Synthesis and structure–activity relationship of 2-phenyliminochromene derivatives as inhibitors for aldo–keto reductase (AKR) 1B10

Inhibitors of a human member (AKR1B10) of the aldo–keto reductase superfamily are regarded as promising therapeutics for the treatment of cancer. Recently, we have discovered (Z)-2-(4-methoxyphenylimino)-7-hydroxy-N-(pyridin-2-yl)-2H-chromene-3-carboxamide (1) as the potent competitive inhibitor using the virtual screening approach, and proposed its 4-methoxy group on the 2-phenylimino moiety as an essential structural prerequisite for the inhibition. In this study, 18 derivatives of 1 were synthesized and their inhibitory potency against AKR1B10 evaluated. Among them, 7-hydroxy-2-(4-methoxyphenylimino)-2H-chromene-3-carboxylic acid benzylamide (5n) was the most potent inhibitor showing a K_i value of 1.3 nM. The structure–activity relationship of the derivatives indicated that the 7-hydroxyl group on the chromene ring, but not the 4-methoxy group, was absolutely required for inhibitory activity, The molecular docking of 5n in AKR1B10 and site-directed mutagenesis of the enzyme residues suggested that the hydrogen-bond interactions between the 7-hydroxyl group of 5n and the catalytic residues (Tyr49 and His111) of the enzyme, together with a π-stacking interaction of the benzylamide moiety of 5n with Trp220, are important for the potent inhibition.     

Sliding Box Docking: a new stand-alone tool for managing docking-based virtual screening along the DNA helix axis

Sliding Box Docking is a program that manages simulations of ligand docking at different defined positions of a three-dimensional DNA structure. The procedure is similar to inverse docking, which is a method that performs docking simulations of a single ligand in the active sites of different targets. Sliding Box Docking manages docking simulations of one ligand into a box that slides along the DNA helix axis in regular steps. For each box position a score is calculated using the separate Autodock Vina software, and the results are automatically plotted. The evaluation of ligand interaction at different DNA locations can highlight the specificity of ligands for different DNA- sequences. When assessing the affinity between ligans AT base pairs, results for docking simulations with a test set that included berenil, distamycin, hoechst 33258, and netropsin were as expected, agreeing well with affinities previously described in the literature.

Availability

Binaries are freely available at https://sourceforge.net/projects/slidingboxdocki     

Structure‐guided screening of chemical database to identify NS3‐NS2B inhibitors for effective therapeutic application in dengue infection

Dengue infection is the most common arthropod‐borne disease caused by dengue viruses, predominantly affecting millions of human beings annually. To find out promising chemical entities for therapeutic application in Dengue, in the current research, a multi‐step virtual screening effort was conceived to screen out the entire “screening library” of the Asinex database. Initially, through “Lipinski rule of five” filtration criterion almost 0.6 million compounds were collected and docked with NS3‐NS2B protein. Thereby, the chemical space was reduced to about 3500 compounds through the analysis of binding affinity obtained from molecular docking study in AutoDock Vina. Further, the “Virtual Screening Workflow” (VSW) utility of Schrödinger suite was used, which follows a stepwise multiple docking programs such as ‐ high‐throughput virtual screening (HTVS), standard precision (SP), and extra precision (XP) docking, and in postprocessing analysis the MM‐GBSA based free binding energy calculation. Finally, five potent molecules were proposed as potential inhibitors for the dengue NS3‐NS2B protein based on the investigation of molecular interactions map and protein‐ligand fingerprint analyses. Different pharmacokinetics and drug‐likeness parameters were also checked, which favour the potentiality of selected molecules for being drug‐like candidates. The molecular dynamics (MD) simulation analyses of protein‐ligand complexes were explained that NS3‐NS2B bound with proposed molecules quite stable in dynamic states as observed from the root means square deviation (RMSD) and root means square fluctuation (RMSF) parameters. The binding free energy was calculated using MM‐GBSA method from the MD simulation trajectories revealed that all proposed molecules possess such a strong binding affinity towards the dengue NS3‐NS2B protein. Therefore, proposed molecules may be potential chemical components for effective inhibition of dengue NS3‐NS2B protein subjected to experimental validation.     

