Comprehensive structural modeling and preparation of human 5-HT2A G-protein coupled receptor in functionally active form

The serotonin 2A receptor (5-HT_2AR) is an important member of the G-protein coupled receptor (GPCR) family involved in an array of neuromodulatory functions. Although the high-resolution structures of truncated versions of GPCRs, captured in ligand-bound conformational states, are available, the structures lack several functional regions, which have crucial roles in receptor response. Here, in order to understand the structure and dynamics of the ligand-free form of the receptor, we have performed meticulous modeling of the 5-HT_2AR with the third intracellular loop (ICL3). Our analyses revealed that the ligand-free ground state structure of 5-HT_2AR has marked distinction with ligand-bound conformations of 5-HT₂ subfamily proteins and exhibits extensive backbone flexibility across the loop regions, suggesting the importance of purifying the receptor in its native form for further studies. Hence, we have standardized a strategy that efficiently increases the expression of 5-HT_2AR by infecting Sf9 cells with a very low multiplicity of infection of baculovirus in conjunction with production boost additive and subsequently, purify the full-length receptor. Furthermore, we have optimized the selective over-expression of glycosylated and nonglycosylated forms of the receptor merely by switching the postinfection growth time, a method that has not been reported earlier.     

A comparative study of available software for high-accuracy homology modeling: from sequence alignments to structural models

An open question in protein homology modeling is, how well do current modeling packages satisfy the dual criteria of quality of results and practical ease of use? To address this question objectively, we examined homology‐built models of a variety of therapeutically relevant proteins. The sequence identities across these proteins range from 19% to 76%. A novel metric, the difference alignment index (DAI), is developed to aid in quantifying the quality of local sequence alignments. The DAI is also used to construct the relative sequence alignment (RSA), a new representation of global sequence alignment that facilitates comparison of sequence alignments from different methods. Comparisons of the sequence alignments in terms of the RSA and alignment methodologies are made to better understand the advantages and caveats of each method. All sequence alignments and corresponding 3D models are compared to their respective structure‐based alignments and crystal structures. A variety of protein modeling software was used. We find that at sequence identities >40%, all packages give similar (and satisfactory) results; at lower sequence identities (<25%), the sequence alignments generated by Profit and Prime, which incorporate structural information in their sequence alignment, stand out from the rest. Moreover, the model generated by Prime in this low sequence identity region is noted to be superior to the rest. Additionally, we note that DSModeler and MOE, which generate reasonable models for sequence identities >25%, are significantly more functional and easier to use when compared with the other structure‐building software.     

Walking through the protein sequence space: towards new generation of the homology modeling

A new method is proposed to reveal apparent evolutionary relationships between protein fragments with similar 3D structures by finding "intermediate" sequences in the proteomic database. Instead of looking for homologies and intermediates for a whole protein domain, we build a chain of intermediate short sequences, which allows one to link similar structural modules of proteins belonging to the same or different families. Several such chains of intermediates can be combined into an evolutionary tree of structural protein modules. All calculations were made for protein fragments of 20 aa residues. Three evolutionary trees for different module structures are described. The aim of the paper is to introduce the new method and to demonstrate its potential for protein structural predictions. The approach also opens new perspectives for protein evolution studies.     

Homology modeling of human histone deacetylase 10 and design of potential selective inhibitors

Abstract

Histone deacetylases (HDACs) are implicated in the pathology of various cancers, and their pharmacological blockade has proven to be promising in reversing the malignant phenotypes. However, lack of crystal structures of some of the human HDAC isoforms (e.g., HDAC10) hinders the design of the isoform-selective inhibitor. Here, the recently solved X-ray crystal structure of Danio rerio (zebrafish) HDAC10 (Protein Data Bank (PDB) ID; 5TD7, released on 24 May 2017) was retrieved from the PDB and used as a template structure to model the three-dimensional structure of human HDAC10. The overall quality of the best model (M0017) was assessed by computing its z-score—a measure of the deviation of the total energy of the structure with respect to an energy distribution derived from random conformations and by docking of known HDAC10 inhibitors to its catalytic cavity. Furthermore, to identify potential HDAC10-selective inhibitor ligand-based virtual screening was carried out against the ZINC database. The free modeled structure of HDAC10 and its complexes with quisinostat and the highest-ranked compound ZINC19749069 were submitted to molecular dynamics simulation. The comparative analysis of root-mean-squared deviation, root-mean-squared fluctuation, radius of gyration (Rg), and potential energy of these systems showed that HDAC10-ZINC19749069 complex remained the most stable over time. Thus, M0017 could be potentially used for structure-based inhibitor against HDAC10, and ZINC19749069 may provide a scaffold for further optimization.

