SEARCH · PubMed Health

Results for “Molecular Docking Simulation”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 631 records · Page 35Linked to original sources

PubMed2005

Hierarchical docking of databases of multiple ligand conformations.

Ligand flexibility is an important problem in molecular docking and virtual screening. To address this challenge, we investigate a hierarchical pre-organization of multiple conformations of small molecules. Such organization of pre-calculated conformations removes the exploration of ligand conformational space from the docking calculation and allows for concise representation of what can be thousands of conformations. The hierarchy also recognizes and prunes incompatible conformations early in the calculation, eliminating redundant calculations of fit. We investigate the method by docking the MDL Drug Data Report (MDDR), an annotated database of 100,000 molecules, into apo and holo forms of seven unrelated targets. This annotated database allows us to track the ranking of tens to hundreds of annotated ligands in each of the docking systems. The binding sites and database are prepared in an automated fashion in an attempt to remove some human bias from the calculations. Many thousands of explicit and implicit ligand conformations may be docked in calculations not much longer than required for single conformer docking. As long as internal energies are not considered, recombination with the hierarchy is additive as the number of degrees of freedom is increased. Molecules with even millions of conformations can be docked in a few minutes on a single desktop computer.

Computer Simulation↗

PubMed2005

[In-silico prediction of pharmacokinetic properties].

In silico methods for predicting pharmacokinetic properties range from data-based approaches such as quantitative structure-activity relationships (QSARs), similarity searches, and 3-dimensional QSAR, to structure-based methods such as ligand-protein docking and pharmacophore modelling. Data-based modelling approaches are effective for many drug absorption, distribution, metabolism, and excretion (ADME) processes such as passive membrane permeation, where their molecular mechanism is barely delineated. Therefore QSAR approaches have been applied to simulate the relationships between ADME parameters and molecular structure and properties. In the present investigation, we describe the application of the genetic algorithm-combined partial least-squares (GA-PLS) method to QSAR modelling of various ADME properties. By selecting an appropriate set of molecular descriptors automatically using the genetic algorithm, many ADME properties could be well explained by simple molecular descriptors derived from the 2-dimensional chemical structure.

Algorithms↗

PubMed1999

Computational ligand design.

A variety of computational tools that are used to assist drug design are reviewed. Particular emphasis is given to the limitations and merits of different methodologies. Recently, a number of general methods have been proposed for clustering compounds in classes of drug-like and non-drug-like molecules. The usefulness of this classification for drug design is discussed. The estimation of (relative) binding affinities is from a theoretical point of view the most challenging part of ligand design. We review three methods for the estimation of binding energies. Firstly, quantitative structure-activity relationships (QSAR) are presented. These have gained significantly from recent developments of experimental techniques for combinatorial synthesis and high-throughput screening as well as the use of powerful computational procedures like genetic algorithms and neural networks for the derivation of models. Secondly, empirical energy functions are shown to lead to more general models than standard QSAR, since they are fitted to a variety of complexes. They have been used recently with considerable success. Thirdly, we briefly outline free energy calculations based on molecular dynamics simulations, the method with the most sound theoretical foundation. Recent developments are reestablishing the interest in this approach. In the last part of this review structure-based ligand design programs are described. These are closely related to docking, with the difference that in design, unlike in most docking procedures, ligands are built on a fragment-by-fragment basis. Finally, a short description of our approach to computational combinatorial ligand design is given.

Drug Design↗

PubMed1998

Flexible docking allowing induced fit in proteins: insights from an open to closed conformational isomers.

