Combination Of Docking Research Articles

P19-targeted ABD-derived protein variants inhibit IL-23 binding and exert suppressive control over IL-23-stimulated expansion of primary human IL-17+ T-cells

Interleukin-23 (IL-23), a heterodimeric cytokine of covalently bound p19 and p40 proteins, has recently been closely associated with development of several chronic autoimmune diseases such as psoriasis, psoriatic arthritis or inflammatory bowel disease. Released by activated dendritic cells, IL-23 interacts with IL-23 receptor (IL-23R) on Th17 cells, thus promoting intracellular signaling, a pivotal step in Th17-driven pro-inflammatory axis. Here, we aimed to block the binding of IL-23 cytokine to its cell-surface receptor by novel inhibitory protein binders targeted to the p19 subunit of human IL-23. To this goal, we used a combinatorial library derived from a scaffold of albumin-binding domain (ABD) of streptococcal protein G, and ribosome display selection, to yield a collection of ABD-derived p19-targeted variants, called ILP binders. From 214 clones analyzed by ELISA, Western blot and DNA sequencing, 53 provided 35 different sequence variants that were further characterized. Using in silico docking in combination with cell-surface competition binding assay, we identified a group of inhibitory candidates that substantially diminished binding of recombinant p19 to the IL-23R on human monocytic THP-1 cells. Of these best p19-blockers, ILP030, ILP317 and ILP323 inhibited IL-23-driven expansion of IL-17-producing primary human CD4+ T-cells. Thus, these novel binders represent unique IL-23-targeted probes useful for IL-23/IL-23R epitope mapping studies and could be used for designing novel p19/IL-23-targeted anti-inflammatory biologics.

Theoretical Studies on Azaindoles as Human Aurora B Kinase Inhibitors: Docking, Pharmacophore and ADMET Studies.

Aurora kinases are the cell cycle mitotic regulators processing multiple functions during cell division. Altered mechanism of these mitotic kinases may contribute to genomic instability that is most often correlated with tumorigenesis, which has been reported in many human cancers. Selective blockage of the aberrantly expressed Aurora kinases has the potential therapeutic assessment to control the deregulated cell cycle machinery and their associated risks of cancer. Using a combination of docking-, ligand- and structure-based pharmacophore strategies, in the present study, we have tried to predict the anticancer potentiality of our synthesized compounds (A1 to A5 and B1 to B9) against human Aurora B kinase. The results revealed that among all the compounds, compound B7 may act as a best candidate to be an agent of the high binding affinity with a score of 113.464kcal/mol and good pharmacophoric features with acceptable fit values of both ligand- and structure-based pharmacophore models. Consequently, ADMET properties are also calculated to predict the safer efficacy of the compounds.

Combined docking and molecular dynamics study of lipase catalyzed kinetic resolution of 1-phenylethanol in organic solvents

A combined docking and molecular dynamics protocol was applied to investigate kinetic resolution of 1-phenylethanol using Burkholderia cepacia lipase (BCL) in different organic solvents. BCL has open structure compared to other lipases and is found to be more effective in kinetic resolution of primary and secondary alcohols compared to other lipases. The fundamental understanding of the difference in specificity of lipases in esterification/transesterification reactions in presence of solvents can help in reduction of experimental cost. In this work, solvents such as hexane, tert-butyl methyl ether, toluene and decalin were studied. The conformational changes in BCL structure were captured using molecular dynamics (MD) studies. The protein conformations from MD were used for docking studies to estimate ΔΔG between R and S form of tetrahedral intermediate. The predicted E value was compared with experimental data for hexane and good agreement was obtained. It was observed that hexane and toluene are better solvents for chiral resolution of 1-phenylethanol compared to tert-butyl methyl ether and decalin when lipase in free form is used. The MD simulations of R form of tetrahedral intermediate in solvents were carried out to study the critical bonds distances.

Absolute binding free energy calculations of CBClip host-guest systems in the SAMPL5 blind challenge.

