Investigations of the underlying mechanisms of HIF-1α and CITED2 binding to TAZ1.

The TAZ1 domain of CREB binding protein is crucial for transcriptional regulation and recognizes multiple targets. The interactions between TAZ1 and its specific targets are related to the cellular hypoxic negative feedback regulation. Previous experiments reported that one of the TAZ1 targets, CITED2, is an efficient competitor of another target, HIF-1α. Here, by developing the structure-based models of TAZ1 complexes, we have uncovered the underlying mechanisms of the competitions between the two intrinsic disordered proteins (IDPs) HIF-1α and CITED2 binding to TAZ1. Our results support the experimental hypothesis on the competition mechanisms and the apparent affinity. Furthermore, the simulations locate the dominant position of forming TAZ1-CITED2 complex in both thermodynamics and kinetics. For thermodynamics, TAZ1-CITED2 is the lowest basin located on the free energy surface of binding in the ternary system. For kinetics, the results suggest that CITED2 binds to TAZ1 faster than HIF-1α. In addition, the analysis of contact map and Φ values is important for guiding further experimental studies to understand the biomolecular functions of IDPs.

Quantifying Chromosome Structural Reorganizations during Differentiation, Reprogramming, and Transdifferentiation.

We developed a nonequilibrium model to study chromosome structural reorganizations within a simplified cell developmental system. From the chromosome structural perspective, we predicted that the neural progenitor cell is on the neural developmental path and very close to the transdifferentiation path from the fibroblast to the neuron cell. We identified an early bifurcation of stem cell differentiation processes and the cell-of-origin-specific reprogramming pathways. Our theoretical results are in good agreement with available experimental evidence, promoting future applications of our approach.

Deciphering the molecular mechanism of the cancer formation by chromosome structural dynamics.

Cancer reflects the dysregulation of the underlying gene network, which is strongly related to the 3D genome organization. Numerous efforts have been spent on experimental characterizations of the structural alterations in cancer genomes. However, there is still a lack of genomic structural-level understanding of the temporal dynamics for cancer initiation and progression. Here, we use a landscape-switching model to investigate the chromosome structural transition during the cancerization and reversion processes. We find that the chromosome undergoes a non-monotonic structural shape-changing pathway with initial expansion followed by compaction during both of these processes. Furthermore, our analysis reveals that the chromosome with a more expanding structure than those at both the normal and cancer cell during cancerization exhibits a sparse contact pattern, which shows significant structural similarity to the one at the embryonic stem cell in many aspects, including the trend of contact probability declining with the genomic distance, the global structural shape geometry and the spatial distribution of loci on the chromosome. In light of the intimate structure-function relationship at the chromosomal level, we further describe the cell state transition processes by the chromosome structural changes, suggesting an elevated cell stemness during the formation of the cancer cells. We show that cell cancerization and reversion are highly irreversible processes in terms of the chromosome structural transition pathways, spatial repositioning of chromosomal loci and hysteresis loop of contact evolution analysis. Our model draws a molecular-scale picture of cell cancerization from the chromosome structural perspective. The process contains initial reprogramming towards the stem cell followed by the differentiation towards the cancer cell, accompanied by an initial increase and subsequent decrease of the cell stemness.

Physics of biomolecular recognition and conformational dynamics.

Biomolecular recognition usually leads to the formation of binding complexes, often accompanied by large-scale conformational changes. This process is fundamental to biological functions at the molecular and cellular levels. Uncovering the physical mechanisms of biomolecular recognition and quantifying the key biomolecular interactions are vital to understand these functions. The recently developed energy landscape theory has been successful in quantifying recognition processes and revealing the underlying mechanisms. Recent studies have shown that in addition to affinity, specificity is also crucial for biomolecular recognition. The proposed physical concept of intrinsic specificity based on the underlying energy landscape theory provides a practical way to quantify the specificity. Optimization of affinity and specificity can be adopted as a principle to guide the evolution and design of molecular recognition. This approach can also be used in practice for drug discovery using multidimensional screening to identify lead compounds. The energy landscape topography of molecular recognition is important for revealing the underlying flexible binding or binding-folding mechanisms. In this review, we first introduce the energy landscape theory for molecular recognition and then address four critical issues related to biomolecular recognition and conformational dynamics: (1) specificity quantification of molecular recognition; (2) evolution and design in molecular recognition; (3) flexible molecular recognition; (4) chromosome structural dynamics. The results described here and the discussions of the insights gained from the energy landscape topography can provide valuable guidance for further computational and experimental investigations of biomolecular recognition and conformational dynamics.

