An experimentally guided umbrella sampling protocol for biomolecules

Imidazole[1,5-a]pyridine derivatives as EGFR tyrosine kinase inhibitors unraveled by umbrella sampling and steered molecular dynamics simulations

Although the use of the tyrosine kinase inhibitors (TKIs) has been proved that it can save live in a cancer treatment, the currently used drugs bring in many undesirable side-effects. Therefore, the search for new drugs and an evaluation of their efficiency are intensively carried out. Recently, a series of eighteen imidazole[1,5-a]pyridine derivatives were synthetized by us, and preliminary analyses pointed out their potential to be an important platform for pharmaceutical development owing to their promising actions as anticancer agents and enzyme (kinase, HIV-protease,…) inhibitors. In the present theoretical study, we further analyzed their efficiency in using a realistic scenario of computational drug design. Our protocol has been developed to not only observe the atomistic interaction between the EGFR protein and our 18 novel compounds using both umbrella sampling and steered molecular dynamics simulations, but also determine their absolute binding free energies. Calculated properties of the 18 novel compounds were in detail compared with those of two known drugs, erlotinib and osimertinib, currently used in cancer treatment. Inspiringly the simulation results promote three imidazole[1,5-a]pyridine derivatives as promising inhibitors into a further step of clinical trials.

Antiviral mechanisms of two broad-spectrum monoclonal antibodies for rabies prophylaxis and therapy

Rabies is an acute and lethal encephalomyelitis caused by lyssaviruses, among which rabies virus (RABV) is the most prevalent and important for public health. Although preventable through the post-exposure administration of rabies vaccine and immunoglobulins (RIGs), the disease is almost invariably fatal since the onset of clinical signs. Two human neutralizing monoclonal antibodies (mAbs), RVC20 and RVC58, have been shown to be effective in treating symptomatic rabies. To better understand how these mAbs work, we conducted structural modeling and in vitro assays to analyze their mechanisms of action, including their ability to mediate Fc-dependent effector functions. Our results indicate that both RVC20 and RVC58 recognize and lock the RABV-G protein in its pre-fusion conformation. RVC58 was shown to neutralize more potently the extra-cellular virus, while RVC20 mainly acts by reducing viral spreading from infected cells. Importantly, RVC20 was more effective in promoting effector functions compared to RVC58 and 17C7-RAB1 mAbs, the latter of which is approved for human rabies post-exposure treatment. These results provide valuable insights into the multiple mechanisms of action of RVC20 and RVC58 mAbs, offering relevant information for the development of these mAbs as treatment for human rabies.

Transition Path Sampling Based Calculations of Free Energies for Enzymatic Reactions: The Case of Human Methionine Adenosyl Transferase and Plasmodium vivax Adenosine Deaminase

Transition path sampling (TPS) is widely used for the calculations of reaction rates, transition state structures, and reaction coordinates of condensed phase systems. Here we discuss a scheme for the calculation of free energies using the ensemble of TPS reactive trajectories in combination with a window-based sampling technique for enzyme-catalyzed reactions. We calculate the free energy profiles of the reactions catalyzed by the human methionine S-adenosyltransferase (MAT2A) enzyme and the Plasmodium vivax adenosine deaminase (pvADA) enzyme to assess the accuracy of this method. MAT2A catalyzes the formation of S-adenosine-l-methionine following a S_N2 mechanism, and using our method, we estimate the free energy barrier for this reaction to be 16 kcal mol^-1, which is in excellent agreement with the experimentally measured activation energy of 17.27 kcal mol^-1. Furthermore, for the pvADA enzyme-catalyzed reaction we estimate a free energy barrier of 21 kcal mol^-1, and the calculated free energy profile is similar to that predicted from experimental observations. Calculating free energies by employing our simple method within TPS provides significant advantages over methods such as umbrella sampling because it is free from any applied external bias, is accurate compared to experimental measurements, and has a reasonable computational cost.

