Добавил:
Sekretar
kiopkiopkiop18@yandex.ru
t.me/Prokururor I Вовсе не секретарь, но почту проверяю
Опубликованный материал нарушает ваши авторские права? Сообщите нам.
Вуз:
Предмет:
Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5639_Библиотеки_им_академика_М_И_Перельмана
.pdf
11 Role ofGenomics andProteomics inDrug Discovery
https://t.me/med1917
possible toxicity at the protein and genetic levels. By guaranteeing that the most
pertinent targets and molecules are given priority, the coupling of these omics technologies with HTS speeds up the drug development process.
Through the integration of high-throughput screening with genomics and proteomics, researchers can leverage the copious amounts of data produced by these
technologies to make better-informed decisions at every stage of the drug discovery
process. By improving target selection, validation, and lead optimization, this integrative method eventually contributes to the development of safer and more potent
medicines. By customizing medicines to each patient’s own genetic and proteomic
prole, it also advances the development of personalized medicine. This integrated
approach will further transform the drug discovery area as long as technology and
data analysis methodologies keep up their current pace of advancement (Bleicher
etal. 2003; Blay etal. 2020).
229
11.6.3 Lead Compound Identication
Lead compound identication is a crucial stage in the drug development process
that entails choosing a few promising compounds from a wider group of possible
therapeutic candidates. The basis for additional research, development, optimization, and testing is provided by these lead molecules. Identication of lead compounds is a complicated procedure that uses a variety of scientic methods and
tools. An outline of the main components is provided here (Noah 2010).
The process of identifying lead compounds frequently starts with a well-dened
molecular target, such as a particular protein or genetic sequence linked to a disease.
The choice of target is essential since it establishes the direction of the lead compound search. Compound libraries with a variety of chemical entities are maintained by biotechnology corporations, research institutes, and pharmaceutical
companies. Natural substances, articial molecules, and proprietary compounds
can all be found in these libraries. These libraries are screened by researchers to nd
lead compounds with the right characteristics (Bogatcheva etal. 2011).
The high-throughput screening (HTS) technique enables the quick assessment of
thousands or even millions of compounds for their efcacy against a particular target. These tests are carried out using automated robotic equipment, which makes
HTS an extremely effective method. Based on a compound’s structure, computer
algorithms are used in silico, or virtual screening, to forecast a compound’s possible
binding afnity to a target. This method reduces the number of chemicals that need
to be tested experimentally. Compounds that precisely t into the target’s active site
can be designed thanks to knowledge of the target’s three-dimensional structure,
which is often gained by methods such as X-ray crystallography. This methodical
approach to design produces lead compounds that have a better chance of succeeding.
In the fragment-based drug design approach, tiny, low molecular weight molecules are screened in order to nd fragments that bind to the target. Lead compounds can be synthesized from these pieces (Doak etal. 2016). After possible lead
230
https://t.me/med1917
compounds or “hits” are found, medicinal chemists carry out a process known as
“hit-to-lead optimization”. This entails modifying the substance chemically and
conducting studies on the structure-activity relationship (SAR) to enhance its pharmacokinetics, selectivity, and binding afnity. In order to ascertain how lead compounds are absorbed, transported, metabolized, and removed by the body, their
absorption, distribution, metabolism, and excretion (ADME) properties are evaluated. It is more probable for compounds with favourable ADME proles to advance
to the following phases of development (Edlin etal. 2012).
To make sure lead compounds are safe for human usage, they go through extensive toxicity testing. This entails examining the compound’s safety margin and any
negative effects. Pharmacokinetic (PK) and pharmacodynamic (PD) proling investigations shed light on the lead compound’s metabolism and invivo interactions
with the target. Predicting its treatment success requires an understanding of these
factors (Eddershaw etal. 2000). To assess a compound’s safety and effectiveness in
a living creature, lead compounds are tested in animal models. The dose, toxicity,
and efcacy for possible human application are all improved by these
investigations.
A single lead molecule is selected to proceed to the next stage of drug development based on the results of all the aforementioned evaluations. We now refer to this
chemical as the “development candidate”. Businesses may submit patent applications at this stage in order to safeguard their lead compounds and other intellectual
property (Raj etal. 2015). Lead compound identication is a highly dynamic and
iterative process, and not all substances that enter the pipeline will eventually turn
into effective medications. Finding the lead molecule with the most promising therapeutic potential while adhering to safety and regulatory requirements is the aim.
