The decomposition of α-aminophosphine oxides to phosphonic acid derivatives (P<Superscript>III</Superscript>)

Aminophosphine oxides and aminophosphonates are, in general, very stable compounds. However, following phosphorus–carbon bond cleavage in aqueous acidic media these compounds sometimes decompose to phosphonic acids derivatives (P^III). Despite some controversy in the literature, careful analysis supported by theoretical studies leads to the conclusion that decomposition to P^III derivatives proceeds via an elimination reaction. Figure The decomposition of α-aminophosphine oxides to phosphonic acid derivatives (P^III)     

Design of Benzene-1,2-diamines as selective inducible nitric oxide synthase inhibitors: a combined de novo design and docking analysis

Selective inhibition of inducible nitric oxide synthases (iNOS) has been a challenging problem for researchers pursuing work in finding methods to treat inflammatory disorders, shock, etc. Though many inhibitors have been studied to date, all are associated with selectivity or potency problems. Additionally, most of the reported compounds have several similarities and fewer number of novel structures are being tried. There is an increasing need to design novel molecules for this target. In this work, de novo design using LUDI, combined with docking analysis using FlexX has been employed in an attempt to identify novel scaffolds. Benzene-1,2-diamines were identified which could mimic the interactions of the substrate analogs and other inhibitors. Comparative docking scores in each of the isoforms of nitric oxide synthase were employed to recognize hits for iNOS selectivity. Figure Figure shows the docked poses of the ligand M226 along with that of the reference GW274150. (FlexX analysis)     

Insights into catalytic activity of industrial enzyme Co-nitrile hydratase. Docking studies of nitriles and amides

Nitrile hydratase (NHase) is an enzyme containing non-corrin Co³⁺ in the non-standard active site. NHases from Pseudonocardia thermophila JCM 3095 catalyse hydration of nitriles to corresponding amides. The efficiency of the enzyme is 100 times higher for aliphatic nitriles then aromatic ones. In order to understand better this selectivity dockings of a series of aliphatic and aromatic nitriles and related amides into a model protein based on an X-ray structure were performed. Substantial differences in binding modes were observed, showing better conformational freedom of aliphatic compounds. Distinct interactions with postranslationally modified cysteines present in the active site of the enzyme were observed. Modeling shows that water molecule activated by a metal ion may easily directly attack the docked acrylonitrile to transform this molecule into acryloamide. Thus docking studies provide support for one of the reaction mechanisms discussed in the literature. Figure Crystalographic structure of Pseudonocardia thermophila JCM 3095 nitrile hydratase (a) and the non-standard active site (b)     

Neighboring group stabilization by σ-holes

We have used density-functional theory to investigate the neighboring-group stabilization of iodine, arsenic, and phosphorus-centered oxyanion moieties in species such as deprotonated 2-iodoxybenzoic acid (IBX) and its analogs. The magnitudes of different stabilizing effects and further candidates for analogous stabilization are analyzed.      

Exploration of the binding affinities between ecdysone agonists and EcR/USP by docking and MM-PB/GBSA approaches

Ecdysone receptor (EcR) is a significant target in the identification of new environmentally friendly pesticides. There are two types of ecdysone agonists: steroidal ecdysone agonists and dibenzoylhydrazines (DBHs). In this study, various modeling methods (homology modeling, molecular docking, MD simulation, binding free energy calculation, and per-residue binding free energy decomposition) were utilized to study the different binding mechanisms of two types of ecdysone agonists. Our theoretical results indicated that the relative binding potencies of DBHs can be ranked sufficiently accurately using the MOE docking method. However, MM/PBSA calculations more accurately predicted the binding affinities between steroidal ecdysone agonists and EcR-LBD. To identify the key residues involved in ecdysone agonist binding, the binding free energy (ΔG _Bind) was decomposed into the energy contributions of individual residues. The results revealed that nine residues—Ile339, Thr343, Met380, Met381, Tyr403, Tyr408, Asp419, Gln503, and Asn504—determined the binding affinities of the DBHs. Glu309, Met342, Arg383, Arg387, and Leu396 were important influences on the binding affinities of the steroidal ecdysone agonists.

