Shape Complementarity Research Articles

Boosted Enzyme Activity via Encapsulation within Metal-Organic Frameworks with Pores Matching Enzyme Size and Shape.

A novel and versatile approach called "physical imprinting" is introduced to modulate enzyme conformation using mesoporous materials, addressing challenges in achieving improved enzyme activity and stability. Metal-organic frameworks with tailored mesopores, precisely matching enzyme size and shape, are synthesized. Remarkably, enzymes encapsulated within these customized mesopores exhibit over 1670% relative activity compared to free enzymes, maintaining outstanding efficiency even under harsh conditions such as heat, exposure to organic solvents, wide-ranging pH extremes from acidic to alkaline, and exposure to a digestion cocktail. After 18 consecutive cycles of use, the immobilized enzymes retain 80% of their initial activity. Additionally, the encapsulated enzymes exhibit a substantial increase in catalytic efficiency, with a 14.1-fold enhancement in kcat/KM compared to native enzymes. This enhancement is among the highest reported for immobilized enzymes. The improved enzyme activity and stability are corroborated by solid-state UV-vis, electron paramagnetic resonance, Fourier-transform infrared spectroscopy, and solid-state NMR spectroscopy. The findings not only offer valuable insights into the crucial role of size and shape complementarity within confined microenvironments but also establish a new pathway for developing solid carriers capable of enhancing enzyme activity and stability.

Structural basis for peroxidase encapsulation inside the encapsulin from the Gram-negative pathogen Klebsiella pneumoniae

Encapsulins are self-assembling protein nanocompartments capable of selectively encapsulating dedicated cargo proteins, including enzymes involved in iron storage, sulfur metabolism, and stress resistance. They represent a unique compartmentalization strategy used by many pathogens to facilitate specialized metabolic capabilities. Encapsulation is mediated by specific cargo protein motifs known as targeting peptides (TPs), though the structural basis for encapsulation of the largest encapsulin cargo class, dye-decolorizing peroxidases (DyPs), is currently unknown. Here, we characterize a DyP-containing encapsulin from the enterobacterial pathogen Klebsiella pneumoniae. By combining cryo-electron microscopy with TP and TP-binding site mutagenesis, we elucidate the molecular basis for cargo encapsulation. TP binding is mediated by cooperative hydrophobic and ionic interactions as well as shape complementarity. Our results expand the molecular understanding of enzyme encapsulation inside protein nanocompartments and lay the foundation for rationally modulating encapsulin cargo loading for biomedical and biotechnological applications.

Complementary hydrophobic interaction of the redox enzyme maturation protein NarJ with the signal peptide of the respiratory nitrate reductase NarG

In bacteria, NarJ plays an essential role as a redox enzyme maturation protein in the assembly of the nitrate reductase NarGHI by interacting with the N-terminal signal peptide of NarG to facilitate cofactor incorporation into NarG. The purpose of our research was to elucidate the exact mechanism of NarG signal peptide recognition by NarJ. We determined the structures of NarJ alone and in complex with the signal peptide of NarG via X-ray crystallography and verified the NarJ-NarG interaction through mutational, binding, and molecular dynamics simulation studies. NarJ adopts a curved α-helix bundle structure with a U-shaped hydrophobic groove on its concave side. This groove accommodates the signal peptide of NarG via a dual binding mode in which the left and right parts of the NarJ groove each interact with two consecutive hydrophobic residues from the N- and C-terminal regions of the NarG signal peptide, respectively, through shape and chemical complementarity. This binding is accompanied by unwinding of the helical structure of the NarG signal peptide and by stabilization of the NarG-binding loop of NarJ. We conclude that NarJ recognizes the NarG signal peptide through a complementary hydrophobic interaction mechanism that mediates a structural rearrangement.

Design of protein-binding peptides with controlled binding affinity: the case of SARS-CoV-2 receptor binding domain and angiotensin-converting enzyme 2 derived peptides.

