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This study analyzes the origin of enzyme catalysis by focusing on the reaction of orotidine 5'-phosphate decarboxylase (ODCase). This reaction involves an enormous catalytic effect of 23 kcal/mol that has been attributed to reactant state destabilization associated with the use of binding energy through the so-called Circe effect. However, our early studies and subsequent key experiments have shown that the presumed effect of the binding energy (namely, the strain exerted by a bond to a phosphate group) does not contribute to the catalysis. In this study, we perform quantitative empirical valence bond calculations that reproduce the catalytic effect of ODCase and the effect of removing the phosphate side chain. The calculations demonstrate that the effect of the phosphate is due to a change in reorganization energy and should not be described as an induced fit effect. Similarly, we show that the overall catalytic effect is due to electrostatic transition state stabilization, which again reflects the smaller reorganization energy in the enzyme than in water. We also elaborate on the problems with the induced fit proposal, including the fact that it does not serve to tell us what the actual origin of the action of the catalytic effect is. In addition to the above points, we use this paper to discuss misconceptions about the meaning of the preorganization effect, as well as other misunderstandings of what is being done in consistent calculations of enzyme catalysis.

A variety of diseases are associated with tyrosine kinase enzymes that activate many proteins via signal transduction cascades. The similar ATP-binding pockets of these tyrosine kinases make it extremely difficult to design selective covalent inhibitors. The present study explores the contribution of the chemical reaction steps to the selectivity of the commercialized inhibitor acalabrutinib over the Bruton's tyrosine kinase (BTK) and the interleukin-2-inducible T-cell kinase (ITK). Ab initio and empirical valence bond (EVB) simulations of the two kinases indicate that the most favorable reaction path involves a water-assisted mechanism of the 2-butynamide reactive group of acalabrutinib. BTK reacts with acalabrutinib with a substantially lower barrier than ITK, according to our calculated free-energy profile and kinetic simulations. Such a difference is due to the microenvironment of the active site, as further supported by a sequence-based analysis of specificity determinants for several commercialized inhibitors. Our study involves a new approach of simulating directly the IC50 and inactivation efficiency

The cleavage of protein inside cell membranes regulates pathological pathways and is a subject of major interest. Thus, the nature of the coupling between the physical environment and the function of such proteins has recently attracted significant experimental and theoretical efforts. However, it is difficult to determine the nature of this coupling uniquely by experimental and theoretical studies unless one can separate the chemical and the environmental factors. This work describes calculations of the activation barriers of the intramembrane rhomboid protease in neutral and charged lipid bilayers and in detergent micelle, trying to explore the environmental effect. The calculations of the chemical barrier are done using the empirical valence bond (EVB) method. Additionally, the renormalization method captures the energetics and dynamical effects of the conformational change. The simulations indicate that the physical environment around the rhomboid protease is not a major factor in changing the chemical catalysis and that the conformational and substrate dynamics do not exhibit long-time coupling. General issues about the action of membrane-embedded enzymes are also considered.

Laboratory evolution combined with computational enzyme design provides the opportunity to generate novel biocatalysts. Nevertheless, it has been challenging to understand how laboratory evolution optimizes designer enzymes by introducing seemingly random mutations. A typical enzyme optimized with laboratory evolution is the abiological Kemp eliminase, initially designed by grafting active site residues into a natural protein scaffold. Here, we relate the catalytic power of laboratory-evolved Kemp eliminases to the statistical energy ( E MaxEnt ) inferred from their natural homologous sequences using the maximum entropy model. The E MaxEnt of designs generated by directed evolution is correlated with enhanced activity and reduced stability, thus displaying a stability-activity trade-off. In contrast, the E MaxEnt for mutants in catalytic-active remote regions (in which remote residues are important for catalysis) is strongly anticorrelated with the activity. These findings provide an insight into the role of protein scaffolds in the adaption to new enzymatic functions. It also indicates that the valley in the E MaxEnt landscape can guide enzyme design for abiological catalysis. Overall, the connection between laboratory and natural evolution contributes to understanding what is optimized in the laboratory and how new enzymatic function emerges in nature, and provides guidance for computational enzyme design.

G-Protein-coupled receptors (GPCRs) belong to an important family of integral membrane receptor proteins that are essential for a variety of transmembrane signaling process, such as vision, olfaction, and hormone responses. They are also involved in many human diseases (Alzheimer's, heart diseases, etc.) and are therefore common drug targets. Thus, understanding the details of the GPCR activation process is a task of major importance. Various types of crystal structures of GPCRs have been solved either at stable end-point states or at possible intermediate states. However, the detailed mechanism of the activation process is still poorly understood. For example, it is not completely clear when the nucleotide release from the G protein occurs and how the key residues on α5 contribute to the coupling process and further affect the binding specificity. In this work we show by free energy analysis that the guanosine diphosphate (GDP) molecule could be released from the Gs protein when the binding cavity is half open. This occurs during the transition to the Gs open state, which is the rate-determining step in the system conformational change. We also account for the experimentally observed slow-down effects by the change of the reaction barriers after mutations. Furthermore, we identify potential key residues on α5 and validated their significance by site-directed mutagenesis, which illustrates that computational works have predictive value even for complex biophysical systems. The methodology of the current work may be applied to other biophysical systems of interest.

