Machine learning models to predict ligand binding affinity for the orexin 1 receptor.

The orexin 1 receptor (OX1R) is a G-protein coupled receptor that regulates a variety of physiological processes through interactions with the neuropeptides orexin A and B. Selective OX1R antagonists exhibit therapeutic effects in preclinical models of several behavioral disorders, including drug seeking and overeating. However, currently there are no selective OX1R antagonists approved for clinical use, fueling demand for novel compounds that act at this target. In this study, we meticulously curated a dataset comprising over 1300 OX1R ligands using a stringent filter and criteria cascade. Subsequently, we developed highly predictive quantitative structure-activity relationship (QSAR) models employing the optimized hyper-parameters for the random forest machine learning algorithm and twelve 2D molecular descriptors selected by recursive feature elimination with a 5-fold cross-validation process. The predictive capacity of the QSAR model was further assessed using an external test set and enrichment study, confirming its high predictivity. The practical applicability of our final QSAR model was demonstrated through virtual screening of the DrugBank database. This revealed two FDA-approved drugs (isavuconazole and cabozantinib) as potential OX1R ligands, confirmed by radiolabeled OX1R binding assays. To our best knowledge, this study represents the first report of highly predictive QSAR models on a large comprehensive dataset of diverse OX1R ligands, which should prove useful for the discovery and design of new compounds targeting this receptor.

Clinical Care of Patients with Neurocognitive Disorders: A Qualitative Study of the Psychiatric Residency Training Experience.

OBJECTIVE: Few data describe how general psychiatry residencies prepare trainees to care for individuals with neurocognitive disorders (NCDs), despite increasing recognition of the need for psychiatrists to provide care for the growing numbers of patients with NCD. This study aims to identify training needs and approaches, as the resident experience is one important perspective that can be added to others, such as milestones developed by expert educators. METHODS: The authors conducted three focus groups of third- and fourth-year general adult psychiatry residency trainees from three different training programs in May and June of 2021. Focus groups consisted of three to eight unique participants per group. Qualitative data analysis techniques derived in grounded theory were utilized to identify themes. RESULTS: Four main themes emerged from the focus groups: unique challenges of NCD care, intrinsic rewards of working with families, perceived gaps in educational experiences, and limited comfort in future practice. CONCLUSIONS: Participants expressed that aspects of NCD care were fundamentally different than care for other mental health conditions encountered in psychiatry residency. They found the progressive nature of the disease to be particularly challenging, and they also expressed challenges with clinical interviews and establishing rapport with individuals with NCDs. However, working with families was especially rewarding. Regardless of training program, participants expressed a need for additional longitudinal and diversified training opportunities to prepare them for future practice in this area.

Recent advances in drug discovery efforts targeting the sigma 1 receptor system: Implications for novel medications designed to reduce excessive drug and food seeking.

Psychiatric disorders characterized by uncontrolled reward seeking, such as substance use disorders (SUDs), alcohol use disorder (AUD) and some eating disorders, impose a significant burden on individuals and society. Despite their high prevalence and substantial morbidity and mortality rates, treatment options for these disorders remain limited. Over the past two decades, there has been a gradual accumulation of evidence pointing to the sigma-1 receptor (S1R) system as a promising target for therapeutic interventions designed to treat these disorders. S1R is a chaperone protein that resides in the endoplasmic reticulum, but under certain conditions translocates to the plasma membrane. In the brain, S1Rs are expressed in several regions important for reward, and following translocation, they physically associate with several reward-related GPCRs, including dopamine receptors 1 and 2 (D1R and D2R). Psychostimulants, alcohol, as well as palatable foods, all alter expression of S1R in regions important for motivated behavior, and S1R antagonists generally decrease behavioral responses to these rewards. Recent advances in structural modeling have permitted the development of highly-selective S1R antagonists with favorable pharmacokinetic profiles, thus providing a therapeutic avenue for S1R-based medications. Here, we provide an up-to-date overview of work linking S1R with motivated behavior for drugs of abuse and food, as well as evidence supporting the clinical utility of S1R antagonists to reduce their excessive consumption. We also highlight potential challenges associated with targeting the S1R system, including the need for a more comprehensive understanding of the underlying neurobiology and careful consideration of the pharmacological properties of S1R-based drugs.

