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The uneven worldwide vaccination coverage against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and emergence of variants escaping immunity call for broadly effective and easily deployable therapeutic agents. We have previously described the human single-chain scFv76 antibody, which recognizes SARS-CoV-2 Alpha, Beta, Gamma and Delta variants. We now show that scFv76 also neutralizes the infectivity and fusogenic activity of the Omicron BA.1 and BA.2 variants. Cryoelectron microscopy (cryo-EM) analysis reveals that scFv76 binds to a well-conserved SARS-CoV-2 spike epitope, providing the structural basis for its broad-spectrum activity. We demonstrate that nebulized scFv76 has therapeutic efficacy in a severe hACE2 transgenic mouse model of coronavirus disease 2019 (COVID-19) pneumonia, as shown by body weight and pulmonary viral load data. Counteraction of infection correlates with inhibition of lung inflammation, as observed by histopathology and expression of inflammatory cytokines and chemokines. Biomarkers of pulmonary endothelial damage were also significantly reduced in scFv76-treated mice. The results support use of nebulized scFv76 for COVID-19 induced by any SARS-CoV-2 variants that have emerged so far.

Protein aggregation into amyloid fibrils is the archetype of aberrant biomolecular self-assembly processes, with more than 50 associated diseases that are mostly uncurable. Understanding aggregation mechanisms is thus of fundamental importance and goes in parallel with the structural characterization of the transient oligomers formed during the process. Oligomers have been proven elusive to high-resolution structural techniques, while the large sizes and long time scales, typical of aggregation processes, have limited the use of computational methods to date. To surmount these limitations, we here present multi- e GO, an atomistic, hybrid structure-based model which, leveraging the knowledge of monomers conformational dynamics and of fibril structures, efficiently captures the essential structural and kinetics aspects of protein aggregation. Multi- e GO molecular dynamics simulations can describe the aggregation kinetics of thousands of monomers. The concentration dependence of the simulated kinetics, as well as the structural features of the resulting fibrils, are in qualitative agreement with in vitro experiments carried out on an amyloidogenic peptide from Transthyretin, a protein responsible for one of the most common cardiac amyloidoses. Multi- e GO simulations allow the formation of primary nuclei in a sea of transient lower-order oligomers to be observed over time and at atomic resolution, following their growth and the subsequent secondary nucleation events, until the maturation of multiple fibrils is achieved. Multi- e GO, combined with the many experimental techniques deployed to study protein aggregation, can provide the structural basis needed to advance the design of molecules targeting amyloidogenic diseases.

