Vladimir Poroikov | IBMC - Academia.edu (original) (raw)
Papers by Vladimir Poroikov
Based o computer-aided prediction of biological activity spectra using PASS computer program pack... more Based o computer-aided prediction of biological activity spectra using PASS computer program package, several antihypertensive drugs belonging to the group of ACE inhibitors have been selected for testing their nootropic activity. Experiments were conducted on mice by the test of spontaneous orientation (patrolling behavior) in the cross-maze. It was found that perindopril in a dose of 1 mg/kg, as well as quinapril and monopril in a dose of 10 mg/kg, improved the patrolling behavior in the cross-maze test. This effect is similar to the effects of standard nootropic drugs piracetam and meclofenoxate (in doses of 300 and 120 mg/kg, respectively). The observed nootropic effect of some ACE inhibitors are likely to be unrelated to their antihypertensive effect, since the nootropic action took place only at relatively low doses of perindopril, quinapril and monopril and was not observed with further increase in the dose. The identification of the nootropic action of antihypertensive drugs...
Химико-фармацевтический журнал, 2014
Взаимодействием 2-хлор-N-(9,10-диоксо-9,10-дигидроантрацен-1-ил)ацетамида с α-, β-, ω-аминокислот... more Взаимодействием 2-хлор-N-(9,10-диоксо-9,10-дигидроантрацен-1-ил)ацетамида с α-, β-, ω-аминокислотами синтезированы новые аминокислотные производные 9,10-антрахинона. Экспериментальное тестирование антимикробного действия синтезированных соединений выявило антибактериальную активность по отношению к Mycobacterium luteum и противогрибковую активность по отношению к Aspergillus niger и Candida tenuis. Полученные результаты экспериментального тестирования биологической активности согласуются с результатами прогноза компьютерной программы PASS. Согласно прогнозу, в дальнейшем целесообразно изучить противоопухолевое и антиоксидантное действие новых синтезированых аминокислотных производных.
Sar and Qsar in Environmental Research, Dec 19, 2017
Abstract Traditional knowledge guides the use of plants for restricted therapeutic indications, b... more Abstract Traditional knowledge guides the use of plants for restricted therapeutic indications, but their pharmacological actions may be found beyond their ethnic therapeutic indications employing emerging computational tools. In this context, the present study was envisaged to explore the novel pharmacological effect of Achyranthes aspera (A. aspera) using PASS and PharmaExpert software tools. Based on the predicted mechanisms of the antidepressant effect for all analysed phytoconstituents of A. aspera, one may suggest its significant antidepressant action. The possible mechanism of this novel pharmacological effect is the enhancement of serotonin release, in particular caused by hexatriacontane. Therefore, pharmacological validation of the methanolic extract, hexatriacontane rich (HRF) and hexatriacontane lacking fraction (HLF) of A. aspera was carried out using the Forced Swimming Test and Tail suspension test in mice. The cortical and hippocampal monoamine and their metabolite levels were measured using high performance liquid chromatography (HPLC). A. aspera methanolic extract, HRF treatments showed a significant antidepressant effect comparable to imipramine. Further, the corresponding surge in cortical and hippocampal monoamine and their metabolite levels was also observed with these treatments. In conclusion, A. aspera has shown a significant antidepressant effect, possibly due to hexatriacontane, by raising monoamine levels.
Molecules
Herein we report the synthesis of some new 1H-1,2,4-triazole functionalized chromenols (3a–3n) vi... more Herein we report the synthesis of some new 1H-1,2,4-triazole functionalized chromenols (3a–3n) via tandem reactions of 1-(alkyl/aryl)-2-(1H-1,2,4-triazole-1-yl) with salicylic aldehydes and the evaluation of their antifungal activity. In silico prediction of biological activity with computer program PASS indicate that the compounds have a high novelty compared to the known antifungal agents. We did not find any close analog among the over 580,000 pharmaceutical agents in the Cortellis Drug Discovery Intelligence database at the similarity cutoff of 70%. The evaluation of antifungal activity in vitro revealed that the highest activity was exhibited by compound 3k, followed by 3n. Their MIC values for different fungi were 22.1–184.2 and 71.3–199.8 µM, respectively. Twelve from fourteen tested compounds were more active than the reference drugs ketoconazole and bifonazole. The most sensitive fungus appeared to be Trichoderma viride, while Aspergillus fumigatus was the most resistant on...
