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Results for “Molecular Docking Simulation”

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PubMed1999

Efficient computational algorithms for docking and for generating and matching a library of functional epitopes II. Computer vision-based techniques for the generation and utilization of functional epitopes.

This is the second review in a two-part series. In the first review (1) we described the computational complexity involved in the docking of a ligand onto a receptor surface. In particular, we focused on efficient algorithms designed to handle this computational task. Such a procedure results in a large number of potential, geometrically feasible solutions. The difficulty is to pinpoint which of these is the more likely candidate. While there exists a number of approaches to rank these solutions according to different criteria, such as the size of the interface or some approximation of their binding energetics, none of the existing methods has been shown to be consistently successful in this endeavor. If the binding site is unknown a priori, the magnitude of the task is awesome. Here we propose one way of addressing this problem, i.e., via derivation and utilization of binding epitopes. If a library of such epitopes is available, particularly for a large number of protein families, it may be used to predict more likely binding sites for a given ligand. We describe an efficient, computer-vision based method to construct binding epitopes focusing on two ways through which such a library can be generated, (i) molecular surface-based, or (ii) residue-based. Alternatively, the two can be combined. We further describe how such a library may be used efficiently in the matching/docking procedure.

Algorithms↗

PubMed2006

Structure-based drug design and structural biology study of novel nonpeptide inhibitors of severe acute respiratory syndrome coronavirus main protease.

Severe acute respiratory syndrome coronavirus (SARS-CoV) main protease (M(pro)), a protein required for the maturation of SARS-CoV, is vital for its life cycle, making it an attractive target for structure-based drug design of anti-SARS drugs. The structure-based virtual screening of a chemical database containing 58,855 compounds followed by the testing of potential compounds for SARS-CoV M(pro) inhibition leads to two hit compounds. The core structures of these two hits, defined by the docking study, are used for further analogue search. Twenty-one analogues derived from these two hits exhibited IC50 values below 50 microM, with the most potent one showing 0.3 microM. Furthermore, the complex structures of two potent inhibitors with SARS-CoV M(pro) were solved by X-ray crystallography. They bind to the protein in a distinct manner compared to all published SARS-CoV M(pro) complex structures. They inhibit SARS-CoV M(pro) activity via intensive H-bond network and hydrophobic interactions, without the formation of a covalent bond. Interestingly, the most potent inhibitor induces protein conformational changes, and the inhibition mechanisms, particularly the disruption of catalytic dyad (His41 and Cys145), are elaborated.

Binding Sites↗

PubMed2004

Proton-coupled electron transfer in soybean lipoxygenase.

The proton-coupled electron transfer reaction catalyzed by soybean lipoxygenase-1 is studied with a multistate continuum theory that represents the transferring hydrogen nucleus as a quantum mechanical wave function. The inner-sphere reorganization energy of the iron cofactor is calculated with density functional theory, and the outer-sphere reorganization energy of the protein is calculated with the frequency-resolved cavity model for conformations obtained with docking simulations. Both classical and quantum mechanical treatments of the proton donor-acceptor vibrational motion are presented. The temperature dependence of the calculated rates and kinetic isotope effects is in agreement with the experimental data. The weak temperature dependence of the rates is due to the relatively small free energy barrier arising from a balance between the reorganization energy and the reaction free energy. The unusually high deuterium kinetic isotope effect of 81 is due to the small overlap of the reactant and product proton vibrational wave functions and the dominance of the lowest energy reactant and product vibronic states in the tunneling process. The temperature dependence of the kinetic isotope effect is strongly influenced by the proton donor-acceptor distance with the dominant contribution to the overall rate. This dominant proton donor-acceptor distance is significantly smaller than the equilibrium donor-acceptor distance and is determined by a balance between the larger coupling and the smaller Boltzmann probability as the distance decreases. Thus, the proton donor-acceptor vibrational motion plays a vital role in decreasing the dominant donor-acceptor distance relative to its equilibrium value to facilitate the proton-coupled electron transfer reaction.

Electron Transport↗

PubMedDate not supplied

Improved mapping of protein binding sites.

