A mechanistic approach to explore novel HDAC1 inhibitor using pharmacophore modeling, 3D- QSAR analysis,molecular docking,density functional and molecular dynamics simulation study

Deregulated epigenetic activity of Histone deacetylase 1 (HDAC1) in tumor development and carcinogenesis pronounces it as promising therapeutic target for cancer treatment. HDAC1 has recently captured the attention of researchers owing to its decisive role in multiple types of cancer. In the present study a multistep framework combining ligand based 3D-QSAR, molecular docking and Molecular Dynamics (MD) simulation studies were performed to explore potential compound with good HDAC1 binding affinity. Four different pharmacophore hypotheses Hypo1 (AADR), Hypo2 (AAAH), Hypo3 (AAAR) and Hypo4 (ADDR) were obtained. The hypothesis Hypo1 (AADR) with two hydrogen bond acceptors (A), one hydrogen bond donor (D) and one aromatics ring (R) was selected to build 3D-QSAR model on the basis of statistical parameter. The pharmacophore hypothesis produced a statistically significant QSAR model, with co-efficient of correlation r² = 0.82 and cross validation correlation co-efficient q² = 0.70. External validation result displays high predictive power with r² (o) value of 0.88 and r² (m) value of 0.58 to carry out further in silico studies. Virtual screening result shows ZINC70450932 as the most promising lead where HDAC1 interacts with residues Asp99, His178, Tyr204, Phe205 and Leu271 forming seven hydrogen bonds. A high docking score (−11.17 kcal/mol) and lower docking energy −37.84 kcal/mol) displays the binding efficiency of the ligand. Binding free energy calculation was done using MM/GBSA to access affinity of ligands towards protein. Density Functional Theory was employed to explore electronic features of the ligands describing intramolcular charge transfer reaction. Molecular dynamics simulation studies at 50 ns display metal ion (Zn)-ligand interaction which is vital to inhibit the enzymatic activity of the protein.     

Identification of p38α MAP kinase inhibitors by pharmacophore based virtual screening

The p38α mitogen-activated protein (MAP) kinase plays a vital role in treating many inflammatory diseases. In the present study, a combined ligand and structure based pharmacophore model was developed to identify potential DFG-in selective p38 MAP kinase inhibitors. Conformations of co-crystallised inhibitors were used in the development and validation of ligand and structure based pharmacophore modeling approached. The validated pharmacophore was utilized in database screening to identify potential hits. After Lipinski's rule of five filter and molecular docking analysis, nineteen hits were purchased and selected for in vitro analysis. The virtual hits exhibited promising activity against tumor necrosis factor-α (TNF-α) with 23–98% inhibition at 10 μM concentration. Out of these seven compounds has shown potent inhibitory activity against p38 MAP kinase with IC₅₀ values ranging from 12.97 to 223.5 nM. In addition, the toxicity study against HepG2 cells was also carried out to confirm the safety profile of identified virtual hits.     

Discovery of potent inhibitor for matrix metalloproteinase-9 by pharmacophore based modeling and dynamics simulation studies

Matrix metalloproteinase-9 (MMP-9) is an attractive target for anticancer therapy. In the present study ligand based pharmacophore modeling was performed to elucidate the structural elements for a diverse class of MMP-9 inhibitors. The pharmacophore model was validated through Güner-Henry (GH) scoring method. The final pharmacophore model consisted of three hydrogen bond acceptors (HBA), and two ring aromatic regions (RA). This model was utilized to screen the natural compound database to seek novel compounds as MMP-9 inhibitors. The identified hits were validated using molecular docking and molecular dynamics simulation studies. Finally, one compound named Hinokiflavone from Juniperus communis had high binding free energy of −26.54 kJ/mol compared with the known inhibitors of MMP-9. Cytotoxicity for hinokiflavone was evaluated by MTT assay. Inhibition of MMP-9 in the presence of hinokiflavone was detected by gelatin zymography and gelatinolytic inhibition assay. Results revealed that the natural compounds derived based on the developed pharmacophore model would be useful for further design and development of MMP-9 inhibitors.     

