Prediction of biological activity spectra via the Internet

The majority of biologically active compounds have both pharmacotherapeutic and side/toxic actions. To estimate general efficacy and safety of the molecules under study, their biological potential should be thoroughly evaluated. In an early stage of study, only information about structural formulae was available and was used as an input for computational prediction. Based on a structural formulae of compounds presented as SDF or MOL-files, computer program PASS predicts 900 pharmacological effects, mechanism of action, and specific toxicity. An average accuracy of prediction in leave-one-out cross-validation is about 85%. For evaluating new compounds, scientific community may use PASS via the Internet for free at URL: http://www.ibmh.msk.su/PASS. In the first 18 months of PASS Inet's use, approximately 1000 researchers from 60 countries have obtained predicted biological activity spectra for about 23,000 different chemical compounds. More than 64 million PASS predictions for almost 250,000 compounds from Open NCI database are available on the web site http://cactus.nci.nih.gov/ncidb2/. These predictions are used for selecting compounds with desirable and without unwanted types of biological activities among the NCI samples available for screening.     

Computer-aided prediction for medicinal chemistry via the Internet1

Some computational tools for medicinal chemistry freely available on the Internet were compared to examine whether the results of prediction obtained with different methods coincided or not. It was shown that the correlation coefficients varied from 0.65 to 0.90 for log P (seven methods), from 0.01 to 0.73 for aqueous solubility (four methods), and from 0.19 to 0.73 for drug-likeness (three methods). While for log P estimates, reasonable average pairwise correlation was found, for aqueous solubility and drug-likeness it was rather poor. Therefore, using computational tools freely available via the Internet, medicinal chemists should evaluate their accuracy versus experimental data for particular series of compounds. In contrast to prediction of above mentioned properties, which can be done with several Internet tools, wide profiling of biological activity can be obtained only with PASS Inet (http://www.ibmc.msk.ru/PASS). PASS Inet was tested by a dozen medicinal chemists for compounds from different chemical series with various kinds of biological activity, and in the majority of cases the results of prediction coincided with the experiments. New anxiolytics, antiarrhythmics, antileishmanials, and other biologically active agents have been identified on this basis. The advantages and limitations of computer-aided predictions for medicinal chemistry via the Internet are discussed.     

PASS biological activity spectrum predictions in the enhanced open NCI database browser

The application of the program PASS (Prediction of Activity Spectra for Substances) to about 250 000 compounds of the NCI Open Database and the incorporation of over 64 million PASS predictions in the Enhanced NCI Database Browser are described. A total of 565 different types of activity are included, encompassing general pharmacological effects, specific mechanisms of action, known toxicities, and others. Application of this Web-based service to prediction of activities of the kinds "Angiogenesis inhibitor," "Antiviral (HIV)", and a set of activities that can be associated with antineoplastic action are reported. For this latter data set, a very substantial enrichment over random selection was found in the PASS predictions. It is shown how the user can conduct complex searches by combining ranges of PASS-predicted probabilities of compounds to be active or to be inactive, respectively, with, e.g., value ranges of physicochemical parameters, presence or absence of particular substructural fragment, and other search criteria.     

Boesenbergia Pandurata Roxb., An Indonesian Medicinal Plant: Phytochemistry,Biological Activity,Plant Biotechnology

Boesenbergia pandurata Roxb. (Zingiberaceae), known as “temu kunci”, is one of the Indonesian medicinal plants. Its rhizome has been traditionally used in folk medicine for treatment of several diseases. Rhizome of B. pandurata contains essential oils and many flavonoid compounds that showed many interesting pharmacological activities, such as antifungal, antibacterial, antioxidant, etc. Interestingly, this plant has several prenylated flavonoid compounds, panduratins, that showed very promising of biological activities, especially as strong antifungal and antibacterial, anti-inflammatory, and anti-cancer. This paper aims to review chemical constituents of this plant and their pharmacological activities and also to give a brief view through biotechnological perspective concerning the several possibilities to produce several valuable prenylated flavonoids from this plant.     