Computational mapping methods place molecular probes--small molecules or functional groups--on a protein surface in order to identify the most favorable binding positions by calculating an interaction potential. Mapping is an important step in a number of flexible docking and drug design algorithms. We have developed improved algorithms for mapping protein surfaces using small organic molecules as molecular probes. The calculations reproduce the binding of eight organic solvents to lysozyme as observed by NMR, as well as the binding of four solvents to thermolysin, in good agreement with x-ray data. Application to protein tyrosine phosphatase 1B shows that the information provided by the mapping can be very useful for drug design. We also studied why the organic solvents bind in the active site of proteins, in spite of the availability of alternative pockets that can very tightly accommodate some of the probes. A possible explanation is that the binding in the relatively large active site retains a number of rotational states, and hence leads to smaller entropy loss than the binding elsewhere else. Indeed, the mapping reveals that the clusters of the ligand molecules in the protein's active site contain different rotational-translational conformers, which represent different local minima of the free energy surface. In order to study the transitions between different conformers, reaction path and molecular dynamics calculations were performed. Results show that most of the rotational states are separated by low free energy barriers at the experimental temperature, and hence the entropy of binding in the active site is expected to be high.

Animals↗

PubMed2005

Modeling and experimental validation of the binary complex of the plectin actin-binding domain and the first pair of fibronectin type III (FNIII) domains of the beta4 integrin.

The binding of plectin to the beta4 subunit of the alpha6beta4 integrin is a critical step in the formation of hemidesmosomes. An important interaction between these two proteins occurs between the actin-binding domain (ABD) of plectin and the first pair of fibronectin type III (FNIII) domains and a small part of the connecting segment of beta4. Previously, a few amino acids, critical for this interaction, were identified in both plectin and beta4 and mapped on the crystal structures of the ABD of plectin and the first pair of FNIII domains of beta4. In the present study, we used this biochemical information and protein-protein docking calculations to construct a model of the binary complex between these two protein domains. The top scoring computational model predicts that the calponin-homology 1 (CH1) domain of the ABD associates with the first and the second FNIII domains of beta4. Our mutational analysis of the residues at the proposed interface of both the FNIII and the CH1 domains is in agreement with the suggested interaction model. Computational simulations to predict protein motions suggest that the exact model of FNIII and plectin CH1 interaction might well differ in detail from the suggested model due to the conformational plasticity of the FNIII domains, which might lead to a closely related but different mode of interaction with the plectin-ABD. Furthermore, we show that Ser-1325 in the connecting segment of beta4 appears to be essential for the recruitment of plectin into hemidesmosomes in vivo. This is consistent with the proposed model and previously published mutational data. In conclusion, our data support a model in which the CH1 domain of the plectin-ABD associates with the groove between the two FNIII domains of beta4.

Actins↗

PubMed2006

Differential targeting of Gbetagamma-subunit signaling with small molecules.

G protein betagamma subunits have potential as a target for therapeutic treatment of a number of diseases. We performed virtual docking of a small-molecule library to a site on Gbetagamma subunits that mediates protein interactions. We hypothesized that differential targeting of this surface could allow for selective modulation of Gbetagamma subunit functions. Several compounds bound to Gbetagamma subunits with affinities from 0.1 to 60 muM and selectively modulated functional Gbetagamma-protein-protein interactions in vitro, chemotactic peptide signaling pathways in HL-60 leukocytes, and opioid receptor-dependent analgesia in vivo. These data demonstrate an approach for modulation of G protein-coupled receptor signaling that may represent an important therapeutic strategy.

Analgesics↗

PubMed2003

LigandFit: a novel method for the shape-directed rapid docking of ligands to protein active sites.

