Hot‐spot analysis to dissect the functional protein–protein interface of a tRNA‐modifying enzyme

Interference with protein–protein interactions of interfaces larger than 1500 Ų by small drug‐like molecules is notoriously difficult, particularly if targeting homodimers. The tRNA modifying enzyme Tgt is only functionally active as a homodimer. Thus, blocking Tgt dimerization is a promising strategy for drug therapy as this protein is key to the development of Shigellosis. Our goal was to identify hot‐spot residues which, upon mutation, result in a predominantly monomeric state of Tgt. The detailed understanding of the spatial location and stability contribution of the individual interaction hot‐spot residues and the plasticity of motifs involved in the interface formation is a crucial prerequisite for the rational identification of drug‐like inhibitors addressing the respective dimerization interface. Using computational analyses, we identified hot‐spot residues that contribute particularly to dimer stability: a cluster of hydrophobic and aromatic residues as well as several salt bridges. This in silico prediction led to the identification of a promising double mutant, which was validated experimentally. Native nano‐ESI mass spectrometry showed that the dimerization of the suggested mutant is largely prevented resulting in a predominantly monomeric state. Crystal structure analysis and enzyme kinetics of the mutant variant further support the evidence for enhanced monomerization and provide first insights into the structural consequences of the dimer destabilization. Proteins 2014; 82:2713–2732. © 2014 Wiley Periodicals, Inc.     

BECN2 interacts with ATG14 through a metastable coiled‐coil to mediate autophagy

ATG14 binding to BECN/Beclin homologs is essential for autophagy, a critical catabolic homeostasis pathway. Here, we show that the α‐helical, coiled‐coil domain (CCD) of BECN2, a recently identified mammalian BECN1 paralog, forms an antiparallel, curved homodimer with seven pairs of nonideal packing interactions, while the BECN2 CCD and ATG14 CCD form a parallel, curved heterodimer stabilized by multiple, conserved polar interactions. Compared to BECN1, the BECN2 CCD forms a weaker homodimer, but binds more tightly to the ATG14 CCD. Mutation of nonideal BECN2 interface residues to more ideal pairs improves homodimer self‐association and thermal stability. Unlike BECN1, all BECN2 CCD mutants bind ATG14, although more weakly than wild type. Thus, polar BECN2 CCD interface residues result in a metastable homodimer, facilitating dissociation, but enable better interactions with polar ATG14 residues stabilizing the BECN2:ATG14 heterodimer. These structure‐based mechanistic differences in BECN1 and BECN2 homodimerization and heterodimerization likely dictate competitive ATG14 recruitment.     

Structure of vaccinia virus A46, an inhibitor of TLR4 signaling pathway,shows the conformation of VIPER motif

Vaccinia virus (VACV) encodes many proteins that interfere with the host immune system. Vaccinia virus A46 protein specifically targets the BB‐loop motif of TIR‐domain‐containing proteins to disrupt receptor:adaptor (e.g., TLR4:MAL and TLR4:TRAM) interactions of the toll‐like receptor signaling. The crystal structure of A46 (75–227) determined at 2.58 Å resolution showed that A46 formed a homodimer and adopted a Bcl‐2‐like fold similar to other VACV proteins such as A52, B14, and K7. Our structure also revealed that VIPER (viral inhibitory peptide of TLR4) motif resides in the α1‐helix and six residues of the VIPER region were exposed to surface for binding to target proteins. In vitro binding assays between wild type and six mutants A46 (75–227) and full‐length MAL identified critical residues in the VIPER motif. Computational modeling of the A46:MAL complex structure showed that the VIPER region of A46 and AB loop of MAL protein formed a major binding interface. In summary, A46 is a homodimer with a Bcl‐2‐like fold and VIPER motif is believed to be involved in the interaction with MAL protein based on our binding assays.     

DockRank: Ranking docked conformations using partner‐specific sequence homology‐based protein interface prediction

Selecting near‐native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. DockRank uses interface residues predicted by partner‐specific sequence homology‐based protein–protein interface predictor (PS‐HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state‐of‐the‐art docking scoring functions using Success Rate (the percentage of cases that have at least one near‐native conformation among the top m conformations) and Hit Rate (the percentage of near‐native conformations that are included among the top m conformations). In cases where it is possible to obtain partner‐specific (PS) interface predictions from PS‐HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state‐of‐the‐art energy‐based scoring functions (improving Success Rate by up to 4‐fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39‐fold). The latter result underscores the importance of using partner‐specific interface residues in scoring docked conformations. We show that DockRank, when used to re‐rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/ . Proteins 2014; 82:250–267. © 2013 Wiley Periodicals, Inc.     

