Molecular Fragment Replacement Research Articles

QSAR, Docking and Molecular Fragment Replacement Study based on a Conformation- Independent Approach on Trifluorophenyl β-aminoamide derivatives as DPP IV Inhibitors

Background: Inhibition of Dipeptidyl peptidase IV (DPP IV) enzyme is an attractive and appropriate target for the treatment of type 2 diabetes. In order to discover for potent DPP IV inhibitors a chemoinformatics studies were performed on fifty nine trifluorophenyl β-aminoamide derivatives using Sybyl X 2.1.1. Methods: The comparative molecular field analysis (CoMFA), comparative molecular similarity index analysis (CoMSIA) and hologram quantitative structural activity relationship (HQSAR) and docking techniques were selected, validated and optimized by a test set of fifteen compounds in order to design new molecules. Result: The values of cross validated r2 (q2), non cross validated r2 and predicted r2 were for CoMFA (q2=0.854, r2=0.928, pred. r2=0. 932), CoMSIA (q2 =0. 864, r2=0. 924, pred. r2=0.922) and HQSAR (q2=0.826, r2=0.942, pred. r2=0.705), respectively. Conclusion: The structure activity relationship of selected analysis suggested that bulky and electron withdrawing substituents at 2nd and 3rd position of piperazine ring; bulky and electron withdrawing substituent at R position and less bulky and electron donating substituent at 5th position of piperazine ring were favorable for inhibition of DPP IV enzyme. In docking analysis (3W2T pdb) amino group and carbonyl group of compound 44 formed hydrogen bond interactions with Glu 206, Tyr 662 and Arg 125 respectively at active site of DPP IV enzyme. The present work finding may be helpful in the designing and optimization of novel DPP IV inhibitors. Keywords: CoMFA, conformational analysis, diabetes, DPP IV, trifluorophenyl & beta;-aminoamide derivatives.

QSAR modeling and in silico design of small-molecule inhibitors targeting the interaction between E3 ligase VHL and HIF-1α.

Protein-protein interactions (PPIs) have attracted much attention recently because of their preponderant role in most biological processes. The prevention of the interaction between E3 ligase VHL and HIF-1[Formula: see text] may improve tolerance to hypoxia and ameliorate the prognosis of many diseases. To obtain novel potent inhibitors of VHL/HIF-1[Formula: see text] interaction, a series of hydroxyproline-based inhibitors were investigated for structural optimization using a combination of QSAR modeling and molecular docking. Here, 2D- and 3D-QSAR models were developed by genetic function approximation (GFA) and comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) methods, respectively. The top-ranked models with strict validation revealed satisfactory statistical parameters (CoMFA with [Formula: see text], 0.637; [Formula: see text], 0.955; [Formula: see text], 0.944; CoMSIA with [Formula: see text], 0.649; [Formula: see text], 0.954; [Formula: see text], 0.911; GFA with [Formula: see text], 0.721; [Formula: see text], 0.801; [Formula: see text], 0.861). The selected five 2D-QSAR descriptors were in good accordance with the 3D-QSAR results, and contour maps gave the visualization of feature requirements for inhibitory activity. A new diverse molecular database was created by molecular fragment replacement and BREED techniques for subsequent virtual screening. Eventually, 31 novel hydroxyproline derivatives stood out as potential VHL/HIF-1[Formula: see text] inhibitors with favorable predictions by the CoMFA, CoMSIA and GFA models. The reliability of this protocol suggests that it could also be applied to the exploration of lead optimization of other PPI targets.

Disordered Regions Flanking Ordered Domains Modulate Signaling Transduction

Signals generated by cell surface receptors are transduced and relayed to downstream intracellular signaling pathways typically through proteins in which folded domains are flanked by regions that are unstructured or only partially structured. Such signaling systems are often multidomain proteins in which disordered linkers provide an effective means to covalently tether and colocalize globular modules (1). However, in several regulatory proteins, linkers have been reported to serve not only as passive covalent tethers, but also as active modulators of the function elicited by adjacent domains (2–4).