Effects of electrostatic interactions on global folding and local conformational dynamics of a multidomain Y-family DNA polymerase.

The Y-family DNA polymerases specialize in translesion DNA synthesis, which is essential for replicating damaged DNA. The Y-family polymerases, which are made up of four stable domains, exhibit extensive distributions of charged residues, and are responsible for the tight formation of the protein-DNA complex. However, it is still unclear how the electrostatic interactions influence the conformational dynamics of the polymerases. Here, we focus on the case of a prototype Y-family DNA polymerase, Dpo4. Using coarse-grained models including a salt-dependent electrostatic potential, we investigate the effects of the electrostatic interactions on the folding process of Dpo4. Our simulations show that strong electrostatic interactions result in a three-state folding of Dpo4, consistent with the experimental observations. This folding process exhibits low cooperativity led by low salt concentration, where the individual domains fold one by one through one single pathway. Since the refined folding order of domains in multidomain proteins can shrink the configurational space, we suggest that the electrostatic interactions facilitate the Dpo4 folding. In addition, we study the local conformational dynamics of Dpo4 in terms of fluctuation and frustration analyses. We show that the electrostatic interactions can exaggerate the local conformational properties, which are in favor of the large-scale conformational transition of Dpo4 during the functional DNA binding. Our results underline the importance of electrostatic interactions in the conformational dynamics of Dpo4 at both the global and local scale, providing useful guidance in protein engineering at the multidomain level.

Binding mechanism and dynamic conformational change of C subunit of PKA with different pathways.

The catalytic subunit of PKA (PKAc) exhibits three major conformational states (open, intermediate, and closed) during the biocatalysis process. Both ATP and substrate/inhibitor can effectively induce the conformational changes of PKAc from open to closed states. Aiming to explore the mechanism of this allosteric regulation, we developed a coarse-grained model and analyzed the dynamics of conformational changes of PKAc during binding by performing molecular dynamics simulations for apo PKAc, binary PKAc (PKAc with ATP, PKAc with PKI), and ternary PKAc (PKAc with ATP and PKI). Our results suggest a mixed binding mechanism of induced fit and conformational selection, with the induced fit dominant. The ligands can drive the movements of Gly-rich loop as well as some regions distal to the active site in PKAc and stabilize them at complex state. In addition, there are two parallel pathways (pathway with PKAc-ATP as an intermediate and pathway PKAc-PKI as an intermediate) during the transition from open to closed states. By molecular dynamics simulations and rate constant analyses, we find that the pathway through PKAc-ATP intermediate is the main binding route from open to closed state because of the fact that the bound PKI will hamper ATP from successful binding and significantly increase the barrier for the second binding subprocess. These findings will provide fundamental insights of the mechanisms of PKAc conformational change upon binding.

Molecular mechanism of multispecific recognition of Calmodulin through conformational changes.

Calmodulin (CaM) is found to have the capability to bind multiple targets. Investigations on the association mechanism of CaM to its targets are crucial for understanding protein-protein binding and recognition. Here, we developed a structure-based model to explore the binding process between CaM and skMLCK binding peptide. We found the cooperation between nonnative electrostatic interaction and nonnative hydrophobic interaction plays an important role in nonspecific recognition between CaM and its target. We also found that the conserved hydrophobic anchors of skMLCK and binding patches of CaM are crucial for the transition from high affinity to high specificity. Furthermore, this association process involves simultaneously both local conformational change of CaM and global conformational changes of the skMLCK binding peptide. We found a landscape with a mixture of the atypical "induced fit," the atypical "conformational selection," and "simultaneously binding-folding," depending on the synchronization of folding and binding. Finally, we extend our discussions on multispecific binding between CaM and its targets. These association characteristics proposed for CaM and skMLCK can provide insights into multispecific binding of CaM.

Position-, disorder-, and salt-dependent diffusion in binding-coupled-folding of intrinsically disordered proteins.