We present a new shape-based method, LigandFit, for accurately docking ligands into protein active sites. The method employs a cavity detection algorithm for detecting invaginations in the protein as candidate active site regions. A shape comparison filter is combined with a Monte Carlo conformational search for generating ligand poses consistent with the active site shape. Candidate poses are minimized in the context of the active site using a grid-based method for evaluating protein-ligand interaction energies. Errors arising from grid interpolation are dramatically reduced using a new non-linear interpolation scheme. Results are presented for 19 diverse protein-ligand complexes. The method appears quite promising, reproducing the X-ray structure ligand pose within an RMS of 2A in 14 out of the 19 complexes. A high-throughput screening study applied to the thymidine kinase receptor is also presented in which LigandFit, when combined with LigScore, an internally developed scoring function, yields very good hit rates for a ligand pool seeded with known actives.

Algorithms↗

PubMed2000

The oxetane ring in taxol.

Numerous structure-activity studies combining synthesis and bioassay have been performed for the anti-cancer drug Taxol. The four-membered D-ring, an oxetane, is one of four structural features regarded to be essential for biological activity. This proposition is examined by application of a Taxol-epothilone minireceptor, K(i) estimation for microtubule binding and docking of Taxol analogues into a model of the Taxol-tubulin complex. In this way, we evaluate the two characteristics considered responsible for oxetane function: (1) rigidification of the tetracyclic Taxol core to provide an appropriate framework for presenting the C-2, C-4, C-13 side chains to the microtubule protein and (2) service as a hydrogen-bond acceptor. An energy decomposition analysis for a series of Taxol analogues demonstrates that the oxetane ring clearly operates by both mechanisms. However, a broader analysis of four-membered ring containing compounds, C- and D-seco derivatives, and structures with no oxetane equivalent underscores that the four-membered ring is not necessary for Taxol analogue bioactivity. Other functional groups and ligand-protein binding characteristics are fully capable of delivering Taxol biobehavior as effectively as the oxetane D-ring. This insight may contribute to the design and development of novel anticancer drugs.

Antineoplastic Agents↗

PubMedDate not supplied

A discussion of measures of enrichment in virtual screening: comparing the information content of descriptors with increasing levels of sophistication.

We have performed virtual screening using some very simple features, by employing the number of atoms per element as molecular descriptors but without regard to any structural information whatsoever. Surprisingly, these atom counts are able to outperform virtual-affinity-based fingerprints and Unity fingerprints in some activity classes. Although molecular weight and other biases were known in target-based virtual screening settings (docking), we report the effect of using very simple descriptors for ligand-based virtual screening, by using clearly defined biological targets and employing a large data set (>100,000 compounds) containing multiple (11) activity classes. Structure-unaware atom count vectors as descriptors in combination with the Euclidean distance measure are able to achieve "enrichment factors" over random selection of around 4 (depending on the particular class of active compounds), putting the enrichment factors reported for more sophisticated virtual screening methods in a different light. They are also able to retrieve active compounds with novel scaffolds instead of merely the expected structural analogues. The added value of many currently used virtual screening methods (calculated as enrichment factors) drops down to a factor of between 1 and 2, instead of often reported double-digit figures. The observed effect is much less profound for simple descriptors such as molecular weight and is only present in cases of atypical (larger) ligands. The current state of virtual screening is not as sophisticated as might be expected, which is due to descriptors still not being able to capture structural properties relevant to binding. This fact can partly be explained by highly nonlinear structure-activity relationships, which represent a severe limitation of the "similar property principle" in the context of bioactivity.

Computer Simulation↗

PubMed1995

Role of a hydrophobic pocket of the human Y1 neuropeptide Y receptor in ligand binding.