Quantitative structure–activity relationship study on BTK inhibitors by modified multivariate adaptive regression spline and CoMSIA methods

Bruton’s tyrosine kinase (BTK) plays a crucial role in B-cell activation and development, and has emerged as a new molecular target for the treatment of autoimmune diseases and B-cell malignancies. In this study, two- and three-dimensional quantitative structure–activity relationship (2D and 3D-QSAR) analyses were performed on a series of pyridine and pyrimidine-based BTK inhibitors by means of genetic algorithm optimized multivariate adaptive regression spline (GA-MARS) and comparative molecular similarity index analysis (CoMSIA) methods. Here, we propose a modified MARS algorithm to develop 2D-QSAR models. The top ranked models showed satisfactory statistical results (2D-QSAR: Q2 = 0.884, r2 = 0.929, r2pred = 0.878; 3D-QSAR: q2 = 0.616, r2 = 0.987, r2pred = 0.905). Key descriptors selected by 2D-QSAR were in good agreement with the conclusions of 3D-QSAR, and the 3D-CoMSIA contour maps facilitated interpretation of the structure–activity relationship. A new molecular database was generated by molecular fragment replacement (MFR) and further evaluated with GA-MARS and CoMSIA prediction. Twenty-five pyridine and pyrimidine derivatives as novel potential BTK inhibitors were finally selected for further study. These results also demonstrated that our method can be a very efficient tool for the discovery of novel potent BTK inhibitors.

Direct photocapture of bromodomains using tropolone chemical probes

Tropolone probes directly photoaffinity label bromodomains.

Equilibrium simulations of proteins using molecular fragment replacement and NMR chemical shifts.

Methods of protein structure determination based on NMR chemical shifts are becoming increasingly common. The most widely used approaches adopt the molecular fragment replacement strategy, in which structural fragments are repeatedly reassembled into different complete conformations in molecular simulations. Although these approaches are effective in generating individual structures consistent with the chemical shift data, they do not enable the sampling of the conformational space of proteins with correct statistical weights. Here, we present a method of molecular fragment replacement that makes it possible to perform equilibrium simulations of proteins, and hence to determine their free energy landscapes. This strategy is based on the encoding of the chemical shift information in a probabilistic model in Markov chain Monte Carlo simulations. First, we demonstrate that with this approach it is possible to fold proteins to their native states starting from extended structures. Second, we show that the method satisfies the detailed balance condition and hence it can be used to carry out an equilibrium sampling from the Boltzmann distribution corresponding to the force field used in the simulations. Third, by comparing the results of simulations carried out with and without chemical shift restraints we describe quantitatively the effects that these restraints have on the free energy landscapes of proteins. Taken together, these results demonstrate that the molecular fragment replacement strategy can be used in combination with chemical shift information to characterize not only the native structures of proteins but also their conformational fluctuations.

3D-QSAR and molecular fragment replacement study on diaminopyrimidine and pyrrolotriazine ALK inhibitors

Over expression of anaplastic lymphoma kinase (ALK) has been found in many types of cancer, and ALK is a promising therapeutic target for the treatment of cancer. To obtain new potent inhibitors of ALK, we conducted lead optimization using 3D-QSAR modeling and molecular docking investigation of 2,4-diaminopyrimidines and 2,7-disubstituted-pyrrolo[2,1-f][1,2,4]triazine-based compounds. Three favorable 3D-QSAR models (CoMFA with q2, 0.555; r2, 0.939; CoMSIA with q2, 0.625; r2, 0.974; Topomer CoMFA with q2, 0.557; r2 0.756) have been developed to predict the biological activity of novel compounds. Topomer Search was utilized for virtual screening to obtain suitable fragments. The novel compounds generated by molecular fragment replacement (MFR) were evaluated by Topomer CoMFA prediction, Glide (docking) and further evaluated with CoMFA and CoMSIA prediction. 25 novel 2,7-disubstituted-pyrrolo[2,1-f][1,2,4]triazine derivatives as potential ALK inhibitors were finally obtained. In this paper, a combination of CoMFA, CoMSIA and Topomer CoMFA could obtain favorable 3D-QSAR models and suitable fragments for ALK inhibitors optimization. The work flow which comprised 3D-QSAR modeling, Topomer Search, MFR, molecular docking and evaluating criteria could be applied to de novo drug design and the resulted compounds initiate us to further optimize and design new potential ALK inhibitors.