Counterbalance of ligand‐ and self‐coupled motions characterizes multispecificity of ubiquitin

Date hub proteins are a type of proteins that show multispecificity in a time‐dependent manner. To understand dynamic aspects of such multispecificity we studied Ubiquitin as a typical example of a date hub protein. Here we analyzed 9 biologically relevant Ubiquitin‐protein (ligand) heterodimer structures by using normal mode analysis based on an elastic network model. Our result showed that the self‐coupled motion of Ubiquitin in the complex, rather than its ligand‐coupled motion, is similar to the motion of Ubiquitin in the unbound condition. The ligand‐coupled motions are correlated to the conformational change between the unbound and bound conditions of Ubiquitin. Moreover, ligand‐coupled motions favor the formation of the bound states, due to its in‐phase movements of the contacting atoms at the interface. The self‐coupled motions at the interface indicated loss of conformational entropy due to binding. Therefore, such motions disfavor the formation of the bound state. We observed that the ligand‐coupled motions are embedded in the motions of unbound Ubiquitin. In conclusion, multispecificity of Ubiquitin can be characterized by an intricate balance of the ligand‐ and self‐coupled motions, both of which are embedded in the motions of the unbound form.     

Loop‐loop interactions govern multiple steps in indole‐3‐glycerol phosphate synthase catalysis

Substrate binding, product release, and likely chemical catalysis in the tryptophan biosynthetic enzyme indole‐3‐glycerol phosphate synthase (IGPS) are dependent on the structural dynamics of the β1α1 active‐site loop. Statistical coupling analysis and molecular dynamic simulations had previously indicated that covarying residues in the β1α1 and β2α2 loops, corresponding to Arg54 and Asn90, respectively, in the Sulfolobus sulfataricus enzyme (ssIGPS), are likely important for coordinating functional motions of these loops. To test this hypothesis, we characterized site mutants at these positions for changes in catalytic function, protein stability and structural dynamics for the thermophilic ssIGPS enzyme. Although there were only modest changes in the overall steady‐state kinetic parameters, solvent viscosity and solvent deuterium kinetic isotope effects indicated that these amino acid substitutions change the identity of the rate‐determining step across multiple temperatures. Surprisingly, the N90A substitution had a dramatic effect on the general acid/base catalysis of the dehydration step, as indicated by the loss of the descending limb in the pH rate profile, which we had previously assigned to Lys53 on the β1α1 loop. These changes in enzyme function are accompanied with a quenching of ps‐ns and µs‐ms timescale motions in the β1α1 loop as measured by nuclear magnetic resonance studies. Altogether, our studies provide structural, dynamic and functional rationales for the coevolution of residues on the β1α1 and β2α2 loops, and highlight the multiple roles that the β1α1 loop plays in IGPS catalysis. Thus, substitution of covarying residues in the active‐site β1α1 and β2α2 loops of indole‐3‐glycerol phosphate synthase results in functional, structural, and dynamic changes, highlighting the multiple roles that the β1α1 loop plays in enzyme catalysis and the importance of regulating the structural dynamics of this loop through noncovalent interactions with nearby structural elements.     

Determinants of substrate specificity and biochemical properties of the sn‐glycerol‐3‐phosphate ATP binding cassette transporter (UgpB–AEC2) of Escherichia coli

Under phosphate starvation conditions, Escherichia coli can utilize sn‐glycerol‐3‐phosphate (G3P) and G3P diesters as phosphate source when transported by an ATP binding cassette importer composed of the periplasmic binding protein, UgpB, the transmembrane subunits, UgpA and UgpE, and a homodimer of the nucleotide binding subunit, UgpC. The current knowledge on the Ugp transporter is solely based on genetic evidence and transport assays using intact cells. Thus, we set out to characterize its properties at the level of purified protein components. UgpB was demonstrated to bind G3P and glycerophosphocholine with dissociation constants of 0.68 ± 0.02 μM and 5.1 ± 0.3 μM, respectively, while glycerol‐2‐phosphate (G2P) is not a substrate. The crystal structure of UgpB in complex with G3P was solved at 1.8 Å resolution and revealed the interaction with two tryptophan residues as key to the preferential binding of linear G3P in contrast to the branched G2P. Mutational analysis validated the crucial role of Trp‐169 for G3P binding. The purified UgpAEC₂ complex displayed UgpB/G3P‐stimulated ATPase activity in proteoliposomes that was neither inhibited by phosphate nor by the signal transducing protein PhoU or the phosphodiesterase UgpQ. Furthermore, a hybrid transporter composed of MalFG–UgpC could be functionally reconstituted while a UgpAE–MalK complex was unstable.     

