Accelerating molecular simulations of proteins using Bayesian inference on weak information

Atomistic molecular dynamics (MD) simulations of protein molecules are too computationally expensive to predict most native structures from amino acid sequences. Here, we integrate “weak” external knowledge into folding simulations to predict protein structures, given their sequence. For example, we instruct the computer “to form a hydrophobic core,” “to form good secondary structures,” or “to seek a compact state.” This kind of information has been too combinatoric, nonspecific, and vague to help guide MD simulations before. Within atomistic replica-exchange molecular dynamics (REMD), we develop a statistical mechanical framework, modeling using limited data with coarse physical insight(s) (MELD + CPI), for harnessing weak information. As a test, we apply MELD + CPI to predict the native structures of 20 small proteins. MELD + CPI samples to within less than 3.2 Å from native for all 20 and correctly chooses the native structures (<4 Å) for 15 of them, including ubiquitin, a millisecond folder. MELD + CPI is up to five orders of magnitude faster than brute-force MD, satisfies detailed balance, and should scale well to larger proteins. MELD + CPI may be useful where physics-based simulations are needed to study protein mechanisms and populations and where we have some heuristic or coarse physical knowledge about states of interest.

Download Full-text

Molecular dynamics simulations suggest stabilizing mutations in a de novo designed α/β protein

Protein Engineering Design and Selection ◽

10.1093/protein/gzaa005 ◽

2019 ◽

Vol 32 (7) ◽

pp. 317-329

Author(s):

Matthew Gill ◽

Michelle E McCully

Keyword(s):

Molecular Dynamics ◽

Secondary Structure ◽

Surface Area ◽

De Novo ◽

Md Simulations ◽

Solvent Accessible Surface Area ◽

Hydrophobic Core ◽

Design Strategies ◽

Major Interest ◽

Core Packing

Abstract Designing functional proteins that can withstand extreme heat is beneficial for industrial and protein therapeutic applications. Thus, elucidating the atomic-level determinants of thermostability is a major interest for rational protein design. To that end, we compared the structure and dynamics of a set of previously designed, thermostable proteins based on the activation domain of human procarboxypeptidase A2 (AYEwt). The mutations in these designed proteins were intended to increase hydrophobic core packing and inter-secondary-structure interactions. To evaluate whether these design strategies were successfully deployed, we performed all-atom, explicit-solvent molecular dynamics (MD) simulations of AYEwt and three designed variants at both 25 and 100°C. Our MD simulations agreed with the relative experimental stabilities of the designs based on their secondary structure content, Cα root-mean-square deviation/fluctuation, and buried-residue solvent accessible surface area. Using a contact analysis, we found that the designs stabilize inter-secondary structure interactions and buried hydrophobic surface area, as intended. Based on our analysis, we designed three additional variants to test the role of helix stabilization, core packing, and a Phe → Met mutation on thermostability. We performed the additional MD simulations and analysis on these variants, and these data supported our predictions.

Download Full-text

PDBMD2CD: providing predicted protein circular dichroism spectra from multiple molecular dynamics-generated protein structures

Nucleic Acids Research ◽

10.1093/nar/gkaa296 ◽

2020 ◽

Vol 48 (W1) ◽

pp. W17-W24 ◽

Cited By ~ 1

Author(s):

Elliot D Drew ◽

Robert W Janes

Keyword(s):

Molecular Dynamics ◽

Circular Dichroism ◽

Protein Structures ◽

Experimental Spectrum ◽

Md Simulations ◽

Resonance Spectroscopy ◽

Cd Spectra ◽

Structure Information ◽

Multiple Protein ◽

Circular Dichroïsm

Abstract PDBMD2CD is a new web server capable of predicting circular dichroism (CD) spectra for multiple protein structures derived from molecular dynamics (MD) simulations, enabling predictions from thousands of protein atomic coordinate files (e.g. MD trajectories) and generating spectra for each of these structures provided by the user. Using MD enables exploration of systems that cannot be monitored by direct experimentation. Validation of MD-derived data from these types of trajectories can be difficult via conventional structure-determining techniques such as crystallography or nuclear magnetic resonance spectroscopy. CD is an experimental technique that can provide protein structure information from such conditions. The website utilizes a much faster (minimum ∼1000×) and more accurate approach for calculating CD spectra than its predecessor, PDB2CD (1). As well as improving on the speed and accuracy of current methods, new analysis tools are provided to cluster predictions or compare them against experimental CD spectra. By identifying a subset of the closest predicted CD spectra derived from PDBMD2CD to an experimental spectrum, the associated cluster of structures could be representative of those found under the conditions in which the MD studies were undertaken, thereby offering an analytical insight into the results. PDBMD2CD is freely available at: https://pdbmd2cd.cryst.bbk.ac.uk.

