The maximal and current accuracy of rigorous protein-ligand binding free energy calculations.

Computational techniques can speed up the identification of hits and accelerate the development of candidate molecules for drug discovery. Among techniques for predicting relative binding affinities, the most consistently accurate is free energy perturbation (FEP), a class of rigorous physics-based methods. However, uncertainty remains about how accurate FEP is and can ever be. Here, we present what we believe to be the largest publicly available dataset of proteins and congeneric series of small molecules, and assess the accuracy of the leading FEP workflow. To ascertain the limit of achievable accuracy, we also survey the reproducibility of experimental relative affinity measurements. We find a wide variability in experimental accuracy and a correspondence between binding and functional assays. When careful preparation of protein and ligand structures is undertaken, FEP can achieve accuracy comparable to experimental reproducibility. Throughout, we highlight reliable protocols that can help maximize the accuracy of FEP in prospective studies.

Accurate Prediction of Protein Thermodynamic Stability Changes upon Residue Mutation using Free Energy Perturbation.

This work describes the application of a physics-based computational approach to predict the relative thermodynamic stability of protein variants, and evaluates the quantitative accuracy of those predictions compared to experimental data obtained from a diverse set of protein systems assayed at variable pH conditions. Physical stability is a key determinant of the clinical and commercial success of biological therapeutics, vaccines, diagnostics, enzymes and other protein-based products. Although experimental techniques for measuring the impact of amino acid residue mutation on the stability of proteins exist, they tend to be time consuming and costly, hence the need for accurate prediction methods. In contrast to many of the commonly available computational methods for stability prediction, the Free Energy Perturbation approach applied in this paper explicitly accounts for solvent effects and samples conformational dynamics using a rigorous molecular dynamics simulation process. On the entire validation dataset, consisting of 328 single point mutations spread across 14 distinct protein structures, our results show good overall correlation with experiment with an R2 of 0.65 and a low mean unsigned error of 0.95 kcal/mol. Application of the FEP approach in conjunction with experimental assessment techniques offers opportunities to lower the time and expense of product development and reduce the risk of costly late-stage failures.

Author Correction: A structural model for microtubule minus-end recognition and protection by CAMSAP proteins.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Neck linker docking is critical for Kinesin-1 force generation in cells but at a cost to motor speed and processivity.

Kinesin force generation involves ATP-induced docking of the neck linker (NL) along the motor core. However, the roles of the proposed steps of NL docking, cover-neck bundle (CNB) and asparagine latch (N-latch) formation, during force generation are unclear. Furthermore, the necessity of NL docking for transport of membrane-bound cargo in cells has not been tested. We generated kinesin-1 motors impaired in CNB and/or N-latch formation based on molecular dynamics simulations. The mutant motors displayed reduced force output and inability to stall in optical trap assays but exhibited increased speeds, run lengths, and landing rates under unloaded conditions. NL docking thus enhances force production but at a cost to speed and processivity. In cells, teams of mutant motors were hindered in their ability to drive transport of Golgi elements (high-load cargo) but not peroxisomes (low-load cargo). These results demonstrate that the NL serves as a mechanical element for kinesin-1 transport under physiological conditions.

A posttranslational modification of the mitotic kinesin Eg5 that enhances its mechanochemical coupling and alters its mitotic function.

Numerous posttranslational modifications have been described in kinesins, but their consequences on motor mechanics are largely unknown. We investigated one of these-acetylation of lysine 146 in Eg5-by creating an acetylation mimetic lysine to glutamine substitution (K146Q). Lysine 146 is located in the α2 helix of the motor domain, where it makes an ionic bond with aspartate 91 on the neighboring α1 helix. Molecular dynamics simulations predict that disrupting this bond enhances catalytic site-neck linker coupling. We tested this using structural kinetics and single-molecule mechanics and found that the K146Q mutation increases motor performance under load and coupling of the neck linker to catalytic site. These changes convert Eg5 from a motor that dissociates from the microtubule at low load into one that is more tightly coupled and dissociation resistant-features shared by kinesin 1. These features combined with the increased propensity to stall predict that the K146Q Eg5 acetylation mimetic should act in the cell as a "brake" that slows spindle pole separation, and we have confirmed this by expressing this modified motor in mitotically active cells. Thus, our results illustrate how a posttranslational modification of a kinesin can be used to fine tune motor behavior to meet specific physiological needs.

A structural model for microtubule minus-end recognition and protection by CAMSAP proteins.