The development of methods able to modulate the binding affinity between proteins and peptides is of paramount biotechnological interest in view of a vast range of applications that imply designed polypeptides capable to impair or favour Protein-Protein Interactions. Here, we applied a peptide design algorithm based on shape complementarity optimization and electrostatic compatibility and provided the first experimental in vitro proof of the efficacy of the design algorithm. Focusing on the interaction between the SARS-CoV-2 Spike Receptor-Binding Domain (RBD) and the human angiotensin-converting enzyme 2 (ACE2) receptor, we extracted a 23-residues long peptide that structurally mimics the major interacting portion of the ACE2 receptor and designed in silico five mutants of such a peptide with a modulated affinity. Remarkably, experimental KD measurements, conducted using biolayer interferometry, matched the in silico predictions. Moreover, we investigated the molecular determinants that govern the variation in binding affinity through molecular dynamics simulation, by identifying the mechanisms driving the different values of binding affinity at a single residue level. Finally, the peptide sequence with the highest affinity, in comparison with the wild type peptide, was expressed as a fusion protein with human H ferritin (HFt) 24-mer. Solution measurements performed on the latter constructs confirmed that peptides still exhibited the expected trend, thereby enhancing their efficacy in RBD binding. Altogether, these results indicate the high potentiality of this general method in developing potent high-affinity vectors for hindering/enhancing protein-protein associations.

An in silico investigation on the binding site preference of PD-1 and PD-L1 for designing antibodies for targeted cancer therapy.

Cancer control and treatment remain a significant challenge in cancer therapy and recently immune checkpoints has considered as a novel treatment strategy to develop anti-cancer drugs. Many cancer types use the immune checkpoints and its ligand, PD-1/PD-L1 pathway, to evade detection and destruction by the immune system, which is associated with altered effector function of PD-1 and PD-L1 overexpression on cancer cells to deactivate T cells. In recent years, mAbs have been employed to block immune checkpoints, therefore normalization of the anti-tumor response has enabled the scientists to develop novel biopharmaceuticals. In vivo affinity maturation of antibodies in targeted therapy has sometimes failed, and current experimental methods cannot accommodate the accurate structural details of protein-protein interactions. Therefore, determining favorable binding sites on the protein surface for modulator design of these interactions is a major challenge. In this study, we used the in silico methods to identify favorable binding sites on the PD-1 and PD-L1 and to optimize mAb variants on a large scale. At first, all the binding areas on PD-1 and PD-L1 have been identified. Then, using the RosettaDesign protocol, thousands of antibodies have been generated for 11 different regions on PD-1 and PD-L1 and then the designs with higher stability, affinity, and shape complementarity were selected. Next, molecular dynamics simulations and MM-PBSA analysis were employed to understand the dynamic, structural features of the complexes and measure the binding affinity of the final designs. Our results suggest that binding sites 1, 3 and 6 on PD-1 and binding sites 9 and 11 on PD-L1 can be regarded as the most appropriate sites for the inhibition of PD-1-PD-L1 interaction by the designed antibodies. This study provides comprehensive information regarding the potential binding epitopes on PD-1 which could be considered as hotspots for designing potential biopharmaceuticals. We also showed that mutations in the CDRs regions will rearrange the interaction pattern between the designed antibodies and targets (PD-1 and PD-L1) with improved affinity to effectively inhibit protein-protein interaction and block the immune checkpoint.

A corannulene-based metallobox for the encapsulation of fullerenes.