Recognition motifs that mediate protein-protein interactions are usually embedded within longer intrinsically disordered regions. While binding interfaces involving the recognition motif in such interactions are well studied, less is known about the role of disordered regions flanking the motifs. The interaction between the transcriptional co-activators NCOA3 (ACTR) and CBP is mediated by coupled binding and folding of the two domains CID and NCBD. Here, we used circular dichroism and kinetics to directly quantify the contribution of the adjacent flanking regions of CID to its interaction with NCBD. Using N-and C terminal combinatorial variants we found that the flanking regions promote binding in an additive fashion while retaining a large degree of disorder in the complex. Experiments at different ionic strengths demonstrated that the increase in affinity is not mediated by electrostatic interactions from the flanking regions. Instead, site-directed mutagenesis and molecular dynamics simulations suggest that binding is promoted by short-lived non-specific hydrophobic contacts between the flanking regions and NCBD. Our findings are consistent with highly frustrated interactions outside of the canonical binding interface resulting in a slightly energetically favorable fuzzy binding. Modulation of affinity via flanking regions could represent a general mechanism for functional regulation by intrinsically disordered protein regions.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Protein aggregation into amyloid fibrils is the archetype of aberrant biomolecular self-assembly processes, with more than 50 diseases associated that are mostly uncurable. Understanding aggregation mechanisms is thus of fundamental importance and goes in parallel with the characterization of the structures of the transient oligomers formed in the process. Oligomers have been proven elusive to high-resolution structural techniques, while the large sizes and long-time scales typical of aggregation processes have limited, so far, the use of computational methods. To surmount these limitations, we introduce here multi-eGO, an atomistic, hybrid structure-based model, which leveraging on the knowledge of monomers conformational dynamics and of fibril structures, can efficiently capture the essential structural and kinetics aspects of protein aggregation. Multi-eGO molecular dynamics simulations can describe the aggregation kinetics of thousands of monomers. The concentration dependence of the simulated kinetics, as well as the structural features of the resulting fibrils, are in qualitative agreement with in vitro experiments on an amyloidogenic peptide of Transthyretin, a protein responsible for one of the most common cardiac amyloidosis. Multi-eGO simulations allow to observe in time and at atomic resolution the formation of primary nuclei in a sea of transient lower order oligomers, to follow their growth and the subsequent secondary nucleation events, till the maturation of multiple fibrils. Multi-eGO, combined with the many experimental techniques deployed to study protein aggregation, can provide the structural basis needed to advance the design of molecules targeting amyloidogenic diseases.Significance StatementAlzheimer’s and Parkinson’s diseases are uncurable pathologies associated to the aberrant aggregation of specific proteins into amyloid fibrils. Understanding the mechanism leading to protein aggregation, by characterizing the structures of the oligomeric species populated in the process, would have a tremendous impact on the design of therapeutic molecules. We propose that a structure-based approach to molecular dynamics simulations can allow following at high resolution the aggregation kinetics of thousands of monomers. Having shown that simulations can describe the aggregation of a Transthyretin amyloidogenic peptide, we demonstrate how their efficiency allows acquiring a wealth of structural information. We foresee that integrating the latter with the many techniques developed to study protein aggregation will support the design of molecules to modulate amyloidogenesis.

Presentation of pathogen-derived epitopes by major histocompatibility complex I (MHC-I) can lead to the activation and expansion of specific CD8

The use of small-angle X-ray scattering (SAXS) in combination with molecular dynamics simulation is hampered by its heavy computational cost. The calculation of SAXS from atomic structures can be speeded up by using a coarse-grain representation of the structure. Following the work of Niebling, Björling & Westenhoff [J. Appl. Cryst. (2014), 47, 1190–1198], the Martini bead form factors for nucleic acids have been derived and then implemented, together with those previously determined for proteins, in the publicly available PLUMED library. A hybrid multi-resolution strategy has also been implemented to perform SAXS restrained simulations at atomic resolution by calculating the virtual positions of the Martini beads on the fly and using them for the calculation of SAXS. The accuracy and efficiency of the method are demonstrated by refining the structure of two protein–nucleic acid complexes. Instrumental for this result is the use of metainference, which allows the consideration and alleviation of the approximations at play in the present SAXS calculations.

Systemic light chain amyloidosis (AL) is a life-threatening disease caused by aggregation and deposition of monoclonal immunoglobulin light chains (LC) in target organs. Severity of heart involvement is the most important factor determining prognosis. Here, we report the 4.0 Å resolution cryo-electron microscopy map and molecular model of amyloid fibrils extracted from the heart of an AL amyloidosis patient with severe amyloid cardiomyopathy. The helical fibrils are composed of a single protofilament, showing typical 4.9 Å stacking and cross-β architecture. Two distinct polypeptide stretches (total of 77 residues) from the LC variable domain (Vl) fit the fibril density. Despite Vl high sequence variability, residues stabilizing the fibril core are conserved through different cardiotoxic Vl, highlighting structural motifs that may be common to misfolding-prone LCs. Our data shed light on the architecture of LC amyloids, correlate amino acid sequences with fibril assembly, providing the grounds for development of innovative medicines., Immunoglobulin Light Chain Amyloidosis (AL) is the most common systemic amyloidosis occurring in Western countries. Here the authors present the 4.0 Å cryo-EM structure of light chain AL55 fibrils that were isolated from the heart of an AL systemic amyloidosis patient.