EDENetworks: A user‐friendly software to build and analyse networks in biogeography,ecology and population genetics

The recent application of graph‐based network theory analysis to biogeography, community ecology and population genetics has created a need for user‐friendly software, which would allow a wider accessibility to and adaptation of these methods. EDENetworks aims to fill this void by providing an easy‐to‐use interface for the whole analysis pipeline of ecological and evolutionary networks starting from matrices of species distributions, genotypes, bacterial OTUs or populations characterized genetically. The user can choose between several different ecological distance metrics, such as Bray‐Curtis or Sorensen distance, or population genetic metrics such as F_ST or Goldstein distances, to turn the raw data into a distance/dissimilarity matrix. This matrix is then transformed into a network by manual or automatic thresholding based on percolation theory or by building the minimum spanning tree. The networks can be visualized along with auxiliary data and analysed with various metrics such as degree, clustering coefficient, assortativity and betweenness centrality. The statistical significance of the results can be estimated either by resampling the original biological data or by null models based on permutations of the data.     

Female‐driven intersexual coevolution in beetle genitalia

Genital coevolution is a pervasive phenomenon as changes in one sex tend to impose fitness consequences on the other, generating sexual conflict. Sexual conflict is often thought to cause stronger selection on males due to the Darwin–Bateman's anisogamy paradigm. However, recent studies have demonstrated that female genitalia may be equally elaborated and perform diverse extra‐copulatory functions. These characteristics suggest that female genitals can also be primary targets of selection, especially where natural selection acts on female‐exclusive functions such as oviposition. Here, we test this hypothesis in a statistical phylogenetic framework across the whole beetle (Coleoptera) phylogeny, investigating whether coevolution of specific genital traits may be triggered by changes in females. We focus on traits of the proctiger, which composes part of the male terminalia and the female ovipositor. Our results present a comprehensive case of male–female genital coevolution and provide solid statistical evidence for a female‐initiated coevolutionary process where the vast majority of evolutionary transitions in males have occurred only after changes in females. We corroborate the hypothesis that female traits may change independently and elicit counter‐adaptations in males. Furthermore, by showing a consistent pattern across the phylogeny of the most diverse group of animals, our results suggest that this female‐driven dynamics may persist through long time scales.     

Coevolving protein residues: maximum likelihood identification and relationship to structure

The identification of protein sites undergoing correlated evolution (coevolution) is of great interest due to the possibility that these pairs will tend to be adjacent in the three-dimensional structure. Identification of such pairs should provide useful information for understanding the evolutionary process, predicting the effects of site-directed substitution, and potentially for predicting protein structure. Here, we develop and apply a maximum likelihood method with the aim of improving detection of coevolution. Unlike previous methods which have had limited success, this method allows for correlations induced by phylogenetic relationships and for variation in rate of evolution along branches, and does not rely on accurate reconstruction of ancestral nodes. In order to reduce the complexity of coevolutionary relationships and identify the primary component of pairwise coevolution between two sites, we reduce the data to a two-state system at each site, regardless of the actual number of residues observed at that site. Simulations show that this strategy is good at identifying simple correlations and at recognizing cases in which the data are insufficient to distinguish between coevolution and spurious correlations. The new method was tested by using size and charge characteristics to group the residues at each site, and then evaluating coevolution in myoglobin sequences. Grouping based on physicochemical characteristics allows categorization of coevolving sites into positive and negative coevolution, depending on the correlation between equilibrium state frequencies. We detected a striking excess of negative coevolution (corresponding to charge) at sites brought into proximity by the periodicity of the alpha-helix, and there was also a tendency for sites with significant likelihood ratios to be close in the three-dimensional structure. Sites on the surface of the protein appear to coevolve both when they are close in the structure, and when they are distant, implying a role for folding and/or avoidance of quaternary structure in the coevolution process.     