After selecting a lead chemical, it moves on to the preclinical and clinical phases of
development, ultimately resulting in the production of a novel pharmaceutical product that will benet patients.
J. Sundarasekar and G. Sahgal
11.7 Drug Development andClinical Trials
11.7.1 Translating Genomic andProteomic Findings into
Drug Candidates
One of the most important phases in the drug development process is the translation
of genomic and proteomic data into drug candidates, where knowledge gained from
the analysis of genes and proteins is applied to create possible medicinal agents.
This multi-phase translation procedure is essential to the release of novel medications on the market. This is a summary of the process by which medication candidates are developed from genomes and proteomic research.
Finding targets in drug discovery is an essential rst step in creating novel medications. Through validation, genes or genetic variants linked to certain diseases are
11 Role ofGenomics andProteomics inDrug Discovery
https://t.me/med1917
231
found through genomic research and may be developed into therapeutic targets.
Proteins implicated in disease pathways are identied by proteomic research; proteins with changed expression, activity, or post-translational changes may also be
suitable targets for therapeutic intervention. To guarantee that a gene or protein is
relevant to a disease, target validation is necessary. Numerous techniques, including
functional genomic assays and knockout experiments in model species, are used to
conrm genetic connections. Experiments showing the functional relevance of proteins in disease mechanisms justify the involvement of proteomics in disease
(Minikel etal. 2020).
Compounds from various libraries are tested using high-throughput screening
(HTS) to see if they have the ability to modify the veried target (Bleicher etal.
2003). Compounds with promising action are called hits. In hit-to-lead optimiza-
tion, hits are optimized by medicinal chemistry to enhance their drug-like qualities. This procedure entails pharmacological proling, structure-activity
relationship (SAR) research, and chemical changes. To make sure lead compounds
are safe for use in toxicology and safety evaluation, they go through a rigorous
toxicological study. These investigations determine a safety margin and evaluate
possible adverse effects. Studies on pharmacokinetics and pharmacodynamics
(PK/PD) shed light on how a substance is digested and interacts with its target in
living things (Eddershaw etal. 2000). For additional development, the top-performing lead compound—often referred to as the “development candidate”—
is chosen.
Companies frequently submit patent applications during the lead compound
identication and development process to safeguard their therapeutic prospects and
intellectual property (Raj et al. 2015). Preclinical research is conducted on the
development of candidates in animal models to assess safety and effectiveness. The
efcacy, toxicity, and proper dosage are all determined in part by these investigations. In regulatory considerations, businesses must take regulatory requirements
into account and make plans for the data and documents required for regulatory
approvals (Siegel and Lakings 2008).
When preclinical research is successful, clinical trials start when the medication
candidate is examined on living people. Multiple steps are included in clinical
studies in order to assess safety and efcacy. The medication candidate may be
granted regulatory permission for commercialization and distribution if clinical
trials provide positive results. Following approval, the medication is subject to
ongoing post- market surveillance to ensure its efcacy and safety (Lemmens and
Gibson 2014).
It usually takes many years to convert the results of genomes and proteomic
research into viable treatment possibilities. This process is difcult and resourceintensive. However, the eld of drug discovery has undergone a revolution because
of the application of genomes and proteomics, which has allowed for the development of more specialized and potent medicines for a range of illnesses. The ultimate
objective is to introduce novel medications that enhance patients’ health and quality
of life.
232
https://t.me/med1917
J. Sundarasekar and G. Sahgal
11.7.2 Clinical Trial Design andPatient Selection
Patient selection and clinical trial design are essential steps in the medication
development process. In order to produce relevant data, guarantee patient safety,
and prove the safety and effectiveness of a novel medical intervention, proper
trial design and patient selection are crucial. Here is a summary of these
elements.
Clinical Trial Design
Research studies called clinical trials are used to evaluate the efcacy and safety of
novel therapies or interventions for a range of illnesses or ailments. Typically, clinical trials are divided into four phases, each of which has a distinct function. Phase
I trials feature a limited number of healthy volunteers or patients and concentrate
on safety and dose. Phase II trials assess safety and efcacy in a broader patient
population. Phase III trials are large-scale studies that evaluate treatment effectiveness and track side effects in a variety of patient populations. Phase IV trials, sometimes referred to as post-marketing trials, monitor a medication’s effectiveness and
safety even after it has been approved and is being used widely (Streiner and
Norman 2009).
