Hinge-Shift Mechanism Modulates Allosteric Regulations in Human Pin1

NRIMD, a Web Server for Analyzing Protein Allosteric Interactions Based on Molecular Dynamics Simulation

Long-range allosteric communication between distant sites and active sites in proteins is central to biological regulation but still poorly characterized, limiting the development of protein engineering and drug design. Addressing this gap, NRIMD is an open-access web server for analyzing long-range interactions in proteins from molecular dynamics (MD) simulations, such as the effect of mutations at distal sites or allosteric ligand binding at allosteric sites on the active center. Based on our recent works on neural relational inference using graph neural networks, this cloud-based web server accepts MD simulation data on any length of residues in the alpha-carbon skeleton format from mainstream MD software. The input trajectory data are validated at the frontend deployed on the cloud and then processed on the backend deployed on a high-performance computer system with a collection of complementary tools. The web server provides a one-stop-shop MD analysis platform to predict long-range interactions and their paths between distant sites and active sites. It provides a user-friendly interface for detailed analysis and visualization. To the best of our knowledge, NRIMD is the first-of-its-kind online service to provide comprehensive long-range interaction analysis on MD simulations, which significantly lowers the barrier of predictions on protein long-range interactions using deep learning. The NRIMD web server is publicly available at https://nrimd.luddy.indianapolis.iu.edu/.

Dissecting the Allosteric Fine-Tuning of Enzyme Catalysis

Fully understanding the mechanism of allosteric regulation in biomolecules requires separating and examining all of the involved factors. In enzyme catalysis, allosteric effector binding shifts the structure and dynamics of the active site, leading to modified energetic (e.g., energy barrier) and dynamical (e.g., diffusion coefficient) factors underlying the catalyzed reaction rate. Such modifications can be subtle and dependent on the type of allosteric effector, representing a fine-tuning of protein function. The microscopic description of allosteric regulation at the level of function-dictating factors has prospective applications in fundamental and pharmaceutical sciences, which is, however, largely missing so far. Here, we characterize the allosteric fine-tuning of enzyme catalysis, using human Pin1 as an example, by performing more than half-millisecond all-atom molecular dynamics simulations. Changes of reaction kinetics and the dictating factors, including the free energy surface along the reaction coordinate and the diffusion coefficient of the reaction dynamics, under various enzyme and allosteric effector binding conditions are examined. Our results suggest equal importance of the energetic and dynamical factors, both of which can be modulated allosterically, and the combined effect determines the final allosteric output. We also reveal the potential dynamic basis for allosteric modulation using an advanced statistical technique to detect function-related conformational dynamics. Methods developed in this work can be applied to other allosteric systems.

Using deep learning and molecular dynamics simulations to unravel the regulation mechanism of peptides as noncompetitive inhibitor of xanthine oxidase

Xanthine oxidase (XO) is a crucial enzyme in the development of hyperuricemia and gout. This study focuses on LWM and ALPM, two food-derived inhibitors of XO. We used molecular docking to obtain three systems and then conducted 200 ns molecular dynamics simulations for the Apo, LWM, and ALPM systems. The results reveal a stronger binding affinity of the LWM peptide to XO, potentially due to increased hydrogen bond formation. Notable changes were observed in the XO tunnel upon inhibitor binding, particularly with LWM, which showed a thinner, longer, and more twisted configuration compared to ALPM. The study highlights the importance of residue F914 in the allosteric pathway. Methodologically, we utilized the perturbed response scan (PRS) based on Python, enhancing tools for MD analysis. These findings deepen our understanding of food-derived anti-XO inhibitors and could inform the development of food-based therapeutics for reducing uric acid levels with minimal side effects.

Engineering gain-of-function mutants of a WW domain by dynamics and structural analysis

Proteins gain optimal fitness such as foldability and function through evolutionary selection. However, classical studies have found that evolutionarily designed protein sequences alone cannot guarantee foldability, or at least not without considering local contacts associated with the initial folding steps. We previously showed that foldability and function can be restored by removing frustration in the folding energy landscape of a model WW domain protein, CC16, which was designed based on Statistical Coupling Analysis (SCA). Substitutions ensuring the formation of five local contacts identified as "on-path" were selected using the closest homolog native folded sequence, N21. Surprisingly, the resulting sequence, CC16-N21, bound to Group I peptides, while N21 did not. Here, we identified single-point mutations that enable N21 to bind a Group I peptide ligand through structure and dynamic-based computational design. Comparison of the docked position of the CC16-N21/ligand complex with the N21 structure showed that residues at positions 9 and 19 are important for peptide binding, whereas the dynamic profiles identified position 10 as allosterically coupled to the binding site and exhibiting different dynamics between N21 and CC16-N21. We found that swapping these positions in N21 with matched residues from CC16-N21 recovers nature-like binding affinity to N21. This study validates the use of dynamic profiles as guiding principles for affecting the binding affinity of small proteins.