A corannulene-bis-N-imidazolium salt was used for the synthesis of two corannulene-bis-N-heterocyclic carbenes of dirhodium(i) complexes of formula (corannulene-di-NHC)[RhCl(COD)]2 and (corannulene-di-NHC)[RhCl(CO)2]2. Both complexes were characterized by spectroscopic techniques, and the electron-donating properties of the corannulene-di-NHC ligand were studied by means of infrared spectroscopy and cyclic voltammetry. The complex (corannulene-di-NHC)[RhCl(COD)]2 was used for the encapsulation of fullerenes C60 and C70, generating host-guest complexes with 2 : 1 stoichiometry, as evidenced by 1H NMR and ITC titrations. Then, a tetra-rhodium(i) metallo-rectangle supported by two corannulene-bis-imidazolylidene ligands and two cofacial 4,4'-bipyridine ligands was prepared and characterized. This metallobox is capable of quantitatively encapsulating fullerenes C60 and C70, forming complexes that are highly stable even at high temperatures. The molecular structure of the metallobox with encapsulated C60 reveals a perfect size and shape complementarity that benefits from the concave-convex π-π interaction between the polyaromatic surfaces of the host and the guest.

Nanoparticles traversing the extracellular matrix induce biophysical perturbation of fibronectin depicted by surface chemistry.

While the filtering and accumulation effects of the extracellular matrix (ECM) on nanoparticles (NPs) have been experimentally observed, the detailed interactions between NPs and specific biomolecules within the ECM remain poorly understood and pose challenges for in vivo molecular-level investigations. Herein, we adopt molecular dynamics simulations to elucidate the impacts of methyl-, hydroxy-, amine-, and carboxyl-modified gold NPs on the cell-binding domains of fibronectin (Fn), an indispensable component of the ECM for cell attachment and signaling. Simulation results show that NPs can specifically bind to distinct Fn domains, and the strength of these interactions depends on the physicochemical properties of NPs. NP-NH3+ exhibits the highest affinity to domains rich in acidic residues, leading to strong electrostatic interactions that induce severe deformation, potentially disrupting the normal functioning of Fn. NP-CH3 and NP-COO- selectively occupy the RGD/PHSRN motifs, which may hinder their recognition by integrins on the cell surface. Additionally, NPs can disrupt the dimerization of Fn through competing for residues at the dimer interface or by diminishing the shape complementarity between dimerized proteins. The mechanical stretching of Fn, crucial for ECM fibrillogenesis, is suppressed by NPs due to their local rigidifying effect. These results provide valuable molecular-level insights into the impacts of various NPs on the ECM, holding significant implications for advancing nanomedicine and nanosafety evaluation.

A π-extended molecular belt with selective binding capability for fullerene C70.

A molecular belt incorporating naphthalene moieties, featuring an ellipsoidal cavity, was precisely engineered through bottom-up synthesis. Its pre-arranged geometry exhibits excellent complementarity to fullerene C70, resulting in remarkable selective binding ability (K = 1.3 × 106 M-1) for C70 compared to C60 (K = 176 M-1), forming a 1 : 1 complex. This superiority was unequivocally demonstrated by the single crystal structure of the complex, which revealed outstanding concave-convex shape complementarity between the two components. This highlights the potential application of molecular belts in the purification and separation of fullerenes.

An efficient and universal In silico screening strategy for acquisition of high-affinity Aptamer and its application in analytical utility

Numerous aptamers against various targets have been identified through the technology of systematic evolution of ligands by exponential enrichment (SELEX), but the affinity of these aptamers are often insufficient due to the limitations of SELEX. Therefore, a more rational in silico screening strategy (ISS) was developed for efficient screening of high affinity aptamers, which took shape complementarity and thermodynamic stability into consideration. Neuron specific enolase (NSE), a tumor marker, was selected as the target molecule. In the screening process, three aptamer candidates with good shape complementarity, lower ΔG values, and higher ZDOCK scores were produced. The dissociation constant (Kd) of these candidates to NSE was determined to be 10.13 nM, 14.82 nM, and 2.76 nM, respectively. Each of them exhibited higher affinity to NSE than the parent aptamer (Kd = 23.83 nM). Finally, an antibody-free fluorescence aptasensor assay, based on the aptamer with the highest affinity, P–5C8G, was conducted, resulting in a limit of detection (LOD) value of 1.8 nM, which was much lower than the parental aptamer (P, LOD = 12.6 nM). The proposed ISS approach provided an efficient and universal strategy to improve the aptamer to have a high affinity and good analytical utility.