Several techniques are frequently used in clinical studies to guarantee the reliability and validity of the ndings. By randomly allocating patients to treatment or
control groups, randomization serves to reduce bias and ensures group comparability. Blinding is a strategy that reduces bias and produces more dependable results by
keeping either the patient or the researcher (double-blind) or both (single-blind)
uninformed of the treatment being provided. In a form of trial known as a placebo
control, the treatment group is compared to a placebo group that is given an inactive
drug. Determining the intervention’s actual efcacy depends on its design. In a
crossover design trial, patients get several treatments one after the other. This can
lower the number of patients needed and allow for comparisons between subjects.
A trial with an adaptive design enables the research design to be changed as data are
gathered and analysed. This adaptability may increase the trial’s effectiveness (Enck
and Klosterhalfen 2019).
The selection of endpoints or the outcomes that are measured to evaluate
treatment efcacy and safety is another crucial component of clinical trials.
Clinical (such as survival or symptom relief), surrogate (such as biomarkers), or
patient- reported (such as quality of life) endpoints are all possible. Selecting the
right primary and secondary endpoints is essential for evaluating the intervention’s risks and benets. To guarantee that the study has the statistical power to
identify signicant effects, choosing the right sample size is also crucial. A number of variables, including the estimated impact size, the signicance threshold,
and the outcome’s unpredictability, affect how big of a sample to use (Chow
etal. 2017).
11 Role ofGenomics andProteomics inDrug Discovery
https://t.me/med1917
233
Patient Selection
A key component of clinical trial design is patient selection, which establishes the
validity and generalizability of the ndings. Patient selection is inuenced by a
number of factors, including informed consent, patient safety, patient preferences,
demographics, disease severity, comorbidities, genetic and biomarker testing, performance status, and ethical issues (Ivy etal. 2010).
The features that patients must full in order to be included in the trial and those
that rule them out are outlined in the inclusion and exclusion criteria (exclusion).
Age, gender, disease stage, medical history, and prior therapy are a few examples of
criteria. The features of the patient population, such as age, gender, race, and ethnicity, are referred to as demographics. To understand how the treatment might inuence different groups, it is important to ensure that the patient population is diverse.
The degree of disease severity reects the stage of the patient’s disease or progression. To evaluate how the treatment affects the disease at different phases, patients
might be categorized based on the severity of their conditions (Kirsten etal. 2016).
Comorbidities are additional illnesses that people may experience in addition to
their main ailment. Comorbidities may have an impact on a patient’s study eligibility and how the results are interpreted. Testing for genetic traits and biomarkers is
one way to determine a patient’s or a disease’s molecular characteristics. Genetic
and biomarker testing may be utilized in precision medicine studies to identify individuals who are more likely to respond well to the prescribed course of action. A
patient’s capacity to do everyday tasks and general state of well-being are reected
in their performance status (Duma etal. 2019).
Patient performance status might affect their eligibility and prognosis in a trial.
It is commonly quantied using scales such as the Eastern Cooperative Oncology
Group (ECOG) performance status. Patients must give their informed permission
before they may partake in a clinical trial. This involves explaining the trial’s goals,
methods, possible dangers, and rewards. For patients to take part in a clinical trial,
informed permission is required. Ensuring patient safety in clinical trials involves
safeguarding them against danger or injury. It is crucial to make sure patients full
stringent safety requirements. For instance, women who are capable of bearing children may need to take pregnancy tests or use contraception (Jin etal. 2017).
A patient’s values and expectations surrounding a clinical trial are reected in
their preferences and quality of life considerations. Patient selection and adherence
to the study procedure may also be inuenced by patient preferences and quality of
life factors. Clinical trial procedures and patient selection are governed by ethical
considerations. Protecting the rights and welfare of patients in clinical trials is the
goal of ethical concepts such as informed consent, respect for autonomy, justice,
and minimizing harm and maximizing benet (Samuel etal. 2022).
Reliable and signicant results can only be achieved by carefully planning clinical trials and selecting volunteers, all while reducing participant risks. These procedures are essential for expanding our understanding of medicine, enhancing patient
care, and developing and introducing novel, secure, and efcient medicines.
