Molecular Parameterisation and the Theoretical Calculation of Electrode Potentials

The difference in reduction potentials between ortho and para-benzoquinones has been calculated. The employs gas phase ab initio and semi-empirical computations in combination with free energy perturbation theory applied to gas and solution phase Monte Carlo simulations. The effects on calculated results of altering solute electrostatic parameterisation in solution phase simulations is examined. Atom centred charges derived from the molecular electrostatic potentials, MEPs, from optimised ab initio wavefunctions and charges generated by consideration of hydrogen bonded complexes are considered. Parameterisation of hydroxyl torsions in hydroquinone molecules is treated in a physically realistic manner. The coupled torsional system of the ortho-hydrobenzoquinone molecule is described by a potential energy surface calculated using gas phase AM1 semi-empirical computations rather than the simple torsional energy functions frequently employed in such calculations. Calculated differences in electrode potentials show that the electrostatic interactions of quinone and hydroquinone molecules in aqueous solution are not well described by atom centred charges derived from ab initio calculated MEPs. Moreover, results in good agreement with the experimental reduction potential difference can be obtained by employing high level ab initio calculations and solution phase electrostatic parameters developed by consideration of hydrogen bonded complexes.     

Molecular Dynamics of the Ha-ras Protein: Nucleotide Atom-Centred Charges within the AMBER Force Field

Molecular dynamics simulations have become an essential tool for the study of biological systems. The Ha-ras protein, is a system suitable for such studies. Despite much recent progress, it is still not known exactly how the protein functions in the cell growth cycle. In this work atom-centred point charges for the guanosine nucleotide ligands are calculated and tested. To be compatible with the other AMBER force field parameters these are fitted to a molecular electrostatic potential derived from an ab initio wavefunction. The smallest basis set able to produce a stable wavefunction for the negatively charged GDP and GTP molecule ions was 3-21G* with diffuse functions added on the phosphate groups. To maintain force field integrity these charges were scaled to be equivalent to STO-3G derived values. This procedure is seen to produce a good magnesium-phosphate interaction potential when compared to 6-31++G* ab initio calculations. With the nucleotides fixed in the binding site conformation, it was found essential to include the electrostatics of the binding site in the calculation of the charges. It was also found to be inappropriate to divide the nucleotide into constituent parts for the calculations. From the calculated charges and experimental data, the nucleotide protonation states in the protein are deduced. It is unlikely that GDP is protonated, GTP probably binds one proton. The charges were tested in MD simulations of a protein modelled on the crystal structure of Tong et al., during which the dynamics of the nucleotide and binding site residues were in good agreement with the crystal structure data. The model is seen to be sensitive, not only to the inclusion of explicit solvent, but to the number of waters ligating the magnesium ion and the conformation of the loop between residues 60 and 66; both pieces of information are lacking in the crystal structure data.     

A force field for naproxen

A united-atom potential model for naproxen suitable for molecular dynamics (MD) simulation has been developed. The charge distribution is approximated by point charges obtained from ab initio calculations using the CHELPG method. Also the intramolecular interactions such as bond and angle vibration, and the torsion potential are obtained from ab initio calculations. The dispersive interaction contribution is taken from the literature. By MD simulation using a naproxen film in slap geometry, the temperature dependence of the density, surface tension and self-diffusion coefficient as well as the melting temperature for the developed potential model are obtained.     

AUGUSTUS at EGASP: using EST,protein and genomic alignments for improved gene prediction in the human genome

Background

A large number of gene prediction programs for the human genome exist. These annotation tools use a variety of methods and data sources. In the recent ENCODE genome annotation assessment project (EGASP), some of the most commonly used and recently developed gene-prediction programs were systematically evaluated and compared on test data from the human genome. AUGUSTUS was among the tools that were tested in this project.

Results

AUGUSTUS can be used as an ab initio program, that is, as a program that uses only one single genomic sequence as input information. In addition, it is able to combine information from the genomic sequence under study with external hints from various sources of information. For EGASP, we used genomic sequence alignments as well as alignments to expressed sequence tags (ESTs) and protein sequences as additional sources of information. Within the category of ab initio programs AUGUSTUS predicted significantly more genes correctly than any other ab initio program. At the same time it predicted the smallest number of false positive genes and the smallest number of false positive exons among all ab initio programs. The accuracy of AUGUSTUS could be further improved when additional extrinsic data, such as alignments to EST, protein and/or genomic sequences, was taken into account.

