Improved 3D-QSAR prediction by multiple-conformational alignment: A case study on PTP1B inhibitors

Three-dimension quantitative structure activity relationship (3D-QSAR) was one of the major statistical techniques to investigate the correlation of biological activity with structural properties of candidate molecules, and the accuracy of statistic greatly depended on molecular alignment methodology. Exhaustive conformational search and successful conformational superposition could extremely improve the predictive accuracy of QSAR modeling. In this work, we proposed a solution to optimize QSAR prediction by multiple-conformational alignment methods, with a set of 40 flexible PTP1B inhibitors as case study. Three different molecular alignment methods were used for the development of 3D-QSAR models listed as following: (1) docking-based alignment (DBA); (2) pharmacophore-based alignment (PBA) and (3) co-crystallized conformer-based alignment (CCBA). Among these three alignments, it was indicated that the CCBA was the best and the fastest strategy in 3D-QSAR development, with the square correlation coefficient (r²) and cross-validated squared correlation coefficient (q²) of comparative molecular field analysis (CoMFA) were 0.992 and 0.694; the r² and q² of comparative molecular similarity indices analysis (CoMSIA) were 0.972 and 0.603, respectively. The alignment methodologies used here not only generated a robust QSAR model with useful molecular field contour maps for designing novel PTP1B inhibitors, but also provided a solution for constructing accurate 3D-QSAR model for various disease targets. Undoubtedly, such attempt in QSAR analysis would greatly help us to understand essential structural features of inhibitors required by its target, and so as to discover more promising chemical derivatives.     

Estimation of active conformations of drugs by a new molecular superposing procedure

We have developed a new program, SUPERPOSE, to superpose two molecules based on the physicochemical properties of functional atoms within individual molecules. SUPERPOSE treats a pseudo-molecule consisting of functional atoms instead of a real molecule. Four types of physicochemical properties – hydrophobicity, presence of a hydrogen-bonding donor, presence of a hydrogen-bonding acceptor and presence of a hydrogen-bonding donor/acceptor – were supposed and a score was given to each overlap. When functional atoms with the same physicochemical properties were overlapped, points were added to the score, and when the functional atoms with different physicochemical properties were overlapped, points were subtracted. We applied SUPERPOSE to 12 pairs of 24 enzyme inhibitors and found that the best scored overlay for each inhibitor pair could successfully reproduce the superposition obtained from X-ray crystallography. Next, we applied SUPERPOSE to estimate the active conformations of the thrombin inhibitors MQPA, 4-TAPAP and NAPAP. Superpositions of conformers sampled by the high-temperature molecular dynamics calculation with respect to the three inhibitors were performed, and 13 sets of conformers having the best common overlay to the three inhibitors were selected. One among 13 sets was consistent with the superposition of the active conformations derived from the X-ray crystallography of the thrombin–inhibitor complexes.     

An automated method for predicting the positions of hydrogen-bonding atoms in binding sites

Hydrogen bonds are the most specific, and therefore predictable of the intermolecular interactions involved in ligand–protein binding. Given the structure of a molecule, it is possible to estimate the positions at which complementary hydrogen-bonding atoms could be found. Crystal-survey data are used in the design of a program, HBMAP, that generates a hydrogen-bond map for any given ligand, which contains all the feasible positions at which a complementary atom could be found. On superposition of ligands, the overlapping regions of their maps represent positions of receptor atoms to which each molecule can bind. The certainty of these positions is increased by the incorporation of a larger number and diversity of molecules. In this work, superposition is achieved using the program HBMATCH, which uses simulated annealing to generate the correspondence between points from the hydrogen-bonding maps of the two molecules. Equivalent matches are distinguished on the basis of their steric similarity. The strategy is tested on a number of ligands for which ligand–protein complexes have been solved crystallographically, which allows validation of the techniques. The receptor atom positions of thermolysin are successfully predicted when the correct superposition is obtained.     

