Protein Allostery and Ligand Design: Computational Design Meets Experiments to Discover Novel Chemical Probes

Conformational Behavior of SARS-Cov-2 Spike Protein Variants: Evolutionary Jumps in Sequence Reverberate in Structural Dynamic Differences

“…To explore whether dynamic signatures exist that can be related to the observed trends in stability, we set out to characterize residue-pair distance fluctuations (DFs) among all amino acid pairs in various proteins. − This calculation, which reports the mean-square fluctuation of the inter-residue distance between any two residues in the protein, informs on the effect of sequence variations on the internal dynamics of the protein. In particular, an increase of global internal flexibility (overall decreased pair coordination) can be related to an enhanced tendency to support transitions to states alternative to the native one.…”

Decrypting the languages of allostery in membrane-bound K-Ras4B using four complementaryin silicoapproaches

“…Languages chosen to interrogate the active state of K-Ras4B at equilibrium include: (i) distance fluctuation (DF) analysis, 14,16,60 which postulates that pairs of residues moving more concertedly than others-with distances remaining closer to the simulation average-should represent hotspots of allosteric change; and (ii) the shortest path map (SPM), 12,30 which reconstructs the main allosteric communication pathway based on networks of vicinal residues that move with high (anti-)correlation. Out of equilibrium, (iii) dynamical non-equilibrium MD (D-NEMD) simulations 17,[61][62][63][64][65][66] which spawns a large number of short (50 ps) MD simulations from as many unperturbed MD frames, in which GTP is nearly instantaneously hydrolyzed by brute force: deviation form equilibrium MD, averaged over all short simulations, reflects the degree of allosteric perturbation induced by hydrolysis.…”

“…To begin with, atomistic molecular dynamics (MD) simulations of membrane-embedded K-Ras4B were set up and conducted, as discussed below, in 20 independent replicas. From these, we directly derived distance fluctuation (DF) 14,16 matrices and shortest path map (SPM) 12,30 as recounted later (i.e., the first two out of the four allosteric languages considered in our study). In addition, a subset of frames isolated from these equilibrium MD simulations serve as the starting point for further nonequilibrium MD simulations per the final two allostery detection methods (languages), i.e., dynamical nonequilibrium MD (D-NEMD) 17 and anisotropic thermal diffusion (ATD).…”

“…1,2 To meet these requirements, proteins populate a diverse array of structures that are intrinsically dynamic [3][4][5] and are required to sustain well defined and finely tuned functional motions. [6][7][8] Allostery 6,9,10 is a fundamental mechanism regulating such functions, whereby distal parts of a protein or multimeric complex (often not intuitively linkable to active sites or binding interfaces) dynamically communicate with each other, with far-reaching repercussions on cellular activities: examples of the many aspects inextricably dependent on allostery 10 include enzyme function, [11][12][13] protein folding by chaperones, [14][15][16] signal transduction, 17 and regulation of transcription and metabolism. Understanding of allostery has been constantly expanding since seminal studies in the 1960s 18 and 1980s, 19 with the topic being extensively reviewed and reformulated.…”

“…Our overarching aim is to extract consensus information that will point us to the key residues/substructures and essential dynamic traits mediating allosteric regulation in K-Ras (K-Ras4B). Chosen methods to decrypt allostery include: (i) residue-pair distance fluctuation (DF) analysis, normally used to detect allosteric "crosstalk" patterns in large proteins and complexes thereof (e.g., 14,16,60 ); (ii) the shortest path map (SPM) method devised by Osuna and coworkers 12,30 to suggest (even distal) mutations that are most likely to allosterically impact on an enzyme's reactivity as desired; (iii) the dynamical nonequilibrium MD (D-NEMD) simulations initially developed by Ciccotti and Jacucci, 61 which maps allosteric signal transduction from effector and/or substrate binding sites in receptors and enzymes; 17,[62][63][64][65][66] and (iv) anisotropic thermal diffusion (ATD) 67 which entails heating an effector in its binding site within a (supercooled) protein or complex, and monitoring whereto the allosteric message propagates.…”