Energetics and protomer communication in the dynamical structure of S100A13 in free and protein-bound states

S100A13 is S100 family of EF-hand-containing calcium-binding protein involved in the secretion of some growth factors and pro-inflammatory cytokines lacking signal peptides. The involvement of S100A13 in cancer progression and inflammatory diseases has been reported. In this study, structures generated during atomistic molecular dynamics simulation were studied. Dynamical network analysis data revealed that native inter-protomer communication network driven principally by vdW interaction (~550 kj/mol) is altered (Receptor for advanced glycation end products (RAGE) C2- and Fibroblast growth factor (FGF)-1-bound S100A13) or completely abolished (interleukin-1 (IL1)-α- and C2A-p40Syt1-bound S100A13) in protein-bound S100A13 homodimer. Bulk water density (weighted atomic density) around exposed S100A13 homodimer surface explored tends to follow the dynamical network lead as S100A13 homodimer appeared densely solvated in C2A-p40Syt1- and IL1)-α-bound states but not in RAGE C2- and FGF-1-bound biosystems. Furthermore, projection of radius of gyration and root mean square deviation (from native structure) variables of the generated structures along the 3D-free energy surface showed anti-parallel β-sheet proximal to Ca²⁺-binding loops-I/II in most metastable complexes retrieved from energy minima state with strong indications for β-sheet network formation during protein binding. Interaction between S100A13 homodimer and ligand–proteins may be dictated by the strength of vdW and electrostatic interaction with possible involvement of bulk water desolvation in some complexes. All these results strongly suggest that disruption of multiprotein receptor complex can be achieved by designing specific compounds targeting a specific aspect of S100A13/protein interaction; such drugs may have clinical usefulness in blocking angiogenesis, reversing cell proliferation and attenuating inflammatory processes.     

C‐H…O hydrogen bonds in FK506‐binding protein–ligand interactions

Hydrogen bonds are important interaction forces observed in protein structures. They can be classified as stronger or weaker depending on their energy, thereby reflecting on the type of donor. The contribution of weak hydrogen bonds is deemed as an important factor toward structure stability along with the stronger bonds. One such bond, the C‐H…O type hydrogen bond, is shown to make a contribution in maintaining three dimensional structures of proteins. Apart from their presence within protein structures, the role of these bonds in protein–ligand interactions is also noteworthy. In this study, we present a statistical analysis on the presence of C‐H…O hydrogen bonds observed between FKBPs and their cognate ligands. The FK506‐binding proteins (FKBPs) carry peptidyl cis–trans isomerase activity apart from the immunosuppressive property by binding to the immunosuppressive drugs FK506 or rapamycin. Because the active site of FKBPs is lined up by many hydrophobic residues, we speculated that the prevalence of C‐H…O hydrogen bonds will be considerable. In a total of 25 structures analyzed, a higher frequency of C‐H…O hydrogen bonds is observed in comparison with the stronger hydrogen bonds. These C‐H…O hydrogen bonds are dominated by a highly conserved donor, the C^α/β of Val55 and an acceptor, the backbone oxygen of Glu54. Both these residues are positioned in the β4‐α1 loop, whereas the other residues Tyr26, Phe36 and Phe99 with higher frequencies are lined up at the opposite face of the active site. These preferences could be implicated in FKBP pharmacophore models toward enhancing the ligand affinity. This study could be a prelude to studying other proteins with hydrophobic pockets to gain better insights into ligand recognition. Copyright © 2013 John Wiley & Sons, Ltd.     

Comparison analysis of primary ligand‐binding sites in seven‐helix membrane proteins

