Physicochemical properties of pore residues predict activation gating of CaV1.2: A correlation mutation analysis

Single point mutations in pore-forming S6 segments of calcium channels may transform a high-voltage-activated into a low-voltage-activated channel, and resulting disturbances in calcium entry may cause channelopathies (Hemara-Wahanui et al., Proc Natl Acad Sci U S A 102(21):7553–7558, 16). Here we ask the question how physicochemical properties of amino acid residues in gating-sensitive positions on S6 segments determine the threshold of channel activation of CaV1.2. Leucine in segment IS6 (L434) and a newly identified activation determinant in segment IIIS6 (G1193) were mutated to a variety of amino acids. The induced leftward shifts of the activation curves and decelerated current activation and deactivation suggest a destabilization of the closed and a stabilisation of the open channel state by most mutations. A selection of 17 physicochemical parameters (descriptors) was calculated for these residues and examined for correlation with the shifts of the midpoints of the activation curve (ΔVact). ΔVact correlated with local side-chain flexibility in position L434 (IS6), with the polar accessible surface area of the side chain in position G1193 (IIIS6) and with hydrophobicity in position I781 (IIS6). Combined descriptor analysis for positions I781 and G1193 revealed that additional amino acid properties may contribute to conformational changes during the gating process. The identified physicochemical properties in the analysed gating-sensitive positions (accessible surface area, side-chain flexibility, and hydrophobicity) predict the shifts of the activation curves of CaV1.2

Allosteric Transitions of Supramolecular Systems Explored by Network Models: Application to Chaperonin GroEL

Identification of pathways involved in the structural transitions of biomolecular systems is often complicated by the transient nature of the conformations visited across energy barriers and the multiplicity of paths accessible in the multidimensional energy landscape. This task becomes even more challenging in exploring molecular systems on the order of megadaltons. Coarse-grained models that lend themselves to analytical solutions appear to be the only possible means of approaching such cases. Motivated by the utility of elastic network models for describing the collective dynamics of biomolecular systems and by the growing theoretical and experimental evidence in support of the intrinsic accessibility of functional substates, we introduce a new method, adaptive anisotropic network model (aANM), for exploring functional transitions. Application to bacterial chaperonin GroEL and comparisons with experimental data, results from action minimization algorithm, and previous simulations support the utility of aANM as a computationally efficient, yet physically plausible, tool for unraveling potential transition pathways sampled by large complexes/assemblies. An important outcome is the assessment of the critical inter-residue interactions formed/broken near the transition state(s), most of which involve conserved residues

Chaperones convert the energy from ATP into the nonequilibrium stabilization of native proteins.

During and after protein translation, molecular chaperones require ATP hydrolysis to favor the native folding of their substrates and, under stress, to avoid aggregation and revert misfolding. Why do some chaperones need ATP, and what are the consequences of the energy contributed by the ATPase cycle? Here, we used biochemical assays and physical modeling to show that the bacterial chaperones GroEL (Hsp60) and DnaK (Hsp70) both use part of the energy from ATP hydrolysis to restore the native state of their substrates, even under denaturing conditions in which the native state is thermodynamically unstable. Consistently with thermodynamics, upon exhaustion of ATP, the metastable native chaperone products spontaneously revert to their equilibrium non-native states. In the presence of ATPase chaperones, some proteins may thus behave as open ATP-driven, nonequilibrium systems whose fate is only partially determined by equilibrium thermodynamics

Cooperative Transition between Open and Closed Conformations in Potassium Channels

Potassium (K+) ion channels switch between open and closed conformations. The nature of this important transition was revealed by comparing the X-ray crystal structures of the MthK channel from Methanobacterium thermoautotrophicum, obtained in its open conformation, and the KcsA channel from Streptomyces lividans, obtained in its closed conformation. We analyzed the dynamic characteristics and energetics of these homotetrameric structures in order to study the role of the intersubunit cooperativity in this transition. For this, elastic models and in silico alanine-scanning mutagenesis were used, respectively. Reassuringly, the calculations manifested motion from the open (closed) towards the closed (open) conformation. The calculations also revealed a network of dynamically and energetically coupled residues. Interestingly, the network suggests coupling between the selectivity filter and the gate, which are located at the two ends of the channel pore. Coupling between these two regions was not observed in calculations that were conducted with the monomer, which emphasizes the importance of the intersubunit interactions within the tetrameric structure for the cooperative gating behavior of the channel

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues

Principles underlying energetic coupling along an allosteric communication trajectory of a voltage-activated K+ channel

The information flow between distal elements of a protein may rely on allosteric communication trajectories lying along the protein's tertiary or quaternary structure. To unravel the underlying features of energy parsing along allosteric pathways in voltage-gated K+ channels, high-order thermodynamic coupling analysis was performed. We report that such allosteric trajectories are functionally conserved and delineated by well defined boundaries. Moreover, allosteric trajectories assume a hierarchical organization whereby increasingly stronger layers of cooperative residue interactions act to ensure efficient and cooperative long-range coupling between distal channel regions. Such long-range communication is brought about by a coupling of local and global conformational changes, suggesting that the allosteric trajectory also corresponds to a pathway of physical deformation. Supported by theoretical analyses and analogy to studies analyzing the contribution of long-range residue coupling to protein stability, we propose that such experimentally derived trajectory features are a general property of allosterically regulated proteins