Download Full-text

RIP-MD: a tool to study residue interaction networks in protein molecular dynamics

PeerJ ◽

10.7717/peerj.5998 ◽

2018 ◽

Vol 6 ◽

pp. e5998 ◽

Cited By ~ 12

Author(s):

Sebastián Contreras-Riquelme ◽

Jose-Antonio Garate ◽

Tomas Perez-Acle ◽

Alberto J.M. Martin

Keyword(s):

Molecular Dynamics ◽

Protein Structures ◽

Md Simulations ◽

Relevant Information ◽

Interaction Networks ◽

Salt Bridges ◽

Residue Interaction ◽

Non Covalent Interactions ◽

Protein Molecular Dynamics ◽

Covalent Interactions

Protein structure is not static; residues undergo conformational rearrangements and, in doing so, create, stabilize or break non-covalent interactions. Molecular dynamics (MD) is a technique used to simulate these movements with atomic resolution. However, given the data-intensive nature of the technique, gathering relevant information from MD simulations is a complex and time consuming process requiring several computational tools to perform these analyses. Among different approaches, the study of residue interaction networks (RINs) has proven to facilitate the study of protein structures. In a RIN, nodes represent amino-acid residues and the connections between them depict non-covalent interactions. Here, we describe residue interaction networks in protein molecular dynamics (RIP-MD), a visual molecular dynamics (VMD) plugin to facilitate the study of RINs using trajectories obtained from MD simulations of proteins. Our software generates RINs from MD trajectory files. The non-covalent interactions defined by RIP-MD include H-bonds, salt bridges, VdWs, cation-π, π–π, Arginine–Arginine, and Coulomb interactions. In addition, RIP-MD also computes interactions based on distances between Cαs and disulfide bridges. The results of the analysis are shown in an user friendly interface. Moreover, the user can take advantage of the VMD visualization capacities, whereby through some effortless steps, it is possible to select and visualize interactions described for a single, several or all residues in a MD trajectory. Network and descriptive table files are also generated, allowing their further study in other specialized platforms. Our method was written in python in a parallelized fashion. This characteristic allows the analysis of large systems impossible to handle otherwise. RIP-MD is available at http://www.dlab.cl/ripmd.

Download Full-text

Relative Affinities of Protein-Cholesterol Interactions from Equilibrium Molecular Dynamics Simulations

10.1101/2021.06.02.446704 ◽

2021 ◽

Author(s):

T. Bertie Ansell ◽

Luke Curran ◽

Michael R Horrell ◽

Tanadet Pipatpolkai ◽

Suzanne C Letham ◽

...

Keyword(s):

Molecular Dynamics ◽

Membrane Proteins ◽

Membrane Protein ◽

Specific Interaction ◽

Protein Structures ◽

Md Simulations ◽

Lipid Binding ◽

Coarse Grained ◽

Binding Affinities ◽

Interaction Sites

Specific interactions of lipids with membrane proteins contribute to protein stability and function. Multiple lipid interactions surrounding a membrane protein are often identified in molecular dynamics (MD) simulations and are, increasingly, resolved in cryo-EM densities. Determining the relative importance of specific interaction sites is aided by determination of lipid binding affinities by experimental or simulation methods. Here, we develop a method for determining protein-lipid binding affinities from equilibrium coarse-grained MD simulations using binding saturation curves, designed to mimic experimental protocols. We apply this method to directly obtain affinities for cholesterol binding to multiple sites on a range of membrane proteins and compare our results with free energies obtained from density-based equilibrium methods and with potential of mean force calculations, getting good agreement with respect to the ranking of affinities for different sites. Thus, our binding saturation method provides a robust, high-throughput alternative for determining the relative consequence of individual sites seen in e.g. cryo-EM derived membrane protein structures surrounded by a plethora of ancillary lipid densities.