QSAR-Based Computational Approaches to Accelerate the Discovery of Sigma-2 Receptor (S2R) Ligands as Therapeutic Drugs.

S2R overexpression is associated with various forms of cancer as well as both neuropsychiatric disorders (e.g., schizophrenia) and neurodegenerative diseases (Alzheimer's disease: AD). In the present study, three ligand-based methods (QSAR modeling, pharmacophore mapping, and shape-based screening) were implemented to select putative S2R ligands from the DrugBank library comprising 2000+ entries. Four separate optimization algorithms (i.e., stepwise regression, Lasso, genetic algorithm (GA), and a customized extension of GA called GreedGene) were adapted to select descriptors for the QSAR models. The subsequent biological evaluation of selected compounds revealed that three FDA-approved drugs for unrelated therapeutic indications exhibited sub-1 uM binding affinity for S2R. In particular, the antidepressant drug nefazodone elicited a S2R binding affinity Ki = 140 nM. A total of 159 unique S2R ligands were retrieved from 16 publications for model building, validation, and testing. To our best knowledge, the present report represents the first case to develop comprehensive QSAR models sourced by pooling and curating a large assemblage of structurally diverse S2R ligands, which should prove useful for identifying new drug leads and predicting their S2R binding affinity prior to the resource-demanding tasks of chemical synthesis and biological evaluation.

Novel Sigma 1 Receptor Antagonists as Potential Therapeutics for Pain Management.

The sigma 1 receptor (S1R) is a molecular chaperone protein located in the endoplasmic reticulum and plasma membranes and has been shown to play important roles in various pathological disorders including pain and, as recently discovered, COVID-19. Employing structure- and QSAR-based drug design strategies, we rationally designed, synthesized, and biologically evaluated a series of novel triazole-based S1R antagonists. Compound 10 exhibited potent binding affinity for S1R, high selectivity over S2R and 87 other human targets, acceptable in vitro metabolic stability, slow clearance in liver microsomes, and excellent blood-brain barrier permeability in rats. Further in vivo studies in rats showed that 10 exhibited negligible acute toxicity in the rotarod test and statistically significant analgesic effects in the formalin test for acute inflammatory pain and paclitaxel-induced neuropathic pain models during cancer chemotherapy. These encouraging results promote further development of our triazole-based S1R antagonists as novel treatments for pain of different etiologies.

Identification of an irreversible PPARγ antagonist with potent anticancer activity.

Melanoma is responsible for most skin cancer deaths, and its incidence continues to rise year after year. Different treatment options have been developed for melanoma depending on the stage of the disease. Despite recent advances in immuno- and targeted therapies, advanced melanoma remains incurable and thus an urgent need persists for safe and more effective melanoma therapeutics. In this study, we demonstrate that a novel compound MM902 (3-(3-(bromomethyl)-5-(4-(tert-butyl) phenyl)-1H-1,2,4-triazol-1-yl) phenol) exhibited potent efficacies in inhibiting the growth of different cancer cells, and suppressed tumor growth in a mouse xenograft model of malignant melanoma. Beginning with MM902 instead of specific targets, computational similarity- and docking-based approaches were conducted to search for known anticancer drugs whose structural features match MM902 and whose pharmacological target would accommodate an irreversible inhibitor. Peroxisome proliferator-activated receptor (PPAR) was computationally identified as one of the pharmacological targets and confirmed by in vitro biochemical assays. MM902 was shown to bind to PPARγ in an irreversible mode of action and to function as a selective antagonist for PPARγ over PPARα and PPARδ. It is hoped that MM902 will serve as a valuable research probe to study the functions of PPARγ in tumorigenesis and other pathological processes.

