The dominant model of musical scales in academic theories is derived from instrument tunings. However, the study of vocal scales - most especially in indigenous cultures - has been all but ignored. The voice is almost certainly the original musical instrument, and so an analysis of vocal scales provides a more naturalistic means of understanding the evolution of music. In particular, we explore the idea that the structure of musical scales is a reflection of the vocal imprecision inherent in the way that people sing, regardless of culture. To investigate this issue globally, we carried out a large-scale computational analysis of 418 ethnographic field recordings of vocal songs from indigenous/traditional cultures, spanning the 10 principal musical-style regions of the world, analyzing the number of pitch-classes, the number of interval-classes, the pitch-class distribution, the scale intervals, and scale typology. The results revealed that vocal scales have reliably larger intervallic spacings between pitch-classes than do theory-based and instrumental scales in Western culture. In addition, the mean interval-size of the scales was significantly correlated with people's imprecision in singing pitches across the world regions. These results lend support to a physiological model in which musical scales optimize pitch spacing in order to accommodate the imprecision inherent in vocal production and thereby maintain distinguishability between pitch-classes during musical communication.

Despite recent breakthroughs in understanding how protein sequence relates to structure and function, considerably less attention has been paid to the general features of protein surfaces beyond those regions involved in binding and catalysis. This article provides a systematic survey of the universe of protein surfaces and quantifies the sizes, shapes, and curvatures of the positively/negatively charged and hydrophobic/hydrophilic surface patches as well as correlations between such patches. It then compares these statistics with the metrics characterizing nanoparticles functionalized with ligands terminated with positively and negatively charged ligands. These particles are of particular interest because they are also surface patchy and have been shown to exhibit both antibiotic and anticancer activities—via selective interactions against various cellular structures—prompting loose analogies to proteins. The analyses support such analogies in several respects (e.g., patterns of charged protrusions and hydrophobic niches similar to those observed in proteins), although there are also significant differences. Looking forward, this work provides a blueprint for the rational design of synthetic nano‐objects with further enhanced mimicry of proteins’ surface properties.

Proteins are intricate molecular machines whose complexity arises from the heterogeneity of the amino acid building blocks and their dynamic network of many-body interactions. These nanomachines gain function when put in the context of a whole organism through interaction with other inhabitants of the biological realm. And this functionality shapes their evolutionary histories through intertwined paths of selection and adaptation. Recent advances in machine learning have solved the decades-old problem of how protein sequence determines their structure. However, the ultimate question regarding the basic logic of protein machines remains open: How does the collective physics of proteins lead to their functionality? and how does a sequence encode the full range of dynamics and chemical interactions that facilitate function? Here, we explore these questions within a physical approach that treats proteins as mechano-chemical machines, which are adapted to function via concerted evolution of structure, motion, and chemical interactions.

Both music and language are found in all known human societies, yet no studies have compared similarities and differences between song, speech, and instrumental music on a global scale. In this Registered Report, we analyzed two global datasets: (i) 300 annotated audio recordings representing matched sets of traditional songs, recited lyrics, conversational speech, and instrumental melodies from our 75 coauthors speaking 55 languages; and (ii) 418 previously published adult-directed song and speech recordings from 209 individuals speaking 16 languages. Of our six preregistered predictions, five were strongly supported: Relative to speech, songs use (i) higher pitch, (ii) slower temporal rate, and (iii) more stable pitches, while both songs and speech used similar (iv) pitch interval size and (v) timbral brightness. Exploratory analyses suggest that features vary along a “musi-linguistic” continuum when including instrumental melodies and recited lyrics. Our study provides strong empirical evidence of cross-cultural regularities in music and speech.

The VocalNotes project investigated how expert traditional music listeners conceive of notes in vocal performances by studying similarities and differences in their transcriptions. Teams of experts from five musical traditions (Japanese folk song, Chinese bangzi opera, Russian traditional village singing, Alpine yodelling, and Romaniote Jewish chanting) each transcribed ~10 minutes of vocal recordings from their culture, where manual transcription consisted of segmentation and note pitch correction, starting from an automatically extracted pitch curve. The experts then compared their independent transcriptions and looked for factors which could have led to disagreements. Western staff notation is not suitable for investigating such variances, because it does not represent sufficiently fine gradations of pitch and timing. We therefore used tools that allowed more precise annotations, namely Tony for segmentation, and Sonic Visualiser for note pitch correction and transcription comparison. We found that overall agreement was prevalent and the concept of note was generally applicable for analysis of vocal performances. Yet in some contexts disagreements were abundant, with the note concept reaching its limits. We identified four primary contexts which led to disagreements across several musical cultures: 1) differences in cultural knowledge between the transcribers, 2) differences in interpreting syllabic boundaries, 3) intra-syllabic pitch changes, and 4) “voice splash” - abrupt pitch changes caused by vocal techniques or used as an expressive device. The VocalNotes dataset, containing the audio of the musical fragments, annotations, and song documentation, has been published for replicability and further research.