Herein, we report the absolute binding free energy calculations of CBClip complexes in the SAMPL5 blind challenge. Initial conformations of CBClip complexes were obtained using docking and molecular dynamics simulations. Free energy calculations were performed using thermodynamic integration (TI) with soft-core potentials and Bennett's acceptance ratio (BAR) method based on a serial insertion scheme. We compared the results obtained with TI simulations with soft-core potentials and Hamiltonian replica exchange simulations with the serial insertion method combined with the BAR method. The results show that the difference between the two methods can be mainly attributed to the van der Waals free energies, suggesting that either the simulations used for TI or the simulations used for BAR, or both are not fully converged and the two sets of simulations may have sampled difference phase space regions. The penalty scores of force field parameters of the 10 guest molecules provided by CHARMM Generalized Force Field can be an indicator of the accuracy of binding free energy calculations. Among our submissions, the combination of docking and TI performed best, which yielded the root mean square deviation of 2.94kcal/mol and an average unsigned error of 3.41kcal/mol for the ten guest molecules. These values were best overall among all participants. However, our submissions had little correlation with experiments.

Experimental, computational and chemometrics studies of BSA-vitamin B6 interaction by UV–Vis, FT-IR, fluorescence spectroscopy, molecular dynamics simulation and hard-soft modeling methods

The interaction of pyridoxine (Vitamin B6) with bovine serum albumin (BSA) is investigated under pseudo-physiological conditions by UV–Vis, fluorescence and FTIR spectroscopy. The intrinsic fluorescence of BSA was quenched by VB6, which was rationalized in terms of the static quenching mechanism. According to fluorescence quenching calculations, the bimolecular quenching constant (kq), dynamic quenching (KSV) and static quenching (KLB) at 310K were obtained. The efficiency of energy transfer and the distance between the donor (BSA) and the acceptor (VB6) were calculated by Foster’s non-radiative energy transfer theory and were equal to 41.1% and 2.11nm.The collected UV–Vis and fluorescence spectra were combined into a row-and column-wise augmented matrix and resolved by multivariate curve resolution-alternating least squares (MCR-ALS). MCR-ALS helped to estimate the stoichiometry of interactions, concentration profiles and pure spectra for three species (BSA, VB6 and VB6-BSA complex) existed in the interaction procedure. Based on the MCR-ALS results, using mass balance equations, a model was developed and binding constant of complex was calculated using non-linear least squares curve fitting. FT-IR spectra showed that the conformation of proteins was altered in presence of VB6. Finally, the combined docking and molecular dynamics (MD) simulations were used to estimate the binding affinity of VB6 to BSA. Five-nanosecond MD simulations were performed on bovine serum albumin (BSA) to study the conformational features of its ligand binding site. From MD results, eleven BSA snapshots were extracted, at every 0.5ns, to explore the binding affinity (GOLD score) of VB6 using a docking procedure. MD simulations indicated that there is a considerable flexibility in the structure of protein that affected ligand recognition. Structural analyses and docking simulations indicated that VB6 binds to site I and GOLD score values depend on the conformations of both BSA and ligand. Molecular modeling results showed that VB6–BSA complex formed not only on the basis of electrostatic forces, but also on the basis of π–π staking and hydrogen bond. There was an excellent agreement between the experimental and computational results. The results presented in this paper, will offer a reference for detailed and systematic studies on the biological effects and action mechanism of small molecules with proteins.

Rapid activity prediction of HIV-1 integrase inhibitors: harnessing docking energetic components for empirical scoring by chemometric and artificial neural network approaches.

Improving performance of scoring functions for drug docking simulations is a challenging task in the modern discovery pipeline. Among various ways to enhance the efficiency of scoring function, tuning of energetic component approach is an attractive option that provides better predictions. Herein we present the first development of rapid and simple tuning models for predicting and scoring inhibitory activity of investigated ligands docked into catalytic core domain structures of HIV-1 integrase (IN) enzyme. We developed the models using all energetic terms obtained from flexible ligand-rigid receptor dockings by AutoDock4, followed by a data analysis using either partial least squares (PLS) or self-organizing maps (SOMs). The models were established using 66 and 64 ligands of mercaptobenzenesulfonamides for the PLS-based and the SOMs-based inhibitory activity predictions, respectively. The models were then evaluated for their predictability quality using closely related test compounds, as well as five different unrelated inhibitor test sets. Weighting constants for each energy term were also optimized, thus customizing the scoring function for this specific target protein. Root-mean-square error (RMSE) values between the predicted and the experimental inhibitory activities were determined to be <1 (i.e. within a magnitude of a single log scale of actual IC50 values). Hence, we propose that, as a pre-functional assay screening step, AutoDock4 docking in combination with these subsequent rapid weighted energy tuning methods via PLS and SOMs analyses is a viable approach to predict the potential inhibitory activity and to discriminate among small drug-like molecules to target a specific protein of interest.