We are investigating the nature of the chemical interactions between the neuropeptide Y (NPY) and its cell surface receptor (Y1). A previous study involving site-directed mutagenesis and computer-aided modelling (Walker et al., 1994) suggested that the C-terminal Tyr36 of NPY, known to be a key residue for receptor binding, might dock at a pocket formed by hydrophobic amino acids of transmembrane domains (TM) 1, 2, 6 and 7 of the Y1 receptor. To investigate which residues were required for ligand binding, we mutated the sequences encoding F41, L43, F96, Y100, F286 and H298 of the human Y1 receptor. The mutant cDNAs were transiently expressed in Hela cells and the ability of the encoded proteins to bind NPY was evaluated. Replacing F41, L43 or F96 with alanines had no effect on NPY binding. On the contrary, Y100, F286 and H298 appeared to be residues critical for ligand binding. In particular, the removal of the hydroxyl group of Y100 (Tyr100-->Phe100 mutation) yielded a protein devoid of affinity for the ligand. The level of expression and the presence on the cell surface of mutants lacking NPY binding activity was assessed by immunological techniques. In addition, we tested the ability of synthetic analogues of neuropeptide Y with substitutions at position 36 to bind to the Y1 receptor. To get spatial insight into the relative positions of the above mentioned residues we constructed a molecular model of the interaction between NPY:Y36 and the elements of the hydrophobic pocket surrounding this residue.

Base Sequence↗

PubMed2005

Docking and 3-D QSAR studies on indolyl aryl sulfones. Binding mode exploration at the HIV-1 reverse transcriptase non-nucleoside binding site and design of highly active N-(2-hydroxyethyl)carboxamide and N-(2-hydroxyethyl)carbohydrazide derivatives.

Three-dimensional quantitative structure-activity relationship (3-D QSAR) studies and docking simulations were developed on indolyl aryl sulfones (IASs), a class of novel HIV-1 non-nucleoside reverse transcriptase (RT) inhibitors (Silvestri, et al. J. Med. Chem. 2003, 46, 2482-2493) highly active against wild type and some clinically relevant resistant strains (Y181C, the double mutant K103N-Y181C, and the K103R-V179D-P225H strain, highly resistant to efavirenz). Predictive 3-D QSAR models using the combination of GRID and GOLPE programs were obtained using a receptor-based alignment by means of docking IASs into the non-nucleoside binding site (NNBS) of RT. The derived 3-D QSAR models showed conventional correlation (r(2)) and cross-validated (q(2)) coefficients values ranging from 0.79 to 0.93 and from 0.59 to 0.84, respectively. All described models were validated by an external test set compiled from previously reported pyrryl aryl sulfones (Artico, et al. J. Med. Chem. 1996, 39, 522-530). The most predictive 3-D QSAR model was then used to predict the activity of novel untested IASs. The synthesis of six designed derivatives (prediction set) allowed disclosure of new IASs endowed with high anti-HIV-1 activities.

Binding Sites↗

PubMed2005

Evaluation of library ranking efficacy in virtual screening.

We present the results of a comprehensive study in which we explored how the docking procedure affects the performance of a virtual screening approach. We used four docking engines and applied 10 scoring functions to the top-ranked docking solutions of seeded databases against six target proteins. The scores of the experimental poses were placed within the total set to assess whether the scoring function required an accurate pose to provide the appropriate rank for the seeded compounds. This method allows a direct comparison of library ranking efficacy. Our results indicate that the LigandFit/Ligscore1 and LigandFit/GOLD docking/scoring combinations, and to a lesser degree FlexX/FlexX, Glide/Ligscore1, DOCK/PMF (Tripos implementation), LigandFit1/Ligscore2 and LigandFit/PMF (Tripos implementation) were able to retrieve the highest number of actives at a 10% fraction of the database when all targets were looked upon collectively. We also show that the scoring functions rank the observed binding modes higher than the inaccurate poses provided that the experimental poses are available. This finding stresses the discriminatory ability of the scoring algorithms, when better poses are available, and suggests that the number of false positives can be lowered with conformers closer to bioactive ones.

Algorithms↗

PubMed2006

Active site acidic residues and structural analysis of modelled human aromatase: a potential drug target for breast cancer.

