CHARMM at 45: Enhancements in Accessibility, Functionality, and Speed.

Since its inception nearly a half century ago, CHARMM has been playing a central role in computational biochemistry and biophysics. Commensurate with the developments in experimental research and advances in computer hardware, the range of methods and applicability of CHARMM have also grown. This review summarizes major developments that occurred after 2009 when the last review of CHARMM was published.

DFT/MM Simulations for Cycloreversion Reaction of Cyclobutane Pyrimidine Dimer with Deprotonated and Protonated E283.

DNA photolyase targets the primary ultraviolet (UV)-induced DNA lesion─cyclobutane pyrimidine dimer (CPD), attaches to it, and catalyzes its dissociation. The catalytic mechanism of DNA photolyase and the role of the conserved residue E283 remain subjects of debate. This study employs two-dimensional potential energy surface maps and minimum free energy paths calculated at the ωB97XD/6-31G/MM level to elucidate these mechanisms.

Training machine learning potentials for reactive systems: A Colab tutorial on basic models.

In the last several years, there has been a surge in the development of machine learning potential (MLP) models for describing molecular systems. We are interested in a particular area of this field - the training of system-specific MLPs for reactive systems - with the goal of using these MLPs to accelerate free energy simulations of chemical and enzyme reactions. To help new members in our labs become familiar with the basic techniques, we have put together a self-guided Colab tutorial (https://cc-ats.

Free Energy Profile Decomposition Analysis for QM/MM Simulations of Enzymatic Reactions.

In enzyme mechanistic studies and mutant design, it is highly desirable to know the individual residue contributions to the reaction free energy and barrier. In this work, we show that such free energy contributions from each residue can be readily obtained by postprocessing quantum mechanical molecular mechanical (ai-QM/MM) free energy simulation trajectories. Specifically, through a mean force integration along the minimum free energy pathway, one can obtain the electrostatic, polarization, and van der Waals contributions from each residue to the free energy barrier.

Hybrid Metal-Ligand Interfacial Dipole Engineering of Functional Plasmonic Nanostructures for Extraordinary Responses of Optoelectronic Properties.

Programmable manipulation of inorganic-organic interfacial electronic properties of ligand-functionalized plasmonic nanoparticles (NPs) is the key parameter dictating their applications such as catalysis, photovoltaics, and biosensing. Here we report the localized surface plasmon resonance (LSPR) properties of gold triangular nanoprisms (Au TNPs) in solid state that are functionalized with dipolar, conjugated ligands. A library of thiocinnamate ligands with varying surface dipole moments were used to functionalize TNPs, which results in ∼150 nm reversible tunability of LSPR peak wavelength with significant peak broadening (∼230 meV).

Bridging semiempirical and ab initio QM/MM potentials by Gaussian process regression and its sparse variants for free energy simulation.

Free energy simulations that employ combined quantum mechanical and molecular mechanical (QM/MM) potentials at ab initio QM (AI) levels are computationally highly demanding. Here, we present a machine-learning-facilitated approach for obtaining AI/MM-quality free energy profiles at the cost of efficient semiempirical QM/MM (SE/MM) methods. Specifically, we use Gaussian process regression (GPR) to learn the potential energy corrections needed for an SE/MM level to match an AI/MM target along the minimum free energy path (MFEP).

Revealing intrinsic changes of DNA induced by spore photoproduct lesion through computer simulation.

In bacterial endospores, a cross-linked thymine dimer, 5-thyminyl-5,6-dihydrothymine, commonly referred to as the spore photoproduct (SP), is found as the dominant DNA photo lesion under UV radiation. During spore germination, SP is faithfully repaired by the spore photoproduct lyase (SPL) for normal DNA replication to resume. Despite this general mechanism, the exact way in which SP modifies the duplex DNA structure so that the damaged site can be recognized by SPL to initiate the repair process is still unclear.