The Structure of the Complex between Yeast Frataxin and Ferrochelatase: CHARACTERIZATION AND PRE-STEADY STATE REACTION OF FERROUS IRON DELIVERY AND HEME SYNTHESIS

Frataxin is a mitochondrial iron-binding protein involved in iron storage, detoxification, and delivery for iron sulfur-cluster assembly and heme biosynthesis. The ability of frataxin from different organisms to populate multiple oligomeric states in the presence of metal ions, e.g. Fe(2+) and Co(2+), led to the suggestion that different oligomers contribute to the functions of frataxin. Here we report on the complex between yeast frataxin and ferrochelatase, the terminal enzyme of heme biosynthesis. Protein-protein docking and cross-linking in combination with mass spectroscopic analysis and single-particle reconstruction from negatively stained electron microscopic images were used to verify the Yfh1-ferrochelatase interactions. The model of the complex indicates that at the 2:1 Fe(2+)-to-protein ratio, when Yfh1 populates a trimeric state, there are two interaction interfaces between frataxin and the ferrochelatase dimer. Each interaction site involves one ferrochelatase monomer and one frataxin trimer, with conserved polar and charged amino acids of the two proteins positioned at hydrogen-bonding distances from each other. One of the subunits of the Yfh1 trimer interacts extensively with one subunit of the ferrochelatase dimer, contributing to the stability of the complex, whereas another trimer subunit is positioned for Fe(2+) delivery. Single-turnover stopped-flow kinetics experiments demonstrate that increased rates of heme production result from monomers, dimers, and trimers, indicating that these forms are most efficient in delivering Fe(2+) to ferrochelatase and sustaining porphyrin metalation. Furthermore, they support the proposal that frataxin-mediated delivery of this potentially toxic substrate overcomes formation of reactive oxygen species.

QSPR approaches to elucidate the stability constants between β-cyclodextrin and some organic compounds: Docking based 3D conformer

In the present investigation, a combination of docking and quantitative structure-property relationship (QSPR) approaches was applied to elucidate the host-guest interactions in β-cyclodextrin complexation with diverse set of organic compounds. Molecular docking was performed to find correct conformations of organic molecules in the cavity of β-cyclodextrin. The conformation with the lowest binding free energy was chosen to calculate molecular descriptors. Some additional descriptors relevant to characterizing the structural properties of inclusion complexes were also calculated and used in QSPR model building. Genetic function approximation technique was applied to choose the best subset of descriptors. The selected descriptors explain that the hydrophobicity, surface area and shape of guest molecules play important roles in the β-cyclodextrin complexation. The final QSPR model, based on multiple linear regression (MLR) method, was characterized by satisfactory statistical performance; calibration (R2c) and prediction (R2p) correlation coefficient of 0.83±0.02 and 0.78±0.07 respectively.

Predicting the impact of mutations on the specific activity of Bacillus thermocatenulatus lipase using a combined approach of docking and molecular dynamics.

Lipases are important biocatalysts owing to their ability to catalyze diverse reactions with exceptional substrate specificities. A combined docking and molecular dynamics (MD) approach was applied to study the chain-length selectivity of Bacillus thermocatenulatus lipase (BTL2) towards its natural substrates (triacylglycerols). A scoring function including electrostatic, van der Waals (vdW) and desolvation energies along with conformational entropy was developed to predict the impact of mutation. The native BTL2 and its 6 mutants (F17A, V175A, V175F, D176F, T178V and I320F) were experimentally analyzed to determine their specific activities towards tributyrin (C4) or tricaprylin (C8), which were used to test our approach. Our scoring methodology predicted the chain-length selectivity of BTL2 with 85.7% (6/7) accuracy with a positive correlation between the calculated scores and the experimental activity values (r = 0.82, p = 0.0004). Additionally, the impact of mutation on activity was predicted with 75% (9/12) accuracy. The described study represents a fast and reliable approach to accurately predict the effect of mutations on the activity and selectivity of lipases and also of other enzymes. Copyright © 2016 John Wiley & Sons, Ltd.

