A large decoy set of protein–protein complexes produced by flexible docking

Computational methods are needed to help characterize the structure and function of protein–protein complexes. To develop and improve such methods, standard test problems are essential. One important test is to identify experimental structures from among large sets of decoys. Here, a flexible docking procedure was used to produce such a large ensemble of decoy complexes. In addition to their use for structure prediction, they can serve as a proxy for the nonspecific, protein–protein complexes that occur transiently in the cell, which are hard to characterize experimentally, yet biochemically important. For 202 homodimers and 41 heterodimers with known X‐ray structures, we produced an average of 1217 decoys each. The structures were characterized in detail. The decoys have rather large protein–protein interfaces, with at least 45 residue–residue contacts for every 100 contacts found in the experimental complex. They have limited intramonomer deformation and limited intermonomer steric conflicts. The decoys thoroughly sample each monomer's surface, with all the surface amino acids being part of at least one decoy interface. The decoys with the lowest intramonomer deformation were analyzed separately, as proxies for nonspecific protein–protein complexes. Their interfaces are less hydrophobic than the experimental ones, with an amino acid composition similar to the overall surface composition. They have a poorer shape complementarity and a weaker association energy, but are no more fragmented than the experimental interfaces, with 2.1 distinct patches of interacting residues on average, compared to 2.6 for the experimental interfaces. The decoys should be useful for testing and parameterizing docking methods and scoring functions; they are freely available as PDB files at http://biology.polytechnique.fr/decoys . © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

Modeling tubulin at interfaces. Immobilization of microtubules on self-assembled monolayers

A theoretical study of protein docking to self-assembled monolayers using a new approach is presented. Docking experiments based on space complementarity implemented in FTDock software were performed for three different proteins: tubulin dimer, cytochrome c, and lysozyme. The proteins were adsorbed on alkanethiol surfaces with different terminating groups and 50,000 best orientations of each protein were analyzed. For all systems three filters based on different chemical and biological approaches were applied. Correctly docked proteins for the cytochrome c and lysozyme systems were found in a list of the first 12 results after applying the geometrical and grouping filter and in a list of the first 3 results after applying the biological filter. We have found that alkanethiol monolayers with odd and even numbers of -CH2- groups have similar properties in terms of interactions with the two proteins. Docking of the tubulin dimer revealed that the orientation favored from the applicational point of view can be found in a list of the first 14 results for monolayers with different terminating groups and that there may be a noticeable difference in tubulin dimer interactions with alkanethiol chains of various length. The results for tubulin dimer docking combined with microtubules ability of reversible assembly suggest that these biological structures may become good candidates to serve as templates for fabrication of nanowires and other nanoscale electronic devices. The new method of theoretical docking presented may be used as a fast and reliable tool complementing other theoretical and experimental techniques of exploring other protein-surface interfaces.     

Distilling the essential features of a protein surface for improving protein-ligand docking,scoring, and virtual screening

For the successful identification and docking of new ligands to a protein target by virtual screening, the essential features of the protein and ligand surfaces must be captured and distilled in an efficient representation. Since the running time for docking increases exponentially with the number of points representing the protein and each ligand candidate, it is important to place these points where the best interactions can be made between the protein and the ligand. This definition of favorable points of interaction can also guide protein structure-based ligand design, which typically focuses on which chemical groups provide the most energetically favorable contacts. In this paper, we present an alternative method of protein template and ligand interaction point design that identifies the most favorable points for making hydrophobic and hydrogen–bond interactions by using a knowledge base. The knowledge-based protein and ligand representations have been incorporated in version 2.0 of SLIDE and resulted in dockings closer to the crystal structure orientations when screening a set of 57 known thrombin and glutathione S–transferase (GST) ligands against the apo structures of these proteins. There was also improved scoring enrichment of the dockings, meaning better differentiation between the chemically diverse known ligands and a 15,000-molecule dataset of randomly-chosen small organic molecules. This approach for identifying the most important points of interaction between proteins and their ligands can equally well be used in other docking and design techniques. While much recent effort has focused on improving scoring functions for protein-ligand docking, our results indicate that improving the representation of the chemistry of proteins and their ligands is another avenue that can lead to significant improvements in the identification, docking, and scoring of ligands.(These authors contributed equally to this work)     

