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 of side effects of drugs, calculating the integral toxicity of drugs taking into account their metabolism, have been developed in the human body, predicting sustainable and sensitive options strains and evaluating the effectiveness of combinations of antiretroviral drugs in patients, taking into account the molecular genetic characteristics of the clinical isolates of HIV-1. Our computer programs are implemented as the web-services freely available on the Internet, which are used by thousands of researchers from many countries of the world to select the most promising substances for the synthesis and determine the priority areas for experimental testing of their biological activity.
Sozdanie novogo lekarstvennogo preparata baziruetsia na analize izvestnoĭ informatsii o mekhanizmakh vozniknoveniia zabolevaniia, molekuliarnykh misheniakh i ligandakh, vzaimodeĭstvie kotorykh s opredelennymi misheniami mozhet okazat' terapevticheskiĭ éffekt. Imeiushchiesia svedeniia o bolezniakh, lekarstvakh, farmakologicheskikh éffektakh, molekuliarnykh misheniakh i lekarstvenno-podobnykh veshchestvakh s uchetom kombinatoriki assotsiativnykh sviazeĭ mezhdu nimi sootvetstvuiut kategorii “Bol'shikh dannykh” (Big Data), analiz kotorykh trebuet primeneniia metodov komp'iuternogo konstruirovaniia lekarstv. Dannyĭ obzor obobshchaet raboty kollektiva laboratorii strukturno-funktsional'nogo konstruirovaniia lekarstv Nauchno-issledovatel'skogo instituta biomeditsinskoĭ khimii imeni V.N. Orekhovicha v étoĭ oblasti. Nami razrabotany podkhody k identifikatsii perspektivnykh farmakologicheskikh misheneĭ, predskazaniiu odnovremenno mnogikh tysiach vidov biologicheskoĭ aktivnosti po strukturnoĭ formule soedineniia, analizu belok-ligandnykh vzaimodeĭstviĭ na osnove otsenki lokal'nogo skhodstva aminokislotnykh posledovatel'nosteĭ, vyiavleniiu veroiatnykh molekuliarnykh mekhanizmov pobochnogo deĭstviia lekarstvennykh preparatov, raschetu integral'noĭ toksichnosti lekarstvennykh soedineniĭ s uchetom ikh metabolizma v organizme cheloveka, predskazaniiu ustoĭchivykh i chuvstvitel'nykh variantov shtammov i otsenke éffektivnosti kombinatsiĭ antiretrovirusnykh preparatov u patsientov s uchetom molekuliarno-geneticheskikh osobennosteĭ klinicheskikh izoliatov VICh-1. Razrabotannye nami metody realizovany v vide svobodno-dostupnykh v seti Internet veb-servisov, kotorye ispol'zuiutsia tysiachami issledovateleĭ iz mnogikh stran mira s tsel'iu otbora naibolee perspektivnykh veshchestv dlia sinteza i opredeleniia prioritetnykh napravleniĭ éksperimental'nogo testirovaniia ikh biologicheskoĭ aktivnosti.
Keywords: bioinformatics; chemical-biological interactions; chemoinformatics; ligand-based drug design; systems pharmacology.