Multiple biological functions and pharmacological effects of lycorine

Lycorine is the major active component from the amaryllidaceae family plant Lycoris radiate, a represent traditional Chinese medicinal herb, and is one of the typical alkaloids with pyrrolophenanthridine nucleus core. Lycorine has drawn great interest in medicinal field due to its divergent chemical structures and multiple biological functions, as well as pharmacological effects on various diseases. Accumulated evidence shows that lycorine not only possesses strong pharmacological effects on many diseases, including anti-leukemia, anti-tumor, anti-angiogenesis, anti-virus, anti-bacteria, anti-inflammation, and antimalaria, but also exerts many other biological functions, such as inhibition of acetylcholinesterase and topoisomerase, suppression of ascorbic acid biosynthesis, and control of circadian period length. Notably, lycorine exhibits its numerous pharmacological effects on various diseases with very low toxicity and mild side effects. The divergent chemical structures, multiple biological functions, and very low toxicity of lycorine imply that the agent is a potential drug candidate that warrants for further preclinical and clinic investigation.     

Prediction of biological activity profiles of cyanobacterial secondary metabolites

Over the past decade cyanobacteria have become an interesting source of new classes of pharmacologically active natural products. Some cyanobacterial secondary metabolites (CSMs) are also well known for their toxic effects on living species. The PASS (Prediction of Activity Spectra for Substances) computer program, which is able to simultaneously predict more than one thousand biological and toxicological activities from only the structural formulas of the chemicals, was used to predict the biological activity profile of 681 CSMs. Multivariate methods were employed to structure and analyse this wealth of biological and chemical information. PASS predictions were successfully compared to the available information on the pharmacological and toxicological activity of these compounds.     

PASS: identification of probable targets and mechanisms of toxicity†

Toxicity of chemical compound is a complex phenomenon that may be caused by its interaction with different targets in the organism. Two distinct types of toxicity can be broadly specified: the first one is caused by the strong compound's interaction with a single target (e.g. AChE inhibition); while the second one is caused by the moderate compound's interaction with many various targets. Computer program PASS predicts about 2500 kinds of biological activities based on the structural formula of chemical compounds. Prediction is based on the robust analysis of structure-activity relationships for about 60,000 biologically active compounds. Mean accuracy exceeds 90% in leave-one-out cross-validation. In addition to some kinds of adverse effects and specific toxicity (e.g. carcinogenicity, mutagenicity, etc.), PASS predicts ～2000 kinds of biological activities at the molecular level, that providing an estimated profile of compound's action in biological space. Such profiles can be used to recognize the most probable targets, interaction with which might be a reason of compound's toxicity. Applications of PASS predictions for analysis of probable targets and mechanisms of toxicity are discussed.     

PASS: identification of probable targets and mechanisms of toxicity

Toxicity of chemical compound is a complex phenomenon that may be caused by its interaction with different targets in the organism. Two distinct types of toxicity can be broadly specified: the first one is caused by the strong compound's interaction with a single target (e.g. AChE inhibition); while the second one is caused by the moderate compound's interaction with many various targets. Computer program PASS predicts about 2500 kinds of biological activities based on the structural formula of chemical compounds. Prediction is based on the robust analysis of structure-activity relationships for about 60,000 biologically active compounds. Mean accuracy exceeds 90% in leave-one-out cross-validation. In addition to some kinds of adverse effects and specific toxicity (e.g. carcinogenicity, mutagenicity, etc.), PASS predicts approximately 2000 kinds of biological activities at the molecular level, that providing an estimated profile of compound's action in biological space. Such profiles can be used to recognize the most probable targets, interaction with which might be a reason of compound's toxicity. Applications of PASS predictions for analysis of probable targets and mechanisms of toxicity are discussed.     