Fast procedure for reconstruction of full-atom protein models from reduced representations

We introduce PULCHRA, a fast and robust method for the reconstruction of full-atom protein models starting from a reduced protein representation. The algorithm is particularly suitable as an intermediate step between coarse-grained model-based structure prediction and applications requiring an all-atom structure, such as molecular dynamics, protein-ligand docking, structure-based function prediction, or assessment of quality of the predicted structure. The accuracy of the method was tested on a set of high-resolution crystallographic structures as well as on a set of low-resolution protein decoys generated by a protein structure prediction algorithm TASSER. The method is implemented as a standalone program that is available for download from http://cssb.biology.gatech.edu/skolnick/files/PULCHRA.     

FDS: flexible ligand and receptor docking with a continuum solvent model and soft-core energy function

The docking of flexible small molecule ligands to large flexible protein targets is addressed in this article using a two-stage simulation-based method. The methodology presented is a hybrid approach where the first component is a dock of the ligand to the protein binding site, based on deriving sets of simultaneously satisfied intermolecular hydrogen bonds using graph theory and a recursive distance geometry algorithm. The output structures are reduced in number by cluster analysis based on distance similarities. These structures are submitted to a modified Monte Carlo algorithm using the AMBER-AA molecular mechanics force field with the Generalized Born/Surface Area (GB/SA) continuum model. This solvent model is not only less expensive than an explicit representation, but also yields increased sampling. Sampling is also increased using a rotamer library to direct some of the protein side-chain movements along with large dihedral moves. Finally, a softening function for the nonbonded force field terms is used, enabling the potential energy function to be slowly turned on throughout the course of the simulation. The docking procedure is optimized, and the results are presented for a single complex of the arabinose binding protein. It was found that for a rigid receptor model, the X-ray binding geometry was reproduced and uniquely identified based on the associated potential energy. However, when side-chain flexibility was included, although the X-ray structure was identified, it was one of three possible binding geometries that were energetically indistinguishable. These results suggest that on relaxing the constraint on receptor flexibility, the docking energy hypersurface changes from being funnel-like to rugged. A further 14 complexes were then examined using the optimized protocol. For each complex the docking methodology was tested for a fully flexible ligand, both with and without protein side-chain flexibility. For the rigid protein docking, 13 out of the 15 test cases were able to find the experimental binding mode; this number was reduced to 11 for the flexible protein docking. However, of these 11, in the majority of cases the experimental binding mode was not uniquely identified, but was present in a cluster of low energy structures that were energetically indistinguishable. These results not only support the presence of a rugged docking energy hypersurface, but also suggest that it may be necessary to consider the possibility of more than one binding conformation during ligand optimization.     

Prediction of Monomeric and Dimeric Structures of CYP102A1 Using AlphaFold2 and AlphaFold Multimer and Assessment of Point Mutation Effect on the Efficiency of Intra- and Interprotein Electron Transfer