Identification of potential tumour-associated carbonic anhydrase isozyme IX inhibitors: atom-based 3D-QSAR modelling,pharmacophore-based virtual screening and molecular docking studies

Abstract

Tumour hypoxia results in dramatic changes in the gene expression, proliferation and survival of tumour cells. The tumour cells shift towards anaerobic glycolysis which results in change of pH in their microenvironment. In response to this stress, over expression of carbonic anhydrase IX (CA IX) genes is observed in many solid tumours. So, selective inhibition of CA IX can be a promising target for anti-cancer drugs. In this work in silico tools like atom-based 3D-QSAR modelling, pharmacophore-based virtual screening and molecular docking were used to identify potential CA IX inhibitors. Based on the training set used in the QSAR model, twenty pharmacophore models were generated. Out of these, HHHR_1, AHHR_1, DHHHR_1, AHHHR_1 model was used to screen a database of 1,50,000 compounds retrieved from ZINC 15 database. R² and Q² was 0.9864 and 0.8799, respectively, for the developed QSAR model. 163 compounds showed a phase screen score above 2.4 in which ZINC02260669 was the highest ranked (screen score, 2.852058) compound in all the four models. Built QSAR model was used to predict the activity of all these 163 compounds and ZINC72370966 showed the highest predicted activity with pKi value of 7.649. These compounds were docked against CA IX (human) protein (PDB ID 5FL6) and molecular docking results showed favourable binding interactions for the best ten identified hits. This work gives design insights and some potential scaffolds which can be developed as CA IX inhibitors.

Communicated by Ramaswamy H. Sarma     

Repurposing of FDA-approved drugs to target MurB and MurE enzymes in Mycobacterium tuberculosis

Abstract

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) is one amongst the top 10 causes of death worldwide. The growing rise in antibiotic resistance compounded with slow and expensive drug discovery has further aggravated the situation. ‘Drug repurposing’ is a promising approach where known drugs are examined for a new indication. In the present study, we have attempted to identify drugs that could target MurB and MurE enzymes involved in the muramic acid synthesis pathway (Mur Pathway) in Mtb. FDA-approved drugs from two repositories i.e. Drug Bank (1932 drugs) and e-LEA3D (1852 drugs) were screened against these proteins. Several criteria were applied to study the protein-drug interactions and the consensus drugs were further studied by molecular dynamics (MD) simulation. Our study found Sulfadoxine (–7.3?kcal/mol) and Pyrimethamine (–7.8?kcal/mol) to show stable interaction with MurB while Lifitegrast (–10.5?kcal/mol) and Sildenafil (–9.1?kcal/mol) showed most reliable interaction with MurE. Furthermore, binding free energy (ΔG_bind), RMSD and RMSF data and the number of hydrogen bonds corroborated the stability of interactions and hence these drugs for repurposing should be explored further.

Communicated by Ramaswamy H. Sarma     

S100A4: a novel partner for heat shock protein 47 in antler stem cells and insight into the calcium ion-induced conformational changes

Abstract

S100A4 is a multiple-function protein highly expressed in tumor or stem cells. We found S100A4 was a novel protein partner for heat shock protein 47 (HSP47) in deer antlerogenic periosteum cells (AP cells), indicating that S100A4 could bind with HSP47. S100A4 had both calcium-dependent and calcium-independent patterns (labeled as SCd and SCi, respectively) to execute different biological activities. Homology models of HSP47, SCd and SCi were constructed. HSP47:collagen model, HSP47:collagen I-V, HSP47:SCd and HSP47:SCi complexes were built using ZDOCK software. Together with free SCd and SCi, 200?ns molecular dynamic (MD) simulations were performed to analyze binding free energies and SCi/SCd conformational changes. The energetic results showed that SCi had the strongest affinity to HSP47, and followed by collagens. SCd had little interaction with HSP47. Decomposition energy results showed that collagen model interacted with HSP47 mainly though neutral amino acids. When SCi bound with HSP47, the majority of mediated amino acids were charged. These results indicated that SCi could compete with collagen on the binding site of HSP47. Root mean square fluctuation (RMSF) values and cross-correlation matrices of principal component analysis (PCA) were calculated to evaluate the SCi/SCd structural variation during MD simulation. Both HSP47 and Ca²⁺ could stabilize the conformation of SCi/SCd. The loops interacting with Ca²⁺s and linking the two EF-hand motifs were impacted particularly. The relative moving directions of α-helices in EF-hands were distinct by the binding effect of HSP47 and Ca²⁺. We found that SCi may regulate the differentiation of AP cells by disturbing the interaction between HSP47 and collagen.

