Dynamic Docking of Conformationally Constrained Macrocycles: Methods and Applications

Conformations of Macrocyclic Peptides Sampled by Nuclear Magnetic Resonance: Models for Cell-Permeability

The biological activities and pharmacological properties of peptides and peptide mimetics are determined by their conformational states. Therefore, a detailed understanding of the conformational landscape is crucial for rational drug design. Nuclear magnetic resonance (NMR) is the only method for structure determination in solution. However, it remains challenging to determine the structures of peptides using NMR because of very weak nuclear Overhauser effects (NOEs), the semiquantitative nature of the rotating frame Overhauser effect (ROE), and the low number of NOEs/ROEs in N-methylated peptides. In this study, we introduce a new approach to investigating the structures of modified macrocyclic peptides. We utilize exact NOEs (eNOEs) in viscous solvent mixtures to replicate various cellular environments. eNOEs provide detailed structural information for highly dynamic modified peptides. Structures of high precision were obtained for cyclosporin A, with a backbone atom rmsd of 0.10 Å. Distinct conformational states in different environments were identified for omphalotin A (OmphA), a fungal nematotoxic and multiple backbone N-methylated macrocyclic peptides. A model for cell-permeation is presented for OmphA, based on its structures in polar, apolar, and mixed polarity solvents. During the transition from a polar to an apolar environment, OmphA undergoes a rearrangement of its H-bonding network, accompanied by a cis to trans isomerization of the ω torsion angle within a type VIa β-turn. We hypothesize that the kinetics of these conformational transitions play a crucial role in determining the membrane-permeation capabilities of OmphA.

Peptidomimetics in cancer targeting

The low efficiency of treatment strategies is one of the main obstacles to developing cancer inhibitors. Up to now, various classes of therapeutics have been developed to inhibit cancer progression. Peptides due to their small size and easy production compared to proteins are highly regarded in designing cancer vaccines and oncogenic pathway inhibitors. Although peptides seem to be a suitable therapeutic option, their short lifespan, instability, and low binding affinity for their target have not been widely applicable against malignant tumors. Given the peptides' disadvantages, a new class of agents called peptidomimetic has been introduced. With advances in physical chemistry and biochemistry, as well as increased knowledge about biomolecule structures, it is now possible to chemically modify peptides to develop efficient peptidomimetics. In recent years, numerous studies have been performed to the evaluation of the effectiveness of peptidomimetics in inhibiting metastasis, angiogenesis, and cancerous cell growth. Here, we offer a comprehensive review of designed peptidomimetics to diagnose and treat cancer.

Dynamic Docking of Macrocycles in Bound and Unbound Protein Structures with DynaDock

Macrocycles are interesting molecules with unique features due to their conformationally constrained yet flexible ring structure. This characteristic poses a difficult challenge for computational modeling studies since they rely on accurate structural descriptions. In particular, molecular docking calculations suffer from the lack of ring flexibility during pose generation, which is often compensated by using pregenerated ligand conformer ensembles. Moreover, receptor structures are mainly treated rigidly, which limits the use of many docking tools. In this study, we optimized our previous molecular dynamics-based sampling and docking pipeline specifically designed for the accurate prediction of macrocyclic compounds. We developed a dihedral classification procedure for in-depth conformational analysis of the macrocyclic rings and extracted structural ensembles that were subsequently docked in both bound and unbound protein structures employing a fully flexible approach. Our results suggest that including a ring conformer close to the bound state in the starting ensemble increases the chance of successful docking. The bioactive conformations of a diverse set of ligands could be predicted with high and decent accuracy in bound and unbound protein structures, respectively, due to the incorporation of full molecular flexibility in our approach. The remaining unsuccessful docking calculations were mainly caused by large flexible substituents that bind to surface-exposed binding sites, rather than the macrocyclic ring per se and could be further improved by explicit molecular dynamics simulations of the docked complex.