The three-dimensional structure of monomers and homodimers of CYP102A1/WT (wild-type) proteins and their A83F and A83I mutant forms was predicted using the AlphaFold2 (AF2) and AlphaFold Multimer (AFMultimer) programs, which were compared with the rate constants of hydroxylation reactions of these enzyme forms to determine the efficiency of intra- and interprotein electron transport in the CYP102A1 hydroxylase system. The electron transfer rate constants (k_et), which determine the rate of indole hydroxylation by the CYP102A1 system, were calculated based on the distances (R) between donor-acceptor prosthetic groups (PG) FAD→FMN→HEME of these proteins using factor β, which describes an exponential decay from R the speed of electron transport (ET) according to the tunnelling mechanism. It was shown that the structure of monomers in the homodimer, calculated using the AlpfaFold Multimer program, is in good agreement with the experimental structures of globular domains (HEME-, FMN-, and FAD-domains) in CYP102A1/WT obtained by X-ray structural analysis, and the structure of isolated monomers predicted in AF2 does not coincide with the structure of monomers in the homodimer, although a high level of similarity in individual domains remains. The structures of monomers and homodimers of A83F and A83I mutants were also calculated, and their structures were compared with the wild-type protein. Significant differences in the structure of all isolated monomers with respect to the structures of monomers in homodimers were also found for them, and at the same time, insignificant differences were revealed for all homodimers. Comparative analysis for CYP102A1/WT between the calculated intra- and interprotein distances FAD→FMN→HEME and the rate constants of hydroxylation in these proteins showed that the distance between prosthetic groups both in the monomer and in the dimer allows the implementation of electron transfer between PGs, which is consistent with experimental literature data about k_cat. For the mutant form of monomer A83I, an increase in the distance between PGs was obtained, which can restrict electron transportation compared to WT; however, for the dimer of this protein, a decrease in the distance between PGs was observed compared to the WT form, which can lead to an increase in the electron transfer rate constant and, accordingly, k_cat. For the monomer and homodimer of the A83F mutant, the calculations showed an increase in the distance between the PGs compared to the WT form, which should have led to a decrease in the electron transfer rate, but at the same time, for the homodimer, the approach of the aromatic group F262 with heme can speed up transportation for this form and, accordingly, the rate of hydroxylation.     

Cholesterol-phospholipid complexation in fluid bilayers as evidenced by nearest-neighbor recognition measurements

Nearest-neighbor recognition experiments have been carried out using varying ratios of exchangeable dimer analogs of 1,2-dimyristoyl-sn-glycero-3-phosphatidylglycerol and 1,2-distearoyl-sn-glycero-3-phosphatidylglycerol in cholesterol-rich unilamellar vesicles at 60 degrees C. Equilibrium dimer distributions that were obtained support a structural model of the liquid-ordered bilayer in which free cholesterol and the longer-chain phospholipid homodimer are in equilibrium with a complex of unique stoichiometry, where one cholesterol molecule combines with two of the long-chain phospholipid homodimers. In this model, the mixing of the short-chain phospholipids with the uncomplexed long-chain phospholipids is ideal, and the complexed dimers are shielded from the disulfide exchange reaction.     

确定蛋白质-短肽复合物结构的新方法

大部分蛋白质 -蛋白质复合物的三维结构在接触表面都显示出很好的几何匹配 .由于蛋白质的表面几何形状和其它的一些物理化学性质在分子的专一性相互作用中起了主要作用 ,所以 ,接触表面几何形状的互补常常被认为是蛋白质分子识别的基础 .一般来说 ,蛋白质接触表面的几何匹配只涉及 5到 1 0几个紧密堆积的氨基酸残基 ,因此 ,蛋白质与蛋白质配体之间的识别计算可以通过蛋白质与突变周围的或与蛋白质表面紧密接触的配体肽段的识别计算来实现 . Stoddard等 [1] 已经利用从 MBP上选取的八肽成功地计算出接近晶体结构的 MBP-受体复合物 .许多研…     

First preparation of spacer-linked cyclic neooligoaminodeoxysaccharides

The preparation of novel cyclic 1,4-butanediol-linked oligoaminodeoxysugars 3-5 and 7 is described which are potential binders to polynucleotides. Neooligosaccharides 3-5 are assembled by two consecutive metathesis protocols. In the first phase metathesis-mediated dimerization of an aminodeoxymonosaccharide which was either allylated at the anomeric center or at C4 led to E/Z mixtures of C2-symmetric homodimers which were transformed into the corresponding 1,4-butanediol linked disaccharides by catalytic hydrogenation of the central olefinic double bond. Double Q-allylation of the head-to-head dimer set the stage for macrocyclization by means of ring-closing metathesis. This ring-closing process was highly dependent of the configuration in the carbohydrate moieties. arabino-Configured homodimer 15 directly yielded the macrocycle 32 which contains two sugar units while under the same metathesis conditions the corresponding ribo-configured starting homodimer 19 afforded cyclic neotetra- and neohexasaccharides 34 and 35 after a preceding dimerization and trimerization step, respectively. In addition, homodimer 23 was coupled with silylglycoside 14a under Lewis-acid promoted glycosidation conditions to furnish the doubly glycosylated homodimer 31. Ring-closing metathesis afforded the macrocyclic neoaminodeoxyoligosaccharide 36 with alternating 1,4-butanediol linkage and glycosidic bond. The primary cyclization products were finally transformed into the respective cyclic neoaminodeoxyoligosaccharides 3-5 and 7 by catalytic hydrogenation and standard deprotection conditions.     

