Drug transporters (DTs) are acknowledged as important determinants governing drug absorption, excretion, and, in many cases, extent of drug entry into target organs (Annu Rev Pharmacol Toxicol. 2012, 52: 249-73). The variability of DTs has thus attracted considerable attentions and broad interests (Nat Rev Drug Discov. 2015, 14: 29-44; Clin Pharmacol Ther. 2019, doi: 10.1002/cpt.1373; Ann Oncol. 2013, 24: 1513-25). There are three aspects of variability: (1) epigenetic regulations and genetic polymorphisms of DTs playing key role in drug resistance (Sci Transl Med. 2016, 8: 348ra97) and clinical treatment optimization (Adv Drug Deliv Rev. 2017, 116: 21-36); (2) species-, tissue-, and disease-specific abundances of DT proteins essential for bridging preclinical study with clinical trial (Mol Pharm. 2015, 12: 4259-69), balancing efficacy and safety (Sci Transl Med. 2016, 8: 352ra109), and predicting disease-drug interaction (Clin Pharmacol Ther. 2018, 104: 900-15), respectively; (3) exogenous factors modulating activity of DTs and leading to the altered disposition of natural substrates and the transported drugs (Adv Drug Deliv Rev. 2015, 86: 17-26; Clin Pharmacol Ther. 2016, 100: 259-67). These variability data are vital for the clinical studies, and the accumulation of such data can lay the foundation for big data-driven precision medicine.

Moreover, due to the extreme complexity of drug dispositions in living organisms, the interplays among different aspects of DT variability have recently emerged to be a new promising research direction of high-impact studies (Drug Resist Updat. 2017, 32: 23-46; Cancer Lett. 2016, 370: 153-64). Particularly, one of the common mechanisms of the cancer multidrug resistance (MDR) is the overexpression of the particular DTs in cancer cells (Cancer Lett. 2016, 370: 153-64), and the developments of exogenous chemical to inhibit the efflux of these DTs are successfully proposed to reverse caner MDR (Drug Resist Updat. 2017, 32: 23-46; Cancer Lett. 2016, 370: 153-64). These and other potential studies require the collectively analyses of multiple data among different aspects of DT variability. However, no database has been available so far to provide the comprehensive information of all aspects of DT variability.

Therefore, the Variability of Drug Transporter Database (VARIDT) was introduced. First, a comprehensive literature review on all drugs approved by U.S. FDA and >1,000 drugs in clinical trial or preclinical research was conducted. Different from the small amount of DTs (~20) well characterized in previous work (Nat Rev Drug Discov. 2010, 9: 215-36), 177 DTs were confirmed for the first time in VARIDT to transport approved drug(s) and 146 DTs were to transport the drug(s) in clinical/preclinical test. Second, for these hundreds of newly confirmed DTs, the VARIDT not only comprehensively provided all three aspect of their variability data but also allowed the mutual connection (interplay) between any two aspects. All in all, the VARIDT is UNIQUE in (1) covering the largest number of DTs confirmed by their corresponding drugs among available knowledge bases, (2) providing for the first time the comprehensive sets of DT variability data, and (3) allowing the interplay analysis among different aspects of DT variability. All diseases in VARIDT were standardized using the latest revision of International Classification of Diseases (ICD-11) to serve comprehensive health management, and the vast majority (~80%) of the confirmed DTs in VARIDT had the data from multiple aspects of variability, which allowed interplays among these aspects. All data are FULLY DOWNLOADABLE .

DT variability is reported to be critical for balancing drug efficacy with safety (Sci Transl Med. 2016, 8: 352ra109), reversing drug resistance (Sci Transl Med. 2016, 8: 348ra97), and predicting drug-drug interaction (Adv Drug Deliv Rev. 2015, 86: 17-26; Br J Pharmacol. 2019, 176: 4558-4573; Chin Med. 2020, 15: 71). Recently, there are increasing demands on the three-dimensional structural variability data of DT, which are expected to provide key information for the studies on precision medicine and rational drug use (Nature. 2019, 576: 315-320). Such data include: (a) the mutation-induced spatial variations in folded state that are critical for the understanding of drug sensitivity and selectivity (Proc Natl Acad Sci U S A. 2019, 116: 8960-8965), (b) the difference among the DT structures of human and model organisms that are key for bridging preclinical study with clinical trials (Science. 2019, 363: 753-756), (c) the outward-facing and inward-facing conformations that are essential for elucidating the dynamics and underlying steps of transporting cycle (Proc Natl Acad Sci U S A. 2019, 116: 12275-12284), and (d) the xenobiotics-driven alterations in 3D complexes of DT that are crucial for revealing the mechanism underlying drug-drug interaction (Elife. 2020, 9: e56427; Oxid Med Cell Longev. 2021, 15: 7467156; Chin J Nat Med. 2019, 17: 490-497). These structure variability data would be indispensable for explaining drug sensitivity and selectivity, bridging preclinical research with clinical trial, revealing the mechanism underlying drug-drug interaction, and so on.

