Oral have studied six mutations and modelled it

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Last updated: May 21, 2019

OralSquamous Cell Carcinoma (OSCC) is most prevalent cancer worldwide withnoticeable human death rate1.The survival rate of the disease hasnot increased though the advancements in the treatment as surgery andchemo-radio therapy.2The major cause of failure to cure this OSCCcould be the resistance towards therapies reoccurrence3.Hyaluronon(HA),a major component of extra cellular matrix,a primary ligand forCD44 plays significant role in oral squamous cell carcinoma progression4.CD44,atrans-membrane glycoprotein,hyaluronic-bindingHAreceptor,expressed in a widevariety of cells5,6,7. Previously it was reported the useofCD44asamarkerforearlymoleculardiagnosisoflung10,prostate11,colorectal12,breast13,gynecologic14,gastric15,headand neck cancer16,lymphoma17,osteosarcoma18.Changes in CD44 Glucosylation site alters CD44 bindingto hyaluronic acid, any mutations in the phosphorylation site of cytoplasmicdomain of CD44 hinder its adhesion function.

Chou reportedchemoresistance in functional CD44 variants,compared to wild type carriers19.Inthis scenario,we have carried out this present computational modelling andsimulations approach to understand the mutation induced changes on the overallstructure, functionality of CD44.Although,many mutations were reported forfunctional damage to the protein. we have selected six major mutations i.

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e,T27A,R41A,T102A,S112A,S122A,R162A reported around the glycosylation site ofCD44 based on this site importance on its functionality keeping in view of thecomplete crystallized structure availability20.  Materials and MethodsSelectionof SNPs for in silico analysisHumanCD44 gene information data was collected from Online Mendelian Inheritance inMan (OMIM)21 and Entrez Gene on National Centre for BiologicalInformation (NCBI) dbSNP was used to take SNPs reported in CD44 gene associatedwith Oral cancer 22,23.6 SNPs were analysed further.The amino acidsequence of CD44 protein was retrieved from the Uniprot database(P16070).Protein3D structure from protein data bank (1UUH) (Fig.1) 24.

Mutantprotein modelingThe3D structure of a protein is crucial to study its functionality,to understandthe effect of SNP’s on its overall structure and function.We used rcsb.org toidentify the protein coded by CD44 gene (PDB ID 1UUH),which is 158 amino acidsin length starting from the residue at position 20,ending at 178.We havestudied six mutations and modelled it by using “mutate a residue” tool in theSchrödinger maestro v9.6 visualization program Maestro, Version 9.6, usedwild type available 3D structure (1UUH) as reference.MDsimulations in water”Desmondv3.

6Package”25,26 was used to run the molecular dynamicsimulations.Used predefined TIP3P water model27 to simulate water molecules.Orthorhombicperiodic boundary conditions were set up to specify the shape, size of therepeating unit buffered at 10Å distances.To neutralize the systemelectrically,appropriate counter Na+/Cl- ions were added to balance the systemcharge, placed randomly in solvated system.

After building the solvatedsystem,performed minimization,relaxation of protein/protein-ligand complexunder NPT ensemble using default protocol of Desmond28,29,whichincludes a total of 9 stages,only  2minimization and 4 short simulations (equilibration phase) are involved beforestarting the actual production time.Summaryof Desmond’s MD simulation stages Moleculardynamic simulations were carried out with the periodic boundary conditions inthe NPT ensemble using OPLS 2005 force field parameters30,31.Thetemperature were kept at 300K and pressure at 1 atmospheric pressure usingNose-Hoover temperature coupling,isotropic scaling32.The operationwas followed by running the 10ns NPT production simulation each and saving theconfigurations thus obtained at 5ps intervals.Analysisof molecular dynamics trajectoryThemolecular dynamics(MDS) trajectory files were analyzed by using simulationquality, event analysis alongside simulation interaction diagram programs of Desmondfor calculating Energies,root-mean-square deviation and fluctuation.Totalintramolecular hydrogen bonds,Radius of Gyration along with secondary structureelements of protein conferring stability.SQA qualitatively validates the systemstability throughout the simulated length of chemical time for the giventemperature,pressure,volume of the total simulation box.

Whereas,SEA analyzeseach frame of simulated trajectory output and SID for estimating the total SSEchange in the protein structure during simulation.Pre-processingand preparation  protein target structureCrystalstructure of CD44 protein in complex with hyaluronic acid1UUH was resolved byX-ray diffraction,with a resolution factor of 2.30Å was retrieved from ProteinData Bank33,34,which was further modified for dockingcalculations as follows:CD44 protein was imported to Maestro v9.