Here we dock a ligand onto a receptor surface allowing hinge-bending domain/substructural movements. Our approach mimics and manifests induced fit in molecular recognition. All angular rotations are allowed on the one hand, while a conformational space search is avoided on the other. Rather than dock each of the molecular parts separately with subsequent reconstruction of the consistently docked molecules, all parts are docked simultaneously while still utilizing the position of the hinge from the start. Like pliers closing on a screw, the receptor automatically closes on its ligand in the best surface-matching way. Movements are allowed either in the ligand or in the larger receptor, hence reproducing induced molecular fit. Hinge bending movements are frequently observed when molecules associate. There are numerous examples of open versus closed conformations taking place upon binding. Such movements are observed when the substrate binds to its respective enzyme. In particular, such movements are of interest in allosteric enzymes. The movements can involve entire domains, subdomains, loops, (other) secondary structure elements, or between any groups of atoms connected by flexible joints. We have implemented the hinges at points and at bonds. By allowing 3-dimensional (3-D) rotation at the hinge, several rotations about (consecutive or nearby) bonds are implicitly taken into account. Alternatively, if required, the point rotation can be restricted to bond rotation. Here we illustrate this hinge-bending docking approach and the insight into flexibility it provides on a complex of the calmodulin with its M13 ligand, positioning the hinges either in the ligand or in the larger receptor. This automated and efficient method is adapted from computer vision and robotics. It enables utilizing entire molecular surfaces rather than focusing a priori on active sites. Hence, allows attaining the overall optimally matching surfaces, the extent and type of motions which are involved. Here we do not treat the conformational flexibility of side-chains or of very small pieces of the molecules. Therefore, currently available methods addressing these issues and the method presented here, are complementary to each other, expanding the repertoire of computational docking tools foreseen to aid in studies of recognition, conformational flexibility and drug design.

Algorithms↗

PubMed2005

Increasing the molecular contacts between maurotoxin and Kv1.2 channel augments ligand affinity.

Scorpion toxins interact with their target ion channels through multiple molecular contacts. Because a "gain of function" approach has never been described to evaluate the importance of the molecular contacts in defining toxin affinity, we experimentally examined whether increasing the molecular contacts between a toxin and an ion channel directly impacts toxin affinity. For this purpose, we focused on two scorpion peptides, the well-characterized maurotoxin with its variant Pi1-like disulfide bridging (MTX(Pi1)), used as a molecular template, and butantoxin (BuTX), used as an N-terminal domain provider. BuTX is found to be 60-fold less potent than MTX(Pi1) in blocking Kv1.2 (IC(50) values of 165 nM for BuTX versus 2.8 nM for MTX(Pi1)). Removal of its N-terminal domain (nine residues) further decreases BuTX affinity for Kv1.2 by 5.6-fold, which is in agreement with docking simulation data showing the importance of this domain in BuTX-Kv1.2 interaction. Transfer of the BuTX N-terminal domain to MTX(Pi1) results in a chimera with five disulfide bridges (BuTX-MTX(Pi1)) that exhibits 22-fold greater affinity for Kv1.2 than MTX(Pi1) itself, in spite of the lower affinity of BuTX as compared to MTX(Pi1). Docking experiments performed with the 3-D structure of BuTX-MTX(Pi1) in solution, as solved by (1)H-NMR, reveal that the N-terminal domain of BuTX participates in the increased affinity for Kv1.2 through additional molecular contacts. Altogether, the data indicate that acting on molecular contacts between a toxin and a channel is an efficient strategy to modulate toxin affinity.

Amino Acid Sequence↗

PubMed1998

Molecular modeling of cytochrome P450 2B1: mode of membrane insertion and substrate specificity.