An Efficient Gaussian-Accelerated Molecular Dynamics (GaMD) Multilevel Enhanced Sampling Strategy: Application to Polarizable Force Fields Simulations of Large Biological Systems

We introduce a novel multilevel enhanced sampling strategy grounded on Gaussian-accelerated Molecular Dynamics (GaMD). First, we propose a GaMD multi-GPUs-accelerated implementation within the Tinker-HP molecular dynamics package. We introduce the new "dual-water" mode and its use with the flexible AMOEBA polarizable force field. By adding harmonic boosts to the water stretching and bonding terms, it accelerates the solvent-solute interactions while enabling speedups, thanks to the use of fast multiple-time step integrators. To further reduce the time-to-solution, we couple GaMD to Umbrella Sampling (US). The GaMD─US/dual-water approach is tested on the 1D Potential of Mean Force (PMF) of the solvated CD2-CD58 system (168 000 atoms), allowing the AMOEBA PMF to converge within 1 kcal/mol of the experimental value. Finally, Adaptive Sampling (AS) is added, enabling AS-GaMD capabilities but also the introduction of the new Adaptive Sampling-US-GaMD (ASUS-GaMD) scheme. The highly parallel ASUS-GaMD setup decreases time to convergence by, respectively, 10 and 20 times, compared to GaMD-US and US. Overall, beside the acceleration of PMF computations, Tinker-HP now allows for the simultaneous use of Adaptive Sampling and GaMD-"dual water" enhanced sampling approaches increasing the applicability of polarizable force fields to large-scale simulations of biological systems.

Molecular Simulations Guidelines for Biological Nanomaterials: From Peptides to Membranes

In studying biological processes and focusing on the molecular mechanisms at the basis of these, molecular dynamics (MD) simulations have demonstrated to be a very useful tool for the past 50 years. This suite of computational methods calculates the time-dependent evolution of a molecular system using physics-based first principles. In this chapter, we give a brief introduction to the theory and practical use of molecular dynamics simulations, highlighting the different models and algorithms that have been developed to tackle specific problems, with a special focus on classical force fields. Some examples of how simulations have been used in the past will help the reader in discerning their power, limitations, and significance.

Computational design of enzymes for biotechnological applications

Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their natural effectiveness has been fine-tuned as a result of millions of years of natural evolution. Such catalytic effectiveness has prompted the use of biocatalysts from multiple sources on different applications, including the industrial production of goods (food and beverages, detergents, textile, and pharmaceutics), environmental protection, and biomedical applications. Natural enzymes often need to be improved by protein engineering to optimize their function in non-native environments. Recent technological advances have greatly facilitated this process by providing the experimental approaches of directed evolution or by enabling computer-assisted applications. Directed evolution mimics the natural selection process in a highly accelerated fashion at the expense of arduous laboratory work and economic resources. Theoretical methods provide predictions and represent an attractive complement to such experiments by waiving their inherent costs. Computational techniques can be used to engineer enzymatic reactivity, substrate specificity and ligand binding, access pathways and ligand transport, and global properties like protein stability, solubility, and flexibility. Theoretical approaches can also identify hotspots on the protein sequence for mutagenesis and predict suitable alternatives for selected positions with expected outcomes. This review covers the latest advances in computational methods for enzyme engineering and presents many successful case studies.

Editing Domain Motions Preorganize the Synthetic Active Site of Prolyl-tRNA Synthetase