Protein dynamics provide mechanistic insights about epistasis among common missense polymorphisms

Sequencing of the protein coding genome has revealed many different missense mutations of human proteins and different population frequencies of corresponding haplotypes, which consist of different sets of those mutations. Here, we present evidence for pairwise intramolecular epistasis (i.e., nonadditive interactions) between many such mutations through an analysis of protein dynamics. We suggest that functional compensation for conserving protein dynamics is a likely evolutionary mechanism that maintains high-frequency mutations that are individually nonneutral but epistatically compensating within proteins. This analysis is the first of its type to look at human proteins with specific high population frequency mutations and examine the relationship between mutations that make up that observed high-frequency protein haplotype. Importantly, protein dynamics revealed a separation between high and low frequency haplotypes within a target protein cytochrome P450 2A7, with the high-frequency haplotypes showing behavior closer to the wild-type protein. Common protein haplotypes containing two mutations display dynamic compensation in which one mutation can correct for the dynamic effects of the other. We also utilize a dynamics-based metric, EpiScore, that evaluates the epistatic interactions and allows us to see dynamic compensation within many other proteins.

A Specific pSer/Thr-Pro Motif Generates Interdomain Communication Bifurcations of Two Modes of Pin1 in Solution Nuclear Magnetic Resonance

Peptides mediate the interdomain communication of Pin1 (peptidyl-prolyl cis-trans isomerase) and can regulate its conformation and biochemical functions, providing an idea for drug design using Pin1. Two template peptide sequences have been widely used in the extended or compact state of Pin1 (Cdc25C, E-Q-P-L-pT-P-V-T-D-L; Pintide, W-F-Y-pS-P-R). The way in which specific pSer/Thr-Pro peptides regulate interdomain communication to achieve the opposite state is not clear. In this study, we subdivided the sequence composition of eight types of modified peptides and investigated the interaction with Pin1 by solution nuclear magnetic resonance and molecular dynamics. Demonstrating sequence dependence on the pSer-Pro or pThr-Pro motif and different residues in anchoring the WW domain, the Pin peptide (Pintide, PintideT, Pin25C, and Pin25CT) transmits this concentration accumulation to the PPIase domain, thus exhibiting two anchoring tendencies. However, the Cdc peptide (Cdc25C, Cdc25CS, Cdctide, and CdctideS) has a low binding energy that makes it difficult for the conformation to reach a steady state. In addition, Pin1 is influenced by both compact and extended states, regulated precisely by the sequence as well as by threonine or serine. These results provide new insight into the interdomain communication of Pin1 via pSer/Thr-Pro peptide binding.

Neural relational inference to learn long-range allosteric interactions in proteins from molecular dynamics simulations

Protein allostery is a biological process facilitated by spatially long-range intra-protein communication, whereby ligand binding or amino acid change at a distant site affects the active site remotely. Molecular dynamics (MD) simulation provides a powerful computational approach to probe the allosteric effect. However, current MD simulations cannot reach the time scales of whole allosteric processes. The advent of deep learning made it possible to evaluate both spatially short and long-range communications for understanding allostery. For this purpose, we applied a neural relational inference model based on a graph neural network, which adopts an encoder-decoder architecture to simultaneously infer latent interactions for probing protein allosteric processes as dynamic networks of interacting residues. From the MD trajectories, this model successfully learned the long-range interactions and pathways that can mediate the allosteric communications between distant sites in the Pin1, SOD1, and MEK1 systems. Furthermore, the model can discover allostery-related interactions earlier in the MD simulation trajectories and predict relative free energy changes upon mutations more accurately than other methods.

Here, the authors apply a neural relational inference model to infer dynamic networks of interacting residues in protein molecular dynamics simulations. The model can predict allosteric communication pathways and relative free energy changes upon mutations.