Identification of novel PAD4 inhibitors based on a pharmacophore model derived from transition state coordinates

1.4 Protein arginine deiminases 4 (PAD4) is an attractive target for the development of novel and selective inhibitors of Rheumatoid Arthritis (RA). F-amidine is known as mechanism-based inhibitor targeting PAD4 and used as inactivators by covalently modifying the active site Cys645. To identify novel structural inhibitors of PAD4, we investigated the flexibility of protein on basis of the transition state geometry of PAD4 inhibited by F-amidine from our previous QM/MM calculation. And a pharmacophore model was generated containing four features (ADHH) using five representative structures from molecular dynamic (MD) simulation on basis of the transition state geometry of PAD4 inhibited by F-amidine. We performed virtual screening using the pharmacophore model and molecular docking methods, resulting in the discovery of two molecules with K_D (dissociation equilibrium constant) values of 112 μM and 218 μΜ against PAD4 through Surface Plasmon Resonance (SPR) experiments. These two molecules could potentially serve as PAD4 inhibitors.     

In silico and in vitro screening to identify structurally diverse non-azole CYP51 inhibitors as potent antifungal agent

The problem of resistance to azole class of antifungals is a serious cause of concern to the medical fraternity and thus there is an urgent need to identify non-azole scaffolds with high affinity for lanosterol 14α-demethylase (CYP51). In view of this we have attempted to identify novel non-azole CYP51 inhibitors through the application of pharmacophore based virtual screening and in vitro evaluation. A rigorously validated pharmacophore model comprising of 2 hydrogen bond acceptor and 2 hydrophobic features has been developed and used to mine NCI database. Out of 265 retrieved hits, NSC 1215 and 1520 have been chosen on the basis of Lipinski’s rule of five, fit and estimated values. Both the hits were docked into the active site of CYP51. In view of high fit value and CDocker score, NSC 1215 and 1520 have been subjected to in vitro microbiological assay. The result reveals that NSC 1215 and 1520 are active against Candida albicans, Candida parapsilosis, Candida tropicalis, and Aspergillus niger. In addition to this the absorption characteristics of both the hits have also been determined using the rat sac technique and permeation in order of NSC 1520 > NSC 1215 has been observed.     

Consensus scoring model for the molecular docking study of mTOR kinase inhibitor

The discovery of mammalian target of rapamycin (mTOR) kinase inhibitors has always been a research hotspot of antitumor drugs. Consensus scoring used in the docking study of mTOR kinase inhibitors usually improves hit rate of virtual screening. Herein, we attempt to build a series of consensus scoring models based on a set of the common scoring functions. In this paper, twenty-five kinds of mTOR inhibitors (16 clinical candidate compounds and 9 promising preclinical compounds) are carefully collected, and selected for the molecular docking study used by the Glide docking programs within the standard precise (SP) mode. The predicted poses of these ligands are saved, and revaluated by twenty-six available scoring functions, respectively. Subsequently, consensus scoring models are trained based on the obtained rescoring results by the partial least squares (PLS) method, and validated by Leave-one-out (LOO) method. In addition, three kinds of ligand efficiency indices (BEI, SEI, and LLE) instead of pIC₅₀ as the activity could greatly improve the statistical quality of build models. Two best calculated models 10 and 22 using the same BEI indice have following statistical parameters, respectively: for model 10, training set R² = 0.767, Q² = 0.647, RMSE = 0.024, and for test set R² = 0.932, RMSE = 0.026; for model 22, raining set R² = 0.790, Q² = 0.627, RMSE = 0.023, and for test set R² = 0.955, RMSE = 0.020. These two consensus scoring model would be used for the docking virtual screening of novel mTOR inhibitors.     

3D-QSAR analysis of TRPV1 inhibitors reveals a pharmacophore applicable to diverse scaffolds and clinical candidates

TRPV1 (Transient Receptor Potential Vanilloid Type 1) receptor, a member of Transient Receptor Potential Vanilloid subfamily of ion channels, occurs in the peripheral and central nervous system, and plays a key role in transmission of pain. Consequently, this has been the target for discovery of several pain relieving agents which have undergone clinical trials. Though several TRPV1 antagonists have progressed to become clinical candidates, many are known to cause temperature elevation in humans, halting their further advancement, and signifying the need for new chemotypes. Different chemical classes of TRPV1 antagonists share three important features: an amide or an isostere flanked by an aromatic (or fused aromatic) ring with polar substitutions on one side, and a hydrophobic group on the other. Recent work identified new series of compounds with these and additional features, leading to improvement of properties, and development of clinical candidates. Herein, we describe a 3D-QSAR model (n = 62; R² = 0.9 and Q² = 0.75) developed from the piperazinyl-aryl series of compounds and a novel 5-point pharmacophore model is shown to fit several diverse scaffolds, six clinical candidates, five pre-clinical candidates and three lead compounds. The pharmacophore model can aid in finding new chemotypes as starting points that can be developed further.     