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Graphical abstract The ecdysone receptor (EcR) is related to insect growth and has been shown to be a useful target for insecticides

     

The studies on substrate,product and inhibitor binding to a wild-type and neuronopathic form of human acid-β-glucosidase

Gaucher disease is a lysosomal storage disorder caused by deficiency of human acid β-glucosidase. Recent x-ray structural elucidation of the enzyme alone and in the presence of its inhibitor was done, which provided an excellent template for further studies on the binding of substrate, product and inhibitor. To draw correlations between the clinical manifestation of the disease driven by point mutations, L444P and L444R, and the placement and function of putative S-binding sites, the presented theoretical studies were undertaken, which comprised of molecular dynamics and molecular docking methods. The obtained results indicate the D443 and D445 residues as extremely important for physiological functionality of an enzyme. They also show, although indirectly, that binding of the substrate is influenced by an interplay of E235 and E334 residues, constituting putative substrate binding site, and the region flanked by D435 and D445 residues. Figure The binding of an arbitrarily chosen structure of glucosylceramide (A), conduritol-β-epoxide (B), glucose (C) to the active site D443/D445 (A1, B1, C1) and E320/E340 (A2, B2, C2) of the wild-type structure of human acid-β-glucosidase. A1, B1, C1 blue mask represents the residues D443-D445; red mask represents the residue D444; A2, B2, C2 blue mask represents loop1 (Ser³⁴⁵-Glu³⁴⁹) and loop2 (Val³⁹⁴-Asp³⁹⁹), whereas red mask the residues E235 and 340     

Reverse-docking study of the TADDOL-catalyzed asymmetric hetero-Diels–Alder reaction

The reverse-docking of a TADDOL catalyst to rigid transition-state (TS) representations of an asymmetric hetero-Diels–Alder reaction is described. The resulting docking poses represent a simplified geometric model of the TS for the catalyzed reaction. The conformational space of the catalyst in proximity to the catalyst-free TS models is sampled stochastically and the energetically favored poses are subjected to a clustering procedure to highlight structural attributes compatible with organocatalysis. Each pose is scored and ranked based on its molecular-mechanics docking energy. The reverse-docking procedure reveals a clear energetic trend in favor of the experimentally preferred product enantiomers. Analysis of the best poses suggests a geometric model that is consistent with principles of molecular recognition, catalysis, and experimental data.      

3D-QSAR and docking studies of 3-arylquinazolinethione derivatives as selective estrogen receptor modulators

3D-QSAR and molecular docking analysis were performed to explore the interaction of estrogen receptors (ERα and ERβ) with a series of 3-arylquinazolinethione derivatives. Using the conformations of these compounds revealed by molecular docking, CoMFA analysis resulted in the first quantitative structure-activity relationship (QSAR) and first quantitative structure-selectivity relationship (QSSR) models predicting the inhibitory activity against ERβ and the selectivity against ERá. The q² and R² values, along with further testing, indicate that the obtained 3D-QSAR and 3D-QSSR models will be valuable in predicting both the inhibitory activity and selectivity of 3-arylquinazolinethione derivatives for these protein targets. A set of 3D contour plots drawn based on the 3D-QSAR and 3D-QSSR models reveal modifications of substituents at C2 and C5 of the quinazoline which my be useful to improve both the activity and selectivity of ERβ/ ERα. Results showed that both the steric and electrostatic factors should appropriately be taken into account in future rational design and development of more active and more selective ERβ inhibitors for the therapeutic treatment of osteoporosis. Figure Structures of ERβ binding with compounds 1aar, 1ax and 1aag obtained from molecular docking     

The molecular basis of urokinase inhibition: from the nonempirical analysis of intermolecular interactions to the prediction of binding affinity

Urokinase-type plasminogen activator (uPA) is a trypsin-like serine protease that plays a crucial role in angiogenesis process. In addition to its physiological role in healthy organisms, angiogenesis is extremely important in cancer growth and metastasis, resulting in numerous attempts to understand its control and to develop new approaches to anticancer therapy. The α-aminoalkylphosphonate diphenyl esters are well known as highly efficient serine protease inhibitors. However, their mode of binding has not been verified experimentally in details. For a group of average and potent phosphonic inhibitors of urokinase, flexible docking calculations were performed to gain an insight into the active site interactions responsible for observed enzyme inhibition. The docking results are consistent with the previously suggested mode of inhibitors binding. Subsequently, rigorous ab initio study of binding energy was carried out, followed by its decomposition according to the variation–perturbation procedure to reveal stabilization energy constituents with clear physical meaning. Availability of the experimental inhibitory activities and comparison with theoretical binding energy allows for the validation of theoretical models of inhibition, as well as estimation of the possible potential for binding affinity prediction. Since the docking results accompanied by molecular mechanics optimization suggested that several crucial active site contacts were too short, the optimal distances corresponding to the minimum ab initio interaction energy were also evaluated. Despite the deficiencies of force field-optimized enzyme-inhibitor structures, satisfactory agreement with experimental inhibitory activity was obtained for the electrostatic interaction energy, suggesting its possible application in the binding affinity prediction. Figure The comparison of an arrangement of inhibitors within uPA active. Amino acid residues form S1 pocket that binds the variable part of inhibitor molecules     