Insight into determinants of substrate binding and transport in a multidrug efflux protein.

Multidrug resistance arising from the activity of integral membrane transporter proteins presents a global public health threat. In bacteria such as Escherichia coli, transporter proteins belonging to the major facilitator superfamily make a considerable contribution to multidrug resistance by catalysing efflux of myriad structurally and chemically different antimicrobial compounds. Despite their clinical relevance, questions pertaining to mechanistic details of how these promiscuous proteins function remain outstanding, and the role(s) played by individual amino acid residues in recognition, binding and subsequent transport of different antimicrobial substrates by multidrug efflux members of the major facilitator superfamily requires illumination. Using in silico homology modelling, molecular docking and mutagenesis studies in combination with substrate binding and transport assays, we identified several amino acid residues that play important roles in antimicrobial substrate recognition, binding and transport by Escherichia coli MdtM, a representative multidrug efflux protein of the major facilitator superfamily. Furthermore, our studies suggested that ‘aromatic clamps’ formed by tyrosine and phenylalanine residues located within the substrate binding pocket of MdtM may be important for antimicrobial substrate recognition and transport by the protein. Such ‘clamps’ may be a structurally and functionally important feature of all major facilitator multidrug efflux proteins.

Active site binding modes of inhibitors of Staphylococcus aureus mevalonate diphosphate decarboxylase from docking and molecular dynamics simulations

Bacterial mevalonate diphosphate decarboxylase (MDD) is an attractive therapeutic target for antibacterial drug development. In this work, we discuss a combined docking and molecular dynamics strategy toward inhibitor binding to bacterial MDD. The docking parameters utilized in this study were first validated with observations for the inhibitors 6-fluoromevalonate diphosphate (FMVAPP) and diphosphoglycolylproline (DPGP) using existing structures for the Staphylococcus epidermidis enzyme. The validated docking protocol was then used to predict structures of the inhibitors bound to Staphylococcus aureus MDD using the unliganded crystal structure of Staphylococcus aureus MDD. We also investigated a possible interactions improvement by combining this docking method with molecular dynamics simulations. Thus, the predicted docking structures were analyzed in a molecular dynamics trajectory to generate dynamic models and reinforce the predicted binding modes. FMVAPP is predicted to make more extensive contacts with S. aureus MDD, forming stable hydrogen bonds with Arg144, Arg193, Lys21, Ser107, and Tyr18, as well as making stable hydrophobic interactions with Tyr18, Trp19, and Met196. The differences in predicted binding are supported by experimentally determined Ki values of 0.23 ± 0.02 and 34 ± 8 μM, for FMVAPP and DPGP, respectively. The structural information coupled with the kinetic characterization obtained from this study should be useful in defining the requirements for inhibition as well as in guiding the selection of active compounds for inhibitor optimization.

Ligand and Structure Based Models for the Identification of Beta 2 Adrenergic Receptor Antagonists.

Ligand bound beta 2 adrenergic receptor (β2AR) crystal structures are in use for screening of compound libraries for identifying inducers and blockers. However, in case of G protein coupled receptors (GPCR), docking and binding energy (BE) calculations are not enough to discriminate agonist and antagonists. Absence of a reliable model for discriminating β2AR antagonist is still a major hurdle. Docking of known antagonists and agonists into activated and ground state β2AR revealed several key intermolecular interactions and H-bonding patterns, which in combination, emerged as a model for prediction of antagonists. Present study identifies an alternative binding orientation, within the binding pocket, for blockers and a minimum grid size to lessen the false positive predictions. Cluster analysis revealed structural variability among the antagonists and a conserved pattern in case of agonists. A combination of docking and structure activity relationship (SAR) model reliably discriminated antagonists. Based on key intermolecular interactions, a set of agonists and antagonists useful to SAR, quantitative structure activity relationship (QSAR) and pharmacophore modeling, has also been proposed for identifying antagonists.

