SwissDock 2024: major enhancements for small-molecule docking with Attracting Cavities and AutoDock Vina.

Drug discovery aims to identify potential therapeutic compounds capable of modulating the activity of specific biological targets. Molecular docking can efficiently support this process by predicting binding interactions between small molecules and macromolecular targets and potentially accelerating screening campaigns. SwissDock is a computational tool released in 2011 as part of the SwissDrugDesign project, providing a free web-based service for small-molecule docking after automatized preparation of ligands and targets. Here, we present the latest version of SwissDock, in which EADock DSS has been replaced by two state-of-the-art docking programs, i.e. Attracting Cavities and AutoDock Vina. AutoDock Vina provides faster docking predictions, while Attracting Cavities offers more accurate results. Ligands can be imported in various ways, including as files, SMILES notation or molecular sketches. Targets can be imported as PDB files or identified by their PDB ID. In addition, advanced search options are available both for ligands and targets, giving users automatized access to widely-used databases. The web interface has been completely redesigned for interactive submission and analysis of docking results. Moreover, we developed a user-friendly command-line access which, in addition to all options of the web site, also enables covalent ligand docking with Attracting Cavities. The new version of SwissDock is freely available at https://www.swissdock.ch/.

Two-Step Covalent Docking with Attracting Cavities.

Due to their various advantages, interest in the development of covalent drugs has been renewed in the past few years. It is therefore important to accurately describe and predict their interactions with biological targets by computer-aided drug design tools such as docking algorithms. Here, we report a covalent docking procedure for our in-house docking code Attracting Cavities (AC), which mimics the two-step mechanism of covalent ligand binding. Ligand binding to the protein cavity is driven by nonbonded interactions, followed by the formation of a covalent bond between the ligand and the protein through a chemical reaction. To test the performance of this method, we developed a diverse, high-quality, openly accessible re-docking benchmark set of 95 covalent complexes bound by 8 chemical reactions to 5 different reactive amino acids. Combination with structures from previous studies resulted in a set of 304 complexes, on which AC obtained a success rate (rmsd ≤ 2 Å) of 78%, outperforming two state-of-the-art covalent docking codes, genetic optimization for ligand docking (GOLD (66%)) and AutoDock (AD (35%)). Using a more stringent success criterion (rmsd ≤ 1.5 Å), AC reached a success rate of 71 vs 55% for GOLD and 26% for AD. We additionally assessed the cross-docking performance of AC on a set of 76 covalent complexes of the SARS-CoV-2 main protease. On this challenging test set of mainly small and highly solvent-exposed ligands, AC yielded success rates of 58 and 28% for re-docking and cross-docking, respectively, compared to 45 and 17% for GOLD.

SwissParam 2023: A Modern Web-Based Tool for Efficient Small Molecule Parametrization.

Most steps of drug discovery are now routinely supported and accelerated by computer-aided drug design tools. Among them, structure-based approaches use the three-dimensional structure of the targeted biomacromolecule as a major source of information. When it comes to calculating the interactions of small molecules with proteins using the equations of molecular mechanics, topologies, atom typing, and force field parameters are required. However, generating parameters for small molecules remains challenging due to the large number of existing chemical groups. The SwissParam web tool was first released in 2011 with the aim of generating parameters and topologies for small molecules based on the Merck molecular force field (MMFF) while being compatible with the CHARMM22/27 force field. Here, we present an updated version of SwissParam, providing various new features, including the possibility to setup covalent ligands. Molecules can now be imported from different file formats or via a molecular sketcher. The MMFF-based approach has been updated to provide parameters and topologies compatible with the CHARMM36 force field. An option was added to generate small molecule parametrizations following the CHARMM General Force Field via the multipurpose atom-typer for CHARMM (MATCH) approach. Additionally, SwissParam now generates information on probable alternative tautomers and protonation states of the query molecule so that the user can consider all microspecies relevant to its compound. The new version of SwissParam is freely available at www.swissparam.ch and can also be accessed through a newly implemented command-line interface.

Attracting Cavities 2.0: Improving the Flexibility and Robustness for Small-Molecule Docking.

