Testing the predictive power of reverse screening to infer drug targets, with the help of machine learning.

Estimating protein targets of compounds based on the similarity principle-similar molecules are likely to show comparable bioactivity-is a long-standing strategy in drug research. Having previously quantified this principle, we present here a large-scale evaluation of its predictive power for inferring macromolecular targets by reverse screening an unprecedented vast external test set of more than 300,000 active small molecules against another bioactivity set of more than 500,000 compounds. We show that machine-learning can predict the correct targets, with the highest probability among 2069 proteins, for more than 51% of the external molecules. The strong enrichment thus obtained demonstrates its usefulness in supporting phenotypic screens, polypharmacology, or repurposing. Moreover, we quantified the impact of the bioactivity knowledge available for proteins in terms of number and diversity of actives. Finally, we advise that developers of such approaches follow an application-oriented benchmarking strategy and use large, high-quality, non-overlapping datasets as provided here.

Identification of clinically relevant T cell receptors for personalized T cell therapy using combinatorial algorithms.

A central challenge in developing personalized cancer cell immunotherapy is the identification of tumor-reactive T cell receptors (TCRs). By exploiting the distinct transcriptomic profile of tumor-reactive T cells relative to bystander cells, we build and benchmark TRTpred, an antigen-agnostic in silico predictor of tumor-reactive TCRs. We integrate TRTpred with an avidity predictor to derive a combinatorial algorithm of clinically relevant TCRs for personalized T cell therapy and benchmark it in patient-derived xenografts.

Herpes simplex encephalitis due to a mutation in an E3 ubiquitin ligase.

Encephalitis is a rare and potentially fatal manifestation of herpes simplex type 1 infection. Following genome-wide genetic analyses, we identified a previously uncharacterized and very rare heterozygous variant in the E3 ubiquitin ligase WWP2, in a 14-month-old girl with herpes simplex encephalitis. The p.R841H variant (NM_007014.4:c.2522G > A) impaired TLR3 mediated signaling in inducible pluripotent stem cells-derived neural precursor cells and neurons; cells bearing this mutation were also more susceptible to HSV-1 infection compared to control cells. The p.R841H variant increased TRIF ubiquitination in vitro. Antiviral immunity was rescued following the correction of p.R841H by CRISPR-Cas9 technology. Moreover, the introduction of p.R841H in wild type cells reduced such immunity, suggesting that this mutation is linked to the observed phenotypes.

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.

Neoantigen-specific CD8 T cells with high structural avidity preferentially reside in and eliminate tumors.

The success of cancer immunotherapy depends in part on the strength of antigen recognition by T cells. Here, we characterize the T cell receptor (TCR) functional (antigen sensitivity) and structural (monomeric pMHC-TCR off-rates) avidities of 371 CD8 T cell clones specific for neoantigens, tumor-associated antigens (TAAs) or viral antigens isolated from tumors or blood of patients and healthy donors. T cells from tumors exhibit stronger functional and structural avidity than their blood counterparts. Relative to TAA, neoantigen-specific T cells are of higher structural avidity and, consistently, are preferentially detected in tumors. Effective tumor infiltration in mice models is associated with high structural avidity and CXCR3 expression. Based on TCR biophysicochemical properties, we derive and apply an in silico model predicting TCR structural avidity and validate the enrichment in high avidity T cells in patients' tumors. These observations indicate a direct relationship between neoantigen recognition, T cell functionality and tumor infiltration. These results delineate a rational approach to identify potent T cells for personalized cancer immunotherapy.

Influenza A virus exploits transferrin receptor recycling to enter host cells.

Influenza A virus (IAV) enters host cells mostly through clathrin-dependent receptor-mediated endocytosis. A single bona fide entry receptor protein supporting this entry mechanism remains elusive. Here we performed proximity ligation of biotin to host cell surface proteins in the vicinity of attached trimeric hemagglutinin-HRP and characterized biotinylated targets using mass spectrometry. This approach identified transferrin receptor 1 (TfR1) as a candidate entry protein. Genetic gain-of-function and loss-of-function experiments, as well as in vitro and in vivo chemical inhibition, confirmed the functional involvement of TfR1 in IAV entry. Recycling deficient mutants of TfR1 do not support entry, indicating that TfR1 recycling is essential for this function. The binding of virions to TfR1 via sialic acids confirmed its role as a directly acting entry factor, but unexpectedly even headless TfR1 promoted IAV particle uptake in trans. TIRF microscopy localized the entering virus-like particles in the vicinity of TfR1. Our data identify TfR1 recycling as a revolving door mechanism exploited by IAV to enter host cells.

