Normal-Mode-Analysis–Monitored Energy Minimization Procedure for Generating Small–Molecule Bound Conformations

The energy minimization of a small molecule alone does not automatically stop at a local minimum of the potential energy surface of the molecule if the minimum is shallow, thus leading to folding of the molecule and consequently hampering the generation of the bound conformation of a guest in the absence of its host. This questions the practicality of virtual screening methods that use conformations at local minima of their potential energy surfaces (local minimum conformations) as potential bound conformations. Here we report a normal-mode-analysis–monitored energy minimization (NEM) procedure that generates local minimum conformations as potential bound conformations. Of 22 selected guest–host complex crystal structures with guest structures possessing up to four rotatable bonds, all complexes were reproduced, with guest mass–weighted root mean square deviations of <1.0 Å, through docking with the NEM–generated guest local minimum conformations. An analysis of the potential energies of these local minimum conformations showed that 22 (100%), 18 (82%), 16 (73%), and 12 (55%) of the 22 guest bound conformations in the crystal structures had conformational strain energies of less than or equal to 3.8, 2.0, 0.6, and 0.0 kcal/mol, respectively. These results suggest that (1) the NEM procedure can generate small–molecule bound conformations, and (2) guests adopt low-strain–energy conformations for complexation, thus supporting the virtual screening methods that use local minimum conformations

Bioactive conformational generation of small molecules: A comparative analysis between force-field and multiple empirical criteria based methods

<p>Abstract</p> <p>Background</p> <p>Conformational sampling for small molecules plays an essential role in drug discovery research pipeline. Based on multi-objective evolution algorithm (MOEA), we have developed a conformational generation method called Cyndi in the previous study. In this work, in addition to Tripos force field in the previous version, Cyndi was updated by incorporation of MMFF94 force field to assess the conformational energy more rationally. With two force fields against a larger dataset of 742 bioactive conformations of small ligands extracted from PDB, a comparative analysis was performed between pure force field based method (FFBM) and multiple empirical criteria based method (MECBM) hybrided with different force fields.</p> <p>Results</p> <p>Our analysis reveals that incorporating multiple empirical rules can significantly improve the accuracy of conformational generation. MECBM, which takes both empirical and force field criteria as the objective functions, can reproduce about 54% (within 1Å RMSD) of the bioactive conformations in the 742-molecule testset, much higher than that of pure force field method (FFBM, about 37%). On the other hand, MECBM achieved a more complete and efficient sampling of the conformational space because the average size of unique conformations ensemble per molecule is about 6 times larger than that of FFBM, while the time scale for conformational generation is nearly the same as FFBM. Furthermore, as a complementary comparison study between the methods with and without empirical biases, we also tested the performance of the three conformational generation methods in MacroModel in combination with different force fields. Compared with the methods in MacroModel, MECBM is more competitive in retrieving the bioactive conformations in light of accuracy but has much lower computational cost.</p> <p>Conclusions</p> <p>By incorporating different energy terms with several empirical criteria, the MECBM method can produce more reasonable conformational ensemble with high accuracy but approximately the same computational cost in comparison with FFBM method. Our analysis also reveals that the performance of conformational generation is irrelevant to the types of force field adopted in characterization of conformational accessibility. Moreover, post energy minimization is not necessary and may even undermine the diversity of conformational ensemble. All the results guide us to explore more empirical criteria like geometric restraints during the conformational process, which may improve the performance of conformational generation in combination with energetic accessibility, regardless of force field types adopted.</p

Biomolecular Design and Receptor-Ligand Interaction of a Potential Industrial Biocatalsyt: A Thermostable Thermolysin-Phosphoethanolamine-Ca2+ Protein Complex

Protein structures are prone to modification based on the fundamental rules of design and function. Calculations of free binding energies (DG) of chemical molecules (effectors) that bind to proteins are important in molecular signaling processes and catalytic mechanisms of certain key enzymes. These calculations can be obtained via in silico and theoretical approaches. A series of 48 pockets were identified in thermolysin (KEI) and the four biggest pockets were selected for their suitable sites for modification. Application of molecular docking on phosphoethanolamine (PSE) and 1,10-phenanthroline (PHN) that act as intermediate ligands in the designated protein complex showed favorable final docked energy at different pockets (-8.49 to -4.80 kcal/mol). Analysis on docking of a divalent metal ion (Ca2+) to ligand (PSE) produced a final docked energy of -4.15 kcal/mol within acceptable distance (1.5 Å £ M ≤ 3.0 Å). It was found that the thermolysin-phosphoetanolamine-Ca2+ represented the putative protein complex of semisynthetic metalloprotease. Combinatorial modeling methods were applied in order to determine the best metalloenzyme complex. The identification of the potential protein pocket was conducted using CASTp. Selected ligands and metal ions were docked into each pocket using AutoDock 3.05. Analyses on their docking energy, non-covalent interaction as well as their geometry were conducted in order to determine the best metalloenzyme complex. This complex displayed the lowest docking energy with the additional Ca2+ suitably docked. It was hypothesized that metal ions can add new functionality to proteins and catalyze some of the challenging biological reactions, particularly in the pharmaceutical and fine chemicals industries

