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Angewandte Chemie (International Ed. in... Nov 2020A significant amount of attention has been given to the design and synthesis of co-crystals by both industry and academia because of its potential to change a molecule's...
A significant amount of attention has been given to the design and synthesis of co-crystals by both industry and academia because of its potential to change a molecule's physicochemical properties. Yet, difficulties arise when searching for adequate combinations of molecules (or coformers) to form co-crystals, hampering the efficient exploration of the target's solid-state landscape. This paper reports on the application of a data-driven co-crystal prediction method based on two types of artificial neural network models and co-crystal data present in the Cambridge Structural Database. The models accept pairs of coformers and predict whether a co-crystal is likely to form. By combining the output of multiple models of both types, our approach shows to have excellent performance on the proposed co-crystal training and validation sets, and has an estimated accuracy of 80 % for molecules for which previous co-crystallization data is unavailable.
PubMed: 32797658
DOI: 10.1002/anie.202009467 -
Philosophical Transactions. Series A,... Mar 2017Feedback traps are tools for trapping and manipulating single charged objects, such as molecules in solution. An alternative to optical tweezers and other... (Review)
Review
Feedback traps are tools for trapping and manipulating single charged objects, such as molecules in solution. An alternative to optical tweezers and other single-molecule techniques, they use feedback to counteract the Brownian motion of a molecule of interest. The trap first acquires information about a molecule's position and then applies an electric feedback force to move the molecule. Since electric forces are stronger than optical forces at small scales, feedback traps are the best way to trap single molecules without 'touching' them (e.g. by putting them in a small box or attaching them to a tether). Feedback traps can do more than trap molecules: they can also subject a target object to forces that are calculated to be the gradient of a desired potential function U(x). If the feedback loop is fast enough, it creates a virtual potential whose dynamics will be very close to those of a particle in an actual potential U(x). But because the dynamics are entirely a result of the feedback loop-absent the feedback, there is only an object diffusing in a fluid-we are free to specify and then manipulate in time an arbitrary potential U(x,t). Here, we review recent applications of feedback traps to studies on the fundamental connections between information and thermodynamics, a topic where feedback plays an even more fundamental role. We discuss how recursive maximum-likelihood techniques allow continuous calibration, to compensate for drifts in experiments that last for days. We consider ways to estimate work and heat, using them to measure fluctuating energies to a precision of ±0.03 kT over these long experiments. Finally, we compare work and heat measurements of the costs of information erasure, the Landauer limit of kT ln 2 per bit of information erased. We argue that, when you want to know the average heat transferred to a bath in a long protocol, you should measure instead the average work and then infer the heat using the first law of thermodynamics.This article is part of the themed issue 'Horizons of cybernetical physics'.
PubMed: 28115614
DOI: 10.1098/rsta.2016.0217 -
Pharmaceutical Research Nov 2016Over the past decade we have witnessed the increasing sophistication of machine learning algorithms applied in daily use from internet searches, voice recognition,... (Review)
Review
Over the past decade we have witnessed the increasing sophistication of machine learning algorithms applied in daily use from internet searches, voice recognition, social network software to machine vision software in cameras, phones, robots and self-driving cars. Pharmaceutical research has also seen its fair share of machine learning developments. For example, applying such methods to mine the growing datasets that are created in drug discovery not only enables us to learn from the past but to predict a molecule's properties and behavior in future. The latest machine learning algorithm garnering significant attention is deep learning, which is an artificial neural network with multiple hidden layers. Publications over the last 3 years suggest that this algorithm may have advantages over previous machine learning methods and offer a slight but discernable edge in predictive performance. The time has come for a balanced review of this technique but also to apply machine learning methods such as deep learning across a wider array of endpoints relevant to pharmaceutical research for which the datasets are growing such as physicochemical property prediction, formulation prediction, absorption, distribution, metabolism, excretion and toxicity (ADME/Tox), target prediction and skin permeation, etc. We also show that there are many potential applications of deep learning beyond cheminformatics. It will be important to perform prospective testing (which has been carried out rarely to date) in order to convince skeptics that there will be benefits from investing in this technique.