Furthermore, continual assessment and improvement of patient selection standards
234
https://t.me/med1917
and trial designs optimize the medication development process and support the
ongoing advancement of health care interventions.
J. Sundarasekar and G. Sahgal
11.7.3 Monitoring andAssessing Drug Efcacy andSafety
As a crucial and ongoing process, monitoring and evaluating drug efcacy and
safety occur across a medication’s whole life cycle, from preclinical development to
clinical trials and post-marketing surveillance. This all-encompassing strategy guarantees that medications are safe for patients to take and are effective in addressing
medical ailments. This is a summary of the main elements involved in tracking and
evaluating the safety and efcacy of drugs (Burnier and Wuerzner 2015).
Drug development is a multi-phase, multi-stage procedure that starts with preclinical evaluation and ends with post-marketing surveillance. A medication candidate must go through rigorous preclinical research, including invitro and invivo
studies, to evaluate its efcacy, mechanism of action, and potential toxicities before
it can move on to human trials. Clinical trials are carried out in several stages, each
with a distinct population and goal. Phase II evaluates efcacy and adverse effects
in a wider patient population, while Phase I concentrates on safety and dosage in a
small sample of healthy volunteers. Large-scale, randomized, controlled studies are
conducted in Phase III to assess efcacy, track side effects, and verify safety across
a range of patient populations. Finding out if a treatment has the desired therapeutic
impact is the main objective of clinical trials. This is usually done by utilizing clinical endpoints, which include survival rates, symptom relief, or other disease- specic
markers (Streiner and Norman 2009).
The medication’s safety is closely monitored both during and after the clinical
trial phase, as well as following regulatory approval. This includes keeping an eye
on and disclosing any unanticipated reactions, side effects, and adverse events.
Studies on pharmacokinetics and pharmacodynamics look at the drug’s interactions
with the body and target and how it is absorbed, distributed, metabolized, and
removed from the body (Eddershaw etal. 2000).
During the post-marketing surveillance phase, the medicine is continuously
observed in real-world settings to ensure safety and efcacy. These data support
label changes and aid in the detection of uncommon or chronic adverse effects.
Pharmacovigilance systems help with the continuous evaluation of drug safety by
gathering, analysing, and reporting adverse events and side effects. A comparative
effectiveness study is sometimes carried out to assess the safety and efcacy of new
drugs in relation to current treatments (Moore etal. 2019).
For the purpose of making regulatory decisions, a drug’s benet-to-risk ratio
must be continuously assessed. For a medication to be sold, it must offer more
advantages than disadvantages. Regulatory control is provided by health organizations such as the FDA in the USA and the EMA in Europe, who make sure that
medications full strict safety and efcacy requirements. Adverse occurrences and
side effects can be reported by patients and medical experts, which helps with the
11 Role ofGenomics andProteomics inDrug Discovery
https://t.me/med1917
continuous monitoring of drug safety. The drug’s label may be amended to reect
any new information regarding safety or efcacy, so patients and healthcare providers are kept informed (Lemmens and Gibson 2014).
The dynamic processes of monitoring and evaluating drug safety and efcacy
seek to strike a balance between the possible hazards and the advantages of treatment. For patient safety and the ongoing advancement of health care, this continuous review is essential. It guarantees that medications in circulation continue to be
safe, effective, and compliant with the most up-to-date scientic research.
235
11.8 Challenges andFuture Directions
11.8.1 Ethical andRegulatory Considerations
The advancement of medical knowledge and the creation of novel medications
depend on clinical trials. To preserve the rights and welfare of participants and guarantee the validity and reliability of the results, they also present ethical and legal
issues that need to be resolved. Among the most important moral and legal concerns
in clinical trials are discussed herein.
The ethical precept of informed consent states that patients and clinical trial participants must provide their assent after being fully informed about the research’s
goals, methods, possible dangers, and potential rewards. Additionally, regulatory
bodies around the world, including the FDA in the United States and the EMA in
Europe, have mandated it as a regulatory requirement (Lema etal. 2009). Patient
safety is the most important ethical precept, according to which any possible dangers connected to the experimental medication must be thoroughly evaluated,
reduced, and made public. Regulatory agencies are also required by law to closely
monitor and assess the safety of pharmaceuticals during their development, and
safety data must undergo a thorough evaluation before being approved for sale
(Siegel and Lakings 2008; Burnier and Wuerzner 2015).