Multiple flexible alignment with SEAL: a study of molecules acting on the colchicine binding site

An extension of the steric and electrostatic alignment alignment (SEAL) method (MultiSEAL) is described that allows the overlay of multiple molecules and conformations. The method is well-suited for the systematic study of possible alignments, also revealing information about the conformational energies associated with a given overlay. It has been tested on three examples: angiotensin II antagonists, 5-HT3 antagonists, and dopaminergic compounds. The utility of the method is further demonstrated in an analysis of molecules that putatively bind to the colchicine site of tubulin. On the basis of its overlay with colchicine, allocolchicine, 2-methoxy-5-(2',3',4'-trimethoxyphenyl)tropone, and combretastatin A-4, it appears that 2-methoxyestradiol (2-ME) is unlikely to fit the colchine site properly. The weak antimitotic activity of 2-ME may be explained by its partial fit in the site.     

QUASI: a novel method for simultaneous superposition of multiple flexible ligands and virtual screening using partial similarity

The structure of many receptors is unknown, and only information about diverse ligands binding to them is available. A new method is presented for the superposition of such ligands, derivation of putative receptor site models and utilization of the models for screening of compound databases. In order to generate a receptor model, the similarity of all ligands is optimized simultaneously taking into account conformational flexibility and also the possibility that the ligands can bind to different regions of the site and only partially overlap. Ligand similarity is defined with respect to a receptor site model serving as a common reference frame. The receptor model is dynamic and coevolves with the ligand alignment until an optimal self-consistent superposition is achieved. When ligand conformational flexibility is permitted, different superposition models are possible and consistent with the data. Clustering of the superposition solutions is used to obtain diverse models. When the models are used to screen a database of compounds, high enrichments are obtained, comparable to those obtained in docking studies.     

Inhibitors of prolyl endopeptidase: Characterization of the pharmacophoric pattern using conformational analysis and 3D-QSAR

Summary A structure-activity study has been carried out on several compounds known as inhibitors of the serine protease prolyl endopeptidase. Conformational analysis has been done using different molecular mechanics methods such as molecular dynamics, or a randomized conformational search method. The conformers obtained were classified using geometric and energetic criteria. A pattern recognition analysis was done in order to divide conformers according to families. The resulting dominant families, for all compounds investigated, showed very similar geometric features. Based on the lowest energy conformers obtained after randomized conformational analysis, a 3D-QSAR model was established using the CoMFA approach. The validity of this model was verified by prediciting correctly the activity of other molecules not used in the construction of this model.     

A fast and efficient method to generate biologically relevant conformations

Summary Mutual binding between a ligand of low molecular weight and its macromolecular receptor demands structural complementarity of both species at the recognition site. To predict binding properties of new molecules before synthesis, information about possible conformations of drug molecules at the active site is required, especially if the 3D structure of the receptor is not known. The statistical analysis of small-molecule crystal data allows one to elucidate conformational preferences of molecular fragments and accordingly to compile libraries of putative ligand conformations. A comparison of geometries adopted by corresponding fragments in ligands bound to proteins shows similar distributions in conformation space. We have developed an automatic procedure that generates different conformers of a given ligand. The entire molecule is decomposed into its individual ring and open-chain torsional fragments, each used in a variety of favorable conformations. The latter ones are produced according to the library information about conformational preferences. During this building process, an extensive energy ranking is applied. Conformers ranked as energetically favorable are subjected to an optimization in torsion angle space. During minimization, unfavorable van der Waals interactions are removed while keeping the open-chain torsion angles as close as possible to the experimentally most frequently observed values. In order to assess how well the generated conformers map conformation space, a comparison with experimental data has been performed. This comparison gives some confidence in the efficiency and completeness of this approach. For some ligands that had been structurally characterized by protein crystallography, the program was used to generate sets of some 10 to 100 conformers. Among these, geometries are found that fall convincingly close to the conformations actually adopted by these ligands at the binding site.     

