•The use of AI-driven solutions to enable pre-clinical drug discovery is growing steadily within the pharmaceutical industry.•AI technologies can be leveraged across the drug discovery value ...chain.•Artificial intelligence may transform the way we do drug discovery, but certainly cannot replace human ingenuity.•AI may become a disruptive technology for drug discovery in the future, but there is still room for healthy skepticism as the field matures.
Artificial intelligence (AI) is becoming an integral part of drug discovery. It has the potential to deliver across the drug discovery and development value chain, starting from target identification and reaching through clinical development. In this review, we provide an overview of current AI technologies and a glimpse of how AI is reimagining preclinical drug discovery by highlighting examples where AI has made a real impact. Considering the excitement and hyperbole surrounding AI in drug discovery, we aim to present a realistic view by discussing both opportunities and challenges in adopting AI in drug discovery.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Epidermal growth factor receptor (EGFR) mutations typically occur in exons 18-21 and are established driver mutations in non-small cell lung cancer (NSCLC)
. Targeted therapies are approved for ...patients with 'classical' mutations and a small number of other mutations
. However, effective therapies have not been identified for additional EGFR mutations. Furthermore, the frequency and effects of atypical EGFR mutations on drug sensitivity are unknown
. Here we characterize the mutational landscape in 16,715 patients with EGFR-mutant NSCLC, and establish the structure-function relationship of EGFR mutations on drug sensitivity. We found that EGFR mutations can be separated into four distinct subgroups on the basis of sensitivity and structural changes that retrospectively predict patient outcomes following treatment with EGFR inhibitors better than traditional exon-based groups. Together, these data delineate a structure-based approach for defining functional groups of EGFR mutations that can effectively guide treatment and clinical trial choices for patients with EGFR-mutant NSCLC and suggest that a structure-function-based approach may improve the prediction of drug sensitivity to targeted therapies in oncogenes with diverse mutations.
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GEOZS, IJS, IMTLJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZAGLJ
Structural coverage of the human kinome has been steadily increasing over time. The structures provide valuable insights into the molecular basis of kinase function and also provide a foundation for ...understanding the mechanisms of kinase inhibitors. There are a large number of kinase structures in the PDB for which the Asp and Phe of the DFG motif on the activation loop swap positions, resulting in the formation of a new allosteric pocket. We refer to these structures as “classical DFG-out” conformations in order to distinguish them from conformations that have also been referred to as DFG-out in the literature but that do not have a fully formed allosteric pocket. We have completed a structural analysis of almost 200 small molecule inhibitors bound to classical DFG-out conformations; we find that they are recognized by both type I and type II inhibitors. In contrast, we find that nonclassical DFG-out conformations strongly select against type II inhibitors because these structures have not formed a large enough allosteric pocket to accommodate this type of binding mode. In the course of this study we discovered that the number of structurally validated type II inhibitors that can be found in the PDB and that are also represented in publicly available biochemical profiling studies of kinase inhibitors is very small. We have obtained new profiling results for several additional structurally validated type II inhibitors identified through our conformational analysis. Although the available profiling data for type II inhibitors is still much smaller than for type I inhibitors, a comparison of the two data sets supports the conclusion that type II inhibitors are more selective than type I. We comment on the possible contribution of the DFG-in to DFG-out conformational reorganization to the selectivity.
We report a phase II study of 50 advanced non-small cell lung cancer (NSCLC) patients with point mutations or insertions in EGFR exon 20 treated with poziotinib (NCT03066206). The study achieved its ...primary endpoint, with confirmed objective response rates (ORRs) of 32% and 31% by investigator and blinded independent review, respectively, with a median progression-free survival of 5.5 months. Using preclinical studies, in silico modeling, and molecular dynamics simulations, we found that poziotinib sensitivity was highly dependent on the insertion location, with near-loop insertions (amino acids A767 to P772) being more sensitive than far-loop insertions, an observation confirmed clinically with ORRs of 46% and 0% observed in near versus far-loop, respectively (p = 0.0015). Putative mechanisms of acquired resistance included EGFR T790M, MET amplifications, and epithelial-to-mesenchymal transition (EMT). Our data demonstrate that poziotinib is active in EGFR exon 20-mutant NSCLC, although this activity is influenced by insertion location.