Identification of adenine nucleotide translocase 4 inhibitors by molecular docking

The protein adenine nucleotide translocase (ANT) is localized in the mitochondrial inner membrane and plays an essential role in transporting ADP into the mitochondrial matrix and ATP out from the matrix for cell utilization. In mammals there are four paralogous ANT genes, of which ANT4 is exclusively expressed in meiotic germ cells. Since ANT4 has been shown essential for spermatogenesis and male fertility in mice, inhibition of ANT4 appears to be a reasonable target for male contraceptive development. Further, in contrast to ANT1, ANT2 and ANT3 that are highly homologous to each other, ANT4 has a distinguishable amino acid sequence, which serves as a basis to develop a selective ANT4 inhibitor. In this study, we aimed to identify candidate compounds that can selectively inhibit ANT4 activity over the other ANTs. We used a structure-based method in which ANT4 was modeled then utilized as the basis for selection of compounds that interact with sites unique to ANT4. A large chemical library (>100,000 small molecules) was screened by molecular docking and effects of these compounds on ADP/ATP exchange through ANT4 were examined using yeast mitochondria expressing human ANT4. Through this, we identified one particular candidate compound, [2,2′-methanediylbis(4-nitrophenol)], which inhibits ANT4 activity with a lower IC₅₀ than the other ANTs (5.8 μM, 4.1 μM, 5.1 μM and 1.4 μM for ANT1, 2, 3 and 4, respectively). This newly identified active lead compound and its chemical structure are expected to provide new opportunities to optimize selective ANT4 inhibitors for contraceptive purposes.     

Pharmacophore modeling,virtual screening,docking and in silico ADMET analysis of protein kinase B (PKB β) inhibitors

Protein kinase B (PKB) is a key mediator of proliferation and survival pathways that are critical for cancer growth. Therefore, inhibitors of PKB are useful agents for the treatment of cancer. Herein, we describe pharmacophore-based virtual screening combined with docking study as a rational strategy for identification of novel hits or leads. Pharmacophore models of PKB β inhibitors were established using the DISCOtech and refined with GASP from compounds with IC₅₀ values ranging from 2.2 to 246 nM. The best pharmacophore model consists of one hydrogen bond acceptor (HBA), one hydrogen bond donor (HBD) site and two hydrophobic (HY) features. The pharmacophore models were validated through receiver operating characteristic (ROC) and Güner-Henry (GH) scoring methods indicated that the model-3 was statistically valuable and reliable in identifying PKB β inhibitors. Pharmacophore model as a 3D search query was searched against NCI database. Several compounds with different structures (scaffolds) were retrieved as hits. Molecules with a Q_fit value of more than 95 and three other known inhibitors were docked in the active site of PKB to further explore the binding mode of these compounds. Finally in silico pharmacokinetic and toxicities were predicted for active hit molecules. The hits reported here showed good potential to be PKB β inhibitors.     

Binding and discerning interactions of PTP1B allosteric inhibitors: Novel insights from molecular dynamics simulations

The α7 helix is either disordered or missing in the three co-crystal structures of allosteric inhibitors with protein tyrosine phosphatase 1B (PTP1B). It was modeled in each complex using the open form of PTP1B structure and studied using molecular dynamics (MD) simulations for 25 ns. B-factor analysis of the residues sheds light on its disordered nature in the co-crystal structures. Further, the ability of inhibitors to act as allosteric inhibitor was studied and established using novel hydrogen bond criteria. The MD simulations were utilized to determine the relative importance of electrostatic and hydrophobic component in to the binding of inhibitors. It was revealed that the hydrophobic interactions predominantly drive the molecular recognition of these inhibitors. Per residue energy decomposition analysis attributed dissimilar affinities of three inhibitors to the several hydrogen bonds and non-bonded interactions. Among the secondary structure elements that surround the allosteric site, helices α6, α7 and loop α6–α7 were notorious in providing variable affinities to the inhibitors. A novel hydrophobic pocket lined by the α7 helix residues Val287, Asn289 and Trp291 was identified in the allosteric site. This study provides useful insights for the rational design of high affinity PTP1B allosteric inhibitors.     