Exploring the binding pocket for pyridopyrimidine ligands at the CCK1 receptor by molecular docking

Pyridopyrimidine-based analogues are among the most highly potent and selective antagonists of cholecystokinin receptor subtype-1 (CCK1R) described to date. To better understand the structural and chemical features responsible for the recognition mechanism, and to explore the binding pocket of these compounds, we performed automated molecular docking using GOLD2.2 software on some derivatives with structural diversity, and propose a putative binding conformation for each compound. The docking protocol was guided by the key role of the Asn333 residue, as revealed by site directed mutagenesis studies. The results suggest two putative binding modes located in the same pocket. Both are characterized by interaction with the main residues revealed by experiment, Asn333 and Arg336, and differ in the spatial position of the Boc-Trp moiety of these compounds. Hydrophobic contacts with residues Thr117, Phe107, Ile352 and Ile329 are also in agreement with experimental data. Despite the poor correlation obtained between the estimated binding energies and the experimental activity, the proposed models allow us to suggest a plausible explanation of the observed binding data in accordance with chemical characteristics of the compounds, and also to explain the observed diastereoselectivity of this family of antagonists towards CCK1R. The most reasonable selected binding conformations could be the starting point for future studies. Figure Superimposition of the two putative binding conformations revealed by molecular docking for pyridopyrimidine-based CCK1 antagonists     

Docking studies on kinesin spindle protein inhibitors: an important cooperative ‘minor binding pocket’ which increases the binding affinity significantly

Fifteen KSP inhibitors were docked into the receptor and the binding mode was analyzed for the first time. It was considered that in addition to the main binding pocket all the inhibitors merged in, there exists a cooperative minor binding pocket, which could be explored for significantly increased binding affinity. In addition, a good linear relationship between the biological activities and the lowest binding free energies has also been found. This may help in predicting the binding affinity of newly designed KSP inhibitors. Figure Two binding pockets considered after the analysis. Seven docked ligands (compound 1–7) were overlapped at the binding site. All inhibitors tested interacted with the main pocket, while CK0106023, interacted also with the cooperative minor pocket mainly surrounded by Arg221 and Ala218. Coloring of the binding site surface are different ends of each amino acid residue: blue represents amino group while red means carboxyl     

3D-QSAR studies of Dipeptidyl peptidase IV inhibitors using a docking based alignment

Dipeptidyl peptidase IV (DPP-IV) deactivates the incretin hormones GLP-1 and GIP by cleaving the penultimate proline or alanine from the N-terminal (P1-position) of the peptide. Inhibition of this enzyme will prevent the degradation of the incretin hormones and maintain glucose homeostasis; this makes it an attractive target for the development of drugs for diabetes. This paper reports 3D-QSAR analysis of several DPP-IV inhibitors, which were aligned by the receptor-based technique. The conformation of the molecules in the active site was obtained through docking methods. The QSAR models were generated on two training sets composed of 74 and 25 molecules which included phenylalanine, thiazolidine, and fluorinated pyrrolidine analogs. The 3D-QSAR models are robust with statistically significant r², q², and values. The CoMFA and CoMSIA models were used to design some new inhibitors with several fold higher binding affinity. Figure The CoMFA contours around molecule D1T155 (a) steric contours - favored (green); disfavored (yellow) (b) electrostatic contours - electropositive (blue); electronegative (red)     

The 3D structure of the defense-related rice protein Pir7b predicted by homology modeling and ligand binding studies

To better understand the ligand-binding mechanism of protein Pir7b, important part in detoxification of a pathogen-derived compound against Pyricularia oryzae, a 3D structure model of protein Pir7b was constructed based on the structure of the template SABP2. Three substrates were docking to this protein, two of them were proved to be active, and some critical residues are identified, which had not been confirmed by the experiments. His87 and Leu17 considered as ‘oxyanion hole’ contribute to initiating the Ser86 nucleophilic attack. Gln187 and Asp139 can form hydrogen bonds with the anilid group to maintain the active binding orientation with the substrates. The docking model can well interpret the specificity of protein Pir7b towards the anilid moiety of the substrates and provide valuable structure information about the ligand binding to protein Pir7b. Figure Ligand binding analysis based on the refined Pir7b model. Magenta dash line, hydrogen bond; Red dash line, distance label. (a) Docking of 2-naphthol AS-acetate to Pir7b model. A 3D figure of 2-naphthol AS-acetate-Pir7b complex is also attached (b) Docking of 2-naphthol AS-2-chlor-propionate to Pir7b model. (c) Docking of 2-naphthol-acetate to Pir7b model.     