Conclusion

AUGUSTUS turned out to be the most accurate ab initio gene finder among the tested tools. Moreover it is very flexible because it can take information from several sources simultaneously into consideration.

     

New Multicentre Point Charge Models for Molecular Electrostatic Potentials from Semiempirical M0-Calculations

Two quasi-multipole electrostatic models for molecular charge distributions are presented. They assign arrays of point charges to nonhydrogen atoms on the basis of hybrid orbitals or localised molecular orbitals. When used with common semiempirical MO-techniques, they reproduce natural atomic orbital derived point charge (NAO-PC) and ab initio molecular potentials well. The localised orbital technique (LMO-PC) is intuitively more attractive than the hybrid orbital-point charge (HO-PC) method, although the former is more CPU-intensive.Electronic Supplementary Material available.     

A computational analysis of some diaryl ureas in relation to their observed crystalline hydrogen bonding patterns

We have carried out anab initio self-consistent-field molecular orbital analysis of the structures, atomic charges and electrostatic potentials of 1,3-bisphenylurea, 1,3-bis(m-nitrophenyl)urea and 1,3-bis(p-nitrophenyl)urea. Our results provide insight into the contrasting hydrogen bond patterns and preferences of these molecules in crystalline environments. The tendency for 1,3-bisphenylurea to form homomeric rather than heteromeric (i.e. host-guest) crystals is attributed to a relatively strong and extended homomeric attractive electrostatic interaction between two like molecules. Our calculated internuclear distances and atomic charges indicate that these molecules have some degree of H...O intramolecular hydrogen bonding between the carbonyl oxygen and the nearest aromatic hydrogens when the aromatic and the urea portions of the molecules are coplanar. This interaction is strongest for the meta nitro derivative, consistent with the latter remaining very nearly planar in its cocrystal structures. Our surface electrostatic potentials for the three diaryl ureas are used to interpret their differing crystallization properties and tendencies to form cocrystals with guest molecules.     

A unified computational view of DNA duplex,triplex, quadruplex and their donor–acceptor interactions

DNA can assume various structures as a result of interactions at atomic and molecular levels (e.g., hydrogen bonds, π–π stacking interactions, and electrostatic potentials), so understanding of the consequences of these interactions could guide development of ways to produce elaborate programmable DNA for applications in bio- and nanotechnology. We conducted advanced ab initio calculations to investigate nucleobase model structures by componentizing their donor-acceptor interactions. By unifying computational conditions, we compared the independent interactions of DNA duplexes, triplexes, and quadruplexes, which led us to evaluate a stability trend among Watson–Crick and Hoogsteen base pairing, stacking, and even ion binding. For a realistic solution-like environment, the influence of water molecules was carefully considered, and the potassium-ion preference of G-quadruplex was first analyzed at an ab initio level by considering both base-base and ion-water interactions. We devised new structure factors including hydrogen bond length, glycosidic vector angle, and twist angle, which were highly effective for comparison between computationally-predicted and experimentally-determined structures; we clarified the function of phosphate backbone during nucleobase ordering. The simulated tendency of net interaction energies agreed well with that of real world, and this agreement validates the potential of ab initio study to guide programming of complicated DNA constructs.     

PSPP: A Protein Structure Prediction Pipeline for Computing Clusters

Background

Protein structures are critical for understanding the mechanisms of biological systems and, subsequently, for drug and vaccine design. Unfortunately, protein sequence data exceed structural data by a factor of more than 200 to 1. This gap can be partially filled by using computational protein structure prediction. While structure prediction Web servers are a notable option, they often restrict the number of sequence queries and/or provide a limited set of prediction methodologies. Therefore, we present a standalone protein structure prediction software package suitable for high-throughput structural genomic applications that performs all three classes of prediction methodologies: comparative modeling, fold recognition, and ab initio. This software can be deployed on a user''s own high-performance computing cluster.