FOXI3 pathogenic variants cause one form of craniofacial microsomia.

Craniofacial microsomia (CFM; also known as Goldenhar syndrome), is a craniofacial developmental disorder of variable expressivity and severity with a recognizable set of abnormalities. These birth defects are associated with structures derived from the first and second pharyngeal arches, can occur unilaterally and include ear dysplasia, microtia, preauricular tags and pits, facial asymmetry and other malformations. The inheritance pattern is controversial, and the molecular etiology of this syndrome is largely unknown. A total of 670 patients belonging to unrelated pedigrees with European and Chinese ancestry with CFM, are investigated. We identify 18 likely pathogenic variants in 21 probands (3.1%) in FOXI3. Biochemical experiments on transcriptional activity and subcellular localization of the likely pathogenic FOXI3 variants, and knock-in mouse studies strongly support the involvement of FOXI3 in CFM. Our findings indicate autosomal dominant inheritance with reduced penetrance, and/or autosomal recessive inheritance. The phenotypic expression of the FOXI3 variants is variable. The penetrance of the likely pathogenic variants in the seemingly dominant form is reduced, since a considerable number of such variants in affected individuals were inherited from non-affected parents. Here we provide suggestive evidence that common variation in the FOXI3 allele in trans with the pathogenic variant could modify the phenotypic severity and accounts for the incomplete penetrance.

Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes.

CD4+ T cells orchestrate the adaptive immune response against pathogens and cancer by recognizing epitopes presented on class II major histocompatibility complex (MHC-II) molecules. The high polymorphism of MHC-II genes represents an important hurdle toward accurate prediction and identification of CD4+ T cell epitopes. Here we collected and curated a dataset of 627,013 unique MHC-II ligands identified by mass spectrometry. This enabled us to precisely determine the binding motifs of 88 MHC-II alleles across humans, mice, cattle, and chickens. Analysis of these binding specificities combined with X-ray crystallography refined our understanding of the molecular determinants of MHC-II motifs and revealed a widespread reverse-binding mode in HLA-DP ligands. We then developed a machine-learning framework to accurately predict binding specificities and ligands of any MHC-II allele. This tool improves and expands predictions of CD4+ T cell epitopes and enables us to discover viral and bacterial epitopes following the aforementioned reverse-binding mode.

Response and Resistance to Trametinib in MAP2K1-Mutant Triple-Negative Melanoma.

The development of targeted therapies for non-BRAF p.Val600-mutant melanomas remains a challenge. Triple wildtype (TWT) melanomas that lack mutations in BRAF, NRAS, or NF1 form 10% of human melanomas and are heterogeneous in their genomic drivers. MAP2K1 mutations are enriched in BRAF-mutant melanoma and function as an innate or adaptive resistance mechanism to BRAF inhibition. Here we report the case of a patient with TWT melanoma with a bona fide MAP2K1 mutation without any BRAF mutations. We performed a structural analysis to validate that the MEK inhibitor trametinib could block this mutation. Although the patient initially responded to trametinib, he eventually progressed. The presence of a CDKN2A deletion prompted us to combine a CDK4/6 inhibitor, palbociclib, with trametinib but without clinical benefit. Genomic analysis at progression showed multiple novel copy number alterations. Our case illustrates the challenges of combining MEK1 and CDK4/6 inhibitors in case of resistance to MEK inhibitor monotherapy.

Bi-allelic TTI1 variants cause an autosomal-recessive neurodevelopmental disorder with microcephaly.

Telomere maintenance 2 (TELO2), Tel2 interacting protein 2 (TTI2), and Tel2 interacting protein 1 (TTI1) are the three components of the conserved Triple T (TTT) complex that modulates activity of phosphatidylinositol 3-kinase-related protein kinases (PIKKs), including mTOR, ATM, and ATR, by regulating the assembly of mTOR complex 1 (mTORC1). The TTT complex is essential for the expression, maturation, and stability of ATM and ATR in response to DNA damage. TELO2- and TTI2-related bi-allelic autosomal-recessive (AR) encephalopathies have been described in individuals with moderate to severe intellectual disability (ID), short stature, postnatal microcephaly, and a movement disorder (in the case of variants within TELO2). We present clinical, genomic, and functional data from 11 individuals in 9 unrelated families with bi-allelic variants in TTI1. All present with ID, and most with microcephaly, short stature, and a movement disorder. Functional studies performed in HEK293T cell lines and fibroblasts and lymphoblastoid cells derived from 4 unrelated individuals showed impairment of the TTT complex and of mTOR pathway activity which is improved by treatment with Rapamycin. Our data delineate a TTI1-related neurodevelopmental disorder and expand the group of disorders related to the TTT complex.