Machine learning based implicit solvent model for aqueous-solution alanine dipeptide molecular dynamics simulations.

Inspired by the recent work from Noé and coworkers on the development of machine learning based implicit solvent model for the simulation of solvated peptides [Chen , , 2021, , 084101], here we report another investigation of the possibility of using machine learning (ML) techniques to "derive" an implicit solvent model directly from explicit solvent molecular dynamics (MD) simulations. For alanine dipeptide, a machine learning potential (MLP) based on the DeepPot-SE representation of the molecule was trained to capture its interactions with its average solvent environment configuration (ASEC). The predicted forces on the solute deviated only by an RMSD of 0.

Facilitating QM/MM free energy simulations by Gaussian process regression with derivative observations.

In combined quantum mechanical and molecular mechanical (QM/MM) free energy simulations, how to synthesize the accuracy of (AI) methods with the speed of semiempirical (SE) methods for a cost-effective QM treatment remains a long-standing challenge. In this work, we present a machine-learning-facilitated method for obtaining AI/MM-quality free energy profiles through efficient SE/MM simulations. In particular, we use Gaussian process regression (GPR) to learn the energy and force corrections needed for SE/MM to match with AI/MM results during molecular dynamics simulations.

Accelerating Quantum Mechanical and Molecular Mechanical (QM/MM) Molecular Dynamics Simulations with Multiple Time Step Integration and a Recalibrated Semiempirical QM/MM Hamiltonian.

Molecular dynamics (MD) simulations employing quantum mechanical and molecular mechanical (ai-QM/MM) potentials are considered to be the state of the art, but the high computational cost associated with the ai-QM calculations remains a theoretical challenge for their routine application. Here, we present a modified protocol of the multiple time step (MTS) method for accelerating ai-QM/MM MD simulations of condensed-phase reactions. Within a previous MTS protocol [Nam 2014, 10, 4175], reference forces are evaluated using a low-level (semiempirical QM/MM) Hamiltonian and employed at inner time steps to propagate the nuclear motions.

Doubly Polarized QM/MM with Machine Learning Chaperone Polarizability.

A major shortcoming of semiempirical (SE) molecular orbital methods is their severe underestimation of molecular polarizability compared with experimental and (AI) benchmark data. In a combined quantum mechanical and molecular mechanical (QM/MM) treatment of solution-phase reactions, solute described by SE methods therefore tends to generate inadequate electronic polarization response to solvent electric fields, which often leads to large errors in free energy profiles. To address this problem, here we present a hybrid framework that improves the response property of SE/MM methods through high-level molecular-polarizability fitting.

Machine-Learning-Assisted Free Energy Simulation of Solution-Phase and Enzyme Reactions.

Despite recent advances in the development of machine learning potentials (MLPs) for biomolecular simulations, there has been limited effort on developing stable and accurate MLPs for enzymatic reactions. Here we report a protocol for performing machine-learning-assisted free energy simulation of solution-phase and enzyme reactions at the ab initio quantum-mechanical/molecular-mechanical (-QM/MM) level of accuracy. Within our protocol, the MLP is built to reproduce the -QM/MM energy and forces on both QM (reactive) and MM (solvent/enzyme) atoms.

Interligand communication in a metal mediated LL'CT system - a case study.

A series of oxo-Mo(iv) complexes, [MoO(Dt)(Dt)] (where Dt = benzene-1,2-dithiol (bdt), toluene-3,4-dithiol (tdt), quinoxaline-2,3-dithiol (qdt), or 3,6-dichloro-benzene-1,2-dithiol (bdtCl); Dt = ,'-dimethylpiperazine-2,3-dithione (MeDt) or ,'-diisopropylpiperazine-2,3-dithione ( PrDt)), possessing a fully oxidized and a fully reduced dithiolene ligand have been synthesized and characterized. The assigned oxidation states of coordinated dithiolene ligands are supported with spectral and crystallographic data. The molecular structure of [MoO(tdt)( PrDt)] () demonstrates a large ligand fold angle of 62.