Metal-mediated affinity and orientation specificity in a computationally designed protein homodimer

Computationally designing protein-protein interactions with high affinity and desired orientation is a challenging task. Incorporating metal-binding sites at the target interface may be one approach for increasing affinity and specifying the binding mode, thereby improving robustness of designed interactions for use as tools in basic research as well as in applications from biotechnology to medicine. Here we describe a Rosetta-based approach for the rational design of a protein monomer to form a zinc-mediated, symmetric homodimer. Our metal interface design, named MID1 (NESG target ID OR37), forms a tight dimer in the presence of zinc (MID1-zinc) with a dissociation constant <30 nM. Without zinc the dissociation constant is 4 μM. The crystal structure of MID1-zinc shows good overall agreement with the computational model, but only three out of four designed histidines coordinate zinc. However, a histidine-to-glutamate point mutation resulted in four-coordination of zinc, and the resulting metal binding site and dimer orientation closely matches the computational model (Cα rmsd = 1.4 ?).     

GalaxyTongDock: Symmetric and asymmetric ab initio protein–protein docking web server with improved energy parameters

Protein–protein docking methods are spotlighted for their roles in providing insights into protein–protein interactions in the absence of full structural information by experiment. GalaxyTongDock is an ab initio protein–protein docking web server that performs rigid-body docking just like ZDOCK but with improved energy parameters. The energy parameters were trained by iterative docking and parameter search so that more native-like structures are selected as top rankers. GalaxyTongDock performs asymmetric docking of two different proteins (GalaxyTongDock_A) and symmetric docking of homo-oligomeric proteins with C_n and D_n symmetries (GalaxyTongDock_C and GalaxyTongDock_D). Performance tests on an unbound docking benchmark set for asymmetric docking and a model docking benchmark set for symmetric docking showed that GalaxyTongDock is better or comparable to other state-of-the-art methods. Experimental and/or evolutionary information on binding interfaces can be easily incorporated by using block and interface options. GalaxyTongDock web server is freely available at http://galaxy.seoklab.org/tongdock . © 2019 Wiley Periodicals, Inc.     

Exploring symmetry as an avenue to the computational design of large protein domains

It has been demonstrated previously that symmetric, homodimeric proteins are energetically favored, which explains their abundance in nature. It has been proposed that such symmetric homodimers underwent gene duplication and fusion to evolve into protein topologies that have a symmetric arrangement of secondary structure elements--"symmetric superfolds". Here, the ROSETTA protein design software was used to computationally engineer a perfectly symmetric variant of imidazole glycerol phosphate synthase and its corresponding symmetric homodimer. The new protein, termed FLR, adopts the symmetric (βα)(8) TIM-barrel superfold. The protein is soluble and monomeric and exhibits two-fold symmetry not only in the arrangement of secondary structure elements but also in sequence and at atomic detail, as verified by crystallography. When cut in half, FLR dimerizes readily to form the symmetric homodimer. The successful computational design of FLR demonstrates progress in our understanding of the underlying principles of protein stability and presents an attractive strategy for the in silico construction of larger protein domains from smaller pieces.     

Protein photocrosslinking reveals dimer of dimers formation on MarR protein in Escherichia coli

The multiple antibiotic resistance regulatory protein(MarR) binds to two promoter sites on the marO operator in Escherichia coli.Our study showed that more than one MarR dimer proteins bound to either of its two promoter sites(Site I and Site II),suggesting that MarR might form higher complexes than homodimers when bound to DNA inside E.coli cells.To further verify this hypothesis,we site-specifically incorporated a photocrosslinking probe at the interface between two MarR dimer proteins.Photolysis in living E.coli cells revealed a covalent linkage between the two interdimer subunits of MarR,suggesting that MarR forms dimer of dimers in vivo.     