Successful extensions of protein-folding energy landscape theory to intrinsically disordered proteins' (IDPs') binding-coupled-folding transition can enormously simplify this biomolecular process into diffusion along a limited number of reaction coordinates, and the dynamics subsequently is described by Kramers' rate theory. As the critical pre-factor, the diffusion coefficient D has direct implications on the binding kinetics. Here, we employ a structure-based model (SBM) to calculate D in the binding-folding of an IDP prototype. We identify a strong position-dependent D during binding by applying a reaction coordinate that directly measures the fluctuations in a Cartesian configuration space. Using the malleability of the SBM, we modulate the degree of conformational disorder in an isolated IDP and determine complex effects of intrinsic disorder on D varying for different binding stages. Here, D tends to increase with disorder during initial binding but shows a non-monotonic relationship with disorder in terms of a decrease-followed-by-increase in D during the late binding stage. The salt concentration, which correlates with electrostatic interactions via Debye-Hückel theory in our SBM, also modulates D in a stepwise way. The speeding up of diffusion by electrostatic interactions is observed during the formation of the encounter complex at the beginning of binding, while the last diffusive binding dynamics is hindered by non-native salt bridges. Because D describes the diffusive speed locally, which implicitly reflects the roughness of the energy landscape, we are eventually able to portray the binding energy landscape, including that from IDPs' binding, then to binding with partial folding, and finally to rigid docking, as well as that under different environmental salt concentrations. Our theoretical results provide key mechanistic insights into IDPs' binding-folding, which is internally conformation- and externally salt-controlled with respect to diffusion.

Roles of conformational disorder and downhill folding in modulating protein-DNA recognition.

Transcription factors are thought to efficiently search for their target DNA site via a combination of conventional 3D diffusion and 1D diffusion along the DNA molecule mediated by non-specific electrostatic interactions. This process requires the DNA-binding protein to quickly exchange between a search competent and a target recognition mode, but little is known as to how these two binding modes are encoded in the conformational properties of the protein. Here, we investigate this issue on the engrailed homeodomain (EngHD), a DNA-binding domain that folds ultrafast and exhibits a complex conformational behavior consistent with the downhill folding scenario. We explore the interplay between folding and DNA recognition using a coarse-grained computational model that allows us to manipulate the folding properties of the protein and monitor its non-specific and specific binding to DNA. We find that conformational disorder increases the search efficiency of EngHD by promoting a fast gliding search mode in addition to sliding. When gliding, EngHD remains loosely bound to DNA moving linearly along its length. A partially disordered EngHD also binds more dynamically to the target site, reducing the half-life of the specific complex via a spring-loaded mechanism. These findings apply to all conditions leading to partial disorder. However, we also find that at physiologically relevant temperatures EngHD is well folded and can only obtain the conformational flexibility required to accelerate 1D diffusion when it folds/unfolds within the downhill scenario (crossing a marginal free energy barrier). In addition, the conformational flexibility of native downhill EngHD enables its fast reconfiguration to lock into the specific binding site upon arrival, thereby affording finer control of the on- and off-rates of the specific complex. Our results provide key mechanistic insights into how DNA-binding domains optimize specific DNA recognition through the control of their conformational dynamics and folding mechanism.

Quantifying the topography of the intrinsic energy landscape of flexible biomolecular recognition.

Biomolecular functions are determined by their interactions with other molecules. Biomolecular recognition is often flexible and associated with large conformational changes involving both binding and folding. However, the global and physical understanding for the process is still challenging. Here, we quantified the intrinsic energy landscapes of flexible biomolecular recognition in terms of binding-folding dynamics for 15 homodimers by exploring the underlying density of states, using a structure-based model both with and without considering energetic roughness. By quantifying three individual effective intrinsic energy landscapes (one for interfacial binding, two for monomeric folding), the association mechanisms for flexible recognition of 15 homodimers can be classified into two-state cooperative "coupled binding-folding" and three-state noncooperative "folding prior to binding" scenarios. We found that the association mechanism of flexible biomolecular recognition relies on the interplay between the underlying effective intrinsic binding and folding energy landscapes. By quantifying the whole global intrinsic binding-folding energy landscapes, we found strong correlations between the landscape topography measure Λ (dimensionless ratio of energy gap versus roughness modulated by the configurational entropy) and the ratio of the thermodynamic stable temperature versus trapping temperature, as well as between Λ and binding kinetics. Therefore, the global energy landscape topography determines the binding-folding thermodynamics and kinetics, crucial for the feasibility and efficiency of realizing biomolecular function. We also found "U-shape" temperature-dependent kinetic behavior and a dynamical cross-over temperature for dividing exponential and nonexponential kinetics for two-state homodimers. Our study provides a unique way to bridge the gap between theory and experiments.