Methodology/Principal Findings

The pipeline consists of a Perl core that integrates more than 20 individual software packages and databases, most of which are freely available from other research laboratories. The query protein sequences are first divided into domains either by domain boundary recognition or Bayesian statistics. The structures of the individual domains are then predicted using template-based modeling or ab initio modeling. The predicted models are scored with a statistical potential and an all-atom force field. The top-scoring ab initio models are annotated by structural comparison against the Structural Classification of Proteins (SCOP) fold database. Furthermore, secondary structure, solvent accessibility, transmembrane helices, and structural disorder are predicted. The results are generated in text, tab-delimited, and hypertext markup language (HTML) formats. So far, the pipeline has been used to study viral and bacterial proteomes.

Conclusions

The standalone pipeline that we introduce here, unlike protein structure prediction Web servers, allows users to devote their own computing assets to process a potentially unlimited number of queries as well as perform resource-intensive ab initio structure prediction.     

Ab initio refinement of an orbital-centred force field for biomolecules: Orbital localisation and parameterisation of the COP(O2)OC fragment of nucleotides

Classical calculations of conformational potential surfaces, based on simple analytical functions of the interactions between atomic centres, continue to be of considerable importance. However, it has become apparent that not all interactions of importance can be included as interactions between positions which are effectively those of the nuclei. Thus, there has been recent interest in including lone pairs and special functions for interactions involving excited state orbitals. A particularly interesting test case is the COP(O₂)OC fragment of the nucleic acid backbone, which would seem to be the most flexible “hinge point” of polynucleotides when the classical type of calculation is carried out. In contrast, ab initio quantum mechanical calculations show the conformational space of this fragment to be much more restricted. The disagreement is such that it calls into doubt the validity of the bench-top modelling of nucleotide behaviour. In the following study, a variety of ab initio calculations are carried out to localise, in an objective manner, non-core orbitals. Coulombic interactions are introduced between these localised orbitals, with charge parameters optimised to reproduce the total ab initio potential surface. The results imply an interesting disgreement with other authors, concerning the importance of lone pair interactions in the nucleotide backbone, and the origins of this disagreement are analysed in some detail.     

A geometry optimization and molecular electrostatic potential mapping study of structure-activity relationship for some anti-Alzheimer agents.

Molecular geometries of some substituted (pyrroloamino)pyridines which possess anti-Alzheimer activity were optimized and potential-derived CHelpG point charges were computed using ab initio SCF molecular orbital approach employing the 3-21G basis set. AM1 molecular orbital calculations were performed using these optimized geometries and thus optimized Hybridization. Displacement Charges (HDC) combined with L?wdin charges continuously distributed in three dimension were obtained. Molecular electrostatic potential (MEP) maps of the molecules were obtained in two ways: (i) using the HDC-based model with the help of which MEP minima near the molecules were located, and (ii) using the CHelpG point charges, MEP values on the van der Waals surfaces of the molecules were computed. The MEP maps computed using both the methods have negative MEP regions near the pyridine nitrogen atom which appears to be the main binding site of the molecules with the appropriate receptor. Both electrostatic interaction and lipophilic association between these molecules and the receptor appear to contribute to biological activity.     

QM/MM model study on properties and structure of some antibiotics in gas phase: Comparison of energy and NMR chemical shift

The combination of Quantum Mechanics (QM) and Molecular Mechanics (MM) methods has become an alternative tool for many applications for which pure QM and MM are not suitable. The QM/MM method has been used for different types of problems, for example: structural biology, surface phenomena, and liquid phase. In this paper, we have used these methods for antibiotics and then we compared results. The calculations were done by the full ab initio method (HF/3-21G) and the (HF/STO-3G) and QM/MM (ONIOM) method with HF (3-21G)/AM1/UFF and HF (STO-3G)/AM1/UFF. We found the geometry obtained by the QM/MM method to be very accurate, and we can use this rapid method in place of time consuming ab initio methods for large molecules. Comparison of energy values in the QM/MM and QM methods is given. In the present work, we compare chemical shifts and conclude that the QM/MM method is a perturbed full QM method. The work has been done on penicillin, streptomycin, benzyl penicillin, neomycin, kanamycin, gentamicin, and amoxicillin.     