Probing the conformational space available to inhibitors in the thermolysin active site using Monte Carlo/energy minimization techniques

The conformational space available to four inhibitors of the bacterial enzyme thermolysin has been searched in the enzyme binding site using a method that combines Monte Carlo type techniques with energy minimization for exploration of the conformational potential energy hypersurface. Molecular mechanics methodology using the AMBER force field was employed for computation of the molecular energetics. Solvation energies were also included in the calculations by employing a technique that estimates hydration energies based on the exposed solvent accessible surface area for each atom of the inhibitor and active site. It was found that in each case, the crystallographically observed conformation was among the low energy conformers discovered. In fact, in three of the calculations it was the lowest energy conformation. The methodology described in this article is expected to be quite useful for studies involving computer aided design and evaluation of enzyme inhibitors.     

A computational study of microsolvation effect on ethylene glycol by density functional method

This study focuses on the conformational analysis of ethylene glycol-(water)n (n=1-3) complex by using density functional theory method and the basis set 6-311++G*. Different conformers are reported and the basis set superposition error corrected total energy is -306.767 5171, -383.221 3135, and -459.694 1528 for lowest energy conformer with 1, 2, and 3 water molecules, respectively, with corresponding binding energy -7.75, -15.43, and -36.28 kcal/mol. On applying many-body analysis it has been found that relaxation energy, two-body, three-body energy have significant contribution to the binding energy for ethylene glycol-(water)3 complex whereas four-body energies are negligible. The most stable conformers of ethylene glycol-(water)n complex are the cyclic structures in which water molecules bridge between the two hydroxyl group of ethylene glycol.     

RMSD and Symmetry

A common approach for comparing the structures of biomolecules or solid bodies is to translate and rotate one structure with respect to the other to minimize the pointwise root-mean-square deviation (RMSD). We present a new, robust numerical algorithm that computes the RMSD between two molecules or all the mutual RMSDs of a list of molecules and, if desired, the corresponding rotation matrix in a minimal number of operations as compared to previous algorithms. The RMSD gradient can also be computed. We address the problem of symmetry, both in alignment (possible alternative alignments due to indistinguishable atoms) as well as geometry. In the latter case, it is possible to have degenerate superposition. A necessary condition is optimal superimposability to one's mirror image. Double (respectively, triple) degeneracy results in a one- (respectively, two)-parameter family of rotations leaving the superposition invariant. The software, frmsd , is freely available at http://www.ams.stonybrook.edu/~coutsias/codes/frmsd.tgz . © 2019 Wiley Periodicals, Inc.     

Time-efficient flexible superposition of medium-sized molecules

We present an efficient algorithm for the structural alignment of medium-sized organic molecules. The algorithm has been developed for applications in 3D QSAR and in receptor modeling. The method assumes one of the molecules, the reference ligand, to be presented in the conformation that it adopts inside the receptor pocket. The second molecule, the test ligand, is considered to be flexible, and is assumed to be given in an arbitrary low-energy conformation. Ligand flexibility is modeled by decomposing the test ligand into molecular fragments, such that ring systems are completely contained in a single fragment. Conformations of fragments and torsional angles of single bonds are taken from a small finite set, which depends on the fragment and bond, respectively. The algorithm superimposes a distinguished base fragment of the test ligand onto a suitable region of the reference ligand and then attaches the remaining fragments of the test ligand in a step-by-step fashion. During this process, a scoring function is optimized that encompasses bonding terms and terms accounting for steric overlap as well as for similarity of chemical properties of both ligands. The algorithm has been implemented in the FLEXS system. To validate the quality of the produced results, we have selected a number of examples for which the mutual superposition of two ligands is experimentally given by the comparison of the binding geometries known from the crystal structures of their corresponding protein–ligand complexes. On more than two-thirds of the test examples the algorithm produces rms deviations of the predicted versus the observed conformation of the test ligand below 1.5 Å. The run time of the algorithm on a single problem instance is a few minutes on a common-day workstation. The overall goal of this research is to drastically reduce run times, while limiting the inaccuracies of the model and the computation to a tolerable level.     

