Heat-induced structural and chemical changes to a computationally designed miniprotein.

The de novo design of miniprotein inhibitors has recently emerged as a new technology to create proteins that bind with high affinity to specific therapeutic targets. Their size, ease of expression, and apparent high stability makes them excellent candidates for a new class of protein drugs. However, beyond circular dichroism melts and hydrogen/deuterium exchange experiments, little is known about their dynamics, especially at the elevated temperatures they seemingly tolerate quite well. To address that and gain insight for future designs, we have focused on identifying unintended and previously overlooked heat-induced structural and chemical changes in a particularly stable model miniprotein, EHEE_rd2_0005. Nuclear magnetic resonance (NMR) studies suggest the presence of dynamics on multiple time and temperature scales. Transiently elevating the temperature results in spontaneous chemical deamidation visible in the NMR spectra, which we validate using both capillary electrophoresis and mass spectrometry (MS) experiments. High temperatures also result in greatly accelerated intrinsic rates of hydrogen exchange and signal loss in NMR heteronuclear single quantum coherence spectra from local unfolding. These losses are in excellent agreement with both room temperature hydrogen exchange experiments and hydrogen bond disruption in replica exchange molecular dynamics simulations. Our analysis reveals important principles for future miniprotein designs and the potential for high stability to result in long-lived alternate conformational states.

Effects of Xylanase A double mutation on substrate specificity and structural dynamics.

While protein activity is traditionally studied with a major focus on the active site, the activity of enzymes has been hypothesized to be linked to the flexibility of adjacent regions, warranting more exploration into how the dynamics in these regions affects catalytic turnover. One such enzyme is Xylanase A (XylA), which cleaves hemicellulose xylan polymers by hydrolysis at internal ß-1,4-xylosidic linkages. It contains a "thumb" region whose flexibility has been suggested to affect the activity. The double mutation D11F/R122D was previously found to affect activity and potentially bias the thumb region to a more open conformation. We find that the D11F/R122D double mutation shows substrate-dependent effects, increasing activity on the non-native substrate ONPX2 but decreasing activity on its native xylan substrate. To characterize how the double mutant causes these kinetics changes, nuclear magnetic resonance (NMR) and molecular dynamics (MD) simulations were used to probe structural and flexibility changes. NMR chemical shift perturbations revealed structural changes in the double mutant relative to the wild-type, specifically in the thumb and fingers regions. Increased slow-timescale dynamics in the fingers region was observed as intermediate-exchange line broadening. Lipari-Szabo order parameters show negligible changes in flexibility in the thumb region in the presence of the double mutation. To help understand if there is increased energetic accessibility to the open state upon mutation, alchemical free energy simulations were employed that indicated thumb opening is more favorable in the double mutant. These studies aid in further characterizing how flexibility in adjacent regions affects the function of XylA.

Oxidation of Dueling Cysteine Promotes Subunit Exchange in SOD1.

The heterodimerization of wild-type (WT) Cu, Zn superoxide dismutase-1 (SOD1) and mutant SOD1 might be a critical step in the pathogenesis of SOD1-linked amyotrophic lateral sclerosis (ALS). Post-translational modifications that accelerate SOD1 heterodimerization remain unidentified. Here, we used capillary electrophoresis to quantify the effect of cysteine-111 oxidation on the rate and free energy of ALS mutant/WT SOD1 heterodimerization. The oxidation of Cys111-ß-SH to sulfinic and sulfonic acid (by hydrogen peroxide) increased rates of heterodimerization (with unoxidized protein) by ∼3-fold. Cysteine oxidation drove the equilibrium free energy of SOD1 heterodimerization by up to ΔΔG = -5.11 ± 0.36 kJ mol-1. Molecular dynamics simulations suggested that this enhanced heterodimerization, between oxidized homodimers and unoxidized homodimers, was promoted by electrostatic repulsion between the two "dueling" Cys111-SO2-/SO3-, which point toward one another in the homodimeric state. Together, these results suggest that oxidation of Cys-111 promotes subunit exchange between oxidized homodimers and unoxidized homodimers, regardless of whether they are mutant or WT dimers.

Predicting binding affinity changes from long-distance mutations using molecular dynamics simulations and Rosetta.