Prolyl-tRNA synthetases (ProRSs) catalyze the covalent attachment of proline onto cognate tRNAs, an indispensable step for protein synthesis in all living organisms. ProRSs are modular enzymes and the "prokaryotic-like" ProRSs are distinguished from "eukaryotic-like" ProRSs by the presence of an editing domain (INS) inserted between motifs 2 and 3 of the main catalytic domain. Earlier studies suggested the presence of coupled-domain dynamics could contribute to catalysis; however, the role that the distal, highly mobile INS domain plays in catalysis at the synthetic active site is not completely understood. In the present study, a combination of theoretical and experimental approaches has been used to elucidate the precise role of INS domain dynamics. Quantum mechanical/molecular mechanical simulations were carried out to model catalytic Pro-AMP formation by Enterococcus faecalis ProRS. The energetics of the adenylate formation by the wild-type enzyme was computed and contrasted with variants containing active site mutations, as well as a deletion mutant lacking the INS domain. The combined results revealed that two distinct types of dynamics contribute to the enzyme's catalytic power. One set of motions is intrinsic to the INS domain and leads to conformational preorganization that is essential for catalysis. A second type of motion, stemming from the electrostatic reorganization of active site residues, impacts the height and width of the energy profile and has a critical role in fine tuning the substrate orientation to facilitate reactive collisions. Thus, motions in a distal domain can preorganize the active site of an enzyme to optimize catalysis.

Potential Mean Force from Umbrella Sampling Simulations: What Can We Learn and What Is Missed?

Changes in free energy provide valuable information for molecular recognition, including both ligand-receptor binding thermodynamics and kinetics. Umbrella sampling (US), a widely used free energy calculation method, has long been used to explore the dissociation process of ligand-receptor systems and compute binding free energy. In existing publications, the binding free energy computed from the potential of mean force (PMF) with US simulation mostly yielded "ball park" values with experimental data. However, the computed PMF values are highly influenced by factors such as initial conformations and/or trajectories provided, the reaction coordinate, and sampling of conformational space in each US window. These critical factors have rarely been carefully studied. Here we used US to study the guest aspirin and 1-butanol dissociation processes of β-cyclodextrin (β-CD) and an inhibitor SB2 dissociation from a p38α mitogen-activated protein kinase (MAPK) complex. For β-CD, we used three different β-CD conformations to generate the dissociation path with US windows. For p38α, we generated the dissociation pathway by using accelerated molecular dynamics followed by conformational relaxing with short conventional MD, steered MD, and manual pulling. We found that, even for small β-CD complexes, different β-CD conformations altered the height of the PMF, but the pattern of PMF was not affected if the MD sampling in each US window was well-converged. Because changing the macrocyclic ring conformation needs to rotate dihedral angles in the ring, a bound ligand largely restrains the motion of cyclodextrin. Therefore, once a guest is in the binding site, cyclodextrin cannot freely change its initial conformation, resulting in different absolute heights of the PMF, which cannot be overcome by running excessively long MD simulations for each US window. Moreover, if the US simulations were not converged, the important barrier and minimum were missed. For ligand-protein systems, our studies also suggest that the dissociation trajectories modeled by an enhanced sampling method must maintain a natural molecular movement to avoid biased PMF plots when using US simulations.

Umbrella sampling molecular dynamics simulations reveal concerted ion movement through G-quadruplex DNA channels

We have applied the umbrella sampling (US) method in all-atom molecular dynamics (MD) simulations to obtain potential of mean force (PMF) profiles for ion transport through three representative G-quadruplex DNA channels: [d(TG₄T)]₄, [d(G₃T₄G₄)]₂, and d[G₄(T₄G₄)₃]. The US MD results are in excellent agreement with those obtained previously with the adaptive biasing force (ABF) method. We then utilized the unique features in the US MD method to investigate multi-ion effects in [d(G₃T₄G₄)]₂ and discovered that the concerted ion movement is crucial for fully explaining the unusual experimental results on ion movement in this particular G-quadruplex system. We anticipate that these modern free-energy methods will be useful tools in evaluating ion transport properties of other G-quadruplex DNA channels.