Simultaneous Docking of Antiviral Drugs and Cyanine Dyes with Proteins Using Multiple Ligand Approach

The protein-based nanosystems for targeted drug delivery of a wide array of substances, ranging from small drugs and therapeutic proteins to nucleic acids and genes, attract increasing attention due to their biocompatibility and biodegradability, extraordinary binding capacity for different ligands, accessibility from natural sources, effective drug protection and gentle encapsulation conditions. Due to the multitude of binding pockets and functional groups on the protein surface, these nanocarriers seem to be highly efficient multifunctional nanotheranostic systems that could incorporate both a therapeutic drug and a visualizing agent. This integration serves multiple purposes, including the regulation of drug release, monitoring the alterations at the target site in response to treatment, and offering crucial insights into the efficacy of the intervention in its early stages. The development of these advanced nanosystems necessitates a thorough comprehension of the potential interactions within these intricate systems. In the present study we assessed the potential of six trimethine and seven pentamethine cyanine dyes to serve as visualizing agents in the drug-protein-dye systems which include functionally significant proteins (cytochrome c, serum albumin, lysozyme and insulin and four antiviral drugs, viz. favipiravir, molnupiravir, nirmatrelvir and ritonavir. The ternary systems with the highest dye-protein surface shape complementarity were established for all groups of the examined cyanine dyes. The influence of the cyanine dye structure on the stability of the drug-protein-dye complexes was assessed. The obtained results indicate that the dye-protein affinity is not solely dependent on the length of the polymethine chain. It was found that the most prospective drug delivery systems containing the trimethines and pentamethines as visualizing agents are AK5-6-, AK5-8- and AK3-11-drug-albumin complexes.

Synergistic Effect of Hyperactive Antifreeze Protein on Inhibition of Gas-Hydrate Growth by Hydrophobic and Hydrophilic Groups.

Antifreeze proteins (AFPs) are biodegradable inhibitors that effectively prevent the formation of natural gas hydrates that block pipelines. In this study, molecular dynamics simulations were employed to establish a kinetic model of the hyperactive insect antifreeze protein (Tenebrio molitor, TmAFP) and its mutants to inhibit the growth of sI natural methane hydrate. Simulations revealed that the hydrophobic and hydrophilic groups of threonine (Thr) residues at hydrate-binding sites played a synergistic role in binding hydrates. The hydrophobic groups anchored TmAFP to the hydrate surface through residues Thr39-Thr65 by migrating pendant hydrophobic methyl groups to the hydrate semicages. The hydrophilic groups stabilized TmAFP by hydrogen bonding with water molecules and integrating them into a quasi-hydrate structure, which more effectively inhibited hydrate growth. The results suggest that the hydrate growth inhibition is attributed to both the shape complementarity and the flexibility of binding residues. The synergy between hydrophobic and hydrophilic groups provides guidance for the design of more effective hydrate inhibitors.

Free energy landscape and thermodynamics properties of novel mutations in PncA of pyrazinamide resistance isolates of Mycobacterium tuberculosis

Pyrazinamide (PZA) is one of the first-line antituberculosis therapy, active against non-replicating Mycobacterium tuberculosis (Mtb). The conversion of PZA into pyrazinoic acid (POA), the active form, required the activity of pncA gene product pyrazinamidase (PZase) activity. Mutations occurred in pncA are the primary cause behind the PZA resistance. However, the resistance mechanism is important to explore using high throughput computational approaches. Here we aimed to explore the mechanism of PZA resistance behind novel P62T, L120R, and V130M mutations in PZase using 200 ns molecular dynamics (MD) simulations. MD simulations were performed to observe the structural changes for these three mutants (MTs) compared to the wild types (WT). Root means square fluctuation, the radius of gyration, free energy landscape, root means square deviation, dynamic cross-correlation motion, and pocket volume were found in variation between WT and MTs, revealing the effects of P62T, L120R, and V130M. The free energy conformational landscape of MTs differs significantly from the WT system, lowering the binding of PZA. The geometric shape complementarity of the drug (PZA) and target protein (PZase) further confirmed that P62T, L120R, and V130M affect the protein structure. These effects on PZase may cause vulnerability to convert PZA into POA. Communicated by Ramaswamy H. Sarma

Assessment of neutralization susceptibility of Omicron subvariants XBB.1.5 and BQ.1.1 against broad-spectrum neutralizing antibodies through epitopes mapping.