Reaction Path-Force Matching in Collective Variables: Determining Ab Initio QM/MM Free Energy Profiles by Fitting Mean Force.

First-principles determination of free energy profiles for condensed-phase chemical reactions is hampered by the daunting costs associated with configurational sampling on ab initio quantum mechanical/molecular mechanical (AI/MM) potential energy surfaces. Here, we report a new method that enables efficient AI/MM free energy simulations through mean force fitting. In this method, a free energy path in collective variables (CVs) is first determined on an efficient reactive aiding potential.

Identifying Thermal Decomposition Products of Nitrate Ester Explosives Using Gas Chromatography-Vacuum Ultraviolet Spectroscopy: An Experimental and Computational Study.

Analysis of nitrate ester explosives (e.g., nitroglycerine) using gas chromatography-vacuum ultraviolet spectroscopy (GC-VUV) results in their thermal decomposition into nitric oxide, water, carbon monoxide, oxygen, and formaldehyde.

Accelerated computation of free energy profile at ab initio quantum mechanical/molecular mechanical accuracy via a semi-empirical reference potential. II. Recalibrating semi-empirical parameters with force matching.

An efficient and accurate reference potential simulation protocol is proposed for producing ab initio quantum mechanical/molecular mechanical (AI-QM/MM) quality free energy profiles for chemical reactions in a solvent or macromolecular environment. This protocol involves three stages: (a) using force matching to recalibrate a semi-empirical quantum mechanical (SE-QM) Hamiltonian for the specific reaction under study; (b) employing the recalibrated SE-QM Hamiltonian (in combination with molecular mechanical force fields) as the reference potential to drive umbrella samplings along the reaction pathway; and (c) computing AI-QM/MM energy values for collected configurations from the sampling and performing weighted thermodynamic perturbation to acquire an AI-QM/MM corrected reaction free energy profile. For three model reactions (identity S2 reaction, Menshutkin reaction, and glycine proton transfer reaction) in aqueous solution and one enzyme reaction (Claisen arrangement in chorismate mutase), our simulations using recalibrated PM3 SE-QM Hamiltonians well reproduced QM/MM free energy profiles at the B3LYP/6-31G* level of theory all within 1 kcal mol with a 20 to 45 fold reduction in the computer time.

Exploring Cycloreversion Reaction of Cyclobutane Pyrimidine Dimers Quantum Mechanically.

The cyclobutane pyrimidine dimer (CPD) is a major photoproduct of deoxyribonucleic acid (DNA) that is damaged by ultraviolet light. This DNA lesion can be repaired by DNA photolyase with the aid of UV light and two cofactors. To understand the repair mechanism of CPD and whether protonation of CPD participates in the DNA repair process, the cycloreversion reactions of four CPD models and proton transfers between the adjacent residue Glu283 and CPD models were explored through the quantum mechanical method.

Mapping Free Energy Pathways for ATP Hydrolysis in the ABC Transporter HlyB by the String Method.

HlyB functions as an adenosine triphosphate (ATP)-binding cassette (ABC) transporter that enables bacteria to secrete toxins at the expense of ATP hydrolysis. Our previous work, based on potential energy profiles from combined quantum mechanical and molecular mechanical (QM/MM) calculations, has suggested that the highly conserved H-loop His residue H662 in the nucleotide binding domain (NBD) of HlyB may catalyze the hydrolysis of ATP through proton relay. To further test this hypothesis when entropic contributions are taken into account, we obtained QM/MM minimum free energy paths (MFEPs) for the HlyB reaction, making use of the string method in collective variables.

Elucidating the role of surface passivating ligand structural parameters in hole wave function delocalization in semiconductor cluster molecules.