Insights into molecular interactions between CaM and its inhibitors from molecular dynamics simulations and experimental data

In order to contribute to the structural basis for rational design of calmodulin (CaM) inhibitors, we analyzed the interaction of CaM with 14 classic antagonists and two compounds that do not affect CaM, using docking and molecular dynamics (MD) simulations, and the data were compared to available experimental data. The Ca2+-CaM-Ligands complexes were simulated 20 ns, with CaM starting in the “open” and “closed” conformations. The analysis of the MD simulations provided insight into the conformational changes undergone by CaM during its interaction with these ligands. These simulations were used to predict the binding free energies (ΔG) from contributions ΔH and ΔS, giving useful information about CaM ligand binding thermodynamics. The ΔG predicted for the CaM’s inhibitors correlated well with available experimental data as the r2 obtained was 0.76 and 0.82 for the group of xanthones. Additionally, valuable information is presented here: I) CaM has two preferred ligand binding sites in the open conformation known as site 1 and 4, II) CaM can bind ligands of diverse structural nature, III) the flexibility of CaM is reduced by the union of its ligands, leading to a reduction in the Ca2+-CaM entropy, IV) enthalpy dominates the molecular recognition process in the system Ca2+-CaM-Ligand, and V) the ligands making more extensive contact with the protein have higher affinity for Ca2+-CaM. Despite their limitations, docking and MD simulations in combination with experimental data continue to be excellent tools for research in pharmacology, toward a rational design of new drugs.

Structure, dynamics, and interaction of Mycobacterium tuberculosis (Mtb) DprE1 and DprE2 examined by molecular modeling, simulation, and electrostatic studies.

The enzymes decaprenylphosphoryl-β-D-ribose oxidase (DprE1) and decaprenylphosphoryl-β-D-ribose-2-epimerase (DprE2) catalyze epimerization of decaprenylphosporyl ribose (DPR) todecaprenylphosporyl arabinose (DPA) and are critical for the survival of Mtb. Crystal structures of DprE1 so far reported display significant disordered regions and no structural information is known for DprE2. We used homology modeling, protein threading, molecular docking and dynamics studies to investigate the structural and dynamic features of Mtb DprE1 and DprE2 and DprE1-DprE2 complex. A three-dimensional model for DprE2 was generated using the threading approach coupled with ab initio modeling. A 50 ns simulation of DprE1 and DprE2 revealed the overall stability of the structures. Principal Component Analysis (PCA) demonstrated the convergence of sampling in both DprE1 and DprE2. In DprE1, residues in the 269–330 area showed considerable fluctuation in agreement with the regions of disorder observed in the reported crystal structures. In DprE2, large fluctuations were detected in residues 95–113, 146–157, and 197–226. The study combined docking and MD simulation studies to map and characterize the key residues involved in DprE1-DprE2 interaction. A 60 ns MD simulation for DprE1-DprE2 complex was also performed. Analysis of data revealed that the docked complex is stabilized by H-bonding, hydrophobic and ionic interactions. The key residues of DprE1 involved in DprE1-DprE2 interactions belong to the disordered region. We also examined the docked complex of DprE1-BTZ043 to investigate the binding pocket of DprE1 and its interactions with the inhibitor BTZ043. In summary, we hypothesize that DprE1-DprE2 interaction is crucial for the synthesis of DPA and DprE1-DprE2 complex may be a new therapeutic target amenable to pharmacological validation. The findings have important implications in tuberculosis (TB) drug discovery and will facilitate drug development efforts against TB.

Predicting peptide vaccine candidates against H1N1 influenza virus through theoretical approaches.

Identification of potential epitopes that might activate the immune system has been facilitated by the employment of algorithms that use experimental data as templates. However, in order to prove the affinity and the map of interactions between the receptor (major histocompatibility complex, MHC, or T-cell receptor) and the potential epitope, further computational studies are required. Docking and molecular dynamics (MDs) simulations have been an effective source of generating structural information at molecular level in immunology. Herein, in order to provide a detailed understanding of the origins of epitope recognition and to select the best peptide candidate to develop an epitope-based vaccine, docking and MDs simulations in combination with MMGBSA free energy calculations and per-residue free energy decomposition were performed, taking as starting complexes those formed between four designed epitopes (P1-P4) from hemagglutinin (HA) of the H1N1 influenza virus and MHC-II anchored in POPC membrane. Our results revealed that the energetic contributions of individual amino acids within the pMHC-II complexes are mainly dictated by van der Waals interactions and the nonpolar part of solvation energy, whereas the electrostatic interactions corresponding to hydrogen bonds and salt bridges determine the binding specificity, being the most favorable interactions formed between p4 and MHC-II. Then, P1-P4 epitopes were synthesized and tested experimentally to compare theoretical and experimental results. Experimental results show that P4 elicited the highest strong humoral immune response to HA of the H1N1 and may induce antibodies that are cross-reactive to other influenza subtypes, suggesting that it could be a good candidate for the development of a peptide-based vaccine.