Topics: Algorithms; Drug Discovery; Machine Learning; Neural Networks, Computer; Pharmaceutical Research; Software
PubMed: 27599991
DOI: 10.1007/s11095-016-2029-7 -
Frontiers in Oncology 2019Glioblastoma multiforme (GBM) is the most common and aggressive malignant primary brain tumour in humans and has a very poor prognosis. The existing treatments have had... (Review)
Review
Glioblastoma multiforme (GBM) is the most common and aggressive malignant primary brain tumour in humans and has a very poor prognosis. The existing treatments have had limited success in increasing overall survival. Thus, identifying and understanding the key molecule(s) responsible for the malignant phenotype of GBM will yield new potential therapeutic targets. The treatment of brain tumours faces unique challenges, including the presence of the blood brain barrier (BBB), which limits the concentration of drugs that can reach the site of the tumour. Nevertheless, several promising treatments have been shown to cross the BBB and have shown promising pre-clinical results. This review will outline the status of several of these promising targeted therapies.
PubMed: 31616641
DOI: 10.3389/fonc.2019.00963 -
Acta Tropica Jul 2021Podoconiosis is a non-filarial and non-communicable disease leading to lymphedema of the lower limbs. Worldwide, 4 million individuals live with podoconiosis, which is... (Review)
Review
Podoconiosis is a non-filarial and non-communicable disease leading to lymphedema of the lower limbs. Worldwide, 4 million individuals live with podoconiosis, which is accompanied by disability and painful intermittent acute inflammatory episodes that attribute to significant disability adjusted life years (DALYs). Different risk factors like contact with volcanic red clay soil, high altitude (above 1000 m), high seasonal rainfall (above 1000 mm/year) and occupation (e.g., subsistence farmer) are associated with the risk of podoconiosis. Although podoconiosis was described to be endemic in 32 countries in Africa, parts of Latin America and South East Asia, knowledge about related genetics, pathophysiology, immunology and especially the causing molecule(s) in the soil remain uncertain. Thus, podoconiosis can be considered as one of the most neglected diseases. This review provides an overview about this non-filarial related geochemical disease and aim to present perspectives and future directions that might be important for better understanding of the disease, prospect for point-of-care diagnosis, achieving protection and developing novel treatment strategies.
Topics: Elephantiasis; Humans; Risk Factors; Soil
PubMed: 33839086
DOI: 10.1016/j.actatropica.2021.105918 -
Biochemistry Apr 2020Messenger RNA degradation is an important component of overall gene expression. During the final step of eukaryotic mRNA degradation, exoribonuclease 1 (Xrn1) carries...
Messenger RNA degradation is an important component of overall gene expression. During the final step of eukaryotic mRNA degradation, exoribonuclease 1 (Xrn1) carries out 5' → 3' processive, hydrolytic degradation of RNA molecules using divalent metal ion catalysis. To initiate studies of the 5' → 3' RNA decay machinery in our lab, we expressed a C-terminally truncated version of Xrn1 and explored its enzymology using a second-generation, time-resolved fluorescence RNA degradation assay. Using this system, we quantitatively explored Xrn1's preference for 5'-monophosphorylated RNA substrates, its pH dependence, and the importance of active site mutations in the molecule's conserved catalytic core. Furthermore, we explore Xrn1's preference for RNAs containing a 5' single-stranded region both in an intermolecular hairpin structure and in an RNA-DNA hybrid duplex system. These results both expand and solidify our understanding of Xrn1, a centrally important enzyme whose biochemical properties have implications in numerous RNA degradation and processing pathways.