Therefore, the structural variability data of DTs were collected and described in VARIDT. First, the experimental structures of all DTs reported in VARIDT were systematically discovered from PubMed and Protein Data Bank. Furthermore, due to the lack of DTs’ structures and their structural variability data, homology modeling is applied as a well-established protocol to construct protein structure (Nat Methods. 2015, 12: 747-750). Four types of DTs’ structural variability data were provided in VARIDT, which included both the experimentally resolved structures and the variability of DT structures generated by homology modeling: (a) 145 mutation-induced structures originating from 42 DTs were collected, (b) 1,622 inter-species structures from 17 species (human, rat, mouse, dog, zebrafish, rabbit, bovine, pig, chicken, sheep, fruit fly, frog, orangutan, monkey, guinea pig, horse, hamster) covering 292 DTs were described, (c) 118 outward/inward-facing conformations belonging to 59 DTs were provided, and (d) 822 xenobiotics-regulated structures of 506 xenobiotics in complex with 57 DTs were collected and described. A total of 292 DTs with at least one type of structure variability data were provided in the latest version of VARIDT, which were closely related to the transportation of 751 drugs (including 508 approved & 243 clinical/preclinical drugs) for the treatment of 259 disease classes (such as coronavirus infections, lung cancer, diabetes mellitus, depression, parkinsonism, hypertension, and asthma) as defined by the latest WHO International Classification of Diseases (Lancet. 2019, 393: 2275). All structure variability data can be viewed, assessed, and downloaded from VARIDT, which is freely assessable without login requirement.

Users can identify entries by searching transporter protein name, transporter gene name, transporter family name, drug name, disease/disease class name of the transported drug, International Classification of Diseases (ICD) code, and so on among the entire textual component of VARIDT. Query can be submitted by entering keywords into the main searching frame. Users can specify part/full drug name, DT name or any other related information in the text field. Moreover, user can search by put drug, DT or other information together into text field (separated by space or tab) for narrowing output results. To facilitate a more customized input query, the wild characters of "*" and "?" are fully supported in VARIDT. For example:

1. If search: "ABCG2", finds only ERD entry with DT name "ABCG2"

2. If search: "Oxaliplatin", finds three ERD entries of three DTs transporting "Oxaliplatin"

3. If search: "Influenza", finds six ERD entries of six DTs transporting "Influenza" drugs

4. If search: "Multidrug and toxin extrusion protein?", finds ERD entry of the DT "Multidrug and toxin extrusion protein 1". Here, "?" represents any one character

5. If search: "Multidrug and toxin *", finds the same entry as above. Here "*" represents a string of any length. In this case, it represents "extrusion protein 1"

For example, if you want to know the detail information of organic anion transporter 1 (SLC22A6), you can search it's transporter information by searching "organic anion transporter 1 (SLC22A6)" in the "Search for Drug Transporter Entries:" field of the home page.

Users can identify entries among the entire textual component of VARIDT by selecting a DT name, DT family name, drug name, xenobiotic name, exogenous factor name, model organism name or ICD-11 defined disease class name from the corresponding drop-down lists.

