Probabilistic Approach to Generating MPOs and Its Application as a Scoring Function for CNS Drugs.
ABSTRACT: Multiparameter optimization (MPO) scoring functions are popular tools for providing guidance on how to design desired molecules in medicinal chemistry. The utility of a new probabilistic MPO (pMPO) scoring function method and its application as a scoring function for CNS drugs are described in this letter. In this new approach, a minimal number of statistically determined empirical boundaries is combined with the probability distribution of the desired molecules to define desirability functions. This approach attempts to minimize the number of parameters that define MPO scores while maintaining a high level of predictive power. Results obtained from a test-set of orally approved drugs show that the pMPO approach described here can be used to separate desired molecules from undesired ones with accuracy comparable to a Bayesian model with the advantage of better human interpretability. The application of this pMPO approach for blood-brain barrier penetrant drugs is also described.
Project description:The interplay among commonly used physicochemical properties in drug design was examined and utilized to create a prospective design tool focused on the alignment of key druglike attributes. Using a set of six physicochemical parameters ((a) lipophilicity, calculated partition coefficient (ClogP); (b) calculated distribution coefficient at pH = 7.4 (ClogD); (c) molecular weight (MW); (d) topological polar surface area (TPSA); (e) number of hydrogen bond donors (HBD); (f) most basic center (pK(a))), a druglikeness central nervous system multiparameter optimization (CNS MPO) algorithm was built and applied to a set of marketed CNS drugs (N = 119) and Pfizer CNS candidates (N = 108), as well as to a large diversity set of Pfizer proprietary compounds (N = 11?303). The novel CNS MPO algorithm showed that 74% of marketed CNS drugs displayed a high CNS MPO score (MPO desirability score ? 4, using a scale of 0-6), in comparison to 60% of the Pfizer CNS candidates. This analysis suggests that this algorithm could potentially be used to identify compounds with a higher probability of successfully testing hypotheses in the clinic. In addition, a relationship between an increasing CNS MPO score and alignment of key in vitro attributes of drug discovery (favorable permeability, P-glycoprotein (P-gp) efflux, metabolic stability, and safety) was seen in the marketed CNS drug set, the Pfizer candidate set, and the Pfizer proprietary diversity set. The CNS MPO scoring function offers advantages over hard cutoffs or utilization of single parameters to optimize structure-activity relationships (SAR) by expanding medicinal chemistry design space through a holistic assessment approach. Based on six physicochemical properties commonly used by medicinal chemists, the CNS MPO function may be used prospectively at the design stage to accelerate the identification of compounds with increased probability of success.
Project description:The ability to activate drugs only at desired locations avoiding systemic immunosuppression and other dose limiting toxicities is highly desirable. Here we present a new approach, named local drug activation, that uses bioorthogonal chemistry to concentrate and activate systemic small molecules at a location of choice. This method is independent of endogenous cellular or environmental markers and only depends on the presence of a preimplanted biomaterial near a desired site (e.g., tumor). We demonstrate the clear therapeutic benefit with minimal side effects of this approach in mice over systemic therapy using a doxorubicin pro-drug against xenograft tumors of a type of soft tissue sarcoma (HT1080).
Project description:Understanding how individuals revise their political beliefs has important implications for society. In a preregistered study (N = 900), we experimentally separated the predictions of 2 leading theories of human belief revision-desirability bias and confirmation bias-in the context of the 2016 U.S. presidential election. Participants indicated who they desired to win, and who they believed would win, the election. Following confrontation with evidence that was either consistent or inconsistent with their desires or beliefs, they again indicated who they believed would win. We observed a robust desirability bias-individuals updated their beliefs more if the evidence was consistent (vs. inconsistent) with their desired outcome. This bias was independent of whether the evidence was consistent or inconsistent with their prior beliefs. In contrast, we found limited evidence of an independent confirmation bias in belief updating. These results have implications for the relevant psychological theories and for political belief revision in practice. (PsycINFO Database Record
Project description:Myeloperoxidase (MPO) has paradoxically been found to be able to both activate matrix metalloproteinases (MMPs) as well as inhibit MMPs. However, these regulatory effects have not yet been observed in vivo, and it is unclear which pathway is relevant in vivo. We aim to track MPO regulation of MMP activity in living animals in neuroinflammation. Mice induced with experimental autoimmune encephalomyelitis (EAE), a mouse model of neuroinflammation and multiple sclerosis, were treated with either the MPO-specific inhibitor 4-aminobenzoic acid hydrazide or saline as control. Mice underwent concurrent magnetic resonance imaging (MRI) with the MPO-specific molecular imaging agent MPO-Gd and fluorescence molecular tomography (FMT) with the MMP-targeting agent MMPsense on day 12 after induction. Biochemical and histopathological correlations were performed. Utilizing concurrent MRI and FMT imaging, we found reduced MMP activity in the brain with MPO inhibition, demonstrating MPO activity positively regulates MMP activity in vivo. In vivo MMPSense activation and MMP-9 activity correlated with MPO-Gd+ lesion volume and disease severity. This was corroborated by in vitro assays and histopathological analyses that showed MMP activity and MMP-9+ cells correlated with MPO activity and MPO+ cells. In conclusion, multimodal molecular imaging demonstrates for the first time MPO regulation of MMP activity in living animals. This approach could serve as a model to study the interactions of other biologically interesting molecules in living organisms.