Communicated by Ramaswamy H. Sarma     

Challenges and opportunities of automated protein-protein docking: HDOCK server vs human predictions in CAPRI Rounds 38-46

Protein-protein docking plays an important role in the computational prediction of the complex structure between two proteins. For years, a variety of docking algorithms have been developed, as witnessed by the critical assessment of prediction interactions (CAPRI) experiments. However, despite their successes, many docking algorithms often require a series of manual operations like modeling structures from sequences, incorporating biological information, and selecting final models. The difficulties in these manual steps have significantly limited the applications of protein-protein docking, as most of the users in the community are nonexperts in docking. Therefore, automated docking like a web server, which can give a comparable performance to human docking protocol, is pressingly needed. As such, we have participated in the blind CAPRI experiments for Rounds 38-45 and CASP13-CAPRI challenge for Round 46 with both our HDOCK automated docking web server and human docking protocol. It was shown that our HDOCK server achieved an “acceptable” or higher CAPRI-rated model in the top 10 submitted predictions for 65.5% and 59.1% of the targets in the docking experiments of CAPRI and CASP13-CAPRI, respectively, which are comparable to 66.7% and 54.5% for human docking protocol. Similar trends can also be observed in the scoring experiments. These results validated our HDOCK server as an efficient automated docking protocol for nonexpert users. Challenges and opportunities of automated docking are also discussed.     

Docking proteins and peptides under evolutionary constraints in Critical Assessment of PRediction of Interactions rounds 38 to 45

Computational structural prediction of macromolecular interactions is a fundamental tool toward the global understanding of cellular processes. The Critical Assessment of PRediction of Interactions (CAPRI) community-wide experiment provides excellent opportunities for blind testing computational docking methods and includes original targets, thus widening the range of docking applications. Our participation in CAPRI rounds 38 to 45 enabled us to expand the way we include evolutionary information in structural predictions beyond our standard free docking InterEvDock pipeline. InterEvDock integrates a coarse-grained potential that accounts for interface coevolution based on joint multiple sequence alignments of two protein partners (co-alignments). However, even though such co-alignments could be built for none of the CAPRI targets in rounds 38 to 45, including host-pathogen and protein-oligosaccharide complexes and a redesigned interface, we identified multiple strategies that can be used to incorporate evolutionary constraints, which helped us to identify the most likely macromolecular binding modes. These strategies include template-based modeling where only local adjustments should be applied when query-template sequence identity is above 30% and larger perturbations are needed below this threshold; covariation-based structure prediction for individual protein partners; and the identification of evolutionarily conserved and structurally recurrent anchoring interface motifs. Overall, we submitted correct predictions among the top 5 models for 12 out of 19 interface challenges, including four High- and five Medium-quality predictions. Our top 20 models included correct predictions for three out of the five targets we missed in the top 5, including two targets for which misleading biological data led us to downgrade correct free docking models.     

In silico identification of mimicking molecule(s) triggering von Willebrand factor in human: a molecular drug target for regulating coagulation pathway

Abstract

Blood coagulation is a complex and dynamic process wherein the body activates its emergency mechanism to stop bleeding and wound healing via the interactions of prothrombotic and antithrombotic agents. von Willebrand factor (VWF) is a complex glycoprotein and initial component of the hemostasis pathway which serves a multipurpose role in blood coagulation process. There are reports of various plants that contain several bioactive compounds possessing properties of inducing blood coagulation directly or indirectly. In the present study, efforts have been made to identify bioactive compounds that may play a significant role in regulation of the coagulation cascade by accelerating VWF and thus enhance the hemostasis process. An antidiuretic peptide drug, Desmopressin, works on VWF and releases them in circulation. Forty-seven compounds from different plant sources were screened through molecular docking, out of which two compounds, Emodin and Peruvianoside II, showed more binding affinity than the reference drug Desmopressin. Emodin and Peruvianoside II showed binding energies ?7.2 and ?7.0?kcal/mol, respectively, when docked with VWF, whereas Desmopressin displayed less binding energy (?6.9?kcal/mol). Emodin belongs to anthraquinone from Rumex hastasus and Peruvianoside II belongs to flavanone glycosides from Thevetia peruviana. The mimicking potential of top identified molecules with respect to the drug was confirmed through simulation analysis. Besides, the molecular dynamics simulation (MDS) study (for 20?ns) showed that the Peruvianoside II protein complex was energetically more stable than Emodin protein complex. Based on the results, Peruvianoside II possesses great potential and thus may be considered for development of drugs for hemostasis.