Cyclization and Docking Protocol for Cyclic Peptide-Protein Modeling Using HADDOCK2.4

An emerging class of therapeutic molecules are cyclic peptides with over 40 cyclic peptide drugs currently in clinical use. Their mode of action is, however, not fully understood, impeding rational drug design. Computational techniques could positively impact their design, but modeling them and their interactions remains challenging due to their cyclic nature and their flexibility. This study presents a step-by-step protocol for generating cyclic peptide conformations and docking them to their protein target using HADDOCK2.4. A dataset of 30 cyclic peptide-protein complexes was used to optimize both cyclization and docking protocols. It supports peptides cyclized via an N- and C-terminus peptide bond and/or a disulfide bond. An ensemble of cyclic peptide conformations is then used in HADDOCK to dock them onto their target protein using knowledge of the binding site on the protein side to drive the modeling. The presented protocol predicts at least one acceptable model according to the critical assessment of prediction of interaction criteria for each complex of the dataset when the top 10 HADDOCK-ranked single structures are considered (100% success rate top 10) both in the bound and unbound docking scenarios. Moreover, its performance in both bound and fully unbound docking is similar to the state-of-the-art software in the field, Autodock CrankPep. The presented cyclization and docking protocol should make HADDOCK a valuable tool for rational cyclic peptide-based drug design and high-throughput screening.

Structurally Guided Reprogramming of Valerenadiene Synthase

Valerena-1,10-diene synthase (VDS) catalyzes the conversion of the universal precursor farnesyl diphosphate into the unusual sesquiterpene valerena-1,10-diene (VLD), which possesses a unique isobutenyl substituent group. In planta, one of VLD's isobutenyl terminal methyl groups becomes oxidized to a carboxylic acid forming valerenic acid (VA), an allosteric modulator of the GABA_A receptor. Because a structure-activity relationship study of VA for its modulatory activity is desired, we sought to manipulate the VDS enzyme for the biosynthesis of structurally diverse scaffolds that could ultimately lead to the generation of VA analogues. Using three-dimensional structural homology models, phylogenetic sequence comparisons to well-characterized sesquiterpene synthases, and a substrate-active site contact mapping approach, the contributions of specific amino acid residues within or near the VDS active site to possible catalytic cascades for VLD and other sesquiterpene products were assessed. An essential role of Tyr535 in a germacrenyl route to VLD was demonstrated, while its contribution to a family of other sesquiterpenes derived from a humulyl route was not. No role for Cys415 or Cys452 serving as a proton donor to reaction intermediates in VLD biosynthesis was observed. However, a gatekeeper role for Asn455 in directing farnesyl carbocations down all-trans catalytic cascades (humulyl and germacrenyl routes) versus a cisoid cascade (nerolidyl route) was demonstrated. Altogether, these results have mapped residues that establish a context for the catalytic cascades operating in VDS and future manipulations for generating more structurally constrained scaffolds.

Leveraging Fungal and Human Calcineurin-Inhibitor Structures, Biophysical Data, and Dynamics To Design Selective and Nonimmunosuppressive FK506 Analogs

Calcineurin is a critical enzyme in fungal pathogenesis and antifungal drug tolerance and, therefore, an attractive antifungal target. Current clinically accessible calcineurin inhibitors, such as FK506, are immunosuppressive to humans, so exploiting calcineurin inhibition as an antifungal strategy necessitates fungal specificity in order to avoid inhibiting the human pathway. Harnessing fungal calcineurin-inhibitor crystal structures, we recently developed a less immunosuppressive FK506 analog, APX879, with broad-spectrum antifungal activity and demonstrable efficacy in a murine model of invasive fungal infection. Our overarching goal is to better understand, at a molecular level, the interaction determinants of the human and fungal FK506-binding proteins (FKBP12) required for calcineurin inhibition in order to guide the design of fungus-selective, nonimmunosuppressive FK506 analogs. To this end, we characterized high-resolution structures of the Mucor circinelloides FKBP12 bound to FK506 and of the Aspergillus fumigatus, M. circinelloides, and human FKBP12 proteins bound to the FK506 analog APX879, which exhibits enhanced selectivity for fungal pathogens. Combining structural, genetic, and biophysical methodologies with molecular dynamics simulations, we identify critical variations in these structurally similar FKBP12-ligand complexes. The work presented here, aimed at the rational design of more effective calcineurin inhibitors, indeed suggests that modifications to the APX879 scaffold centered around the C₁₅, C₁₆, C₁₈, C₃₆, and C₃₇ positions provide the potential to significantly enhance fungal selectivity. IMPORTANCE Invasive fungal infections are a leading cause of death in the immunocompromised patient population. The rise in drug resistance to current antifungals highlights the urgent need to develop more efficacious and highly selective agents. Numerous investigations of major fungal pathogens have confirmed the critical role of the calcineurin pathway for fungal virulence, making it an attractive target for antifungal development. Although FK506 inhibits calcineurin, it is immunosuppressive in humans and cannot be used as an antifungal. By combining structural, genetic, biophysical, and in silico methodologies, we pinpoint regions of the FK506 scaffold and a less immunosuppressive analog, APX879, centered around the C₁₅ to C₁₈ and C₃₆ to C₃₇ positions that could be altered with selective extensions and/or deletions to enhance fungal selectivity. This work represents a significant advancement toward realizing calcineurin as a viable target for antifungal drug discovery.