Clinical trial design ethical guideline states that clinical trials should be
planned to minimize participant risk while providing an effective and efcient
response to scientic issues. Regulatory bodies are also required by law to offer
recommendations and evaluate trial procedures in order to guarantee that the trials are ethically sound and well-designed (Siegel and Lakings 2008; Ivy etal.
2010). Transparency and disclosure are the ethical precepts that complete disclo-
sure of trial results—both favourable and unfavourable—is necessary to further
medical understanding. Transparency in the pharmaceutical sector is becoming
increasingly important, and regulatory bodies frequently demand the disclosure
of clinical trial results (Siegel and Lakings 2008). Independent ethical review
boards (IRBs) or ethics committees are responsible for supervising clinical trials
and ensuring that the study design and participant protections are suitable.
Regulatory authorities must also obtain IRB permission in order for clinical trials
to move forward (Kim 2012).
236
https://t.me/med1917
Placebo use refers to the ethical precept that, in order to prevent withholding
potentially helpful therapy, the use of placebos in clinical trials should be minimized, particularly when effective therapies are available. Regulations that prioritize patient welfare and outline the circumstances in which placebos may be used
are also mandatory (Enck and Klosterhalfen 2019). The data integrity ethical concept states that academics and the pharmaceutical business have basic ethical duties
to maintain data integrity and to present results honestly. Additionally, regulatory
bodies are required to carefully examine the accuracy of data provided for drug
approval; failure to do so may result in harsh penalties (Kim 2012). On top of that,
regulatory bodies ought to have the power and means to thoroughly assess the quality, safety, and efcacy of drugs. Additionally, it is mandated by law that regulatory
bodies, such as the FDA in the United States and the EMA in Europe, evaluate and
approve new pharmaceuticals in accordance with scientic and ethical standards
(Siegel and Lakings 2008).
Data sharing ethical tenet of data sharing holds that patients can gain from scientic advancements and clinical trial data can be shared while maintaining patient
privacy and condentiality. Additionally, several regulatory bodies increasingly
mandate data sharing as a condition of their post-market transparency and surveillance initiatives. Trials involving vulnerable populations, such as children, pregnant
women, or the elderly, must take extra precautions and provide special concern to
these groups. It is also required by law that regulatory rules give disadvantaged
populations certain protections and requirements (Jin etal. 2017).
Regulations are based on ethical concepts, and ethical values themselves are
entwined with regulatory considerations. Ensuring that new medication development upholds the greatest standards of ethics, openness, and patient safety while
beneting patients and society is the aim. These factors are dynamic and everevolving, mirroring the rapidly changing elds of science, technology, and medicine.
J. Sundarasekar and G. Sahgal
11.8.2 Emerging Technologies inGenomics andProteomics
At the front edge of biomedical research, the dynamic elds of genomics and proteomics provide profound insights into the molecular underpinnings of health and
illness. Scientists may now study biological systems with never-before-seen accuracy
and depth because of emerging tools in proteomics and genomics (Chung etal. 2007).
Genomics
The study of an organism’s whole genetic make-up, or genomics, is one of the most
fascinating areas of modern biology. The development of sequencing technology
has transformed genomics by enabling unprecedentedly fast, accurate, and highresolution analysis of DNA and RNA.Among the most innovative technologies for
sequencing are discussed here.
11 Role ofGenomics andProteomics inDrug Discovery
https://t.me/med1917
237
Single-cell sequencing technique enables the examination of individual cells,
exposing heterogeneity inside the cell and illuminating the roles played by many
cell types in intricate biological processes, including development, cancer, and
immunological responses. Companies such as Oxford Nanopore Technologies provide nanopore sequencing, which allows real-time study of DNA or RNA as it ows
through a nanopore. Because of its great portability, this technology is useful for
quick diagnostics and eld applications.
Beyond DNA sequencing, the eld of epigenomics is studying changes in epigenetic marks, such as DNA methylation and histone modications, to gain a better
understanding of how genes are regulated and how diseases are caused by these
changes. Metagenomics technology makes it possible to sequence whole microbial
populations in intricate settings. Grasping the signicance of the microbiome in
human health and disease and environmental ecosystems requires a grasp of
metagenomics.
