The Early Era of Laser-Selective Chemistry 1960∼1985: Roots of Modern Quantum Control.

Physicists revolutionized the scientific world when they invented the laser in 1960. During the next two decades, fruitful interplay occurred between theoreticians and experimentalists seeking progress in laser-selective chemistry. In the Early Era, defined as 1960∼1985, scientists gradually realized the immense complexity of the problem of performing tailored manipulations at the molecular scale. However, their efforts opened the doors to a new, broader scientific field of research called quantum control which developed in the Modern Era, defined as 1985 to the present time. This Perspective aims to show that the roots of quantum control may be linked to endeavors to manipulate chemical reactions with lasers and thus reaches as far back as the invention of the laser in 1960. We will emphasize the role of advancing technology, the prescience in the questions raised by researchers, and the role of interdisciplinary research. The Perspective concludes with an assessment of what was achieved in the Early Era.

Interdiction in the Early Folding of the p53 DNA-Binding Domain Leads to Its Amyloid-Like Misfolding.

In this article, we investigate two issues: (a) the initial contact formation events along the folding pathway of the DNA-binding domain of the tumor suppressor protein p53 (core p53); and (b) the intermolecular events leading to its conversion into a prion-like form upon incubation with peptide P8(250-257). In the case of (a), the calculations employ the sequential collapse model (SCM) to identify the segments involved in the initial contact formation events that nucleate the folding pathway. The model predicts that there are several possible initial non-local contacts of comparative stability. The most stable of these possible initial contacts involve the protein segments 159AMAIY163 and 251ILTII255, and it is the only native-like contact. Thus, it is predicted to constitute "Nature's shortcut" to the native structure of the core domain of p53. In the case of issue (b), these findings are then combined with experimental evidence showing that the incubation of the core domain of p53 with peptide P8(250-257), which is equivalent to the native protein segment 250PILTIITL257, leads to an amyloid conformational transition. It is explained how the SCM predicts that P8(250-257) effectively interdicts in the formation of the most stable possible initial contact and, thereby, disrupts the subsequent normal folding. Interdiction by polymeric P8(250-257) seeds is also studied. It is then hypothesized that enhanced folding through one or several of the less stable contacts could play a role in P8(250-257)-promoted core p53 amyloid misfolding. These findings are compared to previous results obtained for the prion protein. Experiments are proposed to test the hypothesis presented regarding core p53 amyloid misfolding.

Protein Folding Interdiction Strategy for Therapeutic Drug Development in Viral Diseases: Ebola VP40 and Influenza A M1.

In a recent paper, we proposed the folding interdiction target region (FITR) strategy for therapeutic drug design in SARS-CoV-2. This paper expands the application of the FITR strategy by proposing therapeutic drug design approaches against Ebola virus disease and influenza A. We predict target regions for folding interdicting drugs on correspondingly relevant structural proteins of both pathogenic viruses: VP40 of Ebola, and matrix protein M1 of influenza A. Identification of the protein targets employs the sequential collapse model (SCM) for protein folding. It is explained that the model predicts natural peptide candidates in each case from which to start the search for therapeutic drugs. The paper also discusses how these predictions could be tested, as well as some challenges likely to be found when designing effective therapeutic drugs from the proposed peptide candidates. The FITR strategy opens a potential new avenue for the design of therapeutic drugs that promises to be effective against infectious diseases.

Identification of Two Early Folding Stage Prion Non-Local Contacts Suggested to Serve as Key Steps in Directing the Final Fold to Be Either Native or Pathogenic.

The initial steps of the folding pathway of the C-terminal domain of the murine prion protein mPrP(90-231) are predicted based on the sequential collapse model (SCM). A non-local dominant contact is found to form between the connecting region between helix 1 and ß-sheet 1 and the C-terminal region of helix 3. This non-local contact nucleates the most populated molten globule-like intermediate along the folding pathway. A less stable early non-local contact between segments 120-124 and 179-183, located in the middle of helix 2, promotes the formation of a less populated molten globule-like intermediate. The formation of the dominant non-local contact constitutes an example of the postulated Nature's Shortcut to the prion protein collapse into the native structure. The possible role of the less populated molten globule-like intermediate is explored as the potential initiation point for the folding for three pathogenic mutants (T182A, I214V, and Q211P in mouse prion numbering) of the prion protein.