Cyclisation strategies for stabilising peptides with irregular conformations

Cyclisation is a common synthetic strategy for enhancing the therapeutic potential of peptide-based molecules. While there are extensive studies on peptide cyclisation for reinforcing regular secondary structures such as α-helices and β-sheets, there are remarkably few reports of cyclising peptides which adopt irregular conformations in their bioactive target-bound state. In this review, we highlight examples where cyclisation techniques have been successful in stabilising irregular conformations, then discuss how the design of cyclic constraints for irregularly structured peptides can be informed by existing β-strand stabilisation approaches, new computational design techniques, and structural principles extracted from cyclic peptide library screening hits. Through this analysis, we demonstrate how existing peptide cyclisation techniques can be adapted to address the synthetic design challenge of stabilising irregularly structured binding motifs.

The latest automated docking technologies for novel drug discovery

INTRODUCTION

Molecular docking has been consolidated as one of the most important methods in the molecular modeling field. It has been recognized as a prominent tool in the study of protein-ligand complexes, to describe intermolecular interactions, to accurately predict poses of multiple ligands, to discover novel promising bioactive compounds. Molecular docking methods have evolved in terms of their accuracy and reliability; but there are pending issues to solve for improving the connection between the docking results and the experimental evidence.

AREAS COVERED

In this article, the author reviews very recent innovative molecular docking applications with special emphasis on reverse docking, treatment of protein flexibility, the use of experimental data to guide the selection of docking poses, the application of Quantum mechanics(QM) in docking, and covalent docking.

EXPERT OPINION

There are several issues being worked on in recent years that will lead to important breakthroughs in molecular docking methods in the near future These developments are related to more efficient exploration of large datasets and receptor conformations, advances in electronic description, and the use of structural information for guiding the selection of results.

Cyclic RGD and isoDGR Integrin Ligands Containing cis-2-amino-1-cyclopentanecarboxylic (cis-β-ACPC) Scaffolds

Integrin ligands containing the tripeptide sequences Arg-Gly-Asp (RGD) and iso-Asp-Gly- Arg (isoDGR) were actively investigated as inhibitors of tumor angiogenesis and directing unit in tumor-targeting drug conjugates. Reported herein is the synthesis, of two RGD and one isoDGR cyclic peptidomimetics containing (1S,2R) and (1R,2S) cis-2-amino-1-cyclopentanecarboxylic acid (cis-β-ACPC), using a mixed solid phase/solution phase synthetic protocol. The three ligands were examined in vitro in competitive binding assays to the purified α_vβ₃ and α₅β₁ receptors using biotinylated vitronectin (α_vβ₃) and fibronectin (α₅β₁) as natural displaced ligands. The IC50 values of the ligands ranged from nanomolar (the two RGD ligands) to micromolar (the isoDGR ligand) with a pronounced selectivity for α_vβ₃ over α₅β₁. In vitro cell adhesion assays were also performed using the human skin melanoma cell line WM115 (rich in integrin α_vβ₃). The two RGD ligands showed IC₅₀ values in the same micromolar range as the reference compound (cyclo[RGDfV]), while for the isoDGR derivative an IC₅₀ value could not be measured for the cell adhesion assay. A conformational analysis of the free RGD and isoDGR ligands by NMR (VT-NMR and NOESY experiments) and computational studies (MC/EM and MD), followed by docking simulations performed in the α_Vβ₃ integrin active site, provided a rationale for the behavior of these ligands toward the receptor.