Molecular docking is a computational approach for predicting the most probable position of a ligand in the binding site of a target macromolecule. Our docking algorithm Attracting Cavities (AC) has been shown to compare favorably to other widely used docking algorithms [Zoete, V.; et al. J. Comput. Chem. 2016, 37, 437]. Here we describe several improvements of AC, making the sampling more robust and providing more flexibility for either fast or high-accuracy docking. We benchmark the performance of AC 2.0 using the 285 complexes of the PDBbind Core set, version 2016. For redocking from randomized ligand conformations, AC 2.0 reaches a success rate of 73.3%, compared to 63.9% for GOLD and 58.0% for AutoDock Vina. Due to its force-field-based scoring function and its thorough sampling procedure, AC 2.0 also performs well for blind docking on the entire receptor surface. The accuracy of its scoring function allows for the detection of problematic experimental structures in the benchmark set. For cross-docking, the AC 2.0 success rate is about 30% lower than for redocking (42.5%), similar to GOLD (42.8%) and better than AutoDock Vina (33.1%), and it can be improved by an informed choice of flexible protein residues. For selected targets with a high success rate in cross-docking, AC 2.0 also achieves good enrichment factors in virtual screening.

Structure-based optimization of type III indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors.

The haem enzyme indoleamine 2,3-dioxygenase 1 (IDO1) catalyses the rate-limiting step in the kynurenine pathway of tryptophan metabolism and plays an essential role in immunity, neuronal function, and ageing. Expression of IDO1 in cancer cells results in the suppression of an immune response, and therefore IDO1 inhibitors have been developed for use in anti-cancer immunotherapy. Here, we report an extension of our previously described highly efficient haem-binding 1,2,3-triazole and 1,2,4-triazole inhibitor series, the best compound having both enzymatic and cellular IC50 values of 34 nM. We provide enzymatic inhibition data for almost 100 new compounds and X-ray diffraction data for one compound in complex with IDO1. Structural and computational studies explain the dramatic drop in activity upon extension to pocket B, which has been observed in diverse haem-binding inhibitor scaffolds. Our data provides important insights for future IDO1 inhibitor design.

Structural Prediction of Peptide-MHC Binding Modes.

The immune system is constantly protecting its host from the invasion of pathogens and the development of cancer cells. The specific CD8+ T-cell immune response against virus-infected cells and tumor cells is based on the T-cell receptor recognition of antigenic peptides bound to class I major histocompatibility complexes (MHC) at the surface of antigen presenting cells. Consequently, the peptide binding specificities of the highly polymorphic MHC have important implications for the design of vaccines, for the treatment of autoimmune diseases, and for personalized cancer immunotherapy. Evidence-based machine-learning approaches have been successfully used for the prediction of peptide binders and are currently being developed for the prediction of peptide immunogenicity. However, understanding and modeling the structural details of peptide/MHC binding is crucial for a better understanding of the molecular mechanisms triggering the immunological processes, estimating peptide/MHC affinity using universal physics-based approaches, and driving the design of novel peptide ligands. Unfortunately, due to the large diversity of MHC allotypes and possible peptides, the growing number of 3D structures of peptide/MHC (pMHC) complexes in the Protein Data Bank only covers a small fraction of the possibilities. Consequently, there is a growing need for rapid and efficient approaches to predict 3D structures of pMHC complexes. Here, we review the key characteristics of the 3D structure of pMHC complexes before listing databases and other sources of information on pMHC structures and MHC specificities. Finally, we discuss some of the most prominent pMHC docking software.

Structure and Plasticity of Indoleamine 2,3-Dioxygenase 1 (IDO1).

Since the discovery of the implication of indoleamine 2,3-dioxygenase 1 (IDO1) in tumoral immune resistance in 2003, the search for inhibitors has been intensely pursued both in academia and in pharmaceutical companies, supported by the publication of the first crystal structure of IDO1 in 2006. More recently, it has become clear that IDO1 is an important player in various biological pathways and diseases ranging from neurodegenerative diseases to infection and autoimmunity. Its inhibition may lead to clinical benefit in different therapeutic settings. At present, over 50 experimental structures of IDO1 in complex with different ligands are available in the Protein Data Bank. Our analysis of this wealth of structural data sheds new light on several open issues regarding IDO1's structure and function.

Azole-Based Indoleamine 2,3-Dioxygenase 1 (IDO1) Inhibitors.