A software package was designed and used in a detailed study of the contact regions (interfaces) ... more A software package was designed and used in a detailed study of the contact regions (interfaces) of a large number of protein-protein complexes using the PDB data. It appeared that for about 75% of the com- plexes the amino acid composition of the subunit surface in the contact region is not essential. Thus one may suggest that, along with the amino acid residues at the interface, the residues in the interior of the globules sub- stantially contribute to protein-protein recognition. Such interactions between quite remote residues are most probably of electrical nature, and are involved in recognition by contributing to the overall electric field created by the protein molecule; the configuration of this field is perhaps the definitive factor of recognition. The overall field of the protein molecule is additively built of the fields created by each constituent residue, and it can be calculated as a sum of the fields created by the protein multipole (aggregate of "partial" e...
Biochemical and Biophysical Research Communications, 2020
This review is dedicated to the comparative analysis of structure-activity relationships for more... more This review is dedicated to the comparative analysis of structure-activity relationships for more than 75 natural and synthetic derivatives of adamantane. Some of these compounds, such as amantadine and memantine, are currently used to treat dementia, Alzheimer's and Parkinson's diseases and other neurodegenerative diseases. The data presented show that the pharmacological potential of 1-fluoroand 1-phosphonic acid adamantane derivatives against Alzheimer's and Parkinson's diseases and other neurodegenerative diseases exceeds those of well-known amantadine and memantine. The information presented in this review highlights the promising directions of studies for biochemists, pharmacologists, medicinal chemists, physiologists, and neurologists, as well as to the pharmaceutical industry.
Biomeditsinskaya Khimiya, 2020
New drug discovery is based on the analysis of public information about the mechanisms of the dis... more New drug discovery is based on the analysis of public information about the mechanisms of the disease, molecular targets, and ligands, which interaction with the target could lead to the normalization of the pathological process. The available data on diseases, drugs, pharmacological effects, molecular targets, and drug-like substances, taking into account the combinatorics of the associative relations between them, correspond to the Big Data. To analyze such data, the application of computer-aided drug design methods is necessary. An overview of the studies in this area performed by the Laboratory for Structure-Function Based Drug Design of IBMC is presented. We have developed the approaches to identifying promising pharmacological targets, predicting several thousand types of biological activity based on the structural formula of the compound, analyzing protein-ligand interactions based on assessing local similarity of amino acid sequences, identifying likely molecular mechanisms ...
International Journal of Molecular Sciences
Depression and schizophrenia are two highly prevalent and severely debilitating neuropsychiatric ... more Depression and schizophrenia are two highly prevalent and severely debilitating neuropsychiatric disorders. Both conventional antidepressant and antipsychotic pharmacotherapies are often inefficient clinically, causing multiple side effects and serious patient compliance problems. Collectively, this calls for the development of novel drug targets for treating depressed and schizophrenic patients. Here, we discuss recent translational advances, research tools and approaches, aiming to facilitate innovative drug discovery in this field. Providing a comprehensive overview of current antidepressants and antipsychotic drugs, we also outline potential novel molecular targets for treating depression and schizophrenia. We also critically evaluate multiple translational challenges and summarize various open questions, in order to foster further integrative cross-discipline research into antidepressant and antipsychotic drug development.
Pure and Applied Chemistry, 2005
Numerous areas of chemistry can benefit from the ongoing genomic revolution. Here, we discuss and... more Numerous areas of chemistry can benefit from the ongoing genomic revolution. Here, we discuss and highlight trends in chemistry in the postgenomic era. The areas of interest include combinatorial approaches in organic chemistry; design and analysis of proteins containing unnatural amino acids; trace element-containing proteins; design and characterization of new enzyme types; applications of postgenomic chemistry in drug design; identification of lipid networks and global characterization of lipid molecular species; development of recombinant and self-proliferating polymers; and applications in food chemistry and bioanalytical chemistry based on new nanoanalytical systems and novel recognition elements.
