² of 0.95, and Pearson-R of 0.98.     

A profound computational study to prioritize the natural compound inhibitors against the P. falciparum orotidine-5-monophosphate decarboxylase enzyme

Abstract

In the current contribution, a multicomplex-based pharmacophore modeling approach was employed on the structural proteome of Plasmodium falciparum orotidine-5-monophosphate decarboxylase enzyme (PfOMPDC). Among the constructed pharmacophore models, the representative hypotheses were selected as the primary filter to screen the molecules with the complementary features responsible for showing inhibition. Thereafter, auxiliary evaluations were performed on the screened candidates via drug-likeness and molecular docking studies. Subsequently, the stability of the docked protein-ligand complexes was scrutinized by employing molecular dynamics simulations and molecular mechanics-Poisson Boltzmann surface area based free binding energy calculations. The stability the docked candidates was compared with the highly active crystallized inhibitor (3S9Y-FNU) to seek more potential candidates. All the docked molecules displayed stable dynamic behavior and high binding free energy in comparison to 3S9Y-FNU. The employed workflow resulted in the retrieval of five drug-like candidates with diverse scaffolds that may show inhibitory activity against PfOMPDC and could be further used as the novel scaffold to develop novel antimalarials.

Communicated by Ramaswamy H. Sarma     

Models of the pharmacophoric pattern and affinity trend of methyl 2-(aminomethyl)-1-phenylcyclopropane-1-carboxylate derivatives as σ1 ligands

Sigma-1 (σ₁) affinities of methyl 2-(aminomethyl)-1-phenylcyclopropane-1-carboxylate (MAPCC) derivatives were modelled by the genetic algorithm with linear assignment of hypermolecular alignment of datasets (GALAHAD) and the comparative molecular field analysis (CoMFA)/comparative molecular similarity indices analysis (CoMSIA) methods. GALAHAD was used for deriving the 3D pharmacophore pattern that encompasses the most potent σ₁ ligands within this series. Five MAPCC derivatives with a high σ₁ affinity were used for deriving this model. The obtained model included a nitrogen atom, the hydrophobes and the hydrogen bond acceptor features; it was able to identify other potent σ₁ ligands. On the other hand, CoMFA and CoMSIA methods were used for deriving quantitative structure–activity relationship (QSAR) models. All QSAR models were trained with 17 compounds, after which they were evaluated for predictive ability with additional five compounds. The best QSAR model was obtained by using CoMSIA, including steric, electrostatic and hydrophobic fields, and had a good predictive quality according to both internal and external validation criteria. In general, the models described herein provide meaningful information relevant for the rational design of new σ₁ ligands.     

Molecular docking and pharmacophore model studies of Rho kinase inhibitors

Molecular docking and pharmacophore model approaches were used to characterise the binding features of four different series of Rho kinase (ROCK) inhibitors. Docking simulation of 20 inhibitors with ROCK was performed. The binding conformations and binding affinities of these inhibitors were obtained using AutoDock 4.0 software. The predicted binding affinities correlate well with the activities of these inhibitors (R ² = 0.904). 3D pharmacophore models were generated for ROCK based on highly active inhibitors implemented in Catalyst 4.11 program. The best pharmacophore model consists of one hydrogen bond acceptor feature and two hydrophobic features, and they all seemed to be essential for inhibitors in terms of their binding activities. It is anticipated that the findings reported in this paper may provide very useful information for designing new ROCK inhibitors.