Biology subjects

Kondrashov, F. A.

Publications and source records attributed to Kondrashov, F. A..

8 recordsLinked to original sources

bioRxiv2026

Beyond additivity: zero-shot methods cannot predict impact of epistasis on protein properties and function

Accurate prediction of properties and function of mutated proteins is crucial for both research and industrial applications. Experimental assessment of mutations relies on biochemical techniques, which, while accurate, are costly and labour-intensive. As an alternative, computational methods have emerged as a scalable and cost-effective solution. A key challenge for predicting functional consequences of mutations is epistasis, a phenomenon where the effect of one mutation is influenced by others. We evaluated the ability of 95 zero-shot models to predict the impact of epistasis on proteins using datasets from ProteinGym. Our results demonstrate that while the current models perform well for single mutations and non-epistatic combinations of mutations, they fail to predict the effect of strongly epistatic combinations of mutations. This exposes deficiencies of the state-of-the-art models and the need for focusing on capturing complex mutational interactions, which is essential for advancing both evolutionary studies and protein design.

bioinformatics↗

bioRxiv2022

Extended family with germline pathogenic variant in polymerase delta provides strong evidence for recessive effect of proofreading inactivation

Mutational processes in germline and in somatic cells are vastly different, and it remains unclear how the same genetic background affects somatic and transmissible mutations. Here, we estimate the impact of an inherited pathogenic variant in the exonuclease domain of polymerase delta (Pol{delta}) on somatic and germline mutational processes and cancer development. In germline cells and in non-cancer somatic cells, the POLD1 L474P variant increases the mutation burden only slightly, contributing [~]11.8% and [~]14.7% of mutations respectively, although it strongly distorts the mutational spectra. By contrast, tumors developed by carriers of inherited pathogenic variants in POLD1 harbor a DNA rearrangement that results in a homozygous state of the pathogenic variant, leading to an extremely high mutation rate. Thus, mutations in both alleles of POLD1 gene are required for strong increase in mutation rate suggesting recessiveness of Pold{delta} proofreading. These results show a similar role of Pol{delta} in germline and somatic replication, and, together with previous findings, illustrate the important differences between Pol{delta} and Pol{varepsilon} in the disruption of their replication fidelity.

genetics↗

bioRxiv2022

Relation between the number of peaks and the number of reciprocal sign epistatic interactions

Empirical essays of fitness landscapes suggest that they may be rugged, that is having multiple fitness peaks. Such fitness landscapes, those that have multiple peaks, necessarily have special local structures, called reciprocal sign epistasis ([14]). Here, we investigate the quantitative relationship between the number of fitness peaks and the number of reciprocal sign epistatic interactions. Previously it has been shown ([14]) that pairwise reciprocal sign epistasis is a necessary but not sufficient condition for the existence of multiple peaks. Applying discrete Morse theory, which to our knowledge has never been used in this context, we extend this result by giving the minimal number of reciprocal sign epistatic interactions required to create a given number of peaks.

evolutionary biology↗

bioRxiv2021

Using AlphaFold to predict the impact of single mutations on protein stability and function

AlphaFold changed the field of structural biology by achieving three-dimensional (3D) structure prediction from protein sequence at experimental quality. The astounding success even led to claims that the protein folding problem is "solved". However, protein folding problem is more than just structure prediction from sequence. Presently, it is unknown if the AlphaFold-triggered revolution could help to solve other problems related to protein folding. Here we assay the ability of AlphaFold to predict the impact of single mutations on protein stability ({Delta}{Delta}G) and function. To study the question we extracted metrics from AlphaFold predictions before and after single mutation in a protein and correlated the predicted change with the experimentally known {Delta}{Delta}G values. Additionally, we correlated the AlphaFold predictions on the impact of a single mutation on structure with a large scale dataset of single mutations in GFP with the experimentally assayed levels of fluorescence. We found a very weak or no correlation between AlphaFold output metrics and change of protein stability or fluorescence. Our results imply that AlphaFold cannot be immediately applied to other problems or applications in protein folding.

