CH3F1 Mock Paper 2024 PDF

1. (a) covered in lectures/workshops (i) What force fields are available to develop parameters for this molecule? Explain why these force fields are suited to this task. Model Answer: Several force fields can be utilized to develop parameters for molecules like benzocaine. Common force fields includ...

1. (a) covered in lectures/workshops (i) What force fields are available to develop parameters for this molecule? Explain why these force fields are suited to this task. Model Answer: Several force fields can be utilized to develop parameters for molecules like benzocaine. Common force fields include CHARMM, AMBER, GROMOS, OPLS, and many others. These force fields are specifically designed to describe the interactions and behaviours of molecules in various environments. CHARMM (Chemistry at Harvard Molecular Mechanics) is suitable for biomolecules and small organic compounds due to its accurate treatment of bond and angle parameters. AMBER (Assisted Model Building with Energy Refinement) is well-suited for simulating biomolecules and organic compounds in different solvent environments, offering extensive parameter sets for various functional groups. GROMOS (Groningen Molecular Simulation) is designed for organic and biomolecular systems, offering a balance between computational efficiency and accuracy. OPLS (Optimized Potential for Liquid Simulations) force field is known for its accuracy in reproducing thermodynamic properties of small organic molecules. The selection of a force field depends on the type of molecule, the intended simulation environment, and the accuracy required for the specific research objectives. All of the above force fields are designed to be additive. (ii) What details are required to develop a topology/parameters for benzocaine? Model Answer: To develop a topology and parameters for benzocaine, several details are necessary. These include: 1. Atom Types: Assigning appropriate atom types to each atom in the molecule based on its chemical environment. 2. Bond Parameters: Determining bond lengths and force constants for all bonds in the molecule. 3. Angle Parameters: Specifying bond angles and force constants for all angles in the molecule. 4. Dihedral Parameters: Defining dihedral angles and force constants for rotatable bonds. 5. Partial Charges: Calculating or obtaining partial charges for each atom to describe the electrostatic interactions. 6. Non-bonded Parameters: Setting van der Waals parameters (σ and ε) to account for steric interactions and Coulombic interactions. All these details are essential for accurately representing the interactions and energetics of benzocaine in a molecular simulation. (iii) Describe the available approaches for calculating partial charges of this molecule? Model Answer: There are several approaches for calculating partial charges of benzocaine: 1. Quantum Mechanical (QM) Methods: QM methods, such as Density Functional Theory (DFT) and ab initio calculations, can accurately determine partial charges by solving the electronic structure of the molecule. 2. Electrostatic Potential Fitting: This approach involves fitting the electrostatic potential around the molecule to derive partial charges that reproduce the experimental or QMcalculated potential. 3. Charge Equilibration Methods: Methods like Charge Equilibration (QEq) distribute charges based on electronegativity and chemical environment to achieve a charge-balanced system. 4. Empirical Charge Models: Some force fields include pre-determined partial charge parameters for common functional groups, derived from experimental data or quantum calculations. The choice of method depends on the accuracy required and the computational resources available. (iv) Justify a benefit and a limitation of using a united atom force field to describe benzocaine. Model Answer: A benefit of using a united atom force field to describe benzocaine is computational efficiency. United atom force fields reduce the number of explicit atoms in the simulation, making it faster compared to all-atom force fields. This allows for longer simulations or the study of larger systems within the same computational resources. A limitation of united atom force fields is the loss of chemical detail. By merging atoms, information about bond lengths, angles, and torsions can be less accurate, leading to potential inaccuracies in certain molecular properties. This loss of resolution can impact the accuracy of certain simulation outcomes, especially for systems where detailed atomic interactions are crucial. (v) Discuss the sources of experimental data that have been used to parameterize force fields to ensure their accuracy? Model Answer: Experimental data used to parameterize force fields come from various sources: 1. Crystallographic Data: X-ray crystallography provides precise information on molecular geometries, bond lengths, and angles, which can be used to validate force field parameters. 