A population-based evolutionary search approach to the multiple minima problem in de novo protein structure prediction

BackgroundElucidating the native structure of a protein molecule from its sequence of amino acids, a problem known as de novo structure prediction, is a long standing challenge in computational structural biology. Difficulties in silico arise due to the high dimensionality of the protein conformational space and the ruggedness of the associated energy surface. The issue of multiple minima is a particularly troublesome hallmark of energy surfaces probed with current energy functions. In contrast to the true energy surface, these surfaces are weakly-funneled and rich in comparably deep minima populated by non-native structures. For this reason, many algorithms seek to be inclusive and obtain a broad view of the low-energy regions through an ensemble of low-energy (decoy) conformations. Conformational diversity in this ensemble is key to increasing the likelihood that the native structure has been captured.MethodsWe propose an evolutionary search approach to address the multiple-minima problem in decoy sampling for de novo structure prediction. Two population-based evolutionary search algorithms are presented that follow the basic approach of treating conformations as individuals in an evolving population. Coarse graining and molecular fragment replacement are used to efficiently obtain protein-like child conformations from parents. Potential energy is used both to bias parent selection and determine which subset of parents and children will be retained in the evolving population. The effect on the decoy ensemble of sampling minima directly is measured by additionally mapping a conformation to its nearest local minimum before considering it for retainment. The resulting memetic algorithm thus evolves not just a population of conformations but a population of local minima.Results and conclusionsResults show that both algorithms are effective in terms of sampling conformations in proximity of the known native structure. The additional minimization is shown to be key to enhancing sampling capability and obtaining a diverse ensemble of decoy conformations, circumventing premature convergence to sub-optimal regions in the conformational space, and approaching the native structure with proximity that is comparable to state-of-the-art decoy sampling methods. The results are shown to be robust and valid when using two representative state-of-the-art coarse-grained energy functions.

De novo design of PLK1 inhibitors based on 2-amino aromatic heterocyclic scaffold: 3D-QSAR and molecular fragment replacement

Polo-like kinase 1 (PLK1) has emerged as an important drug target for developing novel anticancer drugs. To design compounds with enhanced inhibitory potency against PLK1, pharmacophore modelling, three-dimensional quantitative structure–activity relationship and molecular fragment replacement were performed on three classes of PLK1 inhibitors (pyrazolopyridines, isoxazolopyridines and imidazotriazines) that have analogous scaffolds. The comparative molecular field analysis (CoMFA) models were developed using the ligand-based and receptor-based pharmacophore alignments, respectively. Taking advantage of the insights gained from CoMFA study, two important points of the scaffolds were replaced with diverse molecular fragments to design new compounds. After filtered with the pharmacophore derived from BI-2536 and predicted by the CoMFA model, 11 promising compounds with high-estimated bioactivities were finally obtained. These results will not only provide meaningful insight into the relationship between PLK1 and inhibitors, but also promote the de novo design of new compounds against PLK1.

Membrane Protein Structure Determination in Membrana

The two principal components of biological membranes, the lipid bilayer and the proteins integrated within it, have coevolved for specific functions that mediate the interactions of cells with their environment. Molecular structures can provide very significant insights about protein function. In the case of membrane proteins, the physical and chemical properties of lipids and proteins are highly interdependent; therefore structure determination should include the membrane environment. Considering the membrane alongside the protein eliminates the possibility that crystal contacts or detergent molecules could distort protein structure, dynamics, and function and enables ligand binding studies to be performed in a natural setting. Solid-state NMR spectroscopy is compatible with three-dimensional structure determination of membrane proteins in phospholipid bilayer membranes under physiological conditions and has played an important role in elucidating the physical and chemical properties of biological membranes, providing key information about the structure and dynamics of the phospholipid components. Recently, developments in the recombinant expression of membrane proteins, sample preparation, pulse sequences for high-resolution spectroscopy, radio frequency probes, high-field magnets, and computational methods have enabled a number of membrane protein structures to be determined in lipid bilayer membranes. In this Account, we illustrate solid-state NMR methods with examples from two bacterial outer membrane proteins (OmpX and Ail) that form integral membrane β-barrels. The ability to measure orientation-dependent frequencies in the solid-state NMR spectra of membrane-embedded proteins provides the foundation for a powerful approach to structure determination based primarily on orientation restraints. Orientation restraints are particularly useful for NMR structural studies of membrane proteins because they provide information about both three-dimensional structure and the orientation of the protein within the membrane. When combined with dihedral angle restraints derived from analysis of isotropic chemical shifts, molecular fragment replacement, and de novo structure prediction, orientation restraints can yield high-quality three-dimensional structures with few or no distance restraints. Using complementary solid-state NMR methods based on oriented sample (OS) and magic angle spinning (MAS) approaches, one can resolve and assign multiple peaks through the use of (15)N/(13)C labeled samples and measure precise restraints to determine structures.