Preference of Small Molecules for Local Minimum Conformations when Binding to Proteins

It is well known that small molecules (ligands) do not necessarily adopt their lowest potential energy conformations when binding to proteins. Analyses of protein-bound ligand crystal structures have reportedly shown that many of them do not even adopt the conformations at local minima of their potential energy surfaces (local minimum conformations). The results of these analyses raise a concern regarding the validity of virtual screening methods that use ligands in local minimum conformations. Here we report a normal-mode-analysis (NMA) study of 100 crystal structures of protein-bound ligands. Our data show that the energy minimization of a ligand alone does not automatically stop at a local minimum conformation if the minimum of the potential energy surface is shallow, thus leading to the folding of the ligand. Furthermore, our data show that all 100 ligand conformations in their protein-bound ligand crystal structures are nearly identical to their local minimum conformations obtained from NMA-monitored energy minimization, suggesting that ligands prefer to adopt local minimum conformations when binding to proteins. These results both support virtual screening methods that use ligands in local minimum conformations and caution about possible adverse effect of excessive energy minimization when generating a database of ligand conformations for virtual screening

Exploring the Conformational Landscape of Bioactive Small Molecules

By using a combination of classical Hamiltonian replica exchange with high-level quantum mechanical calculations on more than one hundred drug-like molecules, we explored here the energy cost associated with binding of drug-like molecules to target macromolecules. We found that, in general, the drug-like molecules present bound to proteins in the Protein Data Bank (PDB) can access easily the bioactive conformation and in fact for 73% of the studied molecules the bioactiveconformation is within 3kBT from the most-stable conformation in solution as determined by DFT/SCRF calculations. Cases with large differences between the most-stable and the bioactive conformations appear in ligands recognized by ionic contacts, or very large structures establishing many favorable interactions with the protein. There are also a few cases where we observed a non-negligible uncertainty related to the experimental structure deposited in PDB. Remarkably, the rough automatic force field used here provides reasonable estimates of the conformational ensemble of drugs in solution. The outlined protocol can be used to better estimate the cost of adopting the bioactive conformation

Promising Tools in Prostate Cancer Research:Selective Non-Steroidal Cytochrome P450 17A1 Inhibitors

Cytochrome P450 17A1 (CYP17A1) is an important target in the treatment of prostate cancer because it produces androgens required for tumour growth. The FDA has approved only one CYP17A1 inhibitor, abiraterone, which contains a steroidal scaffold similar to the endogenous CYP17A1 substrates. Abiraterone is structurally similar to the substrates of other cytochrome P450 enzymes involved in steroidogenesis, and interference can pose a liability in terms of side effects. Using non-steroidal scaffolds is expected to enable the design of compounds that interact more selectively with CYP17A1. Therefore, we combined a structure-based virtual screening approach with density functional theory (DFT) calculations to suggest non-steroidal compounds selective for CYP17A1. In vitro assays demonstrated that two such compounds selectively inhibited CYP17A1 17α-hydroxylase and 17,20-lyase activities with IC(50) values in the nanomolar range, without affinity for the major drug-metabolizing CYP2D6 and CYP3A4 enzymes and CYP21A2, with the latter result confirmed in human H295R cells

The good, the bad and the twisted: a survey of ligand geometry in protein crystal structures

The protein databank now contains the structures of over 11,000 ligands bound to proteins. These structures are invaluable in applied areas such as structure-based drug design, but are also the substrate for understanding the energetics of intermolecular interactions with proteins. Despite their obvious importance, the careful analysis of ligands bound to protein structures lags behind the analysis of the protein structures themselves. We present an analysis of the geometry of ligands bound to proteins and highlight the role of small molecule crystal structures in enabling molecular modellers to critically evaluate a ligand model’s quality and investigate protein-induced strain

A Unified Model of the GABA(A) Receptor Comprising Agonist and Benzodiazepine Binding Sites