635.UsingProtein Preparation Wizard (PPW),Schrödinger36 included biologicalunits and assigned bond orders,created zero-order bonds to metals,createddisulfide bonds,converted any selenomethionines to methionines,deleted allwater molecules,generated metal binding states for hetero atoms,added missinghydrogens and capped termini.Also checked for any missing side chains,missingloops to fill using prime module integrated within PPW and found none.

Underreview and modify tab of PPW,all the co-crystallized ligands/hetero atoms andwaters were identified,removed from the structure.Under the refine tab ofPPW,we have optimized the H-bond network to fix the overlapping hydrogens andthe most likely positions of thiol and hydroxyl hydrogen atoms, protonationstates,tautomers of ‘His’ residues,Chi ‘flip’ assignments for’Gln’,’Asn’,’His’residueswere selected by protein assignment script shipped by Schrodinger.At pH7.0,theprotein was minimized by applying OPLS2005 force field30,31.Finally,restrainedminimization was performed until the average root mean square deviation (RMSD)of the non-hydrogen atoms converged to 0.

30Å.ligandThe3D coordinates of quinine were retrieved from Pubchem database37.Ligandsfor docking studies were prepared using Autodock mgltoolsv1.4.6.Before ligandpreparation,ligand structure was energy minimized by charmm’s forcefield.

Ionization state was set to generate all possible states atpH7.0±2.0.Keeping in view of the flexibility of the rings present in eachligand and their possibility to change conformations during dockingcalculations,we have specified to generate low energy ring conformation viaallowing maximum possible rotatable bonds. Liganddocking Themolecular dynamics(MDS) trajectory files were analyzed by using simulationquality, event analysis alongside simulation interaction diagram programs ofDesmond for calculating Energies, root-mean-square deviation andfluctuation.Total intramolecular hydrogen bonds,Radius of Gyration along withsecondary structure elements of protein conferring stability.

SQA qualitativelyvalidates the system stability throughout the simulated length of chemical timefor the given temperature,pressure,volume of the total simulationbox.Whereas,SEA analyzes each frame of simulated trajectory output and SID forestimating the total SSE change in the protein structure during simulation.CD44-Quinine dockinganalysisRecently,aconsiderable amount of literature has suggested high potent activity of quininecompound against cancer.In continuation to the quest of understanding thepotential of this natural compound, we have recently performed a lab scalestudy to evaluate the antioxidanteffects of quinine via anti-lipidperoxidation,antioxidant effect on cancer cells (KB and HEp-2).Our MTT assay based studieshas revealed that quinine has a IC50 value of 125.23?m for 24hr and 117.

81?mfor 48hr with respect to KB cell line.Whereas, it was 147.58?m and 123.74?mwith Hep2.39 In another study,we have demonstrated that quinine treatment significantlyinhibited the cell viability and cell proliferation leading to increasedreactive oxygen species generation,induction of MMPdepolarization,morphological changes,DNA damage in dose and time-dependentmanner.

Moreover,quinine significantly decreased theiNOS,COX-2,IL-6,Bcl-2,mutant p53 simultaneously up-regulated Bax,caspase-3expressions suggesting,that quinine may serve as a potential candidate in theprevention of cell proliferation and enhances apoptosis via inhibitingup-stream signaling.40In this scenario, taking our present study toa step further,we have investigated the impact ofmutations on the inhibitor recognition functions of CD44 protein,dockinganalysis was carried out with specific inhibitor quinine indicated that themutations contribute to weaker interaction with the drug, primarily due to lossof interactions of the drug with surrounding residues.We utilisedwild-type(CD44-quinine),T27A(T27A-quinine) for our analysis(Figure.8).Comparing the binding free energy of CD44 to the drug,mutant T27Aexhibited the weakest interaction with the energy value of ?5.58 Kcal/mol with81.25?m of inhibition constant when compared to wild-type complex -6.

05Kcal/mol with 36.62?m.This result signifies better conjugation of inhibitor tothe binding pocket of the receptor.Mutant T27A complex exhibited the leastbinding affinity towards quinine, which was confirmed by the docking scores. Protein-ligand MDsimulations in waterSince molecular docking representsonly a single snapshot of protein–ligand interactions, we have performedmolecular dynamic simulations in order to study the protein–ligand interactionsin motion contributing for their stable bound conformation and to visualize theeffect of ligand binding on protein conformational changes. The effect ofquinine on wild-type CD44 and T27A mutant was studied through MD simulations.