Comprehensive 3D-QSAR Model Predicts Binding Affinity of Structurally Diverse Sigma 1 Receptor Ligands.

The Sigma 1 Receptor (S1R) has attracted intense interest as a pharmaceutical target for various therapeutic indications, including the treatment of neuropathic pain and the potentiation of opioid analgesia. Efforts by drug developers to rationally design S1R antagonists have been spurred recently by the 2016 publication of the high-resolution X-ray crystal structure of the ligand-bound human S1R. Until now, however, the absence in the published literature of a single, large-scale, and comprehensive quantitative structure-activity relationship (QSAR) model that encompasses a structurally diverse collection of S1R ligands has impaired rapid progress. To our best knowledge, the present study represents the first report of a statistically robust and highly predictive 3D-QSAR model (R2 = 0.92, Q2 = 0.62, Rpred2 = 0.81) based on the X-ray crystal structure of human S1R and constructed from a pooled compilation of 180 S1R antagonists that encompass five structurally diverse chemical families investigated using identical experimental protocols. Best practices, as recommended by the Organization for Economic Cooperation and Development (OECD: http://www.oecd.org/ ), were adopted for pooling data from disparate sources and for QSAR model development and both internal and external model validation. The practical utility of the final 3D-QSAR model was tested by virtual screening of the DrugBank database of FDA approved drugs supplemented by eight reported S1R antagonists. Among the top-ranked 40 DrugBank hits, four approved drugs which were previously unknown as S1R antagonists were tested using in vitro radiolabeled human S1R binding assays. Of these, two drugs (diphenhydramine and phenyltoloxamine) exhibited potent S1R binding affinity with Ki = 58 nM and 160 nM, respectively. As diphenhydramine is approved as an antiallergic, and phenyltoloxamine as an analgesic and sedative, each of these compounds represents a viable starting point for a drug discovery campaign aimed at the development of novel S1R antagonists for a wide range of therapeutic indications.

Virtual Screening and Experimental Testing of B1 Metallo-ß-lactamase Inhibitors.

The global rise of metallo-ß-lactamases (MBLs) is problematic due to their ability to inactivate most ß-lactam antibiotics. MBL inhibitors that could be coadministered with and restore the efficacy of ß-lactams are highly sought after. In this study, we employ virtual screening of candidate MBL inhibitors without thiols or carboxylates to avoid off-target effects using the Avalanche software package, followed by experimental validation of the selected compounds. As target enzymes, we chose the clinically relevant B1 MBLs NDM-1, IMP-1, and VIM-2. Among 32 compounds selected from an approximately 1.5 million compound library, 6 exhibited IC50 values less than 40 µM against NDM-1 and/or IMP-1. The most potent inhibitors of NDM-1, IMP-1, and VIM-2 had IC50 values of 19 ± 2, 14 ± 1, and 50 ± 20 µM, respectively. While chemically diverse, the most potent inhibitors all contain combinations of hydroxyl, ketone, ester, amide, or sulfonyl groups. Docking studies suggest that these electron-dense moieties are involved in Zn(II) coordination and interaction with protein residues. These novel scaffolds could serve as the basis for further development of MBL inhibitors. A procedure for renaming NDM-1 residues to conform to the class B ß-lactamase (BBL) numbering scheme is also included.

Small molecule inhibitors block Gas6-inducible TAM activation and tumorigenicity.

