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 (ai-QM/MM) level of accuracy. Within our protocol, the MLP is built to reproduce the ai-QM/MM energy and forces on both QM (reactive) and MM (solvent/enzyme) atoms. As an alternative strategy, a delta machine learning potential (ΔMLP) is trained to reproduce the differences between the ai-QM/MM and semiempirical (se) QM/MM energies and forces. To account for the effect of the condensed-phase environment in both MLP and ΔMLP, the DeePMD representation of a molecular system is extended to incorporate the external electrostatic potential and field on each QM atom. Using the Menshutkin and chorismate mutase reactions as examples, we show that the developed MLP and ΔMLP reproduce the ai-QM/MM energy and forces with errors that on average are less than 1.0 kcal/mol and 1.0 kcal mol–1 Å–1, respectively, for representative configurations along the reaction pathway. For both reactions, MLP/ΔMLP-based simulations yielded free energy profiles that differed by less than 1.0 kcal/mol from the reference ai-QM/MM results at only a fraction of the computational cost

Dynamic, structural and thermodynamic basis of insulin-like growth factor 1 kinase allostery mediated by activation loop phosphorylation

Despite the importance of kinases' catalytic activity regulation in cell signaling, detailed mechanisms underlying their activity regulation are poorly understood. Herein, using insulin-like growth factor 1 receptor kinase (IGF-1RK) as a model, the mechanisms of kinase regulation by its activation loop (A-loop) phosphorylation were investigated through molecular dynamics (MD) and alchemical free energy simulations. Analyses of the simulation results and free energy landscapes determined for the entire catalytic cycle of the kinase revealed that A-loop phosphorylation affects each step in the IGF-1RK catalytic cycle, including conformational change, substrate binding/product release and catalytic phosphoryl transfer. Specifically, the conformational equilibrium of the kinase is shifted by 13.2 kcal mol−1 to favor the active conformation after A-loop phosphorylation, which increases substrate binding affinity of the activated kinase. This free energy shift is achieved primarily viadestabilization of the inactive conformation. The free energy of the catalytic reaction is also changed by 3.3 kcal mol−1 after the phosphorylation and in the end, facilitates product release. Analyses of MD simulations showed that A-loop phosphorylation produces these energetic effects by perturbing the side chain interactions around each A-loop tyrosine. These interaction changes are propagated to the remainder of the kinase to modify the orientations and dynamics of the αC-helix and A-loop, and together yield the observed free energy changes. Since many protein kinases share similar interactions identified in this work, the mechanisms of kinase allostery and catalysis unraveled here can be applicable to them

Protein dynamics : the future is bright and complicated!

Biological life depends on motion, and this manifests itself in proteins that display motion over a formidable range of time scales spanning from femtoseconds vibrations of atoms at enzymatic transition states, all the way to slow domain motions occurring on micro to milliseconds. An outstanding challenge in contemporary biophysics and structural biology is a quantitative understanding of the linkages among protein structure, dynamics, and function. These linkages are becoming increasingly explorable due to conceptual and methodological advances. In this Perspective article, we will point toward future directions of the field of protein dynamics with an emphasis on enzymes. Research questions in the field are becoming increasingly complex such as the mechanistic understanding of high-order interaction networks in allosteric signal propagation through a protein matrix, or the connection between local and collective motions. In analogy to the solution to the "protein folding problem,"we argue that the way forward to understanding these and other important questions lies in the successful integration of experiment and computation, while utilizing the present rapid expansion of sequence and structure space. Looking forward, the future is bright, and we are in a period where we are on the doorstep to, at least in part, comprehend the importance of dynamics for biological function

Trapping the ATP binding state leads to a detailed understanding of the F-1-ATPase mechanism

The rotary motor enzyme FoF1-ATP synthase uses the protonmotive force across a membrane to synthesize ATP from ADP and P-i (H2PO4-) under cellular conditions that favor the hydrolysis reaction by a factor of 2 x 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 F-1-ATPase, whose structure is known from crystallography. By use of molecular dynamics simulations we trap a second structure, which is rotated by 40 degrees from the catalytic dwell conformation and represents the state associated with ATP binding, in accord with single-molecule experiments. Using the two structures, we show why Pi is not released immediately after ATP hydrolysis, but only after a subsequent 120 degrees rotation, in agreement with experiment. A concerted conformational change of the alpha(3)beta(3) crown is shown to induce the 40 degrees rotation of the gamma-subunit only when the beta(E) subunit is empty, whereas with Pi bound, beta(E) serves as a latch to prevent the rotation of gamma. The present results provide a rationalization of how F-1-ATPase achieves the coupling between the small changes in the active site of beta(DP) and the 40 degrees rotation of gamma

