Table 4.

List of available ligand- and structure-based molecular modeling studies on uptake transporters discussed in this review.

Paper	Transporter	Method	Description	Results
Tanihara et al.[132]	MATE1	Binary classification modeling	Identification of key features for inhibitory mechanism	Cationic charge is crucial for MATE1 inhibition.
Diao et al. [25]	MATE1	Bayesian machine learning modeling	Identification of key features for inhibitory mechanism	Six-membered rings including nitrogen are important for MATE1 inhibition.
Astorga et al. [5]	MATE1	IVIS pharmacophore modeling	Iterative identification of new MATE1 inhibitors by using pharmacophore-based virtual screening	Two hydrophobic features, H-bond acceptor and cationic feature have occurred in final pharmacophore model for MATE1.
Zhang et al. [130]	MATE1	Structural model building, molecular dynamics simulation	Topology of human MATE1 transporter, stability of constructed structural model	Human MATE1 transporter consists of 12 TM which have a functional role; 13th TM is not required for the transport.
Wittwer et al. [122]	MATE1	Binary classification modeling	Identification of key features for inhibitory mechanism	Cationic charge, molecular weight, and lipophilicity are important features for MATE1 inhibition.
Xu et al. [126]	MATE1	Combinatorial pharmacophore modeling	Studying multiple inhibitory mechanisms of MATE1 inhibitors	Four different binding sites (two competitive, one non-competitive and one mixed inhibition binding site) were identified for MATE1.
Xu et al. [126]	MATE1	Structural model building, molecular docking	Elucidate the evidence of multiple binding sites from combinatorial pharmacophore model	Four different binding sites (two competitive, one non-competitive and one mixed inhibition binding site) were identified for MATE1.
Astorga et al. [5]	MATE2-K	IVIS pharmacophore modeling	Iterative identification of new MATE2-K inhibitors by using pharmacophore-based virtual screening	Two hydrophobic features, H-bond acceptor and cationic feature have occurred in final pharmacophore model.
Perry et al. [93]	OAT1	Structural model building	Identification of critical residues important for OAT1 transport function	Importance of aromatic amino acid at at position 230 has been discovered.
Truong et al. [133]	OAT1, OAT3	QSAR modeling	Comparison of interactions of antiviral drugs with OAT1 versus OAT3	Number of H-bond donors (alcohols and amides) and total polar surface area have triggered a preferred inhibitory activity towards OAT1.
Tsigelny et al. [112]	OAT1	Molecular dynamics simulation	Investigations of dynamics events accompanying OAT1 transport	Tilting mechanism of two hemi-domains is crucial for the initialization of transport process.
Soars et al. [134]	OAT1, OAT3	QSAR modeling	Comparison of inhibitor features between OAT1 and OAT3	OAT1 and OAT3 inhibitors have statistically significant inhibitory profiles.
Bednarczyk et al. [135]	OCT1	LB pharmacophore modeling	Identification of important pharmacophoric features for OCT1 inhibition	Three hydrophobic and one positive ionizable feature are important features for OCT1 inhibition.
Moaddel et al. [79]	OCT1	LB pharmacophore modeling	Studying stereroselective recognition of OCT1 transporters	One positive ionizable feature, one hydrophobic, and two H-bond acceptor features are important for OCT1 inhibition.
Ahlin et al. [1]	OCT1	QSAR modeling	Identification of molecular features being important for inhibitory activity	H-bond donors, lipophilicity, cationic charge positively correlate with OCT1 inhibition.
Badolo et al. [6]	OCT1	QSAR modeling	Identification of molecular features being important for inhibitory activity	Topological polar surface area negatively correlates with OCT1 inhibition.
Shaikh et al. [104]	OCT1, OATP1B1, OATP1B3, OATP2B1	QSAR/PCM modeling, substructural analysis	Identification of important molecular features and structural fragments for substrate activity against reported transporters	Developed models were used for prediction of substrate propensity for blood-brain barrier transporters.
Dakal et al. [22]	OCT1, OCT2, OCT3, OCTN1, OCTN2	Structural model building	Multiscale structural models construction for OCT transporters	Constructed structural models for OCTs share close structural similarity with GLUT3 transporter (pdb id: 5c65).
Chen et al. [19]	OCT1	Structural model building, molecular docking	Identification of critical residues important for OCT1 activity; virtual screening for sake of detecting new OCT1 inhibitors	D474 is important for ligand binding; detection of two distinct binding sites in translocation channel.
Boxberger et al. [13]	OCT1	Structural model building, molecular docking	Identification of critical residues important for OCT1 activity	Identification of three distinct binding sites based on the presence of critical residues (W218, Y222, T226, I443, I447, Q475).
Kido et al. [58]	OCT2	QSAR modeling	Identiffication of molecular determinants for OCT2 inhibitors	Suggestion of multiple binding sites for OCT2 transporter.
Suhre et al. [136]	OCT2	2D-QSAR modeling, Comparative Molecular Field Analysis (CoMFA)	Identification of molecular determinants of OCT2 substrates and inhibitors	Hydrophobicity, steric factor, and number of rotatable bonds were identified as important features for OCT2 inhibition.
Wittwer et al. [122]	OCT2	QSAR modeling	Identification of molecular determinants of OCT2 inhibitors	Occurrence of both zwitterionic and basic functional groups is important for OCT2 inhibition.
Xu et al. [125]	OCT2	Combinatorial pharmacophore modeling	Studying multiple inhibitory mechanism of OCT2 inhibitors	Four distinct pharmacophore hypotheses, corresponding to the competitive inhibition (one hypothesis), non-competitive inhibition by occlusion (two hypotheses), and one mixed inhibition pattern, have been identified for OCT2 inhibitors.
