Induced Fit Docking Approach Research Articles

A Robust Induced Fit Docking Approach with the Combination of the Hybrid All-Atom/United-Atom/Coarse-Grained Model and Simulated Annealing.

Molecular docking remains an indispensable tool in computational biology and structure-based drug discovery. However, the correct prediction of binding poses remains a major challenge for molecular docking, especially for target proteins where a substrate binding induces significant reorganization of the active site. Here, we introduce an Induced Fit Docking (IFD) approach named AA/UA/CG-SA-IFD, which combines a hybrid All-Atom/United-Atom/Coarse-Grained model with Simulated Annealing. In this approach, the core region is represented by the All-Atom(AA) model, while the protein environment beyond the core region and the solvent are treated with either the United-Atom (UA) or the Coarse-Grained (CG) model. By combining the Elastic Network Model (ENM) for the CG region, the hybrid model ensures a reasonable description of ligand binding and the environmental effects of the protein, facilitating highly efficient and reliable sampling of ligand binding through Simulated Annealing (SA) at a high temperature. Upon validation with two testing sets, the AA/UA/CG-SA-IFD approach demonstrates remarkable accuracy and efficiency in induced fit docking, even for challenging cases where the docked poses significantly deviate from crystal structures.

Virtual screening and biological evaluation to identify pharmaceuticals potentially causing hypertension and hypokalemia by inhibiting steroid 11β-hydroxylase

Several drugs were found after their market approval to unexpectedly inhibit adrenal 11β-hydroxylase (CYP11B1)-dependent cortisol synthesis. Known side-effects of CYP11B1 inhibition include hypertension and hypokalemia, due to a feedback activation of adrenal steroidogenesis, leading to supraphysiological concentrations of 11-deoxycortisol and 11-deoxycorticosterone that can activate the mineralocorticoid receptor. This results in potassium excretion and sodium and water retention, ultimately causing hypertension. With the risk known but usually not addressed in preclinical evaluation, this study aimed to identify drugs and drug candidates inhibiting CYP11B1. Two conceptually different virtual screening methods were combined, a pharmacophore based and an induced fit docking approach. Cell-free and cell-based CYP11B1 activity measurements revealed several inhibitors with IC50 values in the nanomolar range. Inhibitors include retinoic acid metabolism blocking agents (RAMBAs), azole antifungals, α2-adrenoceptor ligands, and a farnesyltransferase inhibitor. The active compounds share a nitrogen atom embedded in an aromatic ring system. Structure activity analysis identified the free electron pair of the nitrogen atom as a prerequisite for the drug-enzyme interaction, with its pKa value as an indicator of inhibitory potency. Another important parameter is drug lipophilicity, exemplified by etomidate. Changing its ethyl ester moiety to a more hydrophilic carboxylic acid group dramatically decreased the inhibitory potential, most likely due to less efficient cellular uptake. The presented work successfully combined different in silico and in vitro methods to identify several previously unknown CYP11B1 inhibitors. This workflow facilitates the identification of compounds that inhibit CYP11B1 and therefore pose a risk for inducing hypertension and hypokalemia.

Elucidation of partial activation of cannabinoid receptor type 2 and identification of potential partial agonists: Molecular dynamics simulation and structure-based virtual screening