Cysteine proteases play a major role in many life processes and are the target of key drugs. The reaction mechanism of these enzymes is a complex process, which involves several steps that are divided into two main groups: acylation and deacylation. In this work, we studied the energy profile for the acylation and a part of the deacylation reaction of three different enzymes, cruzain, papain, and the Q19A-mutated papain with the benzyloxycarbonyl-phenylalanylarginine-4-methylcoumaryl-7-amide (CBZ-FR-AMC) substrate. The calculations were performed using the EVB and PDLD/S-LRA methods. The overall agreement between the calculated and observed results is encouraging and indicates that we captured the correct reaction mechanism. Finally, our finding indicates that the minimum of the reaction profile, between the acylation and deacylation steps, should provide an excellent state for the binding of covalent inhibitors.

The COVID-19 pandemic has been a public health emergency with continuously evolving deadly variants around the globe. Among many preventive and therapeutic strategies, the design of covalent inhibitors targeting the main protease (M(pro)) of SARS-CoV-2 that causes COVID-19 has been one of the hotly pursued areas. Currently, about 30% of marketed drugs that target enzymes are covalent inhibitors. Such inhibitors have been shown in recent years to have many advantages that counteract past reservation of their potential off-target activities, which can be minimized by modulation of the electrophilic warhead and simultaneous optimization of nearby noncovalent interactions. This process can be greatly accelerated by exploration of binding affinities using computational models, which are not well-established yet due to the requirement of capturing the chemical nature of covalent bond formation. Here, we present a robust computational method for effective prediction of absolute binding free energies (ABFEs) of covalent inhibitors. This is done by integrating the protein dipoles Langevin dipoles method (in the PDLD/S-LRA/β version) with quantum mechanical calculations of the energetics of the reaction of the warhead and its amino acid target, in water. This approach evaluates the combined effects of the covalent and noncovalent contributions. The applicability of the method is illustrated by predicting the ABFEs of covalent inhibitors of SARS-CoV-2 M(pro) and the 20S proteasome. Our results are found to be reliable in predicting ABFEs for cases where the warheads are significantly different. This computational protocol might be a powerful tool for designing effective covalent inhibitors especially for SARS-CoV-2 M(pro) and for targeted protein degradation.

Understanding the activation mechanism of the μ-opioid receptor (μ-OR) and its selective coupling to the inhibitory G protein (Gi) is vital for pharmaceutical research aimed at finding treatments for the opioid overdose crisis. Many attempts have been made to understand the mechanism of the μ-OR activation, following the elucidation of new crystal structures such as the antagonist- and agonist-bound μ-OR. However, the focus has not been placed on the underlying energetics and specificity of the activation process. An energy-based picture would not only help to explain this coupling but also help to explore why other possible options are not common. For example, one would like to understand why μ-OR is more selective to Gi than a stimulatory G protein (Gs). Our study used homology modeling and a coarse-grained model to generate all of the possible "end states" of the thermodynamic cycle of the activation of μ-OR. The end points were further used to generate reasonable intermediate structures of the receptor and the Gi to calculate two-dimensional free energy landscapes. The results of the landscape calculations helped to propose a plausible sequence of conformational changes in the μ-OR and Gi system and for exploring the path that leads to its activation. Furthermore, in silico alanine scanning calculations of the last 21 residues of the C terminals of Gi and Gs were performed to shed light on the selective binding of Gi to μ-OR. Overall, the present work appears to demonstrate the potential of multiscale modeling in exploring the action of G protein-coupled receptors.

The ATPase-catalysed conversion of ATP to ADP is a fundamental process in biology. During the hydrolysis of ATP, the α3β3 domain undergoes conformational changes while the central stalk (γ/D) rotates unidirectionally. Experimental studies have suggested that different catalytic mechanisms operate depending on the type of ATPase, but the structural and energetic basis of these mechanisms remains unclear. In particular, it is not clear how the positions of the catalytic dwells influence the energy transduction. Here we show that the observed dwell positions, unidirectional rotation and movement against the applied torque are reflections of the free-energy surface of the systems. Instructively, we determine that the dwell positions do not substantially affect the stopping torque. Our results suggest that the three resting states and the pathways that connect them should not be treated equally. The current work demonstrates how the free-energy landscape determines the behaviour of different types of ATPases. Despite the fundamental role of ATPase in catalysing ATP hydrolysis, the structural and energetic aspects of this process are not fully understood. Coarse-grained computational models have now been used to calculate the free-energy surfaces of different types of ATPases. The catalytic dwell is shown not to be crucial for movement against applied torque.

A variety of signals, including inflammasome activation, trigger the formation of large transmembrane pores by gasdermin D (GSDMD). There are primarily two functions of the GSDMD pore, to drive lytic cell death, known as pyroptosis, and to permit the release of leaderless interleukin-1 (IL-1) family cytokines, a process that does not require pyroptosis. We are interested in the mechanism by which the GSDMD pore channels IL-1 release from living cells. Recent studies revealed that electrostatic interaction, in addition to cargo size, plays a critical role in GSDMD-dependent protein release. Here, we determined computationally that to enable electrostatic filtering against pro-IL-1β, acidic lipids in the membrane need to effectively neutralize positive charges in the membrane-facing patches of the GSDMD pore. In addition, we predicted that salt has an attenuating effect on electrostatic filtering and then validated this prediction using a liposome leakage assay. A calibrated electrostatic screening factor is necessary to account for the experimental observations, suggesting that ion distribution within the pore may be different from the bulk solution. Our findings corroborate the electrostatic influence of IL-1 transport exerted by the GSDMD pore and reveal extrinsic factors, including lipid and salt, that affect the electrostatic environment.