материалы конференции, 2021
International Journal of Molecular Sciences
Viruses cause various infections that may affect human lifestyle for durations ranging from sever... more Viruses cause various infections that may affect human lifestyle for durations ranging from several days to for many years. Although preventative and therapeutic remedies are available for many viruses, they may still have a profound impact on human life. The human immunodeficiency virus type 1 is the most common cause of HIV infection, which represents one of the most dangerous and complex diseases since it affects the immune system and causes its disruption, leading to secondary complications and negatively influencing health-related quality of life. While highly active antiretroviral therapy may decrease the viral load and the velocity of HIV infection progression, some individual peculiarities may affect viral load control or the progression of T-cell malfunction induced by HIV. Our study is aimed at the text-based identification of molecular mechanisms that may be involved in viral infection progression, using HIV as a case study. Specifically, we identified human proteins and ...
Frontiers in Genetics
Human immunodeficiency virus (HIV) infection remains one of the most severe problems for humanity... more Human immunodeficiency virus (HIV) infection remains one of the most severe problems for humanity, particularly due to the development of HIV resistance. To evaluate an association between viral sequence data and drug combinations and to estimate an effect of a particular drug combination on the treatment results, collection of the most representative drug combinations used to cure HIV and the biological data on amino acid sequences of HIV proteins is essential. We have created a new, freely available web database containing 1,651 amino acid sequences of HIV structural proteins [reverse transcriptase (RT), protease (PR), integrase (IN), and envelope protein (ENV)], treatment history information, and CD4+ cell count and viral load data available by the user’s query. Additionally, the biological data on new HIV sequences and treatment data can be stored in the database by any user followed by an expert’s verification. The database is available on the web at http://www.way2drug.com/rhi...
Current Medicinal Chemistry, 2021
Nowadays, computational approaches play an important role in the design of new drug-like compound... more Nowadays, computational approaches play an important role in the design of new drug-like compounds and optimization of pharmacotherapeutic treatment of diseases. The emerging growth of viral infections, including those caused by the Human Immunodeficiency Virus (HIV), Ebola virus, recently detected coronavirus, and some others lead to many newly infected people with a high risk of death or severe complications. A huge amount of chemical, biological, clinical data is at the disposal of the researchers. Therefore, there are many opportunities to find the relationships between the particular features of chemical data and the antiviral activity of biologically active compounds based on machine learning approaches. Biological and clinical data can also be used for building models to predict relationships between viral genotype and drug resistance, which might help determine the clinical outcome of treatment. In the current study, we consider machine learning approaches in the antiviral r...
Pharmaceutical Chemistry Journal, 2018
A structure-activity relationship model was constructed to predict adverse drug effects on the ca... more A structure-activity relationship model was constructed to predict adverse drug effects on the cardiovascular system. Models were constructed using sets of drug structures compiled by us with information about adverse effects from analyses and data integrated from various sources. The five most common cardiovascular adverse effects, i.e., myocardial infarction, ischemic stroke, cardiac failure, ventricular tachycardia, and arterial hypertension were analyzed in the work. The PASS software that has proved to be efficient in numerous studies was used to construct the appropriate models. The obtained models were accurate enough to be useful for estimating cardiovascular adverse effects of new drugs. An appropriate evaluation could be made in the very early stages of drug discovery because only the structural formula was needed for the prediction.
Biochemistry (Moscow) Supplement Series B: Biomedical Chemistry, 2016
Applicability of our computer programs PASS and PharmaExpert for prediction of biological activit... more Applicability of our computer programs PASS and PharmaExpert for prediction of biological activity spectra of rather complex and structurally diverse phytocomponents of medicinal plants, both separately and in combinations has been evaluated. For this purpose we have created the web-resource containing known information about structural formulas and biological activity of 1906 phytocomponents of 50 Ayurvedic medicinal plants used in Traditional Indian Medicine (TIM) (http://ayurveda.pharmaexpert.ru). The PASS training set was updated by addition of information about structure and biological activity of 946 natural compounds; then the training procedure and validation were performed, to estimate the quality of PASS prediction. It was shown that the differences between the average accuracy of prediction obtained in leave-5%-out cross-validation (94.467%) and in leave-one-out cross-validation (94.605%) are very small thus demonstrating high predictive ability of the program. Results of biological activity spectra prediction for all phytocomponents included in our database coincided in 83.5% of cases with known experimental data. Additional types of biological activity predicted with high probability indicate further promising directions for further studies of certain phytocomponents of some medicinal plants. The analysis of prediction results of sets of phytocomponents in each of 50 medicinal plants was made by the PharmaExpert software. Based on this analysis, we found that the combination of phytocomponents from Passiflora incarnata may exhibit nootropic, anticonvulsant, and antidepressant effects. Experiments carried out in mice models confirmed the predicted effects of P. incarnata extracts.