The number of possible melodies is unfathomably large, yet despite this virtually unlimited potential for melodic variation, melodies from different societies can be surprisingly similar. The motor constraint hypothesis accounts for certain similarities, such as scalar motion and contour shape, but not for other major common features, such as repetition, song length, and scale size. Here we investigate the role of information constraints in shaping these hallmarks of melodies. We measure determinants of information rate in 62 corpora of Folk melodies spanning several continents, finding multiple trade-offs that all act to constrain the information rate across societies. By contrast, 39 corpora of Art music from Europe (including Turkey) show longer, more complex melodies, and increased complexity over time, suggesting different cultural-evolutionary selection pressures in Art and Folk music, possibly due to the use of written versus oral transmission. Our parameter-free model predicts the empirical scale degree distribution using information constraints on scalar motion, melody length, and, most importantly, information rate. These results provide strong evidence that information constraints during cultural transmission of music limit the number of notes in a scale, and suggests that a tendency for intermediate melodic complexity reflects a fundamental constraint on the cultural evolution of melody.

AI algorithms have proven to be excellent predictors of protein structure, but whether and how much these algorithms can capture the underlying physics remains an open question. Here, we aim to test this question using the Alphafold2 (AF) algorithm: We use AF to predict the subtle structural deformation induced by single mutations, quantified by strain, and compare with experimental datasets of corresponding perturbations in folding free energy ΔΔG. Unexpectedly, we find that physical strain alone – without any additional data or computation – correlates almost as well with ΔΔGas state-of-the-art energy-based and machine-learning predictors. This indicates that the AF-predicted structures alone encode fine details about the energy landscape. In particular, the structures encode significant information on stability, enough to estimate (de-)stabilizing effects of mutations, thus paving the way for the development of novel, structure-based stability predictors for protein design and evolution.

Since antiquity, musical scales have been explained by harmony rather than melody. This view relies on the mathematically designed scales of a few traditions, and was never directly tested. Testing it requires cross-cultural data and a method that judges theories by what they get wrong as well as right. We provide both, modelling scale evolution across 1,314 scales from 96 countries. A Melody model explains the near-universal preference for step-sizes of 1-3 semitones, and matches independent data from melodies, singing, and psychoacoustics. Harmony does far less: it explains the music-theoretic scales, but in those measured from performance it adds only a weak bias towards fourths, fifths, and octaves. Harmony's importance has been overstated, likely due to the historical focus on music-theoretic rather than measured scales. Melody is the primary driver of global scale structure; harmonic constraints are less impactful and mainly reflect musicological theory over musical performance.

Scales, sets of discrete pitches that form the basis of melodies, are thought to be one of the most universal hallmarks of music. But we know relatively little about cross-cultural diversity of scales or how they evolved. To remedy this, we assemble a cross-cultural database (Database of Musical Scales: DaMuSc) of scale data, collected over the past century by various ethnomusicologists. Statistical analyses of the data highlight that certain intervals (e.g., the octave, fifth, second) are used frequently across cultures. Despite some diversity among scales, it is the similarities across societies which are most striking: step intervals are restricted to 100-400 cents; most scales are found close to equidistant 5- and 7-note scales. We discuss potential mechanisms of variation and selection in the evolution of scales, and how the assembled data may be used to examine the root causes of convergent evolution.

AlphaFold2 (AF) is a promising tool, but is it accurate enough to predict single mutation effects? Here, we report that the localized structural deformation between protein pairs differing by only 1-3 mutations – as measured by the effective strain – is correlated across 3,901 experimental and AF-predicted structures. Furthermore, analysis of ∼11,000 proteins shows that the local structural change correlates with various phenotypic changes. These findings suggest that AF can predict the range and magnitude of single-mutation effects on average, and we propose a method to improve precision of AF predictions and to indicate when predictions are unreliable.