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•Poziotinib yields a 32% response rate in EGFR exon 20-mutant NSCLC•Poziotinib sensitivity is highly dependent on insertion location•Near-loop exon 20 insertions are more sensitive to poziotinib than far-loop insertions•Mechanisms of acquired poziotinib resistance include EGFR T790M and MET amplifications
Elamin et al. show that poziotinib is active in EGFR exon 20-mutant non-small cell lung cancer. The activity of poziotinib is influenced by insertion location in exon 20, with near-loop insertion being more sensitive than far-loop insertion. Poziotinib acquired resistance is mediated via EGFR-dependent and -independent mechanisms.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
We characterized the landscape and drug sensitivity of ERBB2 (HER2) mutations in cancers. In 11 datasets (n = 211,726), ERBB2 mutational hotspots varied across 25 tumor types. Common HER2 mutants ...yielded differential sensitivities to eleven EGFR/HER2 tyrosine kinase inhibitors (TKIs) in vitro, and molecular dynamics simulations revealed that mutants with a reduced drug-binding pocket volume were associated with decreased affinity for larger TKIs. Overall, poziotinib was the most potent HER2 mutant-selective TKI tested. Phase II clinical testing in ERBB2 exon 20-mutant non-small cell lung cancer resulted in a confirmed objective response rate of 42% in the first 12 evaluable patients. In pre-clinical models, poziotinib upregulated HER2 cell-surface expression and potentiated the activity of T-DM1, resulting in complete tumor regression with combination treatment.
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•ERBB2 mutations occur in at least 25 tumor types with varying patterns of mutations•Mutation-induced changes in drug-binding pocket volume dictate drug sensitivity•Poziotinib inhibits mutant HER2, yielding a 42% response rate in NSCLC patients•Combination of poziotinib with T-DM1 potentiates antitumor activity of both agents
Robichaux et al. show that ERBB2 mutation hotspots vary across human tumor types, which affect the volume of the HER2 TKI binding pocket and dictate drug sensitivity. Poziotinib is the most potent HER2 TKI among those tested. Moreover, poziotinib enhances T-DM1 efficacy by increasing the cell-surface HER2 level.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Understanding the conformational propensities of proteins is key to solving many problems in structural biology and biophysics. The co‐variation of pairs of mutations contained in multiple sequence ...alignments of protein families can be used to build a Potts Hamiltonian model of the sequence patterns which accurately predicts structural contacts. This observation paves the way to develop deeper connections between evolutionary fitness landscapes of entire protein families and the corresponding free energy landscapes which determine the conformational propensities of individual proteins. Using statistical energies determined from the Potts model and an alignment of 2896 PDB structures, we predict the propensity for particular kinase family proteins to assume a “DFG‐out” conformation implicated in the susceptibility of some kinases to type‐II inhibitors, and validate the predictions by comparison with the observed structural propensities of the corresponding proteins and experimental binding affinity data. We decompose the statistical energies to investigate which interactions contribute the most to the conformational preference for particular sequences and the corresponding proteins. We find that interactions involving the activation loop and the C‐helix and HRD motif are primarily responsible for stabilizing the DFG‐in state. This work illustrates how structural free energy landscapes and fitness landscapes of proteins can be used in an integrated way, and in the context of kinase family proteins, can potentially impact therapeutic design strategies.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Molecular docking is a powerful tool used in drug discovery and structural biology for predicting the structures of ligand–receptor complexes. However, the accuracy of docking calculations can be ...limited by factors such as the neglect of protein reorganization in the scoring function; as a result, ligand screening can produce a high rate of false positive hits. Although absolute binding free energy methods still have difficulty in accurately rank-ordering binders, we believe that they can be fruitfully employed to distinguish binders from nonbinders and reduce the false positive rate. Here we study a set of ligands that dock favorably to a newly discovered, potentially allosteric site on the flap of HIV-1 protease. Fragment binding to this site stabilizes a closed form of protease, which could be exploited for the design of allosteric inhibitors. Twenty-three top-ranked protein–ligand complexes from AutoDock were subject to the free energy screening using two methods, the recently developed binding energy analysis method (BEDAM) and the standard double decoupling method (DDM). Free energy calculations correctly identified most of the false positives (≥83%) and recovered all the confirmed binders. The results show a gap averaging ≥3.7 kcal/mol, separating the binders and the false positives. We present a formula that decomposes the binding free energy into contributions from the receptor conformational macrostates, which provides insights into the roles of different binding modes. Our binding free energy component analysis further suggests that improving the treatment for the desolvation penalty associated with the unfulfilled polar groups could reduce the rate of false positive hits in docking. The current study demonstrates that the combination of docking with free energy methods can be very useful for more accurate ligand screening against valuable drug targets.