Use of Umbrella Sampling to Calculate the Entrance/Exit Pathway for Z-Pro-Prolinal Inhibitor in Prolyl Oligopeptidase

Prolyl oligopeptidase (POP), a member of the prolyl endopeptidase family, is known to play a role in several neurological disorders. Its primary function is to cleave a wide range of small oligopeptides, including neuroactive peptides. We have used force biased molecular dynamics simulation to study the binding mechanism of POP. We examined three possible binding pathways using Steered Molecular Dynamics (SMD) and Umbrella Sampling (US) on a crystal structure of porcine POP with bound Z-pro-prolinal (ZPP). Using SMD, an exit pathway between the first and seventh blade of the β-propeller domain of POP was found to be a nonviable route. US on binding pathways through the β-propeller tunnel and the TYR190-GLN208 flexible loop at the interface between both POP domains allowed us to isolate the flexible loop pathway as the most probable. Further analysis of that pathway suggests a long-range covariation of the interdomain H-bond network, which indicates the possibility of large-scale domain reorientation observed in bacterial homologues and hypothesized to also occur in human POP.

The role of oligomerization and cooperative regulation in protein function: the case of tryptophan synthase

The oligomerization/co-localization of protein complexes and their cooperative regulation in protein function is a key feature in many biological systems. The synergistic regulation in different subunits often enhances the functional properties of the multi-enzyme complex. The present study used molecular dynamics and Brownian dynamics simulations to study the effects of allostery, oligomerization and intermediate channeling on enhancing the protein function of tryptophan synthase (TRPS). TRPS uses a set of α/β–dimeric units to catalyze the last two steps of L-tryptophan biosynthesis, and the rate is remarkably slower in the isolated monomers. Our work shows that without their binding partner, the isolated monomers are stable and more rigid. The substrates can form fairly stable interactions with the protein in both forms when the protein reaches the final ligand–bound conformations. Our simulations also revealed that the α/β–dimeric unit stabilizes the substrate–protein conformation in the ligand binding process, which lowers the conformation transition barrier and helps the protein conformations shift from an open/inactive form to a closed/active form. Brownian dynamics simulations with a coarse-grained model illustrate how protein conformations affect substrate channeling. The results highlight the complex roles of protein oligomerization and the fine balance between rigidity and dynamics in protein function.

Conformational changes of enzymes are often related to regulating and creating an optimal environment for efficient chemistry. An increasing number of evidences also indicate that oligomerization/co-localization of proteins contributes to the efficiency of metabolic pathways. Although static structures have been available for many multi-enzyme complexes, their efficiency is also governed by the synergistic regulation between the multi-units. Our study applies molecular dynamics and Brownian dynamics simulations to the model system, the tryptophan synthase complex. The multi-enzyme complex is a bienzyme nanomachine and its catalytic activity is intimately related to the allosteric signaling and the metabolite transfer between its α– and β–subunits connected by a 25-Å long channel. Our studies suggest that the binding partner is crucial for the ligand binding processes. Although the isolated monomers are stable in the ligand–free state and can form stable interaction if the substrate is in the final bound conformation, it has higher energy barrier when ligand binds to the active site. We also show that the channel does not always exist, but it may be blocked before the enzyme reaches its final bound conformation. The results highlight the importance of forming protein complexes and the cooperative changes during different states.

Biomolecular Structure and Modeling: Problem and Application Perspective

The experimental progress described in the previous chapter has been accompanied by an increasing desire to relate the complex three-dimensional (3D) shapes of biomolecules to their biological functions and interactions with other molecular systems. Structural biology, computational biology, genomics, proteomics, bioinformatics, chemoinformatics, and others are natural partner disciplines in such endeavors.

Molecular dynamics-based approaches for enhanced sampling of long-time, large-scale conformational changes in biomolecules

The rugged energy landscape of biomolecules together with shortcomings of traditional molecular dynamics (MD) simulations require specialized methods for capturing large-scale, long-time configurational changes along with chemical dynamics behavior. In this report, MD-based methods for biomolecules are surveyed, involving modification of the potential, simulation protocol, or algorithm as well as global reformulations. While many of these methods are successful at probing the thermally accessible configuration space at the expense of altered kinetics, more sophisticated approaches like transition path sampling or Markov chain models are required to obtain mechanistic information, reaction pathways, and/or reaction rates. Divide-and-conquer methods for sampling and for piecing together reaction rate information are especially suitable for readily available computer cluster networks. Successful applications to biomolecules remain a challenge.