Topics: Exoribonucleases; Hydrogen-Ion Concentration; Models, Molecular; Saccharomyces cerevisiae; Saccharomyces cerevisiae Proteins
PubMed: 32251580
DOI: 10.1021/acs.biochem.9b01035 -
Frontiers in Pharmacology 2015The use of herbal therapies for treatment and management of cardiovascular diseases (CVDs) is increasing. Plants contain a bounty of phytochemicals that have proven to... (Review)
Review
The use of herbal therapies for treatment and management of cardiovascular diseases (CVDs) is increasing. Plants contain a bounty of phytochemicals that have proven to be protective by reducing the risk of various ailments and diseases. Indeed, accumulating literature provides the scientific evidence and hence reason d'etre for the application of herbal therapy in relation to CVDs. Slowly, but absolutely, herbal remedies are being entrenched into evidence-based medical practice. This is partly due to the supporting clinical trials and epidemiological studies. The rationale for this expanding interest and use of plant based treatments being that a significant proportion of hypertensive patients do not respond to Modern therapeutic medication. Other elements to this equation are the cost of medication, side-effects, accessibility, and availability of drugs. Therefore, we believe it is pertinent to review the literature on the beneficial effects of herbs and their isolated compounds as medication for treatment of hypertension, a prevalent risk factor for CVDs. Our search utilized the PubMed and ScienceDirect databases, and the criterion for inclusion was based on the following keywords and phrases: hypertension, high blood pressure, herbal medicine, complementary and alternative medicine (CAM), nitric oxide, vascular smooth muscle cell (VSMC) proliferation, hydrogen sulfide, nuclear factor kappa-B, oxidative stress, and epigenetics/epigenomics. Each of the aforementioned keywords was co-joined with herb in question, and where possible with its constituent molecule(s). In this first of a two-part review, we provide a brief introduction of hypertension, followed by a discussion of the molecular and cellular mechanisms. We then present and discuss the plants that are most commonly used in the treatment and management of hypertension.
PubMed: 26834637
DOI: 10.3389/fphar.2015.00323 -
Journal of Natural Products Jun 2023Fungal metabolites represent an underutilized resource in the development of novel anticancer drugs. This review will focus on the promising fungal nephrotoxin... (Review)
Review
Fungal metabolites represent an underutilized resource in the development of novel anticancer drugs. This review will focus on the promising fungal nephrotoxin orellanine, found in mushrooms including (Fools webcap). Emphasis will be placed on its historical significance, structural features, and associated toxicomechanics. Chromatographic methods for analysis of the compound and its metabolites, its synthesis, and chemotherapeutic potential are also discussed. Although orellanine's exceptional selectivity for proximal tubular cells is well documented, the mechanics of its toxicity in kidney tissue remains disputed. Here, the most commonly proposed hypotheses are detailed in the context of the molecule's structure, the symptoms seen following ingestion, and its characteristic prolonged latency period. Chromatographic analysis of orellanine and its related substances remains challenging, while biological evaluation of the compound is complicated by uncertainty regarding the role of active metabolites. This has limited efforts to structurally refine the molecule; despite numerous established methods for its synthesis, there is minimal published material on how orellanine's structure might be optimized for therapeutic use. Despite these obstacles, orellanine has generated promising data in preclinical studies of metastatic clear cell renal cell carcinoma, leading to the early 2022 announcement of phase I/II trials in humans.
Topics: Humans; Mycotoxins; Neoplasms; 2,2'-Dipyridyl; Agaricales
PubMed: 37308446
DOI: 10.1021/acs.jnatprod.2c01068 -
The Journal of Physical Chemistry. A Mar 2023Charge migration (CM) is a coherent attosecond process that involves the movement of localized holes across a molecule. To determine the relationship between a...
Charge migration (CM) is a coherent attosecond process that involves the movement of localized holes across a molecule. To determine the relationship between a molecule's structure and the CM dynamics it exhibits, we perform systematic studies of para-functionalized bromobenzene molecules (X-CH-R) using real-time time-dependent density functional theory. We initiate valence-electron dynamics by emulating rapid strong-field ionization leading to a localized hole on the bromine atom. The resulting CM, which takes on the order of 1 fs, occurs via an X localized → CH delocalized → R localized mechanism. Interestingly, the hole contrast on the acceptor functional group increases with increasing electron-donating strength. This trend is well-described by the Hammett σ value of the group, which is a commonly used metric for quantifying the effect of functionalization on the chemical reactivity of benzene derivatives. These results suggest that simple attochemistry principles and a density-based picture can be used to predict and understand CM.
PubMed: 36791088
DOI: 10.1021/acs.jpca.3c00568