Multiscaled exploration of coupled folding and binding of an intrinsically disordered molecular recognition element in measles virus nucleoprotein.

Numerous relatively short regions within intrinsically disordered proteins (IDPs) serve as molecular recognition elements (MoREs). They fold into ordered structures upon binding to their partner molecules. Currently, there is still a lack of in-depth understanding of how coupled binding and folding occurs in MoREs. Here, we quantified the unbound ensembles of the α-MoRE within the intrinsically disordered C-terminal domain of the measles virus nucleoprotein. We developed a multiscaled approach by combining a physics-based and an atomic hybrid model to decipher the mechanism by which the α-MoRE interacts with the X domain of the measles virus phosphoprotein. Our multiscaled approach led to remarkable qualitative and quantitative agreements between the theoretical predictions and experimental results (e.g., chemical shifts). We found that the free α-MoRE rapidly interconverts between multiple discrete partially helical conformations and the unfolded state, in accordance with the experimental observations. We quantified the underlying global folding-binding landscape. This leads to a synergistic mechanism in which the recognition event proceeds via (minor) conformational selection, followed by (major) induced folding. We also provided evidence that the α-MoRE is a compact molten globule-like IDP and behaves as a downhill folder in the induced folding process. We further provided a theoretical explanation for the inherent connections between "downhill folding," "molten globule," and "intrinsic disorder" in IDP-related systems. Particularly, we proposed that binding and unbinding of IDPs proceed in a stepwise way through a "kinetic divide-and-conquer" strategy that confers them high specificity without high affinity.

Specificity and affinity quantification of flexible recognition from underlying energy landscape topography.

Flexibility in biomolecular recognition is essential and critical for many cellular activities. Flexible recognition often leads to moderate affinity but high specificity, in contradiction with the conventional wisdom that high affinity and high specificity are coupled. Furthermore, quantitative understanding of the role of flexibility in biomolecular recognition is still challenging. Here, we meet the challenge by quantifying the intrinsic biomolecular recognition energy landscapes with and without flexibility through the underlying density of states. We quantified the thermodynamic intrinsic specificity by the topography of the intrinsic binding energy landscape and the kinetic specificity by association rate. We found that the thermodynamic and kinetic specificity are strongly correlated. Furthermore, we found that flexibility decreases binding affinity on one hand, but increases binding specificity on the other hand, and the decreasing or increasing proportion of affinity and specificity are strongly correlated with the degree of flexibility. This shows more (less) flexibility leads to weaker (stronger) coupling between affinity and specificity. Our work provides a theoretical foundation and quantitative explanation of the previous qualitative studies on the relationship among flexibility, affinity and specificity. In addition, we found that the folding energy landscapes are more funneled with binding, indicating that binding helps folding during the recognition. Finally, we demonstrated that the whole binding-folding energy landscapes can be integrated by the rigid binding and isolated folding energy landscapes under weak flexibility. Our results provide a novel way to quantify the affinity and specificity in flexible biomolecular recognition.

Dynamic conformational change regulates the protein-DNA recognition: an investigation on binding of a Y-family polymerase to its target DNA.

Protein-DNA recognition is a central biological process that governs the life of cells. A protein will often undergo a conformational transition to form the functional complex with its target DNA. The protein conformational dynamics are expected to contribute to the stability and specificity of DNA recognition and therefore may control the functional activity of the protein-DNA complex. Understanding how the conformational dynamics influences the protein-DNA recognition is still challenging. Here, we developed a two-basin structure-based model to explore functional dynamics in Sulfolobus solfataricus DNA Y-family polymerase IV (DPO4) during its binding to DNA. With explicit consideration of non-specific and specific interactions between DPO4 and DNA, we found that DPO4-DNA recognition is comprised of first 3D diffusion, then a short-range adjustment sliding on DNA and finally specific binding. Interestingly, we found that DPO4 is under a conformational equilibrium between multiple states during the binding process and the distributions of the conformations vary at different binding stages. By modulating the strength of the electrostatic interactions, the flexibility of the linker, and the conformational dynamics in DPO4, we drew a clear picture on how DPO4 dynamically regulates the DNA recognition. We argue that the unique features of flexibility and conformational dynamics in DPO4-DNA recognition have direct implications for low-fidelity translesion DNA synthesis, most of which is found to be accomplished by the Y-family DNA polymerases. Our results help complete the description of the DNA synthesis process for the Y-family polymerases. Furthermore, the methods developed here can be widely applied for future investigations on how various proteins recognize and bind specific DNA substrates.

