Added an all new ESSA2 method into ProDy.

[buffbyte]

ESSA-2 builds on the original ESSA in several key ways:

- Uniform Crowding Perturbation: The perturbation is standardized by adding uniform number of nodes to each residue, thus ensuring a consistent “crowding” effect.

- MSF-Based Essentiality Metric: Instead of relying on changes in eigenvalues, ESSA-2 uses changes in mean square fluctuations (MSFs) to measure essentiality. This approach accounts for both eigenvalues and eigenvectors, giving a more direct assessment of how perturbations influence the amplitude of protein motions rather than just their frequencies.

- Allosteric Crowding Analysis:** ESSA-2 includes a function for targeted crowding of known allosteric drug-binding sites. This makes it possible to study how perturbations at these sites affect distant regions, effectively modeling long-range allosteric effects.

- Flexible Mode Selection: Users will have the choice to determine the number of modes by specifying the percentage variance.

[buffbyte]

from prody import *
from numpy import *
from matplotlib.pyplot import *
from essa2 import ESSA2

pdb = parsePDB('1pzo', compressed=False)
pdb.select('calpha')

essa= ESSA2()
essa.setSystem(pdb, num_modes=3, lig="A 300 A 301")

essa.refMSFs();
essa.scanResidues();
essa.zscores();
essa.plotESSAZscores()
essa.writeESSAZscoresToPDB()
essa.plotMSFchangeMap()

[AnthonyBogetti]

@buffbyte I was able to run it successfully, following a few changes. I made some comments in the code, please review and revise. Once the imports are cleaned up and the tqdm dependency is taken care of, we can write a unit test for it.

[AnthonyBogetti]

Please make the changes and request a re-review once finished.