Dynamic Allostery Highlights the Evolutionary Differences between the CoV-1 and CoV-2 Main Proteases

The SARS-CoV-2 coronavirus has become one of the most immediate and widely-studied systems since its identification and subsequent global outbreak from 2019-2021. In an effort to understand the biophysical changes as a result of mutations, the mechanistic details of multiple different proteins within the SARS-CoV-2 virus have been studied and compared with SARS-CoV-1. Focusing on the main protease (mPro), we first explored the long-range dynamics using the Dynamic Coupling Index (DCI) to investigate the dynamic coupling between the catalytic site residues and the rest of the protein, both inter and intra chain, for the CoV-1 and CoV-2 mPro. We found that there is significant cross-chain coupling between these active sites and specific distal residues in the CoV-2 mPro not present in CoV-1. The enhanced long distance interactions, particularly between the two chains, suggest subsequently enhanced cooperativity for CoV-2. A further comparative analysis of the dynamic flexibility using the Dynamic Flexibility Index (DFI) between the CoV-1 and CoV-2 mPros shows that the inhibitor binding near active sites induces change in flexibility to a distal region of the protein, opposite in behavior between the two systems; this region becomes more flexible upon inhibitor binding in CoV-1 while it becomes less flexible in the CoV-2 mPro. Upon inspection, we show that, on average, the dynamic flexibility of the sites substituted from CoV-1 to CoV-2 changes significantly less than the average calculated across all residues within the structure, indicating that the differences in behaviors between the two systems is likely the result of allosteric influence, where the new substitutions in CoV-2 induce flexibility and dynamical changes elsewhere in the structure.

Design of novel cyanovirin-N variants by modulation of binding dynamics through distal mutations

We develop integrated co-evolution and dynamic coupling (ICDC) approach to identify, mutate, and assess distal sites to modulate function. We validate the approach first by analyzing the existing mutational fitness data of TEM-1 β-lactamase and show that allosteric positions co-evolved and dynamically coupled with the active site significantly modulate function. We further apply ICDC approach to identify positions and their mutations that can modulate binding affinity in a lectin, cyanovirin-N (CV-N), that selectively binds to dimannose, and predict binding energies of its variants through Adaptive BP-Dock. Computational and experimental analyses reveal that binding enhancing mutants identified by ICDC impact the dynamics of the binding pocket, and show that rigidification of the binding residues compensates for the entropic cost of binding. This work suggests a mechanism by which distal mutations modulate function through dynamic allostery and provides a blueprint to identify candidates for mutagenesis in order to optimize protein function.

A Redox-Sensitive Cysteine Is Required for PIN1At Function

Parvulins are ubiquitous peptidyl-prolyl isomerases (PPIases) required for protein folding and regulation. Among parvulin members, Arabidopsis PIN1At, human PIN1, and yeast ESS1 share a conserved cysteine residue but differ by the presence of an N-terminal WW domain, absent in PIN1At. In this study, we have explored whether the cysteine residue of Arabidopsis PIN1At is involved in catalysis and subject to oxidative modifications. From the functional complementation of yeast ess1 mutant, we concluded that the cysteine at position 69 is mandatory for PIN1At function in vivo, unless being replaced by an Asp which is found in a few parvulin members. This result correlates with a decrease of the in vitro PPIase activity of non-functional PIN1At cysteinic variants. A decrease of PIN1At activity was observed upon H₂O₂ treatment. The in vitro oxidation of cysteine 69, which has an acidic pK_a value of 4.9, leads to the formation of covalent dimers that are reduced by thioredoxins, or to sulfinic or sulfonic acid forms at higher H₂O₂ excess. These investigations highlight the importance of the sole cysteine residue of PIN1At for activity. The reversible formation of an intermolecular disulfide bond might constitute a protective or regulatory mechanism under oxidizing conditions.

Substitutions at Nonconserved Rheostat Positions Modulate Function by Rewiring Long-Range, Dynamic Interactions