This study sheds new light on the role of acidic residues present in the active site cavity of human aromatase. Eight acidic residues (E129, D222, E245, E302, D309, E379, D380 and D476) lining the cavity are identified and studied using comparative modeling, docking, molecular dynamics as well as statistical techniques. The structural environment of these acidic residues is studied to assess the stability of the corresponding carboxylate anions. Results indicate that the environment of the residues E245, E302 and D222 is most suitable for carboxylate ion formation in the uncomplexed form. However, the stability of D309, D222 and D476 anions is seen to increase on complexation to steroidal substrates. In particular, the interaction between D309 and T310, which assists proton transfer, is found to be formed following androgen/nor-androgen complexation. The residue D309 is found to be clamped in the presence of substrate which is not observed in the case of the other residues although they exhibit changes in properties following substrate binding. Information entropic analysis indicates that the residues D309, D222 and D476 have more conformational flexibility compared to E302 and E245 prior to substrate binding. Interaction similar to that between D476 and D309, which is expected to assist androgen aromatization, is proposed between E302 and E245. The inhibition of aromatase activity by 4-hydroxy androstenedione (formestane) is attributed to a critical hydrogen bond formation between the hydroxy moiety and T310/D309 as well as the large distance from D476. The results corroborate well with earlier site directed mutagenesis studies.

Amino Acids, Acidic↗

PubMed2005

Virtual ligand screening against Escherichia coli dihydrofolate reductase: improving docking enrichment using physics-based methods.

Motivated by their participation in the McMaster Data-Mining and Docking Competition, the authors developed 2 new computational technologies and applied them to docking against Escherichia coli dihydrofolate reductase: a receptor preparation procedure that incorporates rotamer optimization of side chains and a physics-based rescoring procedure for estimating relative binding affinities of the protein-ligand complexes. Both methods use the same energy function, consisting of the all-atom OPLS-AA force field and a generalized Born solvent model, which treats the protein receptor and small-molecule ligands in a consistent manner. Thus, the energy function is similar to that used in more sophisticated approaches, such as free-energy perturbation and the molecular mechanics Poisson-Boltzmann/surface area, but sampling during the rescoring procedure is limited to simple energy minimization of the ligand. The use of a highly efficient minimization algorithm permitted the authors to apply this rescoring procedure to hundreds of thousands of protein-ligand complexes during the competition, using a modest Linux cluster. To test these methods, they used the 12 competitive inhibitors identified in the training set, plus methotrexate, as positive controls in enrichment studies with both the training and test sets, each containing 50,000 compounds. The key conclusion is that combining the receptor preparation and rescoring methods makes it possible to identify most of the positive controls within the top few tenths of a percent of the rank-ordered training and test set libraries.

Computational Biology↗

PubMed2003

Inhibitors of vitamin D hydroxylases: structure-activity relationships.

Aiming at new drugs to efficiently treat diseases, in which either increased or decreased levels of active vitamin D are desirable, we have designed some 400 structurally different azole-type inhibitors and examined their capacity to selectively block vitamin D metabolism by CYP24 or synthesis by CYP27B, in human keratinocytes. Based on resulting data, we built pharmacophore models of the active sites using commercial software. The overlay of potent selective compounds indicated similar docking modes in the two-substrate pockets and allowed for identification of bioactive conformations. Superimposing these bioactive conformations with low energy conformers of 25(OH)D(3) suggested that the substrate-mimicked by strong inhibitors in size, shape and lipophilic character-binds to both enzymes in 6s-trans configuration. Pharmacophoric models implied a similar geometry of the substrate sites, nevertheless specific features of CYP24 and CYP27B could be defined. Bulky substituents in alpha-position to the azole caused selectivity for CYP24, whereas bulky substituents in beta-position could result in selectivity for CYP27B. Moreover, studies with small sterically restricted inhibitors revealed a probable location of the 3-OH-group of 25(OH)D(3) in CYP27B. In the absence of crystal structures, our inhibitors are valuable tools to model and understand the active sites of vitamin D hydroxylases, resulting in the design of powerful, selective therapeutics.

25-Hydroxyvitamin D3 1-alpha-Hydroxylase↗

PubMed2004

Computer modeling of the rhamnogalacturonase-"hairy" pectin complex.