Computational study of β-N-acetylhexosaminidase from Talaromyces flavus, a glycosidase with high substrate flexibility.

Backgroundβ-N-Acetylhexosaminidase (GH20) from the filamentous fungus Talaromyces flavus, previously identified as a prominent enzyme in the biosynthesis of modified glycosides, lacks a high resolution three-dimensional structure so far. Despite of high sequence identity to previously reported Aspergillus oryzae and Penicilluim oxalicum β-N-acetylhexosaminidases, this enzyme tolerates significantly better substrate modification. Understanding of key structural features, prediction of effective mutants and potential substrate characteristics prior to their synthesis are of general interest.ResultsComputational methods including homology modeling and molecular dynamics simulations were applied to shad light on the structure-activity relationship in the enzyme. Primary sequence analysis revealed some variable regions able to influence difference in substrate affinity of hexosaminidases. Moreover, docking in combination with consequent molecular dynamics simulations of C-6 modified glycosides enabled us to identify the structural features required for accommodation and processing of these bulky substrates in the active site of hexosaminidase from T. flavus. To access the reliability of predictions on basis of the reported model, all results were confronted with available experimental data that demonstrated the principal correctness of the predictions as well as the model.ConclusionsThe main variable regions in β-N-acetylhexosaminidases determining difference in modified substrate affinity are located close to the active site entrance and engage two loops. Differences in primary sequence and the spatial arrangement of these loops and their interplay with active site amino acids, reflected by interaction energies and dynamics, account for the different catalytic activity and substrate specificity of the various fungal and bacterial β-N-acetylhexosaminidases.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0465-8) contains supplementary material, which is available to authorized users.

Computer-aided structure-based design of multitarget leads for Alzheimer's disease.

Alzheimer's disease is a neurodegenerative pathology with unmet clinical needs. A highly desirable approach to this syndrome would be to find a single lead that could bind to some or all of the selected biomolecules that participate in the amyloid cascade, the most accepted route for Alzheimer disease genesis. In order to circumvent the challenge posed by the sizable differences in the binding sites of the molecular targets, we propose a computer-assisted protocol based on a pharmacophore and a set of required interactions with the targets that allows for the automated screening of candidates. We used a combination of docking and molecular dynamics protocols in order to discard nonbinders, optimize the best candidates, and provide a rationale for their potential as inhibitors. To provide a proof of concept, we proceeded to screen the literature and databases, a task that allowed us to identify a set of carbazole-containing compounds that initially showed affinity only for the cholinergic targets in our experimental assays. Two cycles of design based on our protocol led to a new set of analogues that were synthesized and assayed. The assay results revealed that the designed inhibitors had improved affinities for BACE-1 by more than 3 orders of magnitude and also displayed amyloid aggregation inhibition and affinity for AChE and BuChE, a result that led us to a group of multitarget amyloid cascade inhibitors that also could have a positive effect at the cholinergic level.

Abstract 5372: A molecular docking strategy for identifying fragment inhibitors of indoleamine 2,3-dioxygenase 1 (IDO1)

