The volume changes of unfolding of dsDNA.

High hydrostatic pressure can have profound effects on the stability of biomacromolecules. The magnitude and direction (stabilizing or destabilizing) of this effect is defined by the volume changes in the system, ΔV. Positive volume changes will stabilize the starting native state, whereas negative volume changes will lead to the stabilization of the final unfolded state. For the DNA double helix, experimental data suggested that when the thermostability of dsDNA is below 50°C, increase in hydrostatic pressure will lead to destabilization; i.e., helix-to-coil transition has negative ΔV. In contrast, the dsDNA sequences with the thermostability above 50°C showed positive ΔV values and were stabilized by hydrostatic pressure. In order to get insight into this switch in the response of dsDNA to hydrostatic pressure as a function of temperature, first we further validated this trend using experimental measurements of ΔV for 10 different dsDNA sequences using pressure perturbation calorimetry. We also developed a computational protocol to calculate the expected volume changes of dsDNA unfolding, which was benchmarked against the experimental set of 50 ΔV values that included, in addition to our data, the values from the literature. Computation predicts well the experimental values of ΔV. Such agreement between computation and experiment lends credibility to the computation protocol and provides molecular level rational for the observed temperature dependence of ΔV that can be traced to the hydration. Difference in the ΔV value for A/T versus G/C basepairs is also discussed.

A framework for highly multiplexed dextramer mapping and prediction of T cell receptor sequences to antigen specificity.

T cell receptor (TCR) antigen-specific recognition is essential for the adaptive immune system. However, building a TCR-antigen interaction map has been challenging due to the staggering diversity of TCRs and antigens. Accordingly, highly multiplexed dextramer-TCR binding assays have been recently developed, but the utility of the ensuing large datasets is limited by the lack of robust computational methods for normalization and interpretation. Here, we present a computational framework comprising a novel method, ICON (Integrative COntext-specific Normalization), for identifying reliable TCR-pMHC (peptide-major histocompatibility complex) interactions and a neural network-based classifier TCRAI that outperforms other state-of-the-art methods for TCR-antigen specificity prediction. We further demonstrated that by combining ICON and TCRAI, we are able to discover novel subgroups of TCRs that bind to a given pMHC via different mechanisms. Our framework facilitates the identification and understanding of TCR-antigen-specific interactions for basic immunological research and clinical immune monitoring.

Molecular Determinants of Temperature Dependence of Protein Volume Change upon Unfolding.

Pressure is a well-known environmental stressor that can either stabilize or destabilize proteins. The volumetric change upon protein unfolding determines the effect of pressure on protein stability, where negative volume changes destabilized proteins at high pressures. High temperature often accompanies high pressure, for example, in the ocean depths near hydrothermal vents or near faults, so it is important to study the effect of temperature on the volumetric change upon unfolding. We previously detailed the magnitude and sign of the molecular determinants of volumetric change, allowing us to quantitatively predict the volumetric change upon protein unfolding. Here, we present a comprehensive analysis of the temperature dependence of the volumetric components of proteins, showing that hydration volume is the primary component that defines expansivities of the native and unfolded states and void volume only contributes slightly to the folded state expansivity.

Molecular determinant of the effects of hydrostatic pressure on protein folding stability.

Hydrostatic pressure is an important environmental variable that plays an essential role in biological adaptation for many extremophilic organisms (for example, piezophiles). Increase in hydrostatic pressure, much like increase in temperature, perturbs the thermodynamic equilibrium between native and unfolded states of proteins. Experimentally, it has been observed that increase in hydrostatic pressure can both increase and decrease protein stability. These observations suggest that volume changes upon protein unfolding can be both positive and negative. The molecular details of this difference in sign of volume changes have been puzzling the field for the past 50 years. Here we present a comprehensive thermodynamic model that provides in-depth analysis of the contribution of various molecular determinants to the volume changes upon protein unfolding. Comparison with experimental data shows that the model allows quantitative predictions of volume changes upon protein unfolding, thus paving the way to proteome-wide computational comparison of proteins from different extremophilic organisms.

ProteinVolume: calculating molecular van der Waals and void volumes in proteins.

BACKGROUND: Voids and cavities in the native protein structure determine the pressure unfolding of proteins. In addition, the volume changes due to the interaction of newly exposed atoms with solvent upon protein unfolding also contribute to the pressure unfolding of proteins. Quantitative understanding of these effects is important for predicting and designing proteins with predefined response to changes in hydrostatic pressure using computational approaches. The molecular surface volume is a useful metric that describes contribution of geometrical volume, which includes van der Waals volume and volume of the voids, to the total volume of a protein in solution, thus isolating the effects of hydration for separate calculations. RESULTS: We developed ProteinVolume, a highly robust and easy-to-use tool to compute geometric volumes of proteins. ProteinVolume generates the molecular surface of a protein and uses an innovative flood-fill algorithm to calculate the individual components of the molecular surface volume, van der Waals and intramolecular void volumes. ProteinVolume is user friendly and is available as a web-server or a platform-independent command-line version. CONCLUSIONS: ProteinVolume is a highly accurate and fast application to interrogate geometric volumes of proteins. ProteinVolume is a free web server available on http://gmlab.bio.rpi.edu . Free-standing platform-independent Java-based ProteinVolume executable is also freely available at this web site.