CAMSAP and Patronin family members regulate microtubule minus-end stability and localization and thus organize noncentrosomal microtubule networks, which are essential for cell division, polarization and differentiation. Here, we found that the CAMSAP C-terminal CKK domain is widely present among eukaryotes and autonomously recognizes microtubule minus ends. Through a combination of structural approaches, we uncovered how mammalian CKK binds between two tubulin dimers at the interprotofilament interface on the outer microtubule surface. In vitro reconstitution assays combined with high-resolution fluorescence microscopy and cryo-electron tomography suggested that CKK preferentially associates with the transition zone between curved protofilaments and the regular microtubule lattice. We propose that minus-end-specific features of the interprotofilament interface at this site serve as the basis for CKK's minus-end preference. The steric clash between microtubule-bound CKK and kinesin motors explains how CKK protects microtubule minus ends against kinesin-13-induced depolymerization and thus controls the stability of free microtubule minus ends.

Mapping the Processivity Determinants of the Kinesin-3 Motor Domain.

Kinesin superfamily members play important roles in many diverse cellular processes, including cell motility, cell division, intracellular transport, and regulation of the microtubule cytoskeleton. How the properties of the family-defining motor domain of distinct kinesins are tailored to their different cellular roles remains largely unknown. Here, we employed molecular-dynamics simulations coupled with energetic calculations to infer the family-specific interactions of kinesin-1 and kinesin-3 motor domains with microtubules in different nucleotide states. We then used experimental mutagenesis and single-molecule motility assays to further assess the predicted residue-wise determinants of distinct kinesin-microtubule binding properties. Collectively, our results identify residues in the L8, L11, and α6 regions that contribute to family-specific microtubule interactions and whose mutation affects motor-microtubule complex stability and processive motility (the ability of an individual motor to take multiple steps along its microtubule filament). In particular, substitutions of prominent kinesin-3 residues with those found in kinesin-1, namely, R167S/H171D, K266D, and R346M, were found to decrease kinesin-3 processivity 10-fold and thus approach kinesin-1 levels.

Integrating protein structural dynamics and evolutionary analysis with Bio3D.

BACKGROUND: Popular bioinformatics approaches for studying protein functional dynamics include comparisons of crystallographic structures, molecular dynamics simulations and normal mode analysis. However, determining how observed displacements and predicted motions from these traditionally separate analyses relate to each other, as well as to the evolution of sequence, structure and function within large protein families, remains a considerable challenge. This is in part due to the general lack of tools that integrate information of molecular structure, dynamics and evolution. RESULTS: Here, we describe the integration of new methodologies for evolutionary sequence, structure and simulation analysis into the Bio3D package. This major update includes unique high-throughput normal mode analysis for examining and contrasting the dynamics of related proteins with non-identical sequences and structures, as well as new methods for quantifying dynamical couplings and their residue-wise dissection from correlation network analysis. These new methodologies are integrated with major biomolecular databases as well as established methods for evolutionary sequence and comparative structural analysis. New functionality for directly comparing results derived from normal modes, molecular dynamics and principal component analysis of heterogeneous experimental structure distributions is also included. We demonstrate these integrated capabilities with example applications to dihydrofolate reductase and heterotrimeric G-protein families along with a discussion of the mechanistic insight provided in each case. CONCLUSIONS: The integration of structural dynamics and evolutionary analysis in Bio3D enables researchers to go beyond a prediction of single protein dynamics to investigate dynamical features across large protein families. The Bio3D package is distributed with full source code and extensive documentation as a platform independent R package under a GPL2 license from http://thegrantlab.org/bio3d/ .

Kinesin-5 allosteric inhibitors uncouple the dynamics of nucleotide, microtubule, and neck-linker binding sites.

Kinesin motor domains couple cycles of ATP hydrolysis to cycles of microtubule binding and conformational changes that result in directional force and movement on microtubules. The general principles of this mechanochemical coupling have been established; however, fundamental atomistic details of the underlying allosteric mechanisms remain unknown. This lack of knowledge hampers the development of new inhibitors and limits our understanding of how disease-associated mutations in distal sites can interfere with the fidelity of motor domain function. Here, we combine unbiased molecular-dynamics simulations, bioinformatics analysis, and mutational studies to elucidate the structural dynamic effects of nucleotide turnover and allosteric inhibition of the kinesin-5 motor. Multiple replica simulations of ATP-, ADP-, and inhibitor-bound states together with network analysis of correlated motions were used to create a dynamic protein structure network depicting the internal dynamic coordination of functional regions in each state. This analysis revealed the intervening residues involved in the dynamic coupling of nucleotide, microtubule, neck-linker, and inhibitor binding sites. The regions identified include the nucleotide binding switch regions, loop 5, loop 7, ?4-?5-loop 13, ?1, and ?4-?6-?7. Also evident were nucleotide- and inhibitor-dependent shifts in the dynamic coupling paths linking functional sites. In particular, inhibitor binding to the loop 5 region affected ?-sheet residues and ?1, leading to a dynamic decoupling of nucleotide, microtubule, and neck-linker binding sites. Additional analyses of point mutations, including P131 (loop 5), Q78/I79 (?1), E166 (loop 7), and K272/I273 (?7) G325/G326 (loop 13), support their predicted role in mediating the dynamic coupling of distal functional surfaces. Collectively, our results and approach, which we make freely available to the community, provide a framework for explaining how binding events and point mutations can alter dynamic couplings that are critical for kinesin motor domain function.