A comparative study based on docking and molecular dynamics simulations over HDAC-tubulin dual inhibitors

Nowadays the ability to prediction of complex behavior rationally based on the computational approaches has been a successful technique in drug discovery. In the present study interactions of a new series of hybrids, which were made by linking colchicine as a tubulin inhibitor and suberoylanilide hydroxamic acid (SAHA) as a HDAC inhibitor, with HDAC8 and HDAC1 were investigated and compared. This research has been facilitated by the availability of experimental information besides employing docking methodology as well as classical molecular dynamics simulations and binding free energy calculation were performed. The obtained findings indicate different modes of interactions and inhibition strengths of the studied inhibitors for HDAC8 and HDAC1. HDAC8 binding free energies (−34.35 to −26.27 kcal/mol) revealed higher binding affinity to HDAC8 compared to HDAC1 (−33.17 to −7.99 kcal/mol). The binding energy contribution of each residue with the hybrid compounds 4a-4e within the active site of HDAC1 and HDAC8 was analyzed and the results confirmed the rule of key amino acids in interaction with the hybrid compounds.     

Designing of potential inhibitors against Staphylococcus aureus sortase A: Combined analogue and structure based approach with in vitro validation

Staphylococcus aureus sortase A is an attractive target of Gram-positive bacteria that plays a crucial role in anchoring of surface proteins to peptidoglycan present in bacterial cell wall. Inhibiting sortase A is an elementary and essential effort in preventing the pathogenesis. In this context, in silico virtual screening of in-house database was performed using ligand based pharmacophore model as a filter. The developed pharmacophore model AAHR 11 consists of two acceptors, one hydrophobic and one ring aromatic feature. Top ranked molecule KKR1 was docked into the active site of the target. After profound analysis, it was analyzed and optimized based on the observations from its binding pose orientation. Upgraded version of KKR1 was KKR2 and has improved docking score, binding interactions and best fit in the binding pocket. KKR1 along with KKR2 were further validated using 100 ns molecular dynamic studies. Both KKR1 and KKR2 contain Indole-thiazolidine moiety and were synthesized. The disk diffusion assay has good initial results (ZI of KKR1, KKR2 were 24, 38 mm at 10 μg/mL and ZI of Ampicillin was 22 at 10 μg/mL) and calculated MICs of the molecules (KKR1 5.56 ± 0.28 μg/mL, KKR2 1.32 ± 0.12 μg/mL, Ampicillin 8 ± 1.1 μg/mL) were in good agreement with standard drug Ampicillin. KKR1 has shown IC₅₀ of 1.23 ± 0.14 μM whereas the optimized lead molecule KKR2 show IC₅₀ of 0.008 ± 0.07 μM. Results from in silico were validated by in vitro studies and proved that indole-thiazolidine molecules would be useful for future development as lead molecules against S. aureus sortase A.     

Novel binding patterns between ganoderic acids and neuraminidase: Insights from docking,molecular dynamics and MM/PBSA studies

Recently, ganoderic acids (GAs) give rise to the attractive candidates of novel neuraminidase (NA) inhibitors. However, there is still no evident conclusion about their binding patterns. To this end, docking, molecular dynamics and MM/PBSA methods were combined to study the binding profiles of GAs with the N1 protein and familiar H274Y and N294S mutations (A/Vietnam/1203/04 stain). It was found that the binding affinities of ganoderic acid DM and Z (ΔG_bind, −16.83 and −10.99 kcal mol⁻¹) are comparable to that of current commercial drug oseltamivir (−23.62 kcal mol⁻¹). Electrostatic interaction is the main driving force, and should be one important factor to evaluate the binding quality and rational design of NA inhibitors. The 150-loop residues Asp151 and Arg152 played an important role in the binding processes. Further analysis revealed that ganoderic acid DM is a potential source of anti-influenza ingredient, with novel binding pattern and advantage over oseltamivir. It had steric hindrance on the 150 cavity of N1 protein, and exerted activities across the H274Y and N294S mutations. This work also pointed out how to effectively design dual-site NA inhibitors and reinforce their affinities. These findings should prove valuable for the in-depth understanding of interactions between NA and GAs, and warrant the experimental aspects to design novel anti-influenza drugs.     