Diao et al. [26]	OCTN2	IVIS pharmacophore modeling	Iterative identification of new OCTN2 inhibitors by using pharmacophore-based virtual screening	Three hydrophobic and one positive ionizable feature are important for OCTN2 inhibition.
Diao et al. [25]	OCTN2	IVIS pharmacophore modeling, Bayesian modeling	Iterative identification of new OCTN2 inhibitors by using pharmacophore-based virtual screening	Two hydrophobic features, one H-bond donor, and positive ionizable feature are important for OCTN2 inhibitors; aromatic and tertiary-amine groups have also been detected via Bayesian modeling.
Mandery et al. [73]	OATP1A2, OATP1B3, OATP2B1	Structural models construction	Comparison of structural determinants for ligand activity among OATP family	K361 and K399 are highly conserved residues across OATP family; K361 is pointing towards the translocation pore; variable loop located within a translocation pore differs in terms of crucial residues for respective targets (R58 and S62 in OATP1B3, Q58 and P62 in OATP1A2, and S64 in OATP2B1).
Chang [17]	OATP1B1	LB pharmacophore modeling	Detection of pharmacophoric features for OATP1B1 substrates	Two H-bond acceptors and two or three hydrophobic features are important for OATP1B1 substrates.
Badolo et al. [6]	OATP1B1, OATP1B3	QSAR modeling	Identification of molecular features being important for OATP1B1/1B3 inhibition	Lipophilicity, polarity, lower base pKa, higher number of H-bond acceptors, and higher molecular weight correlate with OATP1B inhibition.
Soars et al. [105]	OATP1B1	QSAR modeling	Identification of molecular features being important for OATP1B1 inhibition	Low number of aromatic bonds (<7), lipophilicity, and hydrogen-bonding potential are important for OATP1B1 inhibition.
Karlgren et al. [54]	OATP1B1	QSAR modeling	Virtual screening for detecting new OATP1B1 inhibitors	Lipophilicity, larger molecular weight, larger polar surface area
Karlgren et al. [55]	OATP1B1, OATP1B3, OATP2B1	QSAR modeling	Comparison of molecular determinants for ligand activity among hepatic OATPs	Lipophilicity and polar surface area are general features for OATP inhibition; OATP2B1 inhibitors are less dependent on polarity than OATP1B1/1B3 inhibitors.
Van de Steeg et al. [114]	OATP1B1	Bayesian modeling	Identification of molecular features being important for OATP1B1 inhibition	Conjugated-bond systems, (hetero)cycles with acceptor/donor atoms inside or outside the rings, molecular weight, molecular surface area, lipophilicity, number of rings, number of rotatable bonds, number of H-bond acceptors are important for OATP1B1 inhibition.
Bruyn et al. [14]	OATP1B1, OATP1B3	PCM modeling	Comparison of molecular determinants for ligand activity for OATP1B1 and OATP1B3 transporter	Lipophilicity, absence of cationic charge, number of ringbonds, presence of an anionic functional group, molecular volume, and substantial number of H-bond acceptors are important for general OATP1B inhibition; low number of aromatic bonds correlates with OATP1B1 inhibition, whereas higher lipophilicity and moderate number of H-bond donors corresponds with OATP1B3 inhibition.
Kotsampasakou et al. [60]	OATP1B1, OATP1B3	QSAR modeling	Comparison of molecular determinants for ligand activity for OATP1B1 and OATP1B3 transporters; virtual screening to search for new OATP1B ligands	Number of H-bond donors and acceptors, LogP, molecular refractivity, topological surface area, molecular weight, number of rotatable bonds, topological radius, topological diameter, topological shape, global topological charge index, have been used to develop models for OATP1B1 and OATP1B3.
Türkova et al. [113]	OATP1B1, OATP1B3, OATP2B1	Substructural analysis, QSAR modeling	Comparison of molecular determinants for ligand activity among hepatic OATPs	Lipophilicity, molecular weight, number of atoms, molecular refractivity, and flexibility are important features for general OATP inhibition; OATP2B1 inhibitors tend to be more planar than OATP1B1/1B3 inhibitors.
Li et al. [69]	OATP1B1	Structural model construction, molecular docking	Exploring the importance of selected amino acids from TM2 on the uptake of Estrone-3-sulphate	D70 and F73 are involved in the interaction with substrates; two distinct binding sites (low- and high- affinity site) for Estrone-3-sulphate have been identified.
Hong et al. [137]	OATP1B1	Structural model construction, molecular docking	Exploring the importance of selected amino acids from TM11 on the uptake of prototypic substrates	Importance of negative charge at position 596 for OATP1B1 uptake.
Glaeser et al., [36]	OATP1B3	Structural model construction,molecular docking	Identification of important amino acids on OATP1B3 transport function	Importance of positive charge at position 41, importance of R580 residue on OATP1B3 transport.
Meier-Abt et al. [77]	OATP1B3, OATP2B1	Structural model construction, molecular docking	Comparison of important amino acids on OATP1B3 and OATP2B1 transport function	R181 might contribute to the OATP1B substrate specificity, while H579 is hypothesized to be crucial for OATP2B family; conservation of H-bonds patterns, as well as helix-breaking residues (proline and glycine patterns), have also been detected.
Gui and Hagenbuch [38]	OATP1B1, OATP1B3	Structural model construction, molecular docking	Comparison of important amino acids on OATP1B1 and OATP2B1 transport function	TM10 is pronounced to drive the differences between OATP1B1 and OATP1B3.
Khuri et al. [57]	OATP2B1	Structural model construction, molecular docking, QSAR modeling	Identification of molecular features being important for OATP2B1 inhibition; virtual screening for new OATP2B1 inhibitors	OATP2B1 inhibitors are lipophilic.