A molecular model of a mammalian membrane-bound cytochrome P450, rat P450 2B1, was constructed in order to elucidate its mode of attachment to the endoplasmic reticulum and the structural basis of substrate specificity. The model was primarily derived from the structure of P450BM-3, which as a class II P450 is the most functionally similar P450 of known structure. However, model development was also guided by the conserved core regions of P450cam and P450terp. To optimally align the P450 2B1 and P450BM-3 sequences, multiple alignment was performed using sequences of five P450s in the II family, followed by minor adjustments on the basis of secondary structure predictions. The resulting P450 2B1 homology model structure was refined by molecular dynamics heating, equilibration, simulation, and energy minimization. The model suggests that the F-G loop serves as both a hydrophobic membrane anchor and entrance channel for hydrophobic substrates from the membrane to the P450 active site. To assess the mode of substrate binding, benzphetamine, testosterone, and benzo[a]pyrene were docked into the active site. The hydrophobic substrate-binding pocket is consistent with the preferences of this P450 toward hydrophobic substrates, while the presence of an acidic Glu-105 in this pocket is consistent with the preference of this P450 for the cationic substrate benzphetamine. This model is thus consistent with several known experimental properties of this P450, such as membrane attachment and substrate selectivity.

Amino Acid Sequence↗

PubMed2006

Protein-ligand docking: current status and future challenges.

Understanding the ruling principles whereby protein receptors recognize, interact, and associate with molecular substrates and inhibitors is of paramount importance in drug discovery efforts. Protein-ligand docking aims to predict and rank the structure(s) arising from the association between a given ligand and a target protein of known 3D structure. Despite the breathtaking advances in the field over the last decades and the widespread application of docking methods, several downsides still exist. In particular, protein flexibility-a critical aspect for a thorough understanding of the principles that guide ligand binding in proteins-is a major hurdle in current protein-ligand docking efforts that needs to be more efficiently accounted for. In this review the key concepts of protein-ligand docking methods are outlined, with major emphasis being given to the general strengths and weaknesses that presently characterize this methodology. Despite the size of the field, the principal types of search algorithms and scoring functions are reviewed and the most popular docking tools are briefly depicted. Recent advances that aim to address some of the traditional limitations associated with molecular docking are also described. A selection of hand-picked examples is used to illustrate these features.

Algorithms↗

PubMed2002

The three-dimensional model of Dictyostelium discoideum racE based on the human rhoA-GDP crystal structure.

The three-dimensional structure of racE was modeled using several homologous small G proteins, and the best model obtained using the human rhoA as modeling template is reported. The three-dimensional fold of the racE model is remarkably similar to the cellular form of human ras p21 crystal structure. Its secondary structure consists of six alpha-helices, six beta-strands and three 3(10) helices. The model retains its secondary structure after a 300 K, 300 ps molecular dynamics (MD) simulation. Important domains of the protein include its effector loop (residues 34-46), the insertion domain (residues 121-136), and the polybasic motif (between 210 and 220) not modeled in the current structure. The effector loop is inherently flexible and the structure docked with GDP exhibits the effector loop moving significantly closer to the nucleotide binding pocket, forming a tighter complex with the bound GDP. The mobility of the effector loop is conferred by a single residue 'hinge' point at residue 34Asp, also allowing the Switch I region, immediately preceding the effector loop, to be equally mobile. In comparison, the Switch II region shows average mobility. The insertion domain is highly flexible, with the insertion taking the form of a helical domain, with several charged residues forming a complex charged interface over the entire insertion region. While the GDP moiety is loosely held in the active site, the metal cation is extensively co-ordinated. The critical residue 38Thr exhibits high mobility, and is seen interacting directly with the metal ion at a distance of 2.64 A, and indirectly via an intervening water molecule. 64Gln, a key residue involved in GTP hydrolysis in ras, is seen facing the beta-phosphate group and the metal ion. Certain residues (i.e. 51Asn, 38Thr and 65Glu) exhibit unique characteristics and these residues, together with 158Val, may play important roles in the maintenance of the protein's integrity and function. There is strong consensus of secondary structural elements between models generated using various templates, such as h-rac1, h-rhoA and h-cdc42 bound to RhoGDI, all sharing only 50-55% sequence identity with racE, which suggests that this model is in all probability an accurate prediction of the true tertiary structure of racE.

Amino Acid Sequence↗

PubMed2006

Parallelized-over-parts computation of absolute binding free energy with docking and molecular dynamics.