Quinine compoundsimulation studies with wild  and T27Amutant The dynamic behaviour of wild andmutant protein via simulations. The RMSD contributions were plotted as the timedependant function of MD simulations between the wild-type and mutant(T27A).Two independent simulations were carried out.The results in Figure 9 shows thatthe RMSDs of the trajectories for the wild-type complex was well below 3.

0Å forthe first 5ns.Throughout the simulation period,no significant fluctuations wereobserved in the backbone of the wild-type implying that the binding of quinineat the active site of the proteins is not only stable and strong but also doesnot disturb the protein backbone stability.When mutant protein residuefluctuations were calculated in presence of ligand quinine,it was observed thatmovements and continous fluctuations noticeable at 1ns (Fig 9b) measured.RMSD valueof the ligand observed in the figure is significantly larger than the RMSD ofthe protein.

According to this observation the ligand has diffused away from itsinitial binding site in the early simulations,which leads to the inefficientbinding with T27A mutant protein.Indeed,wild-type and mutant T27A complex tendto reach a steady equilibrium,while RMSD of the mutant complex was noticeablyhigh.Mutant complex T27A remained distinguished throughout the simulationresulting in maximum backbone RMSD of ?3.2Å.

This difference in thedeviation range explains the change in stability of the mutant protein,which inturn reflects the impact of substituted amino acid in the protein structure.In order to calculate the residualmobility of each lead molecules in CD44 protein–ligandcomplexes(wild-typeandmutant),Root Mean Square Fluctuation was calculated ineach complexes and the graph was plotted against the residue number based onthe trajectory period of MD simulation to identify the higher flexibilityregions in the protein.In protein RMSF graph of mutant complex,we can see thatthe major peaks of fluctuations have been observed with 120-125 residues withover 4Å,and residues between 140-145 with >4.2Å have highest deviationduring the MD simulations.Rest of the residues were found to be quite stableand fluctuating well below 2.

0Å.Despite the fact that mutant complex T27Ashowed deviation from its starting conformation.Analysis of fluctuation scoredepicted that the higher degree of flexibility was observed in mutant(T27A)complex than wild-type structure.This suggests that T27A mutation affects thebinding of quinine and makes the backbone more flexible to move.We also monitorchanges in secondary structure during the simulations,it was observed thatwild-type and mutant proteins maintaining an average of around 64% SSE,there isno significant change observed in the secondary structure of mutant complex(Figure 10).From our analysis,it is well revealed that wild-type complex formstrong hydrogen bond with quinine and it is maintained throughout thesimulation,while the mutant complex T27A showing very weak intermolecularhydrogen bonds and these bonds were not maintained thorough out the simulationtime.

Hydrogen bonds in the wild-type complex structure might help to maintainits rigidity while less tendency of the mutant involved in participating inhydrogen bonding with solvent makes it more flexible.The most notable changewas seen in T27A mutation which was well supported by an increase in bindingenergy and loss of hydrogen bond interactions with the mutant protein whencompared to the wild-type protein. In our study, a clear understanding ofstability loss was seen in the RMSF,RMSD which were also accompanied by lessnumber of intermolecular bonds for T27A when compared to wild-type CD44protein.Interaction profile ofligand with wild  and mutant during MDsimulationWhen one of the best snapshots ofMD trajectory was analyzed,it has been observed that quinine forming stronghydrogen bond with GLU75 residue at catalytic site of wild-type CD44 proteinwith over 94% occupancy,but mutant protein was not forming hydrogen bonds withGLU75 residue  whereas it was trying toform hydrogen bond with SER71 with over 2% occupancy only during MD trajectory(Figure 9).Results of the hydrophobic interactions of the ligand with wild-typeprotein shows, that it was found to be interacting with PHE30,His35 and in themutant protein MD simulations it was found to be forming hydrophobicinteractions with LEU70,ILE91 but these interactions not maintaining at least10% of the MD simulation time.

From the total contacts formed between quininewith wild-type and T27A mutant CD44 residues,wild-type was found to be incontact with residues ASN25,ILE26,THR27,PHE30, HIS35,GLY73,GLU75,THR76,CYS77,ARG78and mutant protein was found to be in contact withresiduesPHE30,HIS35,LEU70,SER71,ILE72,GLY73,PHE74,GLU75,THR76,CYS77,ILE91,HIS92,PRO93,THR102,GLU127,ARG150,TYR169(Figure10).  

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