Although computational enzyme design is of great importance, the advances utilizing physics-based approaches have been slow, and further progress is urgently needed. One promising direction is using machine learning, but such strategies have not been established as effective tools for predicting the catalytic power of enzymes. Here, we show that the statistical energy inferred from homologous sequences with the maximum entropy (MaxEnt) principle significantly correlates with enzyme catalysis and stability at the active site region and the more distant region, respectively. This finding decodes enzyme architecture and offers a connection between enzyme evolution and the physical chemistry of enzyme catalysis, and it deepens our understanding of the stability-activity trade-off hypothesis for enzymes. Overall, the strong correlations found here provide a powerful way of guiding enzyme design.

The pandemic caused by SARS-CoV-2 has cost millions of lives and tremendous social/financial loss. The virus continues to evolve and mutate. In particular, the recently emerged "UK", "South Africa", and Delta variants show higher infectivity and spreading speed. Thus, the relationship between the mutations of certain amino acids and the spreading speed of the virus is a problem of great importance. In this respect, understanding the mutational mechanism is crucial for surveillance and prediction of future mutations as well as antibody/vaccine development. In this work, we used a coarse-grained model (that was used previously in predicting the importance of mutations of N501) to calculate the free energy change of various types of single-site or combined-site mutations. This was done for the UK, South Africa, and Delta mutants. We investigated the underlying mechanisms of the binding affinity changes for mutations at different spike protein domains of SARS-CoV-2 and provided the energy basis for the resistance of the E484 mutant to the antibody m396. Other potential mutation sites were also predicted. Furthermore, the in silico predictions were assessed by functional experiments. The results establish that the faster spreading of recently observed mutants is strongly correlated with the binding-affinity enhancement between virus and human receptor as well as with the reduction of the binding to the m396 antibody. Significantly, the current approach offers a way to predict new variants and to assess the effectiveness of different antibodies toward such variants.

G-Protein-coupled receptors (GPCRs) belong to an important family of integral membrane receptor proteins that are essential for a variety of transmembrane signaling process, such as vision, olfaction, and hormone responses. They are also involved in many human diseases (Alzheimer's, heart diseases, etc.) and are therefore common drug targets. Thus, understanding the details of the GPCR activation process is a task of major importance. Various types of crystal structures of GPCRs have been solved either at stable end-point states or at possible intermediate states. However, the detailed mechanism of the activation process is still poorly understood. For example, it is not completely clear when the nucleotide release from the G protein occurs and how the key residues on α5 contribute to the coupling process and further affect the binding specificity. In this work we show by free energy analysis that the guanosine diphosphate (GDP) molecule could be released from the G

The elucidation of the detailed mechanism used by F(0) to convert proton gradient to torque and rotational motion presents a major puzzle despite significant biophysical and structural progress. Although the conceptual model has advanced our understanding of the working principles of such systems, it is crucial to explore the actual mechanism using structure-based models that actually reproduce a unidirectional proton-driven rotation. Our previous work used a coarse-grained (CG) model to simulate the action of F(0). However, the simulations were based on a very tentative structural model of the interaction between subunit a and subunit c. Here, we again use a CG model but with a recent cryo-EM structure of cF(1)F(0) and also explore the proton path using our water flooding and protein dipole Langevin dipole semimacroscopic formalism with its linear response approximation version (PDLD/S-LRA) approaches. The simulations are done in the combined space defined by the rotational coordinate and the proton transport coordinate. The study reproduced the effect of the protomotive force on the rotation of the F(0) while establishing the electrostatic origin of this effect. Our landscape reproduces the correct unidirectionality of the synthetic direction of the F(0) rotation and shows that it reflects the combined electrostatic coupling between the proton transport path and the c-ring conformational change. This work provides guidance for further studies in other proton-driven mechanochemical systems and should lead (when combined with studies of F(1)) to a complete energy transduction picture of the F(0)F(1)-ATPase system.

G-protein-coupled receptors (GPCRs) are among the most important receptors in human physiology and pathology. They serve as master regulators of numerous key processes and are involved in as well as cause debilitating diseases. Consequently, GPCRs are among the most attractive targets for drug design and pharmaceutical interventions (>30% of drugs on the market). The glucagon-like peptide 1 (GLP-1) hormone receptor GLP1R is closely involved in insulin secretion by pancreatic β-cells and constitutes a major druggable target for the development of anti-diabetes and obesity agents. GLP1R structure was recently solved, with ligands, allosteric modulators and as part of a complex with its cognate G protein. However, the translation of this structural data into structure/function understanding remains limited. The current study functionally characterizes GLP1R with special emphasis on ligand and cellular partner binding interactions and presents a free-energy landscape as well as a functional model of the activation cycle of GLP1R. Our results should facilitate a deeper understanding of the molecular mechanism underlying GLP1R activation, forming a basis for improved development of targeted therapeutics for diabetes and related disorders.