Crystal morphology prediction of 1,3,3-trinitroazetidine in ethanol solvent by molecular dynamics simulation

In order to understand the mechanism of the effect of solvent on the crystal morphology of explosives, and be convenient for the choice of crystallization solvent, the attachment energy (AE) model was performed to predict the growth morphology and the main crystal faces of 1,3,3-trinitroazetidine (TNAZ) in vacuum. The molecular dynamics simulation was applied to investigate the interactions of TNAZ crystal faces and ethanol solvent, and the growth habit of TNAZ in ethanol solvent was predicted using the modified AE model. The results indicate that the morphology of TNAZ crystal in vacuum is dominated by the six faces of [0 2 1], [1 1 2], [0 0 2], [1 0 2], [1 1 1] and [0 2 0], and the crystal shape is similar to polyhedron. In ethanol solvent, The binding strength of ethanol with TNAZ faces changes in the order of [0 2 1] > [1 1 2] > [0 0 2] > [1 0 2] > [1 1 1] > [0 2 0], which causes that [1 1 1] and [0 2 0] faces disappear and the crystal morphology becomes more regular. The radial distribution function analysis shows that the interactions between solvent and crystal faces mainly consist of coulomb interaction, van der Waals force and hydrogen bonds.     

Solvent effect on the crystal morphology of 2,6-diamino-3,5-dinitropyridine-1-oxide: A molecular dynamics simulation study

The attachment energy (AE) calculations were performed to predict the growth morphology of 2,6-diamino-3,5-dinitropyridine-1-oxide (ANPyO) in vacuum. The molecular dynamics (MD) method was applied to simulate the interaction of trifluoroacetic acid solvent with the habit faces and the corrected AE model was adopted to predict the growth habit of ANPyO in the solvent. The results indicate that the growth morphology of ANPyO in vacuum is dominated by (1 1 0), (1 0 0), (1 0 −1) and (1 1 −2) faces. The corrected AE energies change in the order of (1 1 0) > (1 0 −1) > (1 1 −2) > (1 0 0), which causes the crystal morphology to become very close to a flake in trifluoroacetic acid solvent and accords well with the results obtained from experiments. The radial distribution function analysis shows that the solvent molecules adsorb on the ANPyO faces mainly via the solvent–crystal face interactions of hydrogen bonds, Coulomb and Van der Waals forces. In addition to the above results, the analysis of diffusion coefficient of trifluoroacetic acid molecules on the crystal growth faces shows that the growth habit is also affected by the diffusion capacity of trifluoroacetic acid molecules. These suggestions may be useful for the formulation design of ANPyO.     

Evaluation of novel Akt1 inhibitors as anticancer agents using virtual co-crystallized pharmacophore generation

The pharmacophoric features of the virtual co-crystallized protein of 17 Akt1 proteins were downloaded from the protein data bank, and explored to end up with 132 generated pharmacophores that had been evaluated using the decoy list composed of 1724 compounds. The areas under the curve of the Receiver-Operating Characteristic (ROC–AUC) were sorted, and the highest ranked pharmacophore 3MV5_2_01 was selected to be used as a searching tool in the National Cancer Institute (NCI) database. The captured hits were mapped based on successful hypotheses and the best fitted compounds were selected. The inhibition of Akt1 was measured and expressed as a percentage of inhibition. 24 out of the 40 compounds showed inhibition of Akt1, out of which 13 compounds showed more than 50% inhibition. Compound 1 showed 93.3% inhibition at 100 μM concentration. To confirm the inhibition of Akt1 phosphorylation, MCF10A cell line was co-treated with 12-O-tetradecanoylphorbol-13-acetate (TPA) and 100 μM of each of the most potent 13 Akt inhibitors (1–13). It was found that compounds 1 exert 91.6% inhibition of Akt1 phosphorylation in MCF10A cell line.     

