Structure-based stabilization of insulin as a therapeutic protein assembly via enhanced aromatic-aromatic interactions

Key contributions to protein structure and stability are provided by weakly polar interactions, which arise from asymmetric electronic distributions within amino acids and peptide bonds. Of particular interest are aromatic side chains whose directional π-systems commonly stabilize protein interiors and interfaces. Here, we consider aromatic-aromatic interactions within a model protein assembly: the dimer interface of insulin. Semi-classical simulations of aromatic-aromatic interactions at this interface suggested that substitution of residue TyrB26 by Trp would preserve native structure while enhancing dimerization (and hence hexamer stability). The crystal structure of a [TrpB26]insulin analog (determined as a T3Rf3 zinc hexamer at a resolution of 2.25 Å) was observed to be essentially identical to that of WT insulin. Remarkably and yet in general accordance with theoretical expectations, spectroscopic studies demonstrated a 150-fold increase in the in vitro lifetime of the variant hexamer, a critical pharmacokinetic parameter influencing design of long-acting formulations. Functional studies in diabetic rats indeed revealed prolonged action following subcutaneous injection. The potency of the TrpB26-modified analog was equal to or greater than an unmodified control. Thus, exploiting a general quantum-chemical feature of protein structure and stability, our results exemplify a mechanism-based approach to the optimization of a therapeutic protein assembly

CHARMM: The biomolecular simulation program

CHARMM (Chemistry at HARvard Molecular Mechanics) is a highly versatile and widely used molecular simulation program. It has been developed over the last three decades with a primary focus on molecules of biological interest, including proteins, peptides, lipids, nucleic acids, carbohydrates, and small molecule ligands, as they occur in solution, crystals, and membrane environments. For the study of such systems, the program provides a large suite of computational tools that include numerous conformational and path sampling methods, free energy estimators, molecular minimization, dynamics, and analysis techniques, and model-building capabilities. The CHARMM program is applicable to problems involving a much broader class of many-particle systems. Calculations with CHARMM can be performed using a number of different energy functions and models, from mixed quantum mechanical-molecular mechanical force fields, to all-atom classical potential energy functions with explicit solvent and various boundary conditions, to implicit solvent and membrane models. The program has been ported to numerous platforms in both serial and parallel architectures. This article provides an overview of the program as it exists today with an emphasis on developments since the publication of the original CHARMM article in 1983. © 2009 Wiley Periodicals, Inc.J Comput Chem, 2009.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63074/1/21287_ftp.pd

QMCube (QM3): An all‐purpose suite for multiscale QM/MM calculations

QMCube (QM3) is a suite written in the Python programming language, initially focused on multiscale QM/MM simulations of biological systems, but open enough to address other kinds of problems. It allows the user to combine highly efficient QM and MM programs, providing unified access to a wide range of computational methods. The suite also supplies additional modules with extra functionalities. These modules facilitate common tasks such as performing the setup of the models or process the data generated during the simulations. The design of QM3 has been carried out considering the least number of external dependencies (only an algebra library, already included in the distribution), which makes it extremely portable. Also, the modular structure of the suite should help to expand and develop new computational methods

Mechanochemical Coupling in the Myosin Motor Domain. I. Insights from Equilibrium Active-Site Simulations