Automated Design of Macrocycles for Therapeutic Applications: From Small Molecules to Peptides and Proteins

Macrocycles and cyclic peptides are increasingly attractive therapeutic modalities as they often have improved affinity, are able to bind to extended protein surfaces, and otherwise have favorable properties. Macrocyclization of a known binder may stabilize its bioactive conformation and improve its metabolic stability, cell permeability, and in certain cases oral bioavailability. Herein, we present implementation and application of an approach that automatically generates, evaluates, and proposes cyclizations utilizing a library of well-established chemical reactions and reagents. Using the three-dimensional (3D) conformation of the linear molecule in complex with a target protein as the starting point, this approach identifies attachment points, generates linkers, evaluates their geometric compatibility, and ranks the resulting molecules with respect to their predicted conformational stability and interactions with the target protein. As we show here with prospective and retrospective case studies, this procedure can be applied for the macrocyclization of small molecules and peptides and even PROteolysis TArgeting Chimeras (PROTACs) and proteins.

Structure-Based Macrocyclization of Substrate Analogue NS2B-NS3 Protease Inhibitors of Zika, West Nile and Dengue viruses

A series of cyclic active-site-directed inhibitors of the NS2B-NS3 proteases from Zika (ZIKV), West Nile (WNV), and dengue-4 (DENV4) viruses has been designed. The most potent compounds contain a reversely incorporated d-lysine residue in the P1 position. Its side chain is connected to the P2 backbone, its α-amino group is converted into a guanidine to interact with the conserved Asp129 side chain in the S1 pocket, and its C terminus is connected to the P3 residue via different linker segments. The most potent compounds inhibit the ZIKV protease with Ki values <5 nM. Crystal structures of seven ZIKV protease inhibitor complexes were determined to support the inhibitor design. All the cyclic compounds possess high selectivity against trypsin-like serine proteases and furin-like proprotein convertases. Both WNV and DENV4 proteases are inhibited less efficiently. Nonetheless, similar structure-activity relationships were observed for these enzymes, thus suggesting their potential application as pan-flaviviral protease inhibitors.

SkeleDock: A Web Application for Scaffold Docking in PlayMolecule

SkeleDock is a scaffold docking algorithm which uses the structure of a protein-ligand complex as a template to model the binding mode of a chemically similar system. This algorithm was evaluated in the D3R Grand Challenge 4 pose prediction challenge, where it achieved competitive performance. Furthermore, we show that if crystallized fragments of the target ligand are available then SkeleDock can outperform rDock docking software at predicting the binding mode. This Application Note also addresses the capacity of this algorithm to model macrocycles and deal with scaffold hopping. SkeleDock can be accessed at https://playmolecule.org/SkeleDock/.

Macrocyclic Modalities Combining Peptide Epitopes and Natural Product Fragments

“Hot loop” protein segments have variable structure and conformation and contribute crucially to protein–protein interactions. We describe a new hot loop mimicking modality, termed PepNats, in which natural product (NP)-inspired structures are incorporated as conformation-determining and -restricting structural elements into macrocyclic hot loop-derived peptides. Macrocyclic PepNats representing hot loops of inducible nitric oxide synthase (iNOS) and human agouti-related protein (AGRP) were synthesized on solid support employing macrocyclization by imine formation and subsequent stereoselective 1,3-dipolar cycloaddition as key steps. PepNats derived from the iNOS DINNN hot loop and the AGRP RFF hot spot sequence yielded novel and potent ligands of the SPRY domain-containing SOCS box protein 2 (SPSB2) that binds to iNOS, and selective ligands for AGRP-binding melanocortin (MC) receptors. NP-inspired fragment absolute configuration determines the conformation of the peptide part responsible for binding. These results demonstrate that combination of NP-inspired scaffolds with peptidic epitopes enables identification of novel hot loop mimics with conformationally constrained and biologically relevant structure.