The emergence of new variants of the SARS-CoV-2 virus has posed a significant challenge in developing broadly neutralizing antibodies (nAbs) with guaranteed therapeutic potential. Some nAbs, such as Sotrovimab, have exhibited varying levels of efficacy against different variants, while others, such as Bebtelovimab and Bamlanivimab-etesevimab are ineffective against specific variants, including BQ.1.1 and XBB. This highlights the urgent need for developing broadly active monoclonal antibodies (mAbs) providing prophylactic and therapeutic benefits to high-risk patients, especially in the face of the risk of reinfection from new variants. Here, we aimed to investigate the feasibility of redirecting existing mAbs against new variants of SARS-CoV-2, as well as to understand how BQ.1.1 and XBB.1.5 can evade broadly neutralizing mAbs. By mapping epitopes and escape sites, we discovered that the new variants evade multiple mAbs, including FDA-approved Bebtelovimab, which showed resilience against other Omicron variants. Our approach, which included simulations, endpoint free energy calculation, and shape complementarity analysis, revealed the possibility of identifying mAbs that are effective against both BQ.1.1 and XBB.1.5. We identified two broad-spectrum mAbs, R200-1F9 and R207-2F11, as potential candidates with increased binding affinity to XBB.1.5 and BQ.1.1 compared to the reference (Wu01) strain. Additionally, we propose that these mAbs do not interfere with Angiotensin Converting Enzyme 2 (ACE2) and bind to conserved epitopes on the receptor binding domain of Spike that are not-overlapping, potentially providing a solution to neutralize these new variants either independently or as part of a combination (cocktail) treatment.

Design of Metal–Organic Assemblies via Shape Complementarity and Conformational Constraints in Dual Curvature Ligands

Design of Metal–Organic Assemblies via Shape Complementarity and Conformational Constraints in Dual Curvature Ligands

Oligomerization-mediated activation of a short prokaryotic Argonaute.

Although eukaryotic and long prokaryotic Argonaute proteins (pAgos) cleave nucleic acids, some short pAgos lack nuclease activity and hydrolyse NAD(P)+ to induce bacterial cell death1. Here we present a hierarchical activation pathway for SPARTA, a short pAgo consisting of an Argonaute (Ago) protein and TIR-APAZ, an associated protein2. SPARTA progresses through distinct oligomeric forms, including a monomeric apo state, a monomeric RNA-DNA-bound state, two dimeric RNA-DNA-bound states and a tetrameric RNA-DNA-bound active state. These snapshots together identify oligomerization as a mechanistic principle of SPARTA activation. The RNA-DNA-binding channel ofapoinactiveSPARTA is occupied by an auto-inhibitory motif in TIR-APAZ. After the binding of RNA-DNA, SPARTA transitions from a monomer to a symmetricdimer and then an asymmetric dimer, in which two TIR domains interact through charge and shape complementarity. Next, two dimers assemble into a tetramer with a central TIR cluster responsible for hydrolysing NAD(P)+. In addition, we observe unique features of interactions between SPARTA and RNA-DNA, including competition between the DNA 3' end and the auto-inhibitory motif, interactions between the RNA G2 nucleotide and Ago, and splaying of the RNA-DNA duplex by two loops exclusive to short pAgos. Together, our findings provide a mechanistic basis for the activation of short pAgos, a large section of the Ago superfamily.

Deciphering the driving forces in crystal packing by analysis of electrostatic energies and contact enrichment ratios.