Abstract As part of our studies to identify novel inhibitors for the immunosuppressive enzyme indoleamine 2,3-dioxygenase 1 (IDO1) for restoring tumor immunity, we investigated the ability of the enzyme's x-ray crystal structure to predict active molecules when used in molecular docking based virtual screening of fragment libraries. The 352 compound Zenobia Therapeutics fragment library was screened by differential scanning fluorimetry and 74 compounds were identified that altered the thermal stability of the protein. Of these, biochemical analysis showed that only 14 inhibited the enzyme activity by &amp;gt;50% at 1 mM, and hydrazine containing fragments were the most potent inhibitors of recombinant human IDO1 (rhIDO1), with the best being a benzothiazole compound retrieving an IC50 of 8 µM. We recently showed that phenylhydrazine is a more potent inhibitor (IC50 0.3 µM), which provided a dataset for testing various docking strategies to discover fragment inhibitors. The fragment library was docked into the IDO1 active site (PDB code 2D0T) using GOLD driven by the scoring functions ChemPLP, Goldscore, ASP or Chemscore. The three top scoring poses for each compound were kept then rescored by each scoring function. The combination of docking by Goldscore and rescoring by Chemscore to identify the top scoring pose gave the best outcome, an 8.3 fold enrichment of active compounds within the top 5% of the ranked library compared to random selection. Based on this docking and scoring strategy we performed a virtual screening campaign on a 14,000 compound library containing commercially available phenylhydrazine derivatives. Our characterization of phenylhydrazine binding indicated that the hydrazine moiety interacts with the heme iron. Based on this, a set of compounds was selected from the top 30% of poses kept from the docked library for biochemical testing that had predicted hydrazine to heme iron interactions. Of 21 compounds chosen, 10 were tested and 9 inhibited IDO1 with IC50 of &amp;lt; 10 µM. Also, compounds predicted to make a hydrogen bond acceptor to heme iron interaction were selected and an additional 9 compounds chosen of which 6 were tested and only 1 inhibited rhIDO1 with IC50 of &amp;lt; 10 µM. For these latter ones the hydrazine was not predicted to interact with the heme iron. This study indicates that the rhIDO1 structure would be useful for discovering inhibitors in a diverse fragment library, and an additional hydrazine to heme iron binding descriptor is useful for finding actives in a library of compounds containing the phenylhydrazine core. Citation Format: Simon Fung, Jack U. Flanagan, Christopher J. Squire, Brian D. Palmer, Lai-Ming Ching. A molecular docking strategy for identifying fragment inhibitors of indoleamine 2,3-dioxygenase 1 (IDO1). [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5372. doi:10.1158/1538-7445.AM2014-5372

Distinguishing binders from false positives by free energy calculations: fragment screening against the flap site of HIV protease.

Molecular docking is a powerful tool used in drug discovery and structural biology for predicting the structures of ligand–receptor complexes. However, the accuracy of docking calculations can be limited by factors such as the neglect of protein reorganization in the scoring function; as a result, ligand screening can produce a high rate of false positive hits. Although absolute binding free energy methods still have difficulty in accurately rank-ordering binders, we believe that they can be fruitfully employed to distinguish binders from nonbinders and reduce the false positive rate. Here we study a set of ligands that dock favorably to a newly discovered, potentially allosteric site on the flap of HIV-1 protease. Fragment binding to this site stabilizes a closed form of protease, which could be exploited for the design of allosteric inhibitors. Twenty-three top-ranked protein–ligand complexes from AutoDock were subject to the free energy screening using two methods, the recently developed binding energy analysis method (BEDAM) and the standard double decoupling method (DDM). Free energy calculations correctly identified most of the false positives (≥83%) and recovered all the confirmed binders. The results show a gap averaging ≥3.7 kcal/mol, separating the binders and the false positives. We present a formula that decomposes the binding free energy into contributions from the receptor conformational macrostates, which provides insights into the roles of different binding modes. Our binding free energy component analysis further suggests that improving the treatment for the desolvation penalty associated with the unfulfilled polar groups could reduce the rate of false positive hits in docking. The current study demonstrates that the combination of docking with free energy methods can be very useful for more accurate ligand screening against valuable drug targets.

Engineering the Pseudomonas aeruginosa II lectin: designing mutants with changed affinity and specificity.

This article focuses on designing mutations of the PA-IIL lectin from Pseudomonas aeruginosa that lead to change in specificity. Following the previous results revealing the importance of the amino acid triad 22-23-24 (so-called specificity-binding loop), saturation in silico mutagenesis was performed, with the intent of finding mutations that increase the lectin's affinity and modify its specificity. For that purpose, a combination of docking, molecular dynamics and binding free energy calculation was used. The combination of methods revealed mutations that changed the performance of the wild-type lectin and its mutants to their preferred partners. The mutation at position 22 resulted in 85% in inactivation of the binding site, and the mutation at 23 did not have strong effects thanks to the side chain being pointed away from the binding site. Molecular dynamics simulations followed by binding free energy calculation were performed on mutants with promising results from docking, and also at those where the amino acid at position 24 was replaced for bulkier or longer polar chain. The key mutants were also prepared in vitro and their binding properties determined by isothermal titration calorimetry. Combination of the used methods proved to be able to predict changes in the lectin performance and helped in explaining the data observed experimentally.