TAM receptors (Tyro-3, Axl, and Mertk) are a family of three homologous type I receptor tyrosine kinases that are implicated in several human malignancies. Overexpression of TAMs and their major ligand Growth arrest-specific factor 6 (Gas6) is associated with more aggressive staging of cancers, poorer predicted patient survival, acquired drug resistance and metastasis. Here we describe small molecule inhibitors (RU-301 and RU-302) that target the extracellular domain of Axl at the interface of the Ig-1 ectodomain of Axl and the Lg-1 of Gas6. These inhibitors effectively block Gas6-inducible Axl receptor activation with low micromolar IC50s in cell-based reporter assays, inhibit Gas6-inducible motility in Axl-expressing cell lines, and suppress H1299 lung cancer tumor growth in a mouse xenograft NOD-SCIDγ model. Furthermore, using homology models and biochemical verifications, we show that RU301 and 302 also inhibit Gas6 inducible activation of Mertk and Tyro3 suggesting they can act as pan-TAM inhibitors that block the interface between the TAM Ig1 ectodomain and the Gas6 Lg domain. Together, these observations establish that small molecules that bind to the interface between TAM Ig1 domain and Gas6 Lg1 domain can inhibit TAM activation, and support the further development of small molecule Gas6-TAM interaction inhibitors as a novel class of cancer therapeutics.

Niclosamide is a Negative Allosteric Modulator of Group I Metabotropic Glutamate Receptors: Implications for Neuropathic Pain.

PURPOSE: Novel therapeutics are greatly needed that target specific pathological receptors and pathways involved in Neuropathic Pain (NP). Extending our previous work published in this Journal on Group I metabotropic glutamate receptor (mGluR) modulators, we now investigate the therapeutic potential of niclosamide in modulating aberrant glutamate transmission in NP. METHOD: Calcium mobilization assays and cross-receptor selectivity experiments are conducted to characterize the pharmacological activity of niclosamide. A focused series of niclosamide analogues is then prepared to elucidate key structural determinants that emerged from computational molecular modeling analysis on drug-receptor interactions. Finally, niclosamide and a carbamate derivative are studied to assess their efficacy in an NP-evoked mechanical hyperalgesia model in rats. RESULTS: Niclosamide is a low-nanomolar allosteric antagonist of Group I mGluRs with high selectivity for Group I over homologous Group III mGluRs. The phenolic hydroxyl group of niclosamide forms a crucial hydrogen bond with mGluR1/5. Its bioactive coplanar conformation is further stabilized by the nitro substituent on the B ring and an intramolecular bond. Mechanical hyperalgesia in NP rats is reversed by niclosamide through three different dosing routes. CONCLUSION: To our knowledge, this is the first report of the salicylanilide class of compounds as potential treatments for NP.

Micellar and structural stability of nanoscale amphiphilic polymers: Implications for anti-atherosclerotic bioactivity.

Atherosclerosis, a leading cause of mortality in developed countries, is characterized by the buildup of oxidized low-density lipoprotein (oxLDL) within the vascular intima, unregulated oxLDL uptake by macrophages, and ensuing formation of arterial plaque. Amphiphilic polymers (AMPs) comprised of a branched hydrophobic domain and a hydrophilic poly(ethylene glycol) (PEG) tail have shown promising anti-atherogenic effects through direct inhibition of oxLDL uptake by macrophages. In this study, five AMPs with controlled variations were evaluated for their micellar and structural stability in the presence of serum and lipase, respectively, to develop underlying structure-atheroprotective activity relations. In parallel, molecular dynamics simulations were performed to explore the AMP conformational preferences within an aqueous environment. Notably, AMPs with ether linkages between the hydrophobic arms and sugar backbones demonstrated enhanced degradation stability and storage stability, and also elicited enhanced anti-atherogenic bioactivity. Additionally, AMPs with increased hydrophobicity elicited increased atheroprotective bioactivity in the presence of serum. These studies provide key insights for designing more serum-stable polymeric micelles as prospective cardiovascular nanotherapies.

Stepping into the omics era: Opportunities and challenges for biomaterials science and engineering.