Modelling the binding mode of macrocycles: Docking and conformational sampling

Drug discovery is increasingly tackling challenging protein binding sites regarding molecular recognition and druggability, including shallow and solvent-exposed protein-protein interaction interfaces. Macrocycles are emerging as promising chemotypes to modulate such sites. Despite their chemical complexity, macrocycles comprise important drugs and offer advantages compared to non-cyclic analogs, hence the recent impetus in the medicinal chemistry of macrocycles. Elaboration of macrocycles, or constituent fragments, can strongly benefit from knowledge of their binding mode to a target. When such information from X-ray crystallography is elusive, computational docking can provide working models. However, few studies have explored docking protocols for macrocycles, since conventional docking methods struggle with the conformational complexity of macrocycles, and also potentially with the shallower topology of their binding sites. Indeed, macrocycle binding mode prediction with the mainstream docking software GOLD has hardly been explored. Here, we present an in-depth study of macrocycle docking with GOLD and the ChemPLP scores. First, we summarize the thorough curation of a test set of 41 protein-macrocycle X-ray structures, raising the issue of lattice contacts with such systems. Rigid docking of the known bioactive conformers was successful (three top ranked poses) for 92.7% of the systems, in absence of crystallographic waters. Thus, without conformational search issues, scoring performed well. However, docking success dropped to 29.3% with the GOLD built-in conformational search. Yet, the success rate doubled to 58.5% when GOLD was supplied with extensive conformer ensembles docked rigidly. The reasons for failure, sampling or scoring, were analyzed, exemplified with particular cases. Overall, binding mode prediction of macrocycles remains challenging, but can be much improved with tailored protocols. The analysis of the interplay between conformational sampling and docking will be relevant to the prospective modelling of macrocycles in general.

A gold mine for drug discovery: Strategies to develop cyclic peptides into therapies

As a versatile therapeutic modality, peptides attract much attention because of their great binding affinity, low toxicity, and the capability of targeting traditionally "undruggable" protein surfaces. However, the deficiency of cell permeability and metabolic stability always limits the success of in vitro bioactive peptides as drug candidates. Peptide macrocyclization is one of the most established strategies to overcome these limitations. Over the past decades, more than 40 cyclic peptide drugs have been clinically approved, the vast majority of which are derived from natural products. The de novo discovered cyclic peptides on the basis of rational design and in vitro evolution, have also enabled the binding with targets for which nature provides no solutions. The current review summarizes different classes of cyclic peptides with diverse biological activities, and presents an overview of various approaches to develop cyclic peptide-based drug candidates, drawing upon series of examples to illustrate each strategy.

Docking Flexible Cyclic Peptides with AutoDock CrankPep

While a new therapeutic cyclic peptide is approved nearly every year, docking large macrocycles has remained challenging. Here, we present a new version of our peptide docking software AutoDock CrankPep (ADCP), extended to dock peptides cyclized through their backbone and/or side chain disulfide bonds. We show that within the top 10 solutions, ADCP identifies the proper interactions for 71% of a data set of 38 complexes, thus making it a useful tool for rational peptide-based drug design.

Predicting the bioactive conformations of macrocycles: a molecular dynamics-based docking procedure with DynaDock

Macrocyclic compounds are of growing interest as a new class of therapeutics, especially as inhibitors binding to protein-protein interfaces. As molecular modeling is a well-established complimentary tool in modern drug design, the number of attempts to develop reliable docking strategies and algorithms to accurately predict the binding mode of macrocycles is rising continuously. Standard molecular docking approaches need to be adapted to this application, as a comprehensive yet efficient sampling of all ring conformations of the macrocycle is necessary. To overcome this issue, we designed a molecular dynamics-based docking protocol for macrocycles, in which the challenging sampling step is addressed by conventional molecular dynamics (750 ns) simulations performed at moderately high temperature (370 K). Consecutive flexible docking with the DynaDock approach based on multiple, pre-sampled ring conformations yields highly accurate poses with ligand RMSD values lower than 1.8 Å. We further investigated the value of molecular dynamics-based complex stability estimations for pose selection and discuss its applicability in combination with standard binding free energy estimations for assessing the quality of poses in future blind docking studies.

MedusaDock 2.0: Efficient and Accurate Protein-Ligand Docking With Constraints

Molecular docking is the key ingredient of virtual drug screening, a promising and cost-effective approach for finding new drugs. A critical limitation of this approach is the inadequate sampling efficiency of both ligand and/or receptor conformations for finding the lowest energy bound state. To circumvent this limitation, we develop a protein-ligand docking methodology capable of incorporating structural constraints, experimentally derived or theoretically predicted, to improve accuracy and efficiency. We develop a web server with a user-friendly online graphical interface as a platform for accurate and efficient protein-ligand molecule docking.