Amino acid substitutions at nonconserved protein positions can have noncanonical and "long-distance" outcomes on protein function. Such outcomes might arise from changes in the internal protein communication network, which is often accompanied by changes in structural flexibility. To test this, we calculated flexibilities and dynamic coupling for positions in the linker region of the lactose repressor protein. This region contains nonconserved positions for which substitutions alter DNA-binding affinity. We first chose to study 11 substitutions at position 52. In computations, substitutions showed long-range effects on flexibilities of DNA-binding positions, and the degree of flexibility change correlated with experimentally measured changes in DNA binding. Substitutions also altered dynamic coupling to DNA-binding positions in a manner that captured other experimentally determined functional changes. Next, we broadened calculations to consider the dynamic coupling between 17 linker positions and the DNA-binding domain. Experimentally, these linker positions exhibited a wide range of substitution outcomes: Four conserved positions tolerated hardly any substitutions ("toggle"), ten nonconserved positions showed progressive changes from a range of substitutions ("rheostat"), and three nonconserved positions tolerated almost all substitutions ("neutral"). In computations with wild-type lactose repressor protein, the dynamic couplings between the DNA-binding domain and these linker positions showed varied degrees of asymmetry that correlated with the observed toggle/rheostat/neutral substitution outcomes. Thus, we propose that long-range and noncanonical substitutions outcomes at nonconserved positions arise from rewiring long-range communication among functionally important positions. Such calculations might enable predictions for substitution outcomes at a range of nonconserved positions.

Hinge-shift mechanism as a protein design principle for the evolution of β-lactamases from substrate promiscuity to specificity

TEM-1 β-lactamase degrades β-lactam antibiotics with a strong preference for penicillins. Sequence reconstruction studies indicate that it evolved from ancestral enzymes that degraded a variety of β-lactam antibiotics with moderate efficiency. This generalist to specialist conversion involved more than 100 mutational changes, but conserved fold and catalytic residues, suggesting a role for dynamics in enzyme evolution. Here, we develop a conformational dynamics computational approach to rationally mold a protein flexibility profile on the basis of a hinge-shift mechanism. By deliberately weighting and altering the conformational dynamics of a putative Precambrian β-lactamase, we engineer enzyme specificity that mimics the modern TEM-1 β-lactamase with only 21 amino acid replacements. Our conformational dynamics design thus re-enacts the evolutionary process and provides a rational allosteric approach for manipulating function while conserving the enzyme active site.

The Role of Rigid Residues in Modulating TEM-1 β-Lactamase Function and Thermostability

The relationship between protein motions (i.e., dynamics) and enzymatic function has begun to be explored in β-lactamases as a way to advance our understanding of these proteins. In a recent study, we analyzed the dynamic profiles of TEM-1 (a ubiquitous class A β-lactamase) and several ancestrally reconstructed homologues. A chief finding of this work was that rigid residues that were allosterically coupled to the active site appeared to have profound effects on enzyme function, even when separated from the active site by many angstroms. In the present work, our aim was to further explore the implications of protein dynamics on β-lactamase function by altering the dynamic profile of TEM-1 using computational protein design methods. The Rosetta software suite was used to mutate amino acids surrounding either rigid residues that are highly coupled to the active site or to flexible residues with no apparent communication with the active site. Experimental characterization of ten designed proteins indicated that alteration of residues surrounding rigid, highly coupled residues, substantially affected both enzymatic activity and stability; in contrast, native-like activities and stabilities were maintained when flexible, uncoupled residues, were targeted. Our results provide additional insight into the structure-function relationship present in the TEM family of β-lactamases. Furthermore, the integration of computational protein design methods with analyses of protein dynamics represents a general approach that could be used to extend our understanding of the relationship between dynamics and function in other enzyme classes.

Allostery and Epistasis: Emergent Properties of Anisotropic Networks

Understanding the underlying mechanisms behind protein allostery and non-additivity of substitution outcomes (i.e., epistasis) is critical when attempting to predict the functional impact of mutations, particularly at non-conserved sites. In an effort to model these two biological properties, we extend the framework of our metric to calculate dynamic coupling between residues, the Dynamic Coupling Index (DCI) to two new metrics: (i) EpiScore, which quantifies the difference between the residue fluctuation response of a functional site when two other positions are perturbed with random Brownian kicks simultaneously versus individually to capture the degree of cooperativity of these two other positions in modulating the dynamics of the functional site and (ii) DCI_asym, which measures the degree of asymmetry between the residue fluctuation response of two sites when one or the other is perturbed with a random force. Applied to four independent systems, we successfully show that EpiScore and DCI_asym can capture important biophysical properties in dual mutant substitution outcomes. We propose that allosteric regulation and the mechanisms underlying non-additive amino acid substitution outcomes (i.e., epistasis) can be understood as emergent properties of an anisotropic network of interactions where the inclusion of the full network of interactions is critical for accurate modeling. Consequently, mutations which drive towards a new function may require a fine balance between functional site asymmetry and strength of dynamic coupling with the functional sites. These two tools will provide mechanistic insight into both understanding and predicting the outcome of dual mutations.