Due to the directed way of testing chemical compounds' in drug research and development many proj... more Due to the directed way of testing chemical compounds' in drug research and development many projects fail because serious adverse effects and toxicity are discovered too late, and many existing prospective activities remain unstudied. Evaluation of the general biological potential of molecules is possible using a computer program PASS that predicts more than 780 pharmacological effects, mechanisms of action, mutagenicity, carcinogenicity, etc. on the basis of structural formulae of compounds, with average accuracy ∼85%. PASS applications to both databases of available samples included hundreds of thousands compounds, and small collections of compounds synthesized by separate medicinal chemists are described. It is shown that 880 compounds from Prestwick chemical library represent a very diverse pharmacological space. New activities can be found in existing compounds by prediction. Therefore, on this basis, the selection of compounds with required and without unwanted properties is possible. Even when PASS cannot predict very new activities, it may recognize some unwanted actions at the early stage of R&D, providing the medicinal chemist with the means to increase the efficiency of projects.
Quantitative Structure-Activity Relationships, 1998
A new method for substance-to-substance similarity analysis based on topoelectric indices is desc... more A new method for substance-to-substance similarity analysis based on topoelectric indices is described. Prediction accuracy of the method is tested using LOO crossvalidation procedure on 910 biologically active compounds. The results demonstrate high discriminative ability of proposed structure description and measure of similarity. The method is applied to compare the set of synthetic substances with well-known endogenous bioregulators. Average accuracy of active compounds recognition is 76%. Therefore, the proposed topoelectric indices and similarity measure can be used for estimating the synthetic molecules resemblance to small endogenous bioregulators.
Journal of Bioinformatics and Computational Biology, 2008
The functional annotation of amino acid sequences is one of the most important problems in bioinf... more The functional annotation of amino acid sequences is one of the most important problems in bioinformatics. Different programs have been successfully applied for recognition of some functional classes; nevertheless, many functional groups still cannot be predicted with the required accuracy. We developed a new method for protein function recognition using the original approach of sequence description. Each sequence of the training set is compared with the query sequence, and the local similarity scores are calculated for the query sequence positions and used as input data for the original classifier. The method was tested using leave-one-out cross-validation for three data sets covering 58 enzyme classes. Two tested sets including noncrossing functional classes were recognized with high accuracy at various levels of classification hierarchy. The majority of these classes were predicted with 100% accuracy, showing a prediction ability comparable with the HMMer method and an accuracy s...
OMICS: A Journal of Integrative Biology, 2006
We propose a new approach to predict functional specificity of proteins from their amino acid seq... more We propose a new approach to predict functional specificity of proteins from their amino acid sequences. Our approach is based on two things: structural Multilevel Neighborhoods of Atom (MNA) descriptors and an original Bayesian algorithm. Usually, a protein sequence is presented as a string of amino acid symbols. Here we introduce a new description of an amino acid sequence: a set of structural MNA descriptors. The MNA descriptor is a string describing an atom and its neighbor atoms according to the selected level. In this work, we also use description of a protein sequence as a set of peptides (strings of amino acid symbols). We performed a case study on two subsubclasses of enzyme nomenclature (EC). It is shown that B-statistics give a sufficient predictive power of enzyme specificity prediction for both MNA descriptors and peptides. We also showed that MNA descriptors give higher accuracy values in comparison with peptides and also provide a choice of MNA descriptor levels for best accuracy prediction. The highest average accuracy prediction that was achieved was 0.98.