Although the major structural transitions in molecular motors are often argued to couple to the binding of Adenosine triphosphate (ATP), the recovery stroke in the conventional myosin has been shown to be dependent on the hydrolysis of ATP. To obtain a clearer mechanistic picture for such “mechanochemical coupling” in myosin, equilibrium active-site simulations with explicit solvent have been carried out to probe the behavior of the motor domain as functions of the nucleotide chemical state and conformation of the converter/relay helix. In conjunction with previous studies of ATP hydrolysis with different active-site conformations and normal mode analysis of structural flexibility, the results help establish an energetics-based framework for understanding the mechanochemical coupling. It is proposed that the activation of hydrolysis does not require the rotation of the lever arm per se, but the two processes are tightly coordinated because both strongly couple to the open/close transition of the active site. The underlying picture involves shifts in the dominant population of different structural motifs as a consequence of changes elsewhere in the motor domain. The contribution of this work and the accompanying paper [36] is to propose the actual mechanism behind these “population shifts” and residues that play important roles in the process. It is suggested that structural flexibilities at both the small and large scales inherent to the motor domain make it possible to implement tight couplings between different structural motifs while maintaining small free-energy drops for processes that occur in the detached states, which is likely a feature shared among many molecular motors. The significantly different flexibility of the active site in different X-ray structures with variable level arm orientations supports the notation that external force sensed by the lever arm may transmit into the active site and influence the chemical steps (nucleotide hydrolysis and/or binding)

Computational Infrared Spectroscopy: Reproducing Kernel- and Multipolar-Based Force Field Simulations for Site-Selective Dynamics of Proteins

Characterizing the structural and functional dynamics of complex systems in the condensed phase requires fine spatial and/or temporal resolution which is a challenging problem, demanding vibrational probes that confer possible functional and steric variation on local properties. Vibrational time occurs in the femtosecond domain and frequencies are dependent on spatial arrangement and the characteristics of the constituent atoms. Therefore, vibrational spectroscopy has become an essential tool to study the structure and dynamics of various biological systems at the molecular level. However, achieving site-specific information on biological molecules of interest, such as proteins, is impossible in many cases or problematic to rely on the intrinsic vibrational modes. To overcome this limitation, the focus of this work is the development and application of several intrinsic backbone and side chain vibrational probes that can be easily incorporated into proteins and be used to site-specifically investigate their structural or environmental properties using reproducing kernel- and multipolar-based force field simulations

Classical and reactive molecular dynamics: Principles and applications in combustion and energy systems

Molecular dynamics (MD) has evolved into a ubiquitous, versatile and powerful computational method for fundamental research in science branches such as biology, chemistry, biomedicine and physics over the past 60 years. Powered by rapidly advanced supercomputing technologies in recent decades, MD has entered the engineering domain as a first-principle predictive method for material properties, physicochemical processes, and even as a design tool. Such developments have far-reaching consequences, and are covered for the first time in the present paper, with a focus on MD for combustion and energy systems encompassing topics like gas/liquid/solid fuel oxidation, pyrolysis, catalytic combustion, heterogeneous combustion, electrochemistry, nanoparticle synthesis, heat transfer, phase change, and fluid mechanics. First, the theoretical framework of the MD methodology is described systemically, covering both classical and reactive MD. The emphasis is on the development of the reactive force field (ReaxFF) MD, which enables chemical reactions to be simulated within the MD framework, utilizing quantum chemistry calculations and/or experimental data for the force field training. Second, details of the numerical methods, boundary conditions, post-processing and computational costs of MD simulations are provided. This is followed by a critical review of selected applications of classical and reactive MD methods in combustion and energy systems. It is demonstrated that the ReaxFF MD has been successfully deployed to gain fundamental insights into pyrolysis and/or oxidation of gas/liquid/solid fuels, revealing detailed energy changes and chemical pathways. Moreover, the complex physico-chemical dynamic processes in catalytic reactions, soot formation, and flame synthesis of nanoparticles are made plainly visible from an atomistic perspective. Flow, heat transfer and phase change phenomena are also scrutinized by MD simulations. Unprecedented details of nanoscale processes such as droplet collision, fuel droplet evaporation, and CO2 capture and storage under subcritical and supercritical conditions are examined at the atomic level. Finally, the outlook for atomistic simulations of combustion and energy systems is discussed in the context of emerging computing platforms, machine learning and multiscale modelling

The interaction of materials and biology: simulations of peptides, surfaces, and biomaterials