In the long-read sequencing method, longer DNA reads can be performed by
technologies such as Oxford Nanopore and PacBio, which lessen the need for intricate genome assembly and make it easier to identify repetitive sequences and structural changes. These technological advancements are revolutionizing our
understanding of biology and creating new opportunities for study and creativity
(Berriman etal. 2007; Huang 2007).
Proteomics
A potent technology known as mass spectrometry imaging (MSI) blends the analytical powers of mass spectrometry with the spatial resolution of imaging methods.
Through the simultaneous detection and localization of hundreds of proteins in tissue slices, MSI makes it possible to determine the distribution and quantity of these
proteins across various cell types and regions. Understanding the molecular causes
of diseases at the tissue level, such as cancer, neurodegeneration, and infection, is
made possible thanks in large part to MSI.
The process of designing and producing new proteins and antibodies with desired
features and functions is known as protein engineering. Protein engineering modies the genetic coding and structure of proteins by using cutting-edge methods such
as phage display and CRISPR-Cas9. In biotechnology, medicine, and agriculture,
protein engineering has several uses, including the creation of novel medications,
diagnostic tools, vaccines, enzymes, and biosensors.
A developing method called “top-down proteomics” examines intact proteins
without rst breaking them down or digesting them. Compared to the conventional
bottom-up method, top-down proteomics has a number of benets, including the
preservation of data on protein isoforms and post-translational modications
(PTMs). PTMs and isoforms play a crucial role in controlling the function and
activity of proteins and are frequently linked to a number of illnesses. A more thorough and precise description of the proteome can be obtained using top-down
proteomics.
238
https://t.me/med1917
J. Sundarasekar and G. Sahgal
The goal of the cutting-edge eld of single-molecule proteomics is to measure
and describe individual proteins in intricate biological systems. The sensitivity,
specicity, and dynamic range constraints of traditional bulk technologies can be
circumvented by single-molecule approaches. Rare protein variations and heterogeneity that are otherwise hidden by averaging effects can be found by single- molecule
proteomics. The temporal and spatial dynamics of protein interactions and conformational changes can also be captured by single-molecule proteomics.
One of the most important methods for understanding the relationships and functional roles of proteins in cells is protein-protein interaction mapping. Complex
networks of protein-protein interactions control a range of biological functions,
including transcription, translation, metabolism, and signalling. Protein-protein
interaction mapping has the ability to identify biomarkers and new therapeutic targets in addition to revealing previously unidentied pathways and mechanisms
underlying health and illness. Proximity labelling and cross-linking mass spectrometry are two emerging technologies that make it possible to explore protein-protein
interactions comprehensively and efciently.
The area of proteomics known as structural proteomics is devoted to guring out
the three-dimensional congurations of proteins and their complexes. Understanding
the architecture of proteins can help us understand their relationships, roles, and
modes of action. Structure-based medication design, which looks for or optimizes
molecules that bind to particular protein targets, is also made easier by structural
proteomics. The area of structural proteomics is progressing because of methods
such as X-ray crystallography and cryo-electron microscopy (cryo-EM), which
allow for the high-resolution imaging of huge and complicated protein complexes
(Jeffery and Bogyo 2003; Thomford etal. 2018).
Integration
The integration of several forms of omics data, including transcriptomics, proteomics, metabolomics, and genomes, is one of the newer developments in omics
research. The goal of these multi-omics techniques is to offer a more thorough and
integrated understanding of intricate biological processes, including the onset of
disease, the response to drugs, and cellular signalling. However, because of the high
dimensionality, variability, and noise of the datasets, analysing and interpreting
multi-omics data presents a number of difculties (Waller etal. 2007).
Articial intelligence (AI) and machine learning approaches are being used more
and more in omics data analysis to address these issues, opening the door to the
identication of unexpected patterns, fresh perspectives, and prediction models. By
fusing omics data with clinical and phenotypic data, AI and machine learning can
also help with customized medicine, drug discovery, and biomarker identication
(Iskar etal. 2012).
Creating articial genes, proteins, and cellular pathways is known as synthetic
biology, and it is another exciting technique that is revolutionizing omics research.
Customized medicinal medicines and diagnostic instruments that target particular
Соседние файлы в папке Библиотека им академика М.И. Перельмана