Download Full-text

Folding simulation of Trp-cage utilizing a new AMBER compatible force field with coupled main chain torsions

Journal of Theoretical and Computational Chemistry ◽

10.1142/s0219633614500266 ◽

2014 ◽

Vol 13 (04) ◽

pp. 1450026 ◽

Cited By ~ 4

Author(s):

Lirong Mou ◽

Xiangyu Jia ◽

Ya Gao ◽

Yongxiu Li ◽

John Z. H. Zhang ◽

...

Keyword(s):

Force Field ◽

Main Chain ◽

Md Simulations ◽

Replica Exchange ◽

Hydrophobic Core ◽

Native Structure ◽

Folding Simulation ◽

Torsion Potential ◽

Folding Simulations ◽

Α Helix

A newly developed AMBER compatible force field with coupled backbone torsion potential terms (AMBER032D) is utilized in a folding simulation of a mini-protein Trp-cage. Through replica exchange and direct molecular dynamics (MD) simulations, a multi-step folding mechanism with a synergetic folding of the hydrophobic core (HPC) and the α-helix in the final stage is suggested. The native structure has the lowest free energy and the melting temperature predicted from the specific heat capacity Cvis only 12 K higher than the experimental measurement. This study, together with our previous study, shows that AMBER032Dis an accurate force field that can be used for protein folding simulations.

Download Full-text

Efficient Treatment of Fixed and Induced Dipolar Interactions

MRS Proceedings ◽

10.1557/proc-653-z7.22 ◽

2000 ◽

Vol 653 ◽

Author(s):

Celeste Sagui ◽

Thoma Darden

Keyword(s):

Molecular Dynamics ◽

Md Simulations ◽

Lagrangian Formalism ◽

Dipolar Interactions ◽

Time Step ◽

Efficient Treatment ◽

Particle Mesh Ewald ◽

Fixed Charges ◽

Self Consistency ◽

Induced Dipoles

AbstractFixed and induced point dipoles have been implemented in the Ewald and Particle-Mesh Ewald (PME) formalisms. During molecular dynamics (MD) the induced dipoles can be propagated along with the atomic positions either by interation to self-consistency at each time step, or by a Car-Parrinello (CP) technique using an extended Lagrangian formalism. The use of PME for electrostatics of fixed charges and induced dipoles together with a CP treatment of dipole propagation in MD simulations leads to a cost overhead of only 33% above that of MD simulations using standard PME with fixed charges, allowing the study of polarizability in largemacromolecular systems.

Download Full-text

Improved Sampling Strategies for Protein Model Refinement based on Molecular Dynamics Simulation

10.26434/chemrxiv.13299197.v1 ◽

2020 ◽

Author(s):

Lim Heo ◽

Collin Arbour ◽

Michael Feig

Keyword(s):

Molecular Dynamics ◽

Molecular Dynamics Simulation ◽

Structure Prediction ◽

Protein Structures ◽

Conformational Space ◽

Dynamics Simulation ◽

Model Refinement ◽

Protein Model ◽

Lower Accuracy ◽

Simulation Based

Protein structures provide valuable information for understanding biological processes. Protein structures can be determined by experimental methods such as X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, or cryogenic electron microscopy. As an alternative, in silico methods can be used to predict protein structures. Those methods utilize protein structure databases for structure prediction via template-based modeling or for training machine-learning models to generate predictions. Structure prediction for proteins distant from proteins with known structures often results in lower accuracy with respect to the true physiological structures. Physics-based protein model refinement methods can be applied to improve model accuracy in the predicted models. Refinement methods rely on conformational sampling around the predicted structures, and if structures closer to the native states are sampled, improvements in the model quality become possible. Molecular dynamics simulations have been especially successful for improving model qualities but although consistent refinement can be achieved, the improvements in model qualities are still moderate. To extend the refinement performance of a simulation-based protocol, we explored new schemes that focus on an optimized use of biasing functions and the application of increased simulation temperatures. In addition, we tested the use of alternative initial models so that the simulations can explore conformational space more broadly. Based on the insight of this analysis we are proposing a new refinement protocol that significantly outperformed previous state-of-the-art molecular dynamics simulation-based protocols in the benchmark tests described here.