Rapid sampling of local minima in protein energy surface and effective reduction through a multi-objective filter.

BackgroundMany problems in protein modeling require obtaining a discrete representation of the protein conformational space as an ensemble of conformations. In ab-initio structure prediction, in particular, where the goal is to predict the native structure of a protein chain given its amino-acid sequence, the ensemble needs to satisfy energetic constraints. Given the thermodynamic hypothesis, an effective ensemble contains low-energy conformations which are similar to the native structure. The high-dimensionality of the conformational space and the ruggedness of the underlying energy surface currently make it very difficult to obtain such an ensemble. Recent studies have proposed that Basin Hopping is a promising probabilistic search framework to obtain a discrete representation of the protein energy surface in terms of local minima. Basin Hopping performs a series of structural perturbations followed by energy minimizations with the goal of hopping between nearby energy minima. This approach has been shown to be effective in obtaining conformations near the native structure for small systems. Recent work by us has extended this framework to larger systems through employment of the molecular fragment replacement technique, resulting in rapid sampling of large ensembles.MethodsThis paper investigates the algorithmic components in Basin Hopping to both understand and control their effect on the sampling of near-native minima. Realizing that such an ensemble is reduced before further refinement in full ab-initio protocols, we take an additional step and analyze the quality of the ensemble retained by ensemble reduction techniques. We propose a novel multi-objective technique based on the Pareto front to filter the ensemble of sampled local minima.Results and conclusionsWe show that controlling the magnitude of the perturbation allows directly controlling the distance between consecutively-sampled local minima and, in turn, steering the exploration towards conformations near the native structure. For the minimization step, we show that the addition of Metropolis Monte Carlo-based minimization is no more effective than a simple greedy search. Finally, we show that the size of the ensemble of sampled local minima can be effectively and efficiently reduced by a multi-objective filter to obtain a simpler representation of the probed energy surface.

Elucidating the ensemble of functionally-relevant transitions in protein systems with a robotics-inspired method

BackgroundMany proteins tune their biological function by transitioning between different functional states, effectively acting as dynamic molecular machines. Detailed structural characterization of transition trajectories is central to understanding the relationship between protein dynamics and function. Computational approaches that build on the Molecular Dynamics framework are in principle able to model transition trajectories at great detail but also at considerable computational cost. Methods that delay consideration of dynamics and focus instead on elucidating energetically-credible conformational paths connecting two functionally-relevant structures provide a complementary approach. Effective sampling-based path planning methods originating in robotics have been recently proposed to produce conformational paths. These methods largely model short peptides or address large proteins by simplifying conformational space.MethodsWe propose a robotics-inspired method that connects two given structures of a protein by sampling conformational paths. The method focuses on small- to medium-size proteins, efficiently modeling structural deformations through the use of the molecular fragment replacement technique. In particular, the method grows a tree in conformational space rooted at the start structure, steering the tree to a goal region defined around the goal structure. We investigate various bias schemes over a progress coordinate for balance between coverage of conformational space and progress towards the goal. A geometric projection layer promotes path diversity. A reactive temperature scheme allows sampling of rare paths that cross energy barriers.Results and conclusionsExperiments are conducted on small- to medium-size proteins of length up to 214 amino acids and with multiple known functionally-relevant states, some of which are more than 13Å apart of each-other. Analysis reveals that the method effectively obtains conformational paths connecting structural states that are significantly different. A detailed analysis on the depth and breadth of the tree suggests that a soft global bias over the progress coordinate enhances sampling and results in higher path diversity. The explicit geometric projection layer that biases the exploration away from over-sampled regions further increases coverage, often improving proximity to the goal by forcing the exploration to find new paths. The reactive temperature scheme is shown effective in increasing path diversity, particularly in difficult structural transitions with known high-energy barriers.