This article describes the mechanisms underlying electronic interactions between surface passivating ligands and (CdSe) semiconductor cluster molecules (SCMs) that facilitate band-gap engineering through the delocalization of hole wave functions without altering their inorganic core. We show here both experimentally and through density functional theory calculations that the expansion of the hole wave function beyond the SCM boundary into the ligand monolayer depends not only on the pre-binding energetic alignment of interfacial orbitals between the SCM and surface passivating ligands but is also strongly influenced by definable ligand structural parameters such as the extent of their π-conjugation [π-delocalization energy; pyrene (Py), anthracene (Anth), naphthalene (Naph), and phenyl (Ph)], binding mode [dithiocarbamate (DTC, -NH-CS), carboxylate (-COO), and amine (-NH)], and binding head group [-SH, -SeH, and -TeH]. We observe an unprecedentedly large ∼650 meV red-shift in the lowest energy optical absorption band of (CdSe) SCMs upon passivating their surface with Py-DTC ligands and the trend is found to be Ph- < Naph- < Anth- < Py-DTC.

Treating electrostatics with Wolf summation in combined quantum mechanical and molecular mechanical simulations.

The Wolf summation approach [D. Wolf et al., J.

Trapping the ATP binding state leads to a detailed understanding of the F1-ATPase mechanism.

The rotary motor enzyme FoF1-ATP synthase uses the proton-motive force across a membrane to synthesize ATP from ADP and Pi (H2PO4(-)) under cellular conditions that favor the hydrolysis reaction by a factor of 2 × 10(5). This remarkable ability to drive a reaction away from equilibrium by harnessing an external force differentiates it from an ordinary enzyme, which increases the rate of reaction without shifting the equilibrium. Hydrolysis takes place in the neighborhood of one conformation of the catalytic moiety F1-ATPase, whose structure is known from crystallography.

Reaction Path Force Matching: A New Strategy of Fitting Specific Reaction Parameters for Semiempirical Methods in Combined QM/MM Simulations.

We present a general strategy of reparametrizing semiempirical (SE) methods against ab initio (AI) methods for combined quantum mechanical and molecular mechanical (QM/MM) simulations of specific chemical reactions in condensed phases. The resulting approach, designated Reaction Path Force Matching (RP-FM), features cycles of sampling configurations along a reaction path on an efficient SE/MM potential energy surface (PES) and adjusting specific reaction parameters (SRPs) in the SE method such that the atomic forces computed at the target AI/MM level are reproduced. Iterative applications of the RP-FM cycle make possible achieving the accuracy of AI/MM simulations without explicitly sampling the computationally expensive AI/MM PES.

Assessing the accuracy of the isotropic periodic sum method through Madelung energy computation.

We tested the isotropic periodic sum (IPS) method for computing Madelung energies of ionic crystals. The performance of the method, both in its nonpolar (IPSn) and polar (IPSp) forms, was compared with that of the zero-charge and Wolf potentials [D. Wolf, P.

Isotropic Periodic Sum Treatment of Long-Range Electrostatic Interactions in Combined Quantum Mechanical and Molecular Mechanical Calculations.

The isotropic periodic sum (IPS) method was extended to describe long-range electrostatic interactions in combined quantum mechanical and molecular mechanical (QM/MM) calculations. The resulting method, designated QM/MM-IPS, was tested for two ion association processes and a model SN2 reaction in aqueous solution. Potential of mean force (PMF) profiles and radial distribution functions computed from the QM/MM-IPS simulations were compared with those obtained by using the existing QM/MM-Ewald sum and cutoff (QM/MM-Cutoff) methods.

Replica exchange molecular dynamics simulations of an α/β-type small acid soluble protein (SASP).

Small acid soluble proteins (SASPs) of α/β-type play a major role in the resistance of spore DNAs to external assaults. It has been found that α/β-type SASP exhibits intrinsic disorder on isolation, but it acquires a defined native state upon binding to DNA. This disorder to order transition is not yet understood.