We present a technique for biomolecular free energy calculations that exploits highly parallelized sampling to significantly reduce the time to results. The technique combines free energies for multiple, nonoverlapping configurational macrostates and is naturally suited to distributed computing. We describe a methodology that uses this technique with docking, molecular dynamics, and free energy perturbation to compute absolute free energies of binding quickly compared to previous methods. The method does not require a priori knowledge of the binding pose as long as the docking technique used can generate reasonable binding modes. We demonstrate the method on the protein FKBP12 and eight of its inhibitors.

Biophysics↗

PubMed2004

Toward the active conformations of rhodopsin and the beta2-adrenergic receptor.

Using sets of experimental distance restraints, which characterize active or inactive receptor conformations, and the X-ray crystal structure of the inactive form of bovine rhodopsin as a starting point, we have constructed models of both the active and inactive forms of rhodopsin and the beta2-adrenergic G-protein coupled receptors (GPCRs). The distance restraints were obtained from published data for site-directed crosslinking, engineered zinc binding, site-directed spin-labeling, IR spectroscopy, and cysteine accessibility studies conducted on class A GPCRs. Molecular dynamics simulations in the presence of either "active" or "inactive" restraints were used to generate two distinguishable receptor models. The process for generating the inactive and active models was validated by the hit rates, yields, and enrichment factors determined for the selection of antagonists in the inactive model and for the selection of agonists in the active model from a set of nonadrenergic GPCR drug-like ligands in a virtual screen using ligand docking software. The simulation results provide new insights into the relationships observed between selected biochemical data, the crystal structure of rhodopsin, and the structural rearrangements that occur during activation.

Animals↗

PubMed2006

QSAR study of a large set of 3-pyridyl ethers as ligands of the alpha4beta2 nicotinic acetylcholine receptor.

Extensive 3D-QSAR studies were performed on 158 diverse analogues of 3-pyridyl ethers, which are excellent ligands of alpha4beta2 neuronal nicotinic acetylcholine receptor (NnAChR). Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques were used to relate the binding affinities with the ligand structures. Two QSAR models were obtained using CoMFA and CoMSIA techniques. The two QSAR models were proved to be statistically significant and have high predictive power. The best CoMFA model yielded the cross-validated q(2)=0.605 and the non-cross-validated r(2)=0.862. The derived model indicated the importance of steric (85.9%) as well as electrostatic (14.1%) contributions. The CoMFA model demonstrated the steric field as the major descriptor of the ligand binding. The best CoMSIA model gave q(2)=0.723 and r(2)=0.685. This model showed that steric (30.3%) and H-bond interaction (61.8%) properties played major roles in ligand binding process. The squares of correlation coefficient for external test set of 28 molecules were 0.723 and 0.685 for the CoMFA model and the CoMSIA model, respectively. The two models were further graphically interpreted in terms of field contribution maps. SAR studies were also performed on different series of compounds in order to get a more reasonable understanding of the interactions between the ligands and the receptor. With the results, we have also presumed some assistant elements as supplements to the traditional pharmacophoric elements. A crude vision of ligand localization in the ligand-binding pocket of the receptor was also obtained, which would favor for the docking study of this kind of ligands.

Binding Sites↗

PubMed2002

Using robotics to fold proteins and dock ligands.