De novo design of N-(pyridin-4-ylmethyl)aniline derivatives as KDR inhibitors: 3D-QSAR, molecular fragment replacement, protein-ligand interaction fingerprint, and ADMET prediction

Vascular endothelial growth factor (VEGF) and its receptor tyrosine kinase VEGFR-2 or kinase insert domain receptor (KDR) have been identified as promising targets for novel anticancer agents. To achieve new potent inhibitors of KDR, we conducted molecular fragment replacement (MFR) studies for the understanding of 3D-QSAR modeling and the docking investigation of arylphthalazines and 2-((1H-Azol-1-yl)methyl)-N-arylbenzamides-based KDR inhibitors. Two favorable 3D-QSAR models (CoMFA with q(2), 0.671; r(2), 0.969; CoMSIA with q(2), 0.608; r(2), 0.936) have been developed to predict the biological activity of new compounds. The new molecular database generated by MFR was virtually screened using Glide (docking) and further evaluated with CoMFA prediction, protein-ligand interaction fingerprint (PLIF) and ADMET analysis. 44 N-(pyridin-4-ylmethyl)aniline derivatives as novel potential KDR inhibitors were finally obtained. In this paper, the work flow developed could be applied to de novo drug design and virtual screening potential KDR inhibitors, and use hit compounds to further optimize and design new potential KDR inhibitors.

An improved algorithm for MFR fragment assembly

A method for generating protein backbone models from backbone only NMR data is presented, which is based on molecular fragment replacement (MFR). In a first step, the PDB database is mined for homologous peptide fragments using experimental backbone-only data i.e. backbone chemical shifts (CS) and residual dipolar couplings (RDC). Second, this fragment library is refined against the experimental restraints. Finally, the fragments are assembled into a protein backbone fold using a rigid body docking algorithm using the RDCs as restraints. For improved performance, backbone nuclear Overhauser effects (NOEs) may be included at that stage. Compared to previous implementations of MFR-derived structure determination protocols this model-building algorithm offers improved stability and reliability. Furthermore, relative to CS-ROSETTA based methods, it provides faster performance and straightforward implementation with the option to easily include further types of restraints and additional energy terms.

De novo design of quinazoline derivatives as CDK2 inhibitors: 3D-QSAR, molecular fragment replacement and Volsurf predictions

Cyclin-dependent kinase 2 (CDK2) has appeared as an important drug target over the years with a multitude of therapeutic potentials. To design compounds with enhanced inhibitory potencies against CDK2, 3D-QSAR and molecular fragment replacement studies were performed on the pyrazolo[4,3-h]quinazoline derivatives, a class of potent CDK2 inhibitors. The contours of 3D-QSAR model revealed important structural features of the inhibitors related to the active site of CDK2. Based on the pyrazolo[4,3-h]quinazoline core, the different substituents at three important points were replaced with diverse molecular fragments. The compounds resulting from fragments assembly with pyrazolo[4,3-h]quinazoline core were then scored with the robust 3D-QSAR model. Furthermore, the absorption, distribution, metabolism and excretion properties of these compounds were predicted by Volsurf to eliminate inappropriate compounds. Thirty-one new potential compounds were finally obtained. These results initiated us to further optimise and design new potential inhibitors.