Plant Secondary Metabolites Produced in Response to Abiotic Stresses Has Potential Application in Pharmaceutical Product Development

Plant secondary metabolites (PSMs) are vital for human health and constitute the skeletal framework of many pharmaceutical drugs. Indeed, more than 25% of the existing drugs belong to PSMs. One of the continuing challenges for drug discovery and pharmaceutical industries is gaining access to natural products, including medicinal plants. This bottleneck is heightened for endangered species prohibited for large sample collection, even if they show biological hits. While cultivating the pharmaceutically interesting plant species may be a solution, it is not always possible to grow the organism outside its natural habitat. Plants affected by abiotic stress present a potential alternative source for drug discovery. In order to overcome abiotic environmental stressors, plants may mount a defense response by producing a diversity of PSMs to avoid cells and tissue damage. Plants either synthesize new chemicals or increase the concentration (in most instances) of existing chemicals, including the prominent bioactive lead compounds morphine, camptothecin, catharanthine, epicatechin-3-gallate (EGCG), quercetin, resveratrol, and kaempferol. Most PSMs produced under various abiotic stress conditions are plant defense chemicals and are functionally anti-inflammatory and antioxidative. The major PSM groups are terpenoids, followed by alkaloids and phenolic compounds. We have searched the literature on plants affected by abiotic stress (primarily studied in the simulated growth conditions) and their PSMs (including pharmacological activities) from PubMed, Scopus, MEDLINE Ovid, Google Scholar, Databases, and journal websites. We used search keywords: “stress-affected plants,” “plant secondary metabolites, “abiotic stress,” “climatic influence,” “pharmacological activities,” “bioactive compounds,” “drug discovery,” and “medicinal plants” and retrieved published literature between 1973 to 2021. This review provides an overview of variation in bioactive phytochemical production in plants under various abiotic stress and their potential in the biodiscovery of therapeutic drugs. We excluded studies on the effects of biotic stress on PSMs.     

Computer-aided prediction for medicinal chemistry via the Internet

Some computational tools for medicinal chemistry freely available on the Internet were compared to examine whether the results of prediction obtained with different methods coincided or not. It was shown that the correlation coefficients varied from 0.65 to 0.90 for log P (seven methods), from 0.01 to 0.73 for aqueous solubility (four methods), and from 0.19 to 0.73 for drug-likeness (three methods). While for log P estimates, reasonable average pairwise correlation was found, for aqueous solubility and drug-likeness it was rather poor. Therefore, using computational tools freely available via the Internet, medicinal chemists should evaluate their accuracy versus experimental data for particular series of compounds. In contrast to prediction of above mentioned properties, which can be done with several Internet tools, wide profiling of biological activity can be obtained only with PASS Inet (http://www.ibmc.msk.ru/PASS). PASS Inet was tested by a dozen medicinal chemists for compounds from different chemical series with various kinds of biological activity, and in the majority of cases the results of prediction coincided with the experiments. New anxiolytics, antiarrhythmics, antileishmanials, and other biologically active agents have been identified on this basis. The advantages and limitations of computer-aided predictions for medicinal chemistry via the Internet are discussed.     

Synthesis and biological properties of 1,8‐naphthalimidebutylamines. Serotonin 5‐HT1A and 5‐HT7 binding data and pass‐assisted search

Syntheses of the N‐substituted butyl derivatives of 1,8‐naphthalimide ( 1‐8 ), containing various arylpiperazines, tetrahydroisoquinoline and methylhomopiperazine moieties attached at 4‐position of the butyl chain have been described. Biological activities were evaluated in vitro for their ability to bind to serotonin 5‐HT_1A and 5‐HT₇ receptors. Due to the structural similarity of derivatives 1‐8 to psychotropic agents, the pharmacological properties of target compounds were predicted using PASS program.     

Current trends in lead discovery: are we looking for the appropriate properties?