Biomaterials were originally designed to augment or replace damaged tissue in the body, but now encompass a wider range of applications including drug delivery, cancer vaccines, electronic sensor devices, and non-fouling coatings for ship hulls. At the heart of all of these applications is the interface between synthetic materials and biology. Modern techniques for studying this interface are limited to the macro and micro scales. With the advent of high performance computing clusters, molecular simulation is now capable of simulating the interface at the nano-scale. This thesis demonstrates how simulation adds important insights to the understanding of biomaterials. It begins with a comprehensive outline of the theoretical aspects of simulating the interface between water and solid surfaces. After this, small surface-bound biological molecules are modelled to explain experiments showing that they can capture cells on the surface. Finally, a new and practical, scalable technique for controlling biological molecules at the surface is developed. This work advances the field of biomaterials by explaining important processes that occur at the interface of biology and technology

A Combined Molecular Dynamics and Density Functional Theory Approach for Generating Liquid Water Configurations for Aqueous-Phase Heterogeneous Catalysis Studies

Aqueous-phase heterogeneous catalysis is an important chemical process in applications such as water remediation, fuel cells, and the production of fuels and chemicals, including from biomass sources. However, designing alternative, improved catalyst materials for these applications is difficult due to fluctuations in the solvation environment surrounding the catalytic species. In order to elucidate the thermodynamics and kinetics of the relevant reactions, it is imperative to gain a better understanding of the roles of liquid water molecules in these reactions. In this work, a method combining both classical and quantum simulations was developed to generate configurations of liquid water molecules over catalytic species adsorbed on a catalyst surface, which can provide valuable insight into the roles of the liquid water reaction environment on aqueous-phase heterogeneous catalysis. The method developed in this work entails combining force field molecular dynamics (FFMD) and density functional theory (DFT) simulations. This method leverages the strengths of each type of simulation to enable the calculation of catalytic energies under “realistic” liquid water configurations. FFMD simulations are used to generate trajectories of liquid water configurations that include thermal fluctuations, while DFT simulations are used to capture the energies associated with bond breaking and forming that are required for microkinetic modeling and catalyst design studies. This FFMD-DFT method was used to calculate the interaction energies between the liquid water environment and the reaction intermediate or transition state species. The trend in the calculated interaction energies was shown to correlate with the trend in hydrogen-bond formation between liquid water molecules and the catalytic species. This work also demonstrated that entropic effects due to the thermal fluctuations in the solvation environment are a significant contribution to the free energies calculated for aqueous-phase, heterogeneously-catalyzed systems. The FFMD-DFT method was also used to calculate reaction energies, activation barriers, and pre-exponential factors to study the kinetics of example O—H and C—H cleavage reactions on a platinum catalyst surface under an aqueous reaction environment. Using this method, it was found that O—H cleavage reactions prefer H2O-mediated pathways, while C—H cleavage reactions prefer non-H2O-mediated pathways. In summary, the FFMD-DFT method developed in this work has been shown to be a robust technique for generating realistic liquid water configurations over catalytic species on a platinum catalyst surface. Those liquid water configurations can be used to calculate catalytic properties that can provide insight into the roles of water molecules in these reactions and facilitate microkinetic modeling and catalyst design studies

Maturation of the SARS-CoV-2 virus is regulated by dimerization of its main protease

SARS-CoV-2 main protease (Mpro) involved in COVID-19 is required for maturation of the virus and infection of host cells. The key question is how to block the activity of Mpro. By combining atomistic simulations with machine learning, we found that the enzyme regulates its own activity by a collective allosteric mechanism that involves dimerization and binding of a single substrate. At the core of the collective mechanism is the coupling between the catalytic site residues, H41 and C145, which direct the activity of Mpro dimer, and two salt bridges formed between R4 and E290 at the dimer interface. If these salt bridges are mutated, the activity of Mpro is blocked. The results suggest that dimerization of main proteases is a general mechanism to foster coronavirus proliferation, and propose a robust drug-based strategy that does not depend on the frequently mutating spike proteins at the viral envelope used to develop vaccines. (c) 2022 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Peer reviewe