MJ0366 from Methanocaldococcus jannaschii is the smallest topologically knotted protein known to date. 92 residues in length, MJ0366 ties a trefoil (3(1)) knot by threading its C-terminal helix through a buttonhole formed by the remainder of the secondary structure elements. By generating a library of point mutations at positions pertinent to the knot formation, we systematically evaluated the contributions of individual residues to the folding stability and kinetics of MJ0366. The experimental Φ-values were used as restraints to computationally generate an ensemble of conformations that correspond to the transition state of MJ0366, which revealed several nonnative contacts. The importance of these nonnative contacts in stabilizing the transition state of MJ0366 was confirmed by a second round of mutagenesis, which also established the pivotal role of F15 in stapling the network of hydrophobic interactions around the threading C-terminal helix. Our converging experimental and computational results show that, despite the small size, the transition state of MJ0366 is formed at a very late stage of the folding reaction coordinate, following a polarized pathway. Eventually, the formation of extensive native contacts, as well as a number of nonnative ones, leads to the threading of the C-terminal helix that defines the topological knot.

The PLUMED consortium unifies developers and contributors to PLUMED, an open-source library for enhanced-sampling, free-energy calculations and the analysis of molecular dynamics simulations. Here, we outline our efforts to promote transparency and reproducibility by disseminating protocols for enhanced-sampling molecular simulations.

Intrinsically disordered protein domains often have multiple binding partners. It is plausible that the strength of pairing with specific partners evolves from an initial low affinity to a higher affinity. However, little is known about the molecular changes in the binding mechanism that would facilitate such a transition. We previously showed that the interaction between two intrinsically disordered domains, NCBD and CID, likely emerged in an ancestral deuterostome organism as a low-affinity interaction that subsequently evolved into a higher-affinity interaction before the radiation of modern vertebrate groups. Here we map native contacts in the transition states of the low-affinity ancestral and high-affinity human NCBD/CID interactions. We show that the coupled binding and folding mechanism is overall similar but with a higher degree of native hydrophobic contact formation in the transition state of the ancestral complex and more heterogeneous transient interactions, including electrostatic pairings, and an increased disorder for the human complex. Adaptation to new binding partners may be facilitated by this ability to exploit multiple alternative transient interactions while retaining the overall binding and folding pathway.

Intrinsically disordered protein (IDP) domains often have multiple binding partners. Little is known regarding molecular changes in the binding mechanism when a new interaction evolves from low to high affinity. Here we compared the degree of native contacts in the transition state of the interaction of two IDP domains, low-affinity ancestral and high-affinity human NCBD and CID. We found that the coupled binding and folding mechanism of the domains is overall similar, but with a higher degree of native hydrophobic contact formation in the transition state of the ancestral complex while more heterogenous transient interactions, including electrostatic, and an increased disorder characterize the human complex. From an evolutionary perspective, adaptation to new binding partners for IDPs may benefit from this ability to exploit multiple alternative transient interactions while retaining the overall pathway.

SAXS experiments provide low-resolution but valuable information about the dynamics of biomolecular systems, which could be ideally integrated into MD simulations to accurately determine conformational ensembles of flexible proteins. The applicability of this strategy is hampered by the high computational cost required to calculate scattering intensities from three-dimensional structures. We previously presented a hybrid resolution method that makes atomistic SAXS-restrained MD simulation feasible by adopting a coarse-grained approach to efficiently back-calculate scattering intensities; here, we extend this technique, applying it in the framework of metainference with the aim to investigate the dynamical behavior of flexible biomolecules. The efficacy of the method is assessed on the K63-diubiquitin, showing that the inclusion of SAXS-restraints is effective in generating a reliable conformational ensemble, improving the agreement with independent experimental data.