Interdiction of Protein Folding for Therapeutic Drug Development in SARS CoV-2.

In this article, we predict the folding initiation events of the ribose phosphatase domain of protein Nsp3 and the receptor binding domain of the spike protein from the severe acute respiratory syndrome (SARS) coronavirus-2. The calculations employ the sequential collapse model and the crystal structures to identify the segments involved in the initial contact formation events of both viral proteins. The initial contact locations may provide good targets for therapeutic drug development. The proposed strategy is based on a drug binding to the contact location, thereby aiming to prevent protein folding. Peptides are suggested as a natural choice for such protein folding interdiction drugs.

Nature's Shortcut to Protein Folding.

This Feature Article presents a view of the protein folding transition based on the hypothesis that Nature has built features within the sequences that enable a Shortcut to efficient folding. Nature's Shortcut is proposed to be the early establishment of a set of nonlocal weak contacts, constituting protein loops that significantly constrain regions of the collapsed disordered protein into a native-like low-resolution fluctuating topology of major sections of the backbone. Nature's establishment of this scaffold of nonlocal contacts is claimed to bypass what would otherwise be a nearly hopeless unaided search for the final three-dimensional structure in proteins longer than ∼100 amino acids. To support this main contention of the Feature Article, the loop hypothesis (LH) description of early folding events is experimentally tested with time-resolved Förster resonance energy transfer techniques for adenylate kinase, and the data are shown to be consistent with theoretical predictions from the sequential collapse model (SCM). The experimentally based LH and the theoretically founded SCM are argued to provide a unified picture of the role of nonlocal contacts as constituting Nature's Shortcut to protein folding. Importantly, the SCM is shown to reliably predict key nonlocal contacts utilizing only primary sequence information. This view on Nature's Shortcut is open to the protein community for further detailed assessment, including its practical consequences, by suitable application of advanced experimental and computational techniques.

Predicting the location of the non-local contacts in α-synuclein.

In this paper, the Sequential Collapse Model (SCM) for protein folding pathways is applied to investigate the location of the non-local contacts in the intrinsically disordered state of α-synuclein, a protein implicated in the onset and spreading of several serious neurodegenerative diseases. The model relies on the entropic cost of forming protein loops due to self-crowding effects, and the protein sequence to determine contact location and stability. It is found that the model predicts the existence of several possible non-local contacts, and the location of the non-local contacts is consistent with existing experimental evidence. The bearing of these findings on the pathogenic mechanism and its regulation is discussed.

Shaped incoherent light for control of kinetics: Optimization of up-conversion hues in phosphors.

We propose a method for interactively controlling multi-species atomic and molecular systems with incoherent light. The technique is referred to as shaped incoherent light for control (SILC), which entails dynamically tailoring the spectrum of a broadband incoherent source to control atomic and molecular scale kinetics. Optimal SILC light patterns can be discovered with adaptive learning techniques where the system's observed response is fed back to the control for adjustment aiming to improve the objective. To demonstrate this concept, we optimized a SILC source to optimally control the evolving hue in near-IR to visible upconverting phosphors, which share many similarities with chemical reaction kinetics including non-linear behavior. Thus, the results suggest that SILC may be a valuable tool for the control of chemical kinetics with tailored incoherent light.

Analytic Solutions to Coherent Control of the Dirac Equation.

A simple framework for Dirac spinors is developed that parametrizes admissible quantum dynamics and also analytically constructs electromagnetic fields, obeying Maxwell's equations, which yield a desired evolution. In particular, we show how to achieve dispersionless rotation and translation of wave packets. Additionally, this formalism can handle control interactions beyond electromagnetic. This work reveals unexpected flexibility of the Dirac equation for control applications, which may open new prospects for quantum technologies.

