The molecular actions of proteins occur along reaction coordinates. Current computer methods have limited ability to explore them. We describe a fast protocol called MELD-path that (1) efficiently samples relevant conformational states via MELD, an accelerator of Molecular Dynamics (MD), (2) seeds multiple short MD trajectories from MELD states, and then (3) constructs Markov State Models (MSM) that give the routes and kinetics. We tested the method against extensive (multi μs) MD simulations of the right-handed- to left-handed-helix transition of a 9-mer peptide of AIB, the symmetry of which allows us to establish convergence. MELD-path finds all the metastable states, their correct relative populations, and the full ensemble of routes, not just a single assumed route. For this transition, we find a very broad route structure. MELD-path is highly parallelizable and efficient, yielding the full route map in a few days of computation. We believe MELD-path could be a general and rapid way to explore mechanistic processes in biomolecules on the computer.

Vibrational spectroscopy is an essential tool in chemical analyses, biological assays, and studies of functional materials. Over the past decade, various coherent nonlinear vibrational spectroscopic techniques have been developed and enabled researchers to study time-correlations of the fluctuating frequencies that are directly related to solute-solvent dynamics, dynamical changes in molecular conformations and local electrostatic environments, chemical and biochemical reactions, protein structural dynamics and functions, characteristic processes of functional materials, and so on. In order to gain incisive and quantitative information on the local electrostatic environment, molecular conformation, protein structure and interprotein contacts, ligand binding kinetics, and electric and optical properties of functional materials, a variety of vibrational probes have been developed and site-specifically incorporated into molecular, biological, and material systems for time-resolved vibrational spectroscopic investigation. However, still, an all-encompassing theory that describes the vibrational solvatochromism, electrochromism, and dynamic fluctuation of vibrational frequencies has not been completely established mainly due to the intrinsic complexity of intermolecular interactions in condensed phases. In particular, the amount of data obtained from the linear and nonlinear vibrational spectroscopic experiments has been rapidly increasing, but the lack of a quantitative method to interpret these measurements has been one major obstacle in broadening the applications of these methods. Among various theoretical models, one of the most successful approaches is a semiempirical model generally referred to as the vibrational spectroscopic map that is based on a rigorous theory of intermolecular interactions. Recently, genetic algorithm, neural network, and machine learning approaches have been applied to the development of vibrational solvatochromism theory. In this review, we provide comprehensive descriptions of the theoretical foundation and various examples showing its extraordinary successes in the interpretations of experimental observations. In addition, a brief introduction to a newly created repository Web site (http://frequencymap.org) for vibrational spectroscopic maps is presented. We anticipate that a combination of the vibrational frequency map approach and state-of-the-art multidimensional vibrational spectroscopy will be one of the most fruitful ways to study the structure and dynamics of chemical, biological, and functional molecular systems in the future.

The authors make the following additions and corrections to the paper, C. Baiz et al., Vibrational Spectroscopic Map, Vibrational Spectroscopy, and Intermolecular Interaction. Chem. Rev. 2020, 120, 7152?7218. 1. The below funding sources should be added to the Acknowledgments section on pages 7204 and 7205: NHG acknowledges support from the National Science Foundation (CHE-1905395). AT thanks the Advanced Materials for Energy-Water Systems (AMEWS) Center (DE-AC02-06CH11357) for support. Thus, the Acknowledgments should be as follows: This work was supported by IBS-R023-D1 (MC). BB wishes to thank the European Union’s Horizon 2020 under the Marie Sk?odowska-Curie Grant Agreement No. 665778, as well as the National Science Centre, Poland (grant no. 2016/23/P/ST4/01720). CRB acknowledges generous support from the National Science Foundation (CHE-847199, BIO-1815354 ) , the National Ins t i t u tes o f Hea l t h (R35GM133359), and the Welch Foundation (F-1891). NHG acknowledges support from the National Science Foundation (CHE-1905395). MWDH-H and JDH thank the University of Nottingham, Green Chemicals Beacon for funding toward this research. AT thanks the Advanced Materials for Energy-Water Systems (AMEWS) Center (DEAC02-06CH11357) for support. MCT acknowledges support from Department of Energy (DE-SC0018983), National Science Foundation (1552996), and National Institutes of Health (GM114500). AGD would like to thank Prof. Andrei Tokmakoff for discussing amide modes when he was a Ph.D. student. LW acknowledges the support from the National Institutes of Health through Award R01GM130697. SAC acknowledges support from National Science Foundation (CHE-1565471). 2. The affiliations of Minhaeng Cho and Kijeong Kwak on page 7201 should be corrected as follows: Minhaeng Cho ? Center for Molecular Spectroscopy and Dynamics, Institute for Basic Science (IBS), Seoul 02841, Republic of Korea; Department of Chemistry, Korea University, Seoul 02841, Republic of Korea Kijeong Kwac ? Center for Molecular Spectroscopy and Dynamics, Institute for Basic Science (IBS), Seoul 02841, Republic of Korea 3. Reference 329 on page 7214 should be replaced with the following paper: (329) Sul, S; Karaiskaj, D.; Jiang Y.; Ge, N.-H. Conformations of N-Acetyl-L-Prolinamide by Two-Dimensional Infrared Spectroscopy. J. Phys. Chem. B 2006, 110, 19891?19905. 4. A correction in the biography of Magnus Hanson-Heine on page 7203 should be made. MH-H received his Ph.D. in 2014, not 2010.

Allosteric regulation plays an important role in many biological processes, such as signal transduction, transcriptional regulation, and metabolism. Allostery is rooted in the fundamental physical properties of macromolecular systems, but its underlying mechanisms are still poorly understood. A collection of contributions to a recent interdisciplinary CECAM (Center Européen de Calcul Atomique et Moléculaire) workshop is used here to provide an overview of the progress and remaining limitations in the understanding of the mechanistic foundations of allostery gained from computational and experimental analyses of real protein systems and model systems. The main conceptual frameworks instrumental in driving the field are discussed. We illustrate the role of these frameworks in illuminating molecular mechanisms and explaining cellular processes, and describe some of their promising practical applications in engineering molecular sensors and informing drug design efforts.