Project description:Most small molecule drugs interact with unintended, often unknown, biological targets and these off-target interactions may lead to both preclinical and clinical toxic events. Undesired off-target interactions are often not detected using current drug discovery assays, such as experimental polypharmacological screens. Thus, improvement in the early identification of off-target interactions represents an opportunity to reduce safety-related attrition rates during preclinical and clinical development. In order to better identify potential off-target interactions that could be linked to predictable safety issues, a novel computational approach to predict safety-relevant interactions currently not covered was designed and evaluated. These analyses, termed Off-Target Safety Assessment (OTSA), cover more than 7,000 targets (~35% of the proteome) and > 2,46,704 preclinical and clinical alerts (as of January 20, 2019). The approach described herein exploits a highly curated training set of >1 million compounds (tracking >20 million compound-structure activity relationship/SAR data points) with known <i>in vitro</i> activities derived from patents, journals, and publicly available databases. This computational process was used to predict both the primary and secondary pharmacological activities for a selection of 857 diverse small molecule drugs for which extensive secondary pharmacology data are readily available (456 discontinued and 401 FDA approved). The OTSA process predicted a total of 7,990 interactions for these 857 molecules. Of these, 3,923 and 4,067 possible high-scoring interactions were predicted for the discontinued and approved drugs, respectively, translating to an average of 9.3 interactions per drug. The OTSA process correctly identified the known pharmacological targets for >70% of these drugs, but also predicted a significant number of off-targets that may provide additional insight into observed <i>in vivo</i> effects. About 51.5% (2,025) and 22% (900) of these predicted high-scoring interactions have not previously been reported for the discontinued and approved drugs, respectively, and these may have a potential for repurposing efforts. Moreover, for both drug categories, higher promiscuity was observed for compounds with a MW range of 300 to 500, TPSA of ~200, and clogP ?7. This computation also revealed significantly lower promiscuity (i.e., number of confirmed off-targets) for compounds with MW > 700 and MW<200 for both categories. In addition, 15 internal small molecules with known off-target interactions were evaluated. For these compounds, the OTSA framework not only captured about 56.8% of <i>in vitro</i> confirmed off-target interactions, but also identified the right pharmacological targets for 14 compounds as one of the top scoring targets. In conclusion, the OTSA process demonstrates good predictive performance characteristics and represents an additional tool with utility during the lead optimization stage of the drug discovery process. Additionally, the computed physiochemical properties such as clogP (i.e., lipophilicity), molecular weight, pKa and logS (i.e., solubility) were found to be statistically different between the approved and discontinued drugs, but the internal compounds were close to the approved drugs space in most part.