Download Full-text

Split the Charge Difference in Two! a Rule of Thumb for Adding Proper Amounts of Ions in MD Simulations

10.26434/chemrxiv.9783155.v2 ◽

2020 ◽

Author(s):

Matías R. Machado ◽

Sergio Pantano

Keyword(s):

Molecular Dynamics ◽

Ionic Strength ◽

Molecular Simulations ◽

Md Simulations ◽

Good Practices ◽

Rule Of Thumb ◽

Ionic Concentrations

Despite the relevance of properly setting ionic concentrations in Molecular Dynamics (MD) simulations, methods or practical rules to set ionic strength are scarce and rarely documented. Based on a recently proposed thermodynamics method we provide an accurate rule of thumb to define the electrolytic content in simulation boxes. Extending the use of good practices in setting up MD systems is promptly needed to ensure reproducibility and consistency in molecular simulations.

Download Full-text

Assessing the Antimalarial Potentials of Phytochemicals: Virtual Screening, Molecular Dynamics and In-Vitro Investigations

Letters in Drug Design & Discovery ◽

10.2174/1570180815666180604085626 ◽

2019 ◽

Vol 16 (3) ◽

pp. 291-300

Author(s):

Saumya K. Patel ◽

Mohd Athar ◽

Prakash C. Jha ◽

Vijay M. Khedkar ◽

Yogesh Jasrai ◽

...

Keyword(s):

Molecular Dynamics ◽

Structural Integrity ◽

Md Simulations ◽

Tylophora Indica ◽

Multidrug Resistance Protein 1 ◽

Receptor Complexes ◽

Resistance Protein ◽

Dynamics Simulations ◽

Stable Trajectory

Background: Combined in-silico and in-vitro approaches were adopted to investigate the antiplasmodial activity of Catharanthus roseus and Tylophora indica plant extracts as well as their isolated components (vinblastine, vincristine and tylophorine). Methods: We employed molecular docking to prioritize phytochemicals from a library of 26 compounds against Plasmodium falciparum multidrug-resistance protein 1 (PfMDR1). Furthermore, Molecular Dynamics (MD) simulations were performed for a duration of 10 ns to estimate the dynamical structural integrity of ligand-receptor complexes. Results: The retrieved bioactive compounds viz. tylophorine, vinblastin and vincristine were found to exhibit significant interacting behaviour; as validated by in-vitro studies on chloroquine sensitive (3D7) as well as chloroquine resistant (RKL9) strain. Moreover, they also displayed stable trajectory (RMSD, RMSF) and molecular properties with consistent interaction profile in molecular dynamics simulations. Conclusion: We anticipate that the retrieved phytochemicals can serve as the potential hits and presented findings would be helpful for the designing of malarial therapeutics.

Download Full-text

On the Use of the Discrete Constant pH Molecular Dynamics to Describe the Conformational Space of Peptides

Polymers ◽

10.3390/polym13010099 ◽

2020 ◽

Vol 13 (1) ◽

pp. 99

Author(s):

Cristian Privat ◽

Sergio Madurga ◽

Francesc Mas ◽

Jaime Rubio-Martínez

Keyword(s):

Molecular Dynamics ◽

Amino Acids ◽

Md Simulations ◽

Point Of View ◽

Conformational Space ◽

Conformational Sampling ◽

Protonation State ◽

Constant Ph ◽

Biochemical Systems ◽

Constant Ph Molecular Dynamics

Solvent pH is an important property that defines the protonation state of the amino acids and, therefore, modulates the interactions and the conformational space of the biochemical systems. Generally, this thermodynamic variable is poorly considered in Molecular Dynamics (MD) simulations. Fortunately, this lack has been overcome by means of the Constant pH Molecular Dynamics (CPHMD) methods in the recent decades. Several studies have reported promising results from these approaches that include pH in simulations but focus on the prediction of the effective pKa of the amino acids. In this work, we want to shed some light on the CPHMD method and its implementation in the AMBER suitcase from a conformational point of view. To achieve this goal, we performed CPHMD and conventional MD (CMD) simulations of six protonatable amino acids in a blocked tripeptide structure to compare the conformational sampling and energy distributions of both methods. The results reveal strengths and weaknesses of the CPHMD method in the implementation of AMBER18 version. The change of the protonation state according to the chemical environment is presumably an improvement in the accuracy of the simulations. However, the simulations of the deprotonated forms are not consistent, which is related to an inaccurate assignment of the partial charges of the backbone atoms in the CPHMD residues. Therefore, we recommend the CPHMD methods of AMBER program but pointing out the need to compare structural properties with experimental data to bring reliability to the conformational sampling of the simulations.

Download Full-text