Seven‐helix transmembrane proteins, including the G‐protein‐coupled receptors (GPCRs), mediate a broad range of fundamental cellular activities through binding to a wide range of ligands. Understanding the structural basis for the ligand‐binding selectivity of these proteins is of significance to their structure‐based drug design. Comparison analysis of proteins' ligand‐binding sites provides a useful way to study their structure‐activity relationships. Various computational methods have been developed for the binding‐site comparison of soluble proteins. In this work, we applied this approach to the analysis of the primary ligand‐binding sites of 92 seven‐helix transmembrane proteins. Results of the studies confirmed that the binding site of bacterial rhodopsins is indeed different from all GPCRs. In the latter group, further comparison of the binding sites indicated a group of residues that could be responsible for ligand‐binding selectivity and important for structure‐based drug design. Furthermore, unexpected binding‐site dissimilarities were observed among adrenergic and adenosine receptors, suggesting that the percentage of the overall sequence identity between a target protein and a template protein alone is not sufficient for selecting the best template for homology modeling of seven‐helix membrane proteins. These results provided novel insight into the structural basis of ligand‐binding selectivity of seven‐helix membrane proteins and are of practical use to the computational modeling of these proteins. © 2010 Wiley Periodicals, Inc. Biopolymers 95: 31–38, 2011.     

Exploiting the Link between Protein Rigidity and Thermostability for Data‐Driven Protein Engineering

Understanding and exploiting the relationship between microscopic structure and macroscopic stability is important for developing strategies to improve protein stability at high temperatures. The thermostability of proteins has been repeatedly linked to an enhanced structural rigidity of the folded native state. In the current study, the rigidity of protein structures from mesophilic and thermophilic organisms along a thermal unfolding trajectory is directly probed. In order to perform this, protein structures were modeled as constraint networks, and the rigidity in these networks was quantified using the Floppy Inclusion and Rigid Substructure Topography (FIRST) method. During the thermal unfolding, a phase transition was observed that defines the rigidity percolation threshold and corresponds to the folded‐unfolded transition in protein folding. Using concepts from percolation theory and network science, a higher phase transition temperature was observed for ca. two‐thirds of the proteins from thermophilic organisms compared to their mesophilic counterparts, when applied to a data set of 20 pairs of homologues. From both the analysis of the microstructure of the constraint networks and monitoring the macroscopic behavior during the thermal unfolding, direct evidence was found for the “corresponding states” concept, which states that mesophilic and thermophilic enzymes are in corresponding states of similar flexibility at their respective optimal temperature. Finally, the current approach facilitated the identification of structural features from which a destabilization of the structure originates upon thermal unfolding. These predictions show a good agreement with the experimental data. Therefore, the information might be exploited in data‐driven protein engineering by pointing to residues that should be varied to obtain a protein with higher thermostability.     

Coiled‐coil interactions are required for post‐Golgi R‐SNARE trafficking

The sorting of post‐Golgi R‐SNAREs (vesicle‐associated membrane protein (VAMP)1, 2, 3, 4, 7 and 8) is still poorly understood. To address this, we developed a system to investigate their localization, trafficking and cell‐surface levels. Here, we show that the distribution and internalization of VAMPs 3 and 8 are determined solely through a new conserved mechanism that uses coiled‐coil interactions, and that VAMP4 does not require these interactions for its trafficking. We propose that VAMPs 3 and 8 are trafficked while in a complex with Q‐SNAREs. We also show that the dileucine motif of VAMP4 is required for both its internalization and retrieval to the trans‐Golgi network. However, when the dileucine motif is mutated, the construct can still be internalized potentially through coiled‐coil interactions with Q‐SNAREs.     

Non‐interacting surface solvation and dynamics in protein–protein interactions

Protein–protein interactions control a plethora of cellular processes, including cell proliferation, differentiation, apoptosis, and signal transduction. Understanding how and why proteins interact will inevitably lead to novel structure‐based drug design methods, as well as design of de novo binders with preferred interaction properties. At a structural and molecular level, interface and rim regions are not enough to fully account for the energetics of protein–protein binding, even for simple lock‐and‐key rigid binders. As we have recently shown, properties of the global surface might also play a role in protein–protein interactions. Here, we report on molecular dynamics simulations performed to understand solvent effects on protein–protein surfaces. We compare properties of the interface, rim, and non‐interacting surface regions for five different complexes and their free components. Interface and rim residues become, as expected, less mobile upon complexation. However, non‐interacting surface appears more flexible in the complex. Fluctuations of polar residues are always lower compared with charged ones, independent of the protein state. Further, stable water molecules are often observed around polar residues, in contrast to charged ones. Our analysis reveals that (a) upon complexation, the non‐interacting surface can have a direct entropic compensation for the lower interface and rim entropy and (b) the mobility of the first hydration layer, which is linked to the stability of the protein–protein complex, is influenced by the local chemical properties of the surface. These findings corroborate previous hypotheses on the role of the hydration layer in shielding protein–protein complexes from unintended protein–protein interactions. Proteins 2015; 83:445–458. © 2014 Wiley Periodicals, Inc.     

