Best ChatGPT prompts for Biochemists and Biophysicists

Given a protein sequence and a set of small molecule ligands, predict the binding affinity of each ligand to the protein using a combination of molecular docking and machine learning algorithms, and provide a ranked list of the top 5 ligands with the highest predicted affinity, including their binding free energies and key interacting residues, assuming a temperature of 310K and a pH of 7.4.

Design an experiment to determine the kinetic parameters of an enzyme-catalyzed reaction, including the Michaelis constant, turnover number, and substrate inhibition constant, using a substrate concentration range of 0.1-10 mM and an enzyme concentration of 1 μM, and provide a detailed protocol including buffer composition, temperature control, and data analysis strategy, as well as a table of expected results and a graph of the predicted kinetic curves.

Perform a molecular dynamics simulation of a protein folding trajectory using the CHARMM force field and the NAMD simulation package, starting from an unfolded state and running for 100 ns with a time step of 2 fs, and analyze the resulting trajectory to identify key folding intermediates, including their structural characteristics and thermodynamic stability, and provide a plot of the folding free energy landscape as a function of the radius of gyration and the number of native contacts.

Construct a gene regulatory network from a set of microarray expression data using a combination of correlation analysis and machine learning algorithms, and identify key transcription factors and their target genes, including their regulatory motifs and binding sites, and provide a visual representation of the network using a graph layout algorithm, as well as a table of the top 10 transcription factors ranked by their predicted regulatory importance.