FIPSDock: A new molecular docking technique driven by fully informed swarm optimization algorithm

The accurate prediction of protein–ligand binding is of great importance for rational drug design. We present herein a novel docking algorithm called as FIPSDock, which implements a variant of the Fully Informed Particle Swarm (FIPS) optimization method and adopts the newly developed energy function of AutoDock 4.20 suite for solving flexible protein–ligand docking problems. The search ability and docking accuracy of FIPSDock were first evaluated by multiple cognate docking experiments. In a benchmarking test for 77 protein/ligand complex structures derived from GOLD benchmark set, FIPSDock has obtained a successful predicting rate of 93.5% and outperformed a few docking programs including particle swarm optimization (PSO)@AutoDock, SODOCK, AutoDock, DOCK, Glide, GOLD, FlexX, Surflex, and MolDock. More importantly, FIPSDock was evaluated against PSO@AutoDock, SODOCK, and AutoDock 4.20 suite by cross‐docking experiments of 74 protein–ligand complexes among eight protein targets (CDK2, ESR1, F2, MAPK14, MMP8, MMP13, PDE4B, and PDE5A) derived from Sutherland‐crossdock‐set. Remarkably, FIPSDock is superior to PSO@AutoDock, SODOCK, and AutoDock in seven out of eight cross‐docking experiments. The results reveal that FIPS algorithm might be more suitable than the conventional genetic algorithm‐based algorithms in dealing with highly flexible docking problems. © 2012 Wiley Periodicals, Inc.     

Attracting cavities for docking. Replacing the rough energy landscape of the protein by a smooth attracting landscape

Molecular docking is a computational approach for predicting the most probable position of ligands in the binding sites of macromolecules and constitutes the cornerstone of structure‐based computer‐aided drug design. Here, we present a new algorithm called Attracting Cavities that allows molecular docking to be performed by simple energy minimizations only. The approach consists in transiently replacing the rough potential energy hypersurface of the protein by a smooth attracting potential driving the ligands into protein cavities. The actual protein energy landscape is reintroduced in a second step to refine the ligand position. The scoring function of Attracting Cavities is based on the CHARMM force field and the FACTS solvation model. The approach was tested on the 85 experimental ligand–protein structures included in the Astex diverse set and achieved a success rate of 80% in reproducing the experimental binding mode starting from a completely randomized ligand conformer. The algorithm thus compares favorably with current state‐of‐the‐art docking programs. © 2015 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.     

Molecular docking using the molecular lipophilicity potential as hydrophobic descriptor: impact on GOLD docking performance

GOLD is a molecular docking software widely used in drug design. In the initial steps of docking, it creates a list of hydrophobic fitting points inside protein cavities that steer the positioning of ligand hydrophobic moieties. These points are generated based on the Lennard-Jones potential between a carbon probe and each atom of the residues delimitating the binding site. To thoroughly describe hydrophobic regions in protein pockets and properly guide ligand hydrophobic moieties toward favorable areas, an in-house tool, the MLP filter, was developed and herein applied. This strategy only retains GOLD hydrophobic fitting points that match the rigorous definition of hydrophobicity given by the molecular lipophilicity potential (MLP), a molecular interaction field that relies on an atomic fragmental system based on 1-octanol/water experimental partition coefficients (log P(oct)). MLP computations in the binding sites of crystallographic protein structures revealed that a significant number of points considered hydrophobic by GOLD were actually polar according to the MLP definition of hydrophobicity. To examine the impact of this new tool, ligand-protein complexes from the Astex Diverse Set and the PDB bind core database were redocked with and without the use of the MLP filter. Reliable docking results were obtained by using the MLP filter that increased the quality of docking in nonpolar cavities and outperformed the standard GOLD docking approach.     