Evaluating High-Throughput Ab Initio Gene Finders to Discover Proteins Encoded in Eukaryotic Pathogen Genomes Missed by Laboratory Techniques

Next generation sequencing technology is advancing genome sequencing at an unprecedented level. By unravelling the code within a pathogen’s genome, every possible protein (prior to post-translational modifications) can theoretically be discovered, irrespective of life cycle stages and environmental stimuli. Now more than ever there is a great need for high-throughput ab initio gene finding. Ab initio gene finders use statistical models to predict genes and their exon-intron structures from the genome sequence alone. This paper evaluates whether existing ab initio gene finders can effectively predict genes to deduce proteins that have presently missed capture by laboratory techniques. An aim here is to identify possible patterns of prediction inaccuracies for gene finders as a whole irrespective of the target pathogen. All currently available ab initio gene finders are considered in the evaluation but only four fulfil high-throughput capability: AUGUSTUS, GeneMark_hmm, GlimmerHMM, and SNAP. These gene finders require training data specific to a target pathogen and consequently the evaluation results are inextricably linked to the availability and quality of the data. The pathogen, Toxoplasma gondii, is used to illustrate the evaluation methods. The results support current opinion that predicted exons by ab initio gene finders are inaccurate in the absence of experimental evidence. However, the results reveal some patterns of inaccuracy that are common to all gene finders and these inaccuracies may provide a focus area for future gene finder developers.     

New potential model for molecular dynamic simulation of liquid HF. I—Parameter optimization for charge equilibration method

In order to build a complete potential model to perform classical molecular dynamic simulations of liquid HF, a new optimization method is proposed to obtain transferable parameters for charge equilibration method on the basis of ab initio reference data. The optimized parameters (the electronegativity χ and the Slater orbital exponent ζ for H and F atoms) appear to be able to reproduce the variations of the electrostatic potential calculated from an ab initio method in a liquid phase of HF molecules for different thermodynamic conditions. It is concluded that the proposed method is general, precise and efficient to obtain transferable and realistic parameters.     

An ab Initio Structural Model of a Nucleoside Permease Predicts Functionally Important Residues

Permeases belonging to the equilibrative nucleoside transporter family promote uptake of nucleosides and/or nucleobases into a wide range of eukaryotes and mediate the uptake of a variety of drugs used in the treatment of cancer, heart disease, AIDS, and parasitic infections. No experimental three-dimensional structure exists for any of these permeases, and they are not present in prokaryotes, the source of many membrane proteins used in crystal structure determination. To generate a structural model for such a transporter, the LdNT1.1 nucleoside permease from the parasitic protozoan Leishmania donovani was modeled using ab initio computation. Site-directed mutations that strongly impair transport or that alter substrate specificity map to the central pore of the ab initio model, whereas mutations that have less pronounced phenotypes map to peripheral positions. The model suggests that aromatic residues present in transmembrane helices 1, 2, and 7 may interact to form an extracellular gate that closes the permeation pathway in the inward oriented conformation. Mutation of two of these three residues abrogated transport activity, consistent with the prediction of the model. The ab initio model is similar to one derived previously using threading analysis, a distinct computational approach, supporting the overall accuracy of both models. However, significant differences in helix orientation and residue position between the two models are apparent, and the mutagenesis data suggest that the ab initio model represents an improvement regarding structural details over the threading model. The putative gating interaction may also help explain differences in substrate specificity between members of this family.Nucleoside transporters play pivotal roles in nucleoside salvage pathways, regulation of adenosine signaling, and the pharmacology of antineoplastic and antiviral nucleoside drugs (1, 2). Salvage of nucleosides and nucleobases is the first step of nucleoside utilization in those cells that lack the metabolic machinery to make purine nucleotides de novo, including protozoan parasites (3) and brain and bone marrow cells in mammals (4). Nucleoside permeases also mediate the uptake of a number of nucleoside analog drugs used to combat the devastating effects of chronic diseases, including those caused by RNA viruses, cancer, and parasitic protozoan infections (5, 6).Equilibrative nucleoside transporters (ENTs)⁴ are a unique family of proteins (the SLC29 family), with no apparent sequence homology to other types of permeases, that enable facilitated diffusion of nucleosides, nucleoside analogs, and nucleobases across cell membranes. Although widely distributed among eukaryotes from protozoa to humans, ENT-like homologs have not been identified in prokaryotes, and therefore crystallization of these transporters is likely to be even more challenging than for those membrane proteins that do have orthologs in prokaryotes. In the absence of a crystallographic structure, the use of genetic and biochemical approaches, especially site-directed mutagenesis, has begun to reveal a significant number of elements involved in ENT function (7–23). Previous studies on the LdNT1.1 adenosine and pyrimidine nucleoside permease from the parasitic protozoan Leishmania donovani, an organism that cannot synthesize purines de novo and relies upon purine uptake for survival, have led to valuable insights into the structure and function of this family of permeases (9, 13, 22). Nevertheless, structural coverage is still sparse, and the functional determinants within the ENTs that control substrate translocation and specificity remain largely unknown.Emerging computational methods to overcome the paucity of high resolution structural data include the development of models based upon ab initio techniques (24–26) and fold recognition or “threading” (27). Ab initio techniques utilize the physical properties of the primary amino acid sequence to predict structures, whereas threading methods search for an optimal fit of the query sequence onto known three-dimensional structures of other proteins. A preliminary three-dimensional topology for the LdNT2 inosine/guanosine/xanthosine transporter from L. donovani was generated using threading analysis upon the template of the structurally resolved glycerol-3-phosphate transporter of E. coli (12), and a similar threading analysis revealed structural similarities between the TbNT1 nucleobase transporter of Trypanosoma brucei and the lactose permease of E. coli (28). In the current study, we have used a distinct computational approach based upon ab initio algorithms (24) in conjunction with site-directed mutagenesis to arrive at a structural model for LdNT1.1. An encouraging outcome is that both the ab initio and threading approaches resulted in two structural models that share the same overall topology. However, the ab initio model provided structural and functional details not previously observed in the threading model. Indeed, experiments based upon the ab initio model led to the identification of eight new residues that moderately affected LdNT1.1 activity and six novel residues whose mutation abrogated transport function. Most notably, the ab initio model revealed two aromatic amino acids (Phe⁴⁸ in TM1 and Trp⁷⁵ in TM2) that may form an interaction motif located in the pore and be involved in holding the transporter in the inward-open conformation. Mutagenesis of these residues confirmed that they are essential for transport. Therefore, the ab initio model of LdNT1.1 offers a framework for predicting intramolecular interactions central to the function of this and related nucleoside permeases.     