A critical assessment of force field accuracy against NMR data for cyclic peptides containing β-amino acids

Hybrid cyclic α/β-peptides, in which one or more β-amino acids are incorporated into the backbone, are gaining increasing interest as potential therapeutics, thanks to their ability to achieve enhanced binding affinities for a biological target through pre-organization in solution. The in silico prediction of their three dimensional structure through strategies such as MD simulations would substantially advance the rational design process. However, whether the molecular mechanics force fields are accurate in sampling highly constrained cyclopeptides containing β-amino acids remains to be verified. Here, we present a systematic assessment of the ability of 8 widely used force fields to reproduce 79 NMR observables (including chemical shifts and 3J scalar couplings) on five cyclic α/β-peptides that contain the integrin recognition motif isoDGR. Most of the investigated force fields, which include force fields from AMBER, OPLS, CHARMM and GROMOS families, display very good agreement with experimental 3J(HN,Hα), suggesting that MD simulations could be an appropriate tool in the rational design of therapeutic cyclic α-peptides. However, for NMR observables directly related to β-amino acids, we observed a poor agreement with experiments and a remarkable dependence of our evaluation on the choice of Karplus parameters. The force field weaknesses herein unveiled might constitute a source of inspiration for further force field optimization.

An Efficient ABC_DE_Based Hybrid Algorithm for Protein-Ligand Docking

Protein–ligand docking is a process of searching for the optimal binding conformation between the receptor and the ligand. Automated docking plays an important role in drug design, and an efficient search algorithm is needed to tackle the docking problem. To tackle the protein–ligand docking problem more efficiently, An ABC_DE_based hybrid algorithm (ADHDOCK), integrating artificial bee colony (ABC) algorithm and differential evolution (DE) algorithm, is proposed in the article. ADHDOCK applies an adaptive population partition (APP) mechanism to reasonably allocate the computational resources of the population in each iteration process, which helps the novel method make better use of the advantages of ABC and DE. The experiment tested fifty protein–ligand docking problems to compare the performance of ADHDOCK, ABC, DE, Lamarckian genetic algorithm (LGA), running history information guided genetic algorithm (HIGA), and swarm optimization for highly flexible protein–ligand docking (SODOCK). The results clearly exhibit the capability of ADHDOCK toward finding the lowest energy and the smallest root-mean-square deviation (RMSD) on most of the protein–ligand docking problems with respect to the other five algorithms.

Formation of macrocyclic ring systems by carbonylation of trifunctional P/B/B frustrated Lewis pairs

The trifunctional P/B/B frustrated Lewis pairs 11a-c featuring bulky aryl groups at phosphorus [Dmesp (a), Tipp (b), Mes* (c)] react with H2 by heterolytic hydrogen splitting followed by cleavage of HB(C6F5)2 to give the zwitterionic six-membered heterocyclic PH phosphonium/borate products 14a-c. Compounds 11a,b react with carbon monoxide by means of a Lewis acid induced CO insertion/rearrangement sequence that eventually results in the formation of the macrocyclic dimers 17a,b. The respective carbonylation reaction of the Mes*P/B/B FLP gives the macrocyclic trimer 18c. The new products were characterized spectroscopically and by X-ray diffraction and the reaction mechanism was analyzed by DFT calculations.

CDNs-STING Interaction Mechanism Investigations and Instructions on Design of CDN-Derivatives

Cyclic dinucleotides (CDNs) present thousand-fold differences of dissociation constants to STING, a pivotal protein in cytosolic dsDNA immunity. To understand how subtle chemical changes in CDNs lead to these substantial variances, a precise ranking of binding affinity is needed. However, the large size and flexibility of CDNs elevate the entropic effect and pose a challenge for this precise prediction. Therefore, in this paper, we developed a new protocol, a combination of selective-integrated tempering sampling of ligands and molecular docking, to take into account the entropic effects originating from extensive ligand configurational space and solvation on binding affinity evaluations. The calculated ranking orders of CDNs and CDN-derivatives to wild type STING and R232H mutant are in agreement with experimental measurements. Further molecular dynamics analysis revealed that the interaction between phosphonate groups and 232R differentiates the binding affinities. The 2'-5' linked phosphonate groups have a larger tendency to form hydrogen bonds with 232R than those with 3'-5' linkages. Moreover, the new protocol identified structural features that enhanced CDNs-STING binding, such as anti-glycosidic bonds and large pro-R distances, which explains the high binding affinity of dithio-RpRp-2'3'-CDA to STING and is expected to provide valuable guidance in the lead-drug optimization.