This work explored the molecular origin of substrate translocation by the AAA+ motor of the 26S proteasome. This exploration was performed by combining different simulation approaches including calculations of binding free energies, coarse-grained simulations, and considerations of the ATP hydrolysis energy. The simulations were used to construct the free energy landscape for the translocation process. This included the evaluation of the conformational barriers in different translocation steps. Our simulation reveals that the substrate translocation by the AAA+ motor is guided in part by electrostatic interactions. We also validated the experimental observation that bulkier residues in pore loop 1 are responsible for substrate translocation. However, our calculation also reveals that the lysine residues prior to the bulkier residues (conserved along pore loop 1) are also important for the translocation process. We believe that this computational study can help in guiding the ongoing research of the proteasome.

Inhibitors of the proteasome have been extensively studied for their applications in the treatment of human diseases such as hematologic malignancies, autoimmune disorders, and viral infections. Many of the proteasome inhibitors reported in the literature target the non-primed site of proteasome's substrate binding pocket. In this study, we designed, synthesized and characterized a series of novel α-keto phenylamide derivatives aimed at both the primed and non-primed sites of the proteasome. In these derivatives, different substituted phenyl groups at the head group targeting the primed site were incorporated in order to investigate their structure-activity relationship and optimize the potency of α-keto phenylamides. In addition, the biological effects of modifications at the cap moiety, P1、P2 and P3 side chain positions were explored. Many derivatives displayed highly potent biological activities in proteasome inhibition and anticancer activity against a panel of six cancer cell lines, which were further rationalized by molecular modeling analyses. Furthermore, a representative α-ketoamide derivative was tested and found to be active in inhibiting the cellular infection of SARS-CoV-2 which causes the COVID-19 pandemic. These results demonstrate that this new class of α-ketoamide derivatives are potent anticancer agents and provide experimental evidence of the anti-SARS-CoV-2 effect by one of them, thus suggesting a possible new lead to develop antiviral therapeutics for COVID-19., Graphical abstract Image 1

The development of reliable ways of predicting the binding free energies of covalent inhibitors is a challenge for computer-aided drug design. Such development is important, for example, in the fight against the SARS-CoV-2 virus, in which covalent inhibitors can provide a promising tool for blocking Mpro, the main protease of the virus. This work develops a reliable and practical protocol for evaluating the binding free energy of covalent inhibitors. Our protocol presents a major advance over other approaches that do not consider the chemical contribution of the binding free energy. Our strategy combines the empirical valence bond method for evaluating the reaction energy profile and the PDLD/S-LRA/s method for evaluating the noncovalent part of the binding process. This protocol has been used in the calculations of the binding free energy of an α-ketoamide inhibitor of Mpro. Encouragingly, our approach reproduces the observed binding free energy. Our study of covalent inhibitors of cysteine proteases indicates that in the choice of an effective warhead it is crucial to focus on the exothermicity of the point on the free energy surface of a peptide cleavage that connects the acylation and deacylation steps. Overall, we believe that our approach should provide a powerful and effective method for in silico design of covalent drugs.

Understanding the activation mechanism of the μ-opioid receptor (μ-OR) and its selective coupling to the inhibitory G protein (G(i)) is vital for pharmaceutical research aimed at finding treatments for the opioid overdose crisis. Many attempts have been made to understand the mechanism of the μ-OR activation, following the elucidation of new crystal structures such as the antagonist- and agonist-bound μ-OR. However, the focus has not been placed on the underlying energetics and specificity of the activation process. An energy-based picture would not only help to explain this coupling but also help to explore why other possible options are not common. For example, one would like to understand why μ-OR is more selective to G(i) than a stimulatory G protein (G(s)). Our study used homology modeling and a coarse-grained model to generate all of the possible “end states” of the thermodynamic cycle of the activation of μ-OR. The end points were further used to generate reasonable intermediate structures of the receptor and the G(i) to calculate two-dimensional free energy landscapes. The results of the landscape calculations helped to propose a plausible sequence of conformational changes in the μ-OR and G(i) system and for exploring the path that leads to its activation. Furthermore, in silico alanine scanning calculations of the last 21 residues of the C terminals of G(i) and G(s) were performed to shed light on the selective binding of G(i) to μ-OR. Overall, the present work appears to demonstrate the potential of multiscale modeling in exploring the action of G protein-coupled receptors.

The proteasome is a key protease in the eukaryotic cells which is responsible for various important cellular processes such as the control of the cell cycle, immune responses, protein homeostasis, inflammation, apoptosis, and the response to proteotoxic stress. Acting as a major molecular machine for protein degradation, proteasome first identifies damaged or obsolete regulatory proteins by attaching ubiquitin chains and subsequently utilizes conserved pore loops of the heterohexameric ring of AAA+ (ATPases associated with diverse cellular activities) to pull and mechanically unfold and translocate the misfolded protein to the active site for proteolysis. A detailed knowledge of the reaction mechanism for this proteasomal proteolysis is of central importance, both for fundamental understanding and for drug discovery. The present study investigates the mechanism of the proteolysis by the proteasome with full consideration of the protein's flexibility and its impact on the reaction free energy. Major attention is paid to the role of the protein electrostatics in determining the activation barriers. The reaction mechanism is studied by considering a small artificial fluorogenic peptide substrate (Suc-LLVY-AMC) and evaluating the activation barriers and reaction free energies for the acylation and deacylation steps, by using the empirical valence bond method. Our results shed light on the proteolysis mechanism and thus should be important for further studies of the proteasome action.