2. Spectroscopic Data: Techniques like NMR spectroscopy and vibrational spectroscopy offer insights into molecular conformations, bond vibrations, and functional group interactions. 3. Thermodynamic Data: Experimental data on thermodynamic properties like heats of formation, vaporization, and solvation are valuable for refining force field parameters. 4. Databases: Experimental databases, such as the Protein Data Bank (PDB) and the Cambridge Structural Database (CSD), provide a wealth of structural information that can be used to derive force field parameters for biomolecules and small organic compounds. 5. Quantum Mechanical Calculations: Experimental data from quantum mechanical calculations, such as gas-phase energies and dipole moments, can be used to optimize force field parameters. Integrating these experimental data into force field development ensures that the simulations accurately represent real-world molecular behaviour. (b) covered in lectures/workshops Benzocaine has been shown to inhibit a sodium ion channel. (i) If the structure of the sodium channel is not known, what molecular modelling approaches can be used to build the channel structure? Model Answer: In the absence of an experimentally determined structure, several molecular modelling approaches can be used to build the structure of the sodium ion channel: 1. Homology Modelling: If homologous ion channels with known structures are available, homology modelling can be applied to model the sodium channel's structure based on sequence similarity. 2. Threading/Fold Recognition: Threading algorithms can identify protein folds that resemble the sodium channel sequence, guiding the construction of a structural model. 3. Ab Initio Structure Prediction: Ab initio methods predict protein structures solely based on physics and first principles, without using templates. However, this approach is computationally demanding and more suitable for smaller proteins. 1. AlphaFold. (ii) What molecular modelling methods could be used to predict the binding of benzocaine to the sodium channel? Model Answer: Several molecular modelling methods can be employed to predict the binding of benzocaine to the sodium channel: 1. Molecular Docking: Molecular docking can predict the binding mode and binding affinity of benzocaine within the sodium channel's binding site, e.g. AutoDock 2. Molecular Dynamics (MD) Simulations: MD simulations can be used to observe the dynamic interactions between benzocaine and the sodium channel over time, providing insights into the stability of the complex. (iii) Design a molecular modelling experiment to show that benzocaine acts by blocking the permeation of Na+ ions? Model Answer: To design a molecular modelling experiment to demonstrate that benzocaine acts by blocking Na+ ion permeation, the following steps can be undertaken: 1. System Setup: Build a molecular model of the benzocaine-bound sodium channel, including the binding site where Na+ ions permeate. 2. Molecular Dynamics Simulations: Conduct MD simulations of the benzocaine-bound sodium channel in an explicit solvent environment. Run simulations with and without benzocaine in the binding site. 3. Permeation Analysis: Analyse the trajectories to compare the permeation of Na+ ions in the presence and absence of benzocaine. Look for any significant differences in ion movements or blockage of the ion pathway. 4. Binding Site Interactions: Investigate the interactions between benzocaine and the binding site residues. Determine if benzocaine disrupts the ion pathway or interferes with Na+ ion movement. 