The heme enzyme indoleamine 2,3-dioxygenase 1 (IDO1) plays an essential role in immunity, neuronal function, and aging through catalysis of the rate-limiting step in the kynurenine pathway of tryptophan metabolism. Many IDO1 inhibitors with different chemotypes have been developed, mainly targeted for use in anti-cancer immunotherapy. Lead optimization of direct heme iron-binding inhibitors has proven difficult due to the remarkable selectivity and sensitivity of the heme-ligand interactions. Here, we present experimental data for a set of closely related small azole compounds with more than 4 orders of magnitude differences in their inhibitory activities, ranging from millimolar to nanomolar levels. We investigate and rationalize their activities based on structural data, molecular dynamics simulations, and density functional theory calculations. Our results not only expand the presently known four confirmed chemotypes of sub-micromolar heme binding IDO1 inhibitors by two additional scaffolds but also provide a model to predict the activities of novel scaffolds.

Inhibition Mechanisms of Indoleamine 2,3-Dioxygenase 1 (IDO1).

Indoleamine 2,3-dioxygenase 1 (IDO1) catalyzes the rate-limiting step in the kynurenine pathway of tryptophan metabolism, which is involved in immunity, neuronal function, and aging. Its implication in pathologies such as cancer and neurodegenerative diseases has stimulated the development of IDO1 inhibitors. However, negative phase III clinical trial results of the IDO1 inhibitor epacadostat in cancer immunotherapy call for a better understanding of the role and the mechanisms of IDO1 inhibition. In this work, we investigate the molecular inhibition mechanisms of four known IDO1 inhibitors and of two quinones in detail, using different experimental and computational approaches. We also determine for the first time the X-ray structure of the highly efficient 1,2,3-triazole inhibitor MMG-0358. Based on our results and a comprehensive literature overview, we propose a classification scheme for IDO1 inhibitors according to their inhibition mechanism, which will be useful for further developments in the field.

Tryptophan metabolism as a common therapeutic target in cancer, neurodegeneration and beyond.

L-Tryptophan (Trp) metabolism through the kynurenine pathway (KP) is involved in the regulation of immunity, neuronal function and intestinal homeostasis. Imbalances in Trp metabolism in disorders ranging from cancer to neurodegenerative disease have stimulated interest in therapeutically targeting the KP, particularly the main rate-limiting enzymes indoleamine-2,3-dioxygenase 1 (IDO1), IDO2 and tryptophan-2,3-dioxygenase (TDO) as well as kynurenine monooxygenase (KMO). However, although small-molecule IDO1 inhibitors showed promise in early-stage cancer immunotherapy clinical trials, a phase III trial was negative. This Review summarizes the physiological and pathophysiological roles of Trp metabolism, highlighting the vast opportunities and challenges for drug development in multiple diseases.

The conserved threonine-rich region of the HCF-1PRO repeat activates promiscuous OGT:UDP-GlcNAc glycosylation and proteolysis activities.

O-Linked GlcNAc transferase (OGT) possesses dual glycosyltransferase-protease activities. OGT thereby stably glycosylates serines and threonines of numerous proteins and, via a transient glutamate glycosylation, cleaves a single known substrate-the so-called HCF-1PRO repeat of the transcriptional co-regulator host-cell factor 1 (HCF-1). Here, we probed the relationship between these distinct glycosylation and proteolytic activities. For proteolysis, the HCF-1PRO repeat possesses an important extended threonine-rich region that is tightly bound by the OGT tetratricopeptide-repeat (TPR) region. We report that linkage of this HCF-1PRO-repeat, threonine-rich region to heterologous substrate sequences also potentiates robust serine glycosylation with the otherwise poor Rp-αS-UDP-GlcNAc diastereomer phosphorothioate and UDP-5S-GlcNAc OGT co-substrates. Furthermore, it potentiated proteolysis of a non-HCF-1PRO-repeat cleavage sequence, provided it contained an appropriately positioned glutamate residue. Using serine- or glutamate-containing HCF-1PRO-repeat sequences, we show that proposed OGT-based or UDP-GlcNAc-based serine-acceptor residue activation mechanisms can be circumvented independently, but not when disrupted together. In contrast, disruption of both proposed activation mechanisms even in combination did not inhibit OGT-mediated proteolysis. These results reveal a multiplicity of OGT glycosylation strategies, some leading to proteolysis, which could be targets of alternative molecular regulatory strategies.

The Binding Mode of N-Hydroxyamidines to Indoleamine 2,3-Dioxygenase 1 (IDO1).

Indoleamine 2,3-dioxygenase 1 (IDO1) is an important target in cancer immunotherapy. The most advanced clinical compound, epacadostat (INCB024360), binds to the heme cofactor of IDO1 through an N-hydroxyamidine function. Conflicting binding modes have recently been proposed, reporting iron binding either through the hydroxyamidine oxygen or through the hydroxyamidine nitrogen atom. Here, we use quantum chemical calculations, docking, and quantum mechanics/molecular mechanics calculations based on available X-ray data to resolve this issue and to propose a physically meaningful binding mode. Our findings will aid the design of novel IDO1 ligands based on this pharmacophore.