Trapping the ATP binding state leads to a detailed understanding of the F-1-ATPase mechanism

The rotary motor enzyme FoF1-ATP synthase uses the protonmotive force across a membrane to synthesize ATP from ADP and P-i (H2PO4-) under cellular conditions that favor the hydrolysis reaction by a factor of 2 x 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 F-1-ATPase, whose structure is known from crystallography. By use of molecular dynamics simulations we trap a second structure, which is rotated by 40 degrees from the catalytic dwell conformation and represents the state associated with ATP binding, in accord with single-molecule experiments. Using the two structures, we show why Pi is not released immediately after ATP hydrolysis, but only after a subsequent 120 degrees rotation, in agreement with experiment. A concerted conformational change of the alpha(3)beta(3) crown is shown to induce the 40 degrees rotation of the gamma-subunit only when the beta(E) subunit is empty, whereas with Pi bound, beta(E) serves as a latch to prevent the rotation of gamma. The present results provide a rationalization of how F-1-ATPase achieves the coupling between the small changes in the active site of beta(DP) and the 40 degrees rotation of gamma

Finančno prestrukturiranje Salonita Anhovo d.d. z izdajo zamenljivih obveznic

To provide molecular-level insights into the spontaneous replication error and the mismatch discrimination mechanisms of human DNA polymerase beta (pol beta), we report four crystal structures of pol beta complexed with dG.dTTP and dA.dCTP mismatches in the presence of Mg2+ or Mn2+. The Mg2+-bound ground-state structures show that the dA.dCTP-Mg2+ complex adopts an 'intermediate' protein conformation while the dG.dTTP-Mg2+ complex adopts an open protein conformation. The Mn2+-bound 'pre-chemistry-state' structures show that the dA.dCTP-Mn2+ complex is structurally very similar to the dA.dCTP-Mg2+ complex, whereas the dG.dTTP-Mn2+ complex undergoes a large-scale conformational change to adopt a Watson-Crick-like dG.dTTP base pair and a closed protein conformation. These structural differences, together with our molecular dynamics simulation studies, suggest that pol beta increases replication fidelity via a two-stage mismatch discrimination mechanism, where one is in the ground state and the other in the closed conformation state. In the closed conformation state, pol beta appears to allow only a Watson-Crick-like conformation for purine.pyrimidine base pairs, thereby discriminating the mismatched base pairs based on their ability to form the Watson-Crick-like conformation. Overall, the present studies provide new insights into the spontaneous replication error and the replication fidelity mechanisms of pol beta

The water R1(ω) NMRD profiles of a hydrated protein from molecular dynamics simulation

 The hydration of a protein, peroxiredoxin 5, is obtained from a molecular dynamics simulation and compared with the picture of hydration which is obtained by analysing the water proton R1 NMRD profiles using a generally accepted relaxation model [K. Venu, V.P. Denisov and B. Halle, J. Am. Chem. Soc. 119,3122(1997)]. The discrepancy between the hydration pictures derived from the water R1(ω 0)-NMRD profiles and MD is relevant in a discussion of the factors behind the stretched NMRD profile, the distribution of orientationalorder parameters and residence times of buried water used in the NMRD model

Acceleration of Semiempirical QM/MM Methods through Message Passage Interface (MPI), Hybrid MPI/Open Multiprocessing, and Self-Consistent Field Accelerator Implementations

The strategy and implementation of scalable and efficient semiempirical (SE) QM/MM methods in CHARMM are described. The serial version of the code was first profiled to identify routines that required parallelization. Afterward, the code was parallelized and accelerated with three approaches. The first approach was the parallelization of the entire QM/MM routines, including the Fock matrix diagonalization routines, using the CHARMM message passage interface (MPI) machinery. In the second approach, two different self-consistent field (SCF) energy convergence accelerators were implemented using density and Fock matrices as targets for their extrapolations in the SCF procedure. In the third approach, the entire QM/MM and MM energy routines were accelerated by implementing the hybrid MPI/open multiprocessing (OpenMP) model in which both the task- and loop-level parallelization strategies were adopted to balance loads between different OpenMP threads. The present implementation was tested on two solvated enzyme systems (including <100 QM atoms) and an S_N2 symmetric reaction in water. The MPI version exceeded existing SE QM methods in CHARMM, which include the SCC-DFTB and SQUANTUM methods, by at least 4-fold. The use of SCF convergence accelerators further accelerated the code by ∼12–35% depending on the size of the QM region and the number of CPU cores used. Although the MPI version displayed good scalability, the performance was diminished for large numbers of MPI processes due to the overhead associated with MPI communications between nodes. This issue was partially overcome by the hybrid MPI/OpenMP approach which displayed a better scalability for a larger number of CPU cores (up to 64 CPUs in the tested systems)