The research paradigm in biomaterials science and engineering is evolving from using low-throughput and iterative experimental designs towards high-throughput experimental designs for materials optimization and the evaluation of materials properties. Computational science plays an important role in this transition. With the emergence of the omics approach in the biomaterials field, referred to as materiomics, high-throughput approaches hold the promise of tackling the complexity of materials and understanding correlations between material properties and their effects on complex biological systems. The intrinsic complexity of biological systems is an important factor that is often oversimplified when characterizing biological responses to materials and establishing property-activity relationships. Indeed, in vitro tests designed to predict in vivo performance of a given biomaterial are largely lacking as we are not able to capture the biological complexity of whole tissues in an in vitro model. In this opinion paper, we explain how we reached our opinion that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field. STATEMENT OF SIGNIFICANCE: In this opinion paper, we postulate that converging genomics and materiomics into a new field would enable a significant acceleration of the development of new and improved medical devices. The use of computational modeling to correlate high-throughput gene expression profiling with high throughput combinatorial material design strategies would add power to the analysis of biological effects induced by material properties. We believe that this extra layer of complexity on top of high-throughput material experimentation is necessary to tackle the biological complexity and further advance the biomaterials field.

Avalanche for shape and feature-based virtual screening with 3D alignment.

This report introduces a new ligand-based virtual screening tool called Avalanche that incorporates both shape- and feature-based comparison with three-dimensional (3D) alignment between the query molecule and test compounds residing in a chemical database. Avalanche proceeds in two steps. The first step is an extremely rapid shape/feature based comparison which is used to narrow the focus from potentially millions or billions of candidate molecules and conformations to a more manageable number that are then passed to the second step. The second step is a detailed yet still rapid 3D alignment of the remaining candidate conformations to the query conformation. Using the 3D alignment, these remaining candidate conformations are scored, re-ranked and presented to the user as the top hits for further visualization and evaluation. To provide further insight into the method, the results from two prospective virtual screens are presented which show the ability of Avalanche to identify hits from chemical databases that would likely be missed by common substructure-based or fingerprint-based search methods. The Avalanche method is extended to enable patent landscaping, i.e., structural refinements to improve the patentability of hits for deployment in drug discovery campaigns.

Elucidating the Role of Residue 67 in IMP-Type Metallo-ß-Lactamase Evolution.

Antibiotic resistance in bacteria is ever changing and adapting, as once-novel ß-lactam antibiotics are losing their efficacy, primarily due to the production of ß-lactamases. Metallo-ß-lactamases (MBLs) efficiently inactivate a broad range of ß-lactam antibiotics, including carbapenems, and are often coexpressed with other antibacterial resistance factors. The rapid dissemination of MBLs and lack of novel antibacterials pose an imminent threat to global health. In an effort to better counter these resistance-conferring ß-lactamases, an investigation of their natural evolution and resulting substrate specificity was employed. In this study, we elucidated the effects of different amino acid substitutions at position 67 in IMP-type MBLs on the ability to hydrolyze and confer resistance to a range of ß-lactam antibiotics. Wild-type ß-lactamases IMP-1 and IMP-10 and mutants IMP-1-V67A and IMP-1-V67I were characterized biophysically and biochemically, and MICs for Escherichia coli cells expressing these enzymes were determined. We found that all variants exhibited catalytic efficiencies (kcat/Km) equal to or higher than that of IMP-1 against all tested ß-lactams except penicillins, against which IMP-1 and IMP-1-V67I showed the highest kcat/Km values. The substrate-specific effects of the different amino acid substitutions at position 67 are discussed in light of their side chain structures and possible interactions with the substrates. Docking calculations were employed to investigate interactions between different side chains and an inhibitor used as a ß-lactam surrogate. The differences in binding affinities determined experimentally and computationally seem to be governed by hydrophobic interactions between residue 67 and the inhibitor and, by inference, the ß-lactam substrates.

Tartaric acid-based amphiphilic macromolecules with ether linkages exhibit enhanced repression of oxidized low density lipoprotein uptake.