Computer-aided enzyme design is a field of great potential importance for biotechnological applications, medical advances, and a fundamental understanding of enzyme action. However, reaching a predictive ability in this direction is extremely challenging. It requires both the ability to predict quantitatively the activation barriers in cases where the structure and sequence are known and the ability to predict the effect of different mutations. In this work, we propose a protocol for predicting reasonable starting structures of mutants of proteins with known structures and for calculating the activation barriers of the generated mutants. Our approach also allows us to use the predicted structures of the generated mutant to predict structures and activation barriers for subsequent set of mutations. This protocol is used to examine the reliability of the in silico directed evolution of Kemp eliminase and haloalkane dehalogenase. We also used the results of single and double mutations as a base for predicting the effect of transition-state stabilization by multiple concurrent mutations. This strategy seems to be useful in creating an activity funnel that provides a qualitative ranking of the catalytic power of different mutants.

G-protein–coupled receptors (GPCRs) are a large group of membrane-bound receptor proteins that are involved in a plethora of diverse processes (e.g., vision, hormone response). In mammals, and particularly in humans, GPCRs are involved in many signal transduction pathways and, as such, are heavily studied for their immense pharmaceutical potential. Indeed, a large fraction of drugs target various GPCRs, and drug-development is often aimed at GPCRs. Therefore, understanding the activation of GPCRs is a challenge of major importance both from fundamental and practical considerations. And yet, despite the remarkable progress in structural understanding, we still do not have a translation of the structural information to an energy-based picture. Here we use coarse-grained (CG) modeling to chart the free-energy landscape of the activation process of the β-2 adrenergic receptor (β(2)AR) as a representative GPCR. The landscape provides the needed tool for analyzing the processes that lead to activation of the receptor upon binding of the ligand (adrenaline) while limiting constitutive activation. Our results pave the way to better understand the biological mechanisms of action of the β(2)AR and GPCRs, from a physical chemistry point of view rather than simply by observing the receptor’s behavior physiologically.

The study of the function of proteins on a quantitative level requires consideration of the water molecules in and around the protein. This requirement presents a major computational challenge due to the fact that the insertion of water molecules can have a very high activation barrier and would require a long simulation time. Recently, we developed a water flooding (WF) approach which is based on a postprocessing Monte Carlo ranking of possible water configurations. This approach appears to provide a very effective way for assessing the insertion free energies and determining the most likely configurations of the internal water molecules. Although the WF approach was used effectively in modeling challenging systems that have not been addressed reliably by other microscopic approaches, it was not validated by a comparison to the more rigorous grand canonical Monte Carlo (GCMC) method. Here we validate the WF approach by comparing its performance to that of the GCMC method. It is found that the WF approach reproduces the GCMC results in well-defined test cases but does so much faster. This established the WF approach as a useful strategy for finding correct water configurations in proteins and thus to provide a powerful way for studies of the functions of proteins.

Understanding the origin of the catalytic power of enzymes has both conceptual and practical importance. One of the most important finding from computational studies of enzyme catalysis is that a major part of the catalytic power is due to the preorganization of the enzyme active site. Unfortunately, misunderstanding of the nontrivial preorganization idea lead some to assume that it does not consider the effect of the protein residues. This major confusion reflects a misunderstanding of the statement that the interaction energy of the enzyme group and the transition state (TS) is similar to the corresponding interaction between the water molecules (in the reference system) and the TS, and that the catalysis is due to the reorganization free energy of the water molecules. Obviously, this finding does not mean that we do not consider the enzyme groups. Another problem is the idea that catalysis is due to substrate preorganization. This more traditional idea is based in some cases on inconsistent interpretation of the action of model compounds, which unfortunately, do not reflect the actual situation in the enzyme active site. The present article addresses the above problems, clarifying first the enzyme polar preorganization idea and the current misunderstandings. Next we take a specific model compound that was used to promote the substrate preorganization proposal and establish its irrelevance to enzyme catalysis. Overall, we show that the origin of the catalytic power of enzymes cannot be assessed uniquely without computer simulations, since at present this is the only way of relating structure and energetics.

The nature of the conversion of chemical energy to directional motion in myosin V is examined by careful simulations that include two complementary methods: direct Langevin Dynamics (LD) simulations with a scaled-down potential that provided a detailed time-resolved mechanism, and kinetic equations solution for the ensemble long-time propagation (based on information collected for segments of the landscape using LD simulations and experimental information). It is found that the directionality is due to the rate-limiting ADP release step rather than the potential energy of the lever arm angle. We show that the energy of the power stroke and the barriers involved in it are of minor consequence to the selectivity of forward over backward steps and instead suggest that the selective release of ADP from a postrigor myosin motor head promotes highly selective and processive myosin V. Our model is supported by different computational methods-LD simulations, Monte Carlo simulations, and kinetic equations solution-as well as by structure-based binding energy calculations.