Communicated by Ramaswamy H. Sarma     

A comparative modeling and molecular docking study on Mycobacterium tuberculosis targets involved in peptidoglycan biosynthesis

An alarming rise of multidrug-resistant Mycobacterium tuberculosis strains and the continuous high global morbidity of tuberculosis have reinvigorated the need to identify novel targets to combat the disease. The enzymes that catalyze the biosynthesis of peptidoglycan in M. tuberculosis are essential and noteworthy therapeutic targets. In this study, the biochemical function and homology modeling of MurI, MurG, MraY, DapE, DapA, Alr, and Ddl enzymes of the CDC1551 M. tuberculosis strain involved in the biosynthesis of peptidoglycan cell wall are reported. Generation of the 3D structures was achieved with Modeller 9.13. To assess the structural quality of the obtained homology modeled targets, the models were validated using PROCHECK, PDBsum, QMEAN, and ERRAT scores. Molecular dynamics simulations were performed to calculate root mean square deviation (RMSD) and radius of gyration (Rg) of MurI and MurG target proteins and their corresponding templates. For further model validation, RMSD and Rg for selected targets/templates were investigated to compare the close proximity of their dynamic behavior in terms of protein stability and average distances. To identify the potential binding mode required for molecular docking, binding site information of all modeled targets was obtained using two prediction algorithms. A docking study was performed for MurI to determine the potential mode of interaction between the inhibitor and the active site residues. This study presents the first accounts of the 3D structural information for the selected M. tuberculosis targets involved in peptidoglycan biosynthesis.     

In silico modeling of ligand molecule for non structural 3 (NS3) protein target of flaviviruses

Flaviviruses are small, enveloped RNA viruses which cause a variety of diseases into animals and man. Despite the existence of licensed vaccines, yellow fever, Japanese encephalitis and tick-borne encephalitis also claim many thousands of victims each year across their vast endemic areas. A number of studies have already revealed that the non-structural NS3 serine protease is required for the maturation of the viral polyprotein and thus is a promising target for the development of antiviral inhibitors. Hence, the 3D structure of NS3 protein was modeled using homology modeling by MODELLER 9v7. Validation of the constructed NS3 protein models were done by PROCHECK, VERYFY3D and through ProSA calculations. Ligands for the catalytic triad (H51, D75, and S135) were designed using LIGBUILDER. The NS3 protein's catalytic triad was explored to find out the interactions pattern for inhibitor binding using molecular docking methodology using AUTODOCK Vina. The interactions of complex NS3protein-ligand conformations, including hydrogen bonds and the bond lengths were analyzed using Accelrys DS Visualizer software. Hence, from this observation, the novel molecule designed was observed to be the best ligand against the NS3 protein of flavivirus. This molecule may prove to be a potential identity in modulating disease manifestation for all the selected flavivirus members. ABBREVIATIONS: NCBI - National Centre for Biotechnological Information, BLAST - Basic Local Alignment Search Tool, DOPE - Discrete optimized protein energy, GROMOS96 - GROningen MOlecular Simulation package, SAVS - Structure Analysis and Validation Server.     

肺炎链球菌双组份系统中的组氨酸激酶(YycG)的同源模建与分析

对肺炎链球菌双组份系统中的组氨酸激酶YycG进行同源模建, 并分析其与底物ADP的相互作用, 为寻找特异性的激酶抑制剂提供了理论依据。采用同源模建的方法构建YycG蛋白的三维结构, 并用ProCheck、Profile_3D软件对此结构模型的合理性进行验证; 用Autodock4.0软件将结构模型与ADP进行自动对接, 分析二者之间的相互作用。序列比对结果显示肺炎链球菌YycG蛋白与Thermotoga maritima X-ray晶体结构序列的同一性达33%; YycG模建后的结构与模板能很好的叠合; 在活性口袋处的保守的氨基酸残基Asn145、Asn149、Lys152以及口袋内部的疏水残基在结合、水解底物ADP的过程中发挥重要作用。组氨酸激酶YycG的模建合理, 该结构模型可作为设计抗菌药的研究起点。     