Computationally modeling how mutations affect protein-protein binding not only helps uncover the biophysics of protein interfaces, but also enables the redesign and optimization of protein interactions. Traditional high-throughput methods for estimating binding free energy changes are currently limited to mutations directly at the interface due to difficulties in accurately modeling how long-distance mutations propagate their effects through the protein structure. However, the modeling and design of such mutations is of substantial interest as it allows for greater control and flexibility in protein design applications. We have developed a method that combines high-throughput Rosetta-based side-chain optimization with conformational sampling using classical molecular dynamics simulations, finding significant improvements in our ability to accurately predict long-distance mutational perturbations to protein binding. Our approach uses an analytical framework grounded in alchemical free energy calculations while enabling exploration of a vastly larger sequence space. When comparing to experimental data, we find that our method can predict internal long-distance mutational perturbations with a level of accuracy similar to that of traditional methods in predicting the effects of mutations at the protein-protein interface. This work represents a new and generalizable approach to optimize protein free energy landscapes for desired biological functions.

Prediction of Fluorophore Brightness in Designed Mini Fluorescence Activating Proteins.

The de novo computational design of proteins with predefined three-dimensional structure is becoming much more routine due to advancements both in force fields and algorithms. However, creating designs with functions beyond folding is more challenging. In that regard, the recent design of small beta barrel proteins that activate the fluorescence of an exogenous small molecule chromophore (DFHBI) is noteworthy. These proteins, termed mini fluorescence activating proteins (mFAPs), have been shown to increase the brightness of the chromophore more than 100-fold upon binding to the designed ligand pocket. The design process created a large library of variants with different brightness levels but gave no rational explanation for why one variant was brighter than another. Here, we use quantum mechanics and molecular dynamics simulations to investigate how molecular flexibility in the ground and excited states influences brightness. We show that the ability of the protein to resist dihedral angle rotation of the chromophore is critical for predicting brightness. Our simulations suggest that the mFAP/DFHBI complex has a rough energy landscape, requiring extensive ground-state sampling to achieve converged predictions of excited-state kinetics. While computationally demanding, this roughness suggests that mFAP protein function can be enhanced by reshaping the energy landscape toward conformations that better resist DFHBI bond rotation.

Free energy calculations of ALS-causing SOD1 mutants reveal common perturbations to stability and dynamics along the maturation pathway.

With over 150 heritable mutations identified as disease-causative, superoxide dismutase 1 (SOD1) has been a main target of amyotrophic lateral sclerosis (ALS) research and therapeutic efforts. However, recent evidence has suggested that neither loss of function nor protein aggregation is responsible for promoting neurotoxicity. Furthermore, there is no clear pattern to the nature or the location of these mutations that could suggest a molecular mechanism behind SOD1-linked ALS. Here, we utilize reliable and accurate computational techniques to predict the perturbations of 10 such mutations to the free energy changes of SOD1 as it matures from apo monomer to metallated dimer. We find that the free energy perturbations caused by these mutations strongly depend on maturational progress, indicating the need for state-specific therapeutic targeting. We also find that many mutations exhibit similar patterns of perturbation to native and non-native maturation, indicating strong thermodynamic coupling between the dynamics at various sites of maturation within SOD1. These results suggest the presence of an allosteric network in SOD1 which is vulnerable to disruption by these mutations. Analysis of these perturbations may contribute to uncovering a unifying molecular mechanism which explains SOD1-linked ALS and help to guide future therapeutic efforts.

Resolving overlapped signals with automated FitNMR analytical peak modeling.

Nuclear magnetic resonance (NMR) is a valuable tool for determining the structures of molecules and probing their dynamics. A longstanding problem facing both small-molecule and macromolecular NMR is overlapped signals in crowded spectra. To address this, we have developed a method that extracts peak features by fitting analytically derived models of NMR lineshapes. The approach takes into account the effects of truncation, apodization, and the resulting artifacts, while avoiding systematic errors that have affected other models. Even severely overlapped peaks, beyond the point of coalescence, can be distinguished in both simulated and experimental data. We show that the method can measure unresolved backbone scalar couplings directly from a 2D proton-nitrogen spectrum of a de novo designed mini protein. The algorithm is implemented in the FitNMR open-source R package and can be used to analyze nearly any type of single or multidimensional data from small molecules or biomolecules.

Altered-specificity mutants of the HIV Rev arginine-rich motif-RRE IIB interaction.

