Discriminant analysis optimizes progress coordinate in weighted ensemble simulations of rare event kinetics.

Calculating the kinetics of rare-but-important conformational transitions in complex biomolecules is a significant challenge in computational biophysics. Because of the long timescales needed to observe such processes, regular molecular dynamics simulations are too slow to sample these events by direct integration of the equations of motion. Recently, the weighted ensemble method has gained significant popularity for its ability to compute the rates of conformational transitions in biomolecular systems using unbiased simulations.

Data efficient learning of molecular slow modes from nonequilibrium metadynamics.

Enhanced sampling simulations help overcome free energy barriers and explore molecular conformational space by applying external bias potential along suitable collective variables (CVs). However, identifying optimal CVs that align with the slow modes of complex molecular systems with many coupled degrees of freedom can be a significant challenge. Deep time-lagged independent component analysis (Deep-TICA) addresses this issue by employing an artificial neural network that generates non-linear combinations of molecular descriptors to learn the slowest degrees of freedom.

Acceleration with Interpretability: A Surrogate Model-Based Collective Variable for Enhanced Sampling.

Most enhanced sampling methods facilitate the exploration of molecular free energy landscapes by applying a bias potential along a reduced dimensional collective variable (CV) space. The success of these methods depends on the ability of the CVs to follow the relevant slow modes of the system. Intuitive CVs, such as distances or contacts, often prove inadequate, particularly in biological systems involving many coupled degrees of freedom.

Enhanced Sampling with Suboptimal Collective Variables: Reconciling Accuracy and Convergence Speed.

We introduce an enhanced sampling algorithm to obtain converged free energy landscapes of molecular rare events, even when the collective variable (CV) used for biasing is not optimal. Our approach samples a time-dependent target distribution by combining the on-the-fly probability enhanced sampling and its exploratory variant, OPES Explore. This promotes more transitions between the relevant metastable states and accelerates the convergence speed of the free energy estimate.

Integrating path sampling with enhanced sampling for rare-event kinetics.

Studying the kinetics of long-timescale rare events is a fundamental challenge in molecular simulation. To address this problem, we propose an integration of two different rare-event sampling philosophies: biased enhanced sampling and unbiased path sampling. Enhanced sampling methods, e.

Molecular Insights into the Conformational and Binding Behaviors of Human Serum Albumin Induced by Surface-Active Ionic Liquids.

Extensive research has been carried out to investigate the stability and function of human serum albumin (HSA) when exposed to surface-active ionic liquids (SAILs) with different head groups (imidazolium, morpholinium, and pyridinium) and alkyl chain lengths (ranging from decyl to tetradecyl). Analysis of the protein fluorescence spectra indicates noticeable changes in the secondary structure of HSA with varying concentrations of all SAILs tested. Helicity calculations based on the Fourier transform infrared (FTIR) data show that HSA becomes more organized at the micellar concentration of SAILs, leading to an increased protein activity at this level.

A Stochastic Landscape Approach for Protein Folding State Classification.

Protein folding is a critical process that determines the functional state of proteins. Proper folding is essential for proteins to acquire their functional three-dimensional structures and execute their biological role, whereas misfolded proteins can lead to various diseases, including neurodegenerative disorders like Alzheimer's and Parkinson's. Therefore, a deeper understanding of protein folding is vital for understanding disease mechanisms and developing therapeutic strategies.

Kinetic View of Enzyme Catalysis from Enhanced Sampling QM/MM Simulations.

The rate constants of enzyme-catalyzed reactions () are often approximated from the barrier height of the reactive step. We introduce an enhanced sampling QM/MM approach that directly calculates the kinetics of enzymatic reactions, without introducing the transition-state theory assumptions, and takes into account the dynamical equilibrium between the reactive and non-reactive conformations of the enzyme/substrate complex. Our computed values are in order-of-magnitude agreement with the experimental data for two representative enzymatic reactions.

Data-driven classification of ligand unbinding pathways.

Studying the pathways of ligand-receptor binding is essential to understand the mechanism of target recognition by small molecules. The binding free energy and kinetics of protein-ligand complexes can be computed using molecular dynamics (MD) simulations, often in quantitative agreement with experiments. However, only a qualitative picture of the ligand binding/unbinding paths can be obtained through a conventional analysis of the MD trajectories.

Kinetics from Metadynamics: Principles, Applications, and Outlook.

Metadynamics is a popular enhanced sampling algorithm for computing the free energy landscape of rare events by using molecular dynamics simulation. Ten years ago, Tiwary and Parrinello introduced the infrequent metadynamics approach for calculating the kinetics of transitions across free energy barriers. Since then, metadynamics-based methods for obtaining rate constants have attracted significant attention in computational molecular science.

Deep learning collective variables from transition path ensemble.

The study of the rare transitions that take place between long lived metastable states is a major challenge in molecular dynamics simulations. Many of the methods suggested to address this problem rely on the identification of the slow modes of the system, which are referred to as collective variables. Recently, machine learning methods have been used to learn the collective variables as functions of a large number of physical descriptors.

A Suite of Tutorials for the WESTPA 2.0 Rare-Events Sampling Software [Article v2.0].

The weighted ensemble (WE) strategy has been demonstrated to be highly efficient in generating pathways and rate constants for rare events such as protein folding and protein binding using atomistic molecular dynamics simulations. Here we present two sets of tutorials instructing users in the best practices for preparing, carrying out, and analyzing WE simulations for various applications using the WESTPA software. The first set of more basic tutorials describes a range of simulation types, from a molecular association process in explicit solvent to more complex processes such as host-guest association, peptide conformational sampling, and protein folding.