Based o computer-aided prediction of biological activity spectra using PASS computer program pack... more Based o computer-aided prediction of biological activity spectra using PASS computer program package, several antihypertensive drugs belonging to the group of ACE inhibitors have been selected for testing their nootropic activity. Experiments were conducted on mice by the test of spontaneous orientation (patrolling behavior) in the cross-maze. It was found that perindopril in a dose of 1 mg/kg, as well as quinapril and monopril in a dose of 10 mg/kg, improved the patrolling behavior in the cross-maze test. This effect is similar to the effects of standard nootropic drugs piracetam and meclofenoxate (in doses of 300 and 120 mg/kg, respectively). The observed nootropic effect of some ACE inhibitors are likely to be unrelated to their antihypertensive effect, since the nootropic action took place only at relatively low doses of perindopril, quinapril and monopril and was not observed with further increase in the dose. The identification of the nootropic action of antihypertensive drugs...
Химико-фармацевтический журнал, 2014
Взаимодействием 2-хлор-N-(9,10-диоксо-9,10-дигидроантрацен-1-ил)ацетамида с α-, β-, ω-аминокислот... more Взаимодействием 2-хлор-N-(9,10-диоксо-9,10-дигидроантрацен-1-ил)ацетамида с α-, β-, ω-аминокислотами синтезированы новые аминокислотные производные 9,10-антрахинона. Экспериментальное тестирование антимикробного действия синтезированных соединений выявило антибактериальную активность по отношению к Mycobacterium luteum и противогрибковую активность по отношению к Aspergillus niger и Candida tenuis. Полученные результаты экспериментального тестирования биологической активности согласуются с результатами прогноза компьютерной программы PASS. Согласно прогнозу, в дальнейшем целесообразно изучить противоопухолевое и антиоксидантное действие новых синтезированых аминокислотных производных.
Sar and Qsar in Environmental Research, Dec 19, 2017
Abstract Traditional knowledge guides the use of plants for restricted therapeutic indications, b... more Abstract Traditional knowledge guides the use of plants for restricted therapeutic indications, but their pharmacological actions may be found beyond their ethnic therapeutic indications employing emerging computational tools. In this context, the present study was envisaged to explore the novel pharmacological effect of Achyranthes aspera (A. aspera) using PASS and PharmaExpert software tools. Based on the predicted mechanisms of the antidepressant effect for all analysed phytoconstituents of A. aspera, one may suggest its significant antidepressant action. The possible mechanism of this novel pharmacological effect is the enhancement of serotonin release, in particular caused by hexatriacontane. Therefore, pharmacological validation of the methanolic extract, hexatriacontane rich (HRF) and hexatriacontane lacking fraction (HLF) of A. aspera was carried out using the Forced Swimming Test and Tail suspension test in mice. The cortical and hippocampal monoamine and their metabolite levels were measured using high performance liquid chromatography (HPLC). A. aspera methanolic extract, HRF treatments showed a significant antidepressant effect comparable to imipramine. Further, the corresponding surge in cortical and hippocampal monoamine and their metabolite levels was also observed with these treatments. In conclusion, A. aspera has shown a significant antidepressant effect, possibly due to hexatriacontane, by raising monoamine levels.
Molecules
Herein we report the synthesis of some new 1H-1,2,4-triazole functionalized chromenols (3a–3n) vi... more Herein we report the synthesis of some new 1H-1,2,4-triazole functionalized chromenols (3a–3n) via tandem reactions of 1-(alkyl/aryl)-2-(1H-1,2,4-triazole-1-yl) with salicylic aldehydes and the evaluation of their antifungal activity. In silico prediction of biological activity with computer program PASS indicate that the compounds have a high novelty compared to the known antifungal agents. We did not find any close analog among the over 580,000 pharmaceutical agents in the Cortellis Drug Discovery Intelligence database at the similarity cutoff of 70%. The evaluation of antifungal activity in vitro revealed that the highest activity was exhibited by compound 3k, followed by 3n. Their MIC values for different fungi were 22.1–184.2 and 71.3–199.8 µM, respectively. Twelve from fourteen tested compounds were more active than the reference drugs ketoconazole and bifonazole. The most sensitive fungus appeared to be Trichoderma viride, while Aspergillus fumigatus was the most resistant on...