The problems of protein folding and ligand docking have been explored largely using molecular dynamics or Monte Carlo methods. These methods are very compute intensive because they often explore a much wider range of energies, conformations and time than necessary. In addition, Monte Carlo methods often get trapped in local minima. We initially showed that robotic motion planning permitted one to determine the energy of binding and dissociation of ligands from protein binding sites (Singh et al., 1999). The robotic motion planning method maps complicated three-dimensional conformational states into a much simpler, but higher dimensional space in which conformational rearrangements can be represented as linear paths. The dimensionality of the conformation space is of the same order as the number of degrees of conformational freedom in three-dimensional space. We were able to determine the relative energy of association and dissociation of a ligand to a protein by calculating the energetics of interaction for a few thousand conformational states in the vicinity of the protein and choosing the best path from the roadmap. More recently, we have applied roadmap planning to the problem of protein folding (Apaydin et al., 2002a). We represented multiple conformations of a protein as nodes in a compact graph with the edges representing the probability of moving between neighboring states. Instead of using Monte Carlo simulation to simulate thousands of possible paths through various conformational states, we were able to use Markov methods to calculate the steady state occupancy of each conformation, needing to calculate the energy of each conformation only once. We referred to this Markov method of representing multiple conformations and transitions as stochastic roadmap simulation or SRS. We demonstrated that the distribution of conformational states calculated with exhaustive Monte Carlo simulations asymptotically approached the Markov steady state if the same Boltzman energy distribution was used in both methods. SRS permits one to calculate contributions from all possible paths simultaneously with far fewer energy calculations than Monte Carlo or molecular dynamics methods. The SRS method also permits one to represent multiple unfolded starting states and multiple, near-native, folded states and all possible paths between them simultaneously. The SRS method is also independent of the function used to calculate the energy of the various conformational states. In a paper to be presented at this conference (Apaydin et al., 2002b) we have also applied SRS to ligand docking in which we calculate the dynamics of ligand-protein association and dissociation in the region of various binding sites on a number of proteins. SRS permits us to determine the relative times of association to and dissociation from various catalytic and non-catalytic binding sites on protein surfaces. Instead of just following the best path in a roadmap, we can calculate the contribution of all the possible binding or dissociation paths and their relative probabilities and energies simultaneously.

Algorithms↗

PubMed2006

Computational study of human phosphomannose isomerase: Insights from homology modeling and molecular dynamics simulation of enzyme bound substrate.

Phosphomannose isomerase is a zinc metalloenzyme that catalyzes the reversible isomerization of mannose-6-phosphate and fructose-6-phosphate, and the three-dimensional (3D) structure of human phosphomannose isomerase has not been reported. In order to understand the catalytic mechanism, the 3D structure of the protein is built by using homology modeling based on the known crystal structure of mannose-6-phosphate isomerase from (PDB code 1PMI). The model structure is further refined by energy minimization and molecular dynamics methods. The mannose-6-phosphate-enzyme complex is developed by molecular docking and the key residues involved in the ligand binding are determined, which will facilitate the understanding of the action mode of the ligands and guide further genetic studies. Our results suggest a hydride transfer mechanism of alpha-hydrogen between the C1 and C2 positions but do not support the cis-enediol mechanism. The detailed mechanism involves, on one side, Zn2+ mediating the movement of a proton between O1 and O2, and, on the other side, the hydrophobic environment formed in part by Tyr278 promoting transfer of a hydride ion.

Amino Acid Sequence↗

PubMed2004

Molecular dynamics simulations of the human CAR ligand-binding domain: deciphering the molecular basis for constitutive activity.

The constitutive androstane receptor (CAR) belongs to the superfamily of nuclear-hormone receptors that function as ligand-activated transcription factors. CAR plays an essential role in the metabolism of xenobiotics and shows--in contrast to related receptors--constitutive activity. However, the molecular basis for the constitutive activity remains unclear. In the present study, homology models of the ligand binding domain (LBD) were generated based on the crystal structures of the related pregnane X (PXR) and the vitamin D receptor (VDR). The models were used to investigate the basal activity of CAR and the effect of coactivator binding. Molecular dynamics (MD) simulations of complexed and uncomplexed receptor revealed a hypothesis for the activation mechanism. The suggested mechanism is supported by experimental results from site-directed mutagenesis. The basal activity of CAR can be explained by specific van-der-Waals interactions between amino acids on the LBD and its C-terminal activation domain (AF-2). Docking studies with the GOLD program yielded the interaction modes of structurally diverse agonists, giving insight into mechanisms by which ligands enhance CAR activity.