Structure of the mitochondrial uncoupling protein 2 determined by NMR molecular fragment replacement

Structure of the mitochondrial uncoupling protein 2 determined by NMR molecular fragment replacement

Folding of Small Proteins by Monte Carlo Simulations with Chemical Shift Restraints without the Use of Molecular Fragment Replacement or Structural Homology

It has recently been shown that protein structures can be determined from nuclear magnetic resonance (NMR) chemical shifts using a molecular fragment replacement strategy. In these approaches, structural motifs are selected from existing protein structures on the basis of chemical shift and sequence homology and assembled to generate new structures. Here, we demonstrate that it is also possible to determine structures of proteins by directly incorporating experimental NMR chemical shifts as structural restraints in conformational searches, without the use of structural homology and molecular fragment replacement. In this approach, a protein is folded from an extended conformation to its native state using a simulated annealing procedure that minimizes an energy function that combines a standard force field with a term that penalizes the differences between experimental and calculated chemical shifts. We provide an initial demonstration of this procedure by determining the structure of two small proteins, with alpha and beta folds, respectively.

Insight into Disulfide Bond Catalysis in Chlamydia from the Structure and Function of DsbH, a Novel Oxidoreductase

The Chlamydia family of human pathogens uses outer envelope proteins that are highly cross-linked by disulfide bonds but nevertheless keeps an unusually high number of unpaired cysteines in its secreted proteins. To gain insight into chlamydial disulfide bond catalysis, the structure, function, and substrate interaction of a novel periplasmic oxidoreductase, termed DsbH, were determined. The structure of DsbH, its redox potential of -269 mV, and its functional properties are similar to thioredoxin and the C-terminal domain of DsbD, i.e. characteristic of a disulfide reductase. As compared with these proteins, the two central residues of the DsbH catalytic motif (CMWC) shield the catalytic disulfide bond and are selectively perturbed by a peptide ligand. This shows that these oxidoreductase family characteristic residues are not only important in determining the redox potential of the catalytic disulfide bond but also in influencing substrate interactions. For DsbH, three functional roles are conceivable; that is, reducing intermolecular disulfides between proteins and small molecules, keeping a specific subset of exported proteins reduced, or maintaining the periplasm of Chlamydia in a generally reducing state.

Comparison of Structure and Dynamics of Micelle-bound Human α-Synuclein and Parkinson Disease Variants

Three point mutations (A30P, E46K, and A53T) as well as gene triplication genetically link the 140-residue protein alpha-synuclein (aS) to the development of Parkinson disease. Here, the structure and dynamics of micelle-bound aS(A30P) and aS(A53T) are described and compared with wild-type aS, in addition to describing the aS-micelle interaction. A53T is sensed only by directly adjacent residues and leaves the backbone structure and dynamics indistinguishable from the wild type. A30P interrupts one helix turn (Val26-Ala29) and destabilizes the preceding one. A shift in helix register following A30P disturbs the canonical succession of polar and hydrophobic residues for at least two turns. The shortened helix-N adopts a slightly higher helical content and is less bent, indicating that strain was present in the micelle-bound helix. In the vicinity of the A30P-induced perturbations, the underlying micelle environment has rearranged, but nevertheless all aS variants maintain similar interrelationships with the micelle. Moreover, aS-micelle immersion correlates well with fast and slow aS backbone dynamics, allowing a rare insight into protein-micelle interplay.

Solution structure of (gamma)S-crystallin by molecular fragment replacement NMR.

The solution structure of murine gammaS-crystallin (gammaS) has been determined by multidimensional triple resonance NMR spectroscopy, using restraints derived from two sets of dipolar couplings, recorded in different alignment media, and supplemented by a small number of NOE distance restraints. gammaS consists of two topologically similar domains, arranged with an approximate twofold symmetry, and each domain shows close structural homology to closely related (approximately 50% sequence identity) domains found in other members of the gamma-crystallin family. Each domain consists of two four-strand "Greek key" beta-sheets. Although the domains are tightly anchored to one another by the hydrophobic surfaces of the two inner Greek key motifs, the N-arm, the interdomain linker and several turn regions show unexpected flexibility and disorder in solution. This may contribute entropic stabilization to the protein in solution, but may also indicate nucleation sites for unfolding or other structural transitions. The method used for solving the gammaS structure relies on the recently introduced molecular fragment replacement method, which capitalizes on the large database of protein structures previously solved by X-ray crystallography and NMR.