Project description:High-density lipoprotein (HDL) has protective effects against the development of atherosclerosis; these effects include reverse cholesterol transport, antioxidant ability, and anti-inflammation. Myeloperoxidase (MPO) secreted by macrophages in atherosclerotic lesions generates tyrosyl radicals in apolipoprotein A-I (apoA-I) molecules, inducing the formation of apoA-I/apoA-II heterodimers through the tyrosine-tyrosine bond in HDL. Functional characterization of HDL oxidized by MPO could provide useful information about the significance of apoA-I/apoA-II heterodimers measurement. We investigated the effects of MPO-induced oxidation on the antiatherogenic functions of HDL as described above. The antioxidant ability of HDL, estimated as the effect on LDL oxidation induced by copper sulfate, was not significantly affected after MPO oxidation. HDL reduced THP-1 monocyte migration by suppressing the stimulation of human umbilical vein endothelial cells induced by lipopolysaccharide (LPS). MPO-oxidized HDL also showed inhibition of THP-1 chemotaxis, but the extent of inhibition was significantly attenuated compared to intact HDL. MPO treatment did not affect the cholesterol efflux capacity of HDL from [(3)H]-cholesterol-laden macrophages derived from THP-1 cells. The principal effect of MPO oxidation on the antiatherogenic potential of HDL would be the reduction of anti-inflammatory ability, suggesting that measurement of apoA-I/apoA-II heterodimers might be useful to estimate anti-inflammatory ability of HDL.
Project description:Fluorescence lifetime imaging microscopy (FLIM) measures fluorescence decay rate at every pixel of an image. FLIM can separate probes of the same color but different fluorescence lifetimes (FL), thus it is a promising approach for multiparameter imaging. However, available GFP-like fluorescent proteins (FP) possess a narrow range of FLs (commonly, 2.3-3.5?ns) which limits their applicability for multiparameter FLIM. Here we report a new FP probe showing both subnanosecond fluorescence lifetime and exceptional fluorescence brightness (80% of EGFP). To design this probe we applied semi-rational amino acid substitutions selection. Critical positions (Thr65, Tyr145, Phe165) were altered based on previously reported effect on FL or excited state electron transfer. The resulting EGFP triple mutant, BrUSLEE (Bright Ultimately Short Lifetime Enhanced Emitter), allows for both reliable detection of the probe and recording FL signal clearly distinguishable from that of the spectrally similar commonly used GFPs. We demonstrated high performance of this probe in multiparameter FLIM experiment. We suggest that amino acid substitutions described here lead to a significant shift in radiative and non-radiative excited state processes equilibrium.
Project description:Antibodies are a highly successful class of biological drugs, with over 50 such molecules approved for therapeutic use and hundreds more currently in clinical development. Improvements in technology for the discovery and optimization of high-potency antibodies have greatly increased the chances for finding binding molecules with desired biological properties; however, achieving drug-like properties at the same time is an additional requirement that is receiving increased attention. In this work, we attempt to quantify the historical limits of acceptability for multiple biophysical metrics of "developability." Amino acid sequences from 137 antibodies in advanced clinical stages, including 48 approved for therapeutic use, were collected and used to construct isotype-matched IgG1 antibodies, which were then expressed in mammalian cells. The resulting material for each source antibody was evaluated in a dozen biophysical property assays. The distributions of the observed metrics are used to empirically define boundaries of drug-like behavior that can represent practical guidelines for future antibody drug candidates.
Project description:Constructive machine learning aims to create examples from its learned domain which are likely to exhibit similar properties. Here, a recurrent neural network was trained with the chemical structures of known cell-migration modulators. This machine learning model was used to generate new molecules that mimic the training compounds. Two top-scoring designs were synthesized, and tested for functional activity in a phenotypic spheroid cell migration assay. These computationally generated small molecules significantly increased the migration of medulloblastoma cells. The results further corroborate the applicability of constructive machine learning to the de novo design of druglike molecules with desired properties.
Project description:Aberrant WNT signaling underlies cancerous transformation and growth in many tissues, such as the colon, breast, liver, and others. Downregulation of the WNT pathway is a desired mode of development of targeted therapies against these cancers. Despite the urgent need, no WNT signaling-directed drugs currently exist, and only very few candidates have reached early phase clinical trials. Among different strategies to develop WNT-targeting anti-cancer therapies, repositioning of existing drugs previously approved for other diseases is a promising approach. Nonsteroidal anti-inflammatory drugs like aspirin, the anti-leprotic clofazimine, and the anti-trypanosomal suramin are among examples of drugs having recently revealed WNT-targeting activities. In total, 16 human-use drug compounds have been found to be working through the WNT pathway and show promise for their prospective repositioning against various cancers. Advances, hurdles, and prospects of developing these molecules as potential drugs against WNT-dependent cancers, as well as approaches for discovering new ones for repositioning, are the foci of the current review.