A replica exchange Monte Carlo algorithm for protein folding in the HP model

Background  

The ab initio protein folding problem consists of predicting protein tertiary structure from a given amino acid sequence by minimizing an energy function; it is one of the most important and challenging problems in biochemistry, molecular biology and biophysics. The ab initio protein folding problem is computationally challenging and has been shown to be -hard even when conformations are restricted to a lattice. In this work, we implement and evaluate the replica exchange Monte Carlo (REMC) method, which has already been applied very successfully to more complex protein models and other optimization problems with complex energy landscapes, in combination with the highly effective pull move neighbourhood in two widely studied Hydrophobic Polar (HP) lattice models.     

CPORT: a consensus interface predictor and its performance in prediction-driven docking with HADDOCK

Background

Macromolecular complexes are the molecular machines of the cell. Knowledge at the atomic level is essential to understand and influence their function. However, their number is huge and a significant fraction is extremely difficult to study using classical structural methods such as NMR and X-ray crystallography. Therefore, the importance of large-scale computational approaches in structural biology is evident. This study combines two of these computational approaches, interface prediction and docking, to obtain atomic-level structures of protein-protein complexes, starting from their unbound components.

Methodology/Principal Findings

Here we combine six interface prediction web servers into a consensus method called CPORT (Consensus Prediction Of interface Residues in Transient complexes). We show that CPORT gives more stable and reliable predictions than each of the individual predictors on its own. A protocol was developed to integrate CPORT predictions into our data-driven docking program HADDOCK. For cases where experimental information is limited, this prediction-driven docking protocol presents an alternative to ab initio docking, the docking of complexes without the use of any information. Prediction-driven docking was performed on a large and diverse set of protein-protein complexes in a blind manner. Our results indicate that the performance of the HADDOCK-CPORT combination is competitive with ZDOCK-ZRANK, a state-of-the-art ab initio docking/scoring combination. Finally, the original interface predictions could be further improved by interface post-prediction (contact analysis of the docking solutions).

Conclusions/Significance

The current study shows that blind, prediction-driven docking using CPORT and HADDOCK is competitive with ab initio docking methods. This is encouraging since prediction-driven docking represents the absolute bottom line for data-driven docking: any additional biological knowledge will greatly improve the results obtained by prediction-driven docking alone. Finally, the fact that original interface predictions could be further improved by interface post-prediction suggests that prediction-driven docking has not yet been pushed to the limit. A web server for CPORT is freely available at http://haddock.chem.uu.nl/services/CPORT.     