5. Free Energy Calculations: Optionally, perform free energy calculations to estimate the energy barriers for Na+ ion permeation with and without benzocaine. c. And (d) covered in lectures. Foundations to (c) covered as well, but not this exact problem. d. In constant height mode a tip is scanned at a constant tip-surface separation. In constant current mode a feedback electronics adjusts the height of the tip with respect to the surface, so as to maintain a constant value of tunnelling current, set by the operator. e. In constant height mode the tunnelling current is used to build the STM image. In constant current mode the height of the tip is changed by applying a voltage to a piezoelectric element holding the tip. The STM image is obtained by displaying the piezo voltage as a function of the tip lateral (x, y) position. f. It is necessary to all but the end of the tip in an insulating material, e.g. wax, so that it is not exposed to the solution. This is because in solution it essentially functions as an electrode and the electrode area should be made as small as possible to remove unwanted (faradaic) currents. g. We covered copper electrochemical dissolution and deposition in some detail, revealing the importance of step and kink sites in the processes. æ 2m F ö÷ h. Since the tunnelling current I can be expressed as I µ expç - 2 d , the ratio of the ç ÷  è ø currents measured at positions A and B is equal to é ù é ù 2mF (d A - d B )ú = expê2 2mF bú , I A / I B = expê- 2   ë û ë û where b is the height of a monoatomic step of the surface. Hence: 30 = exp[2𝑏√( 2 × 9.109 × 10!"# × 5 × 1.6 × 10!#$ )/1.0546 × 10!"% J ⋅ s ] ln 30 = 2𝑏√(2 × 9.109 × 10!"# × 5 × 1.6 × 10!#$ )/1.0546 × 10!"% &' "( × #.(,%-×#(!"# ".,23×#(!"# b =.√(.× $.#($ ×#(!"$ ×,×#.- ×#(!$% ) =..%#% ×#(!&# = 1.49 Å 2. covered in lectures/workshops (a) I am leading the students through this question much more than I would have done in the past. Number of molecules adsorbed = 5.0 x 10-4 mol g-1 x NA = 3.0 x 1020 Surface area is no. of molecules adsorbed x cross sectional area (which the students are given in notes). 48 m2 g-1. Unseen, but similar calculations covered. (b) N(s) = Cs-D/2; So N(s1)/ N(s2) = s1-D/2/s2-D/2; So N(Kr) = N(N2) (16/23)1.3 = 5 x 10-4 mol g1 x 0.624 = 3.12 x 10-4 mol g-1 The surface area is thus 3.12 x 10-4 mol g-1 x 23 x 10-20 x 6.02 x 1023 = 43.2 m2 Impact of the fractal surface, with quite high D value so that even a slightly smaller probe molecule sees a noticeably smaller surface area. Unseen problem –similar problems (mainly graphical with several probe molecules) in lectures and workshop. (c) A number of examples given in lectures. Two prominent ones are self-cleaning paints and water repellent surfaces. (d) Three antibiotics of the penicillin family are shown in Figure 2. Design and discuss a set of molecular modelling experiments to compare the strength of binding of the three ligands to their inhibition site on PBP and therefore calculate which ligand has the greatest affinity? Use the molecular images below to illustrate your answer. Model Answer: To compare the binding strength of the three penicillin family antibiotics to their inhibition site on Penicillin-Binding Proteins (PBP), a series of molecular modelling experiments can be performed: 1. Molecular Docking: Conduct molecular docking simulations of each antibiotic (penicillin G, penicillin V, and ampicillin) into the active site of PBP. Molecular docking predicts the binding modes and binding energies of ligands to their target PBP. 2. Binding Free Energy Calculations: Utilise advanced computational methods like Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA), Molecular Mechanics/Generalized Born Surface Area (MM/GBSA), Potential of Mean Force, Absolute Free Energy calculations or, in this case, relative FEP to calculate the binding free energy of each antibiotic-PBP complex. The binding free energy estimates the strength of the ligand-protein interactions. May be suitable to suggest WTMetaD if resource is plentiful. 3. Molecular Dynamics (MD) Simulations: Perform MD simulations of the three antibioticPBP complexes in an explicit solvent environment. MD simulations provide insights into the dynamic behaviour of the complexes and the stability of ligand-protein interactions over time. 4. Interaction Analysis: Analyse the MD trajectories to investigate specific interactions between the antibiotics and PBP. Identify key residues involved in ligand binding and their contribution to the overall binding affinity. By comparing the binding free energies and interaction profiles of the three antibiotics, it is possible to determine which ligand exhibits the greatest affinity for PBP and therefore has the strongest binding. (e) covered in lectures/workshops As part of your experiment above you also set up a molecular dynamics simulation of penicillin G solvated in water and ions. (i) What is the role of the periodic unit cell? Model Answer: The periodic unit cell in molecular dynamics simulations