scholarly journals A gyógyszerkutatás új irányzatai: hatékonyság és biztonságosság

2021 ◽  
Vol 2 (2) ◽  
pp. 177-183
Author(s):  
András Kotschy

Összefoglaló. A betegségek mögött meghúzódó biokémiai, sejtbiológiai változások molekuláris szintű megértése a korszerű gyógyszerkutatás alapját képezi. A kiválasztott biológiai célpont, leggyakrabban egy fehérje, működésének gátlásától vagy fokozásától azt reméljük, hogy elősegíti a gyógyulást. A hagyományos gyógyszerkutatási megközelítések molekuláris alapját a kiválasztott fehérjével való közvetlen kölcsönhatás jelentette. Ugyanakkor a sejten belüli molekuláris biológiai folyamatok részletesebb megértése több új megközelítést nyitott a gyógyszerkutatás számára. A közlemény ezeket a gyógyszerkutatási irányzatokat mutatja be, külön kitérve biztonságosságukra. Summary. Human diseases originate from and are accompanied by changes in the biochemistry of cells. The molecular level understanding of these deviations from normal functioning is key to the curing of the diseases, therefore a principal objective of drug discovery. The key-lock principle postulated by Emil Fischer serves well the understanding of most enzymatic processes and has been helping researchers both in academia and industry to discover new drugs. The binding of a small molecule to the target protein and inhibiting or activating its function is the basis for the efficient functioning of a long list of current drugs. Sometimes the desired biological effect comes from the selective action on a single protein, in other instances it is the combined effect on the working of several proteins. The appropriate selectivity profile is key to the safety and efficiency of the drug in both cases. The completion of the Human Genome Project, in parallel with a significant improvement in the performance of the analytical instrumentation, increased our molecular and systemic level understanding of diseases immensely. Analysis of the differences between healthy and diseased cells and tissues led to the identification of new targets, a lot of which are not classical enzymes but proteins exerting their effect through molecular interactions with other proteins or nucleic acids. Although these proteins were considered undruggable some decades ago, their disease modifying potential led to the discovery of new approaches and modalities to target them. The inhibition of protein-protein interactions, for example, requires the selective targeting of hydrophobic surfaces, sometimes with very high affinity. Drug candidates acting through this molecular mechanism are typically beyond the size of classical drugs that might complicate their development. Besides interacting directly with the protein of interest we might also impact its working through manipulating its quantity within the cell. Interference with the proteasomal degradation of cellular proteins, blocking its working, or hijacking it to selectively increase the degradation of our protein of choice are promising new modalities that are transitioning from research into clinical practice. Alternatively, one might also interfere with the transcriptional machinery. Selective blocking of the messenger RNA responsible for carrying the sequence information of the targeted protein by using so called antisense oligonucleotides, small interfering RNAs, or micro RNAs can result in a decreased synthesis of the protein. Appropriately designed oligonucleotides can also enhance protein synthesis or lead to an alteration of the sequence to synthesize for a given protein. Finally, we might also target the epigenetic regulatory machinery, which is in charge of unpacking the DNA double helix from its storage form and making it available for transcription. This interference typically leads to a more complex change, the parallel modulation of the level of several proteins at the same time.

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Kanchan Jha ◽  
Sriparna Saha

Abstract Protein is the primary building block of living organisms. It interacts with other proteins and is then involved in various biological processes. Protein–protein interactions (PPIs) help in predicting and hence help in understanding the functionality of the proteins, causes and growth of diseases, and designing new drugs. However, there is a vast gap between the available protein sequences and the identification of protein–protein interactions. To bridge this gap, researchers proposed several computational methods to reveal the interactions between proteins. These methods merely depend on sequence-based information of proteins. With the advancement of technology, different types of information related to proteins are available such as 3D structure information. Nowadays, deep learning techniques are adopted successfully in various domains, including bioinformatics. So, current work focuses on the utilization of different modalities, such as 3D structures and sequence-based information of proteins, and deep learning algorithms to predict PPIs. The proposed approach is divided into several phases. We first get several illustrations of proteins using their 3D coordinates information, and three attributes, such as hydropathy index, isoelectric point, and charge of amino acids. Amino acids are the building blocks of proteins. A pre-trained ResNet50 model, a subclass of a convolutional neural network, is utilized to extract features from these representations of proteins. Autocovariance and conjoint triad are two widely used sequence-based methods to encode proteins, which are used here as another modality of protein sequences. A stacked autoencoder is utilized to get the compact form of sequence-based information. Finally, the features obtained from different modalities are concatenated in pairs and fed into the classifier to predict labels for protein pairs. We have experimented on the human PPIs dataset and Saccharomyces cerevisiae PPIs dataset and compared our results with the state-of-the-art deep-learning-based classifiers. The results achieved by the proposed method are superior to those obtained by the existing methods. Extensive experimentations on different datasets indicate that our approach to learning and combining features from two different modalities is useful in PPI prediction.