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IJS, KILJ, NUK, PNG, UL, UM
Seasonal and pandemic influenza viruses continue to be a leading global health concern. Emerging resistance to the current drugs and the variable efficacy of vaccines underscore the need for ...developing new flu drugs that will be broadly effective against wild-type and drug-resistant influenza strains. Here, we report the discovery and development of a class of inhibitors targeting the cap-snatching endonuclease activity of the viral polymerase. A high-resolution crystal form of pandemic 2009 H1N1 influenza polymerase acidic protein N-terminal endonuclease domain (PAN) was engineered and used for fragment screening leading to the identification of new chemical scaffolds binding to the PAN active site cleft. During the course of screening, binding of a third metal ion that is potentially relevant to endonuclease activity was detected in the active site cleft of PAN in the presence of a fragment. Using structure-based optimization, we developed a highly potent hydroxypyridinone series of compounds from a fragment hit that defines a new mode of chelation to the active site metal ions. A compound from the series demonstrating promising enzymatic inhibition in a fluorescence-based enzyme assay with an IC50 value of 11 nM was found to have an antiviral activity (EC50) of 11 μM against PR8 H1N1 influenza A in MDCK cells.
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IJS, KILJ, NUK, PNG, UL, UM, UPUK
HIV-1 reverse transcriptase (RT) undergoes a series of conformational changes during viral replication and is a central target for antiretroviral therapy. The intrinsic flexibility of RT can provide ...novel allosteric sites for inhibition. Crystals of RT that diffract X-rays to better than 2 Å resolution facilitated the probing of RT for new druggable sites using fragment screening by X-ray crystallography. A total of 775 fragments were grouped into 143 cocktails, which were soaked into crystals of RT in complex with the non-nucleoside drug rilpivirine (TMC278). Seven new sites were discovered, including the Incoming Nucleotide Binding, Knuckles, NNRTI Adjacent, and 399 sites, located in the polymerase region of RT, and the 428, RNase H Primer Grip Adjacent, and 507 sites, located in the RNase H region. Three of these sites (Knuckles, NNRTI Adjacent, and Incoming Nucleotide Binding) are inhibitory and provide opportunities for discovery of new anti-AIDS drugs.
We have identified novel HIV-1 capsid inhibitors targeting the PF74 binding site. Acting as the building block of the HIV-1 capsid core, the HIV-1 capsid protein plays an important role in the viral ...life cycle and is an attractive target for antiviral development. A structure-based virtual screening workflow for hit identification was employed, which includes docking 1.6 million commercially-available drug-like compounds from the ZINC database to the capsid dimer, followed by applying two absolute binding free energy (ABFE) filters on the 500 top-ranked molecules from docking. The first employs the Binding Energy Distribution Analysis Method (BEDAM) in implicit solvent. The top-ranked compounds are then refined using the Double Decoupling method in explicit solvent. Both docking and BEDAM refinement were carried out on the IBM World Community Grid as part of the FightAIDS@Home project. Using this virtual screening workflow, we identified 24 molecules with calculated binding free energies between − 6 and − 12 kcal/mol. We performed thermal shift assays on these molecules to examine their potential effects on the stability of HIV-1 capsid hexamer and found that two compounds, ZINC520357473 and ZINC4119064 increased the melting point of the latter by 14.8 °C and 33 °C, respectively. These results support the conclusion that the two ZINC compounds are primary hits targeting the capsid dimer interface. Our simulations also suggest that the two hit molecules may bind at the capsid dimer interface by occupying a new sub-pocket that has not been exploited by existing CA inhibitors. The possible causes for why other top-scored compounds suggested by ABFE filters failed to show measurable activity are discussed.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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