Hepatitis C virus (HCV) currently affects several million people across the globe. One of the major classes of drugs against HCV inhibits the NS3/4A protease of the polyprotein chain. Efficacy of these drugs is severely limited due to the high mutation rate that results in several genetically related quasispecies. The molecular mechanism of drug resistance is frequently deduced from structural studies and binding free energies. However, prediction of new mutations requires the evaluation of both binding free energy of the drug as well as the parameters (κcat and KM) for the natural substrate. The vitality values offer a good approach to investigate and predict mutations that render resistance to the inhibitor. A successful mutation should only affect the binding of the drug and not the catalytic activity and binding of the natural substrate. In this article, we have calculated the vitality values for four known drug inhibitors that are either currently in use or in clinical trials, evaluating binding free energies by the relevant PDLD/S-LRA method and activation barriers by the EVB method. The molecular details pertaining to resistance are also discussed. We show that our calculations are able to reproduce the catalytic effects and binding free energies in a good agreement with the corresponding observed values. Importantly, previous computational approaches have not been able to achieve this task. The trend for the vitality values is in accordance with experimental findings. Finally, we calculate the vitality values for mutations that have either not been studied experimentally or reported for some inhibitors.

Molecular motors are multi-subunit complexes that are indispensable for accomplishing various tasks of the living cells. One such molecular motor is the FOF1 ATP synthase that synthesizes ATP at the expense of the membrane proton gradient. Elucidating the molecular origin of the motor function is challenging despite significant advances in various experimental fields. Currently atomic simulations of whole motor complexes cannot reach to functionally relevant time scales that extend beyond the millisecond regime. Moreover, to reveal the underlying molecular origin of the function, one must model the coupled chemical and conformational events using physically and chemically meaningful multiscaling techniques. In this review, we discuss our approach to model the action of the F1 and FO molecular motors, where emphasis is laid on elucidating the molecular origin of the driving force that leads to directional rotation at the expense of ATP hydrolysis or proton gradients. We have used atomic structures of the motors and used hierarchical multiscaling techniques to generate low dimensional functional free energy surfaces of the complete mechano-chemical process. These free energy surfaces were studied further to calculate important characteristics of the motors, such as, rotational torque, temporal dynamics, occurrence of intermittent dwell states, etc. We also studied the result of mutating various parts of the motor domains and our observations correspond very well with the experimental findings. Overall, our studies have generated a cumulative understanding of the motor action, and especially highlight the crucial role of electrostatics in establishing the mechano-chemical coupling.

Pol η belongs to the important Y family of DNA polymerases that can catalyze translesion synthesis across sites of damaged DNA. This activity involves the reduced fidelity of Pol η for 8-oxo-7,8-dhyedro-2′-deoxoguanosin(8-oxoG). The fundamental interest in Pol η has grown recently with the demonstration of the importance of a 3rd Mg2+ ion. The current work explores both the fidelity of Pol η and the role of the 3rd metal ion, by using empirical valence bond (EVB) simulations. The simulations reproduce the observed trend in fidelity and shed a new light on the role of the 3rd metal ion. It is found that this ion does not lead to a major catalytic effect, but most probably plays an important role in reducing the product release barrier. Furthermore, it is concluded, in contrast to some implications, that the effect of this metal does not violate transition state theory, and the evaluation of the catalytic effect must conserve the molecular composition upon moving from the reactant to the transition state. Proteins 2017; 85:1446–1453. © 2017 Wiley Periodicals, Inc.

The detailed dynamics of the cycle of myosin-V are explored by simulation approaches, examining the nature of the energy-driven motion. Our study started with Langevin dynamics (LD) simulations on a very coarse landscape with a single rate-limiting barrier and reproduced the stall force and the hand-over-hand dynamics. We then considered a more realistic landscape and used time-dependent Monte Carlo (MC) simulations that allowed trajectories long enough to reproduce the force/velocity characteristic sigmoidal correlation, while also reproducing the hand-over-hand motion. Overall, our study indicated that the notion of a downhill lever-up to lever-down process (popularly known as the powerstroke mechanism) is the result of the energetics of the complete myosin-V cycle and is not the source of directional motion or force generation on its own. The present work further emphasizes the need to use well-defined energy landscapes in studying molecular motors in general and myosin in particular.

Increasing the accuracy of the evaluation of ligand-binding energies is one of the most important tasks of current computational biology. Here we explore the accuracy of free energy perturbation (FEP) approaches by comparing the performance of a "regular" FEP method to the one using replica exchange to enhance the sampling on a well-defined benchmark. The examination was limited to the so-called alchemical perturbations which are restricted to a fragment of the drug, and therefore, the calculation is a relative one rather than the absolute binding energy of the drug. Overall, our calculations reach the 1 kcal/mol accuracy limit. It is also shown that the accurate prediction of the position of water molecules around the binding pocket is important for FEP calculations. Interestingly, the replica exchange method does not significantly improve the accuracy of binding energies, suggesting that we reach the limit where the force field quality is a critical factor for accurate calculations.

Understanding the reaction mechanism of CRISPR-associated protein 9 (Cas9) is crucial for the application of programmable gene editing. Despite the availability of the structures of Cas9 in apo- and substrate-bound forms, the catalytically active structure is still unclear. Our first attempt to explore the catalytic mechanism of Cas9 HNH domain has been based on the reasonable assumption that we are dealing with the same mechanism as endonuclease VII, including the assumption that the catalytic water is in the first shell of the Mg2+ . Trying this mechanism with the cryo-EM structure forced us to induce significant structural change driven by the movement of K848 (or other positively charged residue) close to the active site to facilitate the proton transfer step. In the present study, we explore a second reaction mechanism where the catalytic water is in the second shell of the Mg2+ and assume that the cryo-EM structure by itself is a suitable representation of a catalytic-ready structure. The alternative mechanism indicates that if the active water is from the second shell, then the calculated reaction barrier is lower compared with the corresponding barrier when the water comes from the first shell.

