Free Protein-Protein Modeling Certification Assessment | StemSkills Lab
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Free Protein-Protein Modeling Certification Assessment

Test your knowledge of protein-protein modeling: interfaces, HADDOCK, hot spots, and CAPRI metrics. Pass at 70% to earn a verifiable StemSkills certificate. Download it as a PDF and add it to your LinkedIn profile. It is free.

Protein-Protein Modeling certification assessment

1
Take the quiz
20 questions on protein-protein modeling. About 20 minutes, at your own pace. No sign-up needed to start.
2
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One click with Google. Your score is saved to your account so you can see whether you passed.
3
Pass? Get certified
Score 70% or more and download your verifiable certificate, then add it to LinkedIn.
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Protein-Protein Modeling Certification Assessment

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Free certification assessment. Pass at 70% to earn a verifiable StemSkills certificate.

  • Questions count: 20
  • Passing grade: 70%
  • Time limit: 20 minutes
Start Quiz
1.
Protein–protein docking predicts:
The DNA sequence of a gene
How two proteins assemble into a complex (relative orientation/interface)
The melting temperature
The codon usage
2.
A protein–protein "interface" refers to:
The set of residues in contact between the two partners
The solvent box
The GUI of the software
The force field file
3.
HADDOCK is notable for being a:
Force field
Data-driven docking approach that uses experimental/ predicted restraints
Rendering engine
Sequence aligner
4.
"Shape complementarity" at an interface describes:
The same secondary structure
Identical sequences
Geometric fit between the two protein surfaces
Equal molecular weights
5.
Rigid-body protein–protein docking initially treats each protein as:
A rigid object, sampling relative translations/rotations
A single atom
A DNA duplex
A flexible chain sampled residue-by-residue
6.
"Induced fit" at a protein–protein interface means:
The sequence mutates
Conformational changes occur upon binding
The interface never changes
Only water binds
7.
Buried surface area (BSA) upon complex formation is used to:
Assign charges
Characterize interface size/extent of burial
Count chains
Measure temperature
8.
A common scoring signal for a plausible PPI model is:
Random orientation
Favorable shape + electrostatic/hydrophobic complementarity with few clashes
Maximum steric clash
Zero contacts
9.
Which experimental data most directly informs restraint-based PPI docking?
Gene expression microarray
Ligand solubility
Mutagenesis/cross-linking/NMR data on interface residues
Codon bias
10.
"Hot spot" residues at an interface are:
Buried metal ions
Residues far from the interface
A few residues contributing disproportionately to binding energy
Only glycines
11.
Homodimer vs heterodimer differ in that a homodimer has:
No interface
Only DNA
Two identical protein chains
Two different proteins
12.
A major challenge in protein–protein docking (vs small-molecule docking) is:
Large, flat interfaces and backbone flexibility of both partners
There is never any interface
No scoring is possible
Ligands are too small
13.
FFT-based docking (e.g., ZDOCK-style) accelerates the search by:
Aligning sequences
Efficiently scanning translations/rotations via correlation in Fourier space
Running MD only
Ignoring the receptor
14.
Refinement of a docked complex often uses:
Sequence trimming
Gel filtration
PCR
Energy minimization / short MD and interface side-chain repacking
15.
Co-evolution / coupled mutations between two proteins can indicate:
No relationship
Residue pairs likely in contact at the interface
The melting point
The expression host
16.
An "encounter complex" in PPI refers to:
Transient early-association states before the final bound complex
A denatured protein
A ligand pose
The final crystal structure
17.
Which metric assesses a predicted complex against a reference (CAPRI-style)?
Tm
BLAST e-value
Codon adaptation index
Interface RMSD / ligand RMSD / fraction of native contacts (fnat)
18.
Electrostatic steering in association means:
Charges are ignored
Long-range electrostatics can guide partners toward the correct orientation
Only van der Waals matters
Water is removed
19.
AlphaFold-Multimer / deep-learning complex prediction primarily leverages:
Explicit-solvent MD only
Manual docking only
Evolutionary/co-evolution signals + learned structural patterns
Gel electrophoresis
20.
After predicting a complex, a reasonable validation is to check:
The gene promoter
Interface plausibility, clash score, and stability under short MD
The PCR cycle number
The ligand's molecular weight only
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