Hirshfeld surface analysis is a widely used tool for identifying the types of intermolecular contacts that contribute most significantly to crystal packing stabilization. One useful metric for analyzing these contacts is the contact enrichment descriptor, which indicates the types of contacts that are over- or under-represented. In this statistical study, enrichment ratios were combined with electrostatic energy (Eelec) data for a variety of compound families. To compute the electrostatic interaction energy between atoms, charge density models from the ELMAM2 database of multipolar atoms were used. As expected, strong hydrogen bonds such as O/N-H...N and O/N-H...O typically display large enrichment values and have the most negative (i.e. favorable) electrostatic energies. Conversely, contacts that are repulsive from an electrostatic perspective are usually the most under-represented. Analyzing the enrichment ratio and electrostatic energy indicators was shown to help identify which favorable contacts are the most competitive with each other. For weaker interactions, such as hydrophobic contacts, the behavior is less clear cut and can depend on other factors such as the chemical content of the molecule. The anticorrelation between contact enrichment and Eelec is generally lost for weaker contacts. However, we observed that C...C contacts are often enriched in crystal structures containing heterocycles, despite the low electrostatic attraction. For molecules with only weak hydrogen bond donors/acceptors and hydrophobic groups, the correlation between contact enrichment and Eelec is still evident for the strongest of these interactions. However, there are some exceptions where the most favorable contacts from an electrostatic perspective are not the most over-represented. This can occur in cases where the shape of the molecule is complex or elongated, favoring dispersion forces and shape complementarity in the packing.

Self-assembly of two-dimensional lattices driven by shape complementarity and attractive interactions

Today, low-dimensional structures are finding an increasingly widespread use in various technological applications such as sensors, catalytic converters etc. Kagome lattice, along with other two-dimensional lattices generated from Archimedean tilings, are of particular interest because of their unique electronic, optical and magnetic properties. Here, based on two simple design principles: shape complementarity and minimization of frustration, we introduce a theoretical model that is able to self-assemble into all Archimedean lattices except one. Within this model each lattice site is represented by a single interacting particle with a specifically designed shape. The required shapes are triangles, squares, rhombi and other relatively simple geometrical figures. Each particle carries a single attractive patch designed to minimize the potential energy of the target structure. As the first step of the lattice assembly, the attractive interactions induce the formation of clusters that have space-filling shapes. At the second step, the clusters coalesce into a superlattice with the desired structure known as the cluster crystal. Monte Carlo simulations are carried out to prove that each target lattice is a) easy to assemble by the model and b) constitutes the minimum free energy conformation. Possible experimental realizations of the proposed model are discussed.

Differences in the organization of interface residues tunes the stability of the SARS-CoV-2 spike-ACE2 complex.

The continuous emergence of novel variants represents one of the major problems in dealing with the SARS-CoV-2 virus. Indeed, also due to its prolonged circulation, more than ten variants of concern emerged, each time rapidly overgrowing the current viral version due to improved spreading features. As, up to now, all variants carry at least one mutation on the spike Receptor Binding Domain, the stability of the binding between the SARS-CoV-2 spike protein and the human ACE2 receptor seems one of the molecular determinants behind the viral spreading potential. In this framework, a better understanding of the interplay between spike mutations and complex stability can help to assess the impact of novel variants. Here, we characterize the peculiarities of the most representative variants of concern in terms of the molecular interactions taking place between the residues of the spike RBD and those of the ACE2 receptor. To do so, we performed molecular dynamics simulations of the RBD-ACE2 complexes of the seven variants of concern in comparison with a large set of complexes with different single mutations taking place on the RBD solvent-exposed residues and for which the experimental binding affinity was available. Analyzing the strength and spatial organization of the intermolecular interactions of the binding region residues, we found that (i) mutations producing an increase of the complex stability mainly rely on instaurating more favorable van der Waals optimization at the cost of Coulombic ones. In particular, (ii) an anti-correlation is observed between the shape and electrostatic complementarities of the binding regions. Finally, (iii) we showed that combining a set of dynamical descriptors is possible to estimate the outcome of point mutations on the complex binding region with a performance of 0.7. Overall, our results introduce a set of dynamical observables that can be rapidly evaluated to probe the effects of novel isolated variants or different molecular systems.