On-the-Fly QM/MM Docking with Attracting Cavities.

We developed a hybrid quantum mechanical/molecular mechanical (QM/MM) on-the-fly docking algorithm to address the challenges of treating polarization and selected metal interactions in docking. The algorithm is based on our classical docking algorithm Attracting Cavities and relies on the semiempirical self-consistent charge density functional tight-binding (SCC-DFTB) method and the CHARMM force field. We benchmarked the performance of this approach on three very diverse data sets: (1) the Astex Diverse set of 85 common noncovalent drug/target complexes formed both by hydrophobic and electrostatic interactions; (2) a zinc metalloprotein data set of 281 complexes, where polarization is strong and ligand/protein interactions are dominated by electrostatic interactions; and (3) a heme protein data set of 72 complexes, where ligand/protein interactions are dominated by covalent ligand/iron binding. Redocking performance of the on-the-fly QM/MM docking algorithm was compared to the performance of classical Attracting Cavities, AutoDock, AutoDock Vina, and GOLD. The results demonstrate that the QM/MM code preserves the high accuracy of most classical scores on the Astex Diverse set, while it yields significant improvements on both sets of metalloproteins at moderate computational cost.

1,2,3-Triazoles as inhibitors of indoleamine 2,3-dioxygenase 2 (IDO2).

Indoleamine 2,3-dioxygenase 2 (IDO2) is a potential therapeutic target for the treatment of diseases that involve immune escape such as cancer. In contrast to IDO1, only a very limited number of inhibitors have been described for IDO2 due to inherent difficulties in expressing and purifying a functionally active, soluble form of the enzyme. Starting from our previously discovered highly efficient 4-aryl-1,2,3-triazole IDO1 inhibitor scaffold, we used computational structure-based methods to design inhibitors of IDO2 which we then tested in cellular assays. Our approach yielded low molecular weight inhibitors of IDO2, the most active displaying an IC50 value of 51µM for mIDO2, and twofold selectivity over hIDO1. These compounds could be useful as molecular probes to investigate the biological role of IDO2, and could inspire the design of new IDO2 inhibitors.

Proteolysis of HCF-1 by Ser/Thr glycosylation-incompetent O-GlcNAc transferase:UDP-GlcNAc complexes.

In complex with the cosubstrate UDP-N-acetylglucosamine (UDP-GlcNAc),O-linked-GlcNAc transferase (OGT) catalyzes Ser/ThrO-GlcNAcylation of many cellular proteins and proteolysis of the transcriptional coregulator HCF-1. Such a dual glycosyltransferase-protease activity, which occurs in the same active site, is unprecedented and integrates both reversible and irreversible forms of protein post-translational modification within one enzyme. Although occurring within the same active site, we show here that glycosylation and proteolysis occur through separable mechanisms. OGT consists of tetratricopeptide repeat (TPR) and catalytic domains, which, together with UDP-GlcNAc, are required for both glycosylation and proteolysis. Nevertheless, a specific TPR domain contact with the HCF-1 substrate is critical for proteolysis but not Ser/Thr glycosylation. In contrast, key catalytic domain residues and even a UDP-GlcNAc oxygen important for Ser/Thr glycosylation are irrelevant for proteolysis. Thus, from a dual glycosyltransferase-protease, essentially single-activity enzymes can be engineered both in vitro and in vivo. Curiously, whereas OGT-mediated HCF-1 proteolysis is limited to vertebrate species, invertebrate OGTs can cleave human HCF-1. We present a model for the evolution of HCF-1 proteolysis by OGT.

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

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

Single amino acid charge switch defines clinically distinct proline-serine-threonine phosphatase-interacting protein 1 (PSTPIP1)-associated inflammatory diseases.

