Computational Pharmacology: Advances in Computational Modeling of Drug–Receptor Interactions and Pharmacokinetics

Dear Colleagues,

Drug–receptor interactions and pharmacokinetics are fundamental aspects of pharmacology, playing crucial roles in various therapeutic processes, notably including drug efficacy, adverse effects, and personalized medicine. Understanding these interactions is essential for elucidating the molecular mechanisms of drug action, optimizing therapeutic outcomes, and developing novel pharmacological agents. Experimental techniques such as in vitro binding assays, pharmacokinetic studies in animal models, and clinical trials, and most recently, high-throughput screening and structure-based approaches, are commonly used to investigate drug behavior and characterization. However, these techniques are notably limited by their inability to capture the dynamic, atomistic-level processes governing drug binding, metabolism, and distribution over time. To address this limitation, computational analysis and pharmacokinetic modeling offer powerful tools for predicting drug-receptor affinities, simulating absorption–distribution–metabolism–excretion (ADME) profiles, and exploring therapeutic windows. Augmenting experimental methods, computational analysis, and modeling techniques uncover critical insights that advance our understanding of drug action and pharmacokinetics. Augmenting experimental methods with computational analysis and modeling techniques uncovers critical insights that advance our understanding of drug action and pharmacokinetics. Accordingly, we encourage submissions to include experimental validations to ensure the robustness of the computational methods.

This Special Issue highlights and disseminates cutting-edge research in computational analysis and modeling of drug–receptor and other intermolecular interactions, including bioactive peptide-, peptoid-, protein-, and lipid-based interactives and their pharmacokinetics.

Thematic areas of interest include, but are not limited to, the following:

• Strengths and limitations of current computational analysis and modeling techniques for investigating drug–receptor and other intermolecular interactions (e.g., drug–enzyme, drug–nucleic acid, protein–protein, and protein–lipid interactions), bioactive peptide–protein and peptoid–target interactions, and pharmacokinetic properties.
• Integration of experimental and computational approaches to validate drug binding affinities, characterize key noncovalent and lipid-mediated interactions, improve pharmacokinetic predictions, and provide a comprehensive understanding of drug action and therapeutic response.
• Artificial intelligence and machine learning-based approaches for predicting multi-target and multi-interaction drug–target relationships, peptidomimetic and peptoid activities, toxicity, efficacy, and pharmacokinetic behaviors.
• Molecular dynamics simulations and computational modeling to explore drug dynamics, lipid bilayer interactions, membrane permeability, intermolecular interaction stability, binding kinetics, and conformational changes in receptor–ligand complexes.
• Molecular docking, pharmacophore modeling, and quantitative structure–activity relationship (QSAR) techniques for studying drug–receptor, drug–transporter, drug–enzyme, drug–nucleic acid, drug–lipid, bioactive peptide–protein, peptoid–protein, and drug–metabolite interactions.
• Applications of computational methods in drug discovery and design targeting complex biomolecular interaction networks, receptor-mediated pathways, and optimizing ADME profiles.

We cordially invite investigators to contribute high-quality original research and review articles that cover any relevant topics that advance our understanding of drug–receptor, lipid-mediated, peptoid–target, and other intermolecular interactions, as well as pharmacokinetics, through computational analysis and modeling. By bringing together diverse perspectives and methodologies, this Special Issue aims to drive innovation in the field and facilitate the development of new pharmacological strategies for improved patient outcomes.

Dr. Clement Agoni
Dr. Indrani Bera
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomolecules is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.