How to Make Distinct Dynamical Systems Appear Spectrally Identical.

We show that a laser pulse can always be found that induces a desired optical response from an arbitrary dynamical system. As illustrations, driving fields are computed to induce the same optical response from a variety of distinct systems (open and closed, quantum and classical). As a result, the observed induced dipolar spectra without detailed information on the driving field are not sufficient to characterize atomic and molecular systems. The formulation may also be applied to design materials with specified optical characteristics. These findings reveal unexplored flexibilities of nonlinear optics.

Erratum: Analytic Solutions to Coherent Control of the Dirac Equation [Phys. Rev. Lett. 119, 173203 (2017)].

This corrects the article DOI: 10.1103/PhysRevLett.119.173203.

Macromolecular Crowding Facilitates the Conformational Transition of on-Pathway Molten Globule States of the Prion Protein.

A simple analytical model is applied to study the effects of macromolecular crowding on the stability of partially folded states of the murine prion protein. It is found that relatively low levels of macromolecular crowding stabilize the partially folded states. The magnitude of the stabilization effect is similar for the partially folded to that of the fully folded state. Thus, the model suggests that it is on-pathway molten globule-like states, rather than partially folded states arising from unfolding of the native state, that play a key role in the pathogenic interconversion mechanism under crowded conditions.

Efficient computations of quantum canonical Gibbs state in phase space.

The Gibbs canonical state, as a maximum entropy density matrix, represents a quantum system in equilibrium with a thermostat. This state plays an essential role in thermodynamics and serves as the initial condition for nonequilibrium dynamical simulations. We solve a long standing problem for computing the Gibbs state Wigner function with nearly machine accuracy by solving the Bloch equation directly in the phase space. Furthermore, the algorithms are provided yielding high quality Wigner distributions for pure stationary states as well as for Thomas-Fermi and Bose-Einstein distributions. The developed numerical methods furnish a long-sought efficient computation framework for nonequilibrium quantum simulations directly in the Wigner representation.

Photonic reagents for concentration measurement of flu-orescent proteins with overlapping spectra.

By exploiting photonic reagents (i.e., coherent control by shaped laser pulses), we employ Optimal Dynamic Discrimination (ODD) as a novel means for quantitatively characterizing mixtures of fluorescent proteins with a large spectral overlap. To illustrate ODD, we simultaneously measured concentrations of in vitro mixtures of Enhanced Blue Fluorescent Protein (EBFP) and Enhanced Cyan Fluorescent Protein (ECFP). Building on this foundational study, the ultimate goal is to exploit the capabilities of ODD for parallel monitoring of genetic and protein circuits by suppressing the spectral cross-talk among multiple fluorescent reporters.

Wigner-Lindblad Equations for Quantum Friction.

Dissipative forces are ubiquitous and thus constitute an essential part of realistic physical theories. However, quantization of dissipation has remained an open challenge for nearly a century. We construct a quantum counterpart of classical friction, a velocity-dependent force acting against the direction of motion. In particular, a translationary invariant Lindblad equation is derived satisfying the appropriate dynamical relations for the coordinate and momentum (i.e., the Ehrenfest equations). Numerical simulations establish that the model approximately equilibrates. These findings significantly advance a long search for a universally valid Lindblad model of quantum friction and open opportunities for exploring novel dissipation phenomena.

Operational dynamic modeling transcending quantum and classical mechanics.

We introduce a general and systematic theoretical framework for operational dynamic modeling (ODM) by combining a kinematic description of a model with the evolution of the dynamical average values. The kinematics includes the algebra of the observables and their defined averages. The evolution of the average values is drawn in the form of Ehrenfest-like theorems. We show that ODM is capable of encompassing wide-ranging dynamics from classical non-relativistic mechanics to quantum field theory. The generality of ODM should provide a basis for formulating novel theories.

Identifying biological network structure, predicting network behavior, and classifying network state with High Dimensional Model Representation (HDMR).