(a) The drop-down list of DT name (gene name: DT protein name) contains DTs that are confirmed by at least one drug transported by these DTs; (b) The drop-down list of DT family name (family full name (abbreviation)) contains protein families that are occupied by all DTs in this section; (c) The drop-down list of drug name contains drugs that have been approved or in clinical/preclinical studies; (d) The drop-down list of DT xenobiotic name contains xenobiotics that driven DT structural alterations in 3D complexes, (e) The drop-down list of exogenous factor name contains a various of distinct exogenous factors; (f) The drop-down list of model organism name contains 16 species (rat, mouse, dog, zebrafish, rabbit, bovine, pig, chicken, sheep, fruit fly, frog, orangutan, monkey, guinea pig, horse, hamster); (g) The drop-down list of ICD-11 defined disease class (ICD-11 code: disease class name) contains distinct disease classes. To accelerate the ERD identification process, these drop-down lists are alphabetically sorted (A-Z). Contrary to the field of "Search for the Epigenetic Regulations of Drug Transporter (ERD)", these drop-down lists search the keyword by the EXACT matching instead of the fuzzy one.

For example, searching "OAT1: Organic anion transporter 1" in the "Search Drug Transporter by Transporter Name:" drop-down list.

DT is known as the key determinant of drug absorption, distribution, clearance, and elimination (Annu Rev Pharmacol Toxicol. 2012, 52: 249-73). This section provides various general information, variability data (general variability data and structural variability data), and molecular transporting profile (drugs, endogenous, and affinity data) of DTs.

For example, searching "P-glycoprotein 1" in the " Search for Drug Transporter Entries:" field of the home page.

The search result lists transporter with transporter information. In this page, the Transporter Info button links to the Drug Transporter (DT) Information page and the Drug Info button links to the Representative Drug/Compound Information.

In the Drug Transporter (DT) Information page, "General Information of DT" section displays a various of general information of P-GP, such as namds, DT family, structural model, function, Diseases, endogenous substrates, and so on.

The “Variability Data of This DT” section contains general and structural variability data. Three aspects of general variability data of P-GP along with the hyperlink to (a) Epigenetic Regulations of DT (ERD), (b) Genetic Polymorphisms of DT (GPD), (c) Disease-specific Protein Abundances of DT (DPAD), (d) Species/Tissue-specific Protein Abundances of DT (S/TPAD), and (e) Exogenous Factors (drugs, dietary constituents, natural products, etc.) Modulating DT Activity (EFMDA). The structural variability data of P-GP contain (a) Mutation-induced Structural Variation (MSV), (b) Inter-species Structural Differences (ISD), (c) Outward/inward-facing Conformation (OIC), and (d) Xenobiotics-regulated Structural Variability (XSV). The regulatory variability data of P-GP contain (a) Microbiota Influence (MBI), (b) Post-translational Modification (PTM), and (c) Transcriptional Regulation variation (TSR).

The “Molecular Transporting Profile of This DT” shows the related drugs, endogenous, and affinity data. The brief information (drug name, indication and highest status) of drugs which are transported by P-GP is displayed by a list and the drugs are classified by its highest status.

The Drug Info button links to the drug information in more detail, including names, 3D and 2D structures, therapeutic class, etc.

In this page, the "Drug-DT Affinity Assessed by Cell Line" section displays the drugs with drug-DT affinity data, which is constructed by drug name, cell line and Km value.

Regulations of drug transporters (DTs) have attracted extensive attentions in recent years, and a variety of regulations have been found to significantly modify the ADME property of a drug by inducing substantial variabilities on the corresponding DT (Pharmacol Ther. 2021, 217: 107647; Physiol Rev. 2022, 102: 993-1024; Clin Pharmacol Ther. 2022, 112: 461-484). A major update of VARIDT was conducted, which systematically described all three aspects of DT regulatory variability: (a) the microbiota influence of DTs, (b) the post-translational modification of DTs, (c) the transcriptional regulation of DTs, (d) the epigenetic regulation of DTs, and (e) the exogenous modulation of DTs.

The microbiota influence (MBI) of DTs is essential for understanding in-vivo transportation of drugs among various organs (Nature. 2021, 597: 533-538). In this section, a total of 2,072 MBI data between 124 microbe or its related proteins/compounds and 145 DTs was described.

For example, selecting "Multidrug resistance-associated protein" in the "Search for Microbiota Influence of Drug Transporter (MBI)" box.

The MBI Info button links to the Detail Information of Microbiota Influence page, and more MBI information is provided.

The “General Information of Drug Transporter (DT)” and “Microbiota Influence of This DT (MBI)” sections are displayed in this page. Below the latter, the first image shows all the microbe families, genes, and species that can regulate this DT.