Computational exploration of the binding mode of heme‐dependent stimulators into the active catalytic domain of soluble guanylate cyclase

Soluble guanylate cyclase (sGC), the main target of nitric oxide (NO), has been proven to have a significant role in coronary artery disease, pulmonary hypertension, erectile dysfunction, and myocardial infarction. One of its agonists, BAY 41‐2272 (Riociguat), has been recently approved for treatment of pulmonary arterial hypertension (PHA), while some others are in clinical phases of development. However, the location of the binding sites for the two known types of agonists, heme‐dependent stimulators and heme‐independent activators, is a matter of debate, particularly for the first group where both a location on the regulatory (H‐NOX) and on the catalytic domain have been suggested by different authors. Here, we address its potential location on the catalytic domain, the unique well characterized at the structural level, by an “in silico” approach. Homology models of the catalytic domain of sGC in “inactive” or “active” conformations were constructed using the structure of previously described crystals of the catalytic domains of “inactive” sGCs (2WZ1, 3ET6) and of “active” adenylate cyclase (1CJU). Each model was submitted to six independent molecular dynamics simulations of about 1 μs. Docking of YC‐1, a classic heme‐dependent stimulator, to all frames of representative trajectories of “inactive” and “active” conformations, followed by calculation of absolute binding free energies with the linear interaction energy (LIE) method, revealed a potential high‐affinity binding site on the “active” structure. The site, located between the pseudo‐symmetric and the catalytic site just over the loop β₂–β₃, does not overlap with the forskolin binding site on adenylate cyclases. Proteins 2016; 84:1534–1548. © 2016 Wiley Periodicals, Inc.     

Affinity enhancement of HER2-binding Z(HER2:342) affibody via rational design approach: a molecular dynamics study

Human epidermal growth factor receptor 2 (HER2) contributes to the development of breast cancers and malignancies. On the other hand, engineered affibody Z(HER2:342) that binds to HER2 can be successfully used for both diagnostic purposes and specific ablation of malignant HER2-positive cell lines. In the current study, electrostatics-based prediction was applied for improving Z(HER2:342) binding affinity using computational design. The affibody Z(HER2:342) alone and in complex with HER2 was energetically minimized, solvated in explicit water, and neutralized. After heating and equilibration steps, the system was studied by isothermal-isobaric (NPT) MD simulation. According to trajectories, Z(HER2:342) specifically binds to HER2 through hydrogen bonds and salt bridges. Based on the electrostatic binding contributions, two affinity-matured variants namely V1 (Tyr35Arg) and V2 (Asn6Asp and Met9Glu) were rationally designed. More investigations through MD simulation show that V1 interacts with HER2 receptor more strongly, compared to Z(HER2:342) and V2.     

Docking and homology modeling explain inhibition of the human vesicular glutamate transporters

As membrane transporter proteins, VGLUT1-3 mediate the uptake of glutamate into synaptic vesicles at presynaptic nerve terminals of excitatory neural cells. This function is crucial for exocytosis and the role of glutamate as the major excitatory neurotransmitter in the central nervous system. The three transporters, sharing 76% amino acid sequence identity in humans, are highly homologous but differ in regional expression in the brain. Although little is known regarding their three-dimensional structures, hydropathy analysis on these proteins predicts 12 transmembrane segments connected by loops, a topology similar to other members in the major facilitator superfamily, where VGLUT1-3 have been phylogenetically classified. In this work, we present a three-dimensional model for the human VGLUT1 protein based on its distant bacterial homolog in the same superfamily, the glycerol-3-phosphate transporter from Escherichia coli. This structural model, stable during molecular dynamics simulations in phospholipid bilayers solvated by water, reveals amino acid residues that face its pore and are likely to affect substrate translocation. Docking of VGLUT1 substrates to this pore localizes two different binding sites, to which inhibitors also bind with an overall trend in binding affinity that is in agreement with previously published experimental data.     