bioinformatics↗

bioRxiv2019

Plants with self-sustained luminescence

In contrast to fluorescent proteins, light emission from luciferase reporters requires exogenous addition of a luciferin substrate. Bacterial bioluminescence has been the single exception, where an operon of five genes is sufficient to produce light autonomously. Although commonly used in prokaryotic hosts, toxicity of the aldehyde substrate has limited its use in eukaryotes1. Here we demonstrate autonomous luminescence in a multicellular eukaryotic organism by incorporating a recently discovered fungal bioluminescent system2 into tobacco plants. We monitored these light-emitting plants from germination to flowering, observing temporal and spatial patterns of luminescence across time scales from seconds to months. The dynamic patterns of luminescence reflected progression through developmental stages, circadian oscillations, transport, and response to injuries. As with other fluorescent and luminescent reporters, we anticipate that this system will be further engineered for varied purposes, especially where exogenous addition of substrate is undesirable.

plant biology↗

bioRxiv2019

HypercubeME: two hundred million combinatorially complete datasets from a single experiment

MotivationEpistasis, the context-dependence of the contribution of an amino acid substitution to fitness, is common in evolution. To detect epistasis, fitness must be measured for at least four genotypes: the reference genotype, two different single mutants and a double mutant with both of the single mutations. For higher-order epistasis of the order n, fitness has to be measured for all 2n genotypes of an n-dimensional hypercube in genotype space forming a \"combinatorially complete dataset\". So far, only a handful of such datasets have been produced by manual curation. Concurrently, random mutagenesis experiments have produced measurements of fitness and other phenotypes in a high-throughput manner, potentially containing a number of combinatorially complete datasets.\n\nResultsWe present an effective recursive algorithm for finding all hypercube structures in random mutagenesis experimental data. To test the algorithm, we applied it to the data from a recent HIS3 protein dataset and found all 199,847,053 unique combinatorially complete genotype combinations of dimensionality ranging from two to twelve. The algorithm may be useful for researchers looking for higher-order epistasis in their high-throughput experimental data.\n\nAvailabilityhttps://github.com/ivankovlab/HypercubeME.git.

evolutionary biology↗

bioRxiv2017

Experimental assay of a fitness landscape on a macroevolutionary scale

Characterizing the fitness landscape, a representation of fitness for a large set of genotypes, is key to understanding how genetic information is interpreted to create functional organisms. Here we determined the evolutionarily-relevant segment of the fitness landscape of His3, a gene coding for an enzyme in the histidine synthesis pathway, focusing on combinations of amino acid states found at orthologous sites of extant species. Just 15% of amino acids found in yeast His3 orthologues were always neutral while the impact on fitness of the remaining 85% depended on the genetic background. Furthermore, at 67% of sites, substitutions are under sign epistasis, having both strongly positive and negative effect in different genetic backgrounds. 46% of sites were under reciprocal sign epistasis. Sign epistasis affected few genotypes but involved interaction of multiple sites, shaping a rugged fitness landscape in which many of the shortest paths between highly fit genotypes are inaccessible.

evolutionary biology↗

bioRxiv2017

Genomic analysis of human polymorphisms affecting drug-protein interactions

Human genetic variability is thought to account for a substantial fraction of individual biochemical characteristics - in biomedical sense, of individual drug response. However, only a handful of human genetic variants have been linked to medication outcomes. Here, we combine data on drug-protein interactions and human genome sequences to assess the impact of human variation on their binding affinity. Using data from the complexes of FDA-drugs and drug-like compounds, we predict SNPs substantially affecting the protein-ligand binding affinities. We estimate that an average individual carries ~6 SNPs affecting ~5 different FDA-approved drugs from among all of the approved compounds. SNPs affecting drug-protein binding affinity have low frequency in the population indicating that the genetic component for many ADEs may be highly personalized with each individual carrying a unique set of relevant SNPs. The reduction of ADEs, therefore, may primarily rely on the application of computational genome analysis in the clinic rather than the experimental study of common SNPs.

bioinformatics↗