Standardized cross-cultural databases of the arts are critical to a balanced scientific understanding of the performing arts, and their role in other domains of human society. This paper introduces the Global Jukebox as a resource for comparative and cross-cultural study of the performing arts and culture. The Global Jukebox adds an extensive and detailed global database of the performing arts that enlarges our understanding of human cultural diversity. Initially prototyped by Alan Lomax in the 1980s, its core is the Cantometrics dataset, encompassing standardized codings on 37 aspects of musical style for 5,776 traditional songs from 1,026 societies. The Cantometrics dataset has been cleaned and checked for reliability and accuracy, and includes a full coding guide with audio training examples (https://theglobaljukebox.org/?songsofearth). Also being released are seven additional datasets coding and describing instrumentation, conversation, popular music, vowel and consonant placement, breath management, social factors, and societies. For the first time, all digitized Global Jukebox data are being made available in open-access, downloadable format (https://github.com/theglobaljukebox), linked with streaming audio recordings (theglobaljukebox.org) to the maximum extent allowed while respecting copyright and the wishes of culture-bearers. The data are cross-indexed with the Database of Peoples, Languages, and Cultures (D-PLACE) to allow researchers to test hypotheses about worldwide coevolution of aesthetic patterns and traditions. As an example, we analyze the global relationship between song style and societal complexity, showing that they are robustly related, in contrast to previous critiques claiming that these proposed relationships were an artifact of autocorrelation (though causal mechanisms remain unresolved).

Proteins need to selectively interact with specific targets among a multitude of similar molecules in the cell. But despite a firm physical understanding of binding interactions, we lack a general theory of how proteins evolve high specificity. Here, we present such a model that combines chemistry, mechanics and genetics, and explains how their interplay governs the evolution of specific protein-ligand interactions. The model shows that there are many routes to achieving molecular discrimination – by varying degrees of flexibility and shape/chemistry complementarity – but the key ingredient is precision. Harder discrimination tasks require more collective and precise coaction of structure, forces and movements. Proteins can achieve this through correlated mutations extending far from a binding site, which fine-tune the localized interaction with the ligand. Thus, the solution of more complicated tasks is enabled by increasing the protein size, and proteins become more evolvable and robust when they are larger than the bare minimum required for discrimination. The model makes testable, specific predictions about the role of flexibility and shape mismatch in discrimination, and how evolution can independently tune affinity and specificity. Thus, the proposed theory of specific binding addresses the natural question of “why are proteins so big?”. A possible answer is that molecular discrimination is often a hard task best performed by adding more layers to the protein.

Proteins are translated from the N to the C terminus, raising the basic question of how this innate directionality affects their evolution. To explore this question, we analyze 16,200 structures from the Protein Data Bank (PDB). We find remarkable enrichment of alpha helices at the C terminus and beta strands at the N terminus. Furthermore, this alpha - beta asymmetry correlates with sequence length and contact order, both determinants of folding rate, hinting at possible links to co-translational folding (CTF). Hence, we propose the "slowest-first'' scheme, whereby protein sequences evolved structural asymmetry to accelerate CTF: the slowest of the cooperatively folding segments are positioned near the N terminus so they have more time to fold during translation. A phenomenological model predicts that CTF can be accelerated by asymmetry in folding rate, up to double the rate, when folding time is commensurate with translation time; analysis of the PDB predicts that structural asymmetry is indeed maximal in this regime. This correspondence is greater in prokaryotes, which generally require faster protein production. Altogether, this indicates that accelerating CTF is a substantial evolutionary force whose interplay with stability and functionality is encoded in secondary structure asymmetry.

Cross-cultural musical analysis requires standardized symbolic representation of sounds such as score notation. However, transcription into notation is usually conducted manually by ear, which is time-consuming and subjective. Our aim is to evaluate the reliability of existing methods for transcribing songs from diverse societies. We had 3 experts independently transcribe a sample of 32 excerpts of traditional monophonic songs from around the world (half a cappella, half with instrumental accompaniment). 16 songs also had pre-existing transcriptions created by 3 different experts. We compared these human transcriptions against one another and against 10 automatic music transcription algorithms. We found that human transcriptions can be sufficiently reliable (~90% agreement, κ ~.7), but current automated methods are not (<60% agreement, κ <.4). No automated method clearly outperformed others, in contrast to our predictions. These results suggest that improving automated methods for cross-cultural music transcription is critical for diversifying MIR.

