pFolMech

Protein Biophysics Lab

Predicting Folding Free Energy Profiles, Conformational Landscapes, and Folding Mechanisms

Frequently Asked Questions

A. Questions on Job Submission

>> Why is my PDB file not getting accepted/generating error?

We are employing a structure based statistical mechanical model (WSME) for predicting the folding thermodynamics of protein and mutant(s). So, some constraints on the PDB file like length of protein, presence of missing atoms etc. have been added to ensure reliability of calculations and model predictions.

>> Do I need to provide my e-mail ID?

Yes, Providing e-mail ID is required as some jobs might take longer to complete. An automated mail with links to result page would be sent on job completion.

>> Why am I not able to retrieve my job?

Jobs are kept in the server for only five days after completion, after which they are permanently deleted. If you are not able to retrieve your job even in the specified time span, please write a mail to us with your job ID.

B. Questions on Model Parameters

>> What are the various model parameters employed to predict thermal unfolding profiles and residue folding probabilities?

The bWSME model involves four thermodynamic parameters namely, the interaction energy per native contact (ξ), the entropic cost of fixing a residue in native conformation (Δ𝑆𝑐𝑜𝑛𝑓), effective dielectric constant (εeff), and the heat capacity change upon fixing a native contact (Δ𝐶𝑝𝑐𝑜𝑛𝑡).

i) The magnitude of effective dielectric constant is fixed to 29. This estimate robustly captures the changes in stability induced by point mutations involving charged residues (Naganathan AN, 2012; Naganathan AN 2013), the differences in stability between mesophilic and thermophilic protein pairs and even the role of phosphorylation in a disorder-to-order protein switch (Gopi S et al, 2015).

ii) The interaction energy per native contact (ξ), is specified by the user and is the only tunable parameter.

iii) Entropic costs are assigned to the protein residues using a structure-based method, whereby an entropic cost of -20.6 J/(mol.K) per residue is assigned for residues identified as coil by (STRIDE) and -14.5 J/(mol.K) per residue for all other residues (Rajasekaran N et al , 2016). Additionally, for glycine and proline, entropic costs of -20.6 J/(mol.K) per residue and 0 J/(mol.K) per residue, respectively, are assigned (Gómez J et al , 1995).

iv) The heat capacity change upon fixing a native contact is fixed to -0.36 J/(mol. K) per contact (Naganathan AN, 2012).

v) Heavy atom contacts are identified with a distance cutoff of 5 Å including the nearest neighbors (j>i).

>> How to identify the optimal block size for a protein?

In the web server, the block size is defined as the ceil(nres/100), where nres is the length of the protein. Ideally, a block size of 1-6 is preferred for the free energy calculations. Note that increasing the block size smoothens the free energy landscape and it is not advised to use a block size beyond 6 for large proteins.

C. General Questions

>> Can I use computationally modeled protein structure as an input for web server predictions?

The server does not differentiate between modeled and experimentally determined protein structures.

>> Can the bWSME model be used to generate free energy profiles using parameters outside of the range allowed by the server or for proteins with over 500 residues?

The MATLAB scripts used in the server are available in the associated GitHub repository. All parameters may be modified in these scripts (Gopi S et al., 2019; Naganathan AN et al., 2021). The scripts may generate NaN or Inf free energy values for certain large proteins or large negative van der Waal's interaction energies. This problem can be rectified by increasing the number of calculating windows (the parameter "wi" in the script FesCalc_Block.m).

2022, Maintained by Protein Biophysics Lab, IIT Madras, Chennai-36, India

Last Updated: February 8, 2022