Cardiovascular disease initiates with the atherogenic cascade of scavenger receptor- (SR-) mediated oxidized low-density lipoprotein (oxLDL) uptake. Resulting foam cell formation leads to lipid-rich lesions within arteries. We designed amphiphilic macromolecules (AMs) to inhibit these processes by competitively blocking oxLDL uptake via SRs, potentially arresting atherosclerotic development. In this study, we investigated the impact of replacing ester linkages with ether linkages in the AM hydrophobic domain. We hypothesized that ether linkages would impart flexibility for orientation to improve binding to SR binding pockets, enhancing anti-atherogenic activity. A series of tartaric acid-based AMs with varying hydrophobic chain lengths and conjugation chemistries were synthesized, characterized, and evaluated for bioactivity. 3-D conformations of AMs in aqueous conditions may have significant effects on anti-atherogenic potency and were simulated by molecular modeling. Notably, ether-linked AMs exhibited significantly higher levels of inhibition of oxLDL uptake than their corresponding ester analogues, indicating a dominant effect of linkage flexibility on pharmacological activity. The degradation stability was also enhanced for ether-linked AMs. These studies further suggested that alkyl chain length (i.e., relative hydrophobicity), conformation (i.e., orientation), and chemical stability play a critical role in modulating oxLDL uptake, and guide the design of innovative cardiovascular therapies.

Carbohydrate-derived amphiphilic macromolecules: a biophysical structural characterization and analysis of binding behaviors to model membranes.

The design and synthesis of enhanced membrane-intercalating biomaterials for drug delivery or vascular membrane targeting is currently challenged by the lack of screening and prediction tools. The present work demonstrates the generation of a Quantitative Structural Activity Relationship model (QSAR) to make a priori predictions. Amphiphilic macromolecules (AMs) "stealth lipids" built on aldaric and uronic acids frameworks attached to poly(ethylene glycol) (PEG) polymer tails were developed to form self-assembling micelles. In the present study, a defined set of novel AM structures were investigated in terms of their binding to lipid membrane bilayers using Quartz Crystal Microbalance with Dissipation (QCM-D) experiments coupled with computational coarse-grained molecular dynamics (CG MD) and all-atom MD (AA MD) simulations. The CG MD simulations capture the insertion dynamics of the AM lipophilic backbones into the lipid bilayer with the PEGylated tail directed into bulk water. QCM-D measurements with Voigt viscoelastic model analysis enabled the quantitation of the mass gain and rate of interaction between the AM and the lipid bilayer surface. Thus, this study yielded insights about variations in the functional activity of AM materials with minute compositional or stereochemical differences based on membrane binding, which has translational potential for transplanting these materials in vivo. More broadly, it demonstrates an integrated computational-experimental approach, which can offer a promising strategy for the in silico design and screening of therapeutic candidate materials.

Identification of Nitazoxanide as a Group I Metabotropic Glutamate Receptor Negative Modulator for the Treatment of Neuropathic Pain: An In Silico Drug Repositioning Study.

PURPOSE: Drug repositioning strategies were employed to explore new therapeutic indications for existing drugs that may exhibit dual negative mGluR1/5 modulating activities as potential treatments for neuropathic pain. METHOD: A customized in silico-in vitro-in vivo drug repositioning scheme was assembled and implemented to search available drug libraries for compounds with dual mGluR1/5 antagonistic activities, that were then evaluated using in vitro functional assays and, for validated hits, in an established animal model for neuropathic pain. RESULTS: Tizoxanide, the primary active metabolite of the FDA approved drug nitazoxanide, fit in silico pharmacophore models constructed for both mGluR1 and mGluR5. Subsequent calcium (Ca++) mobilization functional assays confirmed that tizoxanide exhibited appreciable antagonist activity for both mGluR1 and mGluR5 (IC50 = 1.8 µM and 1.2 µM, respectively). The in vivo efficacy of nitazoxanide administered by intraperitoneal injection was demonstrated in a rat model for neuropathic pain. CONCLUSION: The major aim of the present study was to demonstrate the utility of an in silico-in vitro-in vivo drug repositioning protocol to facilitate the repurposing of approved drugs for new therapeutic indications. As an example, this particular investigation successfully identified nitazoxanide and its metabolite tizoxanide as dual mGluR1/5 negative modulators. A key finding is the vital importance for drug screening libraries to include the structures of drug active metabolites, such as those emanating from prodrugs which are estimated to represent 5-7% of marketed drugs.