The new drug discovery paradigm is based on high-throughput technologies, both with respect to synthesis and screening. The progression HTS hits lead series candidate drug marketed drug appears to indicate that the probability of reaching launched status is one in a million. This has shifted the focus from good quality candidate drugs to good quality leads. We examined the current trends in lead discovery by comparing MW (molecular weight), LogP (octanol/water partition coefficient, estimated by Kowwin [17]) and LogSw (intrinsic water solubility, estimated by Wskowwin [18]) for the following categories: 62 leads and 75 drugs [11]; compounds in the development phase (I, II, III and launched), as indexed in MDDR; and compounds indexed in medicinal chemistry journals [ref. 20], categorized according to their biological activity. Comparing the distribution of the above properties, the 62 lead structures show the lowest median with respect to MW (smaller) and LogP (less hydrophobic), and the highest median with respect to LogSw (more soluble). By contrast, over 50% of the medicinal chemistry compounds with activities above 1 nanomolar have MW > 425, LogP > 4.25 and LogSw < -4.75, indicating that the reported active compounds are larger, more hydrophobic and less soluble when compared to time-tested quality leads. In the MDDR set, a progressive constraint to reduce MW and LogP, and to increase LogSw, can be observed when examining trends in the developmental sequence: phase I, II, III and launched drugs. These trends indicate that other properties besides binding affinity, e.g., solubility and hydrophobicity, need to be considered when choosing the appropriate leads.     

Computer aided prediction of biological activity spectra: Evaluating versus known and predicting of new activities for thiazole derivatives

Computer aided prediction of biological activity spectra by the computer program PASS was applied to a set of 89 new thiazole derivatives. Experimentally tested activities (NSAID, local anaesthetic and antioxidant) coincide with the experiment in 70.8% cases, that exceeds significantly the random guess-work (～0.1%). Therefore, computer aided prediction using the Prediction of Activity Spectra for Substances (PASS) system (http://www.ibmh.msk.su/PASS) provides a reliable basis for planning of synthesis and experimental study for new compounds. New psychotropic activities are predicted for some compounds from the series under study. In particular, 7, 44 and 55 compounds likely have anxiolytic, anticonvulsant and cognition enhancer effects, respectively. Most of these compounds have the estimated values of probability to be active ( P a ) less than 60%. Therefore, if their activity will be confirmed by the experiment, they might occur to be New Chemical Entities.     

Physical basis of the reactivity of carbonyl compounds

Summary By comparison of physical and chemical data an individual characteristic bonds it is shown that the chemical nature of these bonds is dependent on their physical state(the electron-nucleus interactions in them), which is manifested in the experimentally determined parameters of these bonds , E, and r. Taking carbonyl compounds as an example, we have shown that from the strictly correlated changes in these parameters in characteristic bonds it is possible to make an estimate, on an experimental basis, of the electron displacements in the bonds as factors determining the reactivities of these bonds and as factors expressing the structure of the molecule and the mutual effects of its atoms.     

Computer aided prediction of biological activity spectra: evaluating versus known and predicting of new activities for thiazole derivatives

Computer aided prediction of biological activity spectra by the computer program PASS was applied to a set of 89 new thiazole derivatives. Experimentally tested activities (NSAID, local anaesthetic and antioxidant) coincide with the experiment in 70.8% cases, that exceeds significantly the random guess-work (approximately 0.1%). Therefore, computer aided prediction using the Prediction of Activity Spectra for Substances (PASS) system (http://www.ibmh.msk.su/PASS) provides a reliable basis for planning of synthesis and experimental study for new compounds. New psychotropic activities are predicted for some compounds from the series under study. In particular, 7, 44 and 55 compounds likely have anxiolytic, anticonvulsant and cognition enhancer effects, respectively. Most of these compounds have the estimated values of probability to be active (Pa) less than 60%. Therefore, if their activity will be confirmed by the experiment, they might occur to be New Chemical Entities.     