The isoDGR sequence is an integrin-binding motif that has been successfully employed as a tumor-vasculature-homing molecule or for the targeted delivery of drugs and diagnostic agents to tumors. In this context, we previously demonstrated that cyclopeptide 2, the product of the conjugation of c(CGisoDGRG) (1) to 4-( N-maleimidomethyl)cyclohexane-1-carboxamide, can be successfully used as a tumor-homing ligand for nanodrug delivery to neoplastic tissues. Here, combining NMR, computational, and biochemical methods, we show that the succinimide ring contained in 2 contributes to stabilizing interactions with ?v?3, an integrin overexpressed in the tumor vasculature. Furthermore, we demonstrate that various cyclopeptides containing the isoDGR sequence embedded in different molecular scaffolds do not induce ?v?3 allosteric activation and work as pure integrin antagonists. These results could be profitably exploited for the rational design of novel isoDGR-based ligands and tumor-targeting molecules with improved ?v?3-binding properties and devoid of adverse integrin-activating effects.

The isoDGR sequence is an integrin-binding motif that has been successfully employed as a tumor-vasculature-homing molecule or for the targeted delivery of drugs and diagnostic agents to tumors. In this context, we previously demonstrated that cyclopeptide 2, the product of the conjugation of c(CGisoDGRG) (1) to 4-( N-maleimidomethyl)cyclohexane-1-carboxamide, can be successfully used as a tumor-homing ligand for nanodrug delivery to neoplastic tissues. Here, combining NMR, computational, and biochemical methods, we show that the succinimide ring contained in 2 contributes to stabilizing interactions with α

Hybrid cyclic α/β-peptides, in which one or more β-amino acids are incorporated into the backbone, are gaining increasing interest as potential therapeutics, thanks to their ability to achieve enhanced binding affinities for a biological target through pre-organization in solution. The in silico prediction of their three dimensional structure through strategies such as MD simulations would substantially advance the rational design process. However, whether the molecular mechanics force fields are accurate in sampling highly constrained cyclopeptides containing β-amino acids remains to be verified. Here, we present a systematic assessment of the ability of 8 widely used force fields to reproduce 79 NMR observables (including chemical shifts and 3J scalar couplings) on five cyclic α/β-peptides that contain the integrin recognition motif isoDGR. Most of the investigated force fields, which include force fields from AMBER, OPLS, CHARMM and GROMOS families, display very good agreement with experimental 3J(HN,Hα), suggesting that MD simulations could be an appropriate tool in the rational design of therapeutic cyclic α-peptides. However, for NMR observables directly related to β-amino acids, we observed a poor agreement with experiments and a remarkable dependence of our evaluation on the choice of Karplus parameters. The force field weaknesses herein unveiled might constitute a source of inspiration for further force field optimization.

We combined metadynamics, docking and molecular mechanics/generalised born surface area (MM/GBSA) re-scoring methods to investigate the impact of single and multiple N-methylation on a set of RGD cyclopeptides displaying different affinity for integrin αIIbβ3. We rationalised the conformational effects induced by N-methylation and its interplay with receptor affinity, obtaining good agreement with experimental data. This approach can be exploited before entering time-consuming and expensive synthesis and binding experiments.