Electrostatic complementarity at the interface drives transient protein-protein interactions

Understanding the mechanisms driving bio-molecules binding and determining the resulting complexes’ stability is fundamental for the prediction of binding regions, which is the starting point for drug-ability and design. Characteristics like the preferentially hydrophobic composition of the binding interfaces, the role of van der Waals interactions, and the consequent shape complementarity between the interacting molecular surfaces are well established. However, no consensus has yet been reached on the role of electrostatic. Here, we perform extensive analyses on a large dataset of protein complexes for which both experimental binding affinity and pH data were available. Probing the amino acid composition, the disposition of the charges, and the electrostatic potential they generated on the protein molecular surfaces, we found that (i) although different classes of dimers do not present marked differences in the amino acid composition and charges disposition in the binding region, (ii) homodimers with identical binding region show higher electrostatic compatibility with respect to both homodimers with non-identical binding region and heterodimers. Interestingly, (iii) shape and electrostatic complementarity, for patches defined on short-range interactions, behave oppositely when one stratifies the complexes by their binding affinity: complexes with higher binding affinity present high values of shape complementarity (the role of the Lennard-Jones potential predominates) while electrostatic tends to be randomly distributed. Conversely, complexes with low values of binding affinity exploit Coulombic complementarity to acquire specificity, suggesting that electrostatic complementarity may play a greater role in transient (or less stable) complexes. In light of these results, (iv) we provide a novel, fast, and efficient method, based on the 2D Zernike polynomial formalism, to measure electrostatic complementarity without the need of knowing the complex structure. Expanding the electrostatic potential on a basis of 2D orthogonal polynomials, we can discriminate between transient and permanent protein complexes with an AUC of the ROC of sim 0.8. Ultimately, our work helps shedding light on the non-trivial relationship between the hydrophobic and electrostatic contributions in the binding interfaces, thus favoring the development of new predictive methods for binding affinity characterization.

Fine tuning rigid body docking results using the Dreiding force field: A computational study of 36 known nanobody-protein complexes.

This paper aims to understand the binding strategies of a nanobody-protein pair by studying known complexes. Rigid body protein-ligand docking programs produce several complexes, called decoys, which are good candidates with high scores of shape complementarity, electrostatic interactions, desolvation, buried surface area, and Lennard-Jones potentials. However, the decoy that corresponds to the native structure is not known. We studied 36 nanobody-protein complexes from the single domain antibody database, sd-Ab DB, http://www.sdab-db.ca/. For each structure, a large number of decoys are generated using the Fast Fourier Transform algorithm of the software ZDOCK. The decoys were ranked according to their target protein-nanobody interaction energies, calculated by using the Dreiding Force Field, with rank 1 having the lowest interaction energy. Out of 36 protein data bank (PDB) structures, 25 true structures were predicted as rank 1. Eleven of the remaining structures required Ångstrom size rigid body translations of the nanobody relative to the protein to match the given PDB structure. After the translation, the Dreiding interaction (DI) energies of all complexes decreased and became rank 1. In one case, rigid body rotations as well as translations of the nanobody were required for matching the crystal structure. We used a Monte Carlo algorithm that randomly translates and rotates the nanobody of a decoy and calculates the DI energy. Results show that rigid body translations and the DI energy are sufficient for determining the correct binding location and pose of ZDOCK created decoys. A survey of the sd-Ab DB showed that each nanobody makes at least one salt bridge with its partner protein, indicating that salt bridge formation is an essential strategy in nanobody-protein recognition. Based on the analysis of the 36 crystal structures and evidence from existing literature, we propose a set of principles that could be used in the design of nanobodies.