Scientists studying music and evolution often discuss similarities and differences between music, language, and bird song, but few studies have simultaneously compared these three domains quantitatively. One of the striking features often considered to distinguish music from speech is pitch discreteness. Here we devised two approaches for quanti- fying pitch discreteness and measured its correlation to human ratings. We utilized a small subset of 9 recordings of human music, human speech, and bird song selected to maximize variation within and between these three domains. Our quantitative analyses confirmed that both methods achieved substantial correlations with subjective ratings of pitch discreteness (r = -0.6). However, both methods suggest that human judgment of pitch discreteness does not necessarily correlate to the “flatness” of fundamental frequency (F0) contours potentially due to some non-linear or cognitive factors involved in pitch perception. Our study suggests that it could be useful to distinguish between acoustic and perceptual pitch discreteness, analogous to the distinction between acoustic F0 and perceived pitch. We also identify areas in need of future development such as automated note segmentation.

Proteins are translated from the N- to the C-terminal, raising the basic question of how this innate directionality affects their evolution. To explore this question, we analyze 16,200 structures from the protein data bank (PDB). We find remarkable enrichment ofα-helices at the C terminal andβ-sheets at the N terminal. Furthermore, thisα-βasymmetry correlates with sequence length and contact order, both determinants of folding rate, hinting at possible links to co-translational folding (CTF). Hence, we propose the ‘slowest-first’ scheme, whereby protein sequences evolved structural asymmetry to accelerate CTF: the slowest-folding elements (e.g. β-sheets) are positioned near the N terminal so they have more time to fold during translation. Our model predicts that CTF can be accelerated, up to double the rate, when folding time is commensurate with translation time; analysis of the PDB reveals that structural asymmetry is indeed maximal in this regime. This correspondence is greater in prokaryotes, which generally require faster protein production. Altogether, this indicates that accelerating CTF is a substantial evolutionary force whose interplay with stability and functionality is encoded in sequence asymmetry.

Musical scales are used in cultures throughout the world, but the question as to how they evolved remains open. Some suggest that scales based on the harmonic series are inherently pleasant, while others propose that scales are chosen that are easy to sing, hear and reproduce accurately. However, testing these theories has been hindered by the sparseness of empirical evidence. Here, to enable such examination, we assimilate data from diverse ethnomusicological sources into a cross-cultural database of scales. We generate populations of scales based on proposed and alternative theories and assess their similarity to empirical distributions from the database. Most scales can be explained as tending to include intervals roughly corresponding to perfect fifths (imperfect fifths), and packing arguments explain the salient features of the distributions. Scales are also preferred if their intervals are compressible, which could facilitate efficient communication and memory of melodies. While no single theory can explain all scales, which appear to evolve according to different selection pressures, the simplest harmonicity-based, imperfect-fifths packing model best fits the empirical data.

Musical scales are used throughout the world, but the question of how they evolved remains open. Some suggest that scales based on the harmonic series are inherently pleasant, while others propose that scales are chosen that are easy to communicate.However, testing these theories has been hindered by the sparseness of empirical evidence. Here, we assimilate data from diverse ethnomusicological sources into a cross-cultural database of scales. We generate populations of scales based on multiple theories and assess their similarity to empirical distributions from the database. Most scales tend to include intervals which are close in size to perfect fifths (“imperfect fifths”), and packing arguments explain the salient features of the distributions. Scales are also preferred if their intervals are compressible, which may facilitate efficient communication and memory of melodies. While scales appear to evolve according to various selection pressures, the simplest, imperfect-fifths packing model best fits the empirical data.

We present a computer simulation study of the phase behavior of colloidal hard cubic frames, i.e., particles with nonconvex cubic wireframe geometry interacting purely by excluded volume. Despite the propensity of cubic wireframe particles to form cubic phases akin to their convex counterparts, these particles exhibit unusual plastic fluctuations in which a random and dynamic fraction of particles rotate around their lattice positions in the crystal lattice while the remainder of the particles remains fully ordered. We argue that this unexpected effect stems from the nonconvex geometry of the particles in which the faces of a particle can be penetrated by the vertices of the nearest neighbors even at high number densities.