This set of Bioinformatics Multiple Choice Questions & Answers (MCQs) focuses on “Conformational Flexibility”.
1. Proteins are dynamic entities that undergo _______
a) only fluctuation of flexible loop regions about equilibrium positions when in solution
b) only limited conformational change of amino acid side-chains when in solution
c) both limited conformational change of amino acid side-chains and fluctuation of flexible loop regions about equilibrium positions when in solution
d) illimitable or total conformational change of amino acid side-chains when in solution
Explanation: Such flexibility can often be adequately treated by ‘soft’ potentials or limited conformational flexibility and/or refinement of side-chains on docking. However, proteins often undergo more extensive conformational changes which may involve large-scale motions of domains relative to one another or possibly conformational change involving order-disorder transitions.
2. Typical motions of proteins will be primarily treated by a rigid body model for docking.
Explanation: These types of motions will be poorly treated by a rigid body model for docking. Again distinction is often made between the general treatment of protein-protein docking and protein-ligand docking.
3. In case of Protein-ligand docking, ______ ligands are often _____ in adapting their shape to fit the receptor binding pocket.
a) small molecule, highly flexible
b) large molecule, highly flexible
c) large molecule, more flexible
d) small molecule, less flexible
Explanation: The degree of conformational flexibility of a small molecule ligand (substrate, cofactor or inhibitor) can be considerable particularly where there are multiple torsion angles. This presents a major challenge in protein-ligand docking and several different approaches have been used to solve this problem.
4. In Multiple conformation rigid-body method, a ligand is assumed to be able to adopt a number (N) of different _______ that are computed _____ the ligand being docked into the receptor.
a) low-energy conformations, after
b) low-energy conformations, prior to
c) high-energy conformations, prior to
d) high-energy conformations, after
Explanation: These, N, low-energy conformations are then docked individually into the receptor assuming a rigid conformation using a descriptor-based approach. The scoring function is used to determine which of the resulting solutions is optimal.
5. The disadvantage of Multiple conformation rigid-body method is that the active conformation may be missed as the result of a minor structural difference not considered in the ___ ligand conformations. Where, the N is the number of low-energy conformations.
a) N +1
Explanation: The disadvantage is that the active conformation may be missed as the result of a minor structural difference not considered in the N ligand conformations and The advantage of this approach is that the search can be restricted to a smaller number of relevant ligand conformations.
6. In Stochastic search methods, they include methods such as Monte Carlo simulation, simulated annealing, Tabu search, genetic algorithms and evolutionary programming.
Explanation: Stochastic processes use a random sampling procedure to search conformational space. The ligand molecule performs a random walk in space in the receptor cavity. Usually, the ligand is placed in a random orientation in the receptor cavity. Then at each step a small displacement is made in any of the degrees of freedom of the ligand molecule (translation, rotation or torsion angle).
7. In a Monte Carlo simulation the score (or energy) is calculated at each step and compared to the previous step. The probability of accepting the step is given by ______ where ΔE is the difference in energy; kB is Boltzmann’s constant and T the temperature.
Explanation: If the new energy is lower the step is accepted, otherwise the result is treated probabilistically by a Boltzmann mechanism. If P (ΔE) is greater than a random number generated between 0 and 1 then the step is accepted. The higher the temperature (or the smaller ΔE at a given T) the higher the likelihood the step is accepted. A conventional Monte Carlo simulation proceeds at constant temperature, whilst in simulated annealing the temperature is gradually cooled during the simulation in an attempt to locate a globally optimal solution. In simulated annealing the computer stores a single solution and generates a new solution randomly.
8. Genetic methods (genetic algorithms and evolutionary programming) store multiple solutions. These solutions form a population of members.
Explanation: Each member has an associated score or fitness. During the search for the global optimal solution successive new populations are created by a procedure involving selection of the fittest members. These members then have offspring to create a new population. Differences arise in how the methods generate offspring. In a genetic algorithm two solutions are mated to form a new offspring solution. In evolutionary programming each member of the population generates an offspring by mutation.
9. Stochastic methods can guarantee reaching a global optimal solution and the methods are computationally costly in comparison to the other methods.
Explanation: The advantages of stochastic methods are that the ligand is able to explore conformational space in a relatively unconstrained way, frequently leading to the globally optimal solution. The disadvantages are that it cannot guarantee reaching a global optimal solution and the methods are computationally costly in comparison to the other methods.
10. Which of the following is true regarding Protein flexibility?
a) Methods have been described for the introduction of side-chain flexibility to both protein-ligand and protein-protein docking
b) Methods have been described for the introduction of side-chain flexibility to protein-ligand docking only
c) The Mean Field principle is rarely used in this
d) Methods have been described for the introduction of side-chain flexibility to protein-protein docking only
Explanation: The Mean Field approach is one type of what are called bounded search methods. Others include the Dead-end-elimination theorem and the A* algorithm. These methods use different approaches to find a solution and a detailed discussion is beyond the scope of this chapter. However, they use a multiple copy representation of protein side chains built using a rotamer library.
Sanfoundry Global Education & Learning Series – Bioinformatics.
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