HIGA: A Running History Information Guided Genetic Algorithm for Protein-Ligand Docking

Protein-ligand docking is an essential part of computer-aided drug design, and it identifies the binding patterns of proteins and ligands by computer simulation. Though Lamarckian genetic algorithm (LGA) has demonstrated excellent performance in terms of protein-ligand docking problems, it can not memorize the history information that it has accessed, rendering it effort-consuming to discover some promising solutions. This article illustrates a novel optimization algorithm (HIGA), which is based on LGA for solving the protein-ligand docking problems with an aim to overcome the drawback mentioned above. A running history information guided model, which includes CE crossover, ED mutation, and BSP tree, is applied in the method. The novel algorithm is more efficient to find the lowest energy of protein-ligand docking. We evaluate the performance of HIGA in comparison with GA, LGA, EDGA, CEPGA, SODOCK, and ABC, the results of which indicate that HIGA outperforms other search algorithms.

Structure-Based Design of Non-natural Macrocyclic Peptides That Inhibit Protein-Protein Interactions

Macrocyclic peptides can interfere with challenging biomolecular targets including protein–protein interactions. Whereas there are various approaches that facilitate the identification of peptide-derived ligands, their evolution into higher affinity binders remains a major hurdle. We report a virtual screen based on molecular docking that allows the affinity maturation of macrocyclic peptides taking non-natural amino acids into consideration. These macrocycles bear large and flexible substituents that usually complicate the use of docking approaches. A virtual library containing more than 1400 structures was screened against the target focusing on docking poses with the core structure resembling a known bioactive conformation. Based on this screen, a macrocyclic peptide 22 involving two non-natural amino acids was evolved showing increased target affinity and biological activity. Predicted binding modes were verified by X-ray crystallography. The presented workflow allows the screening of large macrocyclic peptides with diverse modifications thereby expanding the accessible chemical space and reducing synthetic efforts.

Investigating the Interaction of Cyclic RGD Peptidomimetics with αVβ₆ Integrin by Biochemical and Molecular Docking Studies

The interaction of a small library of cyclic RGD (Arg-Gly-Asp) peptidomimetics with α_Vβ₆ integrin has been investigated by means of competitive solid phase binding assays to the isolated receptor and docking calculations in the crystal structure of the α_Vβ₆ binding site. To this aim, a rigid receptor-flexible ligand docking protocol has been set up and then applied to predict the binding mode of the cyclic RGD peptidomimetics to α_Vβ₆ integrin. Although the RGD interaction with α_Vβ₆ recapitulates the RGD binding mode observed in α_Vβ₃, differences between the integrin binding pockets can strongly affect the ligand binding ability. In general, the peptidomimetics exhibited IC₅₀ values for integrin α_Vβ₆ (i.e., the concentration of compound required for 50% inhibition of biotinylated fibronectin binding to isolated α_Vβ₆ integrin) in the nanomolar range (77–345 nM), about 10–100 times higher than those for the related α_Vβ₃ receptor, with a single notable ligand displaying a low nanomolar IC₅₀ value (2.3 nM). Insights from the properties of the binding pocket combined with the analysis of the docking poses provided a rationale for ligand recognition and selectivity.