3D-SDAR modeling of hERG potassium channel affinity: A case study in model design and toxicophore identification

A dataset of 237 human Ether-à-go-go Related Gene (hERG) potassium channel inhibitors (180 of which were used for model building and validation, whereas 57 constituted the “true” external prediction set) collected from 22 literature sources was modeled by 3D-SDAR. To produce reliable and reproducible classification models for hERG blocking, the initial set of 180 chemicals was split into two subsets: a balanced modeling set consisting of 118 compounds and an unbalanced validation set comprised of 62 compounds. A PLS bagging-like algorithm written in Matlab was used to process the data and assign each compound to one of the two (hERG+ or hERG-) activity classes. The best predictive model evaluated on the basis of a fully randomized hold-out test set (comprising 20% of the modeling set) used 4 latent variables and a grid of 6 ppm × 6 ppm × 1 Å in the C-C region, 6 ppm × 30 ppm × 1 Å in the C-N region, and 30 ppm × 30 ppm × 1 Å in the N-N region. An overall accuracy of 0.84 was obtained for both the hold-out test set and the validation set. Further, an external prediction set consisting of 57 drugs and drug derivatives was used to estimate the true predictive power of the reported 3D-SDAR model – a slight reduction of the overall accuracy down to 0.77 was observed. 3D-SDAR map of the most frequently occurring bins and their projection on the standard coordinate space of the chemical structures allowed identification of a three-center toxicophore composed of two aromatic rings and an amino group. A U test along the distance axis of the most frequently occurring 3D-SDAR bins was used to set the distance limits of the toxicophore. This toxicophore was found to be similar to an earlier reported phospholipidosis (PLD) toxicophore.     

Identification and in vitro evaluation of new leads as selective and competitive glycogen synthase kinase-3β inhibitors through ligand and structure based drug design

Glycogen synthase kinase-3β elicits multi-functional effects on intracellular signaling pathways, thereby making the kinase a therapeutic target in multiple pathologies. Hence, it is important to selectively inhibit GSK-3β over structurally and biologically similar targets, such as CDK5. The current study was designed to identify and evaluate novel ATP-competitive GSK-3β inhibitors. The study was designed to identify new leads by ligand based drug design, structure based drug design and in vitro evaluation. The best validated pharmacophore model (AADRRR) identified using LBDD was derived from a dataset of 135 molecules. There were 357 primary hits within the SPECS database using this pharmacophore model. A SBDD approach to the GSK-3β and CDK5 proteins was applied to all primary hits, and 5 selective inhibitors were identified for GSK-3β. GSK-3β and CDK5 in vitro kinase inhibition assays were performed with these molecules to confirm their selectivity for GSK-3β. The molecules showed IC₅₀ values ranging from 0.825 μM to 1.116 μM and were 23- to 57-fold selective for GSK-3β. Of all the molecules, molecule 3 had the lowest IC₅₀ value of 0.825 μM. Our research identified molecules possessing benzothiophene, isoquinoline, thiazolidinedione imidazo-isoquinoline and quinazolinone scaffolds. Potency of these molecules may be due to H-bond interaction with backbone residues of Val135, Asp133 and side chain interaction with Tyr134. Selectivity over CDK5 may be due to side chain interactions with Asp200, backbone of Val61, ionic interaction with Lys60 and π-cationic interaction with Arg141. These selective molecules were also exhibited small atom hydrophobicity and H-bond interaction with water molecule.     

Computational assessment of several hydrogen-free high energy compounds

Tetrazino-tetrazine-tetraoxide (TTTO) is an attractive high energy compound, but unfortunately, it is not yet experimentally synthesized so far. Isomerization of TTTO leads to its five isomers, bond-separation energies were empolyed to compare the global stability of six compounds, it is found that isomer 1 has the highest bond-separation energy (1204.6 kJ/mol), compared with TTTO (1151.2 kJ/mol); thermodynamic properties of six compounds were theoretically calculated, including standard formation enthalpies (solid and gaseous), standard fusion enthalpies, standard vaporation enthalpies, standard sublimation enthalpies, lattice energies and normal melting points, normal boiling points; their detonation performances were also computed, including detonation heat (Q, cal/g), detonation velocity (D, km/s), detonation pressure (P, GPa) and impact sensitivity (h₅₀, cm), compared with TTTO (Q = 1311.01 J/g, D = 9.228 km/s, P = 40.556 GPa, h₅₀ = 12.7 cm), isomer 5 exhibites better detonation performances (Q = 1523.74 J/g, D = 9.389 km/s, P = 41.329 GPa, h₅₀ =  28.4 cm).