Topography of funneled landscapes determines the thermodynamics and kinetics of protein folding.

The energy landscape approach has played a fundamental role in advancing our understanding of protein folding. Here, we quantify protein folding energy landscapes by exploring the underlying density of states. We identify three quantities essential for characterizing landscape topography: the stabilizing energy gap between the native and nonnative ensembles δE, the energetic roughness ΔE, and the scale of landscape measured by the entropy S. We show that the dimensionless ratio between the gap, roughness, and entropy of the system Λ=δE/(ΔE√(2S)) accurately predicts the thermodynamics, as well as the kinetics of folding. Large Λ implies that the energy gap (or landscape slope towards the native state) is dominant, leading to more funneled landscapes. We investigate the role of topological and energetic roughness for proteins of different sizes and for proteins of the same size, but with different structural topologies. The landscape topography ratio Λ is shown to be monotonically correlated with the thermodynamic stability against trapping, as characterized by the ratio of folding temperature versus trapping temperature. Furthermore, Λ also monotonically correlates with the folding kinetic rates. These results provide the quantitative bridge between the landscape topography and experimental folding measurements.

A Computational and Chemical Design Strategy for Manipulating Glycan-Protein Recognition.

Glycans are complex biomolecules that encode rich information and regulate various biological processes, such as fertilization, host-pathogen binding, and immune recognition, through interactions with glycan-binding proteins. A key driving force for glycan-protein recognition is the interaction between the π electron density of aromatic amino acid side chains and polarized C─H groups of the pyranose (termed the CH-π interaction). However, the relatively weak binding affinity between glycans and proteins has hindered the application of glycan detection and imaging. Here, computational modeling and molecular dynamics simulations are employed to design a chemical strategy that enhances the CH-π interaction between glycans and proteins by genetically incorporating electron-rich tryptophan derivatives into a lectin PhoSL, which specifically recognizes core fucosylated N-linked glycans. This significantly enhances the binding affinity of PhoSL with the core fucose ligand and enables sensitive detection and imaging of core fucosylated glycans in vitro and in xenograft tumors in mice. Further, the study showed that this strategy is applicable to improve the binding affinity of GafD lectin for N-acetylglucosamine-containing glycans. The approach thus provides a general and effective way to manipulate glycan-protein recognition for glycoscience applications.

Importance of electrostatic interactions in the association of intrinsically disordered histone chaperone Chz1 and histone H2A.Z-H2B.

Histone chaperones facilitate assembly and disassembly of nucleosomes. Understanding the process of how histone chaperones associate and dissociate from the histones can help clarify their roles in chromosome metabolism. Some histone chaperones are intrinsically disordered proteins (IDPs). Recent studies of IDPs revealed that the recognition of the biomolecules is realized by the flexibility and dynamics, challenging the century-old structure-function paradigm. Here we investigate the binding between intrinsically disordered chaperone Chz1 and histone variant H2A.Z-H2B by developing a structure-based coarse-grained model, in which Debye-Hückel model is implemented for describing electrostatic interactions due to highly charged characteristic of Chz1 and H2A.Z-H2B. We find that major structural changes of Chz1 only occur after the rate-limiting electrostatic dominant transition state and Chz1 undergoes folding coupled binding through two parallel pathways. Interestingly, although the electrostatic interactions stabilize bound complex and facilitate the recognition at first stage, the rate for formation of the complex is not always accelerated due to slow escape of conformations with non-native electrostatic interactions at low salt concentrations. Our studies provide an ionic-strength-controlled binding/folding mechanism, leading to a cooperative mechanism of "local collapse or trapping" and "fly-casting" together and a new understanding of the roles of electrostatic interactions in IDPs' binding.

Quantifying the large-scale chromosome structural dynamics during the mitosis-to-G1 phase transition of cell cycle.