The genus and species of microbes are provided behind. User can click on the column where the species name is located to show/hide the full list microbe regulations related to it.

For example, when click on the column of Clostridium sporogenes, relevant regulation mechanism, regulation factor, studied phenotype/tissue and in vivo/vitro model information will be presented. In the end, there will be a detailed description of how the species regulates the transporter.

It should be noted that the impact of MBI on DT may be achieved through certain specific regulatory mechanisms. In VARIDT, the specific mechanisms of the impact of literature on reported MBI are included and provided on the webpage, highlighted in bold. Users can also click the corresponding button to jump to the specific page of the regulatory mechanism.

In addition, users can click on the Microbe Info button behind the species name to get more detailed information related to this species.

The “General Information of This Species” and “Drug Transporter(s) Regulated by This Species” sections are displayed in this page. In addition to displaying the basic information of the strain (Species Name, Taxonomy ID and Lineage), the transporters regulated by the species are also listed according to mechanism classification.

What's more, VARIDT 3.0 also provides the figure to show the species relative abundances under different disease states.

The post-translational modification (PTM) of DTs is vital for drug disposition (Nat Rev Microbiol. 2019, 17: 651-664) and the revealing of the mechanism underlying disease progression (Nat Commun. 2021, 12: 5872). A total of 10,255 PTM data of 418 DTs involving 24 post-translational modification types such as (phosphorylation, ubiquitination, glycosylation, acetylation, etc.) was contained in this section.

For example, searching “BSEP” or “Bile salt export pump” in the “Search for the Post-Translational Modifications of Drug Transporter (MBI)” from the corresponding drop-down list.

The search result lists of the transporter with transporter information, and MBI Info button links to the Detail Information of Post-Translational Modifications.

The “General Information of Drug Transporter (DT)” and “Post-Translational Modification of This DT” sections are displayed in this page. In “Post-Translational Modification of This DT” part, the amino acid sequence of the transporter and an overview of BSEP modification sites with functional and structural information are displayed first, using different background colors in the sequence to represent the type of PTM modification that will occur at that site. For BSEP, there are four types of PTM modifications that occur (N-glycation, oxidation, phosphorylation, and ubiquitination).

Following closely is detailed information on the occurrence of PTM in the transporter. The role of PTM, affected drug/substrate modified residue/location, experimental material/method are shown in a list. In the end, there will be a detailed description of how the species regulates the transporter.

The transcriptional regulation (TSR) of DTs is critical for the reversing of multidrug resistance (Gastroenterology. 2021, 597: 533-538) and the discovery of new therapies Cardiovasc Res. 2022,118: 2458-2477). A total of 10,610 TSR data between 357 transcription factors and 381 DTs was enrolled in this section.

For example, searching the “Transcription factor AP-2 alpha” in the “Search for the Transcriptional Regulations of Drug Transporter (TSR)” filed.

The result displays several related DTs. The Information of TSR page can be accessed by clicking the TSR Info button.

The “General Information of Drug Transporter (DT)” and “Transcription Factor (TF) Regulation of This DT” sections are displayed in this page.Below the latter, the first image shows all the TF superclass class, and tf gene name that can regulate this DT.

All TSR information is classified according to TF superclass and TF gene name.

After clicking on the TF gene name, detailed experimental information (TF protein name, affected drug/substrate, studied phenotype/tissue, related DT changes and experimental material) will be displayed.

In addition, users can click on the Transcription Factor Info button behind the TF protein name to get more detailed information related to this TF.

Take Transcription factor AP-2-alpha (TFAP2A) for example. The “General Information of This TF” and “Drug Transporter(s) Regulated by This TF” sections are displayed in this page.

Some TSRs are caused by phenotype variability. To faciliate users to conduct a systematic analysis of these variability data and have a comprehensive understanding of intricate dynamics of drug response and inspire personalized treatment strategies, relevant phenotypic variability factors were included in the detailed description of TSR.

In the second part, DTs regulated by this TF is classified according to activation, repression, and direct binding.

The last part of this page is the “Disease specific Protein Abundances of TF”. Users can view the expression differences between the TF and healthy tissues under different disease states and conveniently download relevant data and images.