2021 ◽  
Author(s):  
Andreas Adam Greifenstein ◽  
SoYoung Jo ◽  
Holger Bierhoff

Abstract The genomes of complex eukaryotes largely contain non-protein-coding DNA, which is pervasively transcribed into a plethora of non-coding RNAs (ncRNAs). The functional importance of many of these ncRNAs has been investigated in the last two decades, revealing their crucial and multifaceted roles in chromatin regulation. A common mode of action of ncRNAs is the recruitment of chromatin modifiers to specific regions in the genome. Whereas many ncRNA–protein interactions have been characterised in detail, binding of ncRNAs to their DNA target sites is much less understood. Recently developed RNA-centric methods have mapped the genome-wide distribution of ncRNAs, however, how ncRNAs achieve locus-specificity remains mainly unresolved. In terms of direct RNA–DNA interactions, two kinds of triple-stranded structures can be formed: R-loops consisting of an RNA:DNA hybrid and a looped out DNA strand, and RNA:DNA triple helices (triplexes), in which the RNA binds to the major groove of the DNA double helix by sequence-specific Hoogsteen base pairing. In this essay, we will review the current knowledge about RNA:DNA triplexes, summarising triplex formation rules, detection methods, and ncRNAs reported to engage in triplexes. While the functional characterisation of RNA:DNA triplexes is still anecdotal, recent advances in high-throughput and computational analyses indicate their widespread distribution in the genome. Thus, we are witnessing a paradigm shift in the appreciation of RNA:DNA triplexes, away from exotic structures towards a prominent mode of ncRNA–chromatin interactions.


Author(s):  
Modou Mamoune Mbaye ◽  
Bouchra El Khalfi ◽  
Noureddine Louanjli ◽  
Brahim Saadani ◽  
Ismail Kaarouch ◽  
...  

The use of extracellular or circulating nucleic acids (Cfs), as a diagnostic or prognostic tool in oncology, has been broadly documented. However, their use in gynecology-obstetrics as non-invasive biomarkers in the management of infertility has become a recurring fact. The circulating nucleic acids are constituted by: free DNA which can be long or short DNA strands resulting from the apoptotic or necrotic processes, the free RNA containing: micro-RNAs (miRNAs) which are short single-stranded ribonucleic acids (RNA) that are able to deter the production of  protein from a gene, Piwi-interacting RNAs (PiRNAs) that are small RNAs expressed in germ cells or even early embryos and small interfering RNAs (siRNAs) that are small RNAs that can bind specifically to a messenger RNA sequence and prevent gene expression by cleaving that RNA. The presence of circulating nucleic acids in many biological fluids such as: urine, seminal plasma and serum, the fact that they are easy to detect, the variation of their level according to the physiopathological conditions of the body and their implication in many biological processes such as folliculogenesis, steroidogenesis and spermatogenesis make nucleic acids circulating important biomarkers of interest in the management of male infertility. They compose a real complementary help for practitioners of medically assisted procreation. As a result, circulating nucleic acids are a promising avenue in the prevention of implantation failures. In this article, we will seek to affirm further, their importance in the management of male infertility, by highlighting their different uses.


Author(s):  
D.P. Bazett-Jones ◽  
F.P. Ottensmeyer

Dark field electron microscopy has been used for the study of the structure of individual macromolecules with a resolution to at least the 5Å level. The use of this technique has been extended to the investigation of structure of interacting molecules, particularly the interaction between DNA and fish protamine, a class of basic nuclear proteins of molecular weight 4,000 daltons.Protamine, which is synthesized during spermatogenesis, binds to chromatin, displaces the somatic histones and wraps up the DNA to fit into the small volume of the sperm head. It has been proposed that protamine, existing as an extended polypeptide, winds around the minor groove of the DNA double helix, with protamine's positively-charged arginines lining up with the negatively-charged phosphates of DNA. However, viewing protamine as an extended protein is inconsistent with the results obtained in our laboratory.


2021 ◽  
pp. 026988112110324
Author(s):  
David J Heal ◽  
Sharon L Smith

Background: Binge-eating disorder (BED) is a common psychiatric condition with adverse psychological and metabolic consequences. Lisdexamfetamine (LDX) is the only approved BED drug treatment. New drugs to treat BED are urgently needed. Methods: A comprehensive review of published psychopathological, pharmacological and clinical findings. Results: The evidence supports the hypothesis that BED is an impulse control disorder with similarities to ADHD, including responsiveness to catecholaminergic drugs, for example LDX and dasotraline. The target product profile (TPP) of the ideal BED drug combines treating the psychopathological drivers of the disorder with an independent weight-loss effect. Drugs with proven efficacy in BED have a common pharmacology; they potentiate central noradrenergic and dopaminergic neurotransmission. Because of the overlap between pharmacotherapy in attention deficit hyperactivity disorder (ADHD) and BED, drug-candidates from diverse pharmacological classes, which have already failed in ADHD would also be predicted to fail if tested in BED. The failure in BED trials of drugs with diverse pharmacological mechanisms indicates many possible avenues for drug discovery can probably be discounted. Conclusions: (1) The efficacy of drugs for BED is dependent on reducing its core psychopathologies of impulsivity, compulsivity and perseveration and by increasing cognitive control of eating. (2) The analysis revealed a large number of pharmacological mechanisms are unlikely to be productive in the search for effective new BED drugs. (3) The most promising areas for new treatments for BED are drugs, which augment noradrenergic and dopaminergic neurotransmission and/or those which are effective in ADHD.


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