Graph-based molecular alignment (GMA)

We describe a combined 2D/3D approach for the superposition of flexible chemical structures, which is based on recent progress in the efficient identification of common subgraphs and a gradient-based torsion space optimization algorithm. The simplicity of the approach is reflected in its generality and computational efficiency: the suggested approach neither requires precalculated statistics on the conformations of the molecules nor does it make simplifying assumptions on the topology of the molecules being compared. Furthermore, graph-based molecular alignment produces alignments that are consistent with the chemistry of the molecules as well as their general structure, as it depends on both the local connectivities between atoms and the overall topology of the molecules. We validate this approach on benchmark sets taken from the literature and show that it leads to good results compared to computationally and algorithmically more involved methods. The results suggest that, for most practical purposes, graph-based molecular alignment is a viable alternative to molecular field alignment with respect to structural superposition and leads to structures of comparable quality in a fraction of the time.     

Flexible matching of test ligands to a 3D pharmacophore using a molecular superposition force field: Comparison of predicted and experimental conformations of inhibitors of three enzymes

Summary A computer procedure TFIT, which uses a molecular superposition force field to flexibly match test compounds to a 3D pharmacophore, was evaluated to find out whether it could reliably predict the bioactive conformations of flexible ligands. The program superposition force field optimizes the overlap of those atoms of the test ligand and template that are of similar chemical type, by applying an attractive force between atoms of the test ligand and template which are close together and of similar type (hydrogen bonding, charge, hydrophobicity). A procedure involving Monte Carlo torsion perturbations, followed by torsional energy minimization, is used to find conformations of the test ligand which cominimize the internal energy of the ligand and the superposition energy of ligand and template. The procedure was tested by applying it to a series of flexible ligands for which the bioactive conformation was known experimentally. The 15 molecules tested were inhibitors of thermolysin, HIV-1 protease or endothiapepsin for which X-ray structures of the bioactive conformation were available. For each enzyme, one of the molecules served as a template and the others, after being conformationally randomized, were fitted. The fitted conformation was then compared to the known binding geometry. The matching procedure was successful in predicting the bioactive conformations of many of the structures tested. Significant deviation from experimental results was found only for parts of molecules where it was readily apparent that the template did not contain sufficient information to accurately determine the bioactive conformation.     

Comparative Molecular Similarity Index Analysis (CoMSIA) to study hydrogen-bonding properties and to score combinatorial libraries

Comparative molecular field analysis has been applied to a data set of thermolysin inhibitors. Fields expressed in terms of molecular similarity indices (CoMSIA) have been used instead of the usually applied Lennard-Jones- and Coulomb-type potentials (CoMFA). Five different properties, assumed to cover the major contributions responsible for ligand binding, have been considered: steric, electrostatic, hydrophobic, and hydrogen-bond donor or acceptor properties. The statistical evaluation of the field properties by PLS analysis reveals a similar predictive potential to CoMFA. However, significantly improved and easily interpretable contour maps are obtained. The features in these maps intuitively suggest where to modify a molecular structure in terms of physicochemical properties and functional groups in order to improve its binding affinity. They can also be interpreted with respect to the known structural protein environment of thermolysin. Most of the highlighted regions in the maps are mirrored by features in the surrounding environment required for binding. Using the derived correlation model, different members of a combinatorial library designed for thermolysin inhibition have been scored for affinity. The results obtained demonstrate the prediction power of the CoMSIA method.     

Conformational features of linear and cyclic enkephalins. A computational study

A theoretical conformational study using the CICADA program package (J. Mol. Struct. (Theochem), 337 (1995) 17) was performed for two linear enkephalins, Leu-enkephalin and Met-enkephalin, and two cyclic analogues, DLFE and DPDPE. The conformational flexibilities of whole molecules and selected torsions were calculated.

The low energy conformers obtained were compared with structures obtained by spectroscopic methods. The mutual space positions of key elements for receptor recognition were analyzed. Conformations were clustered using RMS deviation computed for selected atoms. The different conformational behavior of aromatic rings in cyclic analogues of enkephalins was observed. While aromatic rings of cyclic analogues exhibit different conformational behavior, the linear enkephalins show similar behavior in these key parts.

Hydrogen bonds predicted by spectroscopic measurements were confirmed by our calculations. Also very specific conformational features, like concerted conformational movement, were analyzed.