Proteomic analysis of resting and thrombin‐stimulated platelets reveals the translocation and functional relevance of HIP‐55 in platelets

The platelet surface is a dynamic interface that changes rapidly in response to stimuli to co‐ordinate the formation of thrombi at sites of vascular injury. Tight control is essential as loss of organisation may result in the inappropriate formation of thrombi (thrombosis) or excessive bleeding. In this paper we describe the comparative analysis of resting and thrombin‐stimulated platelet membrane proteomes and associated proteins to identify proteins important to platelet function. Surface proteins were labelled using a biotin tag and isolated by NeurtrAvidin affinity chromatography. Liquid phase IEF and SDS‐PAGE were used to separate proteins, and bands of increased intensity in the stimulated platelet fractions were digested and identified by FT‐ICR mass spectrometry. Novel proteins were identified along with proteins known to be translocated to the platelet surface. Furthermore, many platelet proteins revealed changes in location associated with function, including G6B and Hip‐55. HIP‐55 is an SH3‐binding protein important in T‐cell receptor signalling. Further analysis of HIP‐55 revealed that this adaptor protein becomes increasingly associated with both Syk and integrin β3 upon platelet activation. Analysis of HIP‐55 deficient platelets revealed reduced fibrinogen binding upon thrombin stimulation, suggesting HIP‐55 to be an important regulator of platelet function.     

Dynamic features of homodimer interfaces calculated by normal‐mode analysis

Knowledge of the dynamic features of protein interfaces is necessary for a deeper understanding of protein–protein interactions. We performed normal‐mode analysis (NMA) of 517 nonredundant homodimers and their protomers to characterize dimer interfaces from a dynamic perspective. The motion vector calculated by NMA for each atom of a dimer was decomposed into internal and external motion vectors in individual component subunits, followed by the averaging of time‐averaged correlations between these vectors over atom pairs in the interface. This averaged correlation coefficient (ACC) was defined for various combinations of vectors and investigated in detail. ACCs decrease exponentially with an increasing interface area and r‐value, that is, interface area divided by the entire subunit surface area. As the r‐value reflects the nature of dimer formation, the result suggests that both the interface area and the nature of dimer formation are responsible for the dynamic properties of dimer interfaces. For interfaces with small or medium r‐values and without intersubunit entanglements, ACCs are found to increase on dimer formation when compared with those in the protomer state. In contrast, ACCs do not increase on dimer formation for interfaces with large r‐values and intersubunit entanglements such as in interwinding dimers. Furthermore, relationships between ACCs for intrasubunit atom pairs and for intersubunit atom pairs are found to significantly differ between interwinding and noninterwinding dimers for external motions. External motions are considered as an important factor for characterizing dimer interfaces.     

A computational method for the design of nested proteins by loop‐directed domain insertion

The computational design of novel nested proteins—in which the primary structure of one protein domain (insert) is flanked by the primary structure segments of another (parent)—would enable the generation of multifunctional proteins. Here we present a new algorithm, called Loop‐Directed Domain Insertion (LooDo), implemented within the Rosetta software suite, for the purpose of designing nested protein domain combinations connected by flexible linker regions. Conformational space for the insert domain is sampled using large libraries of linker fragments for linker‐to‐parent domain superimposition followed by insert‐to‐linker superimposition. The relative positioning of the two domains (treated as rigid bodies) is sampled efficiently by a grid‐based, mutual placement compatibility search. The conformations of the loop residues, and the identities of loop as well as interface residues, are simultaneously optimized using a generalized kinematic loop closure algorithm and Rosetta EnzymeDesign, respectively, to minimize interface energy. The algorithm was found to consistently sample near‐native conformations and interface sequences for a benchmark set of structurally similar but functionally divergent domain‐inserted enzymes from the α/β hydrolase superfamily, and discriminates well between native and nonnative conformations and sequences, although loop conformations tended to deviate from the native conformations. Furthermore, in cross‐domain placement tests, native insert‐parent domain combinations were ranked as the best‐scoring structures compared to nonnative domain combinations. This algorithm should be broadly applicable to the design of multi‐domain protein complexes with any combination of inserted or tandem domain connections.