Polyester monomers lack ability to bind and activate both androgenic and estrogenic receptors as determined by in vitro and in silico methods.

The paper presents results from the screening of seven monomers used by Eastman Chemical to make various polymers. Ethylene glycol, diethylene glycol, polytetramethylene glycol, isophthalic acid, monosodium-5-sulfoisophthalic acid, 1,4-cyclohexanedicarboxylic acid, and dimethylcyclohexanedicarboxylate were screened for potential androgenicity or estrogenicity. The following studies were conducted: QSAR for binding to the AR and ER, in vitro Androgen Receptor Binding Assay, in vitro Estrogen Receptor Binding Assays (alpha and beta isoforms), in vitro Androgen Receptor Transactivation Assay in human cells, and in vitro Estrogen Receptor Transactivation Assay in human cells. None of the QSAR models predicted that any of the monomers possessed appreciable binding affinity for either AR or ER. Binding assays showed no evidence of interaction with either the AR or the alpha or beta ER receptors. Similarly, the AR and ER transactivation assays were negative. Moreover, six of the seven monomers have been subjected to 13-week and developmental toxicity studies in rats with no androgen- or estrogen-related effects being noted. Given the negative results of the in vitro screening assays (except PMG which demonstrated cytotoxicity) as well as available repeated dose and developmental and reproductive studies, the data suggest that none of the monomers tested exhibit androgenic or estrogenic hazards.

Novel virtual screening approach for the discovery of human tyrosinase inhibitors.

Tyrosinase is the key enzyme involved in the human pigmentation process, as well as the undesired browning of fruits and vegetables. Compounds inhibiting tyrosinase catalytic activity are an important class of cosmetic and dermatological agents which show high potential as depigmentation agents used for skin lightening. The multi-step protocol employed for the identification of novel tyrosinase inhibitors incorporated the Shape Signatures computational algorithm for rapid screening of chemical libraries. This algorithm converts the size and shape of a molecule, as well its surface charge distribution and other bio-relevant properties, into compact histograms (signatures) that lend themselves to rapid comparison between molecules. Shape Signatures excels at scaffold hopping across different chemical families, which enables identification of new actives whose molecular structure is distinct from other known actives. Using this approach, we identified a novel class of depigmentation agents that demonstrated promise for skin lightening product development.

Fragment-based Shape Signatures: a new tool for virtual screening and drug discovery.

Since its introduction in 2003, the Shape Signatures method has been successfully applied in a number of drug design projects. Because it uses a ray-tracing approach to directly measure molecular shape and properties (as opposed to relying on chemical structure), it excels at scaffold hopping, and is extraordinarily easy to use. Despite its advantages, a significant drawback of the method has hampered its application to certain classes of problems; namely, when the chemical structures considered are large and contain heterogeneous ring-systems, the method produces descriptors that tend to merely measure the overall size of the molecule, and begin to lose selective power. To remedy this, the approach has been reformulated to automatically decompose compounds into fragments using ring systems as anchors, and to likewise partition the ray-trace in accordance with the fragment assignments. Subsequently, descriptors are generated that are fragment-based, and query and target molecules are compared by mapping query fragments onto target fragments in all ways consistent with the underlying chemical connectivity. This has proven to greatly extend the selective power of the method, while maintaining the ease of use and scaffold-hopping capabilities that characterized the original implementation. In this work, we provide a full conceptual description of the next generation Shape Signatures, and we underline the advantages of the method by discussing its practical applications to ligand-based virtual screening. The new approach can also be applied in receptor-based mode, where protein-binding sites (partitioned into subsites) can be matched against the new fragment-based Shape Signatures descriptors of library compounds.