GMXPBSA 2.0 is a user-friendly suite of Bash/Perl scripts for streamlining MM/PBSA calculations on structural ensembles derived from GROMACS trajectories, to automatically calculate binding free energies for protein–protein or ligand–protein complexes. GMXPBSA 2.0 is flexible and can easily be customized to specific needs. Additionally, it performs computational alanine scanning (CAS) to study the effects of ligand and/or receptor alanine mutations on the free energy of binding. Calculations require only for protein–protein or protein–ligand MD simulations. GMXPBSA 2.0 performs different comparative analysis, including a posteriori generation of alanine mutants of the wild-type complex, calculation of the binding free energy values of the mutant complexes and comparison of the results with the wild-type system. Moreover, it compares the binding free energy of different complexes trajectories, allowing the study the effects of non-alanine mutations, post-translational modifications or unnatural amino acids on the binding free energy of the system under investigation. Finally, it can calculate and rank relative affinity to the same receptor utilizing MD simulations of proteins in complex with different ligands. In order to dissect the different MM/PBSA energy contributions, including molecular mechanic (MM), electrostatic contribution to solvation (PB) and nonpolar contribution to solvation (SA), the tool combines two freely available programs: the MD simulations software GROMACS and the Poisson–Boltzmann equation solver APBS. All the calculations can be performed in single or distributed automatic fashion on a cluster facility in order to increase the calculation by dividing frames across the available processors. The program is freely available under the GPL license. Program summary Program title: GMXPBSA 2.0 Catalogue identifier: AETQ_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AETQ_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 185 937 No. of bytes in distributed program, including test data, etc.: 7 074 217 Distribution format: tar.gz Programming language: Bash, Perl. Computer: Any computer. Operating system: Linux, Unix OS. RAM: ∼2 GB Classification: 3. External routines: APBS ( http://www.Poissonboltzmann.org/apbs/ ) and GROMACS installations ( http://www.gromacs.org ). Optionally LaTeX. Nature of problem: Calculates the Molecular Mechanics (MM) data (Lennard-Jones and Coulomb terms) and the solvation energy terms (polar and nonpolar terms respectively) from an ensemble of structures derived from GROMACS molecular dynamics simulation trajectory. These calculations are performed for each single component of the simulated complex, including protein and ligand. In order to cancel out artefacts an identical grid setup for each component, including complex, protein and ligand, is required. Performs statistical analysis on the extracted data and comparison with wild-type complex in case of either computational alanine scanning or calculations on a set of simulations. Evaluates possible outliers in the frames extracted from the simulations during the binding free energy calculations. Solution method: The tool combines the freely available programs GROMACS and APBS to: 1. extract frames from a single or multiple complex molecular dynamics (MD) simulation, allowing comparison between multiple trajectories; 2. split the complex frames in the single components including complex, protein and ligand; 3. calculate the Lennard-Jones and Coulomb energy values (MM terms); 4. calculate the polar solvation energy values using the implicit solvation Poisson–Boltzmann model (PB); 5. calculate the nonpolar solvation energy value based on the solvent accessible surface area (SASA); 6. combine all the calculated terms into the final binding free energy value; 7. repeat the same procedure from point 1 to 6 for each simulation in case of computational alanine scanning (CAS) or simultaneous comparison of different MDs. Restrictions: Input format files compatible with GROMACS engine 4.5 and later versions. Availability of the force field or of the topology files. Running time: On a single core, Lennard-Jones, Coulomb and nonpolar solvation terms calculations require a few minutes. The time required for polar solvation terms calculations depends on the system size.