Synthesis,characterization and pharmacological investigations of some novel heterocyclic derivatives incorporating pyrene and sugar moieties

A series of substituted pyrene derivatives 2–15 incorporated heterocyclic and sugar moieties were synthesized and evaluated as antiviral activities using 1-acetylpyrene as a starting material. The structure assignment of the new compounds was based on chemical and spectroscopic evidence. The detailed synthesis, spectroscopic data and pharmacological activities of the synthesized compounds were reported.     

Synthesis of new imidazole derivatives

The derivatives of 1‐propyl‐ and 1‐butyl‐ of 2‐methyl‐5‐nitroimidazole containing phenylpiperazine, m‐chloro‐ and o‐methoxyphenylpiperazine attached at the end of alkyl chain were synthesed. For the obtained new compounds, the biological activity was predicted using the computer program PASS.     

Top 200 Medicines: Can New Actions be Discovered Through Computer-aided Prediction?

Abstract

Computer-aided prediction of the biological activity spectra by the program PASS was applied to a set of 130 pharmaceuticals from the list of the Top 200 medicines. The known pharmacological effects were found in the predicted activity spectra in 93.2% of cases. Additionally, the probability of some supplementary effects was also predicted to be significant, including angiogenesis inhibition, bone formation stimulation, possible use in cognition disorders treatment, multiple sclerosis treatment, etc. These predictions, if confirmed experimentally, may become a cause for a new application of pharmaceuticals from the Top 200 list. Most of known side and toxic effects were also predicted by PASS. PASS predictions at earlier R&D stages may thus provide a basis for finding new “leads” among already launched drugs and may help direct more attention to those particular effects of pharmaceuticals in clinical use which become apparent only in a small part of the population and require additional precautions.     

Biological activity of bicyclic and tricyclic diterpenoids from Salvia species of immediate pharmacological and pharmaceutical interest

Diterpenoids are a class of compounds that derive from the condensation of four isoprene units that leads to a wide variety of complex chemical structures, including acyclic bi-, tri-and tetra-cyclic compounds; in Salvia species, only bi-, tri-and tetra-cyclic compounds have been found. This review covers a wide range of biological activities and mode of action of diterpenoids isolated from Salvia species that might raise some pharmacological and pharmaceutical interest. We have produced a synoptic table where the biological activities of the main active principles are summarized. Our analysis emphasizes that diterpenoids from Salvia species continue to be a plant defence system since their antimicrobic activity. Experimental studies show that most of diterpenoids considered have cytotoxic and/or antiproliferative activity. Some of them have also cardiovascular and central effects. In a less extended manner, diterpenoids from Salvia species show gastrointestinal, urinary, antinflammatory, antidiabetic, ipolipidemic and antiaggregating effects. In the last decade, several clinical trials have been developed in order to investigate the real value of Salvia extracts treatment; results obtained are promising and confer scientific basis in the use of medicinal plants from folk medicine.     

Diversified Synthetic Strategies for Pyrroloindoles: An Overview

In current scenario, heterocyclic compounds' role in medicinal chemistry has been tremendously increased as they possess wide number of pharmacological activities. One of the common heterocycles include indole skeleton with well‐established biological significance in field of medicinal chemistry. Fusion of indole nucleus with pyrrole heterocycle constitutes pyrroloindole scaffold, which further modifies the existing properties of indole alone. Pyrroloindole is a privileged scaffold found in various types of bioactive entities including natural compounds and exhibits wide variety of pharmacological activities like muscle relaxant, antifungal, antitumor, and antibiotic. Therefore, it is considered as attractive template for drug discovery. From several years, numbers of synthetic strategies have been reported for the synthesis of pyrroloindole and its derivatives, including also natural compounds such as amauromine, yuremamine, and chimonanthines. Here, in this review, we have tried to compile various synthetic strategies of pyrroloindole and its derivatives.