GPU-Accelerated Implementation of Continuous Constant pH Molecular Dynamics in Amber: pK_a Predictions with Single-pH Simulations

Abstract

We present a GPU implementation of the continuous constant pH molecular dynamics (CpHMD) based on the most recent generalized Born implicit-solvent model in the pmemd engine of the Amber molecular dynamics package. To test the accuracy of the tool for rapid pKa predictions, a series of 2-ns single-pH simulations were performed for over 120 titratable residues in 10 benchmark proteins that were previously used to test the various continuous CpHMD methods. The calculated pKa’s showed a root-mean-square deviation of 0.80 and correlation coefficient of 0.83 with respect to experiment. 90% of the pKa’s were converged with estimated errors below 0.1 pH units. Surprisingly, this level of accuracy is similar to our previous replica-exchange simulations with 2 ns per replica and an exchange attempt frequency of 2 ps−1 (Huang, Harris and Shen, J Chem Info Model, 2018). Interestingly, for the linked titration sites in two enzymes, although residue-specific protonation state sampling in the single-pH simulations was not converged within 2 ns, the protonation fraction of the linked residues appeared to be largely converged, and the experimental macroscopic pKa values were reproduced to within 1 pH unit. Comparison with replica-exchange simulations with different exchange attempt frequencies showed that the splitting between the two macroscopic pKa’s is underestimated with frequent exchange attempts such as 2 ps−1, while single-pH simulations overestimate the splitting. The same trend is seen for the single-pH vs. replica-exchange simulations of a hydrogen-bonded aspartyl dyad in a much larger protein. A 2-ns single-pH simulation of a 400-residue protein takes about one hour on a single NVIDIA GeForce RTX 2080 graphics card, which is over 1000 times faster than a CpHMD run on a single CPU core of a high-performance computing cluster node. Thus, we envision that GPU-accelerated continuous CpHMD may be used in routine pKa predictions for a variety of applications, from assisting MD simulations with protonation state assignment to offering pH-dependent corrections of binding free energies and identifying reactive hot spots for covalent drug design.

Proton-Coupled Conformational Activation of SARS Coronavirus Main Proteases and Opportunity for Designing Small-Molecule Broad-Spectrum Targeted Covalent Inhibitors

“…We performed the pH replica-exchange GBNeck2-CpHMD simulations, 20 , 21 which have been shown to give accurate p K a estimates, particularly for Cys 22 and His. 21 The simulations were initiated from the aforementioned crystal structure of SARS-CoV-2 Mpro (PDB: 6y2g( 5 )), whereby all side chains of Asp/Glu/His/Cys/Lys were allowed to titrate. Nine pH replicas were used over a pH range of 5–9, with a total sampling time of 495 ns.…”

“…All Asp, Glu, His, Cys, and Lys side chains were allowed to titrate, with the CpHMD default model p K a ’s of 3.8, 4.2, 6.5, 8.5, and 10.4, respectively. 21 The simulations were run at 300 K with an ionic strength of 0.15 M and an effectively infinite cutoff (999 Å) for nonbonded interactions. The SHAKE algorithm was used to constrain the bonds involving the hydrogens to allow for a 2 fs time step.…”

Assessment of proton-coupled conformational dynamics of SARS and MERS coronavirus papain-like proteases: Implication for designing broad-spectrum antiviral inhibitors

“…The structure was then energy minimized and equilibrated in GB-Neck2 implicit solvent, 26 following our previous protocol. 28 The energy minimization was performed using the steepest decent algorithm for 5000 steps and the conjugate-gradient algorithm for 1000 steps. The equilibration was performed at pH 7 in four stages, each having 2000 MD steps with gradually decreased restraining force constants of 5 kcal/mol/Å 2 , 2 kcal/mol/Å 2 , 1 kcal/mol/Å 2 , and 0 kcal/mol/Å 2 .…”

“…The titration simulations were performed using the recently implemented GPU-accelerated GBNeck2-CpHMD method 28 in the pmemd engine of Amber18. 22 The implementation is built upon the CPU version of the GBNeck2-CpHMD module 21 and the GPU version of the GBNeck2 module 26,29–31 in Amber18.…”

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

“…Some reports pinpointed the strengths and weaknesses [ 37 , 38 , 39 , 40 , 41 ] of these methods as well as a few reviews compiled its development in the past [ 42 , 43 ]. Fortunately, CPHMD methods have improved by introducing modified force fields, water models, or other algorithm details, but adopting also enhanced-sampling approaches to get over the drawbacks [ 22 , 29 , 30 , 44 , 45 , 46 , 47 , 48 , 49 ].…”