Bioactive conformations of two seminal delta opioid receptor penta-peptides inferred from free-energy profiles.

Delta-opioid (DOP) receptors are members of the G protein-coupled receptor (GPCR) sub-family of opioid receptors, and are evolutionarily related, with homology exceeding 70%, to cognate mu-opioid (MOP), kappa-opioid (KOP), and nociceptin opioid (NOP) receptors. DOP receptors are considered attractive drug targets for pain management because agonists at these receptors are reported to exhibit strong antinociceptive activity with relatively few side effects. Among the most potent analgesics targeting the DOP receptor are the linear and cyclic enkephalin analogs known as DADLE (Tyr-D-Ala-Gly-Phe-D-Leu) and DPDPE (Tyr-D-Pen-Gly-Phe-D-Pen), respectively. Several computational and experimental studies have been carried out over the years to characterize the conformational profile of these penta-peptides with the ultimate goal of designing potent peptidomimetic agonists for the DOP receptor. The computational studies published to date, however, have investigated only a limited range of timescales and used over-simplified representations of the solvent environment. We provide here a thorough exploration of the conformational space of DADLE and DPDPE in an explicit solvent, using microsecond-scale molecular dynamics and bias-exchange metadynamics simulations. Free-energy profiles derived from these simulations point to a small number of DADLE and DPDPE conformational minima in solution, which are separated by relatively small energy barriers. Candidate bioactive forms of these peptides are selected from identified common spatial arrangements of key pharmacophoric points within all sampled conformations.

Mapping the structural and dynamical features of kinesin motor domains.

Kinesin motor proteins drive intracellular transport by coupling ATP hydrolysis to conformational changes that mediate directed movement along microtubules. Characterizing these distinct conformations and their interconversion mechanism is essential to determining an atomic-level model of kinesin action. Here we report a comprehensive principal component analysis of 114 experimental structures along with the results of conventional and accelerated molecular dynamics simulations that together map the structural dynamics of the kinesin motor domain. All experimental structures were found to reside in one of three distinct conformational clusters (ATP-like, ADP-like and Eg5 inhibitor-bound). These groups differ in the orientation of key functional elements, most notably the microtubule binding α4-α5, loop8 subdomain and α2b-ß4-ß6-ß7 motor domain tip. Group membership was found not to correlate with the nature of the bound nucleotide in a given structure. However, groupings were coincident with distinct neck-linker orientations. Accelerated molecular dynamics simulations of ATP, ADP and nucleotide free Eg5 indicate that all three nucleotide states could sample the major crystallographically observed conformations. Differences in the dynamic coupling of distal sites were also evident. In multiple ATP bound simulations, the neck-linker, loop8 and the α4-α5 subdomain display correlated motions that are absent in ADP bound simulations. Further dissection of these couplings provides evidence for a network of dynamic communication between the active site, microtubule-binding interface and neck-linker via loop7 and loop13. Additional simulations indicate that the mutations G325A and G326A in loop13 reduce the flexibility of these regions and disrupt their couplings. Our combined results indicate that the reported ATP and ADP-like conformations of kinesin are intrinsically accessible regardless of nucleotide state and support a model where neck-linker docking leads to a tighter coupling of the microtubule and nucleotide binding regions. Furthermore, simulations highlight sites critical for large-scale conformational changes and the allosteric coupling between distal functional sites.

Exploiting antigenic diversity for vaccine design: the chlamydia ArtJ paradigm.