A software package was designed and used in a detailed study of the contact regions (interfaces) ... more A software package was designed and used in a detailed study of the contact regions (interfaces) of a large number of protein-protein complexes using the PDB data. It appeared that for about 75% of the com- plexes the amino acid composition of the subunit surface in the contact region is not essential. Thus one may suggest that, along with the amino acid residues at the interface, the residues in the interior of the globules sub- stantially contribute to protein-protein recognition. Such interactions between quite remote residues are most probably of electrical nature, and are involved in recognition by contributing to the overall electric field created by the protein molecule; the configuration of this field is perhaps the definitive factor of recognition. The overall field of the protein molecule is additively built of the fields created by each constituent residue, and it can be calculated as a sum of the fields created by the protein multipole (aggregate of "partial" e...
Biochemical and Biophysical Research Communications, 2020
This review is dedicated to the comparative analysis of structure-activity relationships for more... more This review is dedicated to the comparative analysis of structure-activity relationships for more than 75 natural and synthetic derivatives of adamantane. Some of these compounds, such as amantadine and memantine, are currently used to treat dementia, Alzheimer's and Parkinson's diseases and other neurodegenerative diseases. The data presented show that the pharmacological potential of 1-fluoroand 1-phosphonic acid adamantane derivatives against Alzheimer's and Parkinson's diseases and other neurodegenerative diseases exceeds those of well-known amantadine and memantine. The information presented in this review highlights the promising directions of studies for biochemists, pharmacologists, medicinal chemists, physiologists, and neurologists, as well as to the pharmaceutical industry.
Biomeditsinskaya Khimiya, 2020
New drug discovery is based on the analysis of public information about the mechanisms of the dis... more New drug discovery is based on the analysis of public information about the mechanisms of the disease, molecular targets, and ligands, which interaction with the target could lead to the normalization of the pathological process. The available data on diseases, drugs, pharmacological effects, molecular targets, and drug-like substances, taking into account the combinatorics of the associative relations between them, correspond to the Big Data. To analyze such data, the application of computer-aided drug design methods is necessary. An overview of the studies in this area performed by the Laboratory for Structure-Function Based Drug Design of IBMC is presented. We have developed the approaches to identifying promising pharmacological targets, predicting several thousand types of biological activity based on the structural formula of the compound, analyzing protein-ligand interactions based on assessing local similarity of amino acid sequences, identifying likely molecular mechanisms ...
International Journal of Molecular Sciences
Depression and schizophrenia are two highly prevalent and severely debilitating neuropsychiatric ... more Depression and schizophrenia are two highly prevalent and severely debilitating neuropsychiatric disorders. Both conventional antidepressant and antipsychotic pharmacotherapies are often inefficient clinically, causing multiple side effects and serious patient compliance problems. Collectively, this calls for the development of novel drug targets for treating depressed and schizophrenic patients. Here, we discuss recent translational advances, research tools and approaches, aiming to facilitate innovative drug discovery in this field. Providing a comprehensive overview of current antidepressants and antipsychotic drugs, we also outline potential novel molecular targets for treating depression and schizophrenia. We also critically evaluate multiple translational challenges and summarize various open questions, in order to foster further integrative cross-discipline research into antidepressant and antipsychotic drug development.
Pure and Applied Chemistry, 2005
Numerous areas of chemistry can benefit from the ongoing genomic revolution. Here, we discuss and... more Numerous areas of chemistry can benefit from the ongoing genomic revolution. Here, we discuss and highlight trends in chemistry in the postgenomic era. The areas of interest include combinatorial approaches in organic chemistry; design and analysis of proteins containing unnatural amino acids; trace element-containing proteins; design and characterization of new enzyme types; applications of postgenomic chemistry in drug design; identification of lipid networks and global characterization of lipid molecular species; development of recombinant and self-proliferating polymers; and applications in food chemistry and bioanalytical chemistry based on new nanoanalytical systems and novel recognition elements.
