PharmaExpert

PharmaExpert is an analyses tool to study the relationships between biological activities, drug-drug interactions and multiple targeting of chemical compounds and selects compounds that have a pre-defined biological activity. It helps answer a question like “How to select the most promising compounds among those known to interact with the selected protein?”


Example of classification and cause–effect relationships between mechanism of action (5-HT1A agonist) and predicted pharmacological effect (Anxiolytic).

PharmaExpert software

PharmaExpert is an expert system taking into account the known relationships between pharmacotherapeutic effects and mechanisms of action of biologically active substances.

Fields of application: Analysis of the cause-effect relationships between the biological activities, estimation of possible positive and negative pharmacokinetic and pharmacodynamic drug-drug interactions, selection of compounds with the needed activity spectra predicted by PASS, identification of compounds with multiple mechanisms of particular pharmacological action.

PharmaExpert is designed to visualize and to analyze the prediction results of PASS and GUSAR software.

Key features of PharmaExpert

PharmaExpert comprises several analysis tools:

Retrieval and interpretation of the PASS prediction results

  • Reading the SD files containing information about the structures of organic compounds and prediction results of their spectra of biological activity provided by PASS, as well as the prediction results of (Q)SAR models of GUSAR;
  • Visualization of relationships between the predicted biological activities based on the known data about the causal relationships between them, and “target-pathway-effect” relationships.

Search for multitargeted ligands

  • Search of compounds with multitarget actions on the basis of the analysis of PASS prediction results.
  • Multitarget actions may be selected for a list of mechanism of action associated with effects, pathways from KEGG, NCI pathways and Reactome, and also with biological processes from Gene Ontology.

Drug-drug interaction analysis

  • analysis of possible positive and negative drug-drug interactions for individual pairs of compounds or for all compounds contained in the SD file.
  • This tool suggests probable types of drug-drug interactions between two selected structures:
  • Additive or Synergistic effects and actions means that both compounds may lead to the same effect.
  • Pharmacokinetic drug-drug interactions include interaction on metabolism and transport levels. It means that both compounds are a substrate/inhibitor/inducer of the same isoform of drug-metabolizing enzymes or transport proteins;
  • Synergistic toxic and side effects mean that both compounds may lead to the same toxic or side effect;
  • Pharmacodynamic drug-drug interactions mean that both compounds act on the same drug-target.

Biological activities

PharmaExpert 2024 contains a knowledgebase with over 15 thousands of known interactions between biological activities, as well as the relationships between proteins, signalling/regulatory pathways (KEGG or Reactome), Gene Ontology biological processes and therapeutic and adverse effects:

All biological activities are divided onto seven types:

  • mechanisms of action;
  • pharmacological effects;
  • toxic and side effects;
  • interaction with antitargets;
  • interaction with drug metabolizing enzymes (inhibition, induction, interaction as a substrate);
  • changing gene expression of individual genes (increase, decrease);
  • interaction with transporter protein (inhibition, stimulation, interaction as a substrate).

Automatic search is provided for compounds acting on any of the mechanisms of action (or simultaneously on several mechanisms of action, up to ten) associated with the therapeutic effect or signalling/regulatory pathway (KEGG or Reactome) and biological process of Gene Ontology. Analysis of possible drug-drug interactions is performed simultaneously for all seven types of biological activity.

User-friendly interface, fast download speed and analysis of the prediction results of PASS and GUSAR

PharmaExpert results can be exported in SD or TXT file.

Benefits of PASS + PharmaExpert

  • PASS input are 2D structural formular of chemical compounds, and formular of existing or even digital (drawn) compounds can be used
  • PASS calculations are done instantly for a big size compound libraries
  • PASS algorithms are robust and provide stable accuracy of predictions even based on the incomplete training set
  • PASS predicts biological activity spectra for each compound in the library for over 10,000 bioactivities
  • PASS training set (SAR base) is updated regularly, with each release
  • PASS predictions can be focused of the bioactivities of your interest
  • PASS can be used to create your own unique & exclusive SAR base
  • PASS estimates the role of individual atoms and atomic groups into bioactivity
  • PharmaExpert is a unique software taking PASS output and providing new insights based on the unique database of mechanism-effect relationships
  • PharmaExpert identifies multitargeted agents, drug-drug interactions, combinations of compounds with synergistic or additive pharmacological effect(s).
  • PASS + PharmaExpert is a unique software package to identify the putative mechanism of action for drug-like compounds, either of natural or synthetic origin.

Recent application of PASS and PharmaExpert

Bocharova OA, Ionov NS, Kazeev IV, Shevchenko VE, Bocharov EV, Karpova RV, Sheychenko OP, Aksyonov AA, Chulkova SV, Kucheryanu VG, Revishchin AV, Pavlova GV, Kosorukov VS, Filimonov DA, Lagunin AA, Matveev VB, Pyatigorskaya NV, Stilidi IS, Poroikov VV.
Computer-aided Evaluation of Polyvalent Medications’ Pharmacological Potential. Multiphytoadaptogen as a Case Study.
Mol Inform. 2023 Jan;42(1):e2200176.

How to cite PharmaExpert:

Lagunin AA, Goel RK, Gawande DY, Pahwa P, Gloriozova TA, Dmitriev AV, Ivanov SM, Rudik AV, Konova VI, Pogodin PV, Druzhilovsky DS, Poroikov VV.
Chemo- and bioinformatics resources for in silico drug discovery from medicinal plants beyond their traditional use: a critical review.
Nat Prod Rep. 2014 Nov;31(11):1585–611.