Deciphering GB1's Single Mutational Landscape: Insights from MuMi Analysis.

Mutational changes that affect the binding of the C2 fragment of Streptococcal protein G (GB1) to the Fc domain of human IgG (IgG-Fc) have been extensively studied using deep mutational scanning (DMS), and the binding affinity of all single mutations has been measured experimentally in the literature. To investigate the underlying molecular basis, we perform in silico mutational scanning for all possible single mutations, along with 2 µs-long molecular dynamics (WT-MD) of the wild-type (WT) GB1 in both unbound and IgG-Fc bound forms. We compute the hydrogen bonds between GB1 and IgG-Fc in WT-MD to identify the dominant hydrogen bonds for binding, which we then assess in conformations produced by Mutation and Minimization (MuMi) to explain the fitness landscape of GB1 and IgG-Fc binding. Furthermore, we analyze MuMi and WT-MD to investigate the dynamics of binding, focusing on the relative solvent accessibility of residues and the probability of residues being located at the binding interface. With these analyses, we explain the interactions between GB1 and IgG-Fc and display the structural features of binding. In sum, our findings highlight the potential of MuMi as a reliable and computationally efficient tool for predicting protein fitness landscapes, offering significant advantages over traditional methods. The methodologies and results presented in this study pave the way for improved predictive accuracy in protein stability and interaction studies, which are crucial for advancements in drug design and synthetic biology.

A stochastic programming approach to the antibiotics time machine problem.

Antibiotics Time Machine is an important problem to understand antibiotic resistance and how it can be reversed. Mathematically, it can be modeled as follows: Consider a set of genotypes, each of which contain a set of mutated and unmutated genes. Suppose that a set of growth rate measurements of each genotype under a set of antibiotics is given. The transition probabilities of a 'realization' of a Markov chain associated with each arc under each antibiotic are computable via a predefined function given the growth rate realizations. The aim is to maximize the expected probability of reaching to the genotype with all unmutated genes given the initial genotype in a predetermined number of transitions, considering the following two sources of uncertainties: (i) the randomness in growth rates, (ii) the randomness in transition probabilities, which are functions of growth rates. We develop stochastic mixed-integer linear programming and dynamic programming approaches to solve static and dynamic versions of the Antibiotics Time Machine Problem under the aforementioned uncertainties. We adapt a Sample Average Approximation approach that exploits the special structure of the problem and provide accurate solutions that perform very well in an out-of-sample analysis.

Kinetic Barrier to Enzyme Inhibition Is Manipulated by Dynamical Local Interactions in E. coli DHFR.

Dihydrofolate reductase (DHFR) is an important drug target and a highly studied model protein for understanding enzyme dynamics. DHFR's crucial role in folate synthesis renders it an ideal candidate to understand protein function and protein evolution mechanisms. In this study, to understand how a newly proposed DHFR inhibitor, 4'-deoxy methyl trimethoprim (4'-DTMP), alters evolutionary trajectories, we studied interactions that lead to its superior performance over that of trimethoprim (TMP). To elucidate the inhibition mechanism of 4'-DTMP, we first confirmed, both computationally and experimentally, that the relative binding free energy cost for the mutation of TMP and 4'-DTMP is the same, pointing the origin of the characteristic differences to be kinetic rather than thermodynamic. We then employed an interaction-based analysis by focusing first on the active site and then on the whole enzyme. We confirmed that the polar modification in 4'-DTMP induces additional local interactions with the enzyme, particularly, the M20 loop. These changes are propagated to the whole enzyme as shifts in the hydrogen bond networks. To shed light on the allosteric interactions, we support our analysis with network-based community analysis and show that segmentation of the loop domain of inhibitor-bound DHFR must be avoided by a successful inhibitor.

Conformational multiplicity of bacterial ferric binding protein revealed by small angle x-ray scattering and molecular dynamics calculations.