Investigation of metal ions induced conformational changes in N-acetyl alanine methyl ester

The conformation of N-acetyl alanine methyl ester CH₃CONHCH(CH₃)COOCH₃ is determined by CNDO/2 and ab initio calculations with minimal GLO basis sets. The binding sites of small monovalent cations to the ligand are investigated by the ab initio method. The chelate geometry involving peptide and ester carbonyl groups was found to be the most preferential conformation.     

<Emphasis Type="Italic">Ab initio</Emphasis> fragment molecular orbital studies of influenza virus hemagglutinin–sialosaccharide complexes toward chemical clarification about the virus host range determination

If we predict the host range of new or mutant influenza virus in advance, we are able to measure against pandemic human influenza immediately after the new virus emerges somewhere. Influenza viral hemagglutinin(HA)–sialoside receptor interaction is a target event for in silico chemical prediction studies about the virus host range determination. We theoretically studied avian and human influenza A virus HA H3 subtype complexed with avian or human type receptor Neu5Acα(2-3 or 2-6)Gal analogues by ab initio fragment molecular orbital (FMO) method at the second order Møller–Plesset (MP2)/6–31G level, which can evaluate correctly not only electrostatic interactions but also lipophilic interactions based on van der Waals dispersion force. Avian H3 bound to avian α2-3 11.4 kcal/mol stronger than to human α2-6 in the model complexes with taking account of intermolecular lipophilic interaction. A substitution at the position 226 between Gln(avian) and Leu(human) on influenza H3 HA1 has altered its virus host range between avian and human. In the ab initio FMO studies, binding energy of avian Gln226Leu H3–human α2-6 was quite similar to that in the human H3–human α2-6 complex with amino acid sequence differences at nine positions in the models. This similarity indicates that avian Gln226Leu H3 virus can infect human with the same level as human H3 virus. Opposite mutation Leu226Gln in the human H3 gave the moderate binding energies to avian α2-3 with similarity to avian H3–α2-3 complex that supported our previous virus-sialoside binding assay. Ab initio FMO studies have revealed the relationship between influenza H3 virus host range and H3–α(2-3 or 2-6) receptors binding. Our theoretical approach may predict the infectious level of new viruses and point out some unknown dangerous mutation positions on HA in advance.     

Introducing a novel method based on the imperialistic competitive algorithm to determine fluorine intermolecular potential from ab initio calculations and calculation of some properties via MD simulations

In this work, the possibility of obtaining an accurate site-site potential model suitable for use in molecular dynamics (MD) simulations of fluorine from ab initio calculations has been explored. The exploration was made on ab initio calculations. To reduce the ab initio pair potentials into a site-site potential, a higher significance was assigned to the configuration which is more stable. For this purpose, the imperialistic competitive algorithm (ICA) was implemented as a powerful optimisation tool. The calculated second virial coefficients were compared to the experimental values to test the quality of the presented intermolecular potential. The relative error for the calculated second virial coefficient ranged from 0.1 to 5.6%. MD simulations were used to evaluate the ability of the proposed intermolecular potential function. The relative error for the MD simulations ranged from 0.5 to 5.2%. The results are in good agreement with experimental data.     

Conformational behaviour of the architectural units of peptides and proteins. Assessment of current understanding by ab initio quantum mechanical methods and refinement of the dipeptide energy surface.

The conformational energy surfaces of analogues of the dipeptide unit of polypeptides and proteins are calculated by ab initio methods using extended basis sets.The calculations are not particularly sensitive to the choice of (extended) basis set.The calculations are shown to support a particular empirical method parameterized with respect to crystal data. Non-hydrogen bonded conformations agree to within 3 kcal mol^?1, even for conformations in which quite considerable degrees of atomic overlap occur.Hydrogen bonded conformations, are, however, in less satisfactory agreement and it is the ab initio calculations which appear to be at fault.A simple correction is applied to the ab initio energy for hydrogen bonded conformations, and with the use of the empirical energy surface a full quantum mechanical conformational energy map is interpolated for the alanyl dipeptide.The effect of flexibility in the peptide backbone is taken into account, and supports recent empirical findings that distortions in valence angles must be considered in calculations of the conformational behaviour of peptides.