Computational modeling of membrane proteins

The determination of membrane protein (MP) structures has always trailed that of soluble proteins due to difficulties in their overexpression, reconstitution into membrane mimetics, and subsequent structure determination. The percentage of MP structures in the protein databank (PDB) has been at a constant 1–2% for the last decade. In contrast, over half of all drugs target MPs, only highlighting how little we understand about drug‐specific effects in the human body. To reduce this gap, researchers have attempted to predict structural features of MPs even before the first structure was experimentally elucidated. In this review, we present current computational methods to predict MP structure, starting with secondary structure prediction, prediction of trans‐membrane spans, and topology. Even though these methods generate reliable predictions, challenges such as predicting kinks or precise beginnings and ends of secondary structure elements are still waiting to be addressed. We describe recent developments in the prediction of 3D structures of both α‐helical MPs as well as β‐barrels using comparative modeling techniques, de novo methods, and molecular dynamics (MD) simulations. The increase of MP structures has (1) facilitated comparative modeling due to availability of more and better templates, and (2) improved the statistics for knowledge‐based scoring functions. Moreover, de novo methods have benefited from the use of correlated mutations as restraints. Finally, we outline current advances that will likely shape the field in the forthcoming decade. Proteins 2015; 83:1–24. © 2014 Wiley Periodicals, Inc.     

In silico characterization of binding mode of CCR8 inhibitor: homology modeling,docking and membrane based MD simulation study

Human CC-chemokine receptor 8 (CCR8) is a crucial drug target in asthma that belongs to G-protein-coupled receptor superfamily, which is characterized by seven transmembrane helices. To date, there is no X-ray crystal structure available for CCR8; this hampers active research on the target. Molecular basis of interaction mechanism of antagonist with CCR8 remains unclear. In order to provide binding site information and stable binding mode, we performed modeling, docking and molecular dynamics (MD) simulation of CCR8. Docking study of biaryl-ether-piperidine derivative (13C) was performed inside predefined CCR8 binding site to get the representative conformation of 13C. Further, MD simulations of receptor and complex (13C-CCR8) inside dipalmitoylphosphatidylcholine lipid bilayers were performed to explore the effect of lipids. Results analyses showed that the Gln91, Tyr94, Cys106, Val109, Tyr113, Cys183, Tyr184, Ser185, Lys195, Thr198, Asn199, Met202, Phe254, and Glu286 were conserved in both docking and MD simulations. This indicated possible role of these residues in CCR8 antagonism. However, experimental mutational studies on these identified residues could be effective to confirm their importance in CCR8 antagonism. Furthermore, calculated Coulombic interactions represented the crucial roles of Glu286, Lys195, and Tyr113 in CCR8 antagonism. Important residues identified in this study overlap with the previous non-peptide agonist (LMD-009) binding site. Though, the non-peptide agonist and currently studied inhibitor (13C) share common substructure, but they differ in their effects on CCR8. So, to get more insight into their agonist and antagonist effects, further side-by-side experimental studies on both agonist (LMD-009) and antagonist (13C) are suggested.     

Ligand-supported homology modeling of the human angiotensin II type 1 (AT(1)) receptor: insights into the molecular determinants of telmisartan binding

Angiotensin II type 1 (AT(1)) receptor belongs to the super-family of G-protein-coupled receptors, and antagonists of the AT(1) receptor are effectively used in the treatment of hypertension. To understand the molecular interactions of these antagonists, such as losartan and telmisartan, with the AT(1) receptor, a homology model of the human AT(1) (hAT(1)) receptor with all connecting loops was constructed from the 2.6 A resolution crystal structure (PDB i.d., 1L9H) of bovine rhodopsin. The initial model generated by MODELLER was subjected to a stepwise ligand-supported model refinement. This protocol involved initial docking of non-peptide AT(1) antagonists in the putative binding site, followed by several rounds of iterative energy minimizations and molecular dynamics simulations. The final model was validated based on its correlation with several structure-activity relationships and site-directed mutagenesis data. The final model was also found to be in agreement with a previously reported AT(1) antagonist pharmacophore model. Docking studies were performed for a series of non-peptide AT(1) receptor antagonists in the active site of the final hAT(1) receptor model. The docking was able to identify key molecular interactions for all the AT(1) antagonists studied. Reasonable correlation was observed between the interaction energy values and the corresponding binding affinities of these ligands, providing further validation for the model. In addition, an extensive unrestrained molecular dynamics simulation showed that the docking-derived bound pose of telmisartan is energetically stable. Knowledge gained from the present studies can be used in structure-based drug design for developing novel ligands for the AT(1) receptor.     