Rational enzyme design presents a major challenge that has not been overcome by computational approaches. One of the key challenges is the difficulty in assessing the magnitude of the maximum possible catalytic activity. In an attempt to overcome this challenge, we introduce a strategy that takes an active enzyme (assuming that its activity is close to the maximum possible activity), design mutations that reduce the catalytic activity, and then try to restore that catalysis by mutating other residues. Here we take as a test case the enzyme haloalkane dehalogenase (DhlA), with a 1,2-dichloroethane substrate. We start by demonstrating our ability to reproduce the results of single mutations. Next, we design mutations that reduce the enzyme activity and finally design double mutations that are aimed at restoring the activity. Using the computational predictions as a guide, we conduct an experimental study that confirms our prediction in one case and leads to inconclusive results in another case with 1,2-dichloroethane as substrate. Interestingly, one of our predicted double mutants catalyzes dehalogenation of 1,2-dibromoethane more efficiently than the wild-type enzyme.

Elucidating the nature of the gene editing mechanism of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is an important task in view of the role of this breakthrough to the advancement of human medicine. In particular, it is crucial to understand the catalytic mechanism of Cas9 (one of the CRISPR associated proteins) and its role in confirming accurate editing. Thus, we focus in this work on an attempt to analyze the catalytic mechanism of Cas9. Considering the absence of detailed structural information on the active form of Cas9, we use an empirical valence bond (EVB) which is calibrated on the closely related mechanism of T4 endonuclease VII. The calibrated EVB is then used in studying the reaction of Cas9, while trying several structural models. It is found that the catalytic activation requires a large conformational change, where K848 or other positively charged group moves from a relatively large distance toward the scissile phosphate. This conformational change leads to the change in position of the Mg(2+) ion and to a major reduction in the activation barrier for the catalytic reaction. Our finding provides an important clue on the nature of the catalytic activation of CAS9 and thus should help in elucidating a key aspect of the gene editing process. For example, the approach used here should be effective in exploring the nature of off target activation and its relationship to the energetics of the unwinding process. This strategy may offer ways to improve the selectivity of Cas9.

Zinc is a vital trace element crucial for the proper function of some 3,000 cellular proteins. Specifically, zinc is essential for key physiological processes including nucleic acid metabolism, regulation of gene expression, signal transduction, cell division, immune- and nervous system functions, wound healing, and apoptosis. Consequently, impairment of zinc homeostasis disrupts key cellular functions resulting in various human pathologies. Mammalian zinc transport proceeds via two transporter families ZnT and ZIP. However, the detailed mechanism of action of ZnT2, which is responsible for vesicular zinc accumulation and zinc secretion into breast milk during lactation, is currently unknown. Moreover, although the putative coupling of zinc transport to the proton gradient in acidic vesicles has been suggested, it has not been conclusively established. Herein we modeled the mechanism of action of ZnT2 and demonstrated both computationally and experimentally, using functional zinc transport assays, that ZnT2 is indeed a proton-coupled zinc antiporter. Bafilomycin A1, a specific inhibitor of vacuolar-type proton ATPase (V-ATPase) which alkalizes acidic vesicles, abolished ZnT2-dependent zinc transport into intracellular vesicles. Moreover, using LysoTracker Red and Lyso-pHluorin, we further showed that upon transient ZnT2 overexpression in intracellular vesicles and addition of exogenous zinc, the vesicular pH underwent alkalization, presumably due to a proton-zinc antiport; this phenomenon was reversed in the presence of TPEN, a specific zinc chelator. Finally, based on computational energy calculations, we propose that ZnT2 functions as an antiporter with a stoichiometry of 2H+/Zn2+ ion. Hence, ZnT2 is a proton motive force-driven, electroneutral vesicular zinc exchanger, concentrating zinc in acidic vesicles on the expense of proton extrusion to the cytoplasm., Author summary Herein we explored the mechanism of action of the human ZnT2 zinc transporter. ZnT2 is essential for zinc accumulation in breast milk and is therefore of paramount medical significance. Expanding on our previous study, we herein present energy calculations suggesting that ZnT2 functions as a proton/zinc antiporter. Our calculations consist of electrostatic and pKa calculations as well as zinc binding free-energy curves. Upon integration of our calculation results, we conclude that ZnT2 functions as an antiporter with a 2H+/Zn2+ stoichiometry, construct a Monte Carlo model to test this mode of ZnT2 transport activity, and validate our computational results experimentally using live human breast epithelial cells. These functional experiments reveal that ZnT2 cannot function in the absence of protons suggesting that it operates as a substrate-induced alternating-access transporter, displaying an apparent 2H+/Zn2+ stoichiometry.

The structures of transport proteins have been steadily revealed in the last few decades, and yet the conversion of this information into molecular-level understanding of their function is still lagging behind. In this study, we try to elucidate how the action of the archaeal sodium/proton antiporter MjNhaP1 depends on its structure-energy relationship. To this end, we calculate the binding energies of its substrates and evaluate the conformational change barrier, focusing on the rotation of the catalytic residue D161. We find that sodium ions and protons compete against a common binding site and that the accessibility of this binding site is restricted to either the inside or outside of the cell. We suggest that the rotation of D161 χ1 angle correlates with the conformational change and is energetically unfavorable when D161 does not bind any substrate. This restriction ensures coupling between the sodium ions and the protons, allowing MjNhaP1 and probably other similar transporters to exchange substrates with minimal leak. Using Monte Carlo simulations we demonstrate the feasibility of our model. Overall we present a complete picture that reproduces the electroneutral (at 1:1 substrate ratio) and coupled transport activity of MjNhaP1 including the energetic basis for the criteria provided by Jardetzky half a century ago.

