iFold is a web portal for interactive protein folding/unfolding simulations. We perform discrete molecular dynamics simulations of proteins using coarse-grained structural models (two-beads/residue).

The underlying approach, discrete molecular dynamics, is one of the fastest strategies for simulating protein dynamics, due, in part, to its efficient sampling of the vast conformation space of biomolecules in both length and time scales. iFold server supports simulations for protein folding, unfolding, thermodynamic scan, simulated annealing and p(fold) analysis.

Currently two-bead/residue Go model is available for protein simulations. Models for DNA and RNA are under development and will be added to iFold in due course. Please use the adjoining menu to register/login to the iFold server. To cite iFold in your research, please use the following reference:

S. Sharma, F. Ding, H. Nie, D. Watson, A. Unnithan, J. Lopp, D. Pozefsky, and N. V. Dokholyan, "iFold: A platform for interactive folding simulations of proteins" Bioinformatics, 22: 2693-2694 (2006).

iFoldRNA is a web portal for interactive RNA folding simulations. We perform discrete molecular dynamics simulations of RNA using coarse-grained structural models (two-beads/residue).

To cite iFoldRNA in your research, please use the following references:

S. Sharma, F. Ding, and N. V. Dokholyan, "iFoldRNA:Three-dimensional RNA structure prediction and folding" Bioinformatics, 24: 1951-1952 (2008).

F. Ding, S. Sharma, P. Chalasani, V. V. Demidov, N. E. Broude, and N. V. Dokholyan, "Large scale simulations of 3D RNA folding by discrete molecular dynamics: From structure prediction to folding mechanisms" RNA, 14: 1164-1173 (2008).

Eris, which takes the name of Greek goddess of discord, is a protein stability prediction server. Eris server calculates the change of the protein stability induced by mutations (ΔΔG) utilizing the recently developed Medusa modeling suite. In our test study, the ΔΔG values of a large dataset (>500) were calculated and compared with the experimental data and significant correlations are found. The correlation coefficients vary from 0.5 to 0.8. Eris also allows refinement of the protein structure when high-resolution structures are not available. Compared with many other stability prediction servers, our method is not specifically trained using protein stability data and should be valid for a wider range of proteins. Furthermore, Eris models backbone flexibility, which turns out to be crucial for ΔΔG estimation of small-to-large mutations. More details are available in our publications:

S. Yin, F. Ding, and N. V. Dokholyan, "Eris: an automated estimator of protein stability" Nature Methods 4, 466-467 (2007)

S. Yin, F. Ding, and N. V. Dokholyan, "Modeling backbone flexibility improves protein stability estimation" Structure, 15: 1567-1576 (2007)

Hinge region predictor (H-Predictor) predicts putative hinge regions involved in protein oligomerization via the domain-swapping mechanism. Domain swapping is an important mechanism for protein oligomerization, in which a fragment of a protein exchanges with a corresponding fragment of another like protein. The segment of polypeptide chain that links the swapped domain and the main protein is the hinge region. In most experimentally observed domain-swapped oligomers, the swapped domains correspond to one or several secondary structural elements from either the N- or C-termini. Only in some rare instances the swapped domains are positioned in the middle of the protein. The domain-swapped oligomeric structures are, therefore, mainly determined by the location and the properties of the hinge region.

Using a simple contact-based potential for enthalpy and graph theory- based estimation for entropy, H-Predictor quantifies for each residue the propensity as the hinge region. Physically, the H-Predictor computes for each residue the effective temperature to populate an "intermediate" state, where the protein unfolds around this residue into two sub-domains each of which maintains their native-like structure. Thus, the smaller the effective temperature, the higher the probability for a residue to be in the hinge-region. The proposed predictor is not a measure of the protein"s propensity for domain-swapping, but rather a structural propensity that a hinge region may result in domain swapping. Additionally, if the protein features folding intermediate, the H-Predictor can also provide hint to the weakest regions that unfold prior to the compete unfolding.

For details of the method, please refer to the paper (F. Ding, K. C. Prutzman, S. L. Campbell, and N. V. Dokholyan, Structure, 14: 5-14 (2006)