Recent advances suggest increased influence of selective pressure in allostery

Allosteric regulation of protein functions is ubiquitous in organismal biology, but the principles governing its evolution are not well understood. Here we discuss recent studies supporting the large-scale existence of latent allostery in ancestor proteins of superfamilies. As suggested, the evolution of allostery could be driven by the need for specificity in paralogs of slow evolving protein complexes with conserved active sites. The same slow evolution is displayed by purifying selection exhibited in allosteric proteins with somatic mutations involved in cancer, where disease-associated mutations are enriched in both orthosteric and allosteric sites. Consequently, disease-associated variants can be used to identify druggable allosteric sites that are specific for paralogs in protein superfamilies with otherwise similar functions.

Allosteric Activation of PI3Kα Results in Dynamic Access to Catalytically Competent Conformations

Class I phosphoinositide-3-kinases (PI3Ks) phosphorylate PIP₂ at its 3' inositol position to generate PIP₃, a second messenger that influences signaling cascades regulating cellular growth, survival, and proliferation. Previous studies have suggested that PI3Kα activation involves dislodging the p85α nSH2 domain from the p110α catalytic subunit by binding activated receptor tyrosine kinases. We carried out molecular dynamics simulations to determine, mechanistically and structurally, how PI3Kα conformations are influenced by physiological effectors and the nSH2 domain. We demonstrate that changes in protein dynamics mediated by allosteric regulation significantly increase the population of catalytically competent states without changing the enzyme ground-state structure. Furthermore, we demonstrate that modulation of active-site residue interactions with enzyme substrates can reciprocally influence nSH2 domain dynamics. Together, these results suggest that dynamic allostery plays a role in populating the catalytically competent conformation of PI3Kα, and provide a key platform for the design of novel chemotherapeutic PI3Kα inhibitors.

Detecting Functional Dynamics in Proteins with Comparative Perturbed-Ensembles Analysis

Recent advances have made all-atom molecular dynamics (MD) a powerful tool to sample the conformational energy landscape. There are still however three major challenges in the application of MD to biological systems: accuracy of force field, time scale, and the analysis of simulation trajectories. Significant progress in addressing the first two challenges has been made and extensively reviewed previously. This Account focuses on strategies of analyzing simulation data of biomolecules that also covers ways to properly design simulations and validate simulation results. In particular, we examine an approach named comparative perturbed-ensembles analysis, which we developed to efficiently detect dynamics in protein MD simulations that can be linked to biological functions. In our recent studies, we implemented this approach to understand allosteric regulations in several disease-associated human proteins. The central task of a comparative perturbed-ensembles analysis is to compare two or more conformational ensembles of a system generated by MD simulations under distinct perturbation conditions. Perturbations can be different sequence variations, ligand-binding conditions, and other physical/chemical modifications of the system. Each simulation is long enough (e.g., microsecond-long) to ensure sufficient sampling of the local substate. Then, sophisticated bioinformatic and statistical tools are applied to extract function-related information from the simulation data, including principal component analysis, residue-residue contact analysis, difference contact network analysis (dCNA) based on the graph theory, and statistical analysis of side-chain conformations. Computational findings are further validated with experimental data. By comparing distinct conformational ensembles, functional micro- to millisecond dynamics can be inferred. In contrast, such a time scale is difficult to reach in a single simulation; even when reached for a single condition of a system, it is elusive as to what dynamical motions are related to functions without, for example, comparing free and substrate-bound proteins at the minimum. We illustrate our approach with three examples. First, we discuss using the approach to identify allosteric pathways in cyclophilin A (CypA), a member of a ubiquitous class of peptidyl-prolyl cis-trans isomerase enzymes. By comparing side-chain torsion-angle distributions of CypA in wild-type and mutant forms, we identified three pathways: two are consistent with recent nuclear magnetic resonance experiments, whereas the third is a novel pathway. Second, we show how the approach enables a dynamical-evolution analysis of the human cyclophilin family. In the analysis, both conserved and divergent conformational dynamics across three cyclophilin isoforms (CypA, CypD, and CypE) were summarized. The conserved dynamics led to the discovery of allosteric networks resembling those found in CypA. A residue wise determinant underlying the unique dynamics in CypD was also detected and validated with additional mutational MD simulations. In the third example, we applied the approach to elucidate a peptide sequence-dependent allosteric mechanism in human Pin 1, a phosphorylation-dependent peptidyl-prolyl isomerase. We finally present our outlook of future directions. Especially, we envisage how the approach could help open a new avenue in drug discovery.