Cell cycle is known to be regulated by the underlying gene network. Chromosomes, which serve as the scaffold for gene expressions, undergo significant structural reorganizations during mitosis. Understanding the mechanism of the cell cycle from the chromosome structural perspective remains a grand challenge. In this study, we applied an integrated theoretical approach to investigate large-scale chromosome structural dynamics during the mitosis-to-G1 phase transition. We observed that the chromosome structural expansion and adaptation of the structural asphericity do not occur synchronously and attributed this behaviour to the unique unloading sequence of the two types of condensins. Furthermore, we observed that the coherent motions between the chromosomal loci are primarily enhanced within the topologically associating domains (TADs) as cells progress to the G1 phase, suggesting that TADs can be considered as both structural and dynamical units for organizing the three-dimensional chromosome. Our analysis also reveals that the quantified pathways of chromosome structural reorganization during the mitosis-to-G1 phase transition exhibit high stochasticity at the single-cell level and show nonlinear behaviours in changing TADs and contacts formed at the long-range regions. Our findings offer valuable insights into large-scale chromosome structural dynamics after mitosis.

Large-scale data-driven and physics-based models offer insights into the relationships among the structures, dynamics, and functions of chromosomes.

The organized three-dimensional chromosome architecture in the cell nucleus provides scaffolding for precise regulation of gene expression. When the cell changes its identity in the cell-fate decision-making process, extensive rearrangements of chromosome structures occur accompanied by large-scale adaptations of gene expression, underscoring the importance of chromosome dynamics in shaping genome function. Over the last two decades, rapid development of experimental methods has provided unprecedented data to characterize the hierarchical structures and dynamic properties of chromosomes. In parallel, these enormous data offer valuable opportunities for developing quantitative computational models. Here, we review a variety of large-scale polymer models developed to investigate the structures and dynamics of chromosomes. Different from the underlying modeling strategies, these approaches can be classified into data-driven ('top-down') and physics-based ('bottom-up') categories. We discuss their contributions to offering valuable insights into the relationships among the structures, dynamics, and functions of chromosomes and propose the perspective of developing data integration approaches from different experimental technologies and multidisciplinary theoretical/simulation methods combined with different modeling strategies.

Multidomain protein solves the folding problem by multifunnel combined landscape: theoretical investigation of a Y-family DNA polymerase.

Approximately three-fourths of eukaryotic proteins are composed of multiple independently folded domains. However, much of our understanding is based on single domain proteins or isolated domains whose studies directly lead to well-known energy landscape theory in which proteins fold by navigating through a funneled energy landscape toward native structure ensembles. The degrees of freedom for proteins with multiple domains are many orders of magnitude larger than that for single domain proteins. Now, the question arises: How do the multidomain proteins solve the "protein folding problem"? Here, we specifically address this issue by exploring the structure folding relationship of Sulfolobus solfataricus DNA polymerase IV (DPO4), a prototype Y-family DNA polymerase which contains a polymerase core consisting of a palm (P domain), a finger (F domain), and a thumb domain (T domain) in addition to a little finger domain (LF domain). The theoretical results are in good agreement with the experimental data and lead to several theoretical predictions. Finally, we propose that for rapid folding into well-defined conformations which carry out the biological functions, four-domain DPO4 employs a divide-and-conquer strategy, that is, combining multiple individual folding funnels into a single funnel (domains fold independently and then coalesce). In this way, the degrees of freedom for multidomain proteins are polynomial rather than exponential, and the conformational search process can be reduced effectively from a large to a smaller time scale.

Multi-scaled explorations of binding-induced folding of intrinsically disordered protein inhibitor IA3 to its target enzyme.

Biomolecular function is realized by recognition, and increasing evidence shows that recognition is determined not only by structure but also by flexibility and dynamics. We explored a biomolecular recognition process that involves a major conformational change - protein folding. In particular, we explore the binding-induced folding of IA3, an intrinsically disordered protein that blocks the active site cleft of the yeast aspartic proteinase saccharopepsin (YPrA) by folding its own N-terminal residues into an amphipathic alpha helix. We developed a multi-scaled approach that explores the underlying mechanism by combining structure-based molecular dynamics simulations at the residue level with a stochastic path method at the atomic level. Both the free energy profile and the associated kinetic paths reveal a common scheme whereby IA3 binds to its target enzyme prior to folding itself into a helix. This theoretical result is consistent with recent time-resolved experiments. Furthermore, exploration of the detailed trajectories reveals the important roles of non-native interactions in the initial binding that occurs prior to IA3 folding. In contrast to the common view that non-native interactions contribute only to the roughness of landscapes and impede binding, the non-native interactions here facilitate binding by reducing significantly the entropic search space in the landscape. The information gained from multi-scaled simulations of the folding of this intrinsically disordered protein in the presence of its binding target may prove useful in the design of novel inhibitors of aspartic proteinases.