serves to mimic an infinite, repeating system. By replicating the simulation box in all three dimensions, the system becomes periodic, meaning the molecules' interactions at the edges of the box are the same as those in the central region. This periodicity avoids boundary effects and allows simulations to model bulk behaviour, making it representative of a larger system. (ii) How is pressure maintained over the course of the simulation? Model Answer: Pressure in the MD simulation is maintained using a barostat, such as the Berendsen or Nose-Hoover methods. The barostat adjusts the box volume to control the pressure and keep it at the desired value. The pressure coupling constant is chosen to control the frequency of volume adjustments, ensuring that the system equilibrates to the desired pressure. (iii) How is temperature controlled during the MD simulation? Model Answer: Temperature in the MD simulation is controlled using a thermostat, such as the Berendsen or Andersen methods. The thermostat couples the system's kinetic energy to a heat bath, allowing the simulation to reach the desired temperature. The temperature coupling constant determines the rate at which the system exchanges energy with the heat bath. (iv) ~4000 (v) 8 Na and 8 Cl. 3. (a) This question is purposely broad. I include a selection of potential answers below. 1. Drug Discovery and Design: Molecular modelling is widely used in drug discovery to understand the interactions between drugs and their target proteins. It helps identify potential lead compounds, optimise their binding affinities, and design new drugs with improved properties. For example, molecular docking can be used to predict the binding mode of a potential drug molecule to a target protein, such as the interaction of a small molecule inhibitor with an enzyme's active site. 2. Protein Structure Prediction: Molecular modelling is used to predict the 3D structure of proteins, especially when experimental methods like X-ray crystallography or NMR spectroscopy are challenging or time-consuming. Comparative modelling, homology modelling, and ab initio methods are used to predict protein structures. For example, homology modelling can be employed to predict the structure of a protein using a known template with a similar sequence. 3. Enzyme Catalysis Studies: Molecular modelling is used to investigate enzyme catalysis mechanisms and understand how enzymes accelerate chemical reactions. Quantum mechanics/molecular mechanics (QM/MM) simulations and transition state theory are employed to study enzymatic reactions. For instance, QM/MM can be used to study the reaction pathway of an enzymecatalysed reaction and identify key intermediates. 4. Material Design and Development: Molecular modelling is utilized in designing and optimizing novel materials with specific properties. Computational methods like Density Functional Theory (DFT) and Molecular Dynamics (MD) simulations can help explore the behaviour of materials at the atomic level. For example, DFT calculations can predict the electronic structure of materials, guiding the design of new semiconductors or catalysts. 5. Solvent Effects and Reaction Mechanisms: Molecular modelling is employed to study solvent effects on chemical reactions and understand reaction mechanisms in different environments. Continuum solvent models and explicit solvent MD simulations can provide insights into the role of solvents in chemical processes. For example, explicit solvent MD simulations can reveal how a chemical reaction proceeds in a solvent environment and assess the solvent's impact on reaction rates. Certainly! Here are three more distinct uses of molecular modeling in modern chemistry: 7. Pharmacophore Modelling: Molecular modelling is employed to construct pharmacophore models, which represent the essential features required for a molecule to interact with a specific biological target. Pharmacophore modelling helps in virtual screening of chemical libraries to identify potential drug candidates with similar pharmacophoric features. For example, pharmacophore modelling can be used to search for new ligands that bind to a specific receptor site, such as the active site of an enzyme. 8. ADME-Tox Prediction: Molecular modelling is utilized to predict the Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADME-Tox) properties of potential drug candidates. Computational methods like QSAR (Quantitative Structure-Activity Relationship) and machine learning algorithms are applied to predict a compound's pharmacokinetic and toxicological behaviour. For example, QSAR models can predict a drug's blood-brain barrier permeability or its potential to cause liver toxicity. 