We present a full-length α(1)β(2)γ(2) GABA receptor model optimized for agonists and benzodiazepine (BZD) allosteric modulators. We propose binding hypotheses for the agonists GABA, muscimol and THIP and for the allosteric modulator diazepam (DZP). The receptor model is primarily based on the glutamate-gated chloride channel (GluCl) from C. elegans and includes additional structural information from the prokaryotic ligand-gated ion channel ELIC in a few regions. Available mutational data of the binding sites are well explained by the model and the proposed ligand binding poses. We suggest a GABA binding mode similar to the binding mode of glutamate in the GluCl X-ray structure. Key interactions are predicted with residues α(1)R66, β(2)T202, α(1)T129, β(2)E155, β(2)Y205 and the backbone of β(2)S156. Muscimol is predicted to bind similarly, however, with minor differences rationalized with quantum mechanical energy calculations. Muscimol key interactions are predicted to be α(1)R66, β(2)T202, α(1)T129, β(2)E155, β(2)Y205 and β(2)F200. Furthermore, we argue that a water molecule could mediate further interactions between muscimol and the backbone of β(2)S156 and β(2)Y157. DZP is predicted to bind with interactions comparable to those of the agonists in the orthosteric site. The carbonyl group of DZP is predicted to interact with two threonines α(1)T206 and γ(2)T142, similar to the acidic moiety of GABA. The chlorine atom of DZP is placed near the important α(1)H101 and the N-methyl group near α(1)Y159, α(1)T206, and α(1)Y209. We present a binding mode of DZP in which the pending phenyl moiety of DZP is buried in the binding pocket and thus shielded from solvent exposure. Our full length GABA(A) receptor is made available as Model S1

Ligand-based drug design : I. conformational studies of GBR 12909 analogs as cocaine antagonists; II. 3d-QSAR studies of salvinorin a analogs as kappa opioid agonists

Ligand-based drug design (LBDD) techniques are applied when the structure of the receptor is unknown but when a series of compounds or ligands have been identified that show the biological activity of the interest. Generally, availability of a series of compounds with high activity, with no activity, and also with a range of intermediate activities for the desired biological target is required. It is common that structures of membrane-bound proteins (for example, monoamine transporter proteins and opioid receptor proteins) are unknown as these proteins are notoriously difficult to crystallize. In Part I of this study, analogs of the flexible dopamine reuptake inhibitor, GBR 12909, may have potential usefulness in the treatment of cocaine abuse. As a first step in the 3D-QSAR modeling of the dopamine transporter (DAT)/serotonin transporter (SERT) selectivity of these compounds, conformational analysis of a piperazine and related piperidine analog of GBR12909 is performed. These analogs have eight rotatable bonds and are somewhat easier to deal with computationally than the parent compound. Ensembles of conformers consisting of local minima on the potential energy surface of the molecule were generated in the vacuum phase and implicit solvent (also known as continuum solvent) by random search conformational analysis using the molecular mechanics methods and the Tripos and MMFF94 force fields. These conformer populations were classified by relative energy, molecular shape, and their behavior in 2D torsional angle space in order to evaluate their sensitivity to the choice of charges and force field. Some differences were noted in the conformer populations due to differences in the treatment of the tertiary amine nitrogen and ether oxygen atom types by the force fields. In Part II of this study, 3D-QSAR studies of salvinorin A analogs as kappa opioid (K) receptor agonists were performed. Salvinorin A is a naturally-occurring diterpene from the plant Salvia divinorum which activates the kappa opioid receptor (KOR) selectively and potently. It is the only known natural non-nitrogenous agent active at the human KOR. Salvinorin A may represent a novel lead compound with possible potential in the treatment of addiction and pain. The primary aim of the current study was to develop Comparative Molecular Field Analysis (CoMFA) models to clarify the correlation between the molecular features of the 2-position analogs of salvinorin A and their KOR binding affinity. The final, stable CoMFA model has predictivity given by q2 of 0.62 and fit given by r2 of 0.86. The steric and electrostatic contributions were 47% and 53%, respectively. The CoMFA contour map indicated that the presence of a negative environment and steric region near the 2-position would lead to improved binding affinity at the KOR. Novel salvinorin A analogs with improved binding affinity were predicted based on the stable and predictive CoMFA model. Novel analogs were synthesized by Dr. Thomas Prisinzano of the University of Iowa and preliminary biological results are available from the Rothman laboratory at the National Institute on Drug Abuse. These novel analogs appear to be KOR selective