Amino Acid Sequence↗

PubMedDate not supplied

Molecular dynamics of a vasopressin V2 receptor in a phospholipid bilayer membrane.

Molecular dynamics simulations were carried out for a V2 receptor (V2R) model embedded in a dimyristoylphosphatidylcholine (DMPC) bilayer. Both free and ligand-bound states of V2R were modeled. Our initial V2R model was obtained using a rule-based automated method for GPCR modeling and refined using constrained simulated annealing in vacuo. The docking site of the native vasopressin ligand was selected and justified upon consideration of ligand-receptor interactions and structure-activity data. The primary purpose of this work was to investigate the usefulness of MD simulation of an integral membrane protein like a GPCR receptor, upon inclusion of a carefully parameterized surrounding lipid membrane and water. Physical properties of the system were evaluated and compared with the fully hydrated pure DMPC bilayer membrane. The solvation interactions, individual lipid-protein interaction and fluctuations of the protein, the lipid, and water were analyzed in detail. As expected, the membrane-spanning helices of the protein fluctuate less than the peripheral loops do. The protein appears to disturb the local lipid structure. Simulations were carried out using AMBER 4.1 package upon constant number-pressure-temperature (NPT) conditions on massively parallel computers Cray T3E and IBM SP2.

Animals↗

PubMed2006

Computer aided comparative analysis of the binding modes of the adenosine receptor agonists for all known subtypes of adenosine receptors.

Molecular models of all known subtypes (A1, A2A, A2B, and A3) of the human adenosine receptors were built in homology with bovine rhodopsin. These models include the transmembrane domain as well as all extracellular and intracellular hydrophilic loops and terminal domains. The molecular docking of adenosine and 46 selected derivatives was performed for each receptor subtype. A binding mode common for all studied agonists was proposed, and possible explanations for differences in the ligand activities were suggested.

Adenosine↗

PubMed2005

Antibiotic binding to monozinc CphA beta-lactamase from Aeromonas hydropila: quantum mechanical/molecular mechanical and density functional theory studies.

The active-site dynamics of apo CphA beta-lactamase from Aeromonas hydropila and its complex with a beta-lactam antibiotic molecule (biapenem) are simulated using a quantum mechanical/molecular mechanical (QM/MM) method and density functional theory (DFT). The quantum region in the QM/MM simulations, which includes the Zn(II) ion and its ligands, the antibiotic molecule, the catalytic water, and an active-site histidine residue, was treated using the self-consistent charge density functional tight binding (SCC-DFTB) model. Biapenem is docked at the active site unambiguously, based on a recent X-ray structure of an enzyme-intermediate complex. The substrate is found to form the fourth ligand of the zinc ion with its 3-carboxylate oxygen and to hydrogen bond with several active-site residues. The stability of the metal-ligand bonds and the hydrogen-bond network is confirmed by 500 ps molecular dynamics simulations of both the apo enzyme and the substrate-enzyme complex. The structure and dynamics of the substrate-enzyme complex provide valuable insights into the mode of catalysis in such enzymes that is central to the bacterial resistance to beta-lactam antibiotics.

Anti-Bacterial Agents↗

PubMed2005

Target flexibility in molecular recognition.

Induced-fit effects are well known in the binding of small molecules to proteins and other macromolecular targets. Among other targets, protein kinases are particularly flexible proteins, so that such effects should be considered in attempts at structure-based inhibitor design for kinase targets. This paper outlines some recent progress in methods for including target flexibility in computational studies of molecular recognition. A focus is the "relaxed complex method," in which ligands are docked to an ensemble of conformations of the target, and the best complexes are re-scored to provide predictions of optimal binding geometries. Early applications of this method have suggested a new approach to the development of inhibitors of HIV-1 Integrase.

Computer Simulation↗