This work presents an adapted Random Sampling - High Dimensional Model Representation (RS-HDMR) algorithm for synergistically addressing three key problems in network biology: (1) identifying the structure of biological networks from multivariate data, (2) predicting network response under previously unsampled conditions, and (3) inferring experimental perturbations based on the observed network state. RS-HDMR is a multivariate regression method that decomposes network interactions into a hierarchy of non-linear component functions. Sensitivity analysis based on these functions provides a clear physical and statistical interpretation of the underlying network structure. The advantages of RS-HDMR include efficient extraction of nonlinear and cooperative network relationships without resorting to discretization, prediction of network behavior without mechanistic modeling, robustness to data noise, and favorable scalability of the sampling requirement with respect to network size. As a proof-of-principle study, RS-HDMR was applied to experimental data measuring the single-cell response of a protein-protein signaling network to various experimental perturbations. A comparison to network structure identified in the literature and through other inference methods, including Bayesian and mutual-information based algorithms, suggests that RS-HDMR can successfully reveal a network structure with a low false positive rate while still capturing non-linear and cooperative interactions. RS-HDMR identified several higher-order network interactions that correspond to known feedback regulations among multiple network species and that were unidentified by other network inference methods. Furthermore, RS-HDMR has a better ability to predict network response under unsampled conditions in this application than the best statistical inference algorithm presented in the recent DREAM3 signaling-prediction competition. RS-HDMR can discern and predict differences in network state that arise from sources ranging from intrinsic cell-cell variability to altered experimental conditions, such as when drug perturbations are introduced. This ability ultimately allows RS-HDMR to accurately classify the experimental conditions of a given sample based on its observed network state.

Quiescent fibroblasts exhibit high metabolic activity.

Many cells in mammals exist in the state of quiescence, which is characterized by reversible exit from the cell cycle. Quiescent cells are widely reported to exhibit reduced size, nucleotide synthesis, and metabolic activity. Much lower glycolytic rates have been reported in quiescent compared with proliferating lymphocytes. In contrast, we show here that primary human fibroblasts continue to exhibit high metabolic rates when induced into quiescence via contact inhibition. By monitoring isotope labeling through metabolic pathways and quantitatively identifying fluxes from the data, we show that contact-inhibited fibroblasts utilize glucose in all branches of central carbon metabolism at rates similar to those of proliferating cells, with greater overflow flux from the pentose phosphate pathway back to glycolysis. Inhibition of the pentose phosphate pathway resulted in apoptosis preferentially in quiescent fibroblasts. By feeding the cells labeled glutamine, we also detected a "backwards" flux in the tricarboxylic acid cycle from α-ketoglutarate to citrate that was enhanced in contact-inhibited fibroblasts; this flux likely contributes to shuttling of NADPH from the mitochondrion to cytosol for redox defense or fatty acid synthesis. The high metabolic activity of the fibroblasts was directed in part toward breakdown and resynthesis of protein and lipid, and in part toward excretion of extracellular matrix proteins. Thus, reduced metabolic activity is not a hallmark of the quiescent state. Quiescent fibroblasts, relieved of the biosynthetic requirements associated with generating progeny, direct their metabolic activity to preservation of self integrity and alternative functions beneficial to the organism as a whole.

Low entropic barrier to the hydrophobic collapse of the prion protein: effects of intermediate states and conformational flexibility.

A simple kinetic model is applied to study the folding reaction of the C-terminal domain of the murine prion protein, mPrP(121-231). The model provides an equation linking a protein's folding rate with its native topology and the conformational entropic cost of folding. The model predicts that the average conformational entropic cost per residue associated with the folding transition of mPrP(121-231) is smaller than the average for a broad sample of two-state folding proteins. The results are consistent with the native state of mPrP(121-231) being more flexible than the average protein, but the behavior could also arise from the presence of early intermediate states. The findings are in agreement with experimental and theoretical results on the prion protein conformational flexibility. The model is fully analytical and provides a simple way to obtain a quantitative measure of conformational flexibility in two-state proteins from kinetic and structural experimental data.