Immunogenomic analysis of human brain metastases reveals diverse immune landscapes across genetically distinct tumors.

Brain metastases (BrMs) are the most common form of brain tumors in adults and frequently originate from lung and breast primary cancers. BrMs are associated with high mortality, emphasizing the need for more effective therapies. Genetic profiling of primary tumors is increasingly used as part of the effort to guide targeted therapies against BrMs, and immune-based strategies for the treatment of metastatic cancer are gaining momentum. However, the tumor immune microenvironment (TIME) of BrM is extremely heterogeneous, and whether specific genetic profiles are associated with distinct immune states remains unknown. Here, we perform an extensive characterization of the immunogenomic landscape of human BrMs by combining whole-exome/whole-genome sequencing, RNA sequencing of immune cell populations, flow cytometry, immunofluorescence staining, and tissue imaging analyses. This revealed unique TIME phenotypes in genetically distinct lung- and breast-BrMs, thereby enabling the development of personalized immunotherapies tailored by the genetic makeup of the tumors.

Both APRIL and antibody-fragment-based CAR T cells for myeloma induce BCMA downmodulation by trogocytosis and internalization.

BACKGROUND: Chimeric antigen receptor (CAR) T cell therapy targeting B cell maturation antigen (BCMA) on multiple myeloma (MM) produces fast but not long-lasting responses. Reasons for treatment failure are poorly understood. CARs simultaneously targeting two antigens may represent an alternative. Here, we (1) designed and characterized novel A proliferation inducing ligand (APRIL) based dual-antigen targeting CARs, and (2) investigated mechanisms of resistance to CAR T cells with three different BCMA-binding moieties (APRIL, single-chain-variable-fragment, heavy-chain-only). METHODS: Three new APRIL-CARs were designed and characterized. Human APRIL-CAR T cells were evaluated for their cytotoxic function in vitro and in vivo, for their polyfunctionality, immune synapse formation, memory, exhaustion phenotype and tonic signaling activity. To investigate resistance mechanisms, we analyzed BCMA levels and cellular localization and quantified CAR T cell-target cell interactions by live microscopy. Impact on pathway activation and tumor cell proliferation was assessed in vitro and in vivo. RESULTS: APRIL-CAR T cells in a trimeric ligand binding conformation conferred fast but not sustained antitumor responses in vivo in mouse xenograft models. In vitro trimer-BBζ CAR T cells were more polyfunctional and formed stronger immune synapses than monomer-BBζ CAR T cells. After CAR T cell-myeloma cell contact, BCMA was rapidly downmodulated on target cells with all evaluated binding moieties. CAR T cells acquired BCMA by trogocytosis, and BCMA on MM cells was rapidly internalized. Since BCMA can be re-expressed during progression and persisting CAR T cells may not protect patients from relapse, we investigated whether non-functional CAR T cells play a role in tumor progression. While CAR T cell-MM cell interactions activated BCMA pathway, we did not find enhanced tumor growth in vitro or in vivo. CONCLUSION: Antitumor responses with APRIL-CAR T cells were fast but not sustained. Rapid BCMA downmodulation occurred independently of whether an APRIL or antibody-based binding moiety was used. BCMA internalization mostly contributed to this effect, but trogocytosis by CAR T cells was also observed. Our study sheds light on the mechanisms underlying CAR T cell failure in MM when targeting BCMA and can inform the development of improved treatment strategies.

Secondary IDH1 resistance mutations and oncogenic IDH2 mutations cause acquired resistance to ivosidenib in cholangiocarcinoma.