9. Computational Spectroscopy: Molecular modelling is used to simulate and analyse various spectroscopic techniques, such as UV-Vis spectroscopy, NMR spectroscopy, and IR spectroscopy. Computational spectroscopy allows researchers to compare experimental spectra with simulated spectra, aiding in the identification and characterization of chemical compounds. For example, NMR chemical shifts can be predicted using quantum chemical calculations to assign peaks in NMR spectra. These additional uses highlight the versatility of molecular modelling techniques and their applications in various fields of chemistry, from drug discovery to materials science and beyond. These are just a few examples of the diverse applications of molecular modelling in modern chemistry, showcasing its importance in various research areas. (b) Molecular dynamics simulations allow the motions of atoms to be studied. (i) What is the typical time-step used in all-atom molecular dynamics simulations? Model Answer: The typical time-step used in all-atom molecular dynamics simulations ranges from 1 to 2 femtoseconds (fs). The time-step is a fundamental parameter that determines the granularity of the simulation and how often the positions and velocities of atoms are updated during the simulation. (ii) How does this time-step enable the updating of atom positions and velocities? Model Answer: During each time-step in molecular dynamics simulations, the equations of motion, such as Newton's equations, are solved to update the positions and velocities of the atoms. By dividing the simulation time into small time-steps, the motion of atoms is effectively approximated as a series of discrete steps, allowing the simulation to capture detailed atomic movements and interactions. (iii) Briefly introduce and explain the numerical integration process used in molecular dynamics. Model Answer: The numerical integration process in molecular dynamics involves solving the equations of motion numerically to predict the positions and velocities of atoms at each time-step. One of the most commonly used methods is the Verlet algorithm, specifically the velocity Verlet algorithm. This process consists of the following steps: 1. Initialization: At the beginning of the simulation, initial positions and velocities of atoms are set based on the starting configuration. 2. Force Calculation: Forces acting on each atom are computed based on the interactions with neighbouring atoms using a force field (e.g., bonded and non-bonded interactions). 3. Position Update: The positions of atoms are updated based on their current positions, velocities, and forces using the following equation: New Position = Current Position + Velocity * Time-step + 0.5 * (Force / Mass) * Timestep^2 4. Force Recalculation: After updating the positions, new forces are calculated for the atoms using the updated atomic positions. 5. Velocity Update: The velocities of atoms are updated based on the current velocities and the new forces using the following equation: New Velocity = Current Velocity + 0.5 * ((New Force + Current Force) / Mass) * Time-step 6. Repeat: Steps 3 to 5 are repeated for each time-step of the simulation, allowing the system to evolve over time. The numerical integration process iterates through time-steps, accurately simulating the atomic movements and behaviour of the system as it progresses through the molecular dynamics simulation. (a) Similar problem in lectures/workshop (i) -492.40 kJ/mol (ii) -6.57 kJ/mol (iii) -498.97 kJ/mol (b) In lectures. Adsorption is REVERSIBLE Three assumptions: 1. Adsorption cannot proceed beyond monolayer coverage. 2. All surface sites are equivalent and can accommodate, at most, one adsorbed atom or molecule. 3. The ability of a molecule to adsorb at a given site is independent of the occupation of neighbouring sites. To comment on how reasonable the assumptions are, students will need to connect with adsorption enthalpy data. There are examples in the lectures that address each of these points. (c) To show these data conform to the Langmuir isotherm, it’s necessary to cast: 𝐾𝑝 𝜃= 1 + 𝐾𝑝 into linear form: 1 1 = +1 𝜃 𝐾𝑝 1 1 1 = +( ) 𝑉 𝐾𝑝𝑉4 𝑉4 1/p/(Torr-1) 10 8 6 4 2 1 (1/V)/cm-3 40 35 30 25 20 17.5 Intercept = 15 cm-3 Þ 𝑉4 = 0.0667 cm3 Slope of (1/V) - 1/p plot is 22.5/9 = 2.5 Torr.cm-3 = (KVm)-1. Hence K-1 = 0.1667; K = 6 Torr-1