Theoretical and experimental study of polycyclic aromatic compounds as β-tubulin inhibitors

In this work, through a docking analysis of compounds from the ZINC chemical library on human β-tubulin using high performance computer cluster, we report new polycyclic aromatic compounds that bind with high energy on the colchicine binding site of β-tubulin, suggesting three new key amino acids. However, molecular dynamic analysis showed low stability in the interaction between ligand and receptor. Results were confirmed experimentally in in vitro and in vivo models that suggest that molecular dynamics simulation is the best option to find new potential β-tubulin inhibitors.

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Graphical abstract Bennett’s acceptance ratio (BAR) method

     

Cancer-relevant biochemical targets of cytotoxic Lonchocarpus flavonoids: A molecular docking analysis

A molecular docking investigation has been carried out on cytotoxic prenylated flavonoids from Lonchocarpus haberi with cancer-relevant chemotherapeutic targets known to be inhibited by flavonoids. Two molecular docking programs, Molegro and ArgusDock, were used to compare the binding energies of Lonchocarpus flavonoids with other flavonoids, inhibitors, or known ligands, to aromatase (CYP 19), fatty acid synthase (FAS), xanthine oxidase (XO), cyclooxygenases (COX-1 and COX-2), lipoxygenase (LOX-3), ornithine decarboxylase (ODC), protein tyrosine kinase (PTK), phosphoinositide 3-kinase (PI3K), protein kinase C (PKC), topoisomerase II (ATP binding site), ATP binding cassette (ABC) transporter, and phospholipase A₂ (PLA). The Lonchocarpus flavonoids examined in this study exhibited docking energies comparable to or stronger than other flavonoids that had been previously shown to be effective inhibitors of these enzymes. Furthermore, prenylated flavonoids, such as the Lonchocarpus flavonoids and xanthohumol, generally showed greater binding energies than the non-prenylated flavonoids. We conclude, therefore, that the Lonchocarpus flavonoids possibly owe their cytotoxic activity by inhibition of one or more of these enzymes.      

CHIH-DFT determination of the molecular structure and IR and UV spectra of solanidine

Solanidine is the steroidal aglycon of some potato glycoalkaloids and a very important precursor for the synthesis of hormones and some pharmacologically active compounds. In this work, we make use of a new chemistry model within Density Functional Theory, called CHIH-DFT, to calculate the molecular structure of solanidine, as well to predict its infrared and ultraviolet spectra. The calculated values are compared with the experimental data available for this molecule as a means of validation of our proposed chemistry model. Figure Molecular structure of solanidine calculated with the CHIH(small) model chemistry     

An ab initio quantum mechanical drug designing procedure: application to the design of balanced dual ACE/NEP inhibitors

This article describes in a sequential fashion how ab initio quantum mechanical methods can be applied to study the pharmacophoric features of drugs. It also describes how accurate drug–receptor interaction calculations can guide the careful design of balanced dual inhibitors, which form an important class of second generation drugs. As an example, the authors have chosen balanced inhibitors of angiotensin converting enzyme/neutral endopeptidase (ACE/NEP) as modern antihypertensive drugs. A unified, accurate, in silico design approach is presented, encompassing all steps from pharmacophore derivation to complete understanding of mechanistic aspects leading to drug design.      

Docking studies suggest ligand-specific δ-opioid receptor conformations

An automated docking procedure was used to study binding of a series of δ-selective ligands to three models of the δ-opioid receptor. These models are thought to represent the three ligand-specific receptor conformations. Docking results are in agreement with point mutation studies and suggest that different ligands—agonists and antagonists—may bind to the same binding site under different receptor conformations. Docking to different receptor models (conformations) also suggests that by changing to a receptor-specific conformation, the receptor may open or close different binding sites to other ligands. Figure  Ligands 5 (green) and 6 (orange) in bindingpocket BP1 of the R1 δ-opioid receptor model