Applying flexible molecular docking to simulate protein retention behavior in hydrophobic interaction chromatography

Interaction between proteins and stationary phase in hydrophobic interaction chromatography (HIC) is differentiated into two thermodynamic processes involving direct nonbonding/conformation interac- tion and surface hydrophobic effect of proteins, hence quantitatively giving rise to a binary linear rela- tion between HIC retention time (RT) at concentrated salting liquid and ligand-protein binding free en- ergy. Then, possible binding manners for 27 proteins of known crystal structures with hydrophobic ligands are simulated and analyzed via ICM flexible molecular docking and genetic algorithm, with re- sults greatly consistent with experimental values. By investigation, it is confirmed local hydrophobic effects of proteins and nonbinding/conformation interaction between ligand and protein both notably influence HIC chromatogram retention behaviors, mainly focusing on exposed portions on the protein surface.     

Molecular dynamics simulations and structure-based network analysis reveal structural and functional aspects of G-protein coupled receptor dimer interactions

A significant amount of experimental evidence suggests that G-protein coupled receptors (GPCRs) do not act exclusively as monomers but also form biologically relevant dimers and oligomers. However, the structural determinants, stoichiometry and functional importance of GPCR oligomerization remain topics of intense speculation. In this study we attempted to evaluate the nature and dynamics of GPCR oligomeric interactions. A representative set of GPCR homodimers were studied through Coarse-Grained Molecular Dynamics simulations, combined with interface analysis and concepts from network theory for the construction and analysis of dynamic structural networks. Our results highlight important structural determinants that seem to govern receptor dimer interactions. A conserved dynamic behavior was observed among different GPCRs, including receptors belonging in different GPCR classes. Specific GPCR regions were highlighted as the core of the interfaces. Finally, correlations of motion were observed between parts of the dimer interface and GPCR segments participating in ligand binding and receptor activation, suggesting the existence of mechanisms through which dimer formation may affect GPCR function. The results of this study can be used to drive experiments aimed at exploring GPCR oligomerization, as well as in the study of transmembrane protein–protein interactions in general.     

Molecular Modeling of Interactions of the Benzolactam-V8 Modulators with the Cys2 Domain of Protein Kinase Cδ

Molecular modeling of interactions of four 7- or 8-substituted benzolactam-V8 （BLV） molecules with the cys2 activator-binding domain of protein kinase C （PKCδ） was carried out using molecular docking program Autodock. The docked models reveal that the hydroxymethyl group at the C（5） atom of the eight-membered ring of each BLV is bound at the bottom of the binding groove of the cys2 domain of PKCδ The BLV molecules make hydrogen bonds and hydrophobic interactions with PKCδ, which are similar to those in the crystal structure of the cys2 domain of PKCδ in complex with phorbol 13-acetate. BLV-1 does not contain a long side chain that is hydrophobic and necessary for membrane insertion, so that it would not be a potent modulator of PKCδ. The other three BLV molecules have long side chains substituted at C（7） or C（8） atoms, and it was predicted, based on the docking results, that they had the PKCδ-binding affinity in the order of BLV-2〉BLV-4〉BLV-3, and BLV-2 would be a potent activator of PKCδ.     

Modeling the Dynamics of Protein–Protein Interfaces,How and Why?

Protein–protein assemblies act as a key component in numerous cellular processes. Their accurate modeling at the atomic level remains a challenge for structural biology. To address this challenge, several docking and a handful of deep learning methodologies focus on modeling protein–protein interfaces. Although the outcome of these methods has been assessed using static reference structures, more and more data point to the fact that the interaction stability and specificity is encoded in the dynamics of these interfaces. Therefore, this dynamics information must be taken into account when modeling and assessing protein interactions at the atomistic scale. Expanding on this, our review initially focuses on the recent computational strategies aiming at investigating protein–protein interfaces in a dynamic fashion using enhanced sampling, multi-scale modeling, and experimental data integration. Then, we discuss how interface dynamics report on the function of protein assemblies in globular complexes, in fuzzy complexes containing intrinsically disordered proteins, as well as in active complexes, where chemical reactions take place across the protein–protein interface.