Cannabinoid receptor type 2 (CB2R) is a member of the class A G protein-coupled receptor (GPCRs) family and a component of the endocannabinoid system that is modulated by the psychoactive chemical from Cannabis sativa, partial agonist Δ9-tetrahydrocannabinol (Δ9-THC). Selective activation of CB2R allows for the treatment of inflammatory and immune-related conditions without the psychotropic effects of CB1R. While CB2R-selective agonists are available, CB2R partial agonists are scarce. Hence, the pharmacological difference between CB2R full agonists and partial agonists remains to be deciphered, prompting the search for novel partial agonists. Here, using an induced-fit docking approach, we built a partial agonist Δ9-THC bound CB2R system from the inactive CB2R structure (PDB ID: 5ZTY) and performed microsecond molecular dynamics (MD) simulations. The simulations reveal an upward shift of the “toggle switch” W6.48(258) and minor outward movement of the transmembrane helix 6 (TM6). Dynamic network model identifies a possible communication path between the ligand and the toggle switch” W6.48(258). Furthermore, to identify potential CB2R partial agonists, we conducted structure-based virtual screening of ZINC15 “Druglike” library containing 17,900742 compounds against 3 conformations derived from MD simulation of CB2R complexed with partial agonist Δ9-THC using Glide virtual screening protocol comprising various filters with increasing accuracy. Nine diverse compounds predicted to have high MM-GBSA binding energy scores and good ADMET properties (including high gastrointestinal absorption and low toxicity) are proposed as potential CB2R partial agonists.

Molecular simulation studies to reveal the binding mechanisms of shikonin derivatives inhibiting VEGFR-2 kinase

Traditional vascular endothelial growth factor receptor 2 (VEGFR-2) inhibitors can manage angiogenesis; however, severe toxicity and resistance limit their long-term applications in clinical therapy. Shikonin (SHK) and its derivatives could be promising to inhibit the VEGFR-2 mediated angiogenesis, as they are reported to bind in the catalytic kinase domain with low affinity. However, the detailed molecular insights and binding dynamics of these natural inhibitors are unknown, which is crucial for potential SHK based lead design. Therefore, the present study employed molecular modeling and simulations techniques to get insight into the binding behaviors of SHK and its two derivates, β-hydroxyisovalerylshikonin (β-HIVS) and acetylshikonin (ACS). Here the intermolecular interactions between protein and ligands were studied by induced fit docking approach, which were further evaluated by treating QM/MM (quantum mechanics/molecular mechanics) and molecular dynamics (MD) simulation. The result showed that the naphthazarin ring of the SHK derivates is vital for strong binding to the catalytic domain; however, the binding stability can be modulated by the side chain modification. Because of having electrostatic potential, this ring makes essential interactions with the DFG (Asp1046 and Phe1047) motif and also allows interacting with the allosteric binding site. Taken together, the studies will advance our knowledge and scope for the development of new selective VEGFR-2 inhibitors based on SHK and its analogs.

Structure based pharmacophore modelling approach for the design of azaindole derivatives as DprE1 inhibitors for tuberculosis

Cell wall of mycobacterium acts as a primary interface which helps in the regulation of important functions and also aids to pathogenicity and virulence of the organism, making it a crucial target for drug discovery. Decaprenylphosphoryl-d-ribose 2′-epimerase (DprE), is important for the growth and survival of Mycobacterium tuberculosis. DprE1 is a donor of arabinose sugars which helps in the formation of cell wall components-lipoarabinomannan and arabinogalactan through Decaprenyl-phosphoryl d-arabinose (DPA) pathway. In our study, we have chosen Azaindole derivatives as DprE1 inhibitors which possess non-covalent property. TBA7371 (azaindole derivative, non-covalent inhibitor) is currently in first phase of clinical trials as DprE1 inhibitor. Azaindoles have been found to be equally potent against drug-sensitive and isoniazid/rifampin-resistant strains. Hence, azaindoles are an attractive class for further optimization as potential DprE1 inhibitors for TB. Structure-based pharmacophore model was generated to investigate the compounds with similar molecular features. Compounds having a good fitness score and pharmacophoric features were compared with the molecules in clinical trial and were proceeded for molecular docking studies to identify the binding affinity of the compounds with target protein DprE1. Energy based calculations using Prime MM-GBSA of Schrodinger was further executed to examine free binding energy of the ligands. The prediction of pharmacokinetic parameters (ADME) plays an important role to identify safe and potent molecules which may further have potential to become drug candidates. Induced-fit docking approach and Molecular Dynamics integrated with Prime MM-GBSA calculations of both hit compounds has further confirmed the binding affinity and stability. All the results obtained from our study were interpreted and compared with DprE1 inhibitor in clinical trials. Study identified ZINC000170252277 as a potential hit compound for further biological evaluation as DprE1 inhibitor.