Predicting residue cooperativity during protein folding: A combined, molecular dynamics and unsupervised learning approach.

Allostery in proteins involves, broadly speaking, ligand-induced conformational transitions that modulate function at active sites distal to where the ligand binds. In contrast, the concept of cooperativity (in the sense used in phase transition theory) is often invoked to understand protein folding and, therefore, function. The modern view on allostery is one based on dynamics and hinges on the time-dependent interactions between key residues in a complex network, interactions that determine the free-energy profile for the reaction at the distal site.

Rare Event Kinetics from Adaptive Bias Enhanced Sampling.

We introduce a novel enhanced sampling approach named on-the-fly probability enhanced sampling (OPES) flooding for calculating the kinetics of rare events from atomistic molecular dynamics simulation. This method is derived from the OPES approach [Invernizzi and Parrinello, 7, 2731-2736], which has been recently developed for calculating converged free energy surfaces for complex systems. In this paper, we describe the theoretical details of the OPES flooding technique and demonstrate the application on three systems of increasing complexity: barrier crossing in a two-dimensional double-well potential, conformational transition in the alanine dipeptide in the gas phase, and the folding and unfolding of the chignolin polypeptide in an aqueous environment.

Force-Field-Dependent DNA Breathing Dynamics: A Case Study of Hoogsteen Base Pairing in A6-DNA.

The Hoogsteen (HG) base pairing conformation, commonly observed in damaged and mutated DNA helices, facilitates DNA repair and DNA recognition. The free energy difference between HG and Watson-Crick (WC) base pairs has been computed in previous studies. However, the mechanism of the conformational transition is not well understood.

Point mutations in SARS-CoV-2 variants induce long-range dynamical perturbations in neutralizing antibodies.

Monoclonal antibodies are emerging as a viable treatment for the coronavirus disease 19 (COVID-19). However, newly evolved variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can reduce the efficacy of currently available antibodies and can diminish vaccine-induced immunity. Here, we demonstrate that the microscopic dynamics of neutralizing monoclonal antibodies can be profoundly modified by the mutations present in the spike proteins of the SARS-COV-2 variants currently circulating in the world population.

Markovian Weighted Ensemble Milestoning (M-WEM): Long-Time Kinetics from Short Trajectories.

We introduce a rare-event sampling scheme, named Markovian Weighted Ensemble Milestoning (M-WEM), which inlays a weighted ensemble framework within a Markovian milestoning theory to efficiently calculate thermodynamic and kinetic properties of long-time-scale biomolecular processes from short atomistic molecular dynamics simulations. M-WEM is tested on the Müller-Brown potential model, the conformational switching in alanine dipeptide, and the millisecond time-scale protein-ligand unbinding in a trypsin-benzamidine complex. Not only can M-WEM predict the kinetics of these processes with quantitative accuracy but it also allows for a scheme to reconstruct a multidimensional free-energy landscape along additional degrees of freedom, which are not part of the milestoning progress coordinate.

Distant residues modulate conformational opening in SARS-CoV-2 spike protein.

Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) involves the attachment of the receptor-binding domain (RBD) of its spike proteins to the ACE2 receptors on the peripheral membrane of host cells. Binding is initiated by a down-to-up conformational change in the spike protein, the change that presents the RBD to the receptor. To date, computational and experimental studies that search for therapeutics have concentrated, for good reason, on the RBD.

Kinetics and free energy of ligand dissociation using weighted ensemble milestoning.

We consider the recently developed weighted ensemble milestoning (WEM) scheme [D. Ray and I. Andricioaei, J.

Free Energy Landscape and Conformational Kinetics of Hoogsteen Base Pairing in DNA vs. RNA.

Genetic information is encoded in the DNA double helix, which, in its physiological milieu, is characterized by the iconical Watson-Crick nucleo-base pairing. Recent NMR relaxation experiments revealed the transient presence of an alternative, Hoogsteen (HG) base pairing pattern in naked DNA duplexes, and estimated its relative stability and lifetime. In contrast with DNA, such structures were not observed in RNA duplexes.

Interfacial water and ion distribution determine ζ potential and binding affinity of nanoparticles to biomolecules.

The molecular features that dictate interactions between functionalized nanoparticles and biomolecules are not well understood. This is in part because for highly charged nanoparticles in solution, establishing a clear connection between the molecular features of surface ligands and common experimental observables such as ζ potential requires going beyond the classical models based on continuum and mean field models. Motivated by these considerations, molecular dynamics simulations are used to probe the electrostatic properties of functionalized gold nanoparticles and their interaction with a charged peptide in salt solutions.

Weighted ensemble milestoning (WEM): A combined approach for rare event simulations.

To directly simulate rare events using atomistic molecular dynamics is a significant challenge in computational biophysics. Well-established enhanced-sampling techniques do exist to obtain the thermodynamic functions for such systems. However, developing methods for obtaining the kinetics of long timescale processes from simulation at atomic detail is comparatively less developed an area.

Controlling Electron Dynamics with Carrier-Envelope Phases of a Laser Pulse.

A theoretical study on the ionization dynamics of carbon atom irradiated with a few-cycle, intense laser field is performed within a quasiclassical model to get mechanistic insights into an earlier reported carrier-envelope phase dependency of ionization probabilities of an atom [ Phys. Rev. Lett.

Effects of alloying on mode-selectivity in HO dissociation on Cu/Ni bimetallic surfaces.

The influence of alloying on mode-selectivity in HO dissociation on Cu/Ni bimetallic surfaces has been studied using a fully quantum approach based on reaction path Hamiltonian. Both the metal alloy catalyst surface and the normal modes of HO impact the chemical reactivity of HO dissociation. A combination of these two different factors will enhance their influence reasonably.