Computational exploration of the network of sequence flow between protein structures

We investigate small sequence adjustments (of one or a few amino acids) that induce large conformational transitions between distinct and stable folds of proteins. Such transitions are intriguing from evolutionary and protein‐design perspectives. They make it possible to search for ancient protein structures or to design protein switches that flip between folds and functions. A network of sequence flow between protein folds is computed for representative structures of the Protein Data Bank. The computed network is dense, on an average each structure is connected to tens of other folds. Proteins that attract sequences from a higher than expected number of neighboring folds are more likely to be enzymes and alpha/beta fold. The large number of connections between folds may reflect the need of enzymes to adjust their structures for alternative substrates. The network of the Cro family is discussed, and we speculate that capacity is an important factor (but not the only one) that determines protein evolution. The experimentally observed flip from all alpha to alpha + beta fold is examined by the network tools. A kinetic model for the transition of sequences between the folds (with only protein stability in mind) is proposed. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

Homology modeling,virtual screening and dynamics study of proteins involved in Pebrine - Serine protease inhibitor 106 and spore wall protein 26

Abstract

Pebrine is a microsporidian disease caused by Nosema bombycis in Bombyx mori (silk worm) which results in brown/black spots. The affected larvae either spin cocoons which are flimsy with low silk content or not spin a cocoon. It has been hypothesised that Serine Protease Inhibitor 106 (SPN106) is responsible for evasion of host immune system by inhibiting the melanization process in silkworms. Also, Spore Wall Protein 26 (SWP26) has been observed to bind with Ig- like protein Bombyx mori turtle-like protein (Bm-TLP) facilitating the attachment of the microsporidian to the host and contributing to infectivity. Till date, there is no crystal structure of the proteins SPN106, SWP26 and Bm-TLP available. In this study, we performed homology modeling of the three structures using Modeller v9.18 and the binding pockets were identified. Virtual screening was conducted using AutoDock Vina on a ligand library consisting of 28,870 lead-like molecules. The protein stability, compactness, fluctuations and protein-ligand interactions were investigated through Molecular Dynamics (MD) simulations studies using Desmond Maestro 11.3 and a potential lead molecule was identified.

Communicated by Ramaswamy H. Sarma     

Deprotonation states of the two active site water molecules regulate the binding of protein phosphatase 5 with its substrate: A molecular dynamics study

Protein phosphatase 5 (PP5), mainly localized in human brain, can dephosphorylate tau protein whose high level of phosphorylation is related to Alzheimer's disease. Similar to other protein phosphatases, PP5 has a conserved motif in the catalytic domain that contains two binding sites for manganese (Mn²⁺) ions. Structural data indicate that two active site water molecules, one bridging the two Mn²⁺ ions and the other terminally coordinated with one of the Mn²⁺ ions (Mn1), are involved in catalysis. Recently, a density functional theory study revealed that the two water molecules can be both deprotonated to keep a neutral active site for catalysis. The theoretical study gives us an insight into the catalytic mechanism of PP5, but the knowledge of how the deprotonation states of the two water molecules affect the binding of PP5 with its substrate is still lacking. To approach this problem, molecular dynamics simulations were performed to model the four possible deprotonation states. Through structural, dynamical and energetic analyses, the results demonstrate that the deprotonation states of the two water molecules affect the structure of the active site including the distance between the two Mn²⁺ ions and their coordination, impact the interaction energy of residues R275, R400 and H304 which directly interact with the substrate phosphoserine, and mediate the dynamics of helix αJ which is involved in regulation of the enzyme's activity. Furthermore, the deprotonation state that is preferable for PP5 binding of its substrate has been identified. These findings could provide new design strategy for PP5 inhibitor.     