Peramivir binding affinity with influenza A neuraminidase and research on its mutations using an induced-fit docking approach

ABSTRACTInfluenza A virus (IAV) has caused epidemic infections worldwide, with many strains resistant to inhibitors of a surface protein, neuraminidase (NA), due to point mutations on its structure. A novel NA inhibitor named peramivir was recently approved, but no exhaustive computational research regarding its binding affinity with wild-type and mutant NA has been conducted. In this study, a thorough investigation of IAV-NA PDB entries of 9 subtypes is described, providing a list of residues constituting the protein-ligand binding sites. The results of induced-fit docking approach point out key residues of wild-type NA participating in hydrogen bonds and/or ionic interactions with peramivir, among which Arg 368 is responsible for a peramivir-NA ionic interaction. Mutations on this residue greatly reduced the binding affinity of peramivir with NA, with 3 mutations R378Q, R378K and R378L (NA6) capable of deteriorating the docking performance of peramivir by over 50%. 200 compounds from 6-scaffolds were docked into these 3 mutant versions, revealing 18 compounds giving the most promising results. Among them, CMC-2012-7-1527-56 (benzoic acid scaffold, IC50 = 32 nM in inhibitory assays with IAV) is deemed the most potential inhibitor of mutant NA resisting both peramivir and zanamivir, and should be further investigated.

Adaptive BP-Dock: An Induced Fit Docking Approach for Full Receptor Flexibility.

We present an induced fit docking approach called Adaptive BP-Dock that integrates perturbation response scanning (PRS) with the flexible docking protocol of RosettaLigand in an adaptive manner. We first perturb the binding pocket residues of a receptor and obtain a new conformation based on the residue response fluctuation profile using PRS. Next, we dock a ligand to this new conformation by RosettaLigand, where we repeat these steps for several iterations. We test this approach on several protein test sets including difficult unbound docking cases such as HIV-1 reverse transcriptase and HIV-1 protease. Adaptive BP-Dock results show better correlation with experimental binding affinities compared to other docking protocols. Overall, the results imply that Adaptive BP-Dock can easily capture binding induced conformational changes by simultaneous sampling of protein and ligand conformations. This can provide faster and efficient docking of novel targets for rational drug design.

Positively Charged Nitrogen is Not Indispensable Requirement for Binding of Nitrogenous κ-Opioid Agonists: Insights from Docking Studies

Induced fit docking approach was utilized to decipher the binding mode of the recently reported dibenz[b,f]1,5- oxazocine derivative having activity towards κ -Opioid receptor. The result of docking to newly resolved crystallographic structure of κ -Opioid receptor established the important interactions as two hydrogen bonds, a π-π interaction, and two hydrophobic interactions. Based on the study it is inferred that protonated nitrogen is not always essential for binding of non-peptidic nitrogen containing opioids to κ -Opioid receptor. Also, docking was performed using well-known kappa agonist pentazocine to prove different binding requirements of the dibenzo compound. A pharmacophoric model has been developed based on the previously known nitrogen containing κ -Opioid receptor agonists and the new dibenzo compound to determine the minimal 3D features, required for κ -Opioid agonist activity. To our knowledge, this is the first report of a binding mode analysis study for non-protonated nitrogen containing κ-Opioid receptor agonist. Keywords: Agonist, Docking, Kappa opioid receptor, Non-peptidic, Opioids, Protonated nitrogen.