GMXPBSA 2.1 is a user-friendly suite of Bash/Perl scripts for streamlining MM/PBSA calculations on structural ensembles derived from GROMACS trajectories, to automatically calculate binding free energies for protein–protein or ligand–protein complexes [R.T. Bradshaw et al., Protein Eng. Des. Sel. 24 (2011) 197–207]. GMXPBSA 2.1 is flexible and can easily be customized to specific needs and it is an improvement of the previous GMXPBSA 2.0 [C. Paissoni et al., Comput. Phys. Commun. (2014), 185, 2920–2929]. Additionally, it performs computational alanine scanning (CAS) to study the effects of ligand and/or receptor alanine mutations on the free energy of binding. Calculations require only for protein–protein or protein–ligand MD simulations. GMXPBSA 2.1 performs different comparative analyses, including a posteriori generation of alanine mutants of the wild-type complex, calculation of the binding free energy values of the mutant complexes and comparison of the results with the wild-type system. Moreover, it compares the binding free energy of different complex trajectories, allowing the study of the effects of non-alanine mutations, post-translational modifications or unnatural amino acids on the binding free energy of the system under investigation. Finally, it can calculate and rank relative affinity to the same receptor utilizing MD simulations of proteins in complex with different ligands. In order to dissect the different MM/PBSA energy contributions, including molecular mechanic (MM), electrostatic contribution to solvation (PB) and nonpolar contribution to solvation (SA), the tool combines two freely available programs: the MD simulations software GROMACS [S. Pronk et al., Bioinformatics 29 (2013) 845–854] and the Poisson–Boltzmann equation solver APBS [N.A. Baker et al., Proc. Natl. Acad. Sci. U.S.A 98 (2001) 10037–10041]. All the calculations can be performed in single or distributed automatic fashion on a cluster facility in order to increase the calculation by dividing frames across the available processors. This new version with respect to our previously published GMXPBSA 2.0 fixes some problem and allows additional kind of calculations, such as CAS on single protein in order to individuate the hot-spots, more custom options to perform APBS calculations, improvements of speed calculation of APBS (precF set to 0), possibility to work with multichain systems (see Summary of revisions for more details). The program is freely available under the GPL license. New version program summary Program title: GMXPBSA 2.1 Catalogue identifier: AETQ_v1_1 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AETQ_v1_1.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 188453 No. of bytes in distributed program, including test data, etc.: 5381839 Distribution format: tar.gz Programming language: Bash, Perl. Computer: Any computer. Operating system: Linux, Unix OS. RAM: 2147483648 bytes Supplementary material: A table of added keywords is available. Classification: 3. Catalogue identifier of previous version: AETQ_v1_0 Journal reference of previous version: Comput. Phys. Comm. 185 (2014) 3016 External routines: Any APBS version (http://www.poissonboltzmann.org/apbs/) and GROMACS version 4.5 or later installations (http://www.gromacs.org). Optionally LaTeX. Does the new version supersede the previous version?: Yes Nature of problem: The Molecular Mechanics (MM) data (Lennard-Jones and Coulomb terms) and the solvation energy terms (polar and nonpolar terms respectively) from an ensemble of structures derived from GROMACS molecular dynamics simulation trajectory are calculated. These calculations are performed for each single component of the simulated complex, including protein and ligand. In order to cancel out artifacts an identical grid setup for each component, including complex, protein and ligand, is required. Statistical analysis on the extracted data and comparison with wild-type complex in the case of either computational alanine scanning or calculations on a set of simulations is performed. Possible outliers in the frames extracted from the simulations during the binding free energy calculations are evaluated. Solution method: The tool combines the freely available programs GROMACS and APBS to: 1. extract frames from a single or multiple complex molecular dynamics (MD) simulation, allowing comparison between multiple trajectories; 2. split the complex frames into the single components including complex, protein and ligand; 3. calculate the Lennard-Jones and Coulomb energy values (MM terms); 4. calculate the polar solvation energy values using the implicit solvation Poisson–Boltzmann model (PB); 5. calculate the nonpolar solvation energy value based on the solvent accessible surface area (SASA); 6. combine all the calculated terms into the final binding-free energy value; 7. repeat the same procedure from point 1 to 6 for each simulation in the case of computational alanine scanning (CAS) or simultaneous comparison of different Mds. Reasons for new version: We had a lot of feedback from our previous GMXPBSA 2.0 publication suggesting improvements. There were also some bugs that required to be fixed urgently in order to keep the program working properly. Summary of revisions: In the update version of GMXPBSA 2.1 we include the following changes: 1. Fixed bug related to the use of amino acids with id>1000. 2. Fixed bug related to the computing of the percentage of failed APBS-jobs. 3. Added the string ‘export LC_NUMERIC = “en_us.UTF-8”’ in each of the three gmxpbsa*.sh scripts to avoid errors related to locale environment variables. 4. Fixed a bug related to the CAS mutation in the cases in which: 1. - no chains information is available from xtc/tpr 2. - the ligand is positioned before the receptor in the pdb 5. Added final message with proper references. 6. Added the possibility of checking the GMXPBSA version with the command “sh gmxpbsa[0,1,2].sh -h”. 7. Included the possibility to use “multichain”. (Added keyword “multichain”, set by default to “n”). Useful if in the pdbs extracted from the trajectory there is more than one chain. The option “multichain” must be used ONLY if the string TER is not present at the end of each chain in the comp/receptor pdb files. 8. Added the possibility of performing ΔGΔG CAS calculations on a single protein. Added keyword “protein_alone”, set by default to “n”, and keyword “itp_protein” that must be set only in the case of “use_topology = y”. When using the option “protein_alone” in the xtc file provided to GMXPBSA the periodic boundary condition must be treated so as to make the broken molecules whole (i.e. trjconv -pbc whole). 9. Modified default values for keywords: coulomb from “coul” to “gmx”, precF from “1” to “0”, linearized from “n” to “y”. 10. Added the possibility of using custom name of trajectories and binary file, xtc and tpr respectively format. Many keywords have been added to allow more flexibility with the APBS options in the input file and to set the option for the cluster. See Table 1 of supplementary material for a list of all the added keywords. Restrictions: Input format files compatible with GROMACS engine 4.5 and later versions. Availability of the force field or of the topology files. Running time: On a single core Lennard-Jones, Coulomb and nonpolar solvation term calculations require a few minutes. The time required for polar solvation term calculations depends on the system size.