Arginine-rich motifs (ARMs) bind RNA structures with high affinity and specificity, and the human immunodeficiency virus (HIV) exploits ARM-RNA interactions to regulate its lifecycle. The expression of HIV structural genes relies on recognition between the ARM of its Rev protein and its primary binding site, an internal loop in the viral RNA, the Rev-response element region IIB (IIB). Many functional variants of the Rev ARM-IIB interaction have been discovered, yet how easily it can evolve new specificities is poorly explored. A double mutant of Rev ARM, R35G-N40 V, uses an unknown strategy to recognize IIB. Here, isothermal titration calorimetry and gel shift assays show that the R35G-N40V-IIB interaction has high affinity and specificity in vitro and a larger unfavorable entropy change upon binding than that of wild-type Rev ARM-IIB. In stark contrast with the critical dependence of wild-type Rev on Arg35, Arg39, Asn40, and Arg44, mutational profiling shows R35G-N40V is highly mutable at positions 40 and 44 and dependent on Gly35, Arg38, Arg39, Arg42, and Arg43. Affinity measurements in vitro and reporter assay measurements in vivo are consistent with the wild-type Rev ARM and R35G-N40V maintaining their recognition strategies when binding IIB mutants specific to wild-type Rev ARM and R35G-N40V, respectively. Some single amino acid mutants of wild-type Rev ARM and R35G-N40V have enhanced specificity, recognizing mutant IIBs yet not wild-type IIB. These results provide another example of viral ARM-RNA interactions evolving new specificities with few mutations, consistent with neutral theories of evolution.

Enhancing NMR derived ensembles with kinetics on multiple timescales.

Nuclear magnetic resonance (NMR) has the unique advantage of elucidating the structure and dynamics of biomolecules in solution at physiological temperatures, where they are in constant movement on timescales from picoseconds to milliseconds. Such motions have been shown to be critical for enzyme catalysis, allosteric regulation, and molecular recognition. With NMR being particularly sensitive to these timescales, detailed information about the kinetics can be acquired. However, nearly all methods of NMR-based biomolecular structure determination neglect kinetics, which introduces a large approximation to the underlying physics, limiting both structural resolution and the ability to accurately determine molecular flexibility. Here we present the Kinetic Ensemble approach that uses a hierarchy of interconversion rates between a set of ensemble members to rigorously calculate Nuclear Overhauser Effect (NOE) intensities. It can be used to simultaneously refine both temporal and structural coordinates. By generalizing ideas from the extended model free approach, the method can analyze the amplitudes and kinetics of motions anywhere along the backbone or side chains. Furthermore, analysis of a large set of crystal structures suggests that NOE data contains a surprising amount of high-resolution information that is better modeled using our approach. The Kinetic Ensemble approach provides the means to unify numerous types of experiments under a single quantitative framework and more fully characterize and exploit kinetically distinct protein states. While we apply the approach here to the protein ubiquitin and cross validate it with previously derived datasets, the approach can be applied to any protein for which NOE data is available.

Mechanistic Insights into Microsecond Time-Scale Motion of Solid Proteins Using Complementary 15N and 1H Relaxation Dispersion Techniques.

NMR relaxation dispersion methods provide a holistic way to observe microsecond time-scale protein backbone motion both in solution and in the solid state. Different nuclei (1H and 15N) and different relaxation dispersion techniques (Bloch-McConnell and near-rotary-resonance) give complementary information about the amplitudes and time scales of the conformational dynamics and provide comprehensive insights into the mechanistic details of the structural rearrangements. In this paper, we exemplify the benefits of the combination of various solution- and solid-state relaxation dispersion methods on a microcrystalline protein (α-spectrin SH3 domain), for which we are able to identify and model the functionally relevant conformational rearrangements around the ligand recognition loop occurring on multiple microsecond time scales. The observed loop motions suggest that the SH3 domain exists in a binding-competent conformation in dynamic equilibrium with a sterically impaired ground-state conformation both in solution and in crystalline form. This inherent plasticity between the interconverting macrostates is compatible with a conformational-preselection model and provides new insights into the recognition mechanisms of SH3 domains.

Recent advances in measuring the kinetics of biomolecules by NMR relaxation dispersion spectroscopy.

Protein function can be modulated or dictated by the amplitude and timescale of biomolecular motion, therefore it is imperative to study protein dynamics. Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful technique capable of studying timescales of motion that range from those faster than molecular reorientation on the picosecond timescale to those that occur in real-time. Across this entire regime, NMR observables can report on the amplitude of atomic motion, and the kinetics of atomic motion can be ascertained with a wide variety of experimental techniques from real-time to milliseconds and several nanoseconds to picoseconds. Still a four orders of magnitude window between several nanoseconds and tens of microseconds has remained elusive. Here, we highlight new relaxation dispersion NMR techniques that serve to cover this "hidden-time" window up to hundreds of nanoseconds that achieve atomic resolution while studying the molecule under physiological conditions.