Functional tunability from a distance: Rheostat positions influence allosteric coupling between two distant binding sites

For protein mutagenesis, a common expectation is that important positions will behave like on/off “toggle” switches (i.e., a few substitutions act like wildtype, most abolish function). However, there exists another class of important positions that manifests a wide range of functional outcomes upon substitution: “rheostat” positions. Previously, we evaluated rheostat positions located near the allosteric binding sites for inhibitor alanine (Ala) and activator fructose-1,6-bisphosphate (Fru-1,6-BP) in human liver pyruvate kinase. When substituted with multiple amino acids, many positions demonstrated moderate rheostatic effects on allosteric coupling between effector binding and phosphoenolpyruvate (PEP) binding in the active site. Nonetheless, the combined outcomes of all positions sampled the full range of possible allosteric coupling (full tunability). However, that study only evaluated allosteric tunability of “local” positions, i.e., positions were located near the binding sites of the allosteric ligand being assessed. Here, we evaluated tunability of allosteric coupling when mutated sites were distant from the allosterically-coupled binding sites. Positions near the Ala binding site had rheostatic outcomes on allosteric coupling between Fru-1,6-BP and PEP binding. In contrast, positions in the Fru-1,6-BP site exhibited modest effects on coupling between Ala and PEP binding. Analyzed in aggregate, both PEP/Ala and PEP/Fru-1,6-BP coupling were again fully tunable by amino acid substitutions at this limited set of distant positions. Furthermore, some positions exhibited rheostatic control over multiple parameters and others exhibited rheostatic effects on one parameter and toggle control over a second. These findings highlight challenges in efforts to both predict/interpret mutational outcomes and engineer functions into proteins.

Molecular Mechanism of the Pin1-Histone H1 Interaction

Pin1 is an essential peptidyl-prolyl isomerase (PPIase) that catalyzes cis-trans prolyl isomerization in proteins containing pSer/Thr-Pro motifs. It has an N-terminal WW domain that targets these motifs and a C-terminal PPIase domain that catalyzes isomerization. Recently, Pin1 was shown to modify the conformation of phosphorylated histone H1 and stabilize the chromatin-H1 interaction by increasing its residence time. This Pin1-histone H1 interaction plays a key role in pathogen response, in infection, and in cell cycle control; therefore, anti-Pin1 therapeutics are an important focus for treating infections as well as cancer. Each of the H1 histones (H1.0-H1.5) contains several potential Pin1 recognition pSer/pThr-Pro motifs. To understand the Pin1-histone H1 interaction fully, we investigated how both the isolated WW domain and full-length Pin1 interact with three H1 histone substrate peptide sequences that were previously identified as important binding partners (H1.1, H1.4, and H1.5). NMR spectroscopy was used to measure the binding affinities and the interdomain dynamics upon binding to these sequences. We observed different K_D values depending on the histone binding site, suggesting that energetics play a role in guiding the Pin1-histone interaction. While interdomain interactions vary between the peptides, we find no evidence for allosteric activation for the histone H1 substrates.

Gears-In-Motion: The Interplay of WW and PPIase Domains in Pin1

Pin1 belongs to the family of the peptidyl-prolyl cis-trans isomerase (PPIase), which is a class of enzymes that catalyze the cis/trans isomerization of the Proline residue. Pin1 is unique and only catalyzes the phosphorylated Serine/Threonine-Proline (S/T-P) motifs of a subset of proteins. Since the discovery of Pin1 as a key protein in cell cycle regulation, it has been implicated in numerous diseases, ranging from cancer to neurodegenerative diseases. The main features of Pin1 lies in its two main domains: the WW (two conserved tryptophan) domain and the PPIase domain. Despite extensive studies trying to understand the mechanisms of Pin1 functions, how these two domains contribute to the biological roles of Pin1 in cellular signaling requires more investigations. The WW domain of Pin1 is known to have a higher affinity to its substrate than that of the PPIase domain. Yet, the WW domain seems to prefer the trans configuration of phosphorylated S/T-P motif, while the PPIase catalyzes the cis to trans isomerasion. Such contradicting information has generated much confusion as to the actual mechanism of Pin1 function. In addition, dynamic allostery has been suggested to be important for Pin1 function. Henceforth, in this review, we will be looking at the progress made in understanding the function of Pin1, and how these understandings can aid us in overcoming the diseases implicated by Pin1 such as cancer during drug development.