Summary: From conformational studies to atomistic descriptions of enzymatic reactions, potential and free energy landscapes can be used to describe biomolecular systems in detail. However, extracting the relevant data of complex 3D energy surfaces can sometimes be laborious. In this article, we present MEPSA (Minimum Energy Path Surface Analysis), a cross-platform user friendly tool for the analysis of energy landscapes from a transition state theory perspective. Some of its most relevant features are: identification of all the barriers and minima of the landscape at once, description of maxima edge profiles, detection of the lowest energy path connecting two minima and generation of transition state theory diagrams along these paths. In addition to a built-in plotting system, MEPSA can save most of the generated data into easily parseable text files, allowing more versatile uses of MEPSA’s output such as the generation of molecular dynamics restraints from a calculated path. Availability and implementation: MEPSA is freely available (under GPLv3 license) at: http://bioweb.cbm.uam.es/software/MEPSA/ Contact: pagomez@cbm.csic.es Supplementary information: Supplementary data are available at Bioinformatics online.

Characteristic or classic phenotype of Cornelia de Lange syndrome (CdLS) is associated with a recognisable facial pattern. However, the heterogeneity in causal genes and the presence of overlapping syndromes have made it increasingly difficult to diagnose only by clinical features. DeepGestalt technology, and its app Face2Gene, is having a growing impact on the diagnosis and management of genetic diseases by analysing the features of affected individuals. Here, we performed a phenotypic study on a cohort of 49 individuals harbouring causative variants in known CdLS genes in order to evaluate Face2Gene utility and sensitivity in the clinical diagnosis of CdLS. Based on the profile images of patients, a diagnosis of CdLS was within the top five predicted syndromes for 97.9% of our cases and even listed as first prediction for 83.7%. The age of patients did not seem to affect the prediction accuracy, whereas our results indicate a correlation between the clinical score and affected genes. Furthermore, each gene presents a different pattern recognition that may be used to develop new neural networks with the goal of separating different genetic subtypes in CdLS. Overall, we conclude that computer-assisted image analysis based on deep learning could support the clinical diagnosis of CdLS.

Inosine-5′-monophosphate dehydrogenase (IMPDH) is an essential enzyme for nucleotide metabolism and cell proliferation. Despite IMPDH is the target of drugs with antiviral, immunosuppressive and antitumor activities, its physiological mechanisms of regulation remain largely unknown. Using the enzyme from the industrial fungus Ashbya gossypii, we demonstrate that the binding of adenine and guanine nucleotides to the canonical nucleotide binding sites of the regulatory Bateman domain induces different enzyme conformations with significantly distinct catalytic activities. Thereby, the comparison of their high-resolution structures defines the mechanistic and structural details of a nucleotide-controlled conformational switch that allosterically modulates the catalytic activity of eukaryotic IMPDHs. Remarkably, retinopathy-associated mutations lie within the mechanical hinges of the conformational change, highlighting its physiological relevance. Our results expand the mechanistic repertoire of Bateman domains and pave the road to new approaches targeting IMPDHs.

RAD21encodes a key component of the cohesin complex, and variants inRAD21have been associated with Cornelia de Lange Syndrome (CdLS). Limited information on phenotypes attributable toRAD21variants and genotype–phenotype relationships is currently published. We gathered a series of 49 individuals from 33 families withRAD21alterations [24 different intragenic sequence variants (2 recurrent), 7 unique microdeletions], including 24 hitherto unpublished cases. We evaluated consequences of 12 intragenic variants by protein modelling and molecular dynamic studies. Full clinical information was available for 29 individuals. Their phenotype is an attenuated CdLS phenotype compared to that caused by variants inNIPBLorSMC1Afor facial morphology, limb anomalies, and especially for cognition and behavior. In the 20 individuals with limited clinical information, additional phenotypes include Mungan syndrome (in patients with biallelic variants) and holoprosencephaly, with or without CdLS characteristics. We describe several additional cases with phenotypes including sclerocornea, in which involvement of theRAD21variant is uncertain. Variants were frequently familial, and genotype–phenotype analyses demonstrated striking interfamilial and intrafamilial variability. Careful phenotyping is essential in interpreting consequences ofRAD21variants, and protein modeling and dynamics can be helpful in determining pathogenicity. The current study should be helpful when counseling families with aRAD21variation.

Summary: n-dimensional energy surfaces are becoming computationally accessible, yet interpreting their information is not straightforward. We present minimum energy path surface analysis over n-dimensional surfaces (MEPSAnd), an open source GUI-based program that natively calculates minimum energy paths across energy surfaces of any number of dimensions. Among other features, MEPSAnd can compute the path through lowest barriers and automatically provide a set of alternative paths. MEPSAnd offers distinct plotting solutions as well as direct python scripting.Availability and implementation: MEPSAnd is freely available (under GPLv3 license) at: http://bioweb.cbm.uam.es/software/MEPSAnd/.Supplementary information: Supplementary data are available at Bioinformatics online.