Abstract PR1: In silico designed covalent peptidomimetic inhibitors (KPT-SINE) of CRM1 modulate tumor suppressor protein nuclear export and induce apoptosis in cancer cells

Abstract Chromosome region maintenance 1/Exportin-1 (CRM1) is a key nuclear export protein whose inhibition leads to nuclear accumulation of tumor suppressor (TSP) and growth regulatory proteins (GRP). Through CRM1 inhibition, nuclear localization of these proteins restores cell cycle checkpoints and genome surveying functions culminating in apoptosis of tumor cells. Conversely, CRM1 inhibition of normal cells induces reversible cell cycle arrest. We developed a structural model of CRM1 suited for binding diverse small molecules and used it to guide the discovery and development of KPT-SINE (selective inhibitors of nuclear export). The model predicted that a switching motion of Met545 and Met583 in CRM1 was required for inhibitor accommodation. We found that published CRM1 inhibitors display efficient mimicry of cargo Nuclear Export Signals (NES) and a thiol reactive warhead proximal to Cys528 in CRM1. This was further confirmed by Yuh Min Chook who solved the X-ray structures of CRM1. In silico screening yielded 402 hits (from a library of ˜250,000 drug-like compounds) with 19 molecules active in vitro (IC50<30μM) and guided the optimization of KPT-SINE. Lead KPT-SINE irreversibly bound and inhibited CRM1 nuclear export and were cytotoxic to a broad range of tumor cells and xenografts. Through comparisons of molecular and cellular markers in both cancer and normal cells we concluded that KPT-SINE treatment ultimately induced cancer cell death. Methods: CRM1 Model: The CRM1 model was developed using the novel consensus Induced Fit Docking approach (cIFD). In vitro/vivo evaluation: Compounds were tested in a cell-based microscopy assay to confirm CRM1-mediated nuclear export inhibition. Cells transfected with mutant CRM1-Cys528Ser were treated with KPT-SINE in order to determine covalent binding to Cys528. Cytotoxic IC50s of KPT-SINE were determined on a panel of cancer cell lines. Multiple KPT-SINE derivatives were tested for: 1) Nuclear localization of TSPs, 2) Effects on cell cycle and viability, 3) Effects on TSP protein expression, and 4) Mouse xenograft model efficacy. Results: KPT-SINE, potent inhibitors in the cell-based microscopy assay (EC50=20-130nM), were robust inhibitors of cancer cell proliferation and inducers of apoptosis. KPT-SINE inhibition of CRM1 started within 30 minutes and reached a maximum in 8 hrs. Additionally, KPT-SINE effects were blocked by transient transfection of mutant CRM1-Cys528Ser, supporting the role of Cys528. We also identified nuclear accumulation of p53, FOXO1a, FOXO3a, APC, IκB, p27, PP2Aα, and p21, which was followed by cell cycle arrest and death of cancer cells while normal cells undergo a reversible block. Both solid (MDA-MB-468) and hematological (Z-138) mouse xenografts treated with KPT-SINE at 25 mg/kg QoDx3 PO weekly for 4 weeks inhibited tumor growth by more than 70%. Immunohistochemical analysis of the tumor molecular markers from KPT-SINE treated animals exhibited nuclear localization of TSPs, a decrease in proliferation (Ki-67), and an increase in apoptosis (TUNEL). Conclusions: We described the correlative effects of KPT-SINE from the accumulation of nuclear TSPs at the molecular level through to potent in vivo efficacy in xenograft models. KPT-SINE, which were discovered and optimized using a structure-based approach, are due for Phase I clinical trials Mid-2012. This proffered talk is also presented as Poster A2. Citation Format: William T. Senapedis, Jr., Erkan Baloglu, Doriana Froim, Dilara McCauley, Yuh Min Chook, Michael Kauffman, Sharon Shacham, Yosef Landesman, Ori Kalid, Sharon Shechter, Jean Richard St Martin, Trinayan Kashyap, Boris Klebanov, Louis Plamondon, Vincent Sandanayaka. In silico designed covalent peptidomimetic inhibitors (KPT-SINE) of CRM1 modulate tumor suppressor protein nuclear export and induce apoptosis in cancer cells [abstract]. In: Proceedings of the AACR Special Conference on Chemical Systems Biology: Assembling and Interrogating Computational Models of the Cancer Cell by Chemical Perturbations; 2012 Jun 27-30; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2012;72(13 Suppl):Abstract nr PR1.