Personalised estimation of a woman's most fertile days.

OBJECTIVES: We propose a new, personalised approach of estimating a woman's most fertile days that only requires recording the first day of menses and can use a smartphone to convey this information to the user so that she can plan or prevent pregnancy. METHODS: We performed a retrospective analysis of two cohort studies (a North Carolina-based study and the Early Pregnancy Study [EPS]) and a prospective multicentre trial (World Health Organization [WHO] study). The North Carolina study consisted of 68 sexually active women with either an intrauterine device or tubal ligation. The EPS comprised 221 women who planned to become pregnant and had no known fertility problems. The WHO study consisted of 706 women from five geographically and culturally diverse settings. Bayesian statistical methods were used to design our proposed method, Dynamic Optimal Timing (DOT). Simulation studies were used to estimate the cumulative pregnancy risk. RESULTS: For the proposed method, simulation analyses indicated a 4.4% cumulative probability of pregnancy over 13 cycles with correct use. After a calibration window, this method flagged between 11 and 13 days when unprotected intercourse should be avoided per cycle. Eligible women should have cycle lengths between 20 and 40 days with a variability range less than or equal to 9 days. CONCLUSIONS: DOT can easily be implemented by computer or smartphone applications, allowing for women to make more informed decisions about their fertility. This approach is already incorporated into a patent-pending system and is available for free download on iPhones and Androids.

Allosteric switch regulates protein-protein binding through collective motion.

Many biological processes depend on allosteric communication between different parts of a protein, but the role of internal protein motion in propagating signals through the structure remains largely unknown. Through an experimental and computational analysis of the ground state dynamics in ubiquitin, we identify a collective global motion that is specifically linked to a conformational switch distant from the binding interface. This allosteric coupling is also present in crystal structures and is found to facilitate multispecificity, particularly binding to the ubiquitin-specific protease (USP) family of deubiquitinases. The collective motion that enables this allosteric communication does not affect binding through localized changes but, instead, depends on expansion and contraction of the entire protein domain. The characterization of these collective motions represents a promising avenue for finding and manipulating allosteric networks.

HK022 Nun Requires Arginine-Rich Motif Residues Distinct from λ N.

UNLABELLED: Bacteriophage λ N protein binds boxB RNA hairpins in the nut (N utilization) sites of immediate early λ transcripts and interacts with host factors to suppress transcriptional termination at downstream terminators. In opposition to λ N, the Nun protein of HK022 binds the boxBs of coinfecting λ transcripts, interacts with a similar or identical set of host factors, and terminates transcription to suppress λ replication. Comparison of N-boxB and Nun-boxB nuclear magnetic resonance (NMR) structural models suggests similar interactions, though limited mutagenesis of Nun is available. Here, libraries of Nun's arginine-rich motif (ARM) were screened for the ability to exclude λ coinfection, and mutants were assayed for Nun termination with a boxB plasmid reporter system. Several Nun ARM residues appear to be immutable: Asp26, Arg28, Arg29, Arg32, Trp33, and Arg36. Asp26 and Trp33 appear to be unable to contact boxB and are not found at equivalent positions in λ N ARM. To understand if the requirement of Asp26, Trp33, and Arg36 indicated differences between HK022 Nun termination and λ N antitermination complexes, the same Nun libraries were fused to the activation domain of λ N and screened for clones able to complement N-deficient λ. Mutants were assayed for N antitermination. Surprisingly, Asp26 and Trp33 were still essential when Nun ARM was fused to N. Docking suggests that Nun ARM contacts a hydrophobic surface of the NusG carboxy-terminal domain containing residues necessary for Nun function. These findings indicate that Nun ARM relies on distinct contacts in its ternary complex and illustrate how protein-RNA recognition can evolve new regulatory functions. IMPORTANCE: λ N protein interacts with host factors to allow λ nut-containing transcripts to elongate past termination signals. A competing bacteriophage, HK022, expresses Nun protein, which causes termination of λ nut transcripts. λ N and HK022 Nun use similar arginine-rich motifs (ARMs) to bind the same boxB RNAs in nut transcripts. Screening libraries of Nun ARM mutants, both in HK022 Nun and in a λ N fusion, revealed amino acids essential to Nun that could bind one or more host factors. Docking suggests that NusG, which is present in both Nun termination and N antitermination, is a plausible partner. These findings could help understand how transcription elongation is regulated and illustrate how subtle differences allow ARMs to evolve new regulatory functions.