The structure of a pectin-bound complex of rhamnogalacturonase was modeled to identify the amino acid residues involved in catalysis and substrate binding. The "hairy" region of pectin, represented by six repeating stretches of (1-->4)-D-galacturonate-(1-->2)-L-rhamnose dimer, was flexibly docked into the putative binding site of rhamnogalacturonase from Aspergillus aculeatus whose X-ray structure is known. A search of the complex configurational space was performed using AutoDock for the dimeric and tetrameric sugar units in which the -1 galacturonate residue has various ring conformations. Then the plausible AutoDock solutions were manually extended to the dodecameric pectin models. Subsequently, the resulting complex models were subjected to solvated molecular dynamics using AMBER. In the best model, the substrate has an extended pseudo-threefold helix with the -1 ring in a 4H3 half-chair that approaches the transition state conformation. The catalytic machinery is clearly defined: Asp197 is a general acid and the activated water bound between Asp177 and Glu198 is a nucleophile. The active site is similar, with a small yet significant difference, to that of polygalacturonase that degrades the pectic "smooth" region of linear homopolymer of D-(1-->4)-linked galacturonic acid. Rhamnogalacturonase has ten binding subsites ranging from -3 to +7, while polygalacturonase has eight subsites from -5 to +3. The model suggests that the eight amino acids including three arginine and three lysine residues, all of which are invariantly conserved in the rhamnogalacturonase family of proteins, are important in substrate binding. The present study may aid in designing mutational studies to characterize rhamnogalacturonase.

Amino Acid Sequence↗

PubMed1995

The binding site of neuropeptide vasopressin V1a receptor. Evidence for a major localization within transmembrane regions.

To identify receptor functional domains underlying binding of the neurohypophysial hormones vasopressin (AVP) and oxytocin (OT), we have constructed a three-dimensional (3D) model of the V1a vasopressin receptor subtype and docked the endogenous ligand AVP. To verify and to refine the 3D model, residues likely to be involved in agonist binding were selected for site-directed mutagenesis. Our experimental results suggest that AVP, which is characterized by a cyclic structure, could be completely buried into a 15-20-A deep cleft defined by the transmembrane helices of the receptor and interact with amino acids located within this region. Moreover, the AVP-binding site is situated in a position equivalent to that described for the cationic neurotransmitters. Since all mutated residues are highly conserved in AVP and OT receptors, we propose that the same agonist-binding site is shared by all members of this receptor family. In contrast, the affinity for the antagonists tested, including those with a structure closely related to AVP, is not affected by mutations. This indicates a different binding mode for agonists and antagonists in the vasopressin receptor.

Amino Acid Sequence↗

PubMed2001

Human type 10 17 beta-hydroxysteroid dehydrogenase: molecular modelling and substrate docking.

17 beta-hydroxysteroid dehydrogenases catalyze the oxidoreduction of hydroxy/oxo groups at position C17 of steroid hormones, thereby constituting a prereceptor control mechanism of hormone action. At present, 11 different mammalian 17 beta-hydroxysteroid dehydrogenases have been identified, catalyzing the cell- and steroid-specific activation and inactivation of estrogens and androgens. The human type 10 17 beta-hydroxysteroid dehydrogenase (17 beta-HSD-10) is a multifunctional mitochondrial enzyme that efficiently catalyzes the oxidative inactivation at C17 of androgens and estrogens. However, it also mediates oxidation of 3 alpha-hydroxy groups of androgens, thereby reactivating androgen metabolites. Finally, it is involved in beta-oxidation of fatty acids by catalyzing the L-hydroxyacyl CoA dehydrogenase reaction of the beta-oxidation cycle. These features and expression profiles suggest a critical role of 17 beta-HSD-10 in neurodegenerative and steroid-dependent cancer forms. Since no three-dimensional structure of 17 beta-HSD-10 is available, homology modelling was carried out to understand the molecular basis of these substrate specificities. The structure obtained displays the properties of a one-domain, alpha/beta fold enzyme of the SDR family. The active site is located within a large, hydrophobic cleft, which forms optimal contacts with the different steroid surfaces. The data provide explanations for the substrate specificities toward the various classes of sex steroid hormones. The model is suitable to explore substrate and inhibitor characteristics that may be used in the development of novel strategies in the treatment of degenerative or malignant diseases.

17-Hydroxysteroid Dehydrogenases↗