Basis for substrate recognition and distinction by matrix metalloproteinases.

Genomic sequencing and structural genomics produced a vast amount of sequence and structural data, creating an opportunity for structure-function analysis in silico [Radivojac P, et al. (2013) Nat Methods 10(3):221-227]. Unfortunately, only a few large experimental datasets exist to serve as benchmarks for function-related predictions. Furthermore, currently there are no reliable means to predict the extent of functional similarity among proteins. Here, we quantify structure-function relationships among three phylogenetic branches of the matrix metalloproteinase (MMP) family by comparing their cleavage efficiencies toward an extended set of phage peptide substrates that were selected from ∼ 64 million peptide sequences (i.e., a large unbiased representation of substrate space). The observed second-order rate constants [k(obs)] across the substrate space provide a distance measure of functional similarity among the MMPs. These functional distances directly correlate with MMP phylogenetic distance. There is also a remarkable and near-perfect correlation between the MMP substrate preference and sequence identity of 50-57 discontinuous residues surrounding the catalytic groove. We conclude that these residues represent the specificity-determining positions (SDPs) that allowed for the expansion of MMP proteolytic function during evolution. A transmutation of only a few selected SDPs proximal to the bound substrate peptide, and contributing the most to selectivity among the MMPs, is sufficient to enact a global change in the substrate preference of one MMP to that of another, indicating the potential for the rational and focused redesign of cleavage specificity in MMPs.

Structure-guided selection of specificity determining positions in the human Kinome.

BACKGROUND: The human kinome contains many important drug targets. It is well-known that inhibitors of protein kinases bind with very different selectivity profiles. This is also the case for inhibitors of many other protein families. The increased availability of protein 3D structures has provided much information on the structural variation within a given protein family. However, the relationship between structural variations and binding specificity is complex and incompletely understood. We have developed a structural bioinformatics approach which provides an analysis of key determinants of binding selectivity as a tool to enhance the rational design of drugs with a specific selectivity profile. RESULTS: We propose a greedy algorithm that computes a subset of residue positions in a multiple sequence alignment such that structural and chemical variation in those positions helps explain known binding affinities. By providing this information, the main purpose of the algorithm is to provide experimentalists with possible insights into how the selectivity profile of certain inhibitors is achieved, which is useful for lead optimization. In addition, the algorithm can also be used to predict binding affinities for structures whose affinity for a given inhibitor is unknown. The algorithm's performance is demonstrated using an extensive dataset for the human kinome. CONCLUSION: We show that the binding affinity of 38 different kinase inhibitors can be explained with consistently high precision and accuracy using the variation of at most six residue positions in the kinome binding site. We show for several inhibitors that we are able to identify residues that are known to be functionally important.

Molecular determinants of the ATP hydrolysis asymmetry of the CCT chaperonin complex.

The eukaryotic cytosolic chaperonin CCT is a molecular machine involved in assisting the folding of proteins involved in important cellular processes. Like other chaperonins, CCT is formed by a double-ring structure but, unlike all of them, each ring is composed of eight different, albeit homologous subunits. This complexity has probably to do with the specificity in substrate interaction and with the mechanism of protein folding that takes place during the chaperonin functional cycle, but its detailed molecular basis remains unknown. We have analyzed the known proteomes in search of residues that are differentially conserved in the eight subunits, as predictors of functional specificity (specificity-determining positions; SDPs). We have found that most of these SDPs are located near the ATP binding site, and that they define four CCT clusters, corresponding to subunits CCT3, CCT6, CCT8 and CCT1/2/4/5/7. Our results point to a spatial organisation of the CCT subunits in two opposite areas of the ring and provide a molecular explanation for the previously described asymmetry in the hydrolysis of ATP.

Inadequacy of Evolutionary Profiles Vis-a-vis Single Sequences in Predicting Transient DNA-Binding Sites in Proteins.

Sequence-based prediction of DNA-binding residues in a protein is a widely studied problem for which machine learning methods with continuously improving predictive power have been developed. Concatenated rows within a sliding window of a Position Specific Substitution Matrix (PSSM) of the protein are currently used as the primary feature set in almost all the methods of predicting DNA-binding residues. Here we report that these evolutionary profiles are powerful, only for identifying conserved binding sites and fall short for the residue positions which undergo binding to non-binding transitions in closely related proteins. We created a database of highly similar protein pairs with known protein-DNA complexes and investigated differential predictability of conserved and transient binding residues within each pair. Retraining machine learning models uniformly, we compared the predictive powers of the models trained on PSSMs against similarly trained models on sparse-encoded single sequences. We found that the transient binding site predictions from evolutionary profiles are outperformed by single-sequence based models under controlled experiments by as much as 8 percentage points. Thus, we conclude that the PSSM-based models are inadequate to predict high-specificity DNA-binding residues. These findings are of critical significance for the design of mutant- and species-specific DNA ligands and for homology based modeling of protein-DNA complexes.

Bioinformatic analysis of subfamily-specific regions in 3D-structures of homologs to study functional diversity and conformational plasticity in protein superfamilies.

Local 3D-structural differences in homologous proteins contribute to functional diversity observed in a superfamily, but so far received little attention as bioinformatic analysis was usually carried out at the level of amino acid sequences. We have developed Zebra3D - the first-of-its-kind bioinformatic software for systematic analysis of 3D-alignments of protein families using machine learning. The new tool identifies subfamily-specific regions (SSRs) - patterns of local 3D-structure (i.e. single residues, loops, or secondary structure fragments) that are spatially equivalent within families/subfamilies, but are different among them, and thus can be associated with functional diversity and function-related conformational plasticity. Bioinformatic analysis of protein superfamilies by Zebra3D can be used to study 3D-determinants of catalytic activity and specific accommodation of ligands, help to prepare focused libraries for directed evolution or assist development of chimeric enzymes with novel properties by exchange of equivalent regions between homologs, and to characterize plasticity in binding sites. A companion Mustguseal web-server is available to automatically construct a 3D-alignment of functionally diverse proteins, thus reducing the minimal input required to operate Zebra3D to a single PDB code. The Zebra3D + Mustguseal combined approach provides the opportunity to systematically explore the value of SSRs in superfamilies and to use this information for protein design and drug discovery. The software is available open-access at https://biokinet.belozersky.msu.ru/Zebra3D.