Measurements of voltage changes in response to charge separation within membrane proteins can offer fundamental information on spectroscopically "invisible" steps. For example, results from studies of voltage changes associated with electron and proton transfer in cytochrome c oxidase could, in principle, be used to discriminate between different theoretical models describing the molecular mechanism of proton pumping. Earlier analyses of data from these measurements have been based on macroscopic considerations that may not allow for exploring the actual molecular mechanisms. Here, we have used a coarse-grained model describing the relation between observed voltage changes and specific charge-transfer reactions, which includes an explicit description of the membrane, the electrolytes, and the electrodes. The results from these calculations offer mechanistic insights at the molecular level. Our main conclusion is that previously assumed mechanistic evidence that was based on electrogenic measurements is not unique. However, the ability of our calculations to obtain reliable voltage changes means that we have a tool that can be used to describe a wide range of electrogenic charge transfers in channels and transporters, by combining voltage measurements with other experiments and simulations to analyze new mechanistic proposals.

Multiscale modeling provides a very powerful means of studying complex biological systems. An important component of this strategy involves coarse-grained (CG) simplifications of regions of the system, which allow effective exploration of complex systems. Here we studied aspects of CG modeling of the human zinc transporter ZnT2. Zinc is an essential trace element with 10% of the proteins in the human proteome capable of zinc binding. Thus, zinc deficiency or impairment of zinc homeostasis disrupt key cellular functions. Mammalian zinc transport proceeds via two transporter families: ZnT and ZIP; however, little is known about the zinc permeation pathway through these transporters. As a step towards this end, we herein undertook comprehensive computational analyses employing multiscale techniques, focusing on the human zinc transporter ZnT2 and its bacterial homologue, YiiP. Energy calculations revealed a favorable pathway for zinc translocation via alternating access. We then identified key residues presumably involved in the passage of zinc ions through ZnT2 and YiiP, and functionally validated their role in zinc transport using site-directed mutagenesis of ZnT2 residues. Finally, we use a CG Monte Carlo simulation approach to sample the transition between the inward-facing and the outward-facing states. We present our structural models of the inward- and outward-facing conformations of ZnT2 as a blueprint prototype of the transporter conformations, including the putative permeation pathway and participating residues. The insights gained from this study may facilitate the delineation of the pathways of other zinc transporters, laying the foundations for the molecular basis underlying ion permeation. This may possibly facilitate the development of therapeutic interventions in pathological states associated with zinc deficiency and other disorders based on loss-of-function mutations in solute carriers., Author summary Herein we employed multiscale modeling and electrostatic energy calculations to delineate, for the first time, a putative zinc permeation pathway, from the cytoplasm into intracellular vesicles (for ZnT2) or to the extracellular milieu (for YiiP), along the membrane-spanning domain of the human zinc transporter ZnT2 and its E. coli homologue, YiiP. These computational findings were functionally validated using site-directed mutagenesis of ZnT2 residues predicted to reside along the putative zinc permeation pathway and zinc transport assay. Our results shed light on the transport mechanisms of ZnT2 and YiiP and pave the way towards the elucidation of the zinc translocation mechanism in other ZnT family members. Furthermore, these findings could also be harnessed to the possible development of therapeutic interventions in zinc-associated pathologies.

The nature of the action of voltage-activated proton transport proteins is a conundrum of great current interest. Here we approach this issue by exploring the action of Hv1, a voltage-gated proton channel found in different cells in humans and other organisms. Our study focuses on evaluating the free energy of transporting a proton through the channel, as well as the effect of the proton transfer through D112, in both the closed and open channel conformations. It is found that D112 allows a transported proton to bypass the electrostatic barrier of the open channel, while not being able to help in passing the barrier in the closed form. This reflects the change in position of the gating arginine residues relative to D112, upon voltage activation. Significantly, the effect of D112 accounts for the observed trend in selectivity by overcoming the electrostatic barrier at its highest point. Thus, the calculations provide a structure/function correlation for the Hv1 system. The present work also clarifies that the action of Hv1 is not controlled by a Grotthuss mechanism but, as is always the case, by the protein electrostatic potential at the rate-limiting barriers.

Many cellular processes are controlled by GTPases, and gaining quantitative understanding of the activation of such processes has been a major challenge. In particular, it is crucial to obtain reliable free-energy surfaces for the relevant reaction paths both in solution and in GTPases active sites. Here, we revisit the energetics of the activation of EF-G and EF-Tu by the ribosome and explore the nature of the catalysis of the GTPase reaction. The comparison of EF-Tu to EF-G allows us to explore the impact of possible problems with the available structure of EF-Tu. Additionally, mutational effects are used for a careful validation of the emerging conclusions. It is found that the reaction may proceed by both a two-water mechanism and a one-water (GTP as a base) mechanism. However, in both cases, the activation involves a structural allosteric effect, which is likely to be a general-activation mechanism for all GTPases.