Simplified models, including implicit-solvent and coarse-grained models, are useful tools to investigate the physical properties of biological macromolecules of large size, like protein complexes, large DNA/RNA strands and chromatin fibres. While advanced Monte Carlo techniques are quite efficient in sampling the conformational space of such models, the availability of realistic potentials is still a limitation to their general applicability. The recent development of a computational scheme capable of designing potentials to reproduce any kind of experimental data that can be expressed as thermal averages of conformational properties of the system has partially alleviated the problem. Here we present a program that implements the optimization of the potential with respect to the experimental data through an iterative Monte Carlo algorithm and a rescaling of the probability of the sampled conformations. The Monte Carlo sampling includes several types of moves, suitable for different kinds of system, and various sampling schemes, such as fixed-temperature, replica-exchange and adaptive simulated tempering. The conformational properties whose thermal averages are used as inputs currently include contact functions, distances and functions of distances, but can be easily extended to any function of the coordinates of the system. Program summary Program title: MonteGrappa Catalogue identifier: AEUO_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEUO_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 139,987 No. of bytes in distributed program, including test data, etc.: 1,889,541 Distribution format: tar.gz Programming language: C. Computer: Any computer with C compilers. Operating system: Linux, Unix, OSX. RAM: Bytes depend on the size of the system, typically 4 GB Classification: 3, 16.1. External routines: gsl, MPI (optional) Nature of problem: Optimize an interaction potential for coarse-grained models of biopolymers based on experimental data expressed as averages of conformational properties. Solution method: Iterative Monte Carlo sampling coupled with minimization of the chi2 between experimental and back-calculated data making use of a reweighting algorithm. Running time: Hours to days, depending on the complexity of the problem.

The current capacity of computers makes it possible to perform simulations of small systems with portable, explicit-solvent potentials achieving high degree of accuracy. However, simplified models must be employed to exploit the behaviour of large systems or to perform systematic scans of smaller systems. While powerful algorithms are available to facilitate the sampling of the conformational space, successful applications of such models are hindered by the availability of simple enough potentials able to satisfactorily reproduce known properties of the system. We develop an interatomic potential to account for a number of properties of proteins in a computationally economic way. The potential is defined within an all-atom, implicit solvent model by contact functions between the different atom types. The associated numerical values can be optimised by an iterative Monte Carlo scheme on any available experimental data, provided that they are expressible as thermal averages of some conformational properties. We test this model on three different proteins, for which we also perform a scan of all possible point mutations with explicit conformational sampling. The resulting models, optimised solely on a subset of native distances, not only reproduce the native conformations within a few Angstroms from the experimental ones, but show the cooperative transition between native and denatured state and correctly predict the measured free--energy changes associated with point mutations. Moreover, differently from other structure-based models, our method leaves a residual degree of frustration, which is known to be present in protein molecules.