This study combines molecular dynamics (MD) simulations with small angle x-ray scattering (SAXS) measurements to investigate the range of conformations that can be adopted by a pH/ionic strength (IS) sensitive protein and to quantify its distinct populations in solution. To explore how the conformational distribution of proteins may be modified in the environmental niches of biological media, we focus on the periplasmic ferric binding protein A (FbpA) from Haemophilus influenzae involved in the mechanism by which bacteria capture iron from higher organisms. We examine iron-binding/release mechanisms of FbpA in varying conditions simulating its biological environment. While we show that these changes fall within the detectable range for SAXS as evidenced by differences observed in the theoretical scattering patterns calculated from the crystal structure models of apo and holo forms, detection of conformational changes due to the point mutation D52A and changes in ionic strength (IS) from SAXS scattering profiles have been challenging. Here, to reach conclusions, statistical analyses with SAXS profiles and results from different techniques were combined in a complementary fashion. The SAXS data complemented by size exclusion chromatography point to multiple and/or alternative conformations at physiological IS, whereas they are well-explained by single crystallographic structures in low IS buffers. By fitting the SAXS data with unique conformations sampled by a series of MD simulations under conditions mimicking the buffers, we quantify the populations of the occupied substates. We also find that the D52A mutant that we predicted by coarse-grained computational modeling to allosterically control the iron binding site in FbpA, responds to the environmental changes in our experiments with conformational selection scenarios that differ from those of the wild type.

DHFR Mutants Modulate Their Synchronized Dynamics with the Substrate by Shifting Hydrogen Bond Occupancies.

Antibiotic resistance is a global health problem in which mutations occurring in functional proteins render drugs ineffective. The working mechanisms of the arising mutants are seldom apparent; a methodology to decipher these mechanisms systematically would render devising therapies to control the arising mutational pathways possible. Here we utilize Cα-Cß bond vector relaxations obtained from moderate length MD trajectories to determine conduits for functionality of the resistance conferring mutants of Escherichia coli dihydrofolate reductase. We find that the whole enzyme is synchronized to the motions of the substrate, irrespective of the mutation introducing gain-of-function or loss-of function. The total coordination of the motions suggests changes in the hydrogen bond dynamics with respect to the wild type as a possible route to determine and classify the mode-of-action of individual mutants. As a result, nine trimethoprim-resistant point mutations arising frequently in evolution experiments are categorized. One group of mutants that display the largest occurrence (L28R, W30G) work directly by modifying the dihydrofolate binding region. Conversely, W30R works indirectly by the formation of the E139-R30 salt bridge which releases energy resulting from tight binding by distorting the binding cavity. A third group (D27E, F153S, I94L) arising as single, resistance invoking mutants in evolution experiment trajectories allosterically and dynamically affects a hydrogen bonding motif formed at residues 59-69-71 which in turn modifies the binding site dynamics. The final group (I5F, A26T, R98P) consists of those mutants that have properties most similar to the wild type; these only appear after one of the other mutants is fixed on the protein structure and therefore display clear epistasis. Thus, we show that the binding event is governed by the entire enzyme dynamics while the binding site residues play gating roles. The adjustments made in the total enzyme in response to point mutations are what make quantifying and pinpointing their effect a hard problem. Here, we show that hydrogen bond dynamics recorded on sub-µs time scales provide the necessary fingerprints to decipher the various mechanisms at play.

Computational strategies for protein conformational ensemble detection.

Protein function is constrained by the three-dimensional structure but is delineated by its dynamics. This framework must satisfy specificity of function along with adaptability to changing environments and evolvability under external constraints. The accessibility of the available regions of the energy landscape for a set of conditions and shifts in the populations upon their modulation have effects propagating across scales, from biomolecular interactions, to organisms, to populations. Developing the ability to detect and juggle protein conformations supplemented by a physics-based understanding has implications for not only in vivo problems but also for resistance impeding drug discovery and bionano-sensor design.

A trimethoprim derivative impedes antibiotic resistance evolution.

The antibiotic trimethoprim (TMP) is used to treat a variety of Escherichia coli infections, but its efficacy is limited by the rapid emergence of TMP-resistant bacteria. Previous laboratory evolution experiments have identified resistance-conferring mutations in the gene encoding the TMP target, bacterial dihydrofolate reductase (DHFR), in particular mutation L28R. Here, we show that 4'-desmethyltrimethoprim (4'-DTMP) inhibits both DHFR and its L28R variant, and selects against the emergence of TMP-resistant bacteria that carry the L28R mutation in laboratory experiments. Furthermore, antibiotic-sensitive E. coli populations acquire antibiotic resistance at a substantially slower rate when grown in the presence of 4'-DTMP than in the presence of TMP. We find that 4'-DTMP impedes evolution of resistance by selecting against resistant genotypes with the L28R mutation and diverting genetic trajectories to other resistance-conferring DHFR mutations with catalytic deficiencies. Our results demonstrate how a detailed characterization of resistance-conferring mutations in a target enzyme can help identify potential drugs against antibiotic-resistant bacteria, which may ultimately increase long-term efficacy of antimicrobial therapies by modulating evolutionary trajectories that lead to resistance.