The mutant IDH1 inhibitor ivosidenib improves outcomes for patients with IDH1-mutated cholangiocarcinoma, but resistance inevitably develops. Mechanisms of resistance and strategies to overcome resistance are poorly understood. Here we describe two patients with IDH1 R132C-mutated metastatic cholangiocarcinoma who developed acquired resistance to ivosidenib. After disease progression, one patient developed an oncogenic IDH2 mutation, and the second patient acquired a secondary IDH1 D279N mutation. To characterize the putative IDH1 resistance mutation, cells expressing the double-mutant were generated. In vitro, IDH1 R132H/D279N produces (R)-2HG less efficiently than IDH1 R132H. However, its binding to ivosidenib is impaired and it retains the ability to produce (R)-2HG and promote cellular transformation in the presence of ivosidenib. The irreversible mutant IDH1 inhibitor LY3410738 binds and blocks (R)-2HG production and cellular transformation by IDH1 R132H/D279N. These resistance mechanisms suggest that IDH1-mutated cholangiocarcinomas remain dependent on (R)-2HG even after prolonged ivosidenib treatment. Sequential mutant IDH inhibitor therapy should be explored as a strategy to overcome acquired resistance to mutant IDH inhibitors.

Structure-based prediction of BRAF mutation classes using machine-learning approaches.

The BRAF kinase is attracting a lot of attention in oncology as alterations of its amino acid sequence can constitutively activate the MAP kinase signaling pathway, potentially contributing to the malignant transformation of the cell but at the same time rendering it sensitive to targeted therapy. Several pathologic BRAF variants were grouped in three different classes (I, II and III) based on their effects on the protein activity and pathway. Discerning the class of a BRAF mutation permits to adapt the treatment proposed to the patient. However, this information is lacking new and experimentally uncharacterized BRAF mutations detected in a patient biopsy. To overcome this issue, we developed a new in silico tool based on machine learning approaches to predict the potential class of a BRAF missense variant. As class I only involves missense mutations of Val600, we focused on the mutations of classes II and III, which are more diverse and challenging to predict. Using a logistic regression model and features including structural information, we were able to predict the classes of known mutations with an accuracy of 90%. This new and fast predictive tool will help oncologists to tackle potential pathogenic BRAF mutations and to propose the most appropriate treatment for their patients.

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.

Actin assembly requirements of the formin Fus1 to build the fusion focus.

In formin-family proteins, actin filament nucleation and elongation activities reside in the formin homology 1 (FH1) and FH2 domains, with reaction rates that vary by at least 20-fold between formins. Each cell expresses distinct formins that assemble one or several actin structures, raising the question of what confers each formin its specificity. Here, using the formin Fus1 in Schizosaccharomyces pombe, we systematically probed the importance of formin nucleation and elongation rates in vivo. Fus1 assembles the actin fusion focus, necessary for gamete fusion to form the zygote during sexual reproduction. By constructing chimeric formins with combinations of FH1 and FH2 domains previously characterized in vitro, we establish that changes in formin nucleation and elongation rates have direct consequences on fusion focus architecture, and that Fus1 native high nucleation and low elongation rates are optimal for fusion focus assembly. We further describe a point mutant in Fus1 FH2 that preserves native nucleation and elongation rates in vitro but alters function in vivo, indicating an additional FH2 domain property. Thus, rates of actin assembly are tailored for assembly of specific actin structures.

Heterozygous variants in CTR9, which encodes a major component of the PAF1 complex, are associated with a neurodevelopmental disorder.

PURPOSE: CTR9 is a subunit of the PAF1 complex (PAF1C) that plays a crucial role in transcription regulation by binding CTR9 to RNA polymerase II. It is involved in transcription-coupled histone modification through promoting H3K4 and H3K36 methylation. We describe the clinical and molecular studies in 13 probands, harboring likely pathogenic CTR9 missense variants, collected through GeneMatcher. METHODS: Exome sequencing was performed in all individuals. CTR9 variants were assessed through 3-dimensional modeling of the activated human transcription complex Pol II-DSIF-PAF-SPT6 and the PAF1/CTR9 complex. H3K4/H3K36 methylation analysis, mitophagy assessment based on tetramethylrhodamine ethyl ester perchlorate immunofluorescence, and RNA-sequencing in skin fibroblasts from 4 patients was performed. RESULTS: Common clinical findings were variable degrees of intellectual disability, hypotonia, joint hyperlaxity, speech delay, coordination problems, tremor, and autism spectrum disorder. Mild dysmorphism and cardiac anomalies were less frequent. For 11 CTR9 variants, de novo occurrence was shown. Three-dimensional modeling predicted a likely disruptive effect of the variants on local CTR9 structure and protein interaction. Additional studies in fibroblasts did not unveil the downstream functional consequences of the identified variants. CONCLUSION: We describe a neurodevelopmental disorder caused by (mainly) de novo variants in CTR9, likely affecting PAF1C function.