материалы конференции, 2021
International Journal of Molecular Sciences
Viruses cause various infections that may affect human lifestyle for durations ranging from sever... more Viruses cause various infections that may affect human lifestyle for durations ranging from several days to for many years. Although preventative and therapeutic remedies are available for many viruses, they may still have a profound impact on human life. The human immunodeficiency virus type 1 is the most common cause of HIV infection, which represents one of the most dangerous and complex diseases since it affects the immune system and causes its disruption, leading to secondary complications and negatively influencing health-related quality of life. While highly active antiretroviral therapy may decrease the viral load and the velocity of HIV infection progression, some individual peculiarities may affect viral load control or the progression of T-cell malfunction induced by HIV. Our study is aimed at the text-based identification of molecular mechanisms that may be involved in viral infection progression, using HIV as a case study. Specifically, we identified human proteins and ...
Frontiers in Genetics
Human immunodeficiency virus (HIV) infection remains one of the most severe problems for humanity... more Human immunodeficiency virus (HIV) infection remains one of the most severe problems for humanity, particularly due to the development of HIV resistance. To evaluate an association between viral sequence data and drug combinations and to estimate an effect of a particular drug combination on the treatment results, collection of the most representative drug combinations used to cure HIV and the biological data on amino acid sequences of HIV proteins is essential. We have created a new, freely available web database containing 1,651 amino acid sequences of HIV structural proteins [reverse transcriptase (RT), protease (PR), integrase (IN), and envelope protein (ENV)], treatment history information, and CD4+ cell count and viral load data available by the user’s query. Additionally, the biological data on new HIV sequences and treatment data can be stored in the database by any user followed by an expert’s verification. The database is available on the web at http://www.way2drug.com/rhi...
Current Medicinal Chemistry, 2021
Nowadays, computational approaches play an important role in the design of new drug-like compound... more Nowadays, computational approaches play an important role in the design of new drug-like compounds and optimization of pharmacotherapeutic treatment of diseases. The emerging growth of viral infections, including those caused by the Human Immunodeficiency Virus (HIV), Ebola virus, recently detected coronavirus, and some others lead to many newly infected people with a high risk of death or severe complications. A huge amount of chemical, biological, clinical data is at the disposal of the researchers. Therefore, there are many opportunities to find the relationships between the particular features of chemical data and the antiviral activity of biologically active compounds based on machine learning approaches. Biological and clinical data can also be used for building models to predict relationships between viral genotype and drug resistance, which might help determine the clinical outcome of treatment. In the current study, we consider machine learning approaches in the antiviral r...
Pharmaceutical Chemistry Journal, 2018
A structure-activity relationship model was constructed to predict adverse drug effects on the ca... more A structure-activity relationship model was constructed to predict adverse drug effects on the cardiovascular system. Models were constructed using sets of drug structures compiled by us with information about adverse effects from analyses and data integrated from various sources. The five most common cardiovascular adverse effects, i.e., myocardial infarction, ischemic stroke, cardiac failure, ventricular tachycardia, and arterial hypertension were analyzed in the work. The PASS software that has proved to be efficient in numerous studies was used to construct the appropriate models. The obtained models were accurate enough to be useful for estimating cardiovascular adverse effects of new drugs. An appropriate evaluation could be made in the very early stages of drug discovery because only the structural formula was needed for the prediction.
Biochemistry (Moscow) Supplement Series B: Biomedical Chemistry, 2016
Applicability of our computer programs PASS and PharmaExpert for prediction of biological activit... more Applicability of our computer programs PASS and PharmaExpert for prediction of biological activity spectra of rather complex and structurally diverse phytocomponents of medicinal plants, both separately and in combinations has been evaluated. For this purpose we have created the web-resource containing known information about structural formulas and biological activity of 1906 phytocomponents of 50 Ayurvedic medicinal plants used in Traditional Indian Medicine (TIM) (http://ayurveda.pharmaexpert.ru). The PASS training set was updated by addition of information about structure and biological activity of 946 natural compounds; then the training procedure and validation were performed, to estimate the quality of PASS prediction. It was shown that the differences between the average accuracy of prediction obtained in leave-5%-out cross-validation (94.467%) and in leave-one-out cross-validation (94.605%) are very small thus demonstrating high predictive ability of the program. Results of biological activity spectra prediction for all phytocomponents included in our database coincided in 83.5% of cases with known experimental data. Additional types of biological activity predicted with high probability indicate further promising directions for further studies of certain phytocomponents of some medicinal plants. The analysis of prediction results of sets of phytocomponents in each of 50 medicinal plants was made by the PharmaExpert software. Based on this analysis, we found that the combination of phytocomponents from Passiflora incarnata may exhibit nootropic, anticonvulsant, and antidepressant effects. Experiments carried out in mice models confirmed the predicted effects of P. incarnata extracts.