Dynamic Community Composition Unravels Allosteric Communication in PDZ3.

The third domain of PSD-95 (PDZ3) is a model for investigating allosteric communication in protein and ligand interactions. While motifs contributing to its binding specificity have been scrutinized, a conformational dynamical basis is yet to be established. Despite the miniscule structural changes due to point mutants, the observed significant binding affinity differences have previously been assessed with a focus on two α-helices located at the binding groove (α2) and the C-terminus (α3). Here, we employ a new computational approach to develop a generalized view on the molecular basis of PDZ3 binding selectivity and interaction communication for a set of point mutants of the protein (G330T, H372A, G330T-H372A) and its ligand (CRIPT, named L1, and its T-2F variant, L2) along with the wild type (WT). To analyze the dynamical aspects hidden in the conformations that are produced by molecular dynamics simulations, we utilize variations in community composition calculated based on the betweenness centrality measure from graph theory. We find that the highly charged N-terminus, which is located far from the ligand, has the propensity to share the same community with the ligand in the biologically functional complexes, indicating a distal segment might mediate the binding dynamics. N- and C-termini of PDZ3 share communities, and α3 acts as a hub for the whole protein by sustaining the communication with all structural segments, albeit being a trait not unique to the functional complexes. Moreover, α2 which lines the binding cavity frequently parts communities with the ligand and is not a controller of the binding but is rather a slave to the overall dynamics coordinated by the N-terminus. Thus, ligand binding fate in PDZ3 is traced to the population of community compositions extracted from dynamics despite the lack of significant conformational changes.

N-Terminus of the Third PDZ Domain of PSD-95 Orchestrates Allosteric Communication for Selective Ligand Binding.

PDZ domains constitute common models to study single-domain allostery without significant structural changes. The third PDZ domain of PSD-95 (PDZ3) is known to have selective structural features that confer unique modulatory roles to this unit. In this model system, two residues, H372 directly connected to the binding site and G330 holding an off-binding-site position, were designated to assess the effect of mutations on binding selectivity. It has been observed that the H372A and G330T-H372A mutations change ligand preferences from class I (T/S amino acid at position -2 of the ligand) to class II (hydrophobic amino acid at the same position). Alternatively, the G330T single mutation leads to the recognition of both ligand classes. We have performed a series of molecular dynamics (MD) simulations for wild-type, H372A, and G330T single mutants and a double mutant of PDZ3 in the absence and presence of both types of ligands. With the combination of free-energy difference calculations and a detailed analysis of MD trajectories, "class switching" and "class bridging" behavior of PDZ3 mutants, as well as their effects on ligand selection and binding affinities are explained. We show that the dynamics of the charged N-terminus plays a fundamental role in determining the binding preferences in PDZ3 by altering the electrostatic energy. These findings are corroborated by simulations on N-terminus-truncated versions of these systems. The dynamical allostery orchestrated by the N-terminus offers a fresh perspective to the study of communication pathways in proteins.

A Coarse-Grained Methodology Identifies Intrinsic Mechanisms That Dissociate Interacting Protein Pairs.

We address the problem of triggering dissociation events between proteins that have formed a complex. We have collected a set of 25 non-redundant, functionally diverse protein complexes having high-resolution three-dimensional structures in both the unbound and bound forms. We unify elastic network models with perturbation response scanning (PRS) methodology as an efficient approach for predicting residues that have the propensity to trigger dissociation of an interacting protein pair, using the three-dimensional structures of the bound and unbound proteins as input. PRS reveals that while for a group of protein pairs, residues involved in the conformational shifts are confined to regions with large motions, there are others where they originate from parts of the protein unaffected structurally by binding. Strikingly, only a few of the complexes have interface residues responsible for dissociation. We find two main modes of response: In one mode, remote control of dissociation in which disruption of the electrostatic potential distribution along protein surfaces play the major role; in the alternative mode, mechanical control of dissociation by remote residues prevail. In the former, dissociation is triggered by changes in the local environment of the protein, e.g., pH or ionic strength, while in the latter, specific perturbations arriving at the controlling residues, e.g., via binding to a third interacting partner is required for decomplexation. We resolve the observations by relying on an electromechanical coupling model which reduces to the usual elastic network result in the limit of the lack of coupling. We validate the approach by illustrating the biological significance of top residues selected by PRS on select cases where we show that the residues whose perturbation leads to the observed conformational changes correspond to either functionally important or highly conserved residues in the complex.