Computational modeling of human coreceptor CCR5 antagonist as a HIV-1 entry inhibitor: using an integrated homology modeling,docking, and membrane molecular dynamics simulation analysis approach

Chemokine receptor 5 (CCR5) is an integral membrane protein that is utilized during human immunodeficiency virus type-1 entry into host cells. CCR5 is a G-protein coupled receptor that contains seven transmembrane (TM) helices. However, the crystal structure of CCR5 has not been reported. A homology model of CCR5 was developed based on the recently reported CXCR4 structure as template. Automated docking of the most potent (14), medium potent (37), and least potent (25) CCR5 antagonists was performed using the CCR5 model. To characterize the mechanism responsible for the interactions between ligands (14, 25, and 37) and CCR5, membrane molecular dynamic (MD) simulations were performed. The position and orientation of ligands (14, 25, and 37) were found to be changed after MD simulations, which demonstrated the ability of this technique to identify binding modes. Furthermore, at the end of simulation, it was found that residues identified by docking were changed and some new residues were introduced in the proximity of ligands. Our results are in line with the majority of previous mutational reports. These results show that hydrophobicity is the determining factor of CCR5 antagonism. In addition, salt bridging and hydrogen bond contacts between ligands (14, 25, and 37) and CCR5 are also crucial for inhibitory activity. The residues newly identified by MD simulation are Ser160, Phe166, Ser180, His181, and Trp190, and so far no site-directed mutagenesis studies have been reported. To determine the contributions made by these residues, additional mutational studies are suggested. We propose a general binding mode for these derivatives based on the MD simulation results of higher (14), medium (37), and lower (25) potent inhibitors. Interestingly, we found some trend for these inhibitors such as, salt bridge interaction between basic nitrogen of ligand and acidic Glu283 seemed necessary for inhibitory activity. Also, two aromatic pockets (pocket I – TM1-3 and pocket II – TM3-6) were linked by the central polar region in TM7, and the simulated inhibitors show important interactions with the Trp86, Tyr89, Tyr108, Phe112, Ile198, Tyr251, Leu255, and Gln280 and Glu283 residues. These results shed light on the usage of MD simulation to identify more stable, optimal binding modes of the inhibitors.     

Molecular modeling,dynamics, and an insight into the structural inhibition of cofactor independent phosphoglycerate mutase isoform 1 from Wuchereria bancrofti using cheminformatics and mutational studies

Phosphoglycerate mutase catalyzes the interconversion between 2-phosphoglycerate and 3-phosphoglycerate in the glycolytic and gluconeogenic pathways. They exist in two unrelated forms, that is either cofactor (2,3-diphosphoglycerate) dependent or cofactor-independent. These two enzymes have no similarity in amino acid sequence, tertiary structure, and in catalytic mechanism. Wuchereria bancrofti (WB) contains the cofactor-independent form, whereas other organisms can possess the dependent form or both. Since, independent phosphoglycerate mutase (iPGM) is an essential gene for the survival of nematodes, and it has no sequence or structural similarity to the cofactor-dependent phosphoglycerate mutase found in mammals, it represents an attractive drug target for the filarial nematodes. In this current study, a putative cofactor-iPGM gene was identified in the protein sequence of the WB. In the absence of crystal structure, a three-dimensional structure was determined using the homology modeling approximation, and the most stable protein conformation was identified through the molecular dynamics simulation studies, using GROMACS 4.5. Further, the functional or characteristic residues were identified through the sequence analysis, potential inhibitors were short-listed and validated, and potential inhibitors were ranked using the cheminformatics and molecular dynamics simulations studies, Prime MM-GBSA approach, respectively.     

Adaptability in protein structures: structural dynamics and implications in ligand design

The basic framework of understanding the mechanisms of protein functions is achieved from the knowledge of their structures which can model the molecular recognition. Recent advancement in the structural biology has revealed that in spite of the availability of the structural data, it is nontrivial to predict the mechanism of the molecular recognition which progresses via situation-dependent structural adaptation. The mutual selectivity of protein–protein and protein–ligand interactions often depends on the modulations of conformations empowered by their inherent flexibility, which in turn regulates the function. The mechanism of a protein’s function, which used to be explained by the ideas of ‘lock and key’ has evolved today as the concept of ‘induced fit’ as well as the ‘population shift’ models. It is felt that the ‘dynamics’ is an essential feature to take into account for understanding the mechanism of protein’s function. The design principles of therapeutic molecules suffer from the problems of plasticity of the receptors whose binding conformations are accurately not predictable from the prior knowledge of a template structure. On the other hand, flexibility of the receptors provides the opportunity to improve the binding affinity of a ligand by suitable substitution that will maximize the binding by modulating the receptors surface. In this paper, we discuss with example how the protein’s flexibility is correlated with its functions in various systems, revealing the importance of its understanding and for making applications. We also highlight the methodological challenges to investigate it computationally and to account for the flexible nature of the molecules in drug design.