A Web Resource for Standardized Benchmark Datasets, Metrics, and Rosetta Protocols for Macromolecular Modeling and Design.

The development and validation of computational macromolecular modeling and design methods depend on suitable benchmark datasets and informative metrics for comparing protocols. In addition, if a method is intended to be adopted broadly in diverse biological applications, there needs to be information on appropriate parameters for each protocol, as well as metrics describing the expected accuracy compared to experimental data. In certain disciplines, there exist established benchmarks and public resources where experts in a particular methodology are encouraged to supply their most efficient implementation of each particular benchmark. We aim to provide such a resource for protocols in macromolecular modeling and design. We present a freely accessible web resource (https://kortemmelab.ucsf.edu/benchmarks) to guide the development of protocols for protein modeling and design. The site provides benchmark datasets and metrics to compare the performance of a variety of modeling protocols using different computational sampling methods and energy functions, providing a "best practice" set of parameters for each method. Each benchmark has an associated downloadable benchmark capture archive containing the input files, analysis scripts, and tutorials for running the benchmark. The captures may be run with any suitable modeling method; we supply command lines for running the benchmarks using the Rosetta software suite. We have compiled initial benchmarks for the resource spanning three key areas: prediction of energetic effects of mutations, protein design, and protein structure prediction, each with associated state-of-the-art modeling protocols. With the help of the wider macromolecular modeling community, we hope to expand the variety of benchmarks included on the website and continue to evaluate new iterations of current methods as they become available.

Diverse mutants of HIV RRE IIB recognize wild-type Rev ARM or Rev ARM R35G-N40V.

The binding of human immunodeficiency virus Rev protein via its arginine-rich motif (ARM) to an internal loop in the Rev-response element region IIB (RRE IIB) is necessary for viral replication. Many variant RNAs and ARMs that bind Rev and RRE IIB have been found. Despite the essential role of Rev asparagine 40 in recognition, the Rev ARM double-mutant R35G-N40V functions well in a Rev-RRE IIB reporter assay, indicating R35G-N40V uses a distinct recognition strategy. To examine how RRE IIB may evolve specificity to wild-type Rev ARM and R35G-N40V, 10 RRE IIB libraries, each completely randomized in overlapping regions, were screened with wild-type Rev ARM and R35G-N40V using a reporter system based on bacteriophage λ N antitermination. Consistent with previous studies, a core element of RRE IIB did not vary, and substitutions occurred at conserved residues only in the presence of other substitutions. Notably, the groove-widening, non-canonical base-pair G48:G71 was mutable to U48:G71 without strong loss of binding to wild-type Rev ARM, suggesting U48:G71 performs the same role by adopting the nearly isosteric, reverse wobble base pair. Originating from RRE IIB, as few as one or two substitutions are sufficient to confer specificity to wild-type Rev or Rev R35G-N40. The diversity of RRE IIB mutants that maintain binding to wild-type Rev ARM and R35G-N40V supports neutral theories of evolution and illustrates paths by which viral RNA-protein interactions can evolve new specificities. Rev-RRE offers an excellent model with which to study the fine structure of how specificity evolves.

Population shuffling of protein conformations.

Motions play a vital role in the functions of many proteins. Discrete conformational transitions to excited states, happening on timescales of hundreds of microseconds, have been extensively characterized. On the other hand, the dynamics of the ground state are widely unexplored. Newly developed high-power relaxation dispersion experiments allow the detection of motions up to a one-digit microsecond timescale. These experiments showed that side chains in the hydrophobic core as well as at protein-protein interaction surfaces of both ubiquitin and the third immunoglobulin binding domain of protein G move on the microsecond timescale. Both proteins exhibit plasticity to this microsecond motion through redistribution of the populations of their side-chain rotamers, which interconvert on the picosecond to nanosecond timescale, making it likely that this "population shuffling" process is a general mechanism.

ORIUM: optimized RDC-based Iterative and Unified Model-free analysis.