We present an interdisciplinary approach that, by incorporating a range of experimental and computational techniques, allows the identification and characterization of functional/immunogenic domains. This approach has been applied to ArtJ, an arginine-binding protein whose orthologs in Chlamydiae trachomatis (CT ArtJ) and pneumoniae (CPn ArtJ) are shown to have different immunogenic properties despite a high sequence similarity (60% identity). We have solved the crystallographic structures of CT ArtJ and CPn ArtJ, which are found to display a type II transporter fold organized in two α-ß domains with the arginine-binding region at their interface. Although ArtJ is considered to belong to the periplasm, we found that both domains contain regions exposed on the bacterial surface. Moreover, we show that recombinant ArtJ binds to epithelial cells in vitro, suggesting a role for ArtJ in host-cell adhesion during Chlamydia infection. Experimental epitope mapping and computational analysis of physicochemical determinants of antibody recognition revealed that immunogenic epitopes reside mainly in the terminal (D1) domain of both CPn and CT ArtJ, whereas the surface properties of the respective binding-prone regions appear sufficiently different to assume divergent immunogenic behavior. Neutralization assays revealed that sera raised against CPn ArtJ D1 partially reduce both CPn and CT infectivity in vitro, suggesting that functional antibodies directed against this domain may potentially impair chlamydial infectivity. These findings suggest that the approach presented here, combining functional and structure-based analyses of evolutionary-related antigens can be a valuable tool for the identification of cross-species immunogenic epitopes for vaccine development.

Predicting interaction sites from the energetics of isolated proteins: a new approach to epitope mapping.

An increasing number of functional studies of proteins have shown that sequence and structural similarities alone may not be sufficient for reliable prediction of their interaction properties. This is particularly true for proteins recognizing specific antibodies, where the prediction of antibody-binding sites, called epitopes, has proven challenging. The antibody-binding properties of an antigen depend on its structure and related dynamics. Aiming to predict the antibody-binding regions of a protein, we investigate a new approach based on the integrated analysis of the dynamical and energetic properties of antigens, to identify nonoptimized, low-intensity energetic interaction networks in the protein structure isolated in solution. The method is based on the idea that recognition sites may correspond to localized regions with low-intensity energetic couplings with the rest of the protein, which allows them to undergo conformational changes, to be recognized by a binding partner, and to tolerate mutations with minimal energetic expense. Upon analyzing the results on isolated proteins and benchmarking against antibody complexes, it is found that the method successfully identifies binding sites located on the protein surface that are accessible to putative binding partners. The combination of dynamics and energetics can thus discriminate between epitopes and other substructures based only on physical properties. We discuss implications for vaccine design.

Structural analysis of a helical peptide unfolding pathway.

The analysis of the folding mechanism in peptides adopting well-defined secondary structure is fundamental to understand protein folding. Herein, we describe the thermal unfolding of a 15-mer vascular endothelial growth factor mimicking alpha-helical peptide (QK(L10A)) through the combination of spectroscopic and computational analyses. In particular, on the basis of the temperature dependencies of QK(L10A) H(alpha) chemical shifts we show that the first phase of the thermal helix unfolding, ending at around 320 K, involves mainly the terminal regions. A second phase of the transition, ending at around 333 K, comprises the central helical region of the peptide. The determination of high-resolution QK(L10A) conformational preferences in water at 313 K allowed us to identify, at atomic resolution, one intermediate of the folding-unfolding pathway. Molecular dynamics simulations corroborate experimental observations detecting a stable central helical turn, which represents the most probable site for the helix nucleation in the folding direction. The data presented herein allows us to draw a folding-unfolding picture for the small peptide QK(L10A) compatible with the nucleation-propagation model. This study, besides contributing to the basic field of peptide helix folding, is useful to gain an insight into the design of stable helical peptides, which could find applications as molecular scaffolds to target protein-protein interactions.

Structure and sequence determinants of aggregation investigated with molecular dynamics.

Spontaneous self-assembly and amyloid formation are a general property of many polypeptides and the information controlling these processes is encoded in the sequence. This determines the form and structural features of the interacting partners that regulate the properties of the final aggregates. Understanding the correlations between sequence, structure and dynamics in peptides and proteins at an atomistic level of resolution still represents one of the grand challenges of modern biological chemistry. In this context, computer simulations represent a valuable approach to understand recognition and spontaneous self-organization, processes that cannot be directly observed experimentally. Herein, we will discuss cases illustrating the extent to which simulations can be used to understand the self-organization properties of natural and designed amyloidogenic peptide sequences. The simulations provide evidence for the influence of specific interactions with well defined stereochemical constraints on fibril formation. The results from our and other groups suggest that simulations can be applied to detect the critical physico-chemical determinants of a certain process and can be helpful in the design of new chemical systems and experiments.