Due to the directed way of testing chemical compounds' in drug research and development many proj... more Due to the directed way of testing chemical compounds' in drug research and development many projects fail because serious adverse effects and toxicity are discovered too late, and many existing prospective activities remain unstudied. Evaluation of the general biological potential of molecules is possible using a computer program PASS that predicts more than 780 pharmacological effects, mechanisms of action, mutagenicity, carcinogenicity, etc. on the basis of structural formulae of compounds, with average accuracy ∼85%. PASS applications to both databases of available samples included hundreds of thousands compounds, and small collections of compounds synthesized by separate medicinal chemists are described. It is shown that 880 compounds from Prestwick chemical library represent a very diverse pharmacological space. New activities can be found in existing compounds by prediction. Therefore, on this basis, the selection of compounds with required and without unwanted properties is possible. Even when PASS cannot predict very new activities, it may recognize some unwanted actions at the early stage of R&D, providing the medicinal chemist with the means to increase the efficiency of projects.
Quantitative Structure-Activity Relationships, 1998
A new method for substance-to-substance similarity analysis based on topoelectric indices is desc... more A new method for substance-to-substance similarity analysis based on topoelectric indices is described. Prediction accuracy of the method is tested using LOO crossvalidation procedure on 910 biologically active compounds. The results demonstrate high discriminative ability of proposed structure description and measure of similarity. The method is applied to compare the set of synthetic substances with well-known endogenous bioregulators. Average accuracy of active compounds recognition is 76%. Therefore, the proposed topoelectric indices and similarity measure can be used for estimating the synthetic molecules resemblance to small endogenous bioregulators.
Journal of Bioinformatics and Computational Biology, 2008
The functional annotation of amino acid sequences is one of the most important problems in bioinf... more The functional annotation of amino acid sequences is one of the most important problems in bioinformatics. Different programs have been successfully applied for recognition of some functional classes; nevertheless, many functional groups still cannot be predicted with the required accuracy. We developed a new method for protein function recognition using the original approach of sequence description. Each sequence of the training set is compared with the query sequence, and the local similarity scores are calculated for the query sequence positions and used as input data for the original classifier. The method was tested using leave-one-out cross-validation for three data sets covering 58 enzyme classes. Two tested sets including noncrossing functional classes were recognized with high accuracy at various levels of classification hierarchy. The majority of these classes were predicted with 100% accuracy, showing a prediction ability comparable with the HMMer method and an accuracy s...
OMICS: A Journal of Integrative Biology, 2006
We propose a new approach to predict functional specificity of proteins from their amino acid seq... more We propose a new approach to predict functional specificity of proteins from their amino acid sequences. Our approach is based on two things: structural Multilevel Neighborhoods of Atom (MNA) descriptors and an original Bayesian algorithm. Usually, a protein sequence is presented as a string of amino acid symbols. Here we introduce a new description of an amino acid sequence: a set of structural MNA descriptors. The MNA descriptor is a string describing an atom and its neighbor atoms according to the selected level. In this work, we also use description of a protein sequence as a set of peptides (strings of amino acid symbols). We performed a case study on two subsubclasses of enzyme nomenclature (EC). It is shown that B-statistics give a sufficient predictive power of enzyme specificity prediction for both MNA descriptors and peptides. We also showed that MNA descriptors give higher accuracy values in comparison with peptides and also provide a choice of MNA descriptor levels for best accuracy prediction. The highest average accuracy prediction that was achieved was 0.98.