BACKGROUND: Hyperzincemia and hypercalprotectinemia (Hz/Hc) is a distinct autoinflammatory entity involving extremely high serum concentrations of the proinflammatory alarmin myeloid-related protein (MRP) 8/14 (S100A8/S100A9 and calprotectin). OBJECTIVE: We sought to characterize the genetic cause and clinical spectrum of Hz/Hc. METHODS: Proline-serine-threonine phosphatase-interacting protein 1 (PSTPIP1) gene sequencing was performed in 14 patients with Hz/Hc, and their clinical phenotype was compared with that of 11 patients with pyogenic arthritis, pyoderma gangrenosum, and acne (PAPA) syndrome. PSTPIP1-pyrin interactions were analyzed by means of immunoprecipitation and Western blotting. A structural model of the PSTPIP1 dimer was generated. Cytokine profiles were analyzed by using the multiplex immunoassay, and MRP8/14 serum concentrations were analyzed by using an ELISA. RESULTS: Thirteen patients were heterozygous for a missense mutation in the PSTPIP1 gene, resulting in a p.E250K mutation, and 1 carried a mutation resulting in p.E257K. Both mutations substantially alter the electrostatic potential of the PSTPIP1 dimer model in a region critical for protein-protein interaction. Patients with Hz/Hc have extremely high MRP8/14 concentrations (2045 ± 1300 µg/mL) compared with those with PAPA syndrome (116 ± 74 µg/mL) and have a distinct clinical phenotype. A specific cytokine profile is associated with Hz/Hc. Hz/Hc mutations altered protein binding of PSTPIP1, increasing interaction with pyrin through phosphorylation of PSTPIP1. CONCLUSION: Mutations resulting in charge reversal in the y-domain of PSTPIP1 (E→K) and increased interaction with pyrin cause a distinct autoinflammatory disorder defined by clinical and biochemical features not found in patients with PAPA syndrome, indicating a unique genotype-phenotype correlation for mutations in the PSTPIP1 gene. This is the first inborn autoinflammatory syndrome in which inflammation is driven by uncontrolled release of members of the alarmin family.

Challenges in the Discovery of Indoleamine 2,3-Dioxygenase 1 (IDO1) Inhibitors.

Since the discovery of indoleamine 2,3-dioxygenase 1 (IDO1) as an attractive target for anticancer therapy in 2003, the search for inhibitors has been intensely pursued both in academia and in pharmaceutical companies. Many novel IDO1 inhibitor scaffolds have been described, and a few potent compounds have entered clinical trials. However, a significant number of the reported compounds contain problematic functional groups, suggesting that enzyme inhibition could be the result of undesirable side reactions instead of selective binding to IDO1. Here, we describe issues in the employed experimental protocols, review and classify reported IDO1 inhibitors, and suggest different approaches for confirming viable inhibitor scaffolds.

Toward on-the-fly quantum mechanical/molecular mechanical (QM/MM) docking: development and benchmark of a scoring function.

We address the challenges of treating polarization and covalent interactions in docking by developing a hybrid quantum mechanical/molecular mechanical (QM/MM) scoring function based on the semiempirical self-consistent charge density functional tight-binding (SCC-DFTB) method and the CHARMM force field. To benchmark this scoring function within the EADock DSS docking algorithm, we created a publicly available dataset of high-quality X-ray structures of zinc metalloproteins ( http://www.molecular-modelling.ch/resources.php ). For zinc-bound ligands (226 complexes), the QM/MM scoring yielded a substantially improved success rate compared to the classical scoring function (77.0% vs 61.5%), while, for allosteric ligands (55 complexes), the success rate remained constant (49.1%). The QM/MM scoring significantly improved the detection of correct zinc-binding geometries and improved the docking success rate by more than 20% for several important drug targets. The performance of both the classical and the QM/MM scoring functions compare favorably to the performance of AutoDock4, AutoDock4Zn, and AutoDock Vina.

Detailed analysis and follow-up studies of a high-throughput screening for indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors.

Indoleamine 2,3-dioxygenase 1 (IDO1) is a key regulator of immune responses and therefore an important therapeutic target for the treatment of diseases that involve pathological immune escape, such as cancer. Here, we describe a robust and sensitive high-throughput screen (HTS) for IDO1 inhibitors using the Prestwick Chemical Library of 1200 FDA-approved drugs and the Maybridge HitFinder Collection of 14,000 small molecules. Of the 60 hits selected for follow-up studies, 14 displayed IC50 values below 20 µM under the secondary assay conditions, and 4 showed an activity in cellular tests. In view of the high attrition rate we used both experimental and computational techniques to identify and to characterize compounds inhibiting IDO1 through unspecific inhibition mechanisms such as chemical reactivity, redox cycling, or aggregation. One specific IDO1 inhibitor scaffold, the imidazole antifungal agents, was chosen for rational structure-based lead optimization, which led to more soluble and smaller compounds with micromolar activity.