High-Order Epistasis in Catalytic Power of Dihydrofolate Reductase Gives Rise to a Rugged Fitness Landscape in the Presence of Trimethoprim Selection.

Evolutionary fitness landscapes of several antibiotic target proteins have been comprehensively mapped showing strong high-order epistasis between mutations, but understanding these effects at the biochemical and structural levels remained open. Here, we carried out an extensive experimental and computational study to quantitatively understand the evolutionary dynamics of Escherichia coli dihydrofolate reductase (DHFR) enzyme in the presence of trimethoprim-induced selection. To facilitate this, we developed a new in vitro assay for rapidly characterizing DHFR steady-state kinetics. Biochemical and structural characterization of resistance-conferring mutations targeting a total of ten residues spanning the substrate binding pocket of DHFR revealed distinct changes in the catalytic efficiencies of mutated DHFR enzymes. Next, we measured biochemical parameters (Km, Ki, and kcat) for a mutant library carrying all possible combinations of six resistance-conferring DHFR mutations and quantified epistatic interactions between them. We found that the high-order epistasis in catalytic power of DHFR (kcat and Km) creates a rugged fitness landscape under trimethoprim selection. Taken together, our data provide a concrete illustration of how epistatic coupling at the level of biochemical parameters can give rise to complex fitness landscapes, and suggest new strategies for developing mutant specific inhibitors.

MODE-TASK: large-scale protein motion tools.

Summary: MODE-TASK, a novel and versatile software suite, comprises Principal Component Analysis, Multidimensional Scaling, and t-Distributed Stochastic Neighbor Embedding techniques using Molecular Dynamics trajectories. MODE-TASK also includes a Normal Mode Analysis tool based on Anisotropic Network Model so as to provide a variety of ways to analyse and compare large-scale motions of protein complexes for which long MD simulations are prohibitive. Beside the command line function, a GUI has been developed as a PyMOL plugin. Availability and implementation: MODE-TASK is open source, and available for download from https://github.com/RUBi-ZA/MODE-TASK. It is implemented in Python and C++. It is compatible with Python 2.x and Python 3.x and can be installed by Conda. Supplementary information: Supplementary data are available at Bioinformatics online.

Unraveling the Motions behind Enterovirus 71 Uncoating.

Enterovirus 71 can be a severe pathogen in small children and immunocompromised adults. Virus uncoating is a critical step in the infection of the host cell; however, the mechanisms that control this process remain poorly understood. We applied normal mode analysis and perturbation response scanning to several complexes of the virus capsid and present a coarse-graining approach to analyze the full capsid. We show that our method offers an alternative to expressing the system as a set of rigid blocks and accounts for the interconnection between nodes within each subunit and protein interfaces across the capsid. In our coarse-grained approach, the modes associated with capsid expansion are captured in the first three nondegenerate modes and correspond to the changes observed in structural studies of the virus. We show that the resolution of the analysis may be modified without losing information on the global motions leading to uncoating. Perturbation response scanning revealed that a protomer cannot serve as a functional unit to explain deformations of the capsid. Instead, we define a pentamer as the minimum functional unit to investigate changes within the capsid. From the modal analysis and perturbation response scanning, we locate a hotspot region surrounding the fivefold axis. The range of the effect of these single, hotspot residues extend to 140 Å. The perturbation of internal capsid residues in this region displayed greatest propensity to capsid expansion, thus indicating the significant role that the RNA genome may play in triggering uncoating.

MD-TASK: a software suite for analyzing molecular dynamics trajectories.

SUMMARY: Molecular dynamics (MD) determines the physical motions of atoms of a biological macromolecule in a cell-like environment and is an important method in structural bioinformatics. Traditionally, measurements such as root mean square deviation, root mean square fluctuation, radius of gyration, and various energy measures have been used to analyze MD simulations. Here, we present MD-TASK, a novel software suite that employs graph theory techniques, perturbation response scanning, and dynamic cross-correlation to provide unique ways for analyzing MD trajectories. AVAILABILITY AND IMPLEMENTATION: MD-TASK has been open-sourced and is available for download from https://github.com/RUBi-ZA/MD-TASK , implemented in Python and supported on Linux/Unix. CONTACT: o.tastanbishop@ru.ac.za.

Mechanisms by Which Salt Concentration Moderates the Dynamics of Human Serum Transferrin.

The dynamical and thermodynamic behavior of human transferrin (hTf) protein in saline aqueous solution of various concentrations is studied. hTf is an essential transport protein circulating iron in the blood and delivering it to tissues. It displays highly pH dependent cooperativity between the two lobes, each carrying an iron, and forms a tight complex with the receptor during endocytosis, eventually recycled to the serum after iron release. Molecular dynamics simulations are used to investigate the effects of the amount of salt on protein conformation and dynamics to analyze the structure-function relationship in free hTf at serum pH. To monitor the ionic strength dependence, four different ionic concentrations, 0, 50, 130, and 210 mM NaCl for two protonation states of the iron coordination site is considered. Two mechanisms by which salt affects hTf are disclosed. In the totally closed state where iron coordinating tyrosines are deprotonated, the addition of even 50 mM of salt alters the electrostatic potential distribution around the protein, opening energetic pathways for tyrosine protonation from nearby charged residues as a required first step for iron release. Once domain opening is observed, conformational plasticity renders the iron binding site more accessible by the solvent. At this second stage of iron release, R124 in the N-lobe is identified as kinetically significant anion binding site that accommodates chloride ions and allosterically communicates with the iron binding residues. Opening motions are maximized at 150 mM IS in the N-lobe, and at 210 mM in the C-lobe. The extra mobility in the latter is thought to preclude binding of hTf to its receptor. Thus, the physiological IS is optimal for exposing iron for release from hTf. However, the calculated binding affinities of iron show that even in the most open conformations, iron dissociation needs to be accompanied by chelators.

Increased substrate affinity in the Escherichia coli L28R dihydrofolate reductase mutant causes trimethoprim resistance.

Dihydrofolate reductase (DHFR) is a ubiquitous enzyme with an essential role in cell metabolism. DHFR catalyzes the reduction of dihydrofolate to tetrahydrofolate, which is a precursor for purine and thymidylate synthesis. Several DHFR targeting antifolate drugs including trimethoprim, a competitive antibacterial inhibitor, have therefore been developed and are clinically used. Evolution of resistance against antifolates is a common public health problem rendering these drugs ineffective. To combat the resistance problem, it is important to understand resistance-conferring changes in the DHFR structure and accordingly develop alternative strategies. Here, we structurally and dynamically characterize Escherichia coli DHFR in its wild type (WT) and trimethoprim resistant L28R mutant forms in the presence of the substrate and its inhibitor trimethoprim. We use molecular dynamics simulations to determine the conformational space, loop dynamics and hydrogen bond distributions at the active site of DHFR for the WT and the L28R mutant. We also report their experimental kcat, Km, and Ki values, accompanied by isothermal titration calorimetry measurements of DHFR that distinguish enthalpic and entropic contributions to trimethoprim binding. Although mutations that confer resistance to competitive inhibitors typically make enzymes more promiscuous and decrease affinity to both the substrate and the inhibitor, strikingly, we find that the L28R mutant has a unique resistance mechanism. While the binding affinity differences between the WT and the mutant for the inhibitor and the substrate are small, the newly formed extra hydrogen bonds with the aminobenzoyl glutamate tail of DHF in the L28R mutant leads to increased barriers for the dissociation of the substrate and the product. Therefore, the L28R mutant indirectly gains resistance by enjoying prolonged binding times in the enzyme-substrate complex. While this also leads to slower product release and decreases the catalytic rate of the L28R mutant, the overall effect is the maintenance of a sufficient product formation rate. Finally, the experimental and computational analyses together reveal the changes that occur in the energetic landscape of DHFR upon the resistance-conferring L28R mutation. We show that the negative entropy associated with the binding of trimethoprim in WT DHFR is due to water organization at the binding interface. Our study lays the framework to study structural changes in other trimethoprim resistant DHFR mutants.

FbpA iron storage and release are governed by periplasmic microenvironments.