Residual dipolar couplings (RDCs) are NMR parameters that provide both structural and dynamic information concerning inter-nuclear vectors, such as N-H(N) and Cα-Hα bonds within the protein backbone. Two approaches for extracting this information from RDCs are the model free analysis (MFA) (Meiler et al. in J Am Chem Soc 123:6098-6107, 2001; Peti et al. in J Am Chem Soc 124:5822-5833, 2002) and the direct interpretation of dipolar couplings (DIDCs) (Tolman in J Am Chem Soc 124:12020-12030, 2002). Both methods have been incorporated into iterative schemes, namely the self-consistent RDC based MFA (SCRM) (Lakomek et al. in J Biomol NMR 41:139-155, 2008) and iterative DIDC (Yao et al. in J Phys Chem B 112:6045-6056, 2008), with the goal of removing the influence of structural noise in the MFA and DIDC formulations. Here, we report a new iterative procedure entitled Optimized RDC-based Iterative and Unified Model-free analysis (ORIUM). ORIUM unifies theoretical concepts developed in the MFA, SCRM, and DIDC methods to construct a computationally less demanding approach to determine these structural and dynamic parameters. In all schemes, dynamic averaging reduces the actual magnitude of the alignment tensors complicating the determination of the absolute values for the generalized order parameters. To readdress this scaling issue that has been previously investigated (Lakomek et al. in J Biomol NMR 41:139-155, 2008; Salmon et al. in Angew Chem Int Edit 48:4154-4157, 2009), a new method is presented using only RDC data to establish a lower bound on protein motion, bypassing the requirement of Lipari-Szabo order parameters. ORIUM and the new scaling procedure are applied to the proteins ubiquitin and the third immunoglobulin domain of protein G (GB3). Our results indicate good agreement with the SCRM and iterative DIDC approaches and signify the general applicability of ORIUM and the proposed scaling for the extraction of inter-nuclear vector structural and dynamic content.

Randomized codon mutagenesis reveals that the HIV Rev arginine-rich motif is robust to substitutions and that double substitution of two critical residues alters specificity.

The binding of the arginine-rich motif (ARM) of HIV Rev protein to its high-affinity site in stem IIB in the Rev response element (RRE) initiates assembly of a ribonucleoprotein complex that mediates the export of essential, incompletely spliced viral transcripts. Many biochemical, genetic, and structural studies of Rev-RRE IIB have been published, yet the roles of many peptide residues in Rev ARM are unconfirmed by mutagenesis. Rev aptamer I (RAI) is an optimized RRE IIB that binds Rev with higher affinity and for which mutational data are sparse. Randomized-codon libraries of Rev ARM were assayed for their ability to bind RRE IIB and RAI using a bacterial reporter system based on bacteriophage λ N-nut antitermination. Most Rev ARM residues tolerated substitutions without strong loss of binding to RRE IIB, and all except arginine 39 tolerated substitution without strong loss of binding to RAI. The pattern of critical Rev residues is not the same for RRE IIB and RAI, suggesting important differences between the interactions. The results support and aid the interpretation of existing structural models. Observed clinical variation is consistent with additional constraints on Rev mutation. By chance, we found double mutants of two highly critical residues, arginine 35 (to glycine) and asparagine 40 (to valine or lysine), that bind RRE IIB well, but not RAI. That an apparently distinct binding mode occurs with only two mutations highlights the ability of ARMs to evolve new recognition strategies and supports the application of neutral theories of evolution to protein-RNA recognition.

Flexible backbone sampling methods to model and design protein alternative conformations.

Sampling alternative conformations is key to understanding how proteins work and engineering them for new functions. However, accurately characterizing and modeling protein conformational ensembles remain experimentally and computationally challenging. These challenges must be met before protein conformational heterogeneity can be exploited in protein engineering and design. Here, as a stepping stone, we describe methods to detect alternative conformations in proteins and strategies to model these near-native conformational changes based on backrub-type Monte Carlo moves in Rosetta. We illustrate how Rosetta simulations that apply backrub moves improve modeling of point mutant side-chain conformations, native side-chain conformational heterogeneity, functional conformational changes, tolerated sequence space, protein interaction specificity, and amino acid covariation across protein-protein interfaces. We include relevant Rosetta command lines and RosettaScripts to encourage the application of these types of simulations to other systems. Our work highlights that critical scoring and sampling improvements will be necessary to approximate conformational landscapes. Challenges for the future development of these methods include modeling conformational changes that propagate away from designed mutation sites and modulating backbone flexibility to predictively design functionally important conformational heterogeneity.