Unraveling the molecular basis of host cell receptor usage in SARS-CoV-2 and other human pathogenic ß-CoVs.

The recent emergence of the novel SARS-CoV-2 in China and its rapid spread in the human population has led to a public health crisis worldwide. Like in SARS-CoV, horseshoe bats currently represent the most likely candidate animal source for SARS-CoV-2. Yet, the specific mechanisms of cross-species transmission and adaptation to the human host remain unknown. Here we show that the unsupervised analysis of conservation patterns across the ß-CoV spike protein family, using sequence information alone, can provide valuable insights on the molecular basis of the specificity of ß-CoVs to different host cell receptors. More precisely, our results indicate that host cell receptor usage is encoded in the amino acid sequences of different CoV spike proteins in the form of a set of specificity determining positions (SDPs). Furthermore, by integrating structural data, in silico mutagenesis and coevolution analysis we could elucidate the role of SDPs in mediating ACE2 binding across the Sarbecovirus lineage, either by engaging the receptor through direct intermolecular interactions or by affecting the local environment of the receptor binding motif. Finally, by the analysis of coevolving mutations across a paired MSA we were able to identify key intermolecular contacts occurring at the spike-ACE2 interface. These results show that effective mining of the evolutionary records held in the sequence of the spike protein family can help tracing the molecular mechanisms behind the evolution and host-receptor adaptation of circulating and future novel ß-CoVs.

Molecular mechanisms of the protein-protein interaction-regulated binding specificity of basic-region leucine zipper transcription factors.

It is well known that the DNA-binding specificity of transcription factors (TFs) is influenced by protein-protein interactions (PPIs). However, the underlying molecular mechanisms remain largely unknown. In this work, we adopted the cAMP-response element-binding protein (CREB) of the basic leucine zipper (bZIP) TF family as a model system, and a workflow of combined bioinformatics and molecular modeling analysis of protein-DNA interaction was tested. First, the multiple sequence alignment and SDPsite method were used to find potential bZIP family binding specificity determining positions (SDPs) within the protein-protein interaction region. Second, the mutation system was analyzed using molecular dynamics simulation. Molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) free energy calculations confirmed the enhancement of the binding affinity of the mutation, which was in agreement with experimental results. The root mean square fluctuation (RMSF) and hydrogen bonding changes suggested an open and close protein dimerization process after the system was mutated, which resulted in the change of the hydrogen bonding of the protein-DNA interface and a slight conformational change. We believe that this work will contribute to understanding the protein-protein interaction-regulated binding specificity of bZIP transcription factors.

Tomato Apical Leaf Curl Virus: A Novel, Monopartite Geminivirus Detected in Tomatoes in Argentina.

Plant viruses that are members of the Geminiviridae family have circular single-stranded DNA (ssDNA) genome and are responsible for major crop diseases worldwide. We have identified and characterized a novel monopartite geminivirus infecting tomato in Argentina. The full-length genome was cloned and sequenced. The genome-wide pairwise identity calculation that resulted in a maximum of 63% identity with all of other known geminiviruses indicated that it is a new geminivirus species. Biolistic infected plants presented interveinal yellowing, apical leaf curling and extreme root hypotrophy. Thus, the name proposed for this species is tomato apical leaf curl virus (ToALCV). The phylogenetic inferences suggested different evolutionary relationships for the replication-associated protein (Rep) and the coat protein (CP). Besides, the sequence similarity network (SSN) protein analyses showed that the complementary-sense gene products (RepA, Rep and C3) are similar to capulavirus while the viron-sense gene products (CP, MP and V3) are similar to topocuvirus, curtovirus and becurtovirus. Based on the data presented, ToALCV genome appears to have "modular organization" supported by its recombination origin. Analyses of the specificity-determining positions (SDPs) of the CP of geminiviruses defined nine subgroups that include geminiviruses that share the same type of insect vector. Our sequences were clustered with the sequences of topocuvirus, whose vector is the treehopper, Micrutalis malleifera. Also, a set of the highest scored amino acid residues was predicted for the CP, which could determine differences in virus transmission specificity. We predict that a treehopper could be the vector of ToALCV, but transmission assays need to be performed to confirm this. Given everything we demonstrate in this paper, ToALCV can be considered a type member of a new putative genus of the Geminiviridae family.

Identification of residues of the archaeal RNA-binding Nip7 proteins specific to environmental conditions.

The understanding of biological and molecular mechanisms providing survival of cells under extreme temperatures and pressures will help to answer fundamental questions related to the origin of life and to design of biotechnologically important enzymes with new properties. Here, we analyze amino acid sequences of the Nip7 proteins from 35 archaeal species to identify positions containing mutations specific to the hydrostatic pressure and temperature of organism's habitat. The number of such positions related to pressure change is much lower than related to temperature change. The results suggest that adaptation to temperature changes of the Nip7 protein cause more pronounced modifications in sequence and structure, than to the pressure changes. Structural analysis of residues at these positions demonstrated their involvement in salt-bridge formation, which may reflect the importance of protein structure stabilization by salt-bridges at extreme environmental conditions.