Docking of Macrocycles: Comparing Rigid and Flexible Docking in Glide

In recent years, there has been an increased interest in using macrocyclic compounds for drug discovery and development. For docking of these commonly large and flexible compounds to be addressed, a screening and a validation set were assembled from the PDB consisting of 16 and 31 macrocycle-containing protein complexes, respectively. The macrocycles were docked in Glide by rigid docking of pregenerated conformational ensembles produced by the macrocycle conformational sampling method (MCS) in Schrödinger Release 2015-3 or by direct Glide flexible docking after performing ring-templating. The two protocols were compared to rigid docking of pregenerated conformational ensembles produced by an exhaustive Monte Carlo multiple minimum (MCMM) conformational search and a shorter MCMM conformational search (MCMM-short). The docking accuracy was evaluated and expressed as the RMSD between the heavy atoms of the ligand as found in the X-ray structure after refinement and the poses obtained by the docking protocols. The median RMSD values for top-scored poses of the screening set were 0.83, 0.80, 0.88, and 0.58 Å for MCMM, MCMM-short, MCS, and Glide flexible docking, respectively. There was no statistically significant difference in the performance between rigid docking of pregenerated conformations produced by the MCS and direct docking using Glide flexible docking. However, the flexible docking protocol was 2-times faster in docking the screening set compared to that of the MCS protocol. In a final study, the new Prime-MCS method was evaluated in Schrödinger Release 2016-3. This method is faster compared that of to MCS; however, the conformations generated were found to be suboptimal for rigid docking. Therefore, on the basis of timing, accuracy, and ease of set up, standard Glide flexible docking with prior ring-templating is recommended over current gold standard protocols using rigid docking of pregenerated conformational ensembles.

The Performance of Several Docking Programs at Reproducing Protein-Macrolide-Like Crystal Structures

The accuracy of five docking programs at reproducing crystallographic structures of complexes of 8 macrolides and 12 related macrocyclic structures, all with their corresponding receptors, was evaluated. Self-docking calculations indicated excellent performance in all cases (mean RMSD values ≤ 1.0) and confirmed the speed of AutoDock Vina. Afterwards, the lowest-energy conformer of each molecule and all the conformers lying 0–10 kcal/mol above it (as given by Macrocycle, from MacroModel 10.0) were subjected to standard docking calculations. While each docking method has its own merits, the observed speed of the programs was as follows: Glide 6.6 > AutoDock Vina 1.1.2 > DOCK 6.5 >> AutoDock 4.2.6 > AutoDock 3.0.5. For most of the complexes, the five methods predicted quite correct poses of ligands at the binding sites, but the lower RMSD values for the poses of highest affinity were in the order: Glide 6.6 ≈ AutoDock Vina ≈ DOCK 6.5 > AutoDock 4.2.6 >> AutoDock 3.0.5. By choosing the poses closest to the crystal structure the order was: AutoDock Vina > Glide 6.6 ≈ DOCK 6.5 ≥ AutoDock 4.2.6 >> AutoDock 3.0.5. Re-scoring (AutoDock 4.2.6//AutoDock Vina, Amber Score and MM-GBSA) improved the agreement between the calculated and experimental data. For all intents and purposes, these three methods are equally reliable.

Computational methods to design cyclic peptides

Cyclic peptides (CPs) are promising modulators of protein-protein interactions (PPIs), but their application remains challenging. It is currently difficult to predict the structures and bioavailability of CPs. The ability to design CPs using computer modeling would greatly facilitate the development of CPs as potent PPI modulators for fundamental studies and as potential therapeutics. Herein, we describe computational methods to generate CP libraries for virtual screening, as well as current efforts to accurately predict the conformations adopted by CPs. These advances are making it possible to envision robust computational design of active CPs. However, unique properties of CPs pose significant challenges associated with sampling CP conformational space and accurately describing CP energetics. These major obstacles to structure prediction likely must be solved before robust design of active CPs can be reliably achieved.

Pyrazolo[1,5-a]pyrimidine-based macrocycles as novel HIV-1 inhibitors: a patent evaluation of WO2015123182

The emergence of drug resistance in Combination Antiretroviral Therapy (cART) confirms a continuing need to investigate novel HIV-1 inhibitors with unexplored mechanisms of action. Recently, a series of pyrazolopyrimidine-based macrocyclic compounds were reported as inhibitors of HIV-1 replication disclosed in the patent WO2015123182. Most of the disclosed compounds possessed in vitro antiviral potency in single-digit nanomolar range, which were determined by MT-2 cell assay. Then, the structural diversity, pharmacophore similarity of HIV-1 IN-LEDGF/p75 inhibitors, and implications for drug design were analyzed. In the end of this article, a glimpse of some macrocycles as potent antiviral agents (drug candidates) was provided. Some strategies and technologies enabling macrocycle design were also described. We expect that further development of these macrocyclic compounds will offer new anti-HIV-1 drug candidates.