Ferric binding protein (FbpA) is part of an elaborate iron piracy mechanism evolved in Gram-negative bacteria, shuttling iron in the periplasmic space, from the outer to the cytoplasmic membrane side. We address how the dissociation process of iron is facilitated, since the binding constant of iron is on the order of 1018 M-1 at 6.5 pH and 200 mM ionic strength (IS). We monitor the conformational preferences of FbpA by extensive molecular dynamics (MD) simulations under conditions where IS, charge states of iron coordinating tyrosines and pH are varied, as well as when a mutation is introduced at an allosteric site. Steered MD is utilized to predict the binding affinity of iron. After triggering lobe opening by changing the charge states of tyrosines, the conformations adopted and the iron binding affinity still depend on pH, IS and allosteric interactions. To relate the observed conformational changes to the environmental conditions that might be encountered in the periplasmic space, we offer a plausible model that couples electrostatic potential distribution to the mechanical motions invoked. Although low pH/IS and allosteric perturbations decrease the affinity of iron, it remains high for spontaneous dissociation. However, the conformational changes modulated by the environmental conditions expose iron for chelation. Our study provides a quantitative dimension and molecular details to interpret the contribution of possible environmental conditions present in the periplasmic space to iron dissociation from FbpA, opening up the opportunity of modulating function via allosteric mutations or altering environmental conditions, thus offering a new route to developing strategies towards antibiotic resistance by targeting nutritional requirements.

Detailed molecular dynamics simulations of human transferrin provide insights into iron release dynamics at serum and endosomal pH.

Human serum transferrin (hTf) transports ferric ions in the blood stream and delivers them to cells via receptor-mediated endocytosis. hTf is folded into two homologous lobes; we utilize three of the available crystal structures delineating large conformational changes involved in iron binding/dissociation. We address the problems of whether the release process follows the same trend at serum (~7.4) and endosomal (~5.6) pH, and if there is communication between the lobes. In the absence of the transferrin receptor, we study the dynamics of the full structure as well as the separate lobes in different closed, partially open, and open conformations under neutral and endosomal pH conditions. Results corroborate those experimental observations underscoring the distinguishing effect of pH on the dynamics of hTf. Furthermore, in a total of 2 µs molecular dynamics simulations, residue fluctuations elucidate the cross talk between the lobes correlated by the peptide linker bridging them at serum pH, while their correlations are lost under endosomal conditions. At serum pH, interplay between relative mobility of the lobes is correlated with iron release rates, rendering the initial conformational change an important contributor to the dynamics under these conditions. Interestingly, C-lobe opening lags behind that of the N-lobe as long as there is at least one iron bound, making the more stable C-lobe an attractive target for recognition by receptors. At endosomal pH, both lobes readily open, making irons available for delivery.

Perturbation response scanning specifies key regions in subtilisin serine protease for both function and stability.

Can one infer the amino acids of the enzymes that are responsible for the stability or the level of the catalytic activity by computationally experimenting on the inhibited enzyme in the enzyme-inhibitor complex? In this article, we answer this question positively both by designing molecular dynamics simulations and by devising coarse-grained methodologies on the subtilisin serine protease. Both methodologies are based on the cross-correlations of the fluctuations of the residues, obtained either by monitoring the trajectories from the simulation or by constructing the inverse Laplacian of the elastic network model, of the complex. A perturbation scanning is applied to the complex using these correlations. The results indicate that the two methods almost point out the same regions on the flexible of the enzyme. These regions are: (i) 50-61, (ii) 155-164 and (iii) 192-194, all of which are designated to be important by experimental studies in the literature.

Protonation states of remote residues affect binding-release dynamics of the ligand but not the conformation of apo ferric binding protein.

We have studied the apo (Fe(3+) free) form of periplasmic ferric binding protein (FbpA) under different conditions and we have monitored the changes in the binding and release dynamics of H2PO4(-) that acts as a synergistic anion in the presence of Fe(3+). Our simulations predict a dissociation constant in agreement with the experimentally measured value under the same ionic pH conditions. We apply perturbations relevant for changes in environmental conditions as (i) different values of ionic strength and (ii) protonation of a group of residues to mimic a different pH environment. Local perturbations are also studied by protonation or mutation of a site distal to the binding region that is known to mechanically manipulate the hinge-like motions of FbpA. We find that while the average conformation of the protein is intact in all simulations, the H2PO4(-) binding constant is substantially altered by the changing conditions. In particular, the bound fraction which is 20% for the wild type system is increased to 50% with a D52A mutation/protonation and further to over 90% at the protonation conditions mimicking those at pH 5.5. The change in the dynamics is traced to the altered electrostatic potential distribution on the surface of the protein which in turn affects hydrogen bonding patterns at the active site. The observations are also quantified by rigorous free energy